{ "short_name": "wdi", "dataset": { "channel": "garden", "namespace": "worldbank_wdi", "short_name": "wdi", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "is_public": true, "version": "2024-05-20", "update_period_days": 365, "non_redistributable": false, "source_checksum": "fdb6daa40aabf3404a47ed02195dac6f" }, "primary_key": [ "country", "year" ], "dimensions": [ { "name": "country", "slug": "country" }, { "name": "year", "slug": "year" } ], "fields": { "country": {}, "year": {}, "ag_agr_trac_no": { "title": "Agricultural machinery, tractors", "description_from_producer": "Agricultural machinery refers to the number of wheel and crawler tractors (excluding garden tractors) in use in agriculture at the end of the calendar year specified or during the first quarter of the following year.\n\nLimitations and exceptions: The data are collected by the Food and Agriculture Organization of the United Nations (FAO) through annual questionnaires. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. The data collected from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.\n\nStatistical concept and methodology: A tractor provides the power and traction to mechanize agricultural tasks, especially tillage. Agricultural implements may be towed behind or mounted on the tractor, and the tractor may also provide a source of power if the implement is mechanized. The most common use of the term \"tractor\" is for the vehicles used on farms. The farm tractor is used for pulling or pushing agricultural machinery or trailers, for plowing, tilling, disking, harrowing, planting, and similar tasks. Planting, tending and harvesting a crop requires both a significant amount of power and a suitable range of tools and equipment. Mechanization of farming has allowed an increase to the area that can be planted and has contributed towards increased yields, mainly due to the precision with which the farming tasks can be accomplished.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ag_con_fert_pt_zs": { "title": "Fertilizer consumption (% of fertilizer production)", "description_from_producer": "Fertilizer consumption measures the quantity of plant nutrients used per unit of arable land. Fertilizer products cover nitrogenous, potash, and phosphate fertilizers (including ground rock phosphate). Traditional nutrients--animal and plant manures--are not included. For the purpose of data dissemination, FAO has adopted the concept of a calendar year (January to December). Some countries compile fertilizer data on a calendar year basis, while others are on a split-year basis.\n\nLimitations and exceptions: The FAO has revised the time series for fertilizer consumption and irrigation for 2002 onward. FAO collects fertilizer statistics for production, imports, exports, and consumption through the new FAO fertilizer resources questionnaire. In the previous release, the data were based on total consumption of fertilizers, but the data in the recent release are based on the nutrients in fertilizers. Some countries compile fertilizer data on a calendar year basis, while others compile on a crop year basis (July-June). Previous editions of this indicator, Fertilizer consumption (100 grams per hectare of arable land), reported data on a crop year basis, but this edition uses the calendar year, as adopted by the FAO. Caution should thus be used when comparing data over time.\n\nThe data are collected by the Food and Agriculture Organization of the United Nations (FAO) through annual questionnaires. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.\n\nStatistical concept and methodology: Fertilizer consumption measures the quantity of plant nutrients, and is calculated as production plus imports minus exports. Because some chemical compounds used for fertilizers have other industrial applications, the consumption data may overstate the quantity available for crops. Fertilizer consumption as a share of production shows the agriculture sector's vulnerability to import and energy price fluctuation.\n\nMost fertilizers that are commonly used in agriculture contain the three basic plant nutrients - nitrogen, phosphorus, and potassium. Some fertilizers also contain certain \"micronutrients,\" such as zinc and other metals that are necessary for plant growth. Materials that are applied to the land primarily to enhance soil characteristics (rather than as plant food) are commonly referred to as soil amendments. Fertilizers and soil amendments are largely derived from raw material, composts and other organic matter, and wastes, such as sewage sludge and certain industrial wastes.\n\nFAO defines arable land as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow; land abandoned as a result of shifting cultivation is excluded.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of fertilizer production", "short_unit": "%" }, "ag_con_fert_zs": { "title": "Fertilizer consumption (kilograms per hectare of arable land)", "description_from_producer": "Fertilizer consumption measures the quantity of plant nutrients used per unit of arable land. Fertilizer products cover nitrogenous, potash, and phosphate fertilizers (including ground rock phosphate). Traditional nutrients--animal and plant manures--are not included. For the purpose of data dissemination, FAO has adopted the concept of a calendar year (January to December). Some countries compile fertilizer data on a calendar year basis, while others are on a split-year basis. Arable land includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded.\n\nLimitations and exceptions: The FAO has revised the time series for fertilizer consumption and irrigation for 2002 onward. FAO collects fertilizer statistics for production, imports, exports, and consumption through the new FAO fertilizer resources questionnaire. In the previous release, the data were based on total consumption of fertilizers, but the data in the recent release are based on the nutrients in fertilizers. Some countries compile fertilizer data on a calendar year basis, while others compile on a crop year basis (July-June). Previous editions of this indicator, Fertilizer consumption (100 grams per hectare of arable land), reported data on a crop year basis, but this edition uses the calendar year, as adopted by the FAO. Caution should thus be used when comparing data over time.\n\nThe data are collected by the Food and Agriculture Organization of the United Nations (FAO) through annual questionnaires. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.\n\nStatistical concept and methodology: Fertilizer consumption measures the quantity of plant nutrients, and is calculated as production plus imports minus exports. Because some chemical compounds used for fertilizers have other industrial applications, the consumption data may overstate the quantity available for crops. Fertilizer consumption as a share of production shows the agriculture sector's vulnerability to import and energy price fluctuation.\n\nMost fertilizers that are commonly used in agriculture contain the three basic plant nutrients - nitrogen, phosphorus, and potassium. Some fertilizers also contain certain \"micronutrients,\" such as zinc and other metals that are necessary for plant growth. Materials that are applied to the land primarily to enhance soil characteristics (rather than as plant food) are commonly referred to as soil amendments. Fertilizers and soil amendments are largely derived from raw material, composts and other organic matter, and wastes, such as sewage sludge and certain industrial wastes.\n\nFAO defines arable land as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow; land abandoned as a result of shifting cultivation is excluded.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kilograms per hectare of arable land", "short_unit": "kilograms" }, "ag_lnd_agri_k2": { "title": "Agricultural land (sq. km)", "description_from_producer": "Agricultural land refers to the share of land area that is arable, under permanent crops, and under permanent pastures. Arable land includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded. Land under permanent crops is land cultivated with crops that occupy the land for long periods and need not be replanted after each harvest, such as cocoa, coffee, and rubber. This category includes land under flowering shrubs, fruit trees, nut trees, and vines, but excludes land under trees grown for wood or timber. Permanent pasture is land used for five or more years for forage, including natural and cultivated crops.\n\nLimitations and exceptions: The data are collected by the Food and Agriculture Organization of the United Nations (FAO) through annual questionnaires. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries. Data on agricultural employment, in particular, should be used with caution. In many countries much agricultural employment is informal and unrecorded, including substantial work performed by women and children. To address some of these concerns, this indicator is heavily footnoted in the database in sources, definition, and coverage. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.\n\nStatistical concept and methodology: Agricultural land constitutes only a part of any country's total area, which can include areas not suitable for agriculture, such as forests, mountains, and inland water bodies. Three components of the agricultural land are a) arable land - land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow, b) permanent pasture - land used for five or more years for forage, including natural and cultivated crops, and c) and under permanent crops - land cultivated with crops that occupy the land for long periods and need not be replanted after each harvest, such as cocoa, coffee, and rubber; land under flowering shrubs, fruit trees, nut trees, and vines is included, but land under trees grown for wood or timber is not.\n\nAgricultural land is also sometimes classified as irrigated and non-irrigated land. In arid and semi-arid countries agriculture is often confined to irrigated land, with very little farming possible in non-irrigated areas. Land abandoned as a result of shifting cultivation is excluded from arable land.\n\nData on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Agricultural land indicator, along with land-use indicators, can also elucidate the environmental sustainability of countries' agricultural practices.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "sq. km", "short_unit": "sq. km" }, "ag_lnd_agri_zs": { "title": "Agricultural land (% of land area)", "description_from_producer": "Agricultural land refers to the share of land area that is arable, under permanent crops, and under permanent pastures. Arable land includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded. Land under permanent crops is land cultivated with crops that occupy the land for long periods and need not be replanted after each harvest, such as cocoa, coffee, and rubber. This category includes land under flowering shrubs, fruit trees, nut trees, and vines, but excludes land under trees grown for wood or timber. Permanent pasture is land used for five or more years for forage, including natural and cultivated crops.\n\nLimitations and exceptions: The data are collected by the Food and Agriculture Organization of the United Nations (FAO) from official national sources through annual questionnaires and are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries. Data on agricultural employment, in particular, should be used with caution. In many countries much agricultural employment is informal and unrecorded, including substantial work performed by women and children. To address some of these concerns, this indicator is heavily footnoted in the database in sources, definition, and coverage.\n\nStatistical concept and methodology: Agriculture is still a major sector in many economies, and agricultural activities provide developing countries with food and revenue. But agricultural activities also can degrade natural resources. Poor farming practices can cause soil erosion and loss of soil fertility. Efforts to increase productivity by using chemical fertilizers, pesticides, and intensive irrigation have environmental costs and health impacts. Excessive use of chemical fertilizers can alter the chemistry of soil. Pesticide poisoning is common in developing countries. And salinization of irrigated land diminishes soil fertility. Thus, inappropriate use of inputs for agricultural production has far-reaching effects.\n\nAgricultural land is also sometimes classified as irrigated and non-irrigated land. In arid and semi-arid countries agriculture is often confined to irrigated land, with very little farming possible in non-irrigated areas. Land abandoned as a result of shifting cultivation is excluded from Arable land.\n\nData on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Agricultural land indicator, along with land-use indicators, can also elucidate the environmental sustainability of countries' agricultural practices.\n\nTotal land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of land area", "short_unit": "%" }, "ag_lnd_arbl_ha": { "title": "Arable land (hectares)", "description_from_producer": "Arable land (in hectares) includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded.\n\nLimitations and exceptions: The Food and Agriculture Organization (FAO) tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries.\n\nThe data collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations. Data on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Agricultural land indicator, along with land-use indicators, can also elucidate the environmental sustainability of countries' agricultural practices.\n\nTrue comparability of the data is limited, however, by variations in definitions, statistical methods, and quality of data. Countries use different definitions land use. The Food and Agriculture Organization of the United Nations (FAO), the primary compiler of the data, occasionally adjusts its definitions of land use categories and revises earlier data. Because the data reflect changes in reporting procedures as well as actual changes in land use, apparent trends should be interpreted cautiously.\n\nSatellite images show land use that differs from that of ground-based measures in area under cultivation and type of land use. Moreover, land use data in some countries (India is an example) are based on reporting systems designed for collecting tax revenue. With land taxes no longer a major source of government revenue, the quality and coverage of land use data have declined.\n\nStatistical concept and methodology: Temporary fallow land refers to land left fallow for less than five years. The abandoned land resulting from shifting cultivation is not included in this category. Data for \"Arable land\" are not meant to indicate the amount of land that is potentially cultivable.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hectares", "short_unit": "hectares", "display": { "name": "Arable land" } }, "ag_lnd_arbl_ha_pc": { "title": "Arable land (hectares per person)", "description_from_producer": "Arable land (hectares per person) includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded.\n\nLimitations and exceptions: The Food and Agriculture Organization (FAO) tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries.\n\nTrue comparability of the data is limited, by variations in definitions, statistical methods, and quality of data. Countries use different definitions land use. The Food and Agriculture Organization of the United Nations (FAO), the primary compiler of the data, occasionally adjusts its definitions of land use categories and revises earlier data. Because the data reflect changes in reporting procedures as well as actual changes in land use, apparent trends should be interpreted cautiously.\n\nSatellite images show land use that differs from that of ground-based measures in area under cultivation and type of land use. Moreover, land use data in some countries (India is an example) are based on reporting systems designed for collecting tax revenue. With land taxes no longer a major source of government revenue, the quality and coverage of land use data have declined.\n\nStatistical concept and methodology: Temporary fallow land refers to land left fallow for less than five years. The abandoned land resulting from shifting cultivation is not included in this category. Data for \"Arable land\" are not meant to indicate the amount of land that is potentially cultivable. The data collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hectares per person", "short_unit": "hectares" }, "ag_lnd_arbl_zs": { "title": "Arable land (% of land area)", "description_from_producer": "Arable land includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded.\n\nLimitations and exceptions: The Food and Agriculture Organization (FAO) tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries.\n\nThe data collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations. Data on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Agricultural land indicator, along with land-use indicators, can also elucidate the environmental sustainability of countries' agricultural practices.\n\nTrue comparability of the data is limited, by variations in definitions, statistical methods, and quality of data. Countries use different definitions land use. The Food and Agriculture Organization of the United Nations (FAO), the primary compiler of the data, occasionally adjusts its definitions of land use categories and revises earlier data. Because the data reflect changes in reporting procedures as well as actual changes in land use, apparent trends should be interpreted cautiously.\n\nSatellite images show land use that differs from that of ground-based measures in area under cultivation and type of land use. Moreover, land use data in some countries (India is an example) are based on reporting systems designed for collecting tax revenue. With land taxes no longer a major source of government revenue, the quality and coverage of land use data have declined.\n\nStatistical concept and methodology: Temporary fallow land refers to land left fallow for less than five years. The abandoned land resulting from shifting cultivation is not included in this category. Data for \"Arable land\" are not meant to indicate the amount of land that is potentially cultivable. Total land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area. The data collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of land area", "short_unit": "%" }, "ag_lnd_crel_ha": { "title": "Land under cereal production (hectares)", "description_from_producer": "Land under cereal production refers to harvested area, although some countries report only sown or cultivated area. Cereals include wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.\n\nLimitations and exceptions: The data are collected by the Food and Agriculture Organization of the United Nations (FAO) through annual questionnaires. They are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries.\n\nData on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses.\n\nStatistical concept and methodology: Cereals production includes wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.\n\nA cereal is a grass cultivated for the edible components of their grain, composed of the endosperm, germ, and bran. Cereal grains are grown in greater quantities and provide more food energy worldwide than any other type of crop; cereal crops therefore can also be called staple crops.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hectares", "short_unit": "hectares" }, "ag_lnd_crop_zs": { "title": "Permanent cropland (% of land area)", "description_from_producer": "Permanent cropland is land cultivated with crops that occupy the land for long periods and need not be replanted after each harvest, such as cocoa, coffee, and rubber. This category includes land under flowering shrubs, fruit trees, nut trees, and vines, but excludes land under trees grown for wood or timber.\n\nLimitations and exceptions: The Food and Agriculture Organization (FAO) tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries.\n\nTrue comparability of the data is limited by variations in definitions, statistical methods, and quality of data. Countries use different definitions land use. The Food and Agriculture Organization of the United Nations (FAO), the primary compiler of the data, occasionally adjusts its definitions of land use categories and revises earlier data. Because the data reflect changes in reporting procedures as well as actual changes in land use, apparent trends should be interpreted cautiously.\n\nSatellite images show land use that differs from that of ground-based measures in area under cultivation and type of land use. Moreover, land use data in some countries (India is an example) are based on reporting systems designed for collecting tax revenue. With land taxes no longer a major source of government revenue, the quality and coverage of land use data have declined.\n\nStatistical concept and methodology: The data on Permanent cropland and land area are collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of land area", "short_unit": "%" }, "ag_lnd_el5m_ru_k2": { "title": "Rural land area where elevation is below 5 meters (sq. km)", "description_from_producer": "Rural land area below 5m is the total rural land area in square kilometers where the elevation is 5 meters or less.\n\nLimitations and exceptions: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is \u201cunequivocal\u201d and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20\u201386 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5\u00b0C by 2100 (Kattenberg and others 1996) and increase of \u201ckiller\u201d heat waves during the warm season (Karl and others 1997).\n\nStatistical concept and methodology: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA\u2019s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).", "origins": [ { "producer": "CIESIN and CIDR (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "sq. km", "short_unit": "sq. km" }, "ag_lnd_el5m_ru_zs": { "title": "Rural land area where elevation is below 5 meters (% of total land area)", "description_from_producer": "Rural land area below 5m is the percentage of total land where the rural land elevation is 5 meters or less.\n\nLimitations and exceptions: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is \u201cunequivocal\u201d and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20\u201386 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5\u00b0C by 2100 (Kattenberg and others 1996) and increase of \u201ckiller\u201d heat waves during the warm season (Karl and others 1997).\n\nStatistical concept and methodology: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA\u2019s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).", "origins": [ { "producer": "CIESIN and CIDR (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total land area", "short_unit": "%" }, "ag_lnd_el5m_ur_k2": { "title": "Urban land area where elevation is below 5 meters (sq. km)", "description_from_producer": "Urban land area below 5m is the total urban land area in square kilometers where the elevation is 5 meters or less.\n\nStatistical concept and methodology: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA\u2019s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).", "origins": [ { "producer": "CIESIN and CIDR (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "sq. km", "short_unit": "sq. km" }, "ag_lnd_el5m_ur_zs": { "title": "Urban land area where elevation is below 5 meters (% of total land area)", "description_from_producer": "Urban land area below 5m is the percentage of total land where the urban land elevation is 5 meters or less.\n\nStatistical concept and methodology: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA\u2019s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).", "origins": [ { "producer": "CIESIN and CIDR (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total land area", "short_unit": "%" }, "ag_lnd_el5m_zs": { "title": "Land area where elevation is below 5 meters (% of total land area)", "description_from_producer": "Land area below 5m is the percentage of total land where the elevation is 5 meters or less.\n\nLimitations and exceptions: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is \u201cunequivocal\u201d and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20\u201386 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5\u00b0C by 2100 (Kattenberg and others 1996) and increase of \u201ckiller\u201d heat waves during the warm season (Karl and others 1997).\n\nStatistical concept and methodology: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA\u2019s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).", "origins": [ { "producer": "CIESIN and CIDR (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total land area", "short_unit": "%" }, "ag_lnd_frst_k2": { "title": "Forest area (sq. km)", "description_from_producer": "Forest area is land under natural or planted stands of trees of at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural production systems (for example, in fruit plantations and agroforestry systems) and trees in urban parks and gardens.\n\nLimitations and exceptions: The Food and Agricultural Organization (FAO) has been collecting and analyzing data on forest area since 1946. This is done at intervals of 5-10 years as part of the Global Forest Resources Assessment (FRA). FAO reports data for 229 countries and territories; for the remaining 56 small island states and territories where no information is provided, a report is prepared by FAO using existing information and a literature search. The data are aggregated at sub-regional, regional and global levels by the FRA team at FAO, and estimates are produced by straight summation.\n\nThe lag between the reference year and the actual production of data series as well as the frequency of data production varies between countries. Deforested areas do not include areas logged but intended for regeneration or areas degraded by fuelwood gathering, acid precipitation, or forest fires. Negative numbers indicate an increase in forest area.\n\nData includes areas with bamboo and palms; forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific scientific, historical, cultural or spiritual interest; windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters; plantations primarily used for forestry or protective purposes, such as rubber-wood plantations and cork oak stands. Data excludes tree stands in agricultural production systems, such as fruit plantations and agroforestry systems. Forest area also excludes trees in urban parks and gardens. The proportion of forest area to total land area is calculated and changes in the proportion are computed to identify trends.\n\nStatistical concept and methodology: Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should reach a minimum height of 5 meters in situ. Areas under reforestation that have not yet reached but are expected to reach a canopy cover of 10 percent and a tree height of 5 meters are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, which are expected to regenerate.\n\nFAO provides detail information on forest cover, and adjusted estimates of forest cover. The current survey uses a uniform definition of forest. Although FAO provides a breakdown of forest cover between natural forest and plantation for developing countries, this indictor data does not reflect that breakdown. Thus the deforestation data may underestimate the rate at which natural forest is disappearing in some countries.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "sq. km", "short_unit": "sq. km" }, "ag_lnd_frst_zs": { "title": "Forest area (% of land area)", "description_from_producer": "Forest area is land under natural or planted stands of trees of at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural production systems (for example, in fruit plantations and agroforestry systems) and trees in urban parks and gardens.\n\nLimitations and exceptions: FAO has been collecting and analyzing data on forest area since 1946. This is done at intervals of 5-10 years as part of the Global Forest Resources Assessment (FRA). FAO reports data for 229 countries and territories; for the remaining 56 small island states and territories where no information is provided, a report is prepared by FAO using existing information and a literature search. The data are aggregated at sub-regional, regional and global levels by the FRA team at FAO, and estimates are produced by straight summation.\n\nThe lag between the reference year and the actual production of data series as well as the frequency of data production varies between countries. Deforested areas do not include areas logged but intended for regeneration or areas degraded by fuelwood gathering, acid precipitation, or forest fires. Negative numbers indicate an increase in forest area.\n\nData includes areas with bamboo and palms; forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific scientific, historical, cultural or spiritual interest; windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters; plantations primarily used for forestry or protective purposes, such as rubber-wood plantations and cork oak stands. Data excludes tree stands in agricultural production systems, such as fruit plantations and agroforestry systems. Forest area also excludes trees in urban parks and gardens. The proportion of forest area to total land area is calculated and changes in the proportion are computed to identify trends.\n\nStatistical concept and methodology: Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should reach a minimum height of 5 meters in situ. Areas under reforestation that have not yet reached but are expected to reach a canopy cover of 10 percent and a tree height of 5 meters are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, which are expected to regenerate.\n\nThe Food and Agriculture Organization (FAO) provides detail information on forest cover, and adjusted estimates of forest cover. The survey uses a uniform definition of forest. Although FAO provides a breakdown of forest cover between natural forest and plantation for developing countries, forest data used to derive this indictor data does not reflect that breakdown. Total land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area. The indictor is derived by dividing total area under forest of a country by country's total land area, and multiplying by 100.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of land area", "short_unit": "%" }, "ag_lnd_irig_ag_zs": { "title": "Agricultural irrigated land (% of total agricultural land)", "description_from_producer": "Agricultural irrigated land refers to agricultural areas purposely provided with water, including land irrigated by controlled flooding.\n\nLimitations and exceptions: The data are collected by the Food and Agriculture Organization of the United Nations (FAO) from official national sources through annual questionnaires and are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries.\n\nStatistical concept and methodology: Irrigated agricultural area refers to area equipped to provide water (via artificial means of irrigation such as by diverting streams, flooding, or spraying) to the crops. In non-irrigated agricultural areas, production of crops is dependent on rain-fed irrigation.\n\nAgricultural land constitutes only a part of any country's total area, which can include areas not suitable for agriculture, such as forests, mountains, and inland water bodies. Agricultural land can also be classified as irrigated and non-irrigated land. In arid and semi-arid countries agriculture is often confined to irrigated land, with very little farming possible in non-irrigated areas.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total agricultural land", "short_unit": "%" }, "ag_lnd_prcp_mm": { "title": "Average precipitation in depth (mm per year)", "description_from_producer": "Average precipitation is the long-term average in depth (over space and time) of annual precipitation in the country. Precipitation is defined as any kind of water that falls from clouds as a liquid or a solid.\n\nLimitations and exceptions: The data are collected by the Food and Agriculture Organization of the United Nations (FAO) through annual questionnaires. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "mm per year", "short_unit": "mm" }, "ag_lnd_totl_k2": { "title": "Land area (sq. km)", "description_from_producer": "Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.\n\nLimitations and exceptions: The data are collected by the Food and Agriculture Organization (FAO) of the United Nations through annual questionnaires. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible.\n\nThe data collected from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.\n\nStatistical concept and methodology: Total land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area. Including areas of former states; for example, the areas of the Union of Soviet Socialist Republics (USSR) are counted in Russian Federationand other successor states.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "sq. km", "short_unit": "sq. km" }, "ag_lnd_totl_ru_k2": { "title": "Rural land area (sq. km)", "description_from_producer": "Rural land area in square kilometers, derived from urban extent grids which distinguish urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights. Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons.\n\nLimitations and exceptions: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is \u201cunequivocal\u201d and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20\u201386 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5\u00b0C by 2100 (Kattenberg and others 1996) and increase of \u201ckiller\u201d heat waves during the warm season (Karl and others 1997).\n\nStatistical concept and methodology: The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) urban extent grid distinguishes urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights . Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT)", "origins": [ { "producer": "Center for International Earth Science Information Network (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "sq. km", "short_unit": "sq. km" }, "ag_lnd_totl_ur_k2": { "title": "Urban land area (sq. km)", "description_from_producer": "Urban land area in square kilometers, based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights. Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons.\n\nStatistical concept and methodology: The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) urban extent grid distinguishes urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights . Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT)", "origins": [ { "producer": "Center for International Earth Science Information Network (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "sq. km", "short_unit": "sq. km" }, "ag_lnd_trac_zs": { "title": "Agricultural machinery, tractors per 100 sq. km of arable land", "description_from_producer": "Agricultural machinery refers to the number of wheel and crawler tractors (excluding garden tractors) in use in agriculture at the end of the calendar year specified or during the first quarter of the following year. Arable land includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded.\n\nLimitations and exceptions: The data are collected by the Food and Agriculture Organization of the United Nations (FAO) through annual questionnaires. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries. Data on agricultural employment, in particular, should be used with caution. In many countries much agricultural employment is informal and unrecorded, including substantial work performed by women and children. To address some of these concerns, this indicator is heavily footnoted in the database in sources, definition, and coverage.\n\nThe data collected from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.\n\nStatistical concept and methodology: A tractor provides the power and traction to mechanize agricultural tasks, especially tillage. Agricultural implements may be towed behind or mounted on the tractor, and the tractor may also provide a source of power if the implement is mechanized. The most common use of the term \"tractor\" is for the vehicles used on farms. The farm tractor is used for pulling or pushing agricultural machinery or trailers, for plowing, tilling, disking, harrowing, planting, and similar tasks. Planting, tending and harvesting a crop requires both a significant amount of power and a suitable range of tools and equipment. Mechanization of farming has allowed an increase to the area that can be planted and has contributed towards increased yields, mainly due to the precision with which the farming tasks can be accomplished.\n\nAgricultural land constitutes only a part of any country's total area, which can include areas not suitable for agriculture, such as forests, mountains, and inland water bodies. Data on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Agricultural land indicator, along with land-use indicators, can also elucidate the environmental sustainability of countries' agricultural practices.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ag_prd_crel_mt": { "title": "Cereal production (metric tons)", "description_from_producer": "Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.\n\nLimitations and exceptions: Data on cereal production may be affected by a variety of reporting and timing differences. Millet and sorghum, which are grown as feed for livestock and poultry in Europe and North America, are used as food in Africa, Asia, and countries of the former Soviet Union. So some cereal crops are excluded from the data for some countries and included elsewhere, depending on their use.\n\nThe data are collected by the Food and Agriculture Organization (FAO) of the United Nations through annual questionnaires and are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries.\n\nThe data collected from official national sources.\n\nStatistical concept and methodology: A cereal is a grass cultivated for the edible components of their grain, composed of the endosperm, germ, and bran. Cereal grains are grown in greater quantities and provide more food energy worldwide than any other type of crop; cereal crops therefore can also be called staple crops. Cereals production data relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded. The Food and Agriculture Organization (FAO) allocates production data to the calendar year in which the bulk of the harvest took place. Most of a crop harvested near the end of a year will be used in the following year.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "metric tons" }, "ag_prd_crop_xd": { "title": "Crop production index (2014-2016 = 100)", "description_from_producer": "Crop production index shows agricultural production for each year relative to the base period 2014-2016. It includes all crops except fodder crops. Regional and income group aggregates for the FAO's production indexes are calculated from the underlying values in international dollars, normalized to the base period 2014-2016.\n\nLimitations and exceptions: The FAO indices may differ from those produced by the countries themselves because of differences in concepts of production, coverage, time periods, weights, time reference of data, methods of calculation, and use of international prices.\n\nAgricultural data are collected by the Food and Agriculture Organization of the United Nations (FAO) from official national sources through annual questionnaires and are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Data on agricultural employment, in particular, should be used with caution. In many countries much agricultural employment is informal and unrecorded, including substantial work performed by women and children. To address some of these concerns, this indicator is heavily footnoted in the database in sources, definition, and coverage.\n\nStatistical concept and methodology: The agricultural production index is prepared by the Food and Agriculture Organization of the United Nations (FAO). The FAO indices of agricultural production show the relative level of the aggregate volume of agricultural production for each year in comparison with the base period 2014-2016. They are based on the sum of price-weighted quantities of different agricultural commodities produced after deductions of quantities used as seed and feed weighted in a similar manner. The resulting aggregate represents, therefore, disposable production for any use except as seed and feed. All the indices at the country, regional and world levels are calculated by the Laspeyres formula*. Production quantities of each commodity are weighted by 2014-2016 average international commodity prices and summed for each year. To obtain the index, the aggregate for a given year is divided by the average aggregate for the base period 2014-2016. Since the FAO indices are based on the concept of agriculture as a single enterprise, amounts of seed and feed are subtracted from the production data to avoid double counting, once in the production data and once with the crops or livestock produced from them. Deductions for seed (in the case of eggs, for hatching) and for livestock and poultry feed apply to both domestically produced and imported commodities. They cover only primary agricultural products destined to animal feed (e.g. maize, potatoes, milk, etc.). Processed and semi-processed feed items such as bran, oilcakes, meals and molasses have been completely excluded from the calculations at all stages. It should be noted that when calculating indices of agricultural, food and nonfood production, all intermediate primary inputs of agricultural origin are deducted. However, for indices of any other commodity group, only inputs originating from within the same group are deducted; thus, only seed is removed from the group \"crops\" and from all crop subgroups, such as cereals, oil crops, etc.; and both feed and seed originating from within the livestock sector (e.g. milk feed, hatching eggs) are removed from the group \"livestock products\". For the main two livestock subgroups, namely, meat and milk, only feed originating from the respective subgroup is removed. Indices which take into account deductions for feed and seed are referred to as ''net''. Indices calculated without any deductions for feed and seed are referred to as ''gross\". The \"international commodity prices\" are used in order to avoid the use of exchange rates for obtaining continental and world aggregates, and also to improve and facilitate international comparative analysis of productivity at the national level. These\" international prices,\" expressed in so-called \"international dollars,\" are derived using a Geary-Khamis formula** for the agricultural sector. This method assigns a single \"price\" to each commodity. For example, one metric ton of wheat has the same price regardless of the country where it was produced. The currency unit in which the prices are expressed has no influence on the indices published. The commodities covered in the computation of indices of agricultural production are all crops and livestock products originating in each country. Practically all products are covered, with the main exception of fodder crops.\n\n* A Laspeyres Index is known as a \"base-weighted\" or \"fixed-weighted\" index because the price increases are weighted by the quantities in the base period. The Consumer Price Index is an example of a Laspeyres Index. http://www.usna.edu/Users/econ/rbrady/312%20Materials/LaspeyresCalc.pdf\n** Geary-Khamis formula is an aggregation method in which category \"international prices\" (reflecting relative category values) and country purchasing power parities (PPPs), (depicting relative country price levels) are estimated simultaneously from a system of linear equations. http://stats.oecd.org/glossary/detail.asp?ID=5528", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2014-2014 = 100" }, "ag_prd_food_xd": { "title": "Food production index (2014-2016 = 100)", "description_from_producer": "Food production index covers food crops that are considered edible and that contain nutrients. Coffee and tea are excluded because, although edible, they have no nutritive value.\n\nLimitations and exceptions: Agricultural data are collected by the Food and Agriculture Organization of the United Nations (FAO) from official national sources through the questionnaire and are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Data on agricultural employment, in particular, should be used with caution. In many countries much agricultural employment is informal and unrecorded, including substantial work performed by women and children. To address some of these concerns, this indicator is heavily footnoted in the database in sources, definition, and coverage.\n\nStatistical concept and methodology: The agricultural production index is prepared by the Food and Agriculture Organization of the United Nations (FAO). The FAO indices of agricultural production show the relative level of the aggregate volume of agricultural production for each year in comparison with the base period 2014-2016. They are based on the sum of price-weighted quantities of different agricultural commodities produced after deductions of quantities used as seed and feed weighted in a similar manner. The resulting aggregate represents, therefore, disposable production for any use except as seed and feed. All the indices at the country, regional and world levels are calculated by the Laspeyres formula*. Production quantities of each commodity are weighted by 2014-2016 average international commodity prices and summed for each year. To obtain the index, the aggregate for a given year is divided by the average aggregate for the base period 2014-2016. Since the FAO indices are based on the concept of agriculture as a single enterprise, amounts of seed and feed are subtracted from the production data to avoid double counting, once in the production data and once with the crops or livestock produced from them. Deductions for seed (in the case of eggs, for hatching) and for livestock and poultry feed apply to both domestically produced and imported commodities. They cover only primary agricultural products destined to animal feed (e.g. maize, potatoes, milk, etc.). Processed and semi-processed feed items such as bran, oilcakes, meals and molasses have been completely excluded from the calculations at all stages. It should be noted that when calculating indices of agricultural, food and nonfood production, all intermediate primary inputs of agricultural origin are deducted. However, for indices of any other commodity group, only inputs originating from within the same group are deducted; thus, only seed is removed from the group \"crops\" and from all crop subgroups, such as cereals, oil crops, etc.; and both feed and seed originating from within the livestock sector (e.g. milk feed, hatching eggs) are removed from the group \"livestock products\". For the main two livestock subgroups, namely, meat and milk, only feed originating from the respective subgroup is removed. Indices which take into account deductions for feed and seed are referred to as ''net''. Indices calculated without any deductions for feed and seed are referred to as ''gross\". The \"international commodity prices\" are used in order to avoid the use of exchange rates for obtaining continental and world aggregates, and also to improve and facilitate international comparative analysis of productivity at the national level. These\" international prices,\" expressed in so-called \"international dollars,\" are derived using a Geary-Khamis formula** for the agricultural sector. This method assigns a single \"price\" to each commodity. For example, one metric ton of wheat has the same price regardless of the country where it was produced. The currency unit in which the prices are expressed has no influence on the indices published. The commodities covered in the computation of indices of agricultural production are all crops and livestock products originating in each country. Practically all products are covered, with the main exception of fodder crops.\n\n* A Laspeyres Index is known as a \"base-weighted\" or \"fixed-weighted\" index because the price increases are weighted by the quantities in the base period. The Consumer Price Index is an example of a Laspeyres Index. http://www.usna.edu/Users/econ/rbrady/312%20Materials/LaspeyresCalc.pdf\n** Geary-Khamis formula is an aggregation method in which category \"international prices\" (reflecting relative category values) and country purchasing power parities (PPPs), (depicting relative country price levels) are estimated simultaneously from a system of linear equations. http://stats.oecd.org/glossary/detail.asp?ID=5528", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2014-2014 = 100" }, "ag_prd_lvsk_xd": { "title": "Livestock production index (2014-2016 = 100)", "description_from_producer": "Livestock production index includes meat and milk from all sources, dairy products such as cheese, and eggs, honey, raw silk, wool, and hides and skins.\n\nLimitations and exceptions: Agricultural data are collected by the Food and Agriculture Organization of the United Nations (FAO) from official national sources through the questionnaire and are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.\n\nThe FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Data on agricultural employment, in particular, should be used with caution. In many countries much agricultural employment is informal and unrecorded, including substantial work performed by women and children. To address some of these concerns, this indicator is heavily footnoted in the database in sources, definition, and coverage.\n\nStatistical concept and methodology: The agricultural production index is prepared by the Food and Agriculture Organization of the United Nations (FAO). The FAO indices of agricultural production show the relative level of the aggregate volume of agricultural production for each year in comparison with the base period 2014-2016. They are based on the sum of price-weighted quantities of different agricultural commodities produced after deductions of quantities used as seed and feed weighted in a similar manner. The resulting aggregate represents, therefore, disposable production for any use except as seed and feed. All the indices at the country, regional and world levels are calculated by the Laspeyres formula*. Production quantities of each commodity are weighted by 2014-2016 average international commodity prices and summed for each year. To obtain the index, the aggregate for a given year is divided by the average aggregate for the base period 2014-2016. Since the FAO indices are based on the concept of agriculture as a single enterprise, amounts of seed and feed are subtracted from the production data to avoid double counting, once in the production data and once with the crops or livestock produced from them. Deductions for seed (in the case of eggs, for hatching) and for livestock and poultry feed apply to both domestically produced and imported commodities. They cover only primary agricultural products destined to animal feed (e.g. maize, potatoes, milk, etc.). Processed and semi-processed feed items such as bran, oilcakes, meals and molasses have been completely excluded from the calculations at all stages. It should be noted that when calculating indices of agricultural, food and nonfood production, all intermediate primary inputs of agricultural origin are deducted. However, for indices of any other commodity group, only inputs originating from within the same group are deducted; thus, only seed is removed from the group \"crops\" and from all crop subgroups, such as cereals, oil crops, etc.; and both feed and seed originating from within the livestock sector (e.g. milk feed, hatching eggs) are removed from the group \"livestock products\". For the main two livestock subgroups, namely, meat and milk, only feed originating from the respective subgroup is removed. Indices which take into account deductions for feed and seed are referred to as ''net''. Indices calculated without any deductions for feed and seed are referred to as ''gross\". The \"international commodity prices\" are used in order to avoid the use of exchange rates for obtaining continental and world aggregates, and also to improve and facilitate international comparative analysis of productivity at the national level. These\" international prices,\" expressed in so-called \"international dollars,\" are derived using a Geary-Khamis formula** for the agricultural sector. This method assigns a single \"price\" to each commodity. For example, one metric ton of wheat has the same price regardless of the country where it was produced. The currency unit in which the prices are expressed has no influence on the indices published. The commodities covered in the computation of indices of agricultural production are all crops and livestock products originating in each country. Practically all products are covered, with the main exception of fodder crops.\n\n* A Laspeyres Index is known as a \"base-weighted\" or \"fixed-weighted\" index because the price increases are weighted by the quantities in the base period. The Consumer Price Index is an example of a Laspeyres Index. http://www.usna.edu/Users/econ/rbrady/312%20Materials/LaspeyresCalc.pdf\n** Geary-Khamis formula is an aggregation method in which category \"international prices\" (reflecting relative category values) and country purchasing power parities (PPPs), (depicting relative country price levels) are estimated simultaneously from a system of linear equations. http://stats.oecd.org/glossary/detail.asp?ID=5528", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2014-2014 = 100" }, "ag_srf_totl_k2": { "title": "Surface area (sq. km)", "description_from_producer": "Surface area is a country's total area, including areas under inland bodies of water and some coastal waterways.\n\nLimitations and exceptions: The data are collected by the Food and Agriculture Organization (FAO) of the United Nations through annual questionnaires. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible.\n\nThe data collected from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.\n\nStatistical concept and methodology: Total land area includes inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area. Including areas of former states; for example, the areas of the Union of Soviet Socialist Republics (USSR) are counted in Russian Federationand other successor states.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "sq. km", "short_unit": "sq. km" }, "ag_yld_crel_kg": { "title": "Cereal yield (kg per hectare)", "description_from_producer": "Cereal yield, measured as kilograms per hectare of harvested land, includes wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded. The FAO allocates production data to the calendar year in which the bulk of the harvest took place. Most of a crop harvested near the end of a year will be used in the following year.\n\nLimitations and exceptions: Cereals production data relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded. The FAO allocates production data to the calendar year in which the bulk of the harvest took place. Most of a crop harvested near the end of a year will be used in the following year.\n\nThe data are collected by the Food and Agriculture Organization of the United Nations (FAO) through annual questionnaires. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries.\n\nData on cereal yield may be affected by a variety of reporting and timing differences. Millet and sorghum, which are grown as feed for livestock and poultry in Europe and North America, are used as food in Africa, Asia, and countries of the former Soviet Union. So some cereal crops are excluded from the data for some countries and included elsewhere, depending on their use.\n\nThe data collected from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.\n\nStatistical concept and methodology: A cereal is a grass cultivated for the edible components of their grain, composed of the endosperm, germ, and bran. Cereal yield is measured as kilograms per hectare of harvested land. Cereal grains are grown in greater quantities and provide more food energy worldwide than any other type of crop; cereal crops therefore can also be called staple crops Cereals production includes wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kg per hectare", "short_unit": "kg" }, "bg_gsr_nfsv_gd_zs": { "title": "Trade in services (% of GDP)", "description_from_producer": "Trade in services is the sum of service exports and imports divided by the value of GDP, all in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "bm_gsr_cmcp_zs": { "title": "Communications, computer, etc. (% of service imports, BoP)", "description_from_producer": "Communications, computer, information, and other services cover international telecommunications; computer data; news-related service transactions between residents and nonresidents; construction services; royalties and license fees; miscellaneous business, professional, and technical services; personal, cultural, and recreational services; manufacturing services on physical inputs owned by others; and maintenance and repair services and government services not included elsewhere.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of service imports, BoP", "short_unit": "%" }, "bm_gsr_fcty_cd": { "title": "Primary income payments (BoP, current US$)", "description_from_producer": "Primary income payments refer to employee compensation paid to nonresident workers and investment income (payments on direct investment, portfolio investment, other investments). Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bm_gsr_gnfs_cd": { "title": "Imports of goods and services (BoP, current US$)", "description_from_producer": "Imports of goods and services comprise all transactions between residents of a country and the rest of the world involving a change of ownership from nonresidents to residents of general merchandise, nonmonetary gold, and services. Data are in current U.S. dollars.\n\nLimitations and exceptions: Discrepancies may arise in the balance of payments because there is no single source for balance of payments data and therefore no way to ensure that the data are fully consistent. Sources include customs data, monetary accounts of the banking system, external debt records, information provided by enterprises, surveys to estimate service transactions, and foreign exchange records. Differences in collection methods - such as in timing, definitions of residence and ownership, and the exchange rate used to value transactions - contribute to net errors and omissions. In addition, smuggling and other illegal or quasi-legal transactions may be unrecorded or misrecorded.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bm_gsr_insf_zs": { "title": "Insurance and financial services (% of service imports, BoP)", "description_from_producer": "Insurance and financial services cover various types of insurance provided to nonresidents by resident insurance enterprises and vice versa, and financial intermediary and auxiliary services (except those of insurance enterprises and pension funds) exchanged between residents and nonresidents.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of service imports, BoP", "short_unit": "%" }, "bm_gsr_mrch_cd": { "title": "Goods imports (BoP, current US$)", "description_from_producer": "Goods imports refer to all movable goods (including nonmonetary gold) involved in a change of ownership from nonresidents to residents. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bm_gsr_nfsv_cd": { "title": "Service imports (BoP, current US$)", "description_from_producer": "Services refer to economic output of intangible commodities that may be produced, transferred, and consumed at the same time. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bm_gsr_royl_cd": { "title": "Charges for the use of intellectual property, payments (BoP, current US$)", "description_from_producer": "Charges for the use of intellectual property are payments and receipts between residents and nonresidents for the authorized use of proprietary rights (such as patents, trademarks, copyrights, industrial processes and designs including trade secrets, and franchises) and for the use, through licensing agreements, of produced originals or prototypes (such as copyrights on books and manuscripts, computer software, cinematographic works, and sound recordings) and related rights (such as for live performances and television, cable, or satellite broadcast). Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bm_gsr_totl_cd": { "title": "Imports of goods, services and primary income (BoP, current US$)", "description_from_producer": "Imports of goods, services and primary income is the sum of goods imports, service imports and primary income payments. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bm_gsr_tran_zs": { "title": "Transport services (% of service imports, BoP)", "description_from_producer": "Transport covers all transport services (sea, air, land, internal waterway, pipeline, space and electricity transmission) performed by residents of one economy for those of another and involving the carriage of passengers, the movement of goods (freight), rental of carriers with crew, and related support and auxiliary services. Also included are postal and courier services. Excluded are freight insurance (included in insurance services); goods procured in ports by nonresident carriers (included in goods); maintenance and repairs on transport equipment (included in maintenance and repair services n.i.e.); and repairs of railway facilities, harbors, and airfield facilities (included in construction).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of service imports, BoP", "short_unit": "%" }, "bm_gsr_trvl_zs": { "title": "Travel services (% of service imports, BoP)", "description_from_producer": "Travel covers goods and services acquired from an economy by travelers for their own use during visits of less than one year in that economy for either business or personal purposes. Travel includes local transport (i.e., transport within the economy being visited and provided by a resident of that economy), but excludes international transport (which is included in passenger transport. Travel also excludes goods for resale, which are included in general merchandise.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of service imports, BoP", "short_unit": "%" }, "bm_klt_dinv_cd_wd": { "title": "Foreign direct investment, net outflows (BoP, current US$)", "description_from_producer": "Foreign direct investment refers to direct investment equity flows in an economy. It is the sum of equity capital, reinvestment of earnings, and other capital. Direct investment is a category of cross-border investment associated with a resident in one economy having control or a significant degree of influence on the management of an enterprise that is resident in another economy. Ownership of 10 percent or more of the ordinary shares of voting stock is the criterion for determining the existence of a direct investment relationship. This series shows net outflows of investment from the reporting economy to the rest of the world. Data are in current U.S. dollars.\n\nLimitations and exceptions: FDI data do not give a complete picture of international investment in an economy. Balance of payments data on FDI do not include capital raised locally, an important source of investment financing in some developing countries. In addition, FDI data omit nonequity cross-border transactions such as intra-unit flows of goods and services.\n\nThe volume of global private financial flows reported by the World Bank generally differs from that reported by other sources because of differences in sources, classification of economies, and method used to adjust and disaggregate reported information. In addition, particularly for debt financing, differences may also reflect how some installments of the transactions and certain offshore issuances are treated.\n\nData on equity flows are shown for all countries for which data are available.\n\nStatistical concept and methodology: Data on equity flows are based on balance of payments data reported by the International Monetary Fund (IMF). Foreign direct investment (FDI) data are supplemented by the World Bank staff estimates using data from the United Nations Conference on Trade and Development (UNCTAD) and official national sources.\n\nThe internationally accepted definition of FDI (from the sixth edition of the IMF's Balance of Payments Manual [2009]), includes the following components: equity investment, including investment associated with equity that gives rise to control or influence; investment in indirectly influenced or controlled enterprises; investment in fellow enterprises; debt (except selected debt); and reverse investment. The Framework for Direct Investment Relationships provides criteria for determining whether cross-border ownership results in a direct investment relationship, based on control and influence. Distinguished from other kinds of international investment, FDI is made to establish a lasting interest in or effective management control over an enterprise in another country. A lasting interest in an investment enterprise typically involves establishing warehouses, manufacturing facilities, and other permanent or long-term organizations abroad. Direct investments may take the form of greenfield investment, where the investor starts a new venture in a foreign country by constructing new operational facilities; joint venture, where the investor enters into a partnership agreement with a company abroad to establish a new enterprise; or merger and acquisition, where the investor acquires an existing enterprise abroad. The IMF suggests that investments should account for at least 10 percent of voting stock to be counted as FDI. In practice many countries set a higher threshold. Many countries fail to report reinvested earnings, and the definition of long-term loans differs among countries. BoP refers to Balance of Payments.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bm_klt_dinv_wd_gd_zs": { "title": "Foreign direct investment, net outflows (% of GDP)", "description_from_producer": "Foreign direct investment refers to direct investment equity flows in an economy. It is the sum of equity capital, reinvestment of earnings, and other capital. Direct investment is a category of cross-border investment associated with a resident in one economy having control or a significant degree of influence on the management of an enterprise that is resident in another economy. Ownership of 10 percent or more of the ordinary shares of voting stock is the criterion for determining the existence of a direct investment relationship. This series shows net outflows of investment from the reporting economy to the rest of the world, and is divided by GDP.\n\nLimitations and exceptions: FDI data do not give a complete picture of international investment in an economy. Balance of payments data on FDI do not include capital raised locally, an important source of investment financing in some developing countries. In addition, FDI data omit nonequity cross-border transactions such as intra-unit flows of goods and services.\n\nThe volume of global private financial flows reported by the World Bank generally differs from that reported by other sources because of differences in sources, classification of economies, and method used to adjust and disaggregate reported information. In addition, particularly for debt financing, differences may also reflect how some installments of the transactions and certain offshore issuances are treated.\n\nData on equity flows are shown for all countries for which data are available.\n\nStatistical concept and methodology: Data on equity flows are based on balance of payments data reported by the International Monetary Fund (IMF). Foreign direct investment (FDI) data are supplemented by the World Bank staff estimates using data from the United Nations Conference on Trade and Development (UNCTAD) and official national sources.\n\nThe internationally accepted definition of FDI (from the sixth edition of the IMF's Balance of Payments Manual [2009]), includes the following components: equity investment, including investment associated with equity that gives rise to control or influence; investment in indirectly influenced or controlled enterprises; investment in fellow enterprises; debt (except selected debt); and reverse investment. The Framework for Direct Investment Relationships provides criteria for determining whether cross-border ownership results in a direct investment relationship, based on control and influence. Distinguished from other kinds of international investment, FDI is made to establish a lasting interest in or effective management control over an enterprise in another country. A lasting interest in an investment enterprise typically involves establishing warehouses, manufacturing facilities, and other permanent or long-term organizations abroad. Direct investments may take the form of greenfield investment, where the investor starts a new venture in a foreign country by constructing new operational facilities; joint venture, where the investor enters into a partnership agreement with a company abroad to establish a new enterprise; or merger and acquisition, where the investor acquires an existing enterprise abroad. The IMF suggests that investments should account for at least 10 percent of voting stock to be counted as FDI. In practice many countries set a higher threshold. Many countries fail to report reinvested earnings, and the definition of long-term loans differs among countries. BoP refers to Balance of Payments.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "bm_trf_prvt_cd": { "title": "Secondary income, other sectors, payments (BoP, current US$)", "description_from_producer": "Secondary income refers to transfers recorded in the balance of payments whenever an economy provides or receives goods, services, income, or financial items without a quid pro quo. All transfers not considered to be capital are current. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_cab_xoka_cd": { "title": "Current account balance (BoP, current US$)", "description_from_producer": "Current account balance is the sum of net exports of goods and services, net primary income, and net secondary income. Data are in current U.S. dollars.\n\nLimitations and exceptions: Discrepancies may arise in the balance of payments because there is no single source for balance of payments data and therefore no way to ensure that the data are fully consistent. Sources include customs data, monetary accounts of the banking system, external debt records, information provided by enterprises, surveys to estimate service transactions, and foreign exchange records. Differences in collection methods - such as in timing, definitions of residence and ownership, and the exchange rate used to value transactions - contribute to net errors and omissions. In addition, smuggling and other illegal or quasi-legal transactions may be unrecorded or misrecorded.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_cab_xoka_gd_zs": { "title": "Current account balance (% of GDP)", "description_from_producer": "Current account balance is the sum of net exports of goods and services, net primary income, and net secondary income.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "bn_fin_totl_cd": { "title": "Net financial account (BoP, current US$)", "description_from_producer": "The net financial account shows net acquisition and disposal of financial assets and liabilities. It measures how net lending to or borrowing from nonresidents is financed, and is conceptually equal to the sum of the balances on the current and capital accounts. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_gsr_fcty_cd": { "title": "Net primary income (BoP, current US$)", "description_from_producer": "Net primary income refers to receipts and payments of employee compensation paid to nonresident workers and investment income (receipts and payments on direct investment, portfolio investment, other investments, and receipts on reserve assets). Data are in current U.S. dollars.\n\nLimitations and exceptions: Discrepancies may arise in the balance of payments because there is no single source for balance of payments data and therefore no way to ensure that the data are fully consistent. Sources include customs data, monetary accounts of the banking system, external debt records, information provided by enterprises, surveys to estimate service transactions, and foreign exchange records. Differences in collection methods - such as in timing, definitions of residence and ownership, and the exchange rate used to value transactions - contribute to net errors and omissions. In addition, smuggling and other illegal or quasi-legal transactions may be unrecorded or misrecorded.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_gsr_gnfs_cd": { "title": "Net trade in goods and services (BoP, current US$)", "description_from_producer": "Net trade in goods and services is derived by offsetting imports of goods and services against exports of goods and services. Exports and imports of goods and services comprise all transactions involving a change of ownership of goods and services between residents of one country and the rest of the world. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_gsr_mrch_cd": { "title": "Net trade in goods (BoP, current US$)", "description_from_producer": "Net trade in goods is the difference between exports and imports of goods. Trade in services is not included. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_kac_eoms_cd": { "title": "Net errors and omissions (BoP, current US$)", "description_from_producer": "Net errors and omissions constitute a residual category needed to ensure that accounts in the balance of payments statement sum to zero. Net errors and omissions are derived as the balance on the financial account minus the balances on the current and capital accounts. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_klt_dinv_cd": { "title": "Foreign direct investment, net (BoP, current US$)", "description_from_producer": "Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. This series shows total net FDI. In BPM6, financial account balances are calculated as the change in assets minus the change in liabilities. Net FDI outflows are assets and net FDI inflows are liabilities. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_klt_ptxl_cd": { "title": "Portfolio Investment, net (BoP, current US$)", "description_from_producer": "Portfolio investment covers transactions in equity securities and debt securities. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_res_incl_cd": { "title": "Reserves and related items (BoP, current US$)", "description_from_producer": "Reserves and related items is the net change in a country's holdings of international reserves resulting from transactions on the current, capital, and financial accounts. Reserve assets are those external assets that are readily available to and controlled by monetary authorities for meeting balance of payments financing needs, and include holdings of monetary gold, special drawing rights (SDRs), reserve position in the International Monetary Fund (IMF), and other reserve assets. Also included are net credit and loans from the IMF (excluding reserve position) and total exceptional financing. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_trf_curr_cd": { "title": "Net secondary income (BoP, current US$)", "description_from_producer": "Secondary income refers to transfers recorded in the balance of payments whenever an economy provides or receives goods, services, income, or financial items without a quid pro quo. All transfers not considered to be capital are current. Data are in current U.S. dollars.\n\nLimitations and exceptions: Discrepancies may arise in the balance of payments because there is no single source for balance of payments data and therefore no way to ensure that the data are fully consistent. Sources include customs data, monetary accounts of the banking system, external debt records, information provided by enterprises, surveys to estimate service transactions, and foreign exchange records. Differences in collection methods - such as in timing, definitions of residence and ownership, and the exchange rate used to value transactions - contribute to net errors and omissions. In addition, smuggling and other illegal or quasi-legal transactions may be unrecorded or misrecorded.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bn_trf_kogt_cd": { "title": "Net capital account (BoP, current US$)", "description_from_producer": "Net capital account records acquisitions and disposals of nonproduced nonfinancial assets, such as land sold to embassies and sales of leases and licenses, as well as capital transfers, including government debt forgiveness. The use of the term capital account in this context is designed to be consistent with the System of National Accounts, which distinguishes between capital transactions and financial transactions. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_grt_exta_cd_wd": { "title": "Grants, excluding technical cooperation (BoP, current US$)", "description_from_producer": "Grants are defined as legally binding commitments that obligate a specific value of funds available for disbursement for which there is no repayment requirement. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data on ODA is for aid-receiving countries. The data cover loans and grants from DAC member countries, multilateral organizations, and non-DAC donors. They do not reflect aid given by recipient countries to other developing countries. As a result, some countries that are net donors (such as Saudi Arabia) are shown as aid recipients. The indicator does not distinguish types of aid (program, project, or food aid; emergency assistance; or post-conflict peacekeeping assistance), which may have different effects on the economy.\n\nBecause the indicator relies on information from donors, it is not necessarily consistent with information recorded by recipients in the balance of payments, which often excludes all or some technical assistance - particularly payments to expatriates made directly by the donor. Similarly, grant commodity aid may not always be recorded in trade data or in the balance of payments. Moreover, DAC statistics exclude aid for military and antiterrorism purposes.\n\nThe aggregates refer to World Bank classifications of economies and therefore may differ from those of the OECD.\n\nStatistical concept and methodology: Grants are transfers made in cash, goods or services for which no repayment is required. Data excludes technical cooperation grants. The flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat. A network of statistical correspondents collects data from aid agencies and government departments (central, state and local) on an ongoing basis. Their task is also to ensure that reporting conforms to the Reporting Directives (definitions and classifications) agreed by the DAC.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_grt_tech_cd_wd": { "title": "Technical cooperation grants (BoP, current US$)", "description_from_producer": "Technical cooperation grants include free-standing technical cooperation grants, which are intended to finance the transfer of technical and managerial skills or of technology for the purpose of building up general national capacity without reference to any specific investment projects; and investment-related technical cooperation grants, which are provided to strengthen the capacity to execute specific investment projects. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data on ODA is for aid-receiving countries. The data cover loans and grants from DAC member countries, multilateral organizations, and non-DAC donors. They do not reflect aid given by recipient countries to other developing countries. As a result, some countries that are net donors (such as Saudi Arabia) are shown as aid recipients. The indicator does not distinguish types of aid (program, project, or food aid; emergency assistance; or post-conflict peacekeeping assistance), which may have different effects on the economy.\n\nBecause this indicator relies on information from donors, it is not necessarily consistent with information recorded by recipients in the balance of payments, which often excludes all or some technical assistance - particularly payments to expatriates made directly by the donor. Similarly, grant commodity aid may not always be recorded in trade data or in the balance of payments. Moreover, DAC statistics exclude aid for military and antiterrorism purposes.\n\nThe aggregates refer to World Bank classifications of economies and therefore may differ from those of the OECD.\n\nStatistical concept and methodology: Technical cooperation contributions take the form mainly of the supply of human resources from donors or action directed to human resources (such as training or advice). Also included are aid for promoting development awareness and aid provided to refugees in the donor economy. Assistance specifically to facilitate a capital project is not included. Technical cooperation ncludes both grants to nationals of aid recipient countries receiving education or training at home or abroad and payments to consultants, advisers and similar personnel as well as teachers and administrators serving in recipient countries (including the cost of associated equipment).\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat. A network of statistical correspondents collects data from aid agencies and government departments (central, state and local) on an ongoing basis. Their task is also to ensure that reporting conforms to the Reporting Directives (definitions and classifications) agreed by the DAC.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_gsr_ccis_cd": { "title": "ICT service exports (BoP, current US$)", "description_from_producer": "Information and communication technology service exports include computer and communications services (telecommunications and postal and courier services) and information services (computer data and news-related service transactions). Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_gsr_ccis_zs": { "title": "ICT service exports (% of service exports, BoP)", "description_from_producer": "Information and communication technology service exports include computer and communications services (telecommunications and postal and courier services) and information services (computer data and news-related service transactions).\n\nLimitations and exceptions: Discrepancies may arise in the balance of payments because there is no single source for balance of payments data and therefore no way to ensure that the data are fully consistent. Sources include customs data, monetary accounts of the banking system, external debt records, information provided by enterprises, surveys to estimate service transactions, and foreign exchange records. Differences in collection methods - such as in timing, definitions of residence and ownership, and the exchange rate used to value transactions - contribute to net errors and omissions. In addition, smuggling and other illegal or quasi-legal transactions may be unrecorded or misrecorded.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of service exports, BoP", "short_unit": "%" }, "bx_gsr_cmcp_zs": { "title": "Communications, computer, etc. (% of service exports, BoP)", "description_from_producer": "Communications, computer, information, and other services cover international telecommunications; computer data; news-related service transactions between residents and nonresidents; construction services; royalties and license fees; miscellaneous business, professional, and technical services; personal, cultural, and recreational services; manufacturing services on physical inputs owned by others; and maintenance and repair services and government services not included elsewhere.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of service exports, BoP", "short_unit": "%" }, "bx_gsr_fcty_cd": { "title": "Primary income receipts (BoP, current US$)", "description_from_producer": "Primary income receipts refer to employee compensation paid to resident workers working abroad and investment income (receipts on direct investment, portfolio investment, other investments, and receipts on reserve assets). Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_gsr_gnfs_cd": { "title": "Exports of goods and services (BoP, current US$)", "description_from_producer": "Exports of goods and services comprise all transactions between residents of a country and the rest of the world involving a change of ownership from residents to nonresidents of general merchandise, net exports of goods under merchanting, nonmonetary gold, and services. Data are in current U.S. dollars.\n\nLimitations and exceptions: Discrepancies may arise in the balance of payments because there is no single source for balance of payments data and therefore no way to ensure that the data are fully consistent. Sources include customs data, monetary accounts of the banking system, external debt records, information provided by enterprises, surveys to estimate service transactions, and foreign exchange records. Differences in collection methods - such as in timing, definitions of residence and ownership, and the exchange rate used to value transactions - contribute to net errors and omissions. In addition, smuggling and other illegal or quasi-legal transactions may be unrecorded or misrecorded.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_gsr_insf_zs": { "title": "Insurance and financial services (% of service exports, BoP)", "description_from_producer": "Insurance and financial services cover various types of insurance provided to nonresidents by resident insurance enterprises and vice versa, and financial intermediary and auxiliary services (except those of insurance enterprises and pension funds) exchanged between residents and nonresidents.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of service exports, BoP", "short_unit": "%" }, "bx_gsr_mrch_cd": { "title": "Goods exports (BoP, current US$)", "description_from_producer": "Goods exports refer to all movable goods (including nonmonetary gold and net exports of goods under merchanting) involved in a change of ownership from residents to nonresidents. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_gsr_nfsv_cd": { "title": "Service exports (BoP, current US$)", "description_from_producer": "Services refer to economic output of intangible commodities that may be produced, transferred, and consumed at the same time. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_gsr_royl_cd": { "title": "Charges for the use of intellectual property, receipts (BoP, current US$)", "description_from_producer": "Charges for the use of intellectual property are payments and receipts between residents and nonresidents for the authorized use of proprietary rights (such as patents, trademarks, copyrights, industrial processes and designs including trade secrets, and franchises) and for the use, through licensing agreements, of produced originals or prototypes (such as copyrights on books and manuscripts, computer software, cinematographic works, and sound recordings) and related rights (such as for live performances and television, cable, or satellite broadcast). Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_gsr_totl_cd": { "title": "Exports of goods, services and primary income (BoP, current US$)", "description_from_producer": "Exports of goods, services and primary income is the sum of goods exports, service exports and primary income receipts. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_gsr_tran_zs": { "title": "Transport services (% of service exports, BoP)", "description_from_producer": "Transport covers all transport services (sea, air, land, internal waterway, pipeline, space and electricity transmission) performed by residents of one economy for those of another and involving the carriage of passengers, the movement of goods (freight), rental of carriers with crew, and related support and auxiliary services. Also included are postal and courier services. Excluded are freight insurance (included in insurance services); goods procured in ports by nonresident carriers (included in goods); maintenance and repairs on transport equipment (included in maintenance and repair services n.i.e.); and repairs of railway facilities, harbors, and airfield facilities (included in construction).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of service exports, BoP", "short_unit": "%" }, "bx_gsr_trvl_zs": { "title": "Travel services (% of service exports, BoP)", "description_from_producer": "Travel covers goods and services acquired from an economy by travelers for their own use during visits of less than one year in that economy for either business or personal purposes. Travel includes local transport (i.e., transport within the economy being visited and provided by a resident of that economy), but excludes international transport (which is included in passenger transport. Travel also excludes goods for resale, which are included in general merchandise.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of service exports, BoP", "short_unit": "%" }, "bx_klt_dinv_cd_wd": { "title": "Foreign direct investment, net inflows (BoP, current US$)", "description_from_producer": "Foreign direct investment refers to direct investment equity flows in the reporting economy. It is the sum of equity capital, reinvestment of earnings, and other capital. Direct investment is a category of cross-border investment associated with a resident in one economy having control or a significant degree of influence on the management of an enterprise that is resident in another economy. Ownership of 10 percent or more of the ordinary shares of voting stock is the criterion for determining the existence of a direct investment relationship. Data are in current U.S. dollars.\n\nLimitations and exceptions: FDI data do not give a complete picture of international investment in an economy. Balance of payments data on FDI do not include capital raised locally, an important source of investment financing in some developing countries. In addition, FDI data omit nonequity cross-border transactions such as intra-unit flows of goods and services.\n\nThe volume of global private financial flows reported by the World Bank generally differs from that reported by other sources because of differences in sources, classification of economies, and method used to adjust and disaggregate reported information. In addition, particularly for debt financing, differences may also reflect how some installments of the transactions and certain offshore issuances are treated.\n\nData on equity flows are shown for all countries for which data are available.\n\nStatistical concept and methodology: Data on equity flows are based on balance of payments data reported by the International Monetary Fund (IMF). Foreign direct investment (FDI) data are supplemented by the World Bank staff estimates using data from the United Nations Conference on Trade and Development (UNCTAD) and official national sources.\n\nThe internationally accepted definition of FDI (from the sixth edition of the IMF's Balance of Payments Manual [2009]), includes the following components: equity investment, including investment associated with equity that gives rise to control or influence; investment in indirectly influenced or controlled enterprises; investment in fellow enterprises; debt (except selected debt); and reverse investment. The Framework for Direct Investment Relationships provides criteria for determining whether cross-border ownership results in a direct investment relationship, based on control and influence. Distinguished from other kinds of international investment, FDI is made to establish a lasting interest in or effective management control over an enterprise in another country. A lasting interest in an investment enterprise typically involves establishing warehouses, manufacturing facilities, and other permanent or long-term organizations abroad. Direct investments may take the form of greenfield investment, where the investor starts a new venture in a foreign country by constructing new operational facilities; joint venture, where the investor enters into a partnership agreement with a company abroad to establish a new enterprise; or merger and acquisition, where the investor acquires an existing enterprise abroad. The IMF suggests that investments should account for at least 10 percent of voting stock to be counted as FDI. In practice many countries set a higher threshold. Many countries fail to report reinvested earnings, and the definition of long-term loans differs among countries. BoP refers to Balance of Payments.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_klt_dinv_wd_gd_zs": { "title": "Foreign direct investment, net inflows (% of GDP)", "description_from_producer": "Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. This series shows net inflows (new investment inflows less disinvestment) in the reporting economy from foreign investors, and is divided by GDP.\n\nLimitations and exceptions: FDI data do not give a complete picture of international investment in an economy. Balance of payments data on FDI do not include capital raised locally, an important source of investment financing in some developing countries. In addition, FDI data omit nonequity cross-border transactions such as intra-unit flows of goods and services.\n\nThe volume of global private financial flows reported by the World Bank generally differs from that reported by other sources because of differences in sources, classification of economies, and method used to adjust and disaggregate reported information. In addition, particularly for debt financing, differences may also reflect how some installments of the transactions and certain offshore issuances are treated.\n\nData on equity flows are shown for all countries for which data are available.\n\nStatistical concept and methodology: Data on equity flows are based on balance of payments data reported by the International Monetary Fund (IMF). Foreign direct investment (FDI) data are supplemented by the World Bank staff estimates using data from the United Nations Conference on Trade and Development (UNCTAD) and official national sources.\n\nThe internationally accepted definition of FDI (from the sixth edition of the IMF's Balance of Payments Manual [2009]), includes the following components: equity investment, including investment associated with equity that gives rise to control or influence; investment in indirectly influenced or controlled enterprises; investment in fellow enterprises; debt (except selected debt); and reverse investment. The Framework for Direct Investment Relationships provides criteria for determining whether cross-border ownership results in a direct investment relationship, based on control and influence. Distinguished from other kinds of international investment, FDI is made to establish a lasting interest in or effective management control over an enterprise in another country. A lasting interest in an investment enterprise typically involves establishing warehouses, manufacturing facilities, and other permanent or long-term organizations abroad. Direct investments may take the form of greenfield investment, where the investor starts a new venture in a foreign country by constructing new operational facilities; joint venture, where the investor enters into a partnership agreement with a company abroad to establish a new enterprise; or merger and acquisition, where the investor acquires an existing enterprise abroad. The IMF suggests that investments should account for at least 10 percent of voting stock to be counted as FDI. In practice many countries set a higher threshold. Many countries fail to report reinvested earnings, and the definition of long-term loans differs among countries. BoP refers to Balance of Payments.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "bx_pef_totl_cd_wd": { "title": "Portfolio equity, net inflows (BoP, current US$)", "description_from_producer": "Portfolio equity includes net inflows from equity securities other than those recorded as direct investment and including shares, stocks, depository receipts (American or global), and direct purchases of shares in local stock markets by foreign investors. Data are in current U.S. dollars.\n\nLimitations and exceptions: Portfolio investors typically have less of a role in the decision making of the enterprise with potentially important implications for future flows and for the volatility of the price and volume of positions. Portfolio investment differs from other investment in that it provides a direct way to access financial markets, and thus it can provide liquidity and flexibility. It is associated with financial markets and with their specialized service providers, such as exchanges, dealers, and regulators. The nature of financial derivatives as instruments through which risk is traded in its own right in financial markets sets them apart from other types of investment. Whereas other instruments may also have risk transfer elements, these other instruments also provide financial or other resources.\n\nThe volume of global private financial flows reported by the World Bank generally differs from that reported by other sources because of differences in sources, classification of economies, and method used to adjust and disaggregate reported information. In addition, particularly for debt financing, differences may also reflect how some installments of the transactions and certain offshore issuances are treated.\n\nData on equity flows are shown for all countries for which data are available.\n\nStatistical concept and methodology: Data on equity flows are based on balance of payments data reported by the International Monetary Fund (IMF).\n\nPortfolio equity investment is defined as cross-border transactions and positions involving equity securities, other than those included in direct investment or reserve assets. Equity securities are equity instruments that are negotiable and designed to be traded, usually on organized exchanges or \"over the counter.\" The negotiability of securities facilitates trading, allowing securities to be held by different parties during their lives. Negotiability allows investors to diversify their portfolios and to withdraw their investment readily. Included in portfolio investment are investment fund shares or units (that is, those issued by investment funds) that are evidenced by securities and that are not reserve assets or direct investment. Although they are negotiable instruments, exchange-traded financial derivatives are not included in portfolio investment because they are in their own category.", "origins": [ { "producer": "International Monetary Fund and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_trf_curr_cd": { "title": "Secondary income receipts (BoP, current US$)", "description_from_producer": "Secondary income refers to transfers recorded in the balance of payments whenever an economy provides or receives goods, services, income, or financial items without a quid pro quo. All transfers not considered to be capital are current. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_trf_pwkr_cd": { "title": "Personal transfers, receipts (BoP, current US$)", "description_from_producer": "Personal transfers consist of all current transfers in cash or in kind made or received by resident households to or from nonresident households. Personal transfers thus include all current transfers between resident and nonresident individuals. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "BoP, current US$", "short_unit": "$" }, "bx_trf_pwkr_dt_gd_zs": { "title": "Personal remittances, received (% of GDP)", "description_from_producer": "Personal remittances comprise personal transfers and compensation of employees. Personal transfers consist of all current transfers in cash or in kind made or received by resident households to or from nonresident households. Personal transfers thus include all current transfers between resident and nonresident individuals. Compensation of employees refers to the income of border, seasonal, and other short-term workers who are employed in an economy where they are not resident and of residents employed by nonresident entities. Data are the sum of two items defined in the sixth edition of the IMF's Balance of Payments Manual: personal transfers and compensation of employees.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "cc_est": { "title": "Control of Corruption: Estimate", "description_from_producer": "Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as \"capture\" of the state by elites and private interests. Estimate gives the country's score on the aggregate indicator, in units of a standard normal distribution, i.e. ranging from approximately -2.5 to 2.5.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "cc_no_src": { "title": "Control of Corruption: Number of Sources", "description_from_producer": "Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as \"capture\" of the state by elites and private interests. Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "cc_per_rnk": { "title": "Control of Corruption: Percentile Rank", "description_from_producer": "Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as \"capture\" of the state by elites and private interests. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "cc_per_rnk_lower": { "title": "Control of Corruption: Percentile Rank, Lower Bound of 90% Confidence Interval", "description_from_producer": "Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as \"capture\" of the state by elites and private interests. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "cc_per_rnk_upper": { "title": "Control of Corruption: Percentile Rank, Upper Bound of 90% Confidence Interval", "description_from_producer": "Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as \"capture\" of the state by elites and private interests. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "cc_std_err": { "title": "Control of Corruption: Standard Error", "description_from_producer": "Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as \"capture\" of the state by elites and private interests. Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "cm_mkt_indx_zg": { "title": "S&P Global Equity Indices (annual % change)", "description_from_producer": "S&P Global Equity Indices measure the U.S. dollar price change in the stock markets covered by the S&P/IFCI and S&P/Frontier BMI country indices.\n\nLimitations and exceptions: The percentage change in stock market prices in U.S. dollars for developing economies is from Standard & Poor's Global Equity Indices (S&P IFCI) and Standard & Poor's Frontier Broad Market Index (BMI). The percentage change for France, Germany, Japan, the United Kingdom, and the United States is from local stock market prices.\n\nThe indicator is an important measure of overall performance. Regulatory and institutional factors that can affect investor confidence, such as entry and exit restrictions, the existence of a securities and exchange commission, and the quality of laws to protect investors, may influence the functioning of stock markets.\n\nBecause markets included in Standard & Poor's emerging markets category vary widely in level of development, it is best to look at the entire category to identify the most significant market trends. And it is useful to remember that stock market trends may be distorted by currency conversions, especially when a currency has registered a significant devaluation.\n\nStatistical concept and methodology: Ratios of end-of-period levels in U.S. dollars over previous end-of-period values in U.S. dollars times 100. These indexes are widely used benchmarks for international portfolio management.", "origins": [ { "producer": "Standard & Poor's (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % change", "short_unit": "%" }, "cm_mkt_lcap_cd": { "title": "Market capitalization of listed domestic companies (current US$)", "description_from_producer": "Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.\n\nLimitations and exceptions: Data cover measures of size (market capitalization, number of listed domestic companies) and liquidity (value of shares traded as a percentage of gross domestic product, value of shares traded as a percentage of market capitalization). The comparability of such data across countries may be limited by conceptual and statistical weaknesses, such as inaccurate reporting and differences in accounting standards.\n\nStatistical concept and methodology: Market capitalization figures include: shares of listed domestic companies; shares of foreign companies which are exclusively listed on an exchange (i.e., the foreign company is not listed on any other exchange); common and preferred shares of domestic companies; and shares without voting rights. Market capitalization figures exclude: collective investment funds ; rights, warrants, ETFs, convertible instruments ; options, futures ; foreign listed shares other than exclusively listed ones; companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status; and companies admitted to trading (i.e., companies whose shares are traded at the exchange but not listed at the exchange).", "origins": [ { "producer": "World Federation of Exchanges (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "cm_mkt_lcap_gd_zs": { "title": "Market capitalization of listed domestic companies (% of GDP)", "description_from_producer": "Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values.\n\nLimitations and exceptions: Data cover measures of size (market capitalization, number of listed domestic companies) and liquidity (value of shares traded as a percentage of gross domestic product, value of shares traded as a percentage of market capitalization). The comparability of such data across countries may be limited by conceptual and statistical weaknesses, such as inaccurate reporting and differences in accounting standards.\n\nStatistical concept and methodology: Market capitalization figures include: shares of listed domestic companies; shares of foreign companies which are exclusively listed on an exchange (i.e., the foreign company is not listed on any other exchange); common and preferred shares of domestic companies; and shares without voting rights. Market capitalization figures exclude: collective investment funds ; rights, warrants, ETFs, convertible instruments ; options, futures ; foreign listed shares other than exclusively listed ones; companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status; and companies admitted to trading (i.e., companies whose shares are traded at the exchange but not listed at the exchange).", "origins": [ { "producer": "World Federation of Exchanges (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "cm_mkt_ldom_no": { "title": "Listed domestic companies, total", "description_from_producer": "Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.\n\nLimitations and exceptions: Data cover measures of size (market capitalization, number of listed domestic companies) and liquidity (value of shares traded as a percentage of gross domestic product, value of shares traded as a percentage of market capitalization). The comparability of such data across countries may be limited by conceptual and statistical weaknesses, such as inaccurate reporting and differences in accounting standards.\n\nStatistical concept and methodology: A company is considered domestic when it is incorporated in the same country as where the exchange is located. The only exception is the case of foreign companies which are exclusively listed on an exchange (i.e., the foreign company is not listed on any other exchange as defined in the domestic market capitalization definition).", "origins": [ { "producer": "World Federation of Exchanges (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "cm_mkt_trad_cd": { "title": "Stocks traded, total value (current US$)", "description_from_producer": "The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.\n\nLimitations and exceptions: Data cover measures of size (market capitalization, number of listed domestic companies) and liquidity (value of shares traded as a percentage of gross domestic product, value of shares traded as a percentage of market capitalization). The comparability of such data across countries may be limited by conceptual and statistical weaknesses, such as inaccurate reporting and differences in accounting standards. Only EOB trades are included in the total value of shares traded.\n\nStatistical concept and methodology: The value of shares traded represent the transfer of ownership effected automatically through the exchange's electronic order book (EOB), where orders placed by trading members are usually exposed to all market users and automatically matched according to precise rules set up by the exchange, generally on a price/time priority basis. For data before 2001, the WFE used two different approaches for the collection of trading data, depending on the individual stock exchange's market organization and rules. The first approach is the Trading System View (TSV). Stock exchanges adopting this view count only those transactions which pass through their trading system or trading floor. The TSV is generally adopted by exchanges which operate a centralized order book (order-driven market). Trades done by their members off the exchange are not included. The second approach is the Regulated Environment View (REV). Stock exchanges in this category include all transactions subject to supervision by the market authority, including transactions made by members, and sometimes non-members, on outside trading systems and transactions into foreign markets. Figures reported under the REV approach will be higher than those reported under the TSV approach.", "origins": [ { "producer": "World Federation of Exchanges (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "cm_mkt_trad_gd_zs": { "title": "Stocks traded, total value (% of GDP)", "description_from_producer": "The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values.\n\nLimitations and exceptions: Data cover measures of size (market capitalization, number of listed domestic companies) and liquidity (value of shares traded as a percentage of gross domestic product, value of shares traded as a percentage of market capitalization). The comparability of such data across countries may be limited by conceptual and statistical weaknesses, such as inaccurate reporting and differences in accounting standards. Only EOB trades are included in the total value of shares traded.\n\nStatistical concept and methodology: The value of shares traded represent the transfer of ownership effected automatically through the exchange's electronic order book (EOB), where orders placed by trading members are usually exposed to all market users and automatically matched according to precise rules set up by the exchange, generally on a price/time priority basis. For data before 2001, the WFE used two different approaches for the collection of trading data, depending on the individual stock exchange's market organization and rules. The first approach is the Trading System View (TSV). Stock exchanges adopting this view count only those transactions which pass through their trading system or trading floor. The TSV is generally adopted by exchanges which operate a centralized order book (order-driven market). Trades done by their members off the exchange are not included. The second approach is the Regulated Environment View (REV). Stock exchanges in this category include all transactions subject to supervision by the market authority, including transactions made by members, and sometimes non-members, on outside trading systems and transactions into foreign markets. Figures reported under the REV approach will be higher than those reported under the TSV approach.", "origins": [ { "producer": "World Federation of Exchanges (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "cm_mkt_trnr": { "title": "Stocks traded, turnover ratio of domestic shares (%)", "description_from_producer": "Turnover ratio is the value of domestic shares traded divided by their market capitalization. The value is annualized by multiplying the monthly average by 12.\n\nLimitations and exceptions: Data cover measures of size (market capitalization, number of listed domestic companies) and liquidity (value of shares traded as a percentage of gross domestic product, value of shares traded as a percentage of market capitalization). The comparability of such data across countries may be limited by conceptual and statistical weaknesses, such as inaccurate reporting and differences in accounting standards. Only domestic shares are used in order to be consistent with domestic market capitalization.\n\nStatistical concept and methodology: Turnover ratio is the value of electronic order book (EOB) domestic shares traded divided by their market capitalization. The value is annualized by multiplying the monthly average by 12, according to the following formula: (Monthly EOB domestic shares traded / Month-end domestic market capitalization) x 12.", "origins": [ { "producer": "World Federation of Exchanges (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "dc_dac_ausl_cd": { "title": "Net bilateral aid flows from DAC donors, Australia (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_autl_cd": { "title": "Net bilateral aid flows from DAC donors, Austria (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_bell_cd": { "title": "Net bilateral aid flows from DAC donors, Belgium (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_canl_cd": { "title": "Net bilateral aid flows from DAC donors, Canada (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_cecl_cd": { "title": "Net bilateral aid flows from DAC donors, European Union institutions (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_chel_cd": { "title": "Net bilateral aid flows from DAC donors, Switzerland (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_czel_cd": { "title": "Net bilateral aid flows from DAC donors, Czech Republic (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_deul_cd": { "title": "Net bilateral aid flows from DAC donors, Germany (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_dnkl_cd": { "title": "Net bilateral aid flows from DAC donors, Denmark (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_espl_cd": { "title": "Net bilateral aid flows from DAC donors, Spain (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_finl_cd": { "title": "Net bilateral aid flows from DAC donors, Finland (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_fral_cd": { "title": "Net bilateral aid flows from DAC donors, France (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_gbrl_cd": { "title": "Net bilateral aid flows from DAC donors, United Kingdom (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_grcl_cd": { "title": "Net bilateral aid flows from DAC donors, Greece (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_hunl_cd": { "title": "Net bilateral aid flows from DAC donors, Hungary (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "dc_dac_irll_cd": { "title": "Net bilateral aid flows from DAC donors, Ireland (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_isll_cd": { "title": "Net bilateral aid flows from DAC donors, Iceland (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_ital_cd": { "title": "Net bilateral aid flows from DAC donors, Italy (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_jpnl_cd": { "title": "Net bilateral aid flows from DAC donors, Japan (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_korl_cd": { "title": "Net bilateral aid flows from DAC donors, Korea, Rep. (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_luxl_cd": { "title": "Net bilateral aid flows from DAC donors, Luxembourg (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_nldl_cd": { "title": "Net bilateral aid flows from DAC donors, Netherlands (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_norl_cd": { "title": "Net bilateral aid flows from DAC donors, Norway (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_nzll_cd": { "title": "Net bilateral aid flows from DAC donors, New Zealand (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_poll_cd": { "title": "Net bilateral aid flows from DAC donors, Poland (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_prtl_cd": { "title": "Net bilateral aid flows from DAC donors, Portugal (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_svkl_cd": { "title": "Net bilateral aid flows from DAC donors, Slovak Republic (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_svnl_cd": { "title": "Net bilateral aid flows from DAC donors, Slovenia (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_swel_cd": { "title": "Net bilateral aid flows from DAC donors, Sweden (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_totl_cd": { "title": "Net bilateral aid flows from DAC donors, Total (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_dac_usal_cd": { "title": "Net bilateral aid flows from DAC donors, United States (current US$)", "description_from_producer": "Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data exclude DAC members\u2019 multilateral aid (contributions to the regular budgets of the multilateral institutions). However, projects executed by multilateral institutions or nongovernmental organizations on behalf of DAC members are classified as bilateral aid (since the donor country effectively controls the use of the funds) and are included in the data.\n\nAid to unspecified economies is included in regional totals and, when possible, income group totals. Aid not allocated by country or region - including administrative costs, research on development, and aid to nongovernmental organizations - is included in the world total. Thus regional and income group totals do not sum to the world total.\n\nStatistical concept and methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_oda_tldc_cd": { "title": "Net ODA provided, to the least developed countries (current US$)", "description_from_producer": "Net Official development assistance (ODA) comprises grants or loans to developing countries and territories on the OECD/DAC list of aid recipients that are undertaken by the official sector with promotion of economic development and welfare as the main objective and at concessional financial terms. The list of least developed countries (LDCs) has been agreed by the General Assembly, on the recommendation of the Committee for Development Policy, Economic and Social Council.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_oda_tldc_gn_zs": { "title": "Net ODA provided to the least developed countries (% of GNI)", "description_from_producer": "Net Official development assistance (ODA) comprises grants or loans to developing countries and territories on the OECD/DAC list of aid recipients that are undertaken by the official sector with promotion of economic development and welfare as the main objective and at concessional financial terms. The list of least developed countries (LDCs) has been agreed by the General Assembly, on the recommendation of the Committee for Development Policy, Economic and Social Council. Series is shown as a share of donors' GNI.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "dc_oda_totl_cd": { "title": "Net ODA provided, total (current US$)", "description_from_producer": "Net Official development assistance (ODA) comprises grants or loans to developing countries and territories on the OECD/DAC list of aid recipients that are undertaken by the official sector with promotion of economic development and welfare as the main objective and at concessional financial terms.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dc_oda_totl_gn_zs": { "title": "Net ODA provided, total (% of GNI)", "description_from_producer": "Net Official development assistance (ODA) comprises grants or loans to developing countries and territories on the OECD/DAC list of aid recipients that are undertaken by the official sector with promotion of economic development and welfare as the main objective and at concessional financial terms. It is shown as a share of donors' GNI.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "dc_oda_totl_kd": { "title": "Net ODA provided, total (constant 2020 US$)", "description_from_producer": "Net Official development assistance (ODA) comprises grants or loans to developing countries and territories on the OECD/DAC list of aid recipients that are undertaken by the official sector with promotion of economic development and welfare as the main objective and at concessional financial terms. Data are in constant 2020 U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2020 US$", "short_unit": "$" }, "dt_dod_dect_cd": { "title": "External debt stocks, total (DOD, current US$)", "description_from_producer": "Total external debt is debt owed to nonresidents repayable in currency, goods, or services. Total external debt is the sum of public, publicly guaranteed, and private nonguaranteed long-term debt, use of IMF credit, and short-term debt. Short-term debt includes all debt having an original maturity of one year or less and interest in arrears on long-term debt. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "DOD, current US$", "short_unit": "$" }, "dt_dod_dect_gn_zs": { "title": "External debt stocks (% of GNI)", "description_from_producer": "Total external debt stocks to gross national income. Total external debt is debt owed to nonresidents repayable in currency, goods, or services. Total external debt is the sum of public, publicly guaranteed, and private nonguaranteed long-term debt, use of IMF credit, and short-term debt. Short-term debt includes all debt having an original maturity of one year or less and interest in arrears on long-term debt. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "dt_dod_dimf_cd": { "title": "Use of IMF credit (DOD, current US$)", "description_from_producer": "Use of IMF Credit: Data related to the operations of the IMF are provided by the IMF Treasurer\u2019s Department. They are converted from special drawing rights into dollars using end-of-period exchange rates for stocks and average-over-the-period exchange rates for flows. IMF trust fund operations under the Enhanced Structural Adjustment Facility, Extended Fund Facility, Poverty Reduction and Growth Facility, and Structural Adjustment Facility (Enhanced Structural Adjustment Facility in 1999) are presented together with all of the IMF\u2019s special facilities (buffer stock, supplemental reserve, compensatory and contingency facilities, oil facilities, and other facilities). SDR allocations are also included in this category. According to the BPM6, SDR allocations are recorded as the incurrence of a debt liability of the member receiving them (because of a requirement to repay the allocation in certain circumstances, and also because interest accrues). This debt item is introduced for the first time this year with historical data starting in 1999.\n\nStatistical concept and methodology: Data related to the operations of the IMF come from the IMF Treasurer's Department and are converted from special drawing rights (SDRs) into dollars using end-of-period exchange rates for stocks and average over the period exchange rates for converting flows. DOD refers to disbursed and outstanding debt; data are in current U.S. dollars.\n\nData on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "DOD, current US$", "short_unit": "$" }, "dt_dod_dlxf_cd": { "title": "External debt stocks, long-term (DOD, current US$)", "description_from_producer": "Long-term debt is debt that has an original or extended maturity of more than one year. It has three components: public, publicly guaranteed, and private nonguaranteed debt. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "DOD, current US$", "short_unit": "$" }, "dt_dod_dpng_cd": { "title": "External debt stocks, private nonguaranteed (PNG) (DOD, current US$)", "description_from_producer": "Private nonguaranteed external debt comprises long-term external obligations of private debtors that are not guaranteed for repayment by a public entity. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "DOD, current US$", "short_unit": "$" }, "dt_dod_dppg_cd": { "title": "External debt stocks, public and publicly guaranteed (PPG) (DOD, current US$)", "description_from_producer": "Public and publicly guaranteed debt comprises long-term external obligations of public debtors, including the national government, Public Corporations, State Owned Enterprises, Development Banks and Other Mixed Enterprises, political subdivisions (or an agency of either), autonomous public bodies, and external obligations of private debtors that are guaranteed for repayment by a public entity. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "DOD, current US$", "short_unit": "$" }, "dt_dod_dstc_cd": { "title": "External debt stocks, short-term (DOD, current US$)", "description_from_producer": "Short-term external debt is defined as debt that has an original maturity of one year or less. Available data permit no distinction between public and private nonguaranteed short-term debt. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "DOD, current US$", "short_unit": "$" }, "dt_dod_dstc_ir_zs": { "title": "Short-term debt (% of total reserves)", "description_from_producer": "Short-term debt includes all debt having an original maturity of one year or less and interest in arrears on long-term debt. Total reserves includes gold.\n\nLimitations and exceptions: The DRS encourages debtor countries to voluntarily provide information on their short-term external obligations. By its nature, short-term external debt is difficult to monitor: loan-by-loan registration is normally impractical, and monitoring systems typically rely on information requested periodically by the central bank from the banking sector. The World Bank regards the debtor country as the authoritative source of information on its short-term debt. Where such information is not available from the debtor country, data are derived from BIS data on international bank lending based on time remaining to original maturity. The data are reported based on residual maturity, but an estimate of short-term external liabilities by original maturity can be derived by deducting from claims due in one year those that have a maturity of between one and two years. However, BIS data include liabilities reported only by banks within the BIS reporting area. The results should thus be interpreted with caution. Because short-term debt poses an immediate burden and is particularly important for monitoring vulnerability, it is compared with total debt and foreign exchange reserves, which are instrumental in providing coverage for such obligations.\n\nA country's external debt burden, both debt outstanding and debt service, affects its creditworthiness and vulnerability. While data related to public and publicly guaranteed debt are reported to the DRS on a loan-by-loan basis, aggregate data on long-term private nonguaranteed debt are reported annually and are reported by the country or estimated by World Bank staff for countries where this type of external debt is known to be significant. Estimates are based on national data from the World Bank's Quarterly External Debt Statistics.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total reserves", "short_unit": "%" }, "dt_dod_dstc_xp_zs": { "title": "Short-term debt (% of exports of goods, services and primary income)", "description_from_producer": "Short-term external debt is defined as debt that has an original maturity of one year or less. Available data permit no distinction between public and private nonguaranteed short-term debt.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of exports of goods, services and primary income", "short_unit": "%" }, "dt_dod_dstc_zs": { "title": "Short-term debt (% of total external debt)", "description_from_producer": "Short-term debt includes all debt having an original maturity of one year or less and interest in arrears on long-term debt. Total external debt is debt owed to nonresidents repayable in currency, goods, or services. Total external debt is the sum of public, publicly guaranteed, and private nonguaranteed long-term debt, use of IMF credit, and short-term debt.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total external debt", "short_unit": "%" }, "dt_dod_mibr_cd": { "title": "PPG, IBRD (DOD, current US$)", "description_from_producer": "Public and publicly guaranteed debt outstanding from the International Bank for Reconstruction and Development (IBRD) is nonconcessional. Nonconcessional debt excludes loans with an original grant element of 35 percent or more. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "DOD, current US$", "short_unit": "$" }, "dt_dod_mida_cd": { "title": "PPG, IDA (DOD, current US$)", "description_from_producer": "Public and publicly guaranteed debt outstanding from the International Development Association (IDA) is concessional. Concessional debt is defined as loans with an original grant element of 35 percent or more. The grant element of a loan is the grant equivalent expressed as a percentage of the amount committed. It is used as a measure of the overall cost of borrowing. The grant equivalent of a loan is its commitment (present) value, less the discounted present value of its contractual debt service; conventionally, future service payments are discounted at 5 percent. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "DOD, current US$", "short_unit": "$" }, "dt_dod_mwbg_cd": { "title": "IBRD loans and IDA credits (DOD, current US$)", "description_from_producer": "IBRD loans and IDA credits are public and publicly guaranteed debt extended by the World Bank Group. The International Bank for Reconstruction and Development (IBRD) lends at market rates. Credits from the International Development Association (IDA) are at concessional rates. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "DOD, current US$", "short_unit": "$" }, "dt_dod_pvlx_cd": { "title": "Present value of external debt (current US$)", "description_from_producer": "Present value of debt is the sum of short-term external debt plus the discounted sum of total debt service payments due on public, publicly guaranteed, and private nonguaranteed long-term external debt over the life of existing loans. This calculation assumes that the PV of loans with a negative grant element is equal to the nominal value of the loan. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_dod_pvlx_ex_zs": { "title": "Present value of external debt (% of exports of goods, services and income)", "description_from_producer": "Present value of debt is the sum of short-term external debt plus the discounted sum of total debt service payments due on public, publicly guaranteed, and private nonguaranteed long-term external debt over the life of existing loans. This calculation assumes that the PV of loans with a negative grant element is equal to the nominal value of the loan. The exports denominator is a three-year average.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of exports of goods, services and income", "short_unit": "%" }, "dt_dod_pvlx_gn_zs": { "title": "Present value of external debt (% of GNI)", "description_from_producer": "Present value of debt is the sum of short-term external debt plus the discounted sum of total debt service payments due on public, publicly guaranteed, and private nonguaranteed long-term external debt over the life of existing loans. This calculation assumes that the PV of loans with a negative grant element is equal to the nominal value of the loan. The GNI denominator is a three-year average.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "dt_nfl_blat_cd": { "title": "Net financial flows, bilateral (NFL, current US$)", "description_from_producer": "Bilateral debt includes loans from governments and their agencies (including central banks), loans from autonomous bodies, and direct loans from official export credit agencies. Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Data show concessional and nonconcessional financial flows from official bilateral sources. The Organisation for Economic Co-operation and Development's (OECD) Development Assistance Committee (DAC) defines concessional flows from bilateral donors as flows with a grant element of at least 25 percent; they are evaluated assuming a 10 percent nominal discount rate.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_bond_cd": { "title": "Portfolio investment, bonds (PPG + PNG) (NFL, current US$)", "description_from_producer": "Bonds are securities issued with a fixed rate of interest for a period of more than one year. They include net flows through cross-border public and publicly guaranteed and private nonguaranteed bond issues. Data are in current U.S. dollars.\n\nLimitations and exceptions: The DRS encourages debtor countries to voluntarily provide information on their short-term external obligations. By its nature, short-term external debt is difficult to monitor: loan-by-loan registration is normally impractical, and monitoring systems typically rely on information requested periodically by the central bank from the banking sector. The World Bank regards the debtor country as the authoritative source of information on its short-term debt. Where such information is not available from the debtor country, data are derived from BIS data on international bank lending based on time remaining to original maturity. The data are reported based on residual maturity, but an estimate of short-term external liabilities by original maturity can be derived by deducting from claims due in one year those that have a maturity of between one and two years. However, BIS data include liabilities reported only by banks within the BIS reporting area. The results should thus be interpreted with caution. Because short-term debt poses an immediate burden and is particularly important for monitoring vulnerability, it is compared with total debt and foreign exchange reserves, which are instrumental in providing coverage for such obligations.\n\nA country's external debt burden, both debt outstanding and debt service, affects its creditworthiness and vulnerability. While data related to public and publicly guaranteed debt are reported to the DRS on a loan-by-loan basis, aggregate data on long-term private nonguaranteed debt are reported annually and are reported by the country or estimated by World Bank staff for countries where this type of external debt is known to be significant. Estimates are based on national data from the World Bank's Quarterly External Debt Statistics.\n\nStatistical concept and methodology: Bonds are debt instruments issued by public and publicly guaranteed or private debtors with durations of one year or longer. Bonds usually give the holder the unconditional right to fixed money income or contractually determined, variable money income.\n\nData on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_dpng_cd": { "title": "Net flows on external debt, private nonguaranteed (PNG) (NFL, current US$)", "description_from_producer": "Private nonguaranteed external debt is an external obligation of a private debtor that is not guaranteed for repayment by a public entity. Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Long-term external debt is defined as debt that has an original or extended maturity of more than one year and that is owed to nonresidents by residents of an economy and repayable in currency, goods, or services. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_faog_cd": { "title": "Net official flows from UN agencies, FAO (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_iaea_cd": { "title": "Net official flows from UN agencies, IAEA (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_ifad_cd": { "title": "Net official flows from UN agencies, IFAD (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_ilog_cd": { "title": "Net official flows from UN agencies, ILO (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_imfc_cd": { "title": "Net financial flows, IMF concessional (NFL, current US$)", "description_from_producer": "Net financial flows received by the borrower during the year are disbursements of loans and credits less repayments of principal. IMF is the International Monetary Fund, which provides concessional lending through the Poverty Reduction and Growth Facility and the IMF Trust Fund. Data are in current U.S. dollars.\n\nStatistical concept and methodology: The International Monetary Fund (IMF) makes concessional funds available through its Extended Credit Facility (which replaced the Poverty Reduction and Growth Facility in 2010), the Standby Credit Facility, and the Rapid Credit Facility. Eligibility is based principally on a country's per capita income and eligibility under IDA.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_imfn_cd": { "title": "Net financial flows, IMF nonconcessional (NFL, current US$)", "description_from_producer": "Net financial flows received by the borrower during the year are disbursements of loans and credits less repayments of principal. IMF is the International Monetary Fund, which provides nonconcessional lending through the credit it provides to its members, mainly to meet balance of payments needs. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Nonconcessional lending from the IMF is provided mainly through Stand-by Arrangements, the Flexible Credit Line, and the Extended Fund Facility.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_mibr_cd": { "title": "Net financial flows, IBRD (NFL, current US$)", "description_from_producer": "Net financial flows received by the borrower during the year are disbursements of loans and credits less repayments of principal. IBRD is the International Bank for Reconstruction and Development, the founding and largest member of the World Bank Group. Data are in current U.S. dollars.\n\nStatistical concept and methodology: The World Bank's International Bank for Reconstruction and Development (IBRD) lends to creditworthy countries at a variable base rate of six-month LIBOR plus a spread, either variable or fixed, for the life of the loan. The rate is reset every six months and applies to the interest period beginning on that date.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_mida_cd": { "title": "Net financial flows, IDA (NFL, current US$)", "description_from_producer": "Net financial flows received by the borrower during the year are disbursements of loans and credits less repayments of principal. IDA is the International Development Association, the concessional loan window of the World Bank Group. Data are in current U.S. dollars.\n\nStatistical concept and methodology: World Bank concessional lending is done by the International Development Association (IDA) based on gross national income (GNI) per capita and performance standards assessed by World Bank staff.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_mlat_cd": { "title": "Net financial flows, multilateral (NFL, current US$)", "description_from_producer": "Public and publicly guaranteed multilateral loans include loans and credits from the World Bank, regional development banks, and other multilateral and intergovernmental agencies. Excluded are loans from funds administered by an international organization on behalf of a single donor government; these are classified as loans from governments. Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Data show concessional and nonconcessional financial flows from international financial institutions. International financial institutions fund nonconcessional lending operations primarily by selling low-interest, highly rated bonds backed by prudent lending and financial policies and the strong financial support of their members. Funds are then on-lent to developing countries at slightly higher interest rates with 15- to 20-year maturities. Lending terms vary with market conditions and institutional policies. Concessional flows from international financial institutions are credits provided through concessional lending facilities. Subsidies from donors or other resources reduce the cost of these loans. Grants are not included in net flows.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_moth_cd": { "title": "Net financial flows, others (NFL, current US$)", "description_from_producer": "Net financial flows received by the borrower during the year are disbursements of loans and credits less repayments of principal. Others is a residual category in the World Bank's Debtor Reporting System. It includes such institutions as the Caribbean Development Fund, Council of Europe, European Development Fund, Islamic Development Bank, Nordic Development Fund, and the like. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_nifc_cd": { "title": "IFC, private nonguaranteed (NFL, current US$)", "description_from_producer": "Nonguaranteed long-term debt privately placed from the International Finance Corporation (IFC). Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_offt_cd": { "title": "PPG, official creditors (NFL, current US$)", "description_from_producer": "Public and publicly guaranteed debt from official creditors includes loans from international organizations (multilateral loans) and loans from governments (bilateral loans). Loans from international organization include loans and credits from the World Bank, regional development banks, and other multilateral and intergovernmental agencies. Excluded are loans from funds administered by an international organization on behalf of a single donor government; these are classified as loans from governments. Government loans include loans from governments and their agencies (including central banks), loans from autonomous bodies, and direct loans from official export credit agencies. Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_pbnd_cd": { "title": "PPG, bonds (NFL, current US$)", "description_from_producer": "Public and publicly guaranteed debt from bonds that are either publicly issued or privately placed. Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_pcbk_cd": { "title": "PPG, commercial banks (NFL, current US$)", "description_from_producer": "Public and publicly guaranteed commercial bank loans from private banks and other private financial institutions. Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_pcbo_cd": { "title": "Commercial banks and other lending (PPG + PNG) (NFL, current US$)", "description_from_producer": "Commercial bank and other lending includes net commercial bank lending (public and publicly guaranteed and private nonguaranteed) and other private credits. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.\n\nStatistical concept and methodology: Commercial banks include all commercial banks, whether or not publicly owned, that provide loans and other financial services. Private creditors include commercial banks, bondholders, and other private creditors. This indicator includes only publicly guaranteed creditors. Nonguaranteed private creditors are shown separately. Bonds include publicly issued or privately placed bonds. Commercial bank loans are loans from private banks and other private financial institutions. Credits of other private creditors include credits from manufacturers, exporters, and other suppliers of goods, plus bank credits covered by a guarantee of an export credit agency.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_pngb_cd": { "title": "PNG, bonds (NFL, current US$)", "description_from_producer": "Nonguaranteed long-term debt from bonds that are privately placed. Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_pngc_cd": { "title": "PNG, commercial banks and other creditors (NFL, current US$)", "description_from_producer": "Nonguaranteed long-term commercial bank loans from private banks and other private financial institutions. Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_prop_cd": { "title": "PPG, other private creditors (NFL, current US$)", "description_from_producer": "Public and publicly guaranteed other private credits from manufacturers, exporters, and other suppliers of goods, and bank credits covered by a guarantee of an export credit agency. Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_prvt_cd": { "title": "PPG, private creditors (NFL, current US$)", "description_from_producer": "Public and publicly guaranteed debt from private creditors include bonds that are either publicly issued or privately placed; commercial bank loans from private banks and other private financial institutions; and other private credits from manufacturers, exporters, and other suppliers of goods, and bank credits covered by a guarantee of an export credit agency. Net flows (or net lending or net disbursements) received by the borrower during the year are disbursements minus principal repayments. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_rdbc_cd": { "title": "Net financial flows, RDB concessional (NFL, current US$)", "description_from_producer": "Net financial flows received by the borrower during the year are disbursements of loans and credits less repayments of principal. Concessional financial flows cover disbursements made through concessional lending facilities. Regional development banks are the African Development Bank, in Tunis, Tunisia, which serves all of Africa, including North Africa; the Asian Development Bank, in Manila, Philippines, which serves South and Central Asia and East Asia and Pacific; the European Bank for Reconstruction and Development, in London, United Kingdom, which serves Europe and Central Asia; and the Inter-American Development Bank, in Washington, D.C., which serves the Americas. Aggregates include amounts for economies not specified elsewhere. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Regional development banks also maintain concessional windows. Their loans are recorded according to each institution's classification and not according to the Organisation for Economic Co-operation and Development's (OECD) Development Assistance Committee (DAC) definition.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_rdbn_cd": { "title": "Net financial flows, RDB nonconcessional (NFL, current US$)", "description_from_producer": "Net financial flows received by the borrower during the year are disbursements of loans and credits less repayments of principal. Nonconcessional financial flows cover all disbursements except those made through concessional lending facilities. Regional development banks are the African Development Bank, in Tunis, Tunisia, which serves all of Africa, including North Africa; the Asian Development Bank, in Manila, Philippines, which serves South and Central Asia and East Asia and Pacific; the European Bank for Reconstruction and Development, in London, United Kingdom, which serves Europe and Central Asia; and the Inter-American Development Bank, in Washington, D.C., which serves the Americas. Aggregates include amounts for economies not specified elsewhere. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "NFL, current US$", "short_unit": "$" }, "dt_nfl_unai_cd": { "title": "Net official flows from UN agencies, UNAIDS (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_uncf_cd": { "title": "Net official flows from UN agencies, UNICEF (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_uncr_cd": { "title": "Net official flows from UN agencies, UNHCR (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_undp_cd": { "title": "Net official flows from UN agencies, UNDP (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_unec_cd": { "title": "Net official flows from UN agencies, UNECE (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_unep_cd": { "title": "Net official flows from UN agencies, UNEP (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "dt_nfl_unfp_cd": { "title": "Net official flows from UN agencies, UNFPA (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_unid_cd": { "title": "Net official flows from UN agencies, UNIDIR (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "dt_nfl_unpb_cd": { "title": "Net official flows from UN agencies, UNPBF (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_unrw_cd": { "title": "Net official flows from UN agencies, UNRWA (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_unta_cd": { "title": "Net official flows from UN agencies, UNTA (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_unwt_cd": { "title": "Net official flows from UN agencies, UNWTO (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "dt_nfl_wfpg_cd": { "title": "Net official flows from UN agencies, WFP (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_nfl_whol_cd": { "title": "Net official flows from UN agencies, WHO (current US$)", "description_from_producer": "Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children\u2019s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO) and United Nations Institute for Disarmament Research (UNIDIR). Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_oda_alld_cd": { "title": "Net official development assistance and official aid received (current US$)", "description_from_producer": "Net official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Net official aid refers to aid flows (net of repayments) from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_oda_alld_kd": { "title": "Net official development assistance and official aid received (constant 2020 US$)", "description_from_producer": "Net official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Net official aid refers to aid flows (net of repayments) from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. Data are in constant 2020 U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2020 US$", "short_unit": "$" }, "dt_oda_oatl_cd": { "title": "Net official aid received (current US$)", "description_from_producer": "Net official aid refers to aid flows (net of repayments) from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. Data are in current U.S. dollars.\n\nLimitations and exceptions: Data on ODA is for aid-receiving countries. The data cover loans and grants from DAC member countries, multilateral organizations, and non-DAC donors. They do not reflect aid given by recipient countries to other developing countries. As a result, some countries that are net donors are shown as aid recipients. The indicator does not distinguish types of aid (program, project, or food aid; emergency assistance; or post-conflict peacekeeping assistance), which may have different effects on the economy.\n\nBecause the indicator relies on information from donors, it is not necessarily consistent with information recorded by recipients in the balance of payments, which often excludes all or some technical assistance - particularly payments to expatriates made directly by the donor. Similarly, grant commodity aid may not always be recorded in trade data or in the balance of payments. Moreover, DAC statistics exclude aid for military and antiterrorism purposes.\n\nThe nominal values may overstate the real value of aid to recipients. Changes in international prices and exchange rates can reduce the purchasing power of aid. Tying aid, still prevalent though declining in importance, also tends to reduce its purchasing power. Tying requires recipients to purchase goods and services from the donor country or from a specified group of countries. Such arrangements prevent a recipient from misappropriating or mismanaging aid receipts, but they may also be motivated by a desire to benefit donor country suppliers.\n\nThe aggregates refer to World Bank classifications of economies and therefore may differ from those of the OECD.\n\nStatistical concept and methodology: Net official aid refers to aid flows (net of repayments) from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. Data are in current U.S. dollars.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on donor reports on bilateral programs by DAC members using standard questionnaires issued by the DAC Secretariat. DAC has 24 members - 23 individual economies and 1 multilateral institution (European Union institutions).\n\nNet official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of DAC, by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Data are in current U.S. dollars.\n\nTotal net disbursements is the sum of grants, capital subscriptions (deposit basis), recoveries and total net loans and other long-term capital.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nNet official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Data are in current U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_oda_oatl_kd": { "title": "Net official aid received (constant 2020 US$)", "description_from_producer": "Net official aid refers to aid flows (net of repayments) from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. Data are in constant 2020 U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "dt_oda_odat_cd": { "title": "Net official development assistance received (current US$)", "description_from_producer": "Net official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Data are in current U.S. dollars.\n\nLimitations and exceptions: Data on ODA is for aid-receiving countries. The data cover loans and grants from DAC member countries, multilateral organizations, and non-DAC donors. They do not reflect aid given by recipient countries to other developing countries. As a result, some countries that are net donors are shown as aid recipients. The indicator does not distinguish types of aid (program, project, or food aid; emergency assistance; or post-conflict peacekeeping assistance), which may have different effects on the economy.\n\nBecause the indicator relies on information from donors, it is not necessarily consistent with information recorded by recipients in the balance of payments, which often excludes all or some technical assistance - particularly payments to expatriates made directly by the donor. Similarly, grant commodity aid may not always be recorded in trade data or in the balance of payments. Moreover, DAC statistics exclude aid for military and antiterrorism purposes.\n\nThe nominal values may overstate the real value of aid to recipients. Changes in international prices and exchange rates can reduce the purchasing power of aid. Tying aid, still prevalent though declining in importance, also tends to reduce its purchasing power. Tying requires recipients to purchase goods and services from the donor country or from a specified group of countries. Such arrangements prevent a recipient from misappropriating or mismanaging aid receipts, but they may also be motivated by a desire to benefit donor country suppliers.\n\nThe aggregates refer to World Bank classifications of economies and therefore may differ from those of the OECD.\n\nStatistical concept and methodology: The flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on donor reports on bilateral programs by DAC members using standard questionnaires issued by the DAC Secretariat. DAC has 24 members - 23 individual economies and 1 multilateral institution (European Union institutions).\n\nNet official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of DAC, by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Data are in current U.S. dollars.\n\nTotal net disbursements is the sum of grants, capital subscriptions (deposit basis), recoveries and total net loans and other long-term capital.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_oda_odat_gi_zs": { "title": "Net ODA received (% of gross capital formation)", "description_from_producer": "Net official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nLimitations and exceptions: Data on ODA is for aid-receiving countries. The data cover loans and grants from DAC member countries, multilateral organizations, and non-DAC donors. They do not reflect aid given by recipient countries to other developing countries. As a result, some countries that are net donors are shown as aid recipients. The indicator does not distinguish types of aid (program, project, or food aid; emergency assistance; or post-conflict peacekeeping assistance), which may have different effects on the economy.\n\nRatio of aid to gross capital formation provides measures of recipient country's dependency on aid. But care must be taken in drawing policy conclusions. For foreign policy reasons some countries have traditionally received large amounts of aid. Thus aid dependency ratio may reveal as much about a donor's interests as about a recipient's needs. The quality of data on government fixed capital formation depends on the quality of government accounting systems which tend to be weak in developing countries. Measures of fixed capital formation by households and corporations - particularly capital outlays by small, unincorporated enterprises - are usually unreliable. Estimates of changes in inventories are rarely complete but usually include the most important activities of commodities.\n\nBecause the indicator relies on information from donors, it is not necessarily consistent with information recorded by recipients in the balance of payments, which often excludes all or some technical assistance - particularly payments to expatriates made directly by the donor. Similarly, grant commodity aid may not always be recorded in trade data or in the balance of payments. Moreover, DAC statistics exclude aid for military and antiterrorism purposes.\n\nThe aggregates refer to World Bank classifications of economies and therefore may differ from those of the OECD.\n\nStatistical concept and methodology: Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).Gross capital formation consists of outlays on additions to the conomy's fixed assets plus net changes in the level of inventories. It is generally obtained from industry reports of acquisitions and distinguishes only the broad categories of capital formation. Data on capital formation may be estimated from direct surveys of enterprises and administrative records or based on the commodity flow methods using data from production, trade and construction activities.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Net ODA received as a percent of gross capital formation is calculated using values in U.S. dollars converted at official exchange rates.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of gross capital formation", "short_unit": "%" }, "dt_oda_odat_gn_zs": { "title": "Net ODA received (% of GNI)", "description_from_producer": "Net official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nLimitations and exceptions: Data on ODA is for aid-receiving countries. The data cover loans and grants from DAC member countries, multilateral organizations, and non-DAC donors. They do not reflect aid given by recipient countries to other developing countries. As a result, some countries that are net donors are shown as aid recipients. The indicator does not distinguish types of aid (program, project, or food aid; emergency assistance; or post-conflict peacekeeping assistance), which may have different effects on the economy.\n\nRatio of aid to gross national income (GNI) provides measures of recipient country's dependency on aid. But care must be taken in drawing policy conclusions. For foreign policy reasons some countries have traditionally received large amounts of aid. Thus aid dependency ratio may reveal as much about a donor's interests as about a recipient's needs.\n\nBecause the indicator relies on information from donors, it is not necessarily consistent with information recorded by recipients in the balance of payments, which often excludes all or some technical assistance - particularly payments to expatriates made directly by the donor. Similarly, grant commodity aid may not always be recorded in trade data or in the balance of payments. Moreover, DAC statistics exclude aid for military and antiterrorism purposes.\n\nThe aggregates refer to World Bank classifications of economies and therefore may differ from those of the OECD.\n\nStatistical concept and methodology: The ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Net ODA received as a percent of GNI is calculated using values in U.S. dollars converted at official exchange rates.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "dt_oda_odat_kd": { "title": "Net official development assistance received (constant 2020 US$)", "description_from_producer": "Net official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Data are in constant 2020 U.S. dollars.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "dt_oda_odat_mp_zs": { "title": "Net ODA received (% of imports of goods, services and primary income)", "description_from_producer": "Net official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nLimitations and exceptions: Data on ODA is for aid-receiving countries. The data cover loans and grants from DAC member countries, multilateral organizations, and non-DAC donors. They do not reflect aid given by recipient countries to other developing countries. As a result, some countries that are net donors are shown as aid recipients. The indicator does not distinguish types of aid (program, project, or food aid; emergency assistance; or post-conflict peacekeeping assistance), which may have different effects on the economy.\n\nRatio of aid to imports of goods and services provides measures of recipient country's dependency on aid. But care must be taken in drawing policy conclusions. For foreign policy reasons some countries have traditionally received large amounts of aid. Thus aid dependency ratio may reveal as much about a donor's interests as about a recipient's needs. Data on imports are compiled from customs reports and balance of payments data. Although data from the payments side provide reasonably reliable records of cross-border transactions, they may not adhere strictly to the appropriate definitions of valuation and timing used in the balance of payments or correspond to the change of ownership criterion. This issue has assumed greater significance with the increasing globalization of international business. Neither customs nor balance of payments data usually capture the illegal transactions that occur in many countries. Goods carried by travelers across borders in league but unreported shuttle trade may further distort trade statistics.\n\nBecause the indicator relies on information from donors, it is not necessarily consistent with information recorded by recipients in the balance of payments, which often excludes all or some technical assistance - particularly payments to expatriates made directly by the donor. Similarly, grant commodity aid may not always be recorded in trade data or in the balance of payments. Moreover, DAC statistics exclude aid for military and antiterrorism purposes.\n\nThe aggregates refer to World Bank classifications of economies and therefore may differ from those of the OECD.\n\nStatistical concept and methodology: Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nData on imports are compiled from customs reports and balance of payments data. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services. They exclude compensation of employees and investment income (factor services in the 1969 SNA) and transfer payments.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Net ODA received as a percent of imports of goods and services is calculated using values in U.S. dollars converted at official exchange rates.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of imports of goods, services and primary income", "short_unit": "%" }, "dt_oda_odat_pc_zs": { "title": "Net ODA received per capita (current US$)", "description_from_producer": "Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients; and is calculated by dividing net ODA received by the midyear population estimate. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nLimitations and exceptions: Data on ODA is for aid-receiving countries. The data cover loans and grants from DAC member countries, multilateral organizations, and non-DAC donors. They do not reflect aid given by recipient countries to other developing countries. As a result, some countries that are net donors are shown as aid recipients. The indicator does not distinguish types of aid (program, project, or food aid; emergency assistance; or post-conflict peacekeeping assistance), which may have different effects on the economy.\n\nBecause the indicator relies on information from donors, it is not necessarily consistent with information recorded by recipients in the balance of payments, which often excludes all or some technical assistance - particularly payments to expatriates made directly by the donor. Similarly, grant commodity aid may not always be recorded in trade data or in the balance of payments. Moreover, DAC statistics exclude aid for military and antiterrorism purposes.\n\nThe aggregates refer to World Bank classifications of economies and therefore may differ from those of the OECD.\n\nStatistical concept and methodology: Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nTotal population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship - except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. The values shown are midyear estimates. Net official development assistance per capita is net ODA divided by midyear population.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nThis definition excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "dt_oda_odat_xp_zs": { "title": "Net ODA received (% of central government expense)", "description_from_producer": "Net official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nLimitations and exceptions: Data on ODA is for aid-receiving countries. The data cover loans and grants from DAC member countries, multilateral organizations, and non-DAC donors. They do not reflect aid given by recipient countries to other developing countries. As a result, some countries that are net donors are shown as aid recipients. The indicator does not distinguish types of aid (program, project, or food aid; emergency assistance; or post-conflict peacekeeping assistance), which may have different effects on the economy.\n\nRatio of aid to central government expense provides measures of recipient country's dependency on aid. But care must be taken in drawing policy conclusions. For foreign policy reasons some countries have traditionally received large amounts of aid. Thus aid dependency ratio may reveal as much about a donor's interests as about a recipient's needs.\n\nThe nominal values used here may overstate the real value of aid to recipients. Changes in international prices and exchange rates can reduce the purchasing power of aid. Tying aid, still prevalent though declining in importance, also tends to reduce its purchasing power. Tying requires recipients to purchase goods and services from the donor country or from a specified group of countries. Such arrangements prevent a recipient from misappropriating or mismanaging aid receipts, but they may also be motivated by a desire to benefit donor country suppliers.\n\nBecause the indicator relies on information from donors, it is not necessarily consistent with information recorded by recipients in the balance of payments, which often excludes all or some technical assistance - particularly payments to expatriates made directly by the donor. Similarly, grant commodity aid may not always be recorded in trade data or in the balance of payments. Moreover, DAC statistics exclude aid for military and antiterrorism purposes.\n\nThe aggregates refer to World Bank classifications of economies and therefore may differ from those of the OECD.\n\nStatistical concept and methodology: Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nCentral government expense is cash payments for operating activities of the government in providing goods and services. It includes compensation of employees (such as wages and salaries), interest and subsidies, grants, social benefits, and other expenses such as rent and dividends.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Net ODA received as a percent of central government expense is calculated using values in U.S. dollars converted using the DEC alternative conversion factor which is the underlying annual exchange rate used for the World Bank Atlas method.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of central government expense", "short_unit": "%" }, "dt_tds_dect_cd": { "title": "Debt service on external debt, total (TDS, current US$)", "description_from_producer": "Total debt service is the sum of principal repayments and interest actually paid in currency, goods, or services on long-term debt, interest paid on short-term debt, and repayments (repurchases and charges) to the IMF. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "TDS, current US$", "short_unit": "$" }, "dt_tds_dect_ex_zs": { "title": "Total debt service (% of exports of goods, services and primary income)", "description_from_producer": "Total debt service to exports of goods, services and primary income. Total debt service is the sum of principal repayments and interest actually paid in currency, goods, or services on long-term debt, interest paid on short-term debt, and repayments (repurchases and charges) to the IMF.\n\nStatistical concept and methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of exports of goods, services and primary income", "short_unit": "%" }, "dt_tds_dect_gn_zs": { "title": "Total debt service (% of GNI)", "description_from_producer": "Total debt service is the sum of principal repayments and interest actually paid in currency, goods, or services on long-term debt, interest paid on short-term debt, and repayments (repurchases and charges) to the IMF.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "dt_tds_dimf_cd": { "title": "IMF repurchases and charges (TDS, current US$)", "description_from_producer": "IMF repurchases are total repayments of outstanding drawings from the General Resources Account during the year specified, excluding repayments due in the reserve tranche. IMF charges cover interest payments with respect to all uses of IMF resources, excluding those resulting from drawings in the reserve tranche. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "TDS, current US$", "short_unit": "$" }, "dt_tds_dppf_xp_zs": { "title": "Debt service to exports (%)", "description_from_producer": "Debt service, the sum of principal repayments and interest actually paid in currency, goods, or services, is expressed as a percentage of exports of goods and services--all transactions between residents of a country and the rest of the world involving a change of ownership from residents to nonresidents of general merchandise, net exports of goods under merchanting, nonmonetary gold, and services. This series differs from the standard debt to exports series in that it covers only long-term public and publicly guaranteed debt and repayments (repurchases and charges) to the IMF.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "dt_tds_dppg_cd": { "title": "Debt service on external debt, public and publicly guaranteed (PPG) (TDS, current US$)", "description_from_producer": "Public and publicly guaranteed debt service is the sum of principal repayments and interest actually paid in currency, goods, or services on long-term obligations of public debtors and long-term private obligations guaranteed by a public entity. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "TDS, current US$", "short_unit": "$" }, "dt_tds_dppg_gn_zs": { "title": "Public and publicly guaranteed debt service (% of GNI)", "description_from_producer": "Public and publicly guaranteed debt service is the sum of principal repayments and interest actually paid in currency, goods, or services on long-term obligations of public debtors and long-term private obligations guaranteed by a public entity.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "dt_tds_dppg_xp_zs": { "title": "Public and publicly guaranteed debt service (% of exports of goods, services and primary income)", "description_from_producer": "Public and publicly guaranteed debt service is the sum of principal repayments and interest actually paid in currency, goods, or services on long-term obligations of public debtors and long-term private obligations guaranteed by a public entity. Exports refer to exports of goods, services, and income.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of exports of goods, services and primary income", "short_unit": "%" }, "dt_tds_mlat_cd": { "title": "Multilateral debt service (TDS, current US$)", "description_from_producer": "Public and publicly guaranteed multilateral loans include loans and credits from the World Bank, regional development banks, and other multilateral and intergovernmental agencies. Excluded are loans from funds administered by an international organization on behalf of a single donor government; these are classified as loans from governments. Debt service payments are the sum of principal repayments and interest payments actually made in the year specified. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "TDS, current US$", "short_unit": "$" }, "dt_tds_mlat_pg_zs": { "title": "Multilateral debt service (% of public and publicly guaranteed debt service)", "description_from_producer": "Multilateral debt service is the repayment of principal and interest to the World Bank, regional development banks, and other multilateral agencies. public and publicly guaranteed debt service is the sum of principal repayments and interest actually paid in currency, goods, or services on long-term obligations of public debtors and long-term private obligations guaranteed by a public entity.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of public and publicly guaranteed debt service", "short_unit": "%" }, "eg_cft_accs_ru_zs": { "title": "Access to clean fuels and technologies for cooking, rural (% of rural population)", "description_from_producer": "Access to clean fuels and technologies for cooking, rural is the proportion of rural population primarily using clean cooking fuels and technologies for cooking. Under WHO guidelines, kerosene is excluded from clean cooking fuels.\n\nStatistical concept and methodology: Data for access to clean fuels and technologies for cooking are based on the World Health Organization\u2019s (WHO) Global Household Energy Database. They are collected among different sources: only data from nationally representative household surveys (including national censuses) were used. Survey sources include Demographic and Health Surveys (DHS) and Living Standards Measurement Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), the World Health Survey (WHS), other nationally developed and implemented surveys, and various government agencies (for example, ministries of energy and utilities). Trends in the proportion of the population using each fuel type are estimated using a single multivariate hierarchical model, with urban and rural disaggregation. Estimates for overall \u2018polluting\u2019 fuels (unprocessed biomass, charcoal, coal, and kerosene) and \u2018clean\u2019 fuels (gaseous fuels, electricity, as well as an aggregation of any other clean fuels like alcohol) are produced by aggregating estimates of relevant fuel types. The model was used to derive clean fuel use estimates for 191 countries (ref. Stoner, O., Shaddick, G., Economou, T., Gumy, S., Lewis, J., Lucio, I., Ruggeri, G. and Adair-Rohani, H. (2020), Global household energy model: a multivariate hierarchical approach to estimating trends in the use of polluting and clean fuels for cooking. J. R. Stat. Soc. C, 69: 815-839). Countries classified by the World Bank as high income (57 countries) in the 2022 fiscal year are assumed to have universal access to clean fuels and technologies for cooking.", "origins": [ { "producer": "World Bank and International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "eg_cft_accs_ur_zs": { "title": "Access to clean fuels and technologies for cooking, urban (% of urban population)", "description_from_producer": "Access to clean fuels and technologies for cooking, urban is the proportion of urban population primarily using clean cooking fuels and technologies for cooking. Under WHO guidelines, kerosene is excluded from clean cooking fuels.\n\nStatistical concept and methodology: Data for access to clean fuels and technologies for cooking are based on the World Health Organization\u2019s (WHO) Global Household Energy Database. They are collected among different sources: only data from nationally representative household surveys (including national censuses) were used. Survey sources include Demographic and Health Surveys (DHS) and Living Standards Measurement Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), the World Health Survey (WHS), other nationally developed and implemented surveys, and various government agencies (for example, ministries of energy and utilities). Trends in the proportion of the population using each fuel type are estimated using a single multivariate hierarchical model, with urban and rural disaggregation. Estimates for overall \u2018polluting\u2019 fuels (unprocessed biomass, charcoal, coal, and kerosene) and \u2018clean\u2019 fuels (gaseous fuels, electricity, as well as an aggregation of any other clean fuels like alcohol) are produced by aggregating estimates of relevant fuel types. The model was used to derive clean fuel use estimates for 191 countries (ref. Stoner, O., Shaddick, G., Economou, T., Gumy, S., Lewis, J., Lucio, I., Ruggeri, G. and Adair-Rohani, H. (2020), Global household energy model: a multivariate hierarchical approach to estimating trends in the use of polluting and clean fuels for cooking. J. R. Stat. Soc. C, 69: 815-839). Countries classified by the World Bank as high income (57 countries) in the 2022 fiscal year are assumed to have universal access to clean fuels and technologies for cooking.", "origins": [ { "producer": "World Bank and International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "eg_cft_accs_zs": { "title": "Access to clean fuels and technologies for cooking (% of population)", "description_from_producer": "Access to clean fuels and technologies for cooking is the proportion of total population primarily using clean cooking fuels and technologies for cooking. Under WHO guidelines, kerosene is excluded from clean cooking fuels.\n\nStatistical concept and methodology: Data for access to clean fuels and technologies for cooking are based on the World Health Organization\u2019s (WHO) Global Household Energy Database. They are collected among different sources: only data from nationally representative household surveys (including national censuses) were used. Survey sources include Demographic and Health Surveys (DHS) and Living Standards Measurement Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), the World Health Survey (WHS), other nationally developed and implemented surveys, and various government agencies (for example, ministries of energy and utilities). Trends in the proportion of the population using each fuel type are estimated using a single multivariate hierarchical model, with urban and rural disaggregation. Estimates for overall \u2018polluting\u2019 fuels (unprocessed biomass, charcoal, coal, and kerosene) and \u2018clean\u2019 fuels (gaseous fuels, electricity, as well as an aggregation of any other clean fuels like alcohol) are produced by aggregating estimates of relevant fuel types. The model was used to derive clean fuel use estimates for 191 countries (ref. Stoner, O., Shaddick, G., Economou, T., Gumy, S., Lewis, J., Lucio, I., Ruggeri, G. and Adair-Rohani, H. (2020), Global household energy model: a multivariate hierarchical approach to estimating trends in the use of polluting and clean fuels for cooking. J. R. Stat. Soc. C, 69: 815-839). Countries classified by the World Bank as high income (57 countries) in the 2022 fiscal year are assumed to have universal access to clean fuels and technologies for cooking.", "origins": [ { "producer": "World Bank and International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%", "display": { "name": "Access to clean fuels and technologies for cooking" }, "presentation": { "title_public": "Share of population with access to clean fuels and technologies for cooking" } }, "eg_egy_prim_pp_kd": { "title": "Energy intensity level of primary energy (MJ/$2017 PPP GDP)", "description_from_producer": "Energy intensity level of primary energy is the ratio between energy supply and gross domestic product measured at purchasing power parity. Energy intensity is an indication of how much energy is used to produce one unit of economic output. Lower ratio indicates that less energy is used to produce one unit of output.\n\nLimitations and exceptions: Energy intensity level is only an imperfect proxy to energy efficiency indicator and it can be affected by a number of factors not necessarily linked to pure efficiency such as climate.\n\nStatistical concept and methodology: This indicator is obtained by dividing total primary energy supply over gross domestic product measured in constant 2017 US dollars at purchasing power parity.", "origins": [ { "producer": "World Bank and International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "eg_elc_accs_ru_zs": { "title": "Access to electricity, rural (% of rural population)", "description_from_producer": "Access to electricity, rural is the percentage of rural population with access to electricity.\n\nStatistical concept and methodology: The World Bank\u2019s Global Electrification Database (GED) compiles nationally representative household survey data, and occasionally census data, from sources going back as far as 1990. The database also incorporates data from the Socio-Economic Database for Latin America and the Caribbean (SEDLAC), Middle East and North Africa Poverty Database (MNAPOV) and the Europe and Central Asia Poverty Database (ECAPOV), which are based on similar surveys. At the time of this analysis, the GED contained 1,375 surveys for 149 countries in 1990-2021.", "origins": [ { "producer": "World Bank and International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of rural population", "short_unit": "%" }, "eg_elc_accs_ur_zs": { "title": "Access to electricity, urban (% of urban population)", "description_from_producer": "Access to electricity, urban is the percentage of urban population with access to electricity.\n\nStatistical concept and methodology: The World Bank\u2019s Global Electrification Database (GED) compiles nationally representative household survey data, and occasionally census data, from sources going back as far as 1990. The database also incorporates data from the Socio-Economic Database for Latin America and the Caribbean (SEDLAC), Middle East and North Africa Poverty Database (MNAPOV) and the Europe and Central Asia Poverty Database (ECAPOV), which are based on similar surveys. At the time of this analysis, the GED contained 1,375 surveys for 149 countries in 1990-2021.", "origins": [ { "producer": "World Bank and International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of urban population", "short_unit": "%" }, "eg_elc_accs_zs": { "title": "Access to electricity (% of population)", "description_from_producer": "Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.\n\nStatistical concept and methodology: The World Bank\u2019s Global Electrification Database (GED) compiles nationally representative household survey data, and occasionally census data, from sources going back as far as 1990. The database also incorporates data from the Socio-Economic Database for Latin America and the Caribbean (SEDLAC), Middle East and North Africa Poverty Database (MNAPOV) and the Europe and Central Asia Poverty Database (ECAPOV), which are based on similar surveys. At the time of this analysis, the GED contained 1,375 surveys for 149 countries in 1990-2021.", "origins": [ { "producer": "World Bank and International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "eg_elc_coal_zs": { "title": "Electricity production from coal sources (% of total)", "description_from_producer": "Sources of electricity refer to the inputs used to generate electricity. Coal refers to all coal and brown coal, both primary (including hard coal and lignite-brown coal) and derived fuels (including patent fuel, coke oven coke, gas coke, coke oven gas, and blast furnace gas). Peat is also included in this category.\n\nLimitations and exceptions: IEA occasionally revises its time series to reflect political changes. For example, the IEA has constructed historical energy statistics for countries of the former Soviet Union. In addition, energy statistics for other countries have undergone continuous changes in coverage or methodology in recent years as more detailed energy accounts have become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Electricity production is total number of kWh generated by power plants separated into electricity plants and CHP plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%", "display": { "name": "Coal" }, "presentation": { "title_public": "Share of total electricity production from coal" } }, "eg_elc_fosl_zs": { "title": "Electricity production from oil, gas and coal sources (% of total)", "description_from_producer": "Sources of electricity refer to the inputs used to generate electricity. Oil refers to crude oil and petroleum products. Gas refers to natural gas but excludes natural gas liquids. Coal refers to all coal and brown coal, both primary (including hard coal and lignite-brown coal) and derived fuels (including patent fuel, coke oven coke, gas coke, coke oven gas, and blast furnace gas). Peat is also included in this category.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "eg_elc_hyro_zs": { "title": "Electricity production from hydroelectric sources (% of total)", "description_from_producer": "Sources of electricity refer to the inputs used to generate electricity. Hydropower refers to electricity produced by hydroelectric power plants.\n\nLimitations and exceptions: IEA occasionally revises its time series to reflect political changes. For example, the IEA has constructed historical energy statistics for countries of the former Soviet Union. In addition, energy statistics for other countries have undergone continuous changes in coverage or methodology in recent years as more detailed energy accounts have become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Electricity production is total number of kWh generated by power plants separated into electricity plants and CHP plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "eg_elc_loss_zs": { "title": "Electric power transmission and distribution losses (% of output)", "description_from_producer": "Electric power transmission and distribution losses include losses in transmission between sources of supply and points of distribution and in the distribution to consumers, including pilferage.\n\nLimitations and exceptions: Electricity consumption is equivalent to production less power plants' own use and transmission, distribution, and transformation losses less exports plus imports. It includes consumption by auxiliary stations, losses in transformers that are considered integral parts of those stations, and electricity produced by pumping installations. Where data are available, it covers electricity generated by primary sources of energy - coal, oil, gas, nuclear, hydro, geothermal, wind, tide and wave, and combustible renewables. Neither production nor consumption data capture the reliability of supplies, including breakdowns, load factors, and frequency of outages.\n\nStatistical concept and methodology: Data on electric power production and consumption are collected from national energy agencies by the International Energy Agency (IEA) and adjusted by the IEA to meet international definitions. Electric power transmission and distribution losses percentage of output is the share of electric power transmission and distribution losses to electricity production which is the total number of GWh generated by power plants separated into electricity plants and CHP plants.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of output", "short_unit": "%" }, "eg_elc_ngas_zs": { "title": "Electricity production from natural gas sources (% of total)", "description_from_producer": "Sources of electricity refer to the inputs used to generate electricity. Gas refers to natural gas but excludes natural gas liquids.\n\nLimitations and exceptions: IEA occasionally revises its time series to reflect political changes. For example, the IEA has constructed historical energy statistics for countries of the former Soviet Union. In addition, energy statistics for other countries have undergone continuous changes in coverage or methodology in recent years as more detailed energy accounts have become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Electricity production from natural gas sources (% of total) is the share of natutal gas, which is natural gas but not natural gas liquids, in total electricity production which is the total number of GWh generated by power plants separated into electricity plants and CHP plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "eg_elc_nucl_zs": { "title": "Electricity production from nuclear sources (% of total)", "description_from_producer": "Sources of electricity refer to the inputs used to generate electricity. Nuclear power refers to electricity produced by nuclear power plants.\n\nLimitations and exceptions: IEA occasionally revises its time series to reflect political changes. For example, the IEA has constructed historical energy statistics for countries of the former Soviet Union. In addition, energy statistics for other countries have undergone continuous changes in coverage or methodology in recent years as more detailed energy accounts have become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Electricity production from nuclear sources (% of total) is the share of electricity produced by nuclear power plants in total electricity production which is the total number of GWh generated by power plants separated into electricity plants and CHP plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "eg_elc_petr_zs": { "title": "Electricity production from oil sources (% of total)", "description_from_producer": "Sources of electricity refer to the inputs used to generate electricity. Oil refers to crude oil and petroleum products.\n\nLimitations and exceptions: IEA occasionally revises its time series to reflect political changes. For example, the IEA has constructed historical energy statistics for countries of the former Soviet Union. In addition, energy statistics for other countries have undergone continuous changes in coverage or methodology in recent years as more detailed energy accounts have become available. Breaks in series are therefore unavoidable.\n\nData on access to electricity are collected by the IEA from industry, national surveys, and international sources.\n\nStatistical concept and methodology: Electricity production from oil sources (% of total) is the share of electricity produced by oil and petroleum products in total electricity production which is the total number of GWh generated by power plants separated into electricity plants and CHP plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "eg_elc_rnew_zs": { "title": "Renewable electricity output (% of total electricity output)", "description_from_producer": "Renewable electricity is the share of electrity generated by renewable power plants in total electricity generated by all types of plants.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total electricity output", "short_unit": "%" }, "eg_elc_rnwx_kh": { "title": "Electricity production from renewable sources, excluding hydroelectric (kWh)", "description_from_producer": "Electricity production from renewable sources, excluding hydroelectric, includes geothermal, solar, tides, wind, biomass, and biofuels.\n\nLimitations and exceptions: IEA occasionally revises its time series to reflect political changes. For example, the IEA has constructed historical energy statistics for countries of the former Soviet Union. In addition, energy statistics for other countries have undergone continuous changes in coverage or methodology in recent years as more detailed energy accounts have become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Electricity production from renewable sources (% of total) is the share of electricity produced by geothermal, solar photovoltaic, solar thermal, tide, wind, industrial waste, municipal waste, primary solid biofuels, biogases, biogasoline, biodiesels, other liquid biofuels, nonspecified primary biofuels and waste, and charcoal in total electricity production which is the total number of GWh generated by power plants separated into electricity plants and CHP plants. Hydropower is excluded. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kWh", "short_unit": "kWh" }, "eg_elc_rnwx_zs": { "title": "Electricity production from renewable sources, excluding hydroelectric (% of total)", "description_from_producer": "Electricity production from renewable sources, excluding hydroelectric, includes geothermal, solar, tides, wind, biomass, and biofuels.\n\nLimitations and exceptions: IEA occasionally revises its time series to reflect political changes. For example, the IEA has constructed historical energy statistics for countries of the former Soviet Union. In addition, energy statistics for other countries have undergone continuous changes in coverage or methodology in recent years as more detailed energy accounts have become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Electricity production from renewable sources (% of total) is the share of electricity produced by geothermal, solar photovoltaic, solar thermal, tide, wind, industrial waste, municipal waste, primary solid biofuels, biogases, biogasoline, biodiesels, other liquid biofuels, nonspecified primary biofuels and waste, and charcoal in total electricity production which is the total number of GWh generated by power plants separated into electricity plants and CHP plants. Hydropower is excluded. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "eg_fec_rnew_zs": { "title": "Renewable energy consumption (% of total final energy consumption)", "description_from_producer": "Renewable energy consumption is the share of renewables energy in total final energy consumption.", "origins": [ { "producer": "World Bank and International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total final energy consumption", "short_unit": "%" }, "eg_gdp_puse_ko_pp": { "title": "GDP per unit of energy use (PPP $ per kg of oil equivalent)", "description_from_producer": "GDP per unit of energy use is the PPP GDP per kilogram of oil equivalent of energy use. PPP GDP is gross domestic product converted to current international dollars using purchasing power parity rates based on the 2017 ICP round. An international dollar has the same purchasing power over GDP as a U.S. dollar has in the United States.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "PPP $ per kg of oil equivalent", "short_unit": "$" }, "eg_gdp_puse_ko_pp_kd": { "title": "GDP per unit of energy use (constant 2017 PPP $ per kg of oil equivalent)", "description_from_producer": "GDP per unit of energy use is the PPP GDP per kilogram of oil equivalent of energy use. PPP GDP is gross domestic product converted to 2017 constant international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as a U.S. dollar has in the United States.\n\nLimitations and exceptions: The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts. The IEA occasionally revises its time series to reflect political changes, and energy statistics undergo continual changes in coverage or methodology as more detailed energy accounts become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: The ratio of gross domestic product (GDP) to energy use indicates energy efficiency. To produce comparable and consistent estimates of real GDP across economies relative to physical inputs to GDP - that is, units of energy use - GDP is converted to 2017 international dollars using purchasing power parity (PPP) rates. Differences in this ratio over time and across economies reflect structural changes in an economy, changes in sectoral energy efficiency, and differences in fuel mixes. Total energy use refers to the use of primary energy before transformation to other end-use fuels (such as electricity and refined petroleum products). It includes energy from combustible renewables and waste - solid biomass and animal products, gas and liquid from biomass, and industrial and municipal waste. Biomass is any plant matter used directly as fuel or converted into fuel, heat, or electricity. Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. GDP data are from World Bank's national accounts files.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2017 PPP $ per kg of oil equivalent", "short_unit": "$" }, "eg_imp_cons_zs": { "title": "Energy imports, net (% of energy use)", "description_from_producer": "Net energy imports are estimated as energy use less production, both measured in oil equivalents. A negative value indicates that the country is a net exporter. Energy use refers to use of primary energy before transformation to other end-use fuels, which is equal to indigenous production plus imports and stock changes, minus exports and fuels supplied to ships and aircraft engaged in international transport.\n\nLimitations and exceptions: The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts. The IEA occasionally revises its time series to reflect political changes, and energy statistics undergo continual changes in coverage or methodology as more detailed energy accounts become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments.\n\nA negative value in energy imports indicates that the country is a net exporter. Energy use refers to use of primary energy before transformation to other end-use fuels, which is equal to indigenous production plus imports and stock changes, minus exports and fuels supplied to ships and aircraft engaged in international transport.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of energy use", "short_unit": "%" }, "eg_use_comm_cl_zs": { "title": "Alternative and nuclear energy (% of total energy use)", "description_from_producer": "Clean energy is noncarbohydrate energy that does not produce carbon dioxide when generated. It includes hydropower and nuclear, geothermal, and solar power, among others.\n\nLimitations and exceptions: The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts. The IEA occasionally revises its time series to reflect political changes, and energy statistics undergo continual changes in coverage or methodology as more detailed energy accounts become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total energy use", "short_unit": "%" }, "eg_use_comm_fo_zs": { "title": "Fossil fuel energy consumption (% of total)", "description_from_producer": "Fossil fuel comprises coal, oil, petroleum, and natural gas products.\n\nLimitations and exceptions: The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts. The IEA occasionally revises its time series to reflect political changes, and energy statistics undergo continual changes in coverage or methodology as more detailed energy accounts become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments.\n\nData for combustible renewables and waste are often based on small surveys or other incomplete information and thus give only a broad impression of developments and are not strictly comparable across countries. The IEA reports include country notes that explain some of these differences. All forms of energy - primary energy and primary electricity - are converted into oil equivalents. A notional thermal efficiency of 33 percent is assumed for converting nuclear electricity into oil equivalents and 100 percent efficiency for converting hydroelectric power.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "eg_use_comm_gd_pp_kd": { "title": "Energy use (kg of oil equivalent) per $1,000 GDP (constant 2017 PPP)", "description_from_producer": "Energy use per PPP GDP is the kilogram of oil equivalent of energy use per constant PPP GDP. Energy use refers to use of primary energy before transformation to other end-use fuels, which is equal to indigenous production plus imports and stock changes, minus exports and fuels supplied to ships and aircraft engaged in international transport. PPP GDP is gross domestic product converted to 2017 constant international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as a U.S. dollar has in the United States.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2017 PPP" }, "eg_use_crnw_zs": { "title": "Combustible renewables and waste (% of total energy)", "description_from_producer": "Combustible renewables and waste comprise solid biomass, liquid biomass, biogas, industrial waste, and municipal waste, measured as a percentage of total energy use.\n\nLimitations and exceptions: The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts. The IEA occasionally revises its time series to reflect political changes, and energy statistics undergo continual changes in coverage or methodology as more detailed energy accounts become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments.\n\nData for combustible renewables and waste are often based on small surveys or other incomplete information and thus give only a broad impression of developments and are not strictly comparable across countries. The IEA reports include country notes that explain some of these differences. All forms of energy - primary energy and primary electricity - are converted into oil equivalents. A notional thermal efficiency of 33 percent is assumed for converting nuclear electricity into oil equivalents and 100 percent efficiency for converting hydroelectric power.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total energy", "short_unit": "%" }, "eg_use_elec_kh_pc": { "title": "Electric power consumption (kWh per capita)", "description_from_producer": "Electric power consumption measures the production of power plants and combined heat and power plants less transmission, distribution, and transformation losses and own use by heat and power plants.\n\nLimitations and exceptions: Data on electric power production and consumption are collected from national energy agencies by the International Energy Agency (IEA) and adjusted by the IEA to meet international definitions. Data are reported as net consumption as opposed to gross consumption. Net consumption excludes the energy consumed by the generating units. For all countries except the United States, total electric power consumption is equal total net electricity generation plus electricity imports minus electricity exports minus electricity distribution losses.\n\nThe IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts. The IEA occasionally revises its time series to reflect political changes, and energy statistics undergo continual changes in coverage or methodology as more detailed energy accounts become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Electric power consumption per capita (kWh ) is the production of power plants and combined heat and power plants less transmission, distribution, and transformation losses and own use by heat and power plants, divided by midyear population. Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. Electricity consumption is equivalent to production less power plants' own use and transmission, distribution, and transformation losses less exports plus imports. It includes consumption by auxiliary stations, losses in transformers that are considered integral parts of those stations, and electricity produced by pumping installations. Where data are available, it covers electricity generated by primary sources of energy - coal, oil, gas, nuclear, hydro, geothermal, wind, tide and wave, and combustible renewables. Neither production nor consumption data capture the reliability of supplies, including breakdowns, load factors, and frequency of outages.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kWh per capita", "short_unit": "kWh" }, "eg_use_pcap_kg_oe": { "title": "Energy use (kg of oil equivalent per capita)", "description_from_producer": "Energy use refers to use of primary energy before transformation to other end-use fuels, which is equal to indigenous production plus imports and stock changes, minus exports and fuels supplied to ships and aircraft engaged in international transport.\n\nLimitations and exceptions: The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts. The IEA occasionally revises its time series to reflect political changes, and energy statistics undergo continual changes in coverage or methodology as more detailed energy accounts become available. Breaks in series are therefore unavoidable.\n\nStatistical concept and methodology: Total energy use refers to the use of primary energy before transformation to other end-use fuels (such as electricity and refined petroleum products). It includes energy from combustible renewables and waste - solid biomass and animal products, gas and liquid from biomass, and industrial and municipal waste. Biomass is any plant matter used directly as fuel or converted into fuel, heat, or electricity. World Bank population estimates are used to calculate per capita data.\n\nEnergy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments.\n\nData for combustible renewables and waste are often based on small surveys or other incomplete information and thus give only a broad impression of developments and are not strictly comparable across countries. The IEA reports include country notes that explain some of these differences. All forms of energy - primary energy and primary electricity - are converted into oil equivalents. A notional thermal efficiency of 33 percent is assumed for converting nuclear electricity into oil equivalents and 100 percent efficiency for converting hydroelectric power.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kg of oil equivalent per capita", "short_unit": "kg of oil equivalent" }, "en_atm_co2e_eg_zs": { "title": "CO2 intensity (kg per kg of oil equivalent energy use)", "description_from_producer": "Carbon dioxide emissions from solid fuel consumption refer mainly to emissions from use of coal as an energy source.\n\nLimitations and exceptions: The U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) calculates annual anthropogenic emissions from data on fossil fuel consumption (from the United Nations Statistics Division's World Energy Data Set) and world cement manufacturing (from the U.S. Department of Interior's Geological Survey, USGS 2011). Although estimates of global carbon dioxide emissions are probably accurate within 10 percent (as calculated from global average fuel chemistry and use), country estimates may have larger error bounds. Trends estimated from a consistent time series tend to be more accurate than individual values.\n\nEach year the CDIAC recalculates the entire time series since 1949, incorporating recent findings and corrections. Estimates exclude fuels supplied to ships and aircraft in international transport because of the difficulty of apportioning the fuels among benefiting countries.\n\nData for carbon dioxide emissions include gases from the burning of fossil fuels and cement manufacture, but excludes emissions from land use such as deforestation.\n\nStatistical concept and methodology: Carbon intensity is the ratio of carbon dioxide per unit of energy, or the amount of carbon dioxide emitted as a result of using one unit of energy in production. Emission intensities are also used to compare the environmental impact of different fuels or activities. The related terms - emission factor and carbon intensity - are often used interchangeably.\n\nCarbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced. Carbon dioxide emissions are often calculated and reported as elemental carbon. The values were converted to actual carbon dioxide mass by multiplying them by 3.667 (the ratio of the mass of carbon to that of carbon dioxide).", "origins": [ { "producer": "Carbon Dioxide Information Analysis Center (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kg per kg of oil equivalent energy use", "short_unit": "kg" }, "en_atm_co2e_gf_kt": { "title": "CO2 emissions from gaseous fuel consumption (kt)", "description_from_producer": "Carbon dioxide emissions from liquid fuel consumption refer mainly to emissions from use of natural gas as an energy source.\n\nLimitations and exceptions: The U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) calculates annual anthropogenic emissions from data on fossil fuel consumption (from the United Nations Statistics Division's World Energy Data Set) and world cement manufacturing (from the U.S. Department of Interior's Geological Survey, USGS 2011). Although estimates of global carbon dioxide emissions are probably accurate within 10 percent (as calculated from global average fuel chemistry and use), country estimates may have larger error bounds. Trends estimated from a consistent time series tend to be more accurate than individual values.\n\nEach year the CDIAC recalculates the entire time series since 1949, incorporating recent findings and corrections. Estimates exclude fuels supplied to ships and aircraft in international transport because of the difficulty of apportioning the fuels among benefiting countries.\n\nStatistical concept and methodology: Carbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced. Data for carbon dioxide emissions include gases from the burning of fossil fuels and cement manufacture, but excludes emissions from land use such as deforestation. Carbon dioxide emissions are often calculated and reported as elemental carbon. The values were converted to actual carbon dioxide mass by multiplying them by 3.667 (the ratio of the mass of carbon to that of carbon dioxide).", "origins": [ { "producer": "Carbon Dioxide Information Analysis Center (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kt", "short_unit": "kt" }, "en_atm_co2e_gf_zs": { "title": "CO2 emissions from gaseous fuel consumption (% of total)", "description_from_producer": "Carbon dioxide emissions from liquid fuel consumption refer mainly to emissions from use of natural gas as an energy source.\n\nLimitations and exceptions: The U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) calculates annual anthropogenic emissions from data on fossil fuel consumption (from the United Nations Statistics Division's World Energy Data Set) and world cement manufacturing (from the U.S. Department of Interior's Geological Survey, USGS 2011). Although estimates of global carbon dioxide emissions are probably accurate within 10 percent (as calculated from global average fuel chemistry and use), country estimates may have larger error bounds. Trends estimated from a consistent time series tend to be more accurate than individual values.\n\nEach year the CDIAC recalculates the entire time series since 1949, incorporating recent findings and corrections. Estimates exclude fuels supplied to ships and aircraft in international transport because of the difficulty of apportioning the fuels among benefiting countries.\n\nStatistical concept and methodology: Carbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced. Data for carbon dioxide emissions include gases from the burning of fossil fuels and cement manufacture, but excludes emissions from land use such as deforestation. Carbon dioxide emissions are often calculated and reported as elemental carbon. The values were converted to actual carbon dioxide mass by multiplying them by 3.667 (the ratio of the mass of carbon to that of carbon dioxide).", "origins": [ { "producer": "Carbon Dioxide Information Analysis Center (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_co2e_kd_gd": { "title": "CO2 emissions (kg per 2015 US$ of GDP)", "description_from_producer": "Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kg per 2015 US$ of GDP", "short_unit": "kg" }, "en_atm_co2e_kt": { "title": "CO2 emissions (kt)", "description_from_producer": "Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring.\n\nLimitations and exceptions: This series excludes Land-use Change & Forestry (LUCF).\n\nThe world data includes international bunker fuel-related emissions and emissions from territories not part of the United Nations Framework Convention on Climate Change (UNFCCC).\n\nStatistical concept and methodology: Carbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced. Data for carbon dioxide emissions include gases from the burning of fossil fuels and cement manufacture, but excludes emissions from land use such as deforestation. The unit of measurement is kt (kiloton). Carbon dioxide emissions are often calculated and reported as elemental carbon. The were converted to actual carbon dioxide mass by multiplying them by 3.667 (the ratio of the mass of carbon to that of carbon dioxide).", "origins": [ { "producer": "World Resources Institute", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kt", "short_unit": "kt" }, "en_atm_co2e_lf_kt": { "title": "CO2 emissions from liquid fuel consumption (kt)", "description_from_producer": "Carbon dioxide emissions from liquid fuel consumption refer mainly to emissions from use of petroleum-derived fuels as an energy source.\n\nLimitations and exceptions: The U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) calculates annual anthropogenic emissions from data on fossil fuel consumption (from the United Nations Statistics Division's World Energy Data Set) and world cement manufacturing (from the U.S. Department of Interior's Geological Survey, USGS 2011). Although estimates of global carbon dioxide emissions are probably accurate within 10 percent (as calculated from global average fuel chemistry and use), country estimates may have larger error bounds. Trends estimated from a consistent time series tend to be more accurate than individual values.\n\nEach year the CDIAC recalculates the entire time series since 1949, incorporating recent findings and corrections. Estimates exclude fuels supplied to ships and aircraft in international transport because of the difficulty of apportioning the fuels among benefiting countries.\n\nStatistical concept and methodology: Carbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced. Data for carbon dioxide emissions include gases from the burning of fossil fuels and cement manufacture, but excludes emissions from land use such as deforestation. Carbon dioxide emissions are often calculated and reported as elemental carbon. The values were converted to actual carbon dioxide mass by multiplying them by 3.667 (the ratio of the mass of carbon to that of carbon dioxide).", "origins": [ { "producer": "Carbon Dioxide Information Analysis Center (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kt", "short_unit": "kt" }, "en_atm_co2e_lf_zs": { "title": "CO2 emissions from liquid fuel consumption (% of total)", "description_from_producer": "Carbon dioxide emissions from liquid fuel consumption refer mainly to emissions from use of petroleum-derived fuels as an energy source.\n\nLimitations and exceptions: The U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) calculates annual anthropogenic emissions from data on fossil fuel consumption (from the United Nations Statistics Division's World Energy Data Set) and world cement manufacturing (from the U.S. Department of Interior's Geological Survey, USGS 2011). Although estimates of global carbon dioxide emissions are probably accurate within 10 percent (as calculated from global average fuel chemistry and use), country estimates may have larger error bounds. Trends estimated from a consistent time series tend to be more accurate than individual values.\n\nEach year the CDIAC recalculates the entire time series since 1949, incorporating recent findings and corrections. Estimates exclude fuels supplied to ships and aircraft in international transport because of the difficulty of apportioning the fuels among benefiting countries.\n\nStatistical concept and methodology: Carbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced. Data for carbon dioxide emissions include gases from the burning of fossil fuels and cement manufacture, but excludes emissions from land use such as deforestation. Carbon dioxide emissions are often calculated and reported as elemental carbon. The values were converted to actual carbon dioxide mass by multiplying them by 3.667 (the ratio of the mass of carbon to that of carbon dioxide).", "origins": [ { "producer": "Carbon Dioxide Information Analysis Center (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_co2e_pc": { "title": "CO2 emissions (metric tons per capita)", "description_from_producer": "Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring.\n\nStatistical concept and methodology: Carbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced. Data for carbon dioxide emissions include gases from the burning of fossil fuels and cement manufacture, but excludes emissions from land use such as deforestation.", "origins": [ { "producer": "World Resources Institute", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "metric tons per capita", "short_unit": "metric tons" }, "en_atm_co2e_pp_gd": { "title": "CO2 emissions (kg per PPP $ of GDP)", "description_from_producer": "Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kg per PPP $ of GDP", "short_unit": "kg" }, "en_atm_co2e_pp_gd_kd": { "title": "CO2 emissions (kg per 2017 PPP $ of GDP)", "description_from_producer": "Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring.\n\nLimitations and exceptions: The U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) calculates annual anthropogenic emissions from data on fossil fuel consumption (from the United Nations Statistics Division's World Energy Data Set) and world cement manufacturing (from the U.S. Department of Interior's Geological Survey, USGS 2011). Although estimates of global carbon dioxide emissions are probably accurate within 10 percent (as calculated from global average fuel chemistry and use), country estimates may have larger error bounds. Trends estimated from a consistent time series tend to be more accurate than individual values.\n\nEach year the CDIAC recalculates the entire time series since 1949, incorporating recent findings and corrections. Estimates exclude fuels supplied to ships and aircraft in international transport because of the difficulty of apportioning the fuels among benefiting countries.\n\nData for carbon dioxide emissions include gases from the burning of fossil fuels and cement manufacture, but excludes emissions from land use such as deforestation.\n\nStatistical concept and methodology: Carbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced. Carbon dioxide emissions are often calculated and reported as elemental carbon. The values were converted to actual carbon dioxide mass by multiplying them by 3.667 (the ratio of the mass of carbon to that of carbon dioxide).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kg per 2017 PPP $ of GDP", "short_unit": "kg" }, "en_atm_co2e_sf_kt": { "title": "CO2 emissions from solid fuel consumption (kt)", "description_from_producer": "Carbon dioxide emissions from solid fuel consumption refer mainly to emissions from use of coal as an energy source.\n\nLimitations and exceptions: The U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) calculates annual anthropogenic emissions from data on fossil fuel consumption (from the United Nations Statistics Division's World Energy Data Set) and world cement manufacturing (from the U.S. Department of Interior's Geological Survey, USGS 2011). Although estimates of global carbon dioxide emissions are probably accurate within 10 percent (as calculated from global average fuel chemistry and use), country estimates may have larger error bounds. Trends estimated from a consistent time series tend to be more accurate than individual values.\n\nEach year the CDIAC recalculates the entire time series since 1949, incorporating recent findings and corrections. Estimates exclude fuels supplied to ships and aircraft in international transport because of the difficulty of apportioning the fuels among benefiting countries.\n\nStatistical concept and methodology: Carbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced. Data for carbon dioxide emissions include gases from the burning of fossil fuels and cement manufacture, but excludes emissions from land use such as deforestation. The unit of measurement is kt (kiloton). Carbon dioxide emissions are often calculated and reported as elemental carbon. The values were converted to actual carbon dioxide mass by multiplying them by 3.667 (the ratio of the mass of carbon to that of carbon dioxide).", "origins": [ { "producer": "Carbon Dioxide Information Analysis Center (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kt", "short_unit": "kt" }, "en_atm_co2e_sf_zs": { "title": "CO2 emissions from solid fuel consumption (% of total)", "description_from_producer": "Carbon dioxide emissions from solid fuel consumption refer mainly to emissions from use of coal as an energy source.\n\nLimitations and exceptions: The U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) calculates annual anthropogenic emissions from data on fossil fuel consumption (from the United Nations Statistics Division's World Energy Data Set) and world cement manufacturing (from the U.S. Department of Interior's Geological Survey, USGS 2011). Although estimates of global carbon dioxide emissions are probably accurate within 10 percent (as calculated from global average fuel chemistry and use), country estimates may have larger error bounds. Trends estimated from a consistent time series tend to be more accurate than individual values.\n\nEach year the CDIAC recalculates the entire time series since 1949, incorporating recent findings and corrections. Estimates exclude fuels supplied to ships and aircraft in international transport because of the difficulty of apportioning the fuels among benefiting countries.\n\nStatistical concept and methodology: The U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) calculates annual anthropogenic emissions from data on fossil fuel consumption (from the United Nations Statistics Division's World Energy Data Set) and world cement manufacturing (from the U.S. Department of Interior's Geological Survey (USGS 2011)). Although estimates of global carbon dioxide emissions are probably accurate within 10 percent (as calculated from global average fuel chemistry and use), country estimates may have larger error bounds. Trends estimated from a consistent time series tend to be more accurate than individual values.\n\nEach year the CDIAC recalculates the entire time series since 1949, incorporating recent findings and corrections. Estimates exclude fuels supplied to ships and aircraft in international transport because of the difficulty of apportioning the fuels among benefiting countries.", "origins": [ { "producer": "Carbon Dioxide Information Analysis Center (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_ghgo_kt_ce": { "title": "Other greenhouse gas emissions, HFC, PFC and SF6 (thousand metric tons of CO2 equivalent)", "description_from_producer": "Other greenhouse gas emissions are by-product emissions of hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride.\n\nLimitations and exceptions: National reporting to the United Nations Framework Convention on Climate Change that follows the Intergovernmental Panel on Climate Change guidelines is based on national emission inventories and covers all sources of anthropogenic carbon dioxide emissions as well as carbon sinks (such as forests). To estimate emissions, the countries that are Parties to the Climate Change Convention (UNFCCC) use complex, state-of-the-art methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC).\n\nStatistical concept and methodology: Other greenhouse gas emissions are by-product emissions of hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride (F-gases (c-C4F8 GWP=8700, C2F6 GWP=9200, C3F8 GWP=7000, C4F10 GWP=7000, C5F12 GWP=7500, C6F14 GWP=7400, C7F16 GWP=7820, CF4 GWP=6500, HFC-125 GWP=2800, HFC-134a GWP=1300, HFC-143a GWP=3800, HFC-152a GWP=140, HFC-227ea GWP=2900, HFC-23 GWP=11700, HFC-236fa GWP=6300, HFC-245fa GWP=858, HFC-32 GWP=650, HFC-365mfc GWP=804, HFC-43-10-mee GWP=1300, SF6 GWP=23900). Derived as residuals from total GHG emissions, CO2 emissions, CH4 emissions, and N2O emissions in kt of CO equivalent. Other greenhouse gases covered under the Kyoto Protocol are hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride. Although emissions of these artificial gases are small, they are more powerful greenhouse gases than carbon dioxide, with much higher atmospheric lifetimes and high global warming potential. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared.", "origins": [ { "producer": "World Bank based on data from the European Commission Joint Research Centre and Netherlands Environmental Assessment Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "thousand metric tons of CO2 equivalent" }, "en_atm_ghgo_zg": { "title": "Other greenhouse gas emissions (% change from 1990)", "description_from_producer": "Other greenhouse gas emissions are by-product emissions of hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride. Each year of data shows the percentage change to that year from 1990.\n\nLimitations and exceptions: National reporting to the United Nations Framework Convention on Climate Change that follows the Intergovernmental Panel on Climate Change guidelines is based on national emission inventories and covers all sources of anthropogenic carbon dioxide emissions as well as carbon sinks (such as forests). To estimate emissions, the countries that are Parties to the Climate Change Convention (UNFCCC) use complex, state-of-the-art methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC).\n\nStatistical concept and methodology: Other greenhouse gas emissions are by-product emissions of hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride (F-gases (c-C4F8 GWP=8700, C2F6 GWP=9200, C3F8 GWP=7000, C4F10 GWP=7000, C5F12 GWP=7500, C6F14 GWP=7400, C7F16 GWP=7820, CF4 GWP=6500, HFC-125 GWP=2800, HFC-134a GWP=1300, HFC-143a GWP=3800, HFC-152a GWP=140, HFC-227ea GWP=2900, HFC-23 GWP=11700, HFC-236fa GWP=6300, HFC-245fa GWP=858, HFC-32 GWP=650, HFC-365mfc GWP=804, HFC-43-10-mee GWP=1300, SF6 GWP=23900). Derived as residuals from total GHG emissions, CO2 emissions, CH4 emissions, and N2O emissions in kt of CO equivalent. Other greenhouse gases covered under the Kyoto Protocol are hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride. Although emissions of these artificial gases are small, they are more powerful greenhouse gases than carbon dioxide, with much higher atmospheric lifetimes and high global warming potential. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared.", "origins": [ { "producer": "World Bank based on data from the European Commission Joint Research Centre and Netherlands Environmental Assessment Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% change from 1990", "short_unit": "%" }, "en_atm_ghgt_kt_ce": { "title": "Total greenhouse gas emissions (kt of CO2 equivalent)", "description_from_producer": "Total greenhouse gas emissions in kt of CO2 equivalent are composed of CO2 totals excluding short-cycle biomass burning (such as agricultural waste burning and savanna burning) but including other biomass burning (such as forest fires, post-burn decay, peat fires and decay of drained peatlands), all anthropogenic CH4 sources, N2O sources and F-gases (HFCs, PFCs and SF6).\n\nLimitations and exceptions: This series excludes Land-use Change & Forestry (LUCF).\n\nThe world data includes international bunker fuel-related emissions and emissions from territories not part of the United Nations Framework Convention on Climate Change (UNFCCC).\n\nStatistical concept and methodology: The GHG totals are expressed in CO2 equivalent using the GWP100 metric of the Second Assessment Report of IPCC and include CO2 (GWP100=1), CH4 (GWP100=21), N2O (GWP100=310) and F-gases (c-C4F8 GWP=8700, C2F6 GWP=9200, C3F8 GWP=7000, C4F10 GWP=7000, C5F12 GWP=7500, C6F14 GWP=7400, C7F16 GWP=7820, CF4 GWP=6500, HFC-125 GWP=2800, HFC-134a GWP=1300, HFC-143a GWP=3800, HFC-152a GWP=140, HFC-227ea GWP=2900, HFC-23 GWP=11700, HFC-236fa GWP=6300, HFC-245fa GWP=858, HFC-32 GWP=650, HFC-365mfc GWP=804, HFC-43-10-mee GWP=1300, SF6 GWP=23900).", "origins": [ { "producer": "World Resources Institute", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kt of CO2 equivalent" }, "en_atm_ghgt_zg": { "title": "Total greenhouse gas emissions (% change from 1990)", "description_from_producer": "Total greenhouse gas emissions are composed of CO2 totals excluding short-cycle biomass burning (such as agricultural waste burning and savanna burning) but including other biomass burning (such as forest fires, post-burn decay, peat fires and decay of drained peatlands), all anthropogenic CH4 sources, N2O sources and F-gases (HFCs, PFCs and SF6). Each year of data shows the percentage change to that year from 1990.\n\nLimitations and exceptions: National reporting to the United Nations Framework Convention on Climate Change that follows the Intergovernmental Panel on Climate Change guidelines is based on national emission inventories and covers all sources of anthropogenic carbon dioxide emissions as well as carbon sinks (such as forests). To estimate emissions, the countries that are Parties to the Climate Change Convention (UNFCCC) use complex, state-of-the-art methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC).\n\nStatistical concept and methodology: The GHG totals are expressed in CO2 equivalent using the GWP100 metric of the Second Assessment Report of IPCC and include CO2 (GWP100=1), CH4 (GWP100=21), N2O (GWP100=310) and F-gases (c-C4F8 GWP=8700, C2F6 GWP=9200, C3F8 GWP=7000, C4F10 GWP=7000, C5F12 GWP=7500, C6F14 GWP=7400, C7F16 GWP=7820, CF4 GWP=6500, HFC-125 GWP=2800, HFC-134a GWP=1300, HFC-143a GWP=3800, HFC-152a GWP=140, HFC-227ea GWP=2900, HFC-23 GWP=11700, HFC-236fa GWP=6300, HFC-245fa GWP=858, HFC-32 GWP=650, HFC-365mfc GWP=804, HFC-43-10-mee GWP=1300, SF6 GWP=23900).", "origins": [ { "producer": "World Bank based on data from the European Commission Joint Research Centre and Netherlands Environmental Assessment Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% change from 1990", "short_unit": "%" }, "en_atm_hfcg_kt_ce": { "title": "HFC gas emissions (thousand metric tons of CO2 equivalent)", "description_from_producer": "Hydrofluorocarbons, used as a replacement for chlorofluorocarbons, are used mainly in refrigeration and semiconductor manufacturing.", "origins": [ { "producer": "European Commission Joint Research Centre and Netherlands Environmental Assessment Agency (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "thousand metric tons of CO2 equivalent" }, "en_atm_meth_ag_kt_ce": { "title": "Agricultural methane emissions (thousand metric tons of CO2 equivalent)", "description_from_producer": "Agricultural methane emissions are emissions from animals, animal waste, rice production, agricultural waste burning (nonenergy, on-site), and savanna burning.\n\nLimitations and exceptions: This series excludes Land-use Change & Forestry (LUCF).\n\nThe world data includes international bunker fuel-related emissions and emissions from territories not part of the United Nations Framework Convention on Climate Change (UNFCCC).\n\nStatistical concept and methodology: IPCC category 4 = Agriculture. Expressed in CO2 equivalent using the GWP100 metric of the Second Assessment Report of IPCC and include CH4 (GWP100=21). Methane emissions result largely from agricultural activities, industrial production landfills and wastewater treatment, and other sources such as tropical forest and other vegetation fires. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared. A kilogram of methane is 21 times as effective at trapping heat in the earth's atmosphere as a kilogram of carbon dioxide within 100 years. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared.", "origins": [ { "producer": "World Resources Institute", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "thousand metric tons of CO2 equivalent" }, "en_atm_meth_ag_zs": { "title": "Agricultural methane emissions (% of total)", "description_from_producer": "Agricultural methane emissions are emissions from animals, animal waste, rice production, agricultural waste burning (nonenergy, on-site), and savanna burning.\n\nLimitations and exceptions: National reporting to the United Nations Framework Convention on Climate Change that follows the Intergovernmental Panel on Climate Change guidelines is based on national emission inventories and covers all sources of anthropogenic carbon dioxide emissions as well as carbon sinks (such as forests). To estimate emissions, the countries that are Parties to the Climate Change Convention (UNFCCC) use complex, state-of-the-art methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC).\n\nStatistical concept and methodology: IPCC category 4 = Agriculture. Methane emissions result largely from agricultural activities, industrial production landfills and wastewater treatment, and other sources such as tropical forest and other vegetation fires. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared. A kilogram of methane is 21 times as effective at trapping heat in the earth's atmosphere as a kilogram of carbon dioxide within 100 years.", "origins": [ { "producer": "World Bank based on data from the European Commission Joint Research Centre and Netherlands Environmental Assessment Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_meth_eg_kt_ce": { "title": "Methane emissions in energy sector (thousand metric tons of CO2 equivalent)", "description_from_producer": "Methane emissions from energy processes are emissions from the production, handling, transmission, and combustion of fossil fuels and biofuels.\n\nLimitations and exceptions: This series excludes Land-use Change & Forestry (LUCF).\n\nThe world data includes international bunker fuel-related emissions and emissions from territories not part of the United Nations Framework Convention on Climate Change (UNFCCC).\n\nStatistical concept and methodology: IPCC category 1 = Energy. Expressed in CO2 equivalent using the GWP100 metric of the Second Assessment Report of IPCC and include CH4 (GWP100=21). Methane emissions are those stemming from human activities such as agriculture and from industrial methane production. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared. A kilogram of methane is 21 times as effective at trapping heat in the earth's atmosphere as a kilogram of carbon dioxide within 100 years. The unit of measurement is kt (kiloton) of carbon dioxide equivalent.", "origins": [ { "producer": "World Resources Institute", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "thousand metric tons of CO2 equivalent" }, "en_atm_meth_eg_zs": { "title": "Energy related methane emissions (% of total)", "description_from_producer": "Methane emissions from energy processes are emissions from the production, handling, transmission, and combustion of fossil fuels and biofuels.\n\nLimitations and exceptions: National reporting to the United Nations Framework Convention on Climate Change that follows the Intergovernmental Panel on Climate Change guidelines is based on national emission inventories and covers all sources of anthropogenic carbon dioxide emissions as well as carbon sinks (such as forests). To estimate emissions, the countries that are Parties to the Climate Change Convention (UNFCCC) use complex, state-of-the-art methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC).\n\nStatistical concept and methodology: IPCC category 1 = Energy. Methane emissions result largely from agricultural activities, industrial production landfills and wastewater treatment, and other sources such as tropical forest and other vegetation fires. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared. A kilogram of methane is 21 times as effective at trapping heat in the earth's atmosphere as a kilogram of carbon dioxide within 100 years. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared.", "origins": [ { "producer": "World Bank based on data from the European Commission Joint Research Centre and Netherlands Environmental Assessment Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_meth_kt_ce": { "title": "Methane emissions (kt of CO2 equivalent)", "description_from_producer": "Methane emissions are those stemming from human activities such as agriculture and from industrial methane production.\n\nLimitations and exceptions: This series excludes Land-use Change & Forestry (LUCF).\n\nThe world data includes international bunker fuel-related emissions and emissions from territories not part of the United Nations Framework Convention on Climate Change (UNFCCC).\n\nStatistical concept and methodology: Methane emissions are those stemming from human activities such as agriculture and from industrial methane production. Expressed in CO2 equivalent using the GWP100 metric of the Second Assessment Report of IPCC and include CH4 (GWP100=21). The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared. A kilogram of methane is 21 times as effective at trapping heat in the earth's atmosphere as a kilogram of carbon dioxide within 100 years.", "origins": [ { "producer": "World Resources Institute", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "kt of CO2 equivalent" }, "en_atm_meth_zg": { "title": "Methane emissions (% change from 1990)", "description_from_producer": "Methane emissions are those stemming from human activities such as agriculture and from industrial methane production. Each year of data shows the percentage change to that year from 1990.\n\nLimitations and exceptions: National reporting to the United Nations Framework Convention on Climate Change that follows the Intergovernmental Panel on Climate Change guidelines is based on national emission inventories and covers all sources of anthropogenic carbon dioxide emissions as well as carbon sinks (such as forests). To estimate emissions, the countries that are Parties to the Climate Change Convention (UNFCCC) use complex, state-of-the-art methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC).\n\nStatistical concept and methodology: Methane emissions are those stemming from human activities such as agriculture and from industrial methane production. Expressed in CO2 equivalent using the GWP100 metric of the Second Assessment Report of IPCC and include CH4 (GWP100=21). The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared. A kilogram of methane is 21 times as effective at trapping heat in the earth's atmosphere as a kilogram of carbon dioxide within 100 years.", "origins": [ { "producer": "World Bank based on data from the European Commission Joint Research Centre and Netherlands Environmental Assessment Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% change from 1990", "short_unit": "%" }, "en_atm_noxe_ag_kt_ce": { "title": "Agricultural nitrous oxide emissions (thousand metric tons of CO2 equivalent)", "description_from_producer": "Agricultural nitrous oxide emissions are emissions produced through fertilizer use (synthetic and animal manure), animal waste management, agricultural waste burning (nonenergy, on-site), and savanna burning.\n\nLimitations and exceptions: This series excludes Land-use Change & Forestry (LUCF).\n\nThe world data includes international bunker fuel-related emissions and emissions from territories not part of the United Nations Framework Convention on Climate Change (UNFCCC).\n\nStatistical concept and methodology: Agricultural nitrous oxide emissions are emissions produced through fertilizer use (synthetic and animal manure), animal waste management, agricultural waste burning (nonenergy, on-site), and savannah burning. IPCC category 4 = Agriculture. Expressed in CO2 equivalent using the GWP100 metric of the Second Assessment Report of IPCC and include N2O (GWP100=310).", "origins": [ { "producer": "World Resources Institute", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "thousand metric tons of CO2 equivalent" }, "en_atm_noxe_ag_zs": { "title": "Agricultural nitrous oxide emissions (% of total)", "description_from_producer": "Agricultural nitrous oxide emissions are emissions produced through fertilizer use (synthetic and animal manure), animal waste management, agricultural waste burning (nonenergy, on-site), and savanna burning.\n\nLimitations and exceptions: National reporting to the United Nations Framework Convention on Climate Change that follows the Intergovernmental Panel on Climate Change guidelines is based on national emission inventories and covers all sources of anthropogenic carbon dioxide emissions as well as carbon sinks (such as forests). To estimate emissions, the countries that are Parties to the Climate Change Convention (UNFCCC) use complex, state-of-the-art methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC).\n\nStatistical concept and methodology: Agricultural nitrous oxide emissions are emissions produced through fertilizer use (synthetic and animal manure), animal waste management, agricultural waste burning (nonenergy, on-site), and savannah burning. IPCC category 4 = Agriculture. Expressed in CO2 equivalent using the GWP100 metric of the Second Assessment Report of IPCC and include N2O (GWP100=310).", "origins": [ { "producer": "World Bank based on data from the European Commission Joint Research Centre and Netherlands Environmental Assessment Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_noxe_eg_kt_ce": { "title": "Nitrous oxide emissions in energy sector (thousand metric tons of CO2 equivalent)", "description_from_producer": "Nitrous oxide emissions from energy processes are emissions produced by the combustion of fossil fuels and biofuels.\n\nLimitations and exceptions: This series excludes Land-use Change & Forestry (LUCF).\n\nThe world data includes international bunker fuel-related emissions and emissions from territories not part of the United Nations Framework Convention on Climate Change (UNFCCC).\n\nStatistical concept and methodology: IPCC category 1 = Energy. Expressed in CO2 equivalent using the GWP100 metric of the Second Assessment Report of IPCC and include N2O (GWP100=310). Nitrous oxide emissions are mainly from fossil fuel combustion, fertilizers, rainforest fires, and animal waste. Nitrous oxide is a powerful greenhouse gas, with an estimated atmospheric lifetime of 114 years, compared with 12 years for methane. The per kilogram global warming potential of nitrous oxide is nearly 310 times that of carbon dioxide within 100 years. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared.", "origins": [ { "producer": "World Resources Institute", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "thousand metric tons of CO2 equivalent" }, "en_atm_noxe_eg_zs": { "title": "Nitrous oxide emissions in energy sector (% of total)", "description_from_producer": "Nitrous oxide emissions from energy processes are emissions produced by the combustion of fossil fuels and biofuels.\n\nLimitations and exceptions: National reporting to the United Nations Framework Convention on Climate Change that follows the Intergovernmental Panel on Climate Change guidelines is based on national emission inventories and covers all sources of anthropogenic carbon dioxide emissions as well as carbon sinks (such as forests). To estimate emissions, the countries that are Parties to the Climate Change Convention (UNFCCC) use complex, state-of-the-art methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC).\n\nStatistical concept and methodology: Nitrous oxide emissions are mainly from fossil fuel combustion, fertilizers, rainforest fires, and animal waste. Nitrous oxide is a powerful greenhouse gas, with an estimated atmospheric lifetime of 114 years, compared with 12 years for methane. The per kilogram global warming potential of nitrous oxide is nearly 310 times that of carbon dioxide within 100 years. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared.", "origins": [ { "producer": "World Bank based on data from the European Commission Joint Research Centre and Netherlands Environmental Assessment Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_noxe_kt_ce": { "title": "Nitrous oxide emissions (thousand metric tons of CO2 equivalent)", "description_from_producer": "Nitrous oxide emissions are emissions from agricultural biomass burning, industrial activities, and livestock management.\n\nLimitations and exceptions: This series excludes Land-use Change & Forestry (LUCF).\n\nThe world data includes international bunker fuel-related emissions and emissions from territories not part of the United Nations Framework Convention on Climate Change (UNFCCC).\n\nStatistical concept and methodology: Nitrous oxide emissions are mainly from fossil fuel combustion, fertilizers, rainforest fires, and animal waste. Nitrous oxide is a powerful greenhouse gas, with an estimated atmospheric lifetime of 114 years, compared with 12 years for methane. The per kilogram global warming potential of nitrous oxide is nearly 310 times that of carbon dioxide within 100 years. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared.", "origins": [ { "producer": "World Resources Institute", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "thousand metric tons of CO2 equivalent" }, "en_atm_noxe_zg": { "title": "Nitrous oxide emissions (% change from 1990)", "description_from_producer": "Nitrous oxide emissions are emissions from agricultural biomass burning, industrial activities, and livestock management. Each year of data shows the percentage change to that year from 1990.\n\nLimitations and exceptions: National reporting to the United Nations Framework Convention on Climate Change that follows the Intergovernmental Panel on Climate Change guidelines is based on national emission inventories and covers all sources of anthropogenic carbon dioxide emissions as well as carbon sinks (such as forests). To estimate emissions, the countries that are Parties to the Climate Change Convention (UNFCCC) use complex, state-of-the-art methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC).\n\nStatistical concept and methodology: Nitrous oxide emissions are mainly from fossil fuel combustion, fertilizers, rainforest fires, and animal waste. Nitrous oxide is a powerful greenhouse gas, with an estimated atmospheric lifetime of 114 years, compared with 12 years for methane. The per kilogram global warming potential of nitrous oxide is nearly 310 times that of carbon dioxide within 100 years. The emissions are usually expressed in carbon dioxide equivalents using the global warming potential, which allows the effective contributions of different gases to be compared.", "origins": [ { "producer": "World Bank based on data from the European Commission Joint Research Centre and Netherlands Environmental Assessment Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% change from 1990", "short_unit": "%" }, "en_atm_pfcg_kt_ce": { "title": "PFC gas emissions (thousand metric tons of CO2 equivalent)", "description_from_producer": "Perfluorocarbons, used as a replacement for chlorofluorocarbons in manufacturing semiconductors, are a byproduct of aluminum smelting and uranium enrichment.", "origins": [ { "producer": "European Commission Joint Research Centre and Netherlands Environmental Assessment Agency (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "thousand metric tons of CO2 equivalent" }, "en_atm_pm25_mc_m3": { "title": "PM2.5 air pollution, mean annual exposure (micrograms per cubic meter)", "description_from_producer": "Population-weighted exposure to ambient PM2.5 pollution is defined as the average level of exposure of a nation's population to concentrations of suspended particles measuring less than 2.5 microns in aerodynamic diameter, which are capable of penetrating deep into the respiratory tract and causing severe health damage. Exposure is calculated by weighting mean annual concentrations of PM2.5 by population in both urban and rural areas.\n\nLimitations and exceptions: Pollutant concentrations are sensitive to local conditions, and even monitoring sites in the same city may register different levels. Direct monitoring of PM2.5 is still rare in most parts of the world, and measurement protocols and standards are not the same for all countries. These data should be considered only a general indication of air quality, intended to inform cross-country comparisons of the health risks due to particulate matter pollution. The guideline set by the World Health Organization (WHO) for PM2.5 is that annual mean concentrations should not exceed 10 micrograms per cubic meter, representing the lower range over which adverse health effects have been observed. The WHO has also recommended guideline values for emissions of PM2.5 from burning fuels in households.\n\nStatistical concept and methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, \"Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors,\" Environ. Sci. Technol 50, no. 7 (2016): 3762\u20133772; GBD 2017 Risk Factors Collaborators, \"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990\u20132017: a systematic analysis for the Global Burden of Disease Study 2017,\" Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Pr\u00fcss-\u00dcst\u00fcn A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Exposure to concentrations of PM2.5 in both urban and rural areas is weighted by population and is aggregated at the national level.", "origins": [ { "producer": "Institute for Health Metrics and Evaluation", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "micrograms per cubic meter", "short_unit": "micrograms" }, "en_atm_pm25_mc_t1_zs": { "title": "PM2.5 pollution, population exposed to levels exceeding WHO Interim Target-1 value (% of total)", "description_from_producer": "Percent of population exposed to ambient concentrations of PM2.5 that exceed the World Health Organization (WHO) Interim Target 1 (IT-1) is defined as the portion of a country\u2019s population living in places where mean annual concentrations of PM2.5 are greater than 35 micrograms per cubic meter. The Air Quality Guideline (AQG) of 10 micrograms per cubic meter is recommended by the WHO as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.\n\nLimitations and exceptions: Pollutant concentrations are sensitive to local conditions, and even monitoring sites in the same city may register different levels. Direct monitoring of PM2.5 is still rare in most parts of the world, and measurement protocols and standards are not the same for all countries. These data should be considered only a general indication of air quality, intended to inform cross-country comparisons of the health risks due to particulate matter pollution. The guideline set by the World Health Organization (WHO) for PM2.5 is that annual mean concentrations should not exceed 10 micrograms per cubic meter, representing the lower range over which adverse health effects have been observed. The WHO has also recommended guideline values for emissions of PM2.5 from burning fuels in households.\n\nStatistical concept and methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, \"Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors,\" Environ. Sci. Technol 50, no. 7 (2016): 3762\u20133772;GBD 2017 Risk Factors Collaborators, \"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990\u20132017: a systematic analysis for the Global Burden of Disease Study 2017,\" Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Pr\u00fcss-\u00dcst\u00fcn A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Overlaying PM2.5 estimates with gridded population data, the percent of a nation's people that lives in areas where PM2.5 concentrations exceed recommended levels is calculated by summing the population for grid cells where PM2.5 concentrations are beyond a threshold value, in this case 10 micrograms per cubic meter, and then dividing by total population.", "origins": [ { "producer": "Brauer et al. (2017) via World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_pm25_mc_t2_zs": { "title": "PM2.5 pollution, population exposed to levels exceeding WHO Interim Target-2 value (% of total)", "description_from_producer": "Percent of population exposed to ambient concentrations of PM2.5 that exceed the World Health Organization (WHO) Interim Target 2 (IT-2) is defined as the portion of a country\u2019s population living in places where mean annual concentrations of PM2.5 are greater than 25 micrograms per cubic meter. The Air Quality Guideline (AQG) of 10 micrograms per cubic meter is recommended by the WHO as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.\n\nLimitations and exceptions: Pollutant concentrations are sensitive to local conditions, and even monitoring sites in the same city may register different levels. Direct monitoring of PM2.5 is still rare in most parts of the world, and measurement protocols and standards are not the same for all countries. These data should be considered only a general indication of air quality, intended to inform cross-country comparisons of the health risks due to particulate matter pollution. The guideline set by the World Health Organization (WHO) for PM2.5 is that annual mean concentrations should not exceed 10 micrograms per cubic meter, representing the lower range over which adverse health effects have been observed. The WHO has also recommended guideline values for emissions of PM2.5 from burning fuels in households.\n\nStatistical concept and methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, \"Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors,\" Environ. Sci. Technol 50, no. 7 (2016): 3762\u20133772; GBD 2017 Risk Factors Collaborators, \"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990\u20132017: a systematic analysis for the Global Burden of Disease Study 2017,\" Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Pr\u00fcss-\u00dcst\u00fcn A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Overlaying PM2.5 estimates with gridded population data, the percent of a nation's people that lives in areas where PM2.5 concentrations exceed recommended levels is calculated by summing the population for grid cells where PM2.5 concentrations are beyond a threshold value, in this case 10 micrograms per cubic meter, and then dividing by total population.", "origins": [ { "producer": "Brauer et al. (2017) via World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_pm25_mc_t3_zs": { "title": "PM2.5 pollution, population exposed to levels exceeding WHO Interim Target-3 value (% of total)", "description_from_producer": "Percent of population exposed to ambient concentrations of PM2.5 that exceed the World Health Organization (WHO) Interim Target 3 (IT-3) is defined as the portion of a country\u2019s population living in places where mean annual concentrations of PM2.5 are greater than 15 micrograms per cubic meter. The Air Quality Guideline (AQG) of 10 micrograms per cubic meter is recommended by the WHO as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.\n\nLimitations and exceptions: Pollutant concentrations are sensitive to local conditions, and even monitoring sites in the same city may register different levels. Direct monitoring of PM2.5 is still rare in most parts of the world, and measurement protocols and standards are not the same for all countries. These data should be considered only a general indication of air quality, intended to inform cross-country comparisons of the health risks due to particulate matter pollution. The guideline set by the World Health Organization (WHO) for PM2.5 is that annual mean concentrations should not exceed 10 micrograms per cubic meter, representing the lower range over which adverse health effects have been observed. The WHO has also recommended guideline values for emissions of PM2.5 from burning fuels in households.\n\nStatistical concept and methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, \"Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors,\" Environ. Sci. Technol 50, no. 7 (2016): 3762\u20133772; GBD 2017 Risk Factors Collaborators, \"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990\u20132017: a systematic analysis for the Global Burden of Disease Study 2017,\" Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Pr\u00fcss-\u00dcst\u00fcn A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Overlaying PM2.5 estimates with gridded population data, the percent of a nation's people that lives in areas where PM2.5 concentrations exceed recommended levels is calculated by summing the population for grid cells where PM2.5 concentrations are beyond a threshold value, in this case 10 micrograms per cubic meter, and then dividing by total population.", "origins": [ { "producer": "Brauer et al. (2017) via World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_pm25_mc_zs": { "title": "PM2.5 air pollution, population exposed to levels exceeding WHO guideline value (% of total)", "description_from_producer": "Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country\u2019s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.\n\nLimitations and exceptions: Pollutant concentrations are sensitive to local conditions, and even monitoring sites in the same city may register different levels. Direct monitoring of PM2.5 is still rare in most parts of the world, and measurement protocols and standards are not the same for all countries. These data should be considered only a general indication of air quality, intended to inform cross-country comparisons of the health risks due to particulate matter pollution. The guideline set by the World Health Organization (WHO) for PM2.5 is that annual mean concentrations should not exceed 10 micrograms per cubic meter, representing the lower range over which adverse health effects have been observed. The WHO has also recommended guideline values for emissions of PM2.5 from burning fuels in households.\n\nStatistical concept and methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, \"Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors,\" Environ. Sci. Technol 50, no. 7 (2016): 3762\u20133772; GBD 2017 Risk Factors Collaborators, \"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990\u20132017: a systematic analysis for the Global Burden of Disease Study 2017,\" Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Pr\u00fcss-\u00dcst\u00fcn A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Overlaying PM2.5 estimates with gridded population data, the percent of a nation's people that lives in areas where PM2.5 concentrations exceed recommended levels is calculated by summing the population for grid cells where PM2.5 concentrations are beyond a threshold value, in this case 10 micrograms per cubic meter, and then dividing by total population.", "origins": [ { "producer": "Brauer et al. (2017) via World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "en_atm_sf6g_kt_ce": { "title": "SF6 gas emissions (thousand metric tons of CO2 equivalent)", "description_from_producer": "Sulfur hexafluoride is used largely to insulate high-voltage electric power equipment.", "origins": [ { "producer": "European Commission Joint Research Centre and Netherlands Environmental Assessment Agency (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "thousand metric tons of CO2 equivalent" }, "en_bir_thrd_no": { "title": "Bird species, threatened", "description_from_producer": "Birds are listed for countries included within their breeding or wintering ranges. Threatened species are the number of species classified by the IUCN as endangered, vulnerable, rare, indeterminate, out of danger, or insufficiently known.\n\nLimitations and exceptions: Reporting the proportion of threatened species on the Red List is complicated by the fact that not all species groups have been fully evaluated, and also by the fact that some species have so little information available that they can only be assessed as Data Deficient (DD). For many of the incompletely evaluated groups, assessment efforts have focused on species that are likely to be threatened; therefore any percentage of threatened species reported for these groups would be heavily biased (i.e., the percentage of threatened species would likely be an overestimate).\n\nSince IUCN has evaluated extinction risk for less than 5 percent of the world's described species, IUCN cannot provide an overall estimate for how many of the planet's species are threatened. For those groups that have been comprehensively evaluated, the proportion of threatened species can be calculated, but the number of threatened species is often uncertain because it is not known whether Data Deficient species are actually threatened or not.\n\nDue to variations in consistency and methods of collection, data quality is highly variable across countries. Some countries update their information more frequently than others, some have more accurate data on extent of coverage, and many underreport the number or extent of protected areas. Also, because of differences in definitions, reporting practices, and reporting periods, cross-country comparability of threatened species is limited.\n\nIn order to ensure global uniformity when describing the habitat in which a taxon (a taxonomic group of any rank) occurs, the threats to a taxon, what conservation actions are in place or are needed, and whether or not the taxon is utilized, a set of standard terms, called Classification Schemes, are being developed, for documenting taxonomy on the IUCN Red List.\n\nStatistical concept and methodology: Species assessed as Critically Endangered (CR), Endangered (EN) or Vulnerable (VU) are referred to as \"threatened\" species. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species collects and disseminates information on the global threated species.\n\nProportion of threatened species is only reported for the more completely evaluated groups (i.e., >90% of species evaluated). Also, the reported percentage of threatened species for each group is presented as a best estimate within a range of possible values bounded by lower and upper estimates:\n\nLower estimate = % threatened extant species if all Data Deficient species are not threatened, i.e., (CR + EN + VU) / (total assessed - EX)\n\nBest estimate = % threatened extant species if Data Deficient species are equally threatened as data sufficient species, i.e., (CR + EN + VU) / (total assessed - EX - DD)\n\nUpper estimate = % threatened extant species if all Data Deficient species are threatened, i.e., (CR + EN + VU + DD) / (total assessed - EX)\n\nAdditional information on ecology and habitat preferences, threats, and conservation action are also collated and assessed as part of Red List process.", "origins": [ { "producer": "International Union for Conservation of Nature (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "en_clc_drsk_xq": { "title": "Disaster risk reduction progress score (1-5 scale; 5=best)", "description_from_producer": "Disaster risk reduction progress score is an average of self-assessment scores, ranging from 1 to 5, submitted by countries under Priority 1 of the Hyogo Framework National Progress Reports. The Hyogo Framework is a global blueprint for disaster risk reduction efforts that was adopted by 168 countries in 2005. Assessments of \"Priority 1\" include four indicators that reflect the degree to which countries have prioritized disaster risk reduction and the strengthening of relevant institutions.\n\nLimitations and exceptions: The Hyogo Framework for Action (FHA) national progress reports assess strategic priorities in the implementation of disaster risk reduction actions and establish baselines on levels of progress achieved in implementing the HFA's five priorities for action. National reporting processes are led by officially designated HFA focal institutions in country, and regional reporting by regional intergovernmental organizations.\n\nHFA's five priorities are:\n1. Making disaster risk reduction a policy priority, institutional strengthening\n2. Risk assessment and early warning systems\n3. Education, information and public awareness\n4. Reducing underlying risk factors\n5. Preparedness for effective response\n\nStatistical concept and methodology: Resilience is measured by the disaster risk reduction progress score, an average of self-assessment scores submitted by countries under Priority 1 of the Hyogo Framework National Progress Reports. The Hyogo Framework is a global blueprint for disaster risk reduction efforts that was adopted by 168 countries in 2005. Assessments of Priority 1 include four indicators that reflect the degree to which countries have prioritized disaster risk reduction and the strengthening of relevant institutions.", "origins": [ { "producer": "UN International Strategy for Disaster Reduction (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1-5 scale; 5=best" }, "en_clc_ghgr_mt_ce": { "title": "GHG net emissions/removals by LUCF (Mt of CO2 equivalent)", "description_from_producer": "GHG net emissions/removals by LUCF refers to changes in atmospheric levels of all greenhouse gases attributable to forest and land-use change activities, including but not limited to (1) emissions and removals of CO2 from decreases or increases in biomass stocks due to forest management, logging, fuelwood collection, etc.; (2) conversion of existing forests and natural grasslands to other land uses; (3) removal of CO2 from the abandonment of formerly managed lands (e.g. croplands and pastures); and (4) emissions and removals of CO2 in soil associated with land-use change and management. For Annex-I countries under the UNFCCC, these data are drawn from the annual GHG inventories submitted to the UNFCCC by each country; for non-Annex-I countries, data are drawn from the most recently submitted National Communication where available. Because of differences in reporting years and methodologies, these data are not generally considered comparable across countries. Data are in million metric tons.", "origins": [ { "producer": "UN Framework Convention on Climate Change (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "Mt of CO2 equivalent" }, "en_clc_mdat_zs": { "title": "Droughts, floods, extreme temperatures (% of population, average 1990-2009)", "description_from_producer": "Droughts, floods and extreme temperatures is the annual average percentage of the population that is affected by natural disasters classified as either droughts, floods, or extreme temperature events. A drought is an extended period of time characterized by a deficiency in a region's water supply that is the result of constantly below average precipitation. A drought can lead to losses to agriculture, affect inland navigation and hydropower plants, and cause a lack of drinking water and famine. A flood is a significant rise of water level in a stream, lake, reservoir or coastal region. Extreme temperature events are either cold waves or heat waves. A cold wave can be both a prolonged period of excessively cold weather and the sudden invasion of very cold air over a large area. Along with frost it can cause damage to agriculture, infrastructure, and property. A heat wave is a prolonged period of excessively hot and sometimes also humid weather relative to normal climate patterns of a certain region. Population affected is the number of people injured, left homeless or requiring immediate assistance during a period of emergency resulting from a natural disaster; it can also include displaced or evacuated people. Average percentage of population affected is calculated by dividing the sum of total affected for the period stated by the sum of the annual population figures for the period stated.\n\nLimitations and exceptions: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is \"unequivocal\" and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20-86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5\u00b0C by 2100 (Kattenberg and others 1996) and increase of \"killer\" heat waves during the warm season (Karl and others 1997).\n\nStatistical concept and methodology: This indicator measures vulnerability of population affected by droughts, floods, and extreme temperature. A drought is an extended period of deficiency in a region's water supply as a result of below average precipitation.", "origins": [ { "producer": "Centre for Research on the Epidemiology of Disasters (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population, average 1990-1990", "short_unit": "%" }, "en_co2_bldg_zs": { "title": "CO2 emissions from residential buildings and commercial and public services (% of total fuel combustion)", "description_from_producer": "CO2 emissions from residential buildings and commercial and public services contains all emissions from fuel combustion in households. This corresponds to IPCC Source/Sink Category 1 A 4 b. Commercial and public services includes emissions from all activities of ISIC Divisions 41, 50-52, 55, 63-67, 70-75, 80, 85, 90-93 and 99.\n\nLimitations and exceptions: As a response to the objectives of the UNFCCC, the IEA Secretariat, together with the IPCC, the OECD and umerous international experts, has helped to develop and refine an internationally-agreed methodology for the calculation and reporting of national greenhouse-gas emissions from fuel combustion. This methodology was published in 1995 in the IPCC Guidelines for National Greenhouse Gas Inventories. After the initial dissemination of the methodology, revisions were added to several chapters, and published as the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (1996 IPCC Guidelines). In April 2006, the IPCC approved the 2006 Guidelines at the 25th session of the IPCC in Mauritius. For now, most countries (as well as the IEA Secretariat) are still calculating their inventories using the 1996 IPCC Guidelines.1. Both the 1996 IPCC Guidelines and the 2006 IPCC Guidelines are available from the IPCC Greenhouse Gas Inventories Programme (www.ipcc-nggip.iges.or.jp).\n\nSince the IPCC methodology for fuel combustion is largely based on energy balances, the IEA estimates for CO2 from fuel combustion have been calculated using the IEA energy balances and the default IPCC methodology. However, other possibly more detailed methodologies may be used by Parties to calculate their inventories. This may lead to different estimates of emissions.\n\nThe carbon dioxide emissions of a country are only an indicator of one greenhouse gas. For a more complete idea of how a country influences climate change, gases such as methane and nitrous oxide should be taken into account. This is particularly important in agricultural economies.\n\nStatistical concept and methodology: Carbon dioxide emissions , largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. In 2010 the International Energy Agency (IEA) released data on carbon dioxide emissions by sector for the first time, allowing a more comprehensive understanding of each sector's contribution to total emissions. The sectoral approach yields data on carbon dioxide emissions from fuel combustion (Intergovernmental Panel on Climate Change [IPCC] source/sink category 1A) as calculated using the IPCC tier 1 sectoral approach.\n\nCarbon emissions from residential buildings and commercial and public services are the sum of emissions from fuel combustion in households (IPCC source/sink category 1A4b) and emissions from all activities of International Standard Industrial Classification divisions 41, 50-52, 55, 63-67, 70-75, 80, 85, 90-93, and 99.\n\nAnthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total fuel combustion", "short_unit": "%" }, "en_co2_etot_zs": { "title": "CO2 emissions from electricity and heat production, total (% of total fuel combustion)", "description_from_producer": "CO2 emissions from electricity and heat production is the sum of three IEA categories of CO2 emissions: (1) Main Activity Producer Electricity and Heat which contains the sum of emissions from main activity producer electricity generation, combined heat and power generation and heat plants. Main activity producers (formerly known as public utilities) are defined as those undertakings whose primary activity is to supply the public. They may be publicly or privately owned. This corresponds to IPCC Source/Sink Category 1 A 1 a. For the CO2 emissions from fuel combustion (summary) file, emissions from own on-site use of fuel in power plants (EPOWERPLT) are also included. (2) Unallocated Autoproducers which contains the emissions from the generation of electricity and/or heat by autoproducers. Autoproducers are defined as undertakings that generate electricity and/or heat, wholly or partly for their own use as an activity which supports their primary activity. They may be privately or publicly owned. In the 1996 IPCC Guidelines, these emissions would normally be distributed between industry, transport and \"other\" sectors. (3) Other Energy Industries contains emissions from fuel combusted in petroleum refineries, for the manufacture of solid fuels, coal mining, oil and gas extraction and other energy-producing industries. This corresponds to the IPCC Source/Sink Categories 1 A 1 b and 1 A 1 c. According to the 1996 IPCC Guidelines, emissions from coke inputs to blast furnaces can either be counted here or in the Industrial Processes source/sink category. Within detailed sectoral calculations, certain non-energy processes can be distinguished. In the reduction of iron in a blast furnace through the combustion of coke, the primary purpose of the coke oxidation is to produce pig iron and the emissions can be considered as an industrial process. Care must be taken not to double count these emissions in both Energy and Industrial Processes. In the IEA estimations, these emissions have been included in this category.\n\nLimitations and exceptions: As a response to the objectives of the UNFCCC, the IEA Secretariat, together with the IPCC, the OECD and umerous international experts, has helped to develop and refine an internationally-agreed methodology for the calculation and reporting of national greenhouse-gas emissions from fuel combustion. This methodology was published in 1995 in the IPCC Guidelines for National Greenhouse Gas Inventories. After the initial dissemination of the methodology, revisions were added to several chapters, and published as the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (1996 IPCC Guidelines). In April 2006, the IPCC approved the 2006 Guidelines at the 25th session of the IPCC in Mauritius. For now, most countries (as well as the IEA Secretariat) are still calculating their inventories using the 1996 IPCC Guidelines.1. Both the 1996 IPCC Guidelines and the 2006 IPCC Guidelines are available from the IPCC Greenhouse Gas Inventories Programme (www.ipcc-nggip.iges.or.jp).\n\nSince the IPCC methodology for fuel combustion is largely based on energy balances, the IEA estimates for CO2 from fuel combustion have been calculated using the IEA energy balances and the default IPCC methodology. However, other possibly more detailed methodologies may be used by Parties to calculate their inventories. This may lead to different estimates of emissions.\n\nThe carbon dioxide emissions of a country are only an indicator of one greenhouse gas. For a more complete idea of how a country influences climate change, gases such as methane and nitrous oxide should be taken into account. This is particularly important in agricultural economies.\n\nStatistical concept and methodology: Carbon dioxide emissions account for the largest share of greenhouse gases, which are associated with global warming. In 2010 the International Energy Agency (IEA) released data on carbon dioxide emissions by sector for the first time, allowing a more comprehensive understanding of each sector's contribution to total emissions. The sectoral approach yields data on carbon dioxide emissions from fuel combustion (Intergovernmental Panel on Climate Change [IPCC] source/sink category 1A) as calculated using the IPCC tier 1 sectoral approach.\n\nCarbon dioxide emissions from electricity and heat production are the sum of emissions from main activity producers of electricity and heat, unallocated autoproducers, and other energy industries. Main activity producers (formerly known as public supply undertakings) generate electricity or heat for sale to third parties as their primary activity and may be privately or publicly owned. Emissions from own onsite use of fuel in power plants are also included in this category. Unallocated autoproducers are undertakings that generate electricity or heat, wholly or partly for their own use as an activity that supports their primary activity and may be privately or publicly owned. In the 1996 IPCC guidelines these emissions were allocated among industry, transport, and \"other\" sectors. Emissions from other energy industries are emissions from fuel combusted in petroleum refineries, the manufacture of solid fuels, coal mining, oil and gas extraction, and other energy-producing industries.\n\nCarbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total fuel combustion", "short_unit": "%" }, "en_co2_manf_zs": { "title": "CO2 emissions from manufacturing industries and construction (% of total fuel combustion)", "description_from_producer": "CO2 emissions from manufacturing industries and construction contains the emissions from combustion of fuels in industry. The IPCC Source/Sink Category 1 A 2 includes these emissions. However, in the 1996 IPCC Guidelines, the IPCC category also includes emissions from industry autoproducers that generate electricity and/or heat. The IEA data are not collected in a way that allows the energy consumption to be split by specific end-use and therefore, autoproducers are shown as a separate item (Unallocated Autoproducers). Manufacturing industries and construction also includes emissions from coke inputs into blast furnaces, which may be reported either in the transformation sector, the industry sector or the separate IPCC Source/Sink Category 2, Industrial Processes.\n\nLimitations and exceptions: As a response to the objectives of the UNFCCC, the IEA Secretariat, together with the IPCC, the OECD and umerous international experts, has helped to develop and refine an internationally-agreed methodology for the calculation and reporting of national greenhouse-gas emissions from fuel combustion. This methodology was published in 1995 in the IPCC Guidelines for National Greenhouse Gas Inventories. After the initial dissemination of the methodology, revisions were added to several chapters, and published as the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (1996 IPCC Guidelines). In April 2006, the IPCC approved the 2006 Guidelines at the 25th session of the IPCC in Mauritius. For now, most countries (as well as the IEA Secretariat) are still calculating their inventories using the 1996 IPCC Guidelines.1. Both the 1996 IPCC Guidelines and the 2006 IPCC Guidelines are available from the IPCC Greenhouse Gas Inventories Programme (www.ipcc-nggip.iges.or.jp).\n\nSince the IPCC methodology for fuel combustion is largely based on energy balances, the IEA estimates for CO2 from fuel combustion have been calculated using the IEA energy balances and the default IPCC methodology. However, other possibly more detailed methodologies may be used by Parties to calculate their inventories. This may lead to different estimates of emissions.\n\nThe carbon dioxide emissions of a country are only an indicator of one greenhouse gas. For a more complete idea of how a country influences climate change, gases such as methane and nitrous oxide should be taken into account. This is particularly important in agricultural economies.\n\nStatistical concept and methodology: Carbon dioxide emissions account for the largest share of greenhouse gases, which are associated with global warming. In 2010 the International Energy Agency (IEA) released data on carbon dioxide emissions by sector for the first time, allowing a more comprehensive understanding of each sector's contribution to total emissions. The sectoral approach yields data on carbon dioxide emissions from fuel combustion (Intergovernmental Panel on Climate Change [IPCC] source/sink category 1A) as calculated using the IPCC tier 1 sectoral approach.\n\nCarbon dioxide emissions from manufacturing industries and construction are the emissions from fuel combustion in industry (IPCC source/sink Category 1A2). Although in the 1996 IPCC guidelines, this category included emissions from industry autoproducers that generate electricity or heat, the IEA data do not allow energy consumption to be categorized by end-use, and thus emissions from autoproducers are listed separately under unallocated autoproducers. Emissions from manufacturing industries and construction include those from coke inputs into blast furnaces, which may be reported under the transformation sector, the industry sector, or industrial processes (IPCC source/sink category 2).\n\nCarbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total fuel combustion", "short_unit": "%" }, "en_co2_othx_zs": { "title": "CO2 emissions from other sectors, excluding residential buildings and commercial and public services (% of total fuel combustion)", "description_from_producer": "CO2 emissions from other sectors, less residential buildings and commercial and public services, contains the emissions from commercial/institutional activities, residential, agriculture/forestry, fishing and other emissions not specified elsewhere that are included in the IPCC Source/Sink Categories 1 A 4 and 1 A 5. In the 1996 IPCC Guidelines, the category also includes emissions from autoproducers in the commercial/residential/agricultural sectors that generate electricity and/or heat. The IEA data are not collected in a way that allows the energy consumption to be split by specific end-use and therefore, autoproducers are shown as a separate item (Unallocated Autoproducers).\n\nLimitations and exceptions: As a response to the objectives of the UNFCCC, the IEA Secretariat, together with the IPCC, the OECD and umerous international experts, has helped to develop and refine an internationally-agreed methodology for the calculation and reporting of national greenhouse-gas emissions from fuel combustion. This methodology was published in 1995 in the IPCC Guidelines for National Greenhouse Gas Inventories. After the initial dissemination of the methodology, revisions were added to several chapters, and published as the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (1996 IPCC Guidelines). In April 2006, the IPCC approved the 2006 Guidelines at the 25th session of the IPCC in Mauritius. For now, most countries (as well as the IEA Secretariat) are still calculating their inventories using the 1996 IPCC Guidelines.1. Both the 1996 IPCC Guidelines and the 2006 IPCC Guidelines are available from the IPCC Greenhouse Gas Inventories Programme (www.ipcc-nggip.iges.or.jp).\n\nSince the IPCC methodology for fuel combustion is largely based on energy balances, the IEA estimates for CO2 from fuel combustion have been calculated using the IEA energy balances and the default IPCC methodology. However, other possibly more detailed methodologies may be used by Parties to calculate their inventories. This may lead to different estimates of emissions.\n\nThe carbon dioxide emissions of a country are only an indicator of one greenhouse gas. For a more complete idea of how a country influences climate change, gases such as methane and nitrous oxide should be taken into account. This is particularly important in agricultural economies.\n\nStatistical concept and methodology: Carbon dioxide emissions account for the largest share of greenhouse gases, which are associated with global warming. In 2010 the International Energy Agency (IEA) released data on carbon dioxide emissions by sector for the first time, allowing a more comprehensive understanding of each sector's contribution to total emissions. The sectoral approach yields data on carbon dioxide emissions from fuel combustion (Intergovernmental Panel on Climate Change [IPCC] source/sink category 1A) as calculated using the IPCC tier 1 sectoral approach.\n\nCarbon dioxide emissions from other sectors are emissions from commercial and institutional activities and from residential, agriculture and forestry, fishing, and other processes not specified elsewhere that are included in IPCC source/sink categories 1A4 and 1A5. Although in the 1996 IPCC guidelines, this category included emissions from autoproducers in the commercial, residential, and agricultural sectors that generate electricity or heat, the IEA data do not allow energy consumption to be classified by end-use, and thus emissions from autoproducers are listed separately under unallocated autoproducers.\n\nCarbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total fuel combustion", "short_unit": "%" }, "en_co2_tran_zs": { "title": "CO2 emissions from transport (% of total fuel combustion)", "description_from_producer": "CO2 emissions from transport contains emissions from the combustion of fuel for all transport activity, regardless of the sector, except for international marine bunkers and international aviation. This includes domestic aviation, domestic navigation, road, rail and pipeline transport, and corresponds to IPCC Source/Sink Category 1 A 3. In addition, the IEA data are not collected in a way that allows the autoproducer consumption to be split by specific end-use and therefore, autoproducers are shown as a separate item (Unallocated Autoproducers).\n\nLimitations and exceptions: As a response to the objectives of the UNFCCC, the IEA Secretariat, together with the IPCC, the OECD and umerous international experts, has helped to develop and refine an internationally-agreed methodology for the calculation and reporting of national greenhouse-gas emissions from fuel combustion. This methodology was published in 1995 in the IPCC Guidelines for National Greenhouse Gas Inventories. After the initial dissemination of the methodology, revisions were added to several chapters, and published as the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (1996 IPCC Guidelines). In April 2006, the IPCC approved the 2006 Guidelines at the 25th session of the IPCC in Mauritius. For now, most countries (as well as the IEA Secretariat) are still calculating their inventories using the 1996 IPCC Guidelines.1. Both the 1996 IPCC Guidelines and the 2006 IPCC Guidelines are available from the IPCC Greenhouse Gas Inventories Programme (www.ipcc-nggip.iges.or.jp).\n\nSince the IPCC methodology for fuel combustion is largely based on energy balances, the IEA estimates for CO2 from fuel combustion have been calculated using the IEA energy balances and the default IPCC methodology. However, other possibly more detailed methodologies may be used by Parties to calculate their inventories. This may lead to different estimates of emissions.\n\nThe carbon dioxide emissions of a country are only an indicator of one greenhouse gas. For a more complete idea of how a country influences climate change, gases such as methane and nitrous oxide should be taken into account. This is particularly important in agricultural economies.\n\nStatistical concept and methodology: Carbon dioxide emissions account for the largest share of greenhouse gases, which are associated with global warming. In 2010 the International Energy Agency (IEA) released data on carbon dioxide emissions by sector for the first time, allowing a more comprehensive understanding of each sector's contribution to total emissions. The sectoral approach yields data on carbon dioxide emissions from fuel combustion (Intergovernmental Panel on Climate Change [IPCC] source/sink category 1A) as calculated using the IPCC tier 1 sectoral approach.\n\nCarbon dioxide emissions from transport are emissions from fuel combustion for all transport activity (IPCC source/sink category 1A3), including domestic aviation, domestic navigation, road, rail, and pipeline transport but excluding international marine bunkers and international aviation. The IEA data do not allow energy consumption to be categorized by end-use, and thus emissions from autoproducers are listed separately under unallocated autoproducers.\n\nCarbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced.", "origins": [ { "producer": "International Energy Agency", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total fuel combustion", "short_unit": "%" }, "en_fsh_thrd_no": { "title": "Fish species, threatened", "description_from_producer": "Fish species are based on Froese, R. and Pauly, D. (eds). 2008. Threatened species are the number of species classified by the IUCN as endangered, vulnerable, rare, indeterminate, out of danger, or insufficiently known.\n\nLimitations and exceptions: Reporting the proportion of threatened species on the Red List is complicated by the fact that not all species groups have been fully evaluated, and also by the fact that some species have so little information available that they can only be assessed as Data Deficient (DD). For many of the incompletely evaluated groups, assessment efforts have focused on species that are likely to be threatened; therefore any percentage of threatened species reported for these groups would be heavily biased (i.e., the percentage of threatened species would likely be an overestimate).\n\nSince IUCN has evaluated extinction risk for less than 5 percent of the world's described species, IUCN cannot provide an overall estimate for how many of the planet's species are threatened. For those groups that have been comprehensively evaluated, the proportion of threatened species can be calculated, but the number of threatened species is often uncertain because it is not known whether Data Deficient species are actually threatened or not.\n\nDue to variations in consistency and methods of collection, data quality is highly variable across countries. Some countries update their information more frequently than others, some have more accurate data on extent of coverage, and many underreport the number or extent of protected areas. Also, because of differences in definitions, reporting practices, and reporting periods, cross-country comparability of threatened species is limited.\n\nIn order to ensure global uniformity when describing the habitat in which a taxon (a taxonomic group of any rank) occurs, the threats to a taxon, what conservation actions are in place or are needed, and whether or not the taxon is utilized, a set of standard terms, called Classification Schemes, are being developed, for documenting taxonomy on the IUCN Red List.\n\nStatistical concept and methodology: Species assessed as Critically Endangered (CR), Endangered (EN) or Vulnerable (VU) are referred to as \"threatened\" species. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species collects and disseminates information on the global threated species.\n\nProportion of threatened species is only reported for the more completely evaluated groups (i.e., >90% of species evaluated). Also, the reported percentage of threatened species for each group is presented as a best estimate within a range of possible values bounded by lower and upper estimates:\n\nLower estimate = % threatened extant species if all Data Deficient species are not threatened, i.e., (CR + EN + VU) / (total assessed - EX)\n\nBest estimate = % threatened extant species if Data Deficient species are equally threatened as data sufficient species, i.e., (CR + EN + VU) / (total assessed - EX - DD)\n\nUpper estimate = % threatened extant species if all Data Deficient species are threatened, i.e., (CR + EN + VU + DD) / (total assessed - EX)\n\nAdditional information on ecology and habitat preferences, threats, and conservation action are also collated and assessed as part of Red List process.", "origins": [ { "producer": "Froese and Pauly (2008) via World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "en_hpt_thrd_no": { "title": "Plant species (higher), threatened", "description_from_producer": "Higher plants are native vascular plant species. Threatened species are the number of species classified by the IUCN as endangered, vulnerable, rare, indeterminate, out of danger, or insufficiently known.\n\nLimitations and exceptions: Reporting the proportion of threatened species on the Red List is complicated by the fact that not all species groups have been fully evaluated, and also by the fact that some species have so little information available that they can only be assessed as Data Deficient (DD). For many of the incompletely evaluated groups, assessment efforts have focused on species that are likely to be threatened; therefore any percentage of threatened species reported for these groups would be heavily biased (i.e., the percentage of threatened species would likely be an overestimate).\n\nAlthough there are over 12,000 plant species on the IUCN Red List, fewer than one thousand of these are properly documented. To help address this gap, IUCN is pursuing global assessments of plant species of value to people including species of high economic value. The conifer and cycad species already on the IUCN Red List need to be fully documented. IUCN is also developing a tool to assist with preliminary assessments of plant species.\n\nSince IUCN has evaluated extinction risk for less than 5 percent of the world's described species, IUCN cannot provide an overall estimate for how many of the planet's species are threatened. For those groups that have been comprehensively evaluated, the proportion of threatened species can be calculated, but the number of threatened species is often uncertain because it is not known whether Data Deficient species are actually threatened or not.\n\nDue to variations in consistency and methods of collection, data quality is highly variable across countries. Some countries update their information more frequently than others, some have more accurate data on extent of coverage, and many underreport the number or extent of protected areas. Also, because of differences in definitions, reporting practices, and reporting periods, cross-country comparability of threatened species is limited.\n\nIn order to ensure global uniformity when describing the habitat in which a taxon (a taxonomic group of any rank) occurs, the threats to a taxon, what conservation actions are in place or are needed, and whether or not the taxon is utilized, a set of standard terms, called Classification Schemes, are being developed, for documenting taxonomy on the IUCN Red List.\n\nStatistical concept and methodology: Species assessed as Critically Endangered (CR), Endangered (EN) or Vulnerable (VU) are referred to as \"threatened\" species. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species collects and disseminates information on the global threated species.\n\nProportion of threatened species is only reported for the more completely evaluated groups (i.e., >90% of species evaluated). Also, the reported percentage of threatened species for each group is presented as a best estimate within a range of possible values bounded by lower and upper estimates:\n\nLower estimate = % threatened extant species if all Data Deficient species are not threatened, i.e., (CR + EN + VU) / (total assessed - EX)\n\nBest estimate = % threatened extant species if Data Deficient species are equally threatened as data sufficient species, i.e., (CR + EN + VU) / (total assessed - EX - DD)\n\nUpper estimate = % threatened extant species if all Data Deficient species are threatened, i.e., (CR + EN + VU + DD) / (total assessed - EX)\n\nAdditional information on ecology and habitat preferences, threats, and conservation action are also collated and assessed as part of Red List process.", "origins": [ { "producer": "International Union for Conservation of Nature (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "higher", "short_unit": "higher" }, "en_mam_thrd_no": { "title": "Mammal species, threatened", "description_from_producer": "Mammal species are mammals excluding whales and porpoises. Threatened species are the number of species classified by the IUCN as endangered, vulnerable, rare, indeterminate, out of danger, or insufficiently known.\n\nLimitations and exceptions: Reporting the proportion of threatened species on the Red List is complicated by the fact that not all species groups have been fully evaluated, and also by the fact that some species have so little information available that they can only be assessed as Data Deficient (DD). For many of the incompletely evaluated groups, assessment efforts have focused on species that are likely to be threatened; therefore any percentage of threatened species reported for these groups would be heavily biased (i.e., the percentage of threatened species would likely be an overestimate).\n\nSome parts of the world, such as the Andes, Central and West Africa, Angola, parts of South and Southeast Asia, and Melanesia, still have sparse information available of their mammal faunas. In addition, many species' names, especially in the tropics, actually represent complexes of several species that have not yet been resolved. The information on the relative importance of different threatening processes to mammal species is incomplete. IUCN codes all threats that appear to have an important impact, but not their relative importance for each species.\n\nSince IUCN has evaluated extinction risk for less than 5 percent of the world's described species, IUCN cannot provide an overall estimate for how many of the planet's species are threatened. For those groups that have been comprehensively evaluated, the proportion of threatened species can be calculated, but the number of threatened species is often uncertain because it is not known whether Data Deficient species are actually threatened or not.\n\nDue to variations in consistency and methods of collection, data quality is highly variable across countries. Some countries update their information more frequently than others, some have more accurate data on extent of coverage, and many underreport the number or extent of protected areas. Also, because of differences in definitions, reporting practices, and reporting periods, cross-country comparability of threatened species is limited.\n\nIn order to ensure global uniformity when describing the habitat in which a taxon (a taxonomic group of any rank) occurs, the threats to a taxon, what conservation actions are in place or are needed, and whether or not the taxon is utilized, a set of standard terms, called Classification Schemes, are being developed, for documenting taxonomy on the IUCN Red List.\n\nStatistical concept and methodology: Species assessed as Critically Endangered (CR), Endangered (EN) or Vulnerable (VU) are referred to as \"threatened\" species. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species collects and disseminates information on the global threated species.\n\nProportion of threatened species is only reported for the more completely evaluated groups (i.e., >90% of species evaluated). Also, the reported percentage of threatened species for each group is presented as a best estimate within a range of possible values bounded by lower and upper estimates:\n\nLower estimate = % threatened extant species if all Data Deficient species are not threatened, i.e., (CR + EN + VU) / (total assessed - EX)\n\nBest estimate = % threatened extant species if Data Deficient species are equally threatened as data sufficient species, i.e., (CR + EN + VU) / (total assessed - EX - DD)\n\nUpper estimate = % threatened extant species if all Data Deficient species are threatened, i.e., (CR + EN + VU + DD) / (total assessed - EX)\n\nAdditional information on ecology and habitat preferences, threats, and conservation action are also collated and assessed as part of Red List process.", "origins": [ { "producer": "International Union for Conservation of Nature (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "en_pop_dnst": { "title": "Population density (people per sq. km of land area)", "description_from_producer": "Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.\n\nLimitations and exceptions: Current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data are provided by the United Nations Population Division and other agencies. The cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in the model and in the data. Because the five-year age group is the cohort unit and five-year period data are used, interpolations to obtain annual data or single age structure may not reflect actual events or age composition.\n\nThe quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data.\n\nStatistical concept and methodology: Population density is midyear population divided by land area in square kilometers. This ratio can be calculated for any territorial unit for any point in time, depending on the source of the population data. Populationestimates are prepared by World Bank staff from variety of sources. They are based on the de facto definition of population and include all residents regardless of legal status or citizenship, within the physical boundaries of a country and under the jurisdiction of that country's political control. Refugees not permanently settled in the country of asylum are considered part of the population of their country of origin. Population numbers are either current census data or historical census data extrapolated through demographic methods. The count also excludes visitors from overseas.\n\nPopulation density is calculated by dividing midyear population by land area in a country. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship - except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "people per sq. km of land area", "short_unit": "people" }, "en_pop_el5m_ru_zs": { "title": "Rural population living in areas where elevation is below 5 meters (% of total population)", "description_from_producer": "Rural population below 5m is the percentage of the total population, living in areas where the elevation is 5 meters or less.\n\nStatistical concept and methodology: Population counts in low elevation zones in the year 1990 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2000 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2010 derived from the application of United Nations 2000-2010 national growth rates to year 2000 population data from GRUMPv1 ( see documentation for full description of methodologies ).", "origins": [ { "producer": "CIESIN and CIDR (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total population", "short_unit": "%" }, "en_pop_el5m_ur_zs": { "title": "Urban population living in areas where elevation is below 5 meters (% of total population)", "description_from_producer": "Urban population below 5m is the percentage of the total population, living in areas where the elevation is 5 meters or less.\n\nStatistical concept and methodology: Population counts in low elevation zones in the year 1990 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2000 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2010 derived from the application of United Nations 2000-2010 national growth rates to year 2000 population data from GRUMPv1 ( see documentation for full description of methodologies ).", "origins": [ { "producer": "CIESIN and CIDR (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total population", "short_unit": "%" }, "en_pop_el5m_zs": { "title": "Population living in areas where elevation is below 5 meters (% of total population)", "description_from_producer": "Population below 5m is the percentage of the total population living in areas where the elevation is 5 meters or less.\n\nLimitations and exceptions: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is \u201cunequivocal\u201d and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20\u201386 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5\u00b0C by 2100 (Kattenberg and others 1996) and increase of \u201ckiller\u201d heat waves during the warm season (Karl and others 1997).\n\nStatistical concept and methodology: Population counts in low elevation zones in the year 1990 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2000 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2010 derived from the application of United Nations 2000-2010 national growth rates to year 2000 population data from GRUMPv1 (see documentation for full description of methodologies).", "origins": [ { "producer": "CIESIN and CIDR (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total population", "short_unit": "%" }, "en_pop_slum_ur_zs": { "title": "Population living in slums (% of urban population)", "description_from_producer": "Population living in slums is the proportion of the urban population living in slum households. A slum household is defined as a group of individuals living under the same roof lacking one or more of the following conditions: access to improved water, access to improved sanitation, sufficient living area, housing durability, and security of tenure, as adopted in the Millennium Development Goal Target 7.D. The successor, the Sustainable Development Goal 11.1.1, considers inadequate housing (housing affordability) to complement the above definition of slums/informal settlements.", "origins": [ { "producer": "UN-HABITAT (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of urban population", "short_unit": "%" }, "en_urb_lcty": { "title": "Population in largest city", "description_from_producer": "Population in largest city is the urban population living in the country's largest metropolitan area.\n\nLimitations and exceptions: Aggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.\n\nMost countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries. For example, in Botswana, agglomeration of 5,000 or more inhabitants where 75 per cent of the economic activity is non-agricultural is considered \"urban\" while in Iceland localities of 200 or more inhabitants, and in Peru population centers with 100 or more dwellings, are considered \"urban.\" In the United States places of 2,500 or more inhabitants, generally having population densities of 1,000 persons per square mile or more are considered \"urban\".\n\nEstimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers. According to China's State Statistical Bureau, by the end of 1996 urban residents accounted for about 43 percent of China's population, more than double the 20 percent considered urban in 1994. In addition to the continuous migration of people from rural to urban areas, one of the main reasons for this shift was the rapid growth in the hundreds of towns reclassified as cities in recent years.\n\nBecause the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.\n\nStatistical concept and methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. The United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data. The cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in the model and in the data. Because the five-year age group is the cohort unit and five-year period data are used, interpolations to obtain annual data or single age structure may not reflect actual events or age composition.\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" Typically, a community or settlement with a population of 2,000 or more is considered urban, but national definitions are most commonly based on size of locality. Eurostat defines urban areas as clusters of contiguous grid cells of 1 km2 with a density of at least 300 inhabitants per km2 and a minimum population of 5,000. Further it defines high-density cluster as contiguous grid cells of 1 km2 with a density of at least 1,500 inhabitants per km2 and a minimum population of 50,000.\n\nThe population of a city or metropolitan area depends on the boundaries chosen. For example, in 1990 Beijing, China, contained 2.3 million people in 87 square kilometers of \"inner city\" and 5.4 million in 158 square kilometers of \"core city.\" The population of \"inner city and inner suburban districts\" was 6.3 million and that of \"inner city, inner and outer suburban districts, and inner and outer counties\" was 10.8 million. (Most countries use the last definition.)", "origins": [ { "producer": "UN Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "en_urb_lcty_ur_zs": { "title": "Population in the largest city (% of urban population)", "description_from_producer": "Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.\n\nLimitations and exceptions: Aggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.\n\nMost countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries. For example, in Botswana, agglomeration of 5,000 or more inhabitants where 75 per cent of the economic activity is non-agricultural is considered \"urban\" while in Iceland localities of 200 or more inhabitants, and in Peru population centers with 100 or more dwellings, are considered \"urban.\" In the United States places of 2,500 or more inhabitants, generally having population densities of 1,000 persons per square mile or more are considered \"urban\".\n\nEstimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers. According to China's State Statistical Bureau, by the end of 1996 urban residents accounted for about 43 percent of China's population, more than double the 20 percent considered urban in 1994. In addition to the continuous migration of people from rural to urban areas, one of the main reasons for this shift was the rapid growth in the hundreds of towns reclassified as cities in recent years.\n\nBecause the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.\n\nStatistical concept and methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. The United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data. The cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in the model and in the data. Because the five-year age group is the cohort unit and five-year period data are used, interpolations to obtain annual data or single age structure may not reflect actual events or age composition.\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" Typically, a community or settlement with a population of 2,000 or more is considered urban, but national definitions are most commonly based on size of locality. Eurostat defines urban areas as clusters of contiguous grid cells of 1 km2 with a density of at least 300 inhabitants per km2 and a minimum population of 5,000. Further it defines high-density cluster as contiguous grid cells of 1 km2 with a density of at least 1,500 inhabitants per km2 and a minimum population of 50,000.\n\nThe population of a city or metropolitan area depends on the boundaries chosen. For example, in 1990 Beijing, China, contained 2.3 million people in 87 square kilometers of \"inner city\" and 5.4 million in 158 square kilometers of \"core city.\" The population of \"inner city and inner suburban districts\" was 6.3 million and that of \"inner city, inner and outer suburban districts, and inner and outer counties\" was 10.8 million. (Most countries use the last definition.)", "origins": [ { "producer": "UN Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of urban population", "short_unit": "%" }, "en_urb_mcty": { "title": "Population in urban agglomerations of more than 1 million", "description_from_producer": "Population in urban agglomerations of more than one million is the country's population living in metropolitan areas that in 2018 had a population of more than one million people.\n\nLimitations and exceptions: Due to varying definitions, it is not possible to compare different agglomerations around the world.\n\nAggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.\n\nMost countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries. For example, in Botswana, agglomeration of 5,000 or more inhabitants where 75 per cent of the economic activity is non-agricultural is considered \"urban\" while in Iceland localities of 200 or more inhabitants, and in Peru population centers with 100 or more dwellings, are considered \"urban.\" In the United States places of 2,500 or more inhabitants, generally having population densities of 1,000 persons per square mile or more are considered \"urban\".\n\nEstimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers. According to China's State Statistical Bureau, by the end of 1996 urban residents accounted for about 43 percent of China's population, more than double the 20 percent considered urban in 1994. In addition to the continuous migration of people from rural to urban areas, one of the main reasons for this shift was the rapid growth in the hundreds of towns reclassified as cities in recent years.\n\nBecause the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.\n\nStatistical concept and methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. The United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data. The cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in the model and in the data. Because the five-year age group is the cohort unit and five-year period data are used, interpolations to obtain annual data or single age structure may not reflect actual events or age composition.\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" Typically, a community or settlement with a population of 2,000 or more is considered urban, but national definitions are most commonly based on size of locality. Eurostat defines urban areas as clusters of contiguous grid cells of 1 km2 with a density of at least 300 inhabitants per km2 and a minimum population of 5,000. Further it defines high-density cluster as contiguous grid cells of 1 km2 with a density of at least 1,500 inhabitants per km2 and a minimum population of 50,000.\n\nThe population of a city or metropolitan area depends on the boundaries chosen. For example, in 1990 Beijing, China, contained 2.3 million people in 87 square kilometers of \"inner city\" and 5.4 million in 158 square kilometers of \"core city.\" The population of \"inner city and inner suburban districts\" was 6.3 million and that of \"inner city, inner and outer suburban districts, and inner and outer counties\" was 10.8 million. (Most countries use the last definition.)", "origins": [ { "producer": "UN Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "en_urb_mcty_tl_zs": { "title": "Population in urban agglomerations of more than 1 million (% of total population)", "description_from_producer": "Population in urban agglomerations of more than one million is the percentage of a country's population living in metropolitan areas that in 2018 had a population of more than one million people.\n\nLimitations and exceptions: Due to varying definitions, it is not possible to compare different agglomerations around the world.\n\nAggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.\n\nMost countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries. For example, in Botswana, agglomeration of 5,000 or more inhabitants where 75 per cent of the economic activity is non-agricultural is considered \"urban\" while in Iceland localities of 200 or more inhabitants, and in Peru population centers with 100 or more dwellings, are considered \"urban.\" In the United States places of 2,500 or more inhabitants, generally having population densities of 1,000 persons per square mile or more are considered \"urban\".\n\nEstimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers. According to China's State Statistical Bureau, by the end of 1996 urban residents accounted for about 43 percent of China's population, more than double the 20 percent considered urban in 1994. In addition to the continuous migration of people from rural to urban areas, one of the main reasons for this shift was the rapid growth in the hundreds of towns reclassified as cities in recent years.\n\nBecause the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.\n\nStatistical concept and methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. The United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data. The cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in the model and in the data. Because the five-year age group is the cohort unit and five-year period data are used, interpolations to obtain annual data or single age structure may not reflect actual events or age composition.\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" Typically, a community or settlement with a population of 2,000 or more is considered urban, but national definitions are most commonly based on size of locality. Eurostat defines urban areas as clusters of contiguous grid cells of 1 km2 with a density of at least 300 inhabitants per km2 and a minimum population of 5,000. Further it defines high-density cluster as contiguous grid cells of 1 km2 with a density of at least 1,500 inhabitants per km2 and a minimum population of 50,000.\n\nThe population of a city or metropolitan area depends on the boundaries chosen. For example, in 1990 Beijing, China, contained 2.3 million people in 87 square kilometers of \"inner city\" and 5.4 million in 158 square kilometers of \"core city.\" The population of \"inner city and inner suburban districts\" was 6.3 million and that of \"inner city, inner and outer suburban districts, and inner and outer counties\" was 10.8 million. (Most countries use the last definition.)", "origins": [ { "producer": "UN Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total population", "short_unit": "%" }, "ep_pmp_desl_cd": { "title": "Pump price for diesel fuel (US$ per liter)", "description_from_producer": "Fuel prices refer to the pump prices of the most widely sold grade of diesel fuel. Prices have been converted from the local currency to U.S. dollars.\n\nStatistical concept and methodology: Data on fuel prices are compiled by the German Agency for International Cooperation (GIZ), from its global network and other sources, including the Allgemeiner Deutscher Automobile Club (for Europe) and the Latin American Energy Organization (for Latin America). Local prices are converted to U.S. dollars using the exchange rate in the Financial Times international monetary table on the survey date. When multiple exchange rates exist, the market, parallel, or black market rate is used.", "origins": [ { "producer": "German Agency for International Cooperation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "US$ per liter", "short_unit": "$" }, "ep_pmp_sgas_cd": { "title": "Pump price for gasoline (US$ per liter)", "description_from_producer": "Fuel prices refer to the pump prices of the most widely sold grade of gasoline. Prices have been converted from the local currency to U.S. dollars.\n\nStatistical concept and methodology: Data on fuel prices are compiled by the German Agency for International Cooperation (GIZ), from its global network and other sources, including the Allgemeiner Deutscher Automobile Club (for Europe) and the Latin American Energy Organization (for Latin America). Local prices are converted to U.S. dollars using the exchange rate in the Financial Times international monetary table on the survey date. When multiple exchange rates exist, the market, parallel, or black market rate is used.", "origins": [ { "producer": "German Agency for International Cooperation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "US$ per liter", "short_unit": "$" }, "er_fsh_aqua_mt": { "title": "Aquaculture production (metric tons)", "description_from_producer": "Aquaculture is understood to mean the farming of aquatic organisms including fish, molluscs, crustaceans and aquatic plants. Aquaculture production specifically refers to output from aquaculture activities, which are designated for final harvest for consumption.\n\nStatistical concept and methodology: Aquaculture production specifically refers to output from aquaculture activities, which are designated for final harvest for consumption. At this time, harvest for ornamental purposes is not included.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "metric tons" }, "er_fsh_capt_mt": { "title": "Capture fisheries production (metric tons)", "description_from_producer": "Capture fisheries production measures the volume of fish catches landed by a country for all commercial, industrial, recreational and subsistence purposes.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "metric tons" }, "er_fsh_prod_mt": { "title": "Total fisheries production (metric tons)", "description_from_producer": "Total fisheries production measures the volume of aquatic species caught by a country for all commercial, industrial, recreational and subsistence purposes. The harvest from mariculture, aquaculture and other kinds of fish farming is also included.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "metric tons" }, "er_gdp_fwtl_m3_kd": { "title": "Water productivity, total (constant 2015 US$ GDP per cubic meter of total freshwater withdrawal)", "description_from_producer": "Water productivity is calculated as GDP in constant prices divided by annual total water withdrawal.\n\nLimitations and exceptions: A common perception is that most of the available freshwater resources are visible (on the surfaces of lakes, reservoirs and rivers). However, this visible water represents only a tiny fraction of global freshwater resources, as most of it is stored in aquifers, with the largest stocks stored in solid form in the Antarctic and in Greenland's ice cap.\n\nThe data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. These estimates are based on different sources and refer to different years, so cross-country comparisons should be made with caution. Because the data are collected intermittently, they may hide significant variations in total renewable water resources from year to year. The data also fail to distinguish between seasonal and geographic variations in water availability within countries. Data for small countries and countries in arid and semiarid zones are less reliable than those for larger countries and countries with greater rainfall.\n\nCaution should also be used in comparing data on annual freshwater withdrawals, which are subject to variations in collection and estimation methods. In addition, inflows and outflows are estimated at different times and at different levels of quality and precision, requiring caution in interpreting the data, particularly for water-short countries, notably in the Middle East and North Africa.\n\nThe data are based on surveys and estimates provided by governments to the Joint Monitoring Programme of the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF). The coverage rates are based on information from service users on actual household use rather than on information from service providers, which may include nonfunctioning systems.\n\nStatistical concept and methodology: Water productivity is an indication only of the efficiency by which each country uses its water resources. Given the different economic structure of each country, these indicators should be used carefully, taking into account a country's sectorial activities and natural resource endowments. GDP data are from World Bank's national accounts files.\n\nWater withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including for cooling thermoelectric plants).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$ GDP per cubic meter of total freshwater withdrawal", "short_unit": "$" }, "er_h2o_fwag_zs": { "title": "Annual freshwater withdrawals, agriculture (% of total freshwater withdrawal)", "description_from_producer": "Annual freshwater withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for agriculture are total withdrawals for irrigation and livestock production. Data are for the most recent year available for 1987-2002.\n\nLimitations and exceptions: A common perception is that most of the available freshwater resources are visible (on the surfaces of lakes, reservoirs and rivers). However, this visible water represents only a tiny fraction of global freshwater resources, as most of it is stored in aquifers, with the largest stocks stored in solid form in the Antarctic and in Greenland's ice cap.\n\nThe data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. These estimates are based on different sources and refer to different years, so cross-country comparisons should be made with caution. Because the data are collected intermittently, they may hide significant variations in total renewable water resources from year to year. The data also fail to distinguish between seasonal and geographic variations in water availability within countries. Data for small countries and countries in arid and semiarid zones are less reliable than those for larger countries and countries with greater rainfall.\n\nCaution should also be used in comparing data on annual freshwater withdrawals, which are subject to variations in collection and estimation methods. In addition, inflows and outflows are estimated at different times and at different levels of quality and precision, requiring caution in interpreting the data, particularly for water-short countries, notably in the Middle East and North Africa.\n\nThe data are based on surveys and estimates provided by governments to the Joint Monitoring Programme of the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF). The coverage rates are based on information from service users on actual household use rather than on information from service providers, which may include nonfunctioning systems.\n\nStatistical concept and methodology: This indicator measures the pressure on the renewable water resources of a country caused by irrigation. According to Commission on Sustainable Development (CSD) agriculture accounts for more than 70 percent of freshwater drawn from lakes, rivers and underground sources. Most is used for irrigation which provides about 40 percent of the world food production. Poor management has resulted in the salinization of about 20 percent of the world's irrigated land, with an additional 1.5 million ha affected annually.\n\nWater withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including for cooling thermoelectric plants).", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total freshwater withdrawal", "short_unit": "%" }, "er_h2o_fwdm_zs": { "title": "Annual freshwater withdrawals, domestic (% of total freshwater withdrawal)", "description_from_producer": "Annual freshwater withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes. Data are for the most recent year available for 1987-2002.\n\nLimitations and exceptions: A common perception is that most of the available freshwater resources are visible (on the surfaces of lakes, reservoirs and rivers). However, this visible water represents only a tiny fraction of global freshwater resources, as most of it is stored in aquifers, with the largest stocks stored in solid form in the Antarctic and in Greenland's ice cap.\n\nThe data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. These estimates are based on different sources and refer to different years, so cross-country comparisons should be made with caution. Because the data are collected intermittently, they may hide significant variations in total renewable water resources from year to year. The data also fail to distinguish between seasonal and geographic variations in water availability within countries. Data for small countries and countries in arid and semiarid zones are less reliable than those for larger countries and countries with greater rainfall.\n\nCaution should also be used in comparing data on annual freshwater withdrawals, which are subject to variations in collection and estimation methods. In addition, inflows and outflows are estimated at different times and at different levels of quality and precision, requiring caution in interpreting the data, particularly for water-short countries, notably in the Middle East and North Africa.\n\nThe data are based on surveys and estimates provided by governments to the Joint Monitoring Programme of the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF). The coverage rates are based on information from service users on actual household use rather than on information from service providers, which may include nonfunctioning systems.\n\nStatistical concept and methodology: Domestic water withdrawal, sometimes used interchangeably with municipal water withdrawal, focuses on human needs (drinking, cooking, cleaning, and sanitation). Data includes renewable freshwater resources, potential over-abstraction of renewable groundwater, withdrawal of fossil groundwater, and the potential use of desalinated water or treated wastewater. It is usually computed as the total water withdrawn by the public distribution network, and includes that part of the industries, which is connected to the municipal network. The ratio between the net consumption and the water withdrawn can vary from 5 to 15 percent in urban areas and from 10 to 50 percent in rural areas.\n\nWater withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total freshwater withdrawal", "short_unit": "%" }, "er_h2o_fwin_zs": { "title": "Annual freshwater withdrawals, industry (% of total freshwater withdrawal)", "description_from_producer": "Annual freshwater withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for industry are total withdrawals for direct industrial use (including withdrawals for cooling thermoelectric plants). Data are for the most recent year available for 1987-2002.\n\nLimitations and exceptions: A common perception is that most of the available freshwater resources are visible (on the surfaces of lakes, reservoirs and rivers). However, this visible water represents only a tiny fraction of global freshwater resources, as most of it is stored in aquifers, with the largest stocks stored in solid form in the Antarctic and in Greenland's ice cap.\n\nThe data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. These estimates are based on different sources and refer to different years, so cross-country comparisons should be made with caution. Because the data are collected intermittently, they may hide significant variations in total renewable water resources from year to year. The data also fail to distinguish between seasonal and geographic variations in water availability within countries. Data for small countries and countries in arid and semiarid zones are less reliable than those for larger countries and countries with greater rainfall.\n\nCaution should also be used in comparing data on annual freshwater withdrawals, which are subject to variations in collection and estimation methods. In addition, inflows and outflows are estimated at different times and at different levels of quality and precision, requiring caution in interpreting the data, particularly for water-short countries, notably in the Middle East and North Africa.\n\nThe data are based on surveys and estimates provided by governments to the Joint Monitoring Programme of the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF). The coverage rates are based on information from service users on actual household use rather than on information from service providers, which may include nonfunctioning systems.\n\nStatistical concept and methodology: Annual industrial freshwater withdrawals include renewable water resources as well as potential over-abstraction of renewable groundwater or potential use of desalinated water or treated wastewater. It includes water for the cooling of thermoelectric plants, but it does not include hydropower.\n\nWater withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for industry are total withdrawals for direct industrial use (including withdrawals for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total freshwater withdrawal", "short_unit": "%" }, "er_h2o_fwst_zs": { "title": "Level of water stress: freshwater withdrawal as a proportion of available freshwater resources", "description_from_producer": "The level of water stress: freshwater withdrawal as a proportion of available freshwater resources is the ratio between total freshwater withdrawn by all major sectors and total renewable freshwater resources, after taking into account environmental water requirements. Main sectors, as defined by ISIC standards, include agriculture; forestry and fishing; manufacturing; electricity industry; and services. This indicator is also known as water withdrawal intensity.\n\nLimitations and exceptions: Water withdrawal as a percentage of water resources is a good indicator of pressure on limited water resources, one of the most important natural resources. However, it only partially addresses the issues related to sustainable water management. Supplementary indicators that capture the multiple dimensions of water management would combine data on water demand management, behavioural changes with regard to water use and the availability of appropriate infrastructure, and measure progress in increasing the efficiency and sustainability of water use, in particular in relation to population and economic growth. They would also recognize the different climatic environments that affect water use in countries, in particular in agriculture, which is the main user of water. Sustainability assessment is also linked to the critical thresholds fixed for this indicator and there is no universal consensus on such threshold.\n\nTrends in water withdrawal show relatively slow patterns of change. Usually, three-five years are a minimum frequency to be able to detect significant changes, as it is unlikely that the indicator would show meaningful variations from one year to the other. Estimation of water withdrawal by sector is the main limitation to the computation of the indicator. Few countries actually publish water use data on a regular basis by sector. Renewable water resources include all surface water and groundwater resources that are available on a yearly basis without consideration of the capacity to harvest and use this resource. Exploitable water resources, which refer to the volume of surface water or groundwater that is available with an occurrence of 90% of the time, are considerably less than renewable water resources, but no universal method exists to assess such exploitable water resources. There is no universally agreed method for the computation of incoming freshwater flows originating outside of a country's borders. Nor is there any standard method to account for return flows, the part of the water withdrawn from its source and which flows back to the river system after use. In countries where return flow represents a substantial part of water withdrawal, the indicator tends to underestimate available water and therefore overestimate the level of water stress.\n\nOther limitations that affect the interpretation of the water stress indicator include: difficulty to obtain accurate, complete and up-to-date data; potentially large variation of sub-national data; lack of account of seasonal variations in water resources; lack of consideration to the distribution among water uses; lack of consideration of water quality and its suitability for use; and the indicator can be higher than 100 per cent when water withdrawal includes secondary freshwater (water withdrawn previously and returned to the system), non-renewable water (fossil groundwater), when annual groundwater withdrawal is higher than annual replenishment (over-abstraction) or when water withdrawal includes part or all of the water set aside for environmental water requirements. Some of these issues can be solved through disaggregation of the index at the level of hydrological units and by distinguishing between different use sectors. However, due to the complexity of water flows, both within a country and between countries, care should be taken not to double-count.\n\nStatistical concept and methodology: Proportion of total renewable water resources withdrawn is the total volume of groundwater and surface water withdrawn from their sources for human use (in the agricultural, municipal and industrial sectors), expressed as a percentage of the total actual renewable water resources. The terms water resources and water withdrawal are understood as freshwater resources and freshwater withdrawal. Water withdrawal is estimated for the following three main sectors: agriculture, municipalities (including domestic water withdrawal) and industries, at country level and expressed in km3/year. The total actual renewable water resources for a country or region are defined as the sum of internal renewable water resources and the external renewable water resources, also expressed in km3/year. The indicator is computed by dividing total water withdrawal by total actual renewable water resources minus environmental requirements and expressed in percentage points.\n\nTotal freshwater withdrawal is the volume of freshwater extracted from its source (rivers, lakes, aquifers) for agriculture, industries and municipalities. It is estimated at the country level for the following three main sectors: agriculture, municipalities (including domestic water withdrawal) and industries. Freshwater withdrawal includes primary freshwater (not withdrawn before), secondary freshwater (previously withdrawn and returned to rivers and groundwater, such as discharged wastewater and agricultural drainage water) and fossil groundwater. It does not include non-conventional water, i.e. direct use of treated wastewater, direct use of agricultural drainage water and desalinated water. Total freshwater withdrawal is in general calculated as being the sum of total water withdrawal by sector minus direct use of wastewater, direct use of agricultural drainage water and use of desalinated water.\n\nTotal renewable freshwater resources are expressed as the sum of internal and external renewable water resources. The terms \u201cwater resources\u201d and \u201cwater withdrawal\u201d are understood here as freshwater resources and freshwater withdrawal. Internal renewable water resources are defined as the long-term average annual flow of rivers and recharge of groundwater for a given country generated from endogenous precipitation. External renewable water resources refer to the flows of water entering the country, taking into consideration the quantity of flows reserved to upstream and downstream countries through agreements or treaties.\n\nEnvironmental water requirements (Env.) are the quantities of water required to sustain freshwater and estuarine ecosystems. Water quality and also the resulting ecosystem services are excluded from this formulation which is confined to water volumes. This does not imply that quality and the support to societies which are dependent on environmental flows are not important and should not be taken care of. Methods of computation of Env. are extremely variable and range from global estimates to comprehensive assessments for river reaches. Water volumes can be expressed in the same units as the total freshwater withdrawal, and then as percentages of the available water resources.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "er_h2o_fwtl_k3": { "title": "Annual freshwater withdrawals, total (billion cubic meters)", "description_from_producer": "Annual freshwater withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including withdrawals for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes. Data are for the most recent year available for 1987-2002.\n\nLimitations and exceptions: A common perception is that most of the available freshwater resources are visible (on the surfaces of lakes, reservoirs and rivers). However, this visible water represents only a tiny fraction of global freshwater resources, as most of it is stored in aquifers, with the largest stocks stored in solid form in the Antarctic and in Greenland's ice cap.\n\nThe data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. These estimates are based on different sources and refer to different years, so cross-country comparisons should be made with caution. Because the data are collected intermittently, they may hide significant variations in total renewable water resources from year to year. The data also fail to distinguish between seasonal and geographic variations in water availability within countries. Data for small countries and countries in arid and semiarid zones are less reliable than those for larger countries and countries with greater rainfall.\n\nCaution should also be used in comparing data on annual freshwater withdrawals, which are subject to variations in collection and estimation methods. In addition, inflows and outflows are estimated at different times and at different levels of quality and precision, requiring caution in interpreting the data, particularly for water-short countries, notably in the Middle East and North Africa.\n\nThe data are based on surveys and estimates provided by governments to the Joint Monitoring Programme of the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF). The coverage rates are based on information from service users on actual household use rather than on information from service providers, which may include nonfunctioning systems.\n\nStatistical concept and methodology: Annual freshwater withdrawals are total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Water withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "billion cubic meters" }, "er_h2o_fwtl_zs": { "title": "Annual freshwater withdrawals, total (% of internal resources)", "description_from_producer": "Annual freshwater withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including withdrawals for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes. Data are for the most recent year available for 1987-2002.\n\nLimitations and exceptions: A common perception is that most of the available freshwater resources are visible (on the surfaces of lakes, reservoirs and rivers). However, this visible water represents only a tiny fraction of global freshwater resources, as most of it is stored in aquifers, with the largest stocks stored in solid form in the Antarctic and in Greenland's ice cap.\n\nThe data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. These estimates are based on different sources and refer to different years, so cross-country comparisons should be made with caution. Because the data are collected intermittently, they may hide significant variations in total renewable water resources from year to year. The data also fail to distinguish between seasonal and geographic variations in water availability within countries. Data for small countries and countries in arid and semiarid zones are less reliable than those for larger countries and countries with greater rainfall.\n\nCaution should also be used in comparing data on annual freshwater withdrawals, which are subject to variations in collection and estimation methods. In addition, inflows and outflows are estimated at different times and at different levels of quality and precision, requiring caution in interpreting the data, particularly for water-short countries, notably in the Middle East and North Africa.\n\nThe data are based on surveys and estimates provided by governments to the Joint Monitoring Programme of the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF). The coverage rates are based on information from service users on actual household use rather than on information from service providers, which may include nonfunctioning systems.\n\nStatistical concept and methodology: Annual freshwater withdrawals are total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of internal resources", "short_unit": "%" }, "er_h2o_intr_k3": { "title": "Renewable internal freshwater resources, total (billion cubic meters)", "description_from_producer": "Renewable internal freshwater resources flows refer to internal renewable resources (internal river flows and groundwater from rainfall) in the country.\n\nLimitations and exceptions: A common perception is that most of the available freshwater resources are visible (on the surfaces of lakes, reservoirs and rivers). However, this visible water represents only a tiny fraction of global freshwater resources, as most of it is stored in aquifers, with the largest stocks stored in solid form in the Antarctic and in Greenland's ice cap.\n\nThe data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. These estimates are based on different sources and refer to different years, so cross-country comparisons should be made with caution. Because the data are collected intermittently, they may hide significant variations in total renewable water resources from year to year. The data also fail to distinguish between seasonal and geographic variations in water availability within countries. Data for small countries and countries in arid and semiarid zones are less reliable than those for larger countries and countries with greater rainfall.\n\nCaution should also be used in comparing data on annual freshwater withdrawals, which are subject to variations in collection and estimation methods. In addition, inflows and outflows are estimated at different times and at different levels of quality and precision, requiring caution in interpreting the data, particularly for water-short countries, notably in the Middle East and North Africa.\n\nThe data are based on surveys and estimates provided by governments to the Joint Monitoring Programme of the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF). The coverage rates are based on information from service users on actual household use rather than on information from service providers, which may include nonfunctioning systems.\n\nStatistical concept and methodology: The data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. Renewable water resources (internal and external) include average annual flow of rivers and recharge of aquifers generated from endogenous precipitation, and those water resources that are not generated in the country, such as inflows from upstream countries (groundwater and surface water), and part of the water of border lakes and/or rivers. Non-renewable water includes groundwater bodies (deep aquifers) that have a negligible rate of recharge on the human time-scale. While renewable water resources are expressed in flows, non-renewable water resources have to be expressed in quantity (stock). Runoff from glaciers where the mass balance is negative is considered non-renewable.\n\nTotal actual renewable water resources correspond to the maximum theoretical yearly amount of water actually available for a country at a given moment. The unit of calculation is km3/year or 109 m3/year. Calculation Criteria is [Water resources: total renewable (actual)] = [Surface water: total renewable (actual)] + [Groundwater: total renewable (actual)] - [Overlap between surface water and groundwater].*\n\nFresh water is naturally occurring water on the Earth's surface. It is a renewable but limited natural resource. Fresh water can only be renewed through the process of the water cycle, where water from seas, lakes, forests, land, rivers, and dams evaporates, forms clouds, and returns as precipitation. However, if more fresh water is consumed through human activities than is restored by nature, the result is that the quantity of fresh water available in lakes, rivers, dams and underground waters can be reduced which can cause serious damage to the surrounding environment.\n\n* http://www.fao.org/nr/water/aquastat/data/glossary/search.html?termId=4188&submitBtn=s&cls=yes", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "billion cubic meters" }, "er_h2o_intr_pc": { "title": "Renewable internal freshwater resources per capita (cubic meters)", "description_from_producer": "Renewable internal freshwater resources flows refer to internal renewable resources (internal river flows and groundwater from rainfall) in the country. Renewable internal freshwater resources per capita are calculated using the World Bank's population estimates.\n\nLimitations and exceptions: A common perception is that most of the available freshwater resources are visible (on the surfaces of lakes, reservoirs and rivers). However, this visible water represents only a tiny fraction of global freshwater resources, as most of it is stored in aquifers, with the largest stocks stored in solid form in the Antarctic and in Greenland's ice cap.\n\nThe data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. These estimates are based on different sources and refer to different years, so cross-country comparisons should be made with caution. Because the data are collected intermittently, they may hide significant variations in total renewable water resources from year to year. The data also fail to distinguish between seasonal and geographic variations in water availability within countries. Data for small countries and countries in arid and semiarid zones are less reliable than those for larger countries and countries with greater rainfall.\n\nCaution should also be used in comparing data on annual freshwater withdrawals, which are subject to variations in collection and estimation methods. In addition, inflows and outflows are estimated at different times and at different levels of quality and precision, requiring caution in interpreting the data, particularly for water-short countries, notably in the Middle East and North Africa.\n\nThe data are based on surveys and estimates provided by governments to the Joint Monitoring Programme of the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF). The coverage rates are based on information from service users on actual household use rather than on information from service providers, which may include nonfunctioning systems.\n\nStatistical concept and methodology: Renewable water resources (internal and external) include average annual flow of rivers and recharge of aquifers generated from endogenous precipitation, and those water resources that are not generated in the country, such as inflows from upstream countries (groundwater and surface water), and part of the water of border lakes and/or rivers. Non-renewable water includes groundwater bodies (deep aquifers) that have a negligible rate of recharge on the human time-scale. While renewable water resources are expressed in flows, non-renewable water resources have to be expressed in quantity (stock). Runoff from glaciers where the mass balance is negative is considered non-renewable. Renewable internal freshwater resources per capita are calculated using the World Bank's population estimates. The unit of calculation is m3/year per inhabitant. Internal renewable freshwater resources per capita are calculated using the World Bank's population estimates.\n\nTotal actual renewable water resources correspond to the maximum theoretical yearly amount of water actually available for a country at a given moment. The unit of calculation is km3/year or 109 m3/year. Calculation Criteria is [Water resources: total renewable (actual)] = [Surface water: total renewable (actual)] + [Groundwater: total renewable (actual)] - [Overlap between surface water and groundwater].*\n\nFresh water is naturally occurring water on the Earth's surface. It is a renewable but limited natural resource. Fresh water can only be renewed through the process of the water cycle, where water from seas, lakes, forests, land, rivers, and dams evaporates, forms clouds, and returns as precipitation. However, if more fresh water is consumed through human activities than is restored by nature, the result is that the quantity of fresh water available in lakes, rivers, dams and underground waters can be reduced which can cause serious damage to the surrounding environment.\n\n* http://www.fao.org/nr/water/aquastat/data/glossary/search.html?termId=4188&submitBtn=s&cls=yes", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cubic meters" }, "er_lnd_ptld_zs": { "title": "Terrestrial protected areas (% of total land area)", "description_from_producer": "Terrestrial protected areas are totally or partially protected areas of at least 1,000 hectares that are designated by national authorities as scientific reserves with limited public access, national parks, natural monuments, nature reserves or wildlife sanctuaries, protected landscapes, and areas managed mainly for sustainable use. Marine areas, unclassified areas, littoral (intertidal) areas, and sites protected under local or provincial law are excluded.\n\nLimitations and exceptions: The data source for this indicator is the World Database on Protected Areas (WDPA), the most comprehensive global dataset on marine and terrestrial protected areas available.\n\nThe extent to which the land areas, including inland waters, and territorial waters of a country/territory are protected is useful for planning purpose to protect biodiversity. However, it is neither an indication of how well managed the terrestrial and marine protected areas are, nor confirmation that protection measures are effectively enforced. Further, the indicator does not provide information on non-designated or internationally designated protected areas that may also be important for conserving biodiversity. There are known data and knowledge gaps for some countries/regions due to difficulties in reporting national protected area data to the WDPA and/or determining whether a site conforms to the IUCN definition of a protected area.\n\nGaps and/or time lags in reporting national protected area data to the WDPA can however result in discrepancies, which are resolved in communication with data providers. The World Conservation Monitoring Centre (WCMC) compiles data on protected areas, numbers of certain species, and numbers of those species under threat from various sources. Because of differences in definitions, reporting practices, and reporting periods, cross-country comparability is limited.\n\nDue to variations in consistency and methods of collection, data quality is highly variable across countries. Some countries update their information more frequently than others, some have more accurate data on extent of coverage, and many underreport the number or extent of protected areas.\n\nStatistical concept and methodology: This indicator is calculated using all the nationally designated protected areas recorded in the World Database on Protected Areas (WDPA) whose location and extent is known. The WDPA database is stored within a Geographic Information System (GIS) that stores information about protected areas such as their name, type and date of designation, documented area, geographic location (point) and/or boundary (polygon).\n\nDesignating an area as protected does not mean that protection is in force. And for small countries that have only protected areas smaller than 1,000 hectares, the size limit in the definition leads to an underestimate of protected areas. Nationally protected areas are defined using the six IUCN management categories for areas of at least 1,000 hectares: scientific reserves and strict nature reserves with limited public access; national parks of national or international significance and not materially affected by human activity; natural monuments and natural landscapes with unique aspects; managed nature reserves and wildlife sanctuaries; protected landscapes (which may include cultural landscapes); and areas managed mainly for the sustainable use of natural systems to ensure long-term protection and maintenance of biological diversity.\n\nA GIS analysis is used to calculate terrestrial and marine protection. For this a global protected area layer is created by combining the polygons and points recorded in the WDPA. Circular buffers are created around points based on the known extent of protected areas for which no polygon is available. Annual protected area layers are created by dissolving the global protected area layer by the known year of establishment of protected areas recorded in the WDPA. The annual protected area layers are overlaid with country/territory boundaries, coastlines and buffered coastlines (delineating the territorial waters) to obtain the absolute coverage (in square kilometers) of protected areas by country/territory. The total area of a country's/territory's terrestrial protected areas and marine protected areas in territorial waters is divided by the total area of its land areas (including inland waters) and territorial waters to obtain the relative coverage (percentage) of protected areas.", "origins": [ { "producer": "UN Environment Programme (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total land area", "short_unit": "%" }, "er_mrn_ptmr_zs": { "title": "Marine protected areas (% of territorial waters)", "description_from_producer": "Marine protected areas are areas of intertidal or subtidal terrain--and overlying water and associated flora and fauna and historical and cultural features--that have been reserved by law or other effective means to protect part or all of the enclosed environment.\n\nLimitations and exceptions: The data source for this indicator is the World Database on Protected Areas (WDPA), the most comprehensive global dataset on marine and terrestrial protected areas available.\n\nThe extent to which the land areas, including inland waters, and territorial waters of a country/territory are protected is useful for planning purpose to protect biodiversity. However, it is neither an indication of how well managed the terrestrial and marine protected areas are, nor confirmation that protection measures are effectively enforced. Further, the indicator does not provide information on non-designated or internationally designated protected areas that may also be important for conserving biodiversity. There are known data and knowledge gaps for some countries/regions due to difficulties in reporting national protected area data to the WDPA and/or determining whether a site conforms to the IUCN definition of a protected area.\n\nGaps and/or time lags in reporting national protected area data to the WDPA can however result in discrepancies, which are resolved in communication with data providers. The World Conservation Monitoring Centre (WCMC) compiles data on protected areas, numbers of certain species, and numbers of those species under threat from various sources. Because of differences in definitions, reporting practices, and reporting periods, cross-country comparability is limited.\n\nDue to variations in consistency and methods of collection, data quality is highly variable across countries. Some countries update their information more frequently than others, some have more accurate data on extent of coverage, and many underreport the number or extent of protected areas.\n\nStatistical concept and methodology: This indicator is calculated using all the nationally designated protected areas recorded in the World Database on Protected Areas (WDPA) whose location and extent is known. The WDPA database is stored within a Geographic Information System (GIS) that stores information about protected areas such as their name, type and date of designation, documented area, geographic location (point) and/or boundary (polygon).\n\nDesignating an area as protected does not mean that protection is in force. And for small countries that have only protected areas smaller than 1,000 hectares, the size limit in the definition leads to an underestimate of protected areas. Nationally protected areas are defined using the six IUCN management categories for areas of at least 1,000 hectares: scientific reserves and strict nature reserves with limited public access; national parks of national or international significance and not materially affected by human activity; natural monuments and natural landscapes with unique aspects; managed nature reserves and wildlife sanctuaries; protected landscapes (which may include cultural landscapes); and areas managed mainly for the sustainable use of natural systems to ensure long-term protection and maintenance of biological diversity.\n\nA GIS analysis is used to calculate terrestrial and marine protection. For this a global protected area layer is created by combining the polygons and points recorded in the WDPA. Circular buffers are created around points based on the known extent of protected areas for which no polygon is available. Annual protected area layers are created by dissolving the global protected area layer by the known year of establishment of protected areas recorded in the WDPA. The annual protected area layers are overlaid with country/territory boundaries, coastlines and buffered coastlines (delineating the territorial waters) to obtain the absolute coverage (in square kilometers) of protected areas by country/territory per year from 1990 to present. The total area of a country's/territory's terrestrial protected areas and marine protected areas in territorial waters is divided by the total area of its land areas (including inland waters) and territorial waters to obtain the relative coverage (percentage) of protected areas.", "origins": [ { "producer": "UN Environment Programme (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of territorial waters", "short_unit": "%" }, "er_ptd_totl_zs": { "title": "Terrestrial and marine protected areas (% of total territorial area)", "description_from_producer": "Terrestrial protected areas are totally or partially protected areas of at least 1,000 hectares that are designated by national authorities as scientific reserves with limited public access, national parks, natural monuments, nature reserves or wildlife sanctuaries, protected landscapes, and areas managed mainly for sustainable use. Marine protected areas are areas of intertidal or subtidal terrain--and overlying water and associated flora and fauna and historical and cultural features--that have been reserved by law or other effective means to protect part or all of the enclosed environment. Sites protected under local or provincial law are excluded.\n\nLimitations and exceptions: The data source for this indicator is the World Database on Protected Areas (WDPA), the most comprehensive global dataset on marine and terrestrial protected areas available.\n\nThe extent to which the land areas, including inland waters, and territorial waters of a country/territory are protected is useful for planning purpose to protect biodiversity. However, it is neither an indication of how well managed the terrestrial and marine protected areas are, nor confirmation that protection measures are effectively enforced. Further, the indicator does not provide information on non-designated or internationally designated protected areas that may also be important for conserving biodiversity. There are known data and knowledge gaps for some countries/regions due to difficulties in reporting national protected area data to the WDPA and/or determining whether a site conforms to the IUCN definition of a protected area.\n\nGaps and/or time lags in reporting national protected area data to the WDPA can however result in discrepancies, which are resolved in communication with data providers. The World Conservation Monitoring Centre (WCMC) compiles data on protected areas, numbers of certain species, and numbers of those species under threat from various sources. Because of differences in definitions, reporting practices, and reporting periods, cross-country comparability is limited.\n\nDue to variations in consistency and methods of collection, data quality is highly variable across countries. Some countries update their information more frequently than others, some have more accurate data on extent of coverage, and many underreport the number or extent of protected areas.\n\nStatistical concept and methodology: This indicator is calculated using all the nationally designated protected areas recorded in the World Database on Protected Areas (WDPA) whose location and extent is known. The WDPA database is stored within a Geographic Information System (GIS) that stores information about protected areas such as their name, type and date of designation, documented area, geographic location (point) and/or boundary (polygon).\n\nA GIS analysis is used to calculate terrestrial and marine protection. For this a global protected area layer is created by combining the polygons and points recorded in the WDPA. Circular buffers are created around points based on the known extent of protected areas for which no polygon is available. Annual protected area layers are created by dissolving the global protected area layer by the known year of establishment of protected areas recorded in the WDPA. The annual protected area layers are overlaid with country/territory boundaries, coastlines and buffered coastlines (delineating the territorial waters) to obtain the absolute coverage (in square kilometers) of protected areas by country/territory per year from 1990 to present. The total area of a country's/territory's terrestrial protected areas and marine protected areas in territorial waters is divided by the total area of its land areas (including inland waters) and territorial waters to obtain the relative coverage (percentage) of protected areas.", "origins": [ { "producer": "UN Environment Programme (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total territorial area", "short_unit": "%" }, "fb_ast_nper_zs": { "title": "Bank nonperforming loans to total gross loans (%)", "description_from_producer": "Bank nonperforming loans to total gross loans are the value of nonperforming loans divided by the total value of the loan portfolio (including nonperforming loans before the deduction of specific loan-loss provisions). The loan amount recorded as nonperforming should be the gross value of the loan as recorded on the balance sheet, not just the amount that is overdue.\n\nLimitations and exceptions: Reporting countries compile the data using different methodologies, which may also vary for different points in time for the same country. Users are advised to consult the accompanying metadata on the IMF FSI website (data.imf.org) to conduct more meaningful cross-country comparisons or to assess the evolution of the indicator for any of the countries.\n\nStatistical concept and methodology: The ratio of bank nonperforming loans to total gross loans is the value of nonperforming loans (gross value of the loan as recorded on the balance sheet) divided by the total value of the loan portfolio (including nonperforming loans before the deduction of loan loss provisions). It measures bank health and efficiency by identifying problems with asset quality in the loan portfolio. International guidelines recommend that loans be classified as nonperforming when payments of principal and interest are 90 days or more past due or when future payments are not expected to be received in full. Data are submitted by national authorities to the IMF following the Financial Soundness Indicators (FSI) Compilation Guide. For country specific metadata, including reporting period, please refer to the GFSR FSI Tables and the Data and Metadata Tables available through FSIs website: http://data.imf.org/.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "fb_atm_totl_p5": { "title": "Automated teller machines (ATMs) (per 100,000 adults)", "description_from_producer": "Automated teller machines are computerized telecommunications devices that provide clients of a financial institution with access to financial transactions in a public place.\n\nLimitations and exceptions: Population-based ratios of the number of branches and ATMs assume a uniform distribution of bank outlets within a country's area and across its population, while in most countries bank branches and ATMs are concentrated in urban centers of the country and are accessible only to some individuals.\n\nStatistical concept and methodology: Data are shown as the total number of ATMs for every 100,000 adults in the reporting country. Calculated as (number of ATMs)*100,000/adult population in the reporting country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 adults" }, "fb_bnk_capa_zs": { "title": "Bank capital to assets ratio (%)", "description_from_producer": "Bank capital to assets is the ratio of bank capital and reserves to total assets. Capital and reserves include funds contributed by owners, retained earnings, general and special reserves, provisions, and valuation adjustments. Capital includes tier 1 capital (paid-up shares and common stock), which is a common feature in all countries' banking systems, and total regulatory capital, which includes several specified types of subordinated debt instruments that need not be repaid if the funds are required to maintain minimum capital levels (these comprise tier 2 and tier 3 capital). Total assets include all nonfinancial and financial assets.\n\nLimitations and exceptions: Reporting countries compile the data using different methodologies, which may also vary for different points in time for the same country. Users are advised to consult the accompanying metadata on the IMF FSI website (data.imf.org) to conduct more meaningful cross-country comparisons or to assess the evolution of the indicator for any of the countries.\n\nStatistical concept and methodology: The ratio of capital to total assets, without the latter being risk weighted. Capital is measured as total capital and reserves as reported in the sectoral balance sheet; for cross-border consolidated data, Tier 1 capital can also be used. It indicates the extent to which assets are funded by other than own funds and is a measure of capital adequacy of the deposit-taking sector. It complements the capital adequacy ratios compiled based on the methodology agreed to by the Basle Committee on Banking Supervision. Also, it measures financial leverage and is sometimes called the leverage ratio. Data are submitted by national authorities to the IMF following the Financial Soundness Indicators (FSI) Compilation Guide. For country specific metadata, including reporting period, please refer to the GFSR FSI Tables and the Data and Metadata Tables available through FSIs website: http://data.imf.org/.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "fb_cbk_brch_p5": { "title": "Commercial bank branches (per 100,000 adults)", "description_from_producer": "Commercial bank branches are retail locations of resident commercial banks and other resident banks that function as commercial banks that provide financial services to customers and are physically separated from the main office but not organized as legally separated subsidiaries.\n\nLimitations and exceptions: Population-based ratios of the number of branches and ATMs assume a uniform distribution of bank outlets within a country's area and across its population, while in most countries bank branches and ATMs are concentrated in urban centers of the country and are accessible only to some individuals.\n\nStatistical concept and methodology: Data are shown as the number of branches of commercial banks for every 100,000 adults in the reporting country. It is calculated as (number of institutions + number of branches)*100,000/adult population in the reporting country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 adults" }, "fb_cbk_brwr_p3": { "title": "Borrowers from commercial banks (per 1,000 adults)", "description_from_producer": "Borrowers from commercial banks are the reported number of resident customers that are nonfinancial corporations (public and private) and households who obtained loans from commercial banks and other banks functioning as commercial banks. For many countries data cover the total number of loan accounts due to lack of information on loan account holders.\n\nLimitations and exceptions: For several countries, data cover all borrowers including commercial banks, credit unions and financial cooperatives, deposit taking microfinance institutions, and other deposit takers. These include all resident financial corporations and quasi-corporations (except the central bank) that are mainly engaged in financial intermediation and that issue liabilities included in the national definition of broad money. These institutions have varying names in different countries, such as savings and loan associations, building societies, rural banks and agricultural banks, post office giro institutions, post office savings banks, savings banks, and money market funds.\n\nStatistical concept and methodology: Borrowers from commercial banks denotes the total number of resident customers that are nonfinancial corporations (public and private) and households who obtained loans from commercial banks for every 1,000 adults in the reporting country. It is calculated as (number of borrowers)*1,000/adult population in the reporting country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 adults" }, "fb_cbk_dptr_p3": { "title": "Depositors with commercial banks (per 1,000 adults)", "description_from_producer": "Depositors with commercial banks are the reported number of deposit account holders at commercial banks and other resident banks functioning as commercial banks that are resident nonfinancial corporations (public and private) and households. For many countries data cover the total number of deposit accounts due to lack of information on account holders. The major types of deposits are checking accounts, savings accounts, and time deposits.\n\nLimitations and exceptions: Access to finance can expand opportunities for all with higher levels of access and use of banking services associated with lower financing obstacles for people and businesses. A stable financial system that promotes efficient savings and investment is also crucial for a thriving democracy and market economy. There are several aspects of access to financial services: availability, cost, and quality of services. The development and growth of credit markets depend on access to timely, reliable, and accurate data on borrowers' credit experiences. Access to credit can be improved by making it easy to create and enforce collateral agreements and by increasing information about potential borrowers' creditworthiness. Lenders look at a borrower's credit history and collateral. Where credit registries and effective collateral laws are absent - as in many developing countries - banks make fewer loans. Indicators that cover getting credit include the strength of legal rights index and the depth of credit information index.\n\nStatistical concept and methodology: Depositors with commercial banks are deposit account holders at commercial banks and other resident banks functioning as commercial banks that are resident nonfinancial corporations (public and private) and households. It is calculated as (number of depositors)*1,000/adult population in the reporting country. The major types of deposits are checking accounts, savings accounts, and time deposits.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 adults" }, "fd_ast_prvt_gd_zs": { "title": "Domestic credit to private sector by banks (% of GDP)", "description_from_producer": "Domestic credit to private sector by banks refers to financial resources provided to the private sector by other depository corporations (deposit taking corporations except central banks), such as through loans, purchases of nonequity securities, and trade credits and other accounts receivable, that establish a claim for repayment. For some countries these claims include credit to public enterprises.\n\nLimitations and exceptions: Credit to the private sector may sometimes include credit to state-owned or partially state-owned enterprises.\n\nStatistical concept and methodology: Credit is an important link in money transmission; it finances production, consumption, and capital formation, which in turn affect economic activity. The data on domestic credit provided to the private sector by banks are taken from the other depository corporations survey (line 22D) of the International Monetary Fund's (IMF) International Financial Statistics. The other depository corporations include all deposit taking corporations (deposit money banks) except monetary authorities (the central bank).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "fd_res_liqu_as_zs": { "title": "Bank liquid reserves to bank assets ratio (%)", "description_from_producer": "Ratio of bank liquid reserves to bank assets is the ratio of domestic currency holdings and deposits with the monetary authorities to claims on other governments, nonfinancial public enterprises, the private sector, and other banking institutions.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "fi_res_totl_cd": { "title": "Total reserves (includes gold, current US$)", "description_from_producer": "Total reserves comprise holdings of monetary gold, special drawing rights, reserves of IMF members held by the IMF, and holdings of foreign exchange under the control of monetary authorities. The gold component of these reserves is valued at year-end (December 31) London prices. Data are in current U.S. dollars.\n\nLimitations and exceptions: Discrepancies may arise in the balance of payments because there is no single source for balance of payments data and therefore no way to ensure that the data are fully consistent. Sources include customs data, monetary accounts of the banking system, external debt records, information provided by enterprises, surveys to estimate service transactions, and foreign exchange records. Differences in collection methods - such as in timing, definitions of residence and ownership, and the exchange rate used to value transactions - contribute to net errors and omissions. In addition, smuggling and other illegal or quasi-legal transactions may be unrecorded or misrecorded.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "includes gold, current US$", "short_unit": "$" }, "fi_res_totl_dt_zs": { "title": "Total reserves (% of total external debt)", "description_from_producer": "International reserves to total external debt stocks.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total external debt", "short_unit": "%" }, "fi_res_totl_mo": { "title": "Total reserves in months of imports", "description_from_producer": "Total reserves comprise holdings of monetary gold, special drawing rights, reserves of IMF members held by the IMF, and holdings of foreign exchange under the control of monetary authorities. The gold component of these reserves is valued at year-end (December 31) London prices. This item shows reserves expressed in terms of the number of months of imports of goods and services they could pay for [Reserves/(Imports/12)].", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "fi_res_xgld_cd": { "title": "Total reserves minus gold (current US$)", "description_from_producer": "Total reserves minus gold comprise special drawing rights, reserves of IMF members held by the IMF, and holdings of foreign exchange under the control of monetary authorities. Gold holdings are excluded. Data are in current U.S. dollars.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "fm_ast_cgov_zg_m3": { "title": "Claims on central government (annual growth as % of broad money)", "description_from_producer": "Claims on central government (IFS line 32AN..ZK) include loans to central government institutions net of deposits.\n\nLimitations and exceptions: Monetary accounts are derived from the balance sheets of financial institutions - the central bank, commercial banks, and nonbank financial intermediaries. Although these balance sheets are usually reliable, they are subject to errors of classification, valuation, and timing and to differences in accounting practices. For example, whether interest income is recorded on an accrual or a cash basis can make a substantial difference, as can the treatment of nonperforming assets. Valuation errors typically arise for foreign exchange transactions, particularly in countries with flexible exchange rates or in countries that have undergone currency devaluation during the reporting period. The valuation of financial derivatives and the net liabilities of the banking system can also be difficult. The quality of commercial bank reporting also may be adversely affected by delays in reports from bank branches, especially in countries where branch accounts are not computerized. Thus the data in the balance sheets of commercial banks may be based on preliminary estimates subject to constant revision. This problem is likely to be even more serious for nonbank financial intermediaries.\n\nStatistical concept and methodology: The banking system's assets include its net foreign assets and net domestic credit. Net domestic credit includes credit extended to the private sector and general government and credit extended to the nonfinancial public sector in the form of investments in short- and long-term government securities and loans to state enterprises; liabilities to the public and private sectors in the form of deposits with the banking system are netted out. Net domestic credit also includes credit to banking and nonbank financial institutions.\n\nDomestic credit is the main vehicle through which changes in the money supply are regulated, with central bank lending to the government often playing the most important role. The central bank can regulate lending to the private sector in several ways - for example, by adjusting the cost of the refinancing facilities it provides to banks, by changing market interest rates through open market operations, or by controlling the availability of credit through changes in the reserve requirements imposed on banks and ceilings on the credit provided by banks to the private sector.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual growth as % of broad money", "short_unit": "%" }, "fm_ast_domo_zg_m3": { "title": "Claims on other sectors of the domestic economy (annual growth as % of broad money)", "description_from_producer": "Claims on other sectors of the domestic economy (IFS line 32S..ZK) include gross credit from the financial system to households, nonprofit institutions serving households, nonfinancial corporations, state and local governments, and social security funds.\n\nLimitations and exceptions: Monetary accounts are derived from the balance sheets of financial institutions - the central bank, commercial banks, and nonbank financial intermediaries. Although these balance sheets are usually reliable, they are subject to errors of classification, valuation, and timing and to differences in accounting practices. For example, whether interest income is recorded on an accrual or a cash basis can make a substantial difference, as can the treatment of nonperforming assets. Valuation errors typically arise for foreign exchange transactions, particularly in countries with flexible exchange rates or in countries that have undergone currency devaluation during the reporting period. The valuation of financial derivatives and the net liabilities of the banking system can also be difficult. The quality of commercial bank reporting also may be adversely affected by delays in reports from bank branches, especially in countries where branch accounts are not computerized. Thus the data in the balance sheets of commercial banks may be based on preliminary estimates subject to constant revision. This problem is likely to be even more serious for nonbank financial intermediaries.\n\nStatistical concept and methodology: The banking system's assets include its net foreign assets and net domestic credit. Net domestic credit includes credit extended to the private sector and general government and credit extended to the nonfinancial public sector in the form of investments in short- and long-term government securities and loans to state enterprises; liabilities to the public and private sectors in the form of deposits with the banking system are netted out. Net domestic credit also includes credit to banking and nonbank financial institutions.\n\nDomestic credit is the main vehicle through which changes in the money supply are regulated, with central bank lending to the government often playing the most important role. The central bank can regulate lending to the private sector in several ways - for example, by adjusting the cost of the refinancing facilities it provides to banks, by changing market interest rates through open market operations, or by controlling the availability of credit through changes in the reserve requirements imposed on banks and ceilings on the credit provided by banks to the private sector.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual growth as % of broad money", "short_unit": "%" }, "fm_ast_doms_cn": { "title": "Net domestic credit (current LCU)", "description_from_producer": "Net domestic credit is the sum of net claims on the central government and claims on other sectors of the domestic economy (IFS line 32). Data are in current local currency.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "fm_ast_nfrg_cn": { "title": "Net foreign assets (current LCU)", "description_from_producer": "Net foreign assets are the sum of foreign assets held by monetary authorities and deposit money banks, less their foreign liabilities. Data are in current local currency.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "fm_ast_prvt_gd_zs": { "title": "Monetary Sector credit to private sector (% GDP)", "description_from_producer": "Domestic credit to private sector refers to financial resources provided to the private sector, such as through loans, purchases of nonequity securities, and trade credits and other accounts receivable, that establish a claim for repayment. For some countries these claims include credit to public enterprises.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "fm_ast_prvt_zg_m3": { "title": "Claims on private sector (annual growth as % of broad money)", "description_from_producer": "Claims on private sector (IFS line 32D..ZK or 32D..ZF) include gross credit from the financial system to individuals, enterprises, nonfinancial public entities not included under net domestic credit, and financial institutions not included elsewhere.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual growth as % of broad money", "short_unit": "%", "display": { "conversionFactor": 100 } }, "fm_lbl_bmny_cn": { "title": "Broad money (current LCU)", "description_from_producer": "Broad money (IFS line 35L..ZK) is the sum of currency outside banks; demand deposits other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler\u2019s checks; and other securities such as certificates of deposit and commercial paper.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "fm_lbl_bmny_gd_zs": { "title": "Broad money (% of GDP)", "description_from_producer": "Broad money (IFS line 35L..ZK) is the sum of currency outside banks; demand deposits other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler\u2019s checks; and other securities such as certificates of deposit and commercial paper.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "fm_lbl_bmny_ir_zs": { "title": "Broad money to total reserves ratio", "description_from_producer": "Broad money (IFS line 35L..ZK) is the sum of currency outside banks; demand deposits other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler\u2019s checks; and other securities such as certificates of deposit and commercial paper.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "fm_lbl_bmny_zg": { "title": "Broad money growth (annual %)", "description_from_producer": "Broad money (IFS line 35L..ZK) is the sum of currency outside banks; demand deposits other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler\u2019s checks; and other securities such as certificates of deposit and commercial paper.\n\nLimitations and exceptions: Monetary accounts are derived from the balance sheets of financial institutions - the central bank, commercial banks, and nonbank financial intermediaries. Although these balance sheets are usually reliable, they are subject to errors of classification, valuation, and timing and to differences in accounting practices. For example, whether interest income is recorded on an accrual or a cash basis can make a substantial difference, as can the treatment of nonperforming assets. Valuation errors typically arise for foreign exchange transactions, particularly in countries with flexible exchange rates or in countries that have undergone currency devaluation during the reporting period. The valuation of financial derivatives and the net liabilities of the banking system can also be difficult. The quality of commercial bank reporting also may be adversely affected by delays in reports from bank branches, especially in countries where branch accounts are not computerized. Thus the data in the balance sheets of commercial banks may be based on preliminary estimates subject to constant revision. This problem is likely to be even more serious for nonbank financial intermediaries.\n\nStatistical concept and methodology: Money and the financial accounts that record the supply of money lie at the heart of a country\u2019s financial system. There are several commonly used definitions of the money supply. The narrowest, M1, encompasses currency held by the public and demand deposits with banks. M2 includes M1 plus time and savings deposits with banks that require prior notice for withdrawal. M3 includes M2 as well as various money market instruments, such as certificates of deposit issued by banks, bank deposits denominated in foreign currency, and deposits with financial institutions other than banks. However defined, money is a liability of the banking system, distinguished from other bank liabilities by the special role it plays as a medium of exchange, a unit of account, and a store of value.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "fp_cpi_totl": { "title": "Consumer price index (2010 = 100)", "description_from_producer": "Consumer price index reflects changes in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used. Data are period averages.\n\nLimitations and exceptions: Consumer price indexes should be interpreted with caution. The definition of a household, the basket of goods, and the geographic (urban or rural) and income group coverage of consumer price surveys can vary widely by country. In addition, weights are derived from household expenditure surveys, which, for budgetary reasons, tend to be conducted infrequently in developing countries, impairing comparability over time. Although useful for measuring consumer price inflation within a country, consumer price indexes are of less value in comparing countries.\n\nStatistical concept and methodology: Consumer price indexes are constructed explicitly, using surveys of the cost of a defined basket of consumer goods and services.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2010 = 100" }, "fp_cpi_totl_zg": { "title": "Inflation, consumer prices (annual %)", "description_from_producer": "Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "fp_wpi_totl": { "title": "Wholesale price index (2010 = 100)", "description_from_producer": "Wholesale price index refers to a mix of agricultural and industrial goods at various stages of production and distribution, including import duties. The Laspeyres formula is generally used.\n\nStatistical concept and methodology: Wholesale price indexes are based on the prices at the first commercial transaction of commodities that are important in a country's output or consumption. Prices are farm-gate for agricultural commodities and ex-factory for industrial goods. Preference is given to indexes with the broadest coverage of the economy.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2010 = 100" }, "fr_inr_dpst": { "title": "Deposit interest rate (%)", "description_from_producer": "Deposit interest rate is the rate paid by commercial or similar banks for demand, time, or savings deposits. The terms and conditions attached to these rates differ by country, however, limiting their comparability.\n\nLimitations and exceptions: Countries use a variety of reporting formats, sample designs, interest compounding formulas, averaging methods, and data presentations for indices and other data series on interest rates. The IMF's Monetary and Financial Statistics Manual does not provide guidelines beyond the general recommendation that such data should reflect market prices and effective (rather than nominal) interest rates and should be representative of the financial assets and markets to be covered. For more information, please see http://www.imf.org/external/pubs/ft/mfs/manual/index.htm.\n\nStatistical concept and methodology: Many interest rates coexist in an economy, reflecting competitive conditions, the terms governing loans and deposits, and differences in the position and status of creditors and debtors. In some economies interest rates are set by regulation or administrative fiat. In economies with imperfect markets, or where reported nominal rates are not indicative of effective rates, it may be difficult to obtain data on interest rates that reflect actual market transactions. Deposit and lending rates are collected by the International Monetary Fund (IMF) as representative interest rates offered by banks to resident customers. The terms and conditions attached to these rates differ by country, however, limiting their comparability.\n\nIn 2009 the IMF began publishing a new presentation of monetary statistics for countries that report data in accordance with its Monetary Financial Statistical Manual 2000. The presentation for countries that report data in accordance with its International Financial Statistics (IFS) remains the same.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "fr_inr_lend": { "title": "Lending interest rate (%)", "description_from_producer": "Lending rate is the bank rate that usually meets the short- and medium-term financing needs of the private sector. This rate is normally differentiated according to creditworthiness of borrowers and objectives of financing. The terms and conditions attached to these rates differ by country, however, limiting their comparability.\n\nLimitations and exceptions: Countries use a variety of reporting formats, sample designs, interest compounding formulas, averaging methods, and data presentations for indices and other data series on interest rates. The IMF's Monetary and Financial Statistics Manual does not provide guidelines beyond the general recommendation that such data should reflect market prices and effective (rather than nominal) interest rates and should be representative of the financial assets and markets to be covered. For more information, please see http://www.imf.org/external/pubs/ft/mfs/manual/index.htm.\n\nStatistical concept and methodology: Many interest rates coexist in an economy, reflecting competitive conditions, the terms governing loans and deposits, and differences in the position and status of creditors and debtors. In some economies interest rates are set by regulation or administrative fiat. In economies with imperfect markets, or where reported nominal rates are not indicative of effective rates, it may be difficult to obtain data on interest rates that reflect actual market transactions. Deposit and lending rates are collected by the International Monetary Fund (IMF) as representative interest rates offered by banks to resident customers. The terms and conditions attached to these rates differ by country, however, limiting their comparability.\n\nIn 2009 the IMF began publishing a new presentation of monetary statistics for countries that report data in accordance with its Monetary Financial Statistical Manual 2000. The presentation for countries that report data in accordance with its International Financial Statistics (IFS) remains the same.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "fr_inr_lndp": { "title": "Interest rate spread (lending rate minus deposit rate, %)", "description_from_producer": "Interest rate spread is the interest rate charged by banks on loans to private sector customers minus the interest rate paid by commercial or similar banks for demand, time, or savings deposits. The terms and conditions attached to these rates differ by country, however, limiting their comparability.\n\nLimitations and exceptions: Countries use a variety of reporting formats, sample designs, interest compounding formulas, averaging methods, and data presentations for indices and other data series on interest rates. The IMF's Monetary and Financial Statistics Manual does not provide guidelines beyond the general recommendation that such data should reflect market prices and effective (rather than nominal) interest rates and should be representative of the financial assets and markets to be covered. For more information, please see http://www.imf.org/external/pubs/ft/mfs/manual/index.htm.\n\nStatistical concept and methodology: The interest rate spread - the margin between the cost of mobilizing liabilities and the earnings on assets - measures financial sector efficiency in intermediation. A narrow spread means low transaction costs, which reduces the cost of funds for investment, crucial to economic growth.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "lending rate minus deposit rate, %", "short_unit": "%" }, "fr_inr_rinr": { "title": "Real interest rate (%)", "description_from_producer": "Real interest rate is the lending interest rate adjusted for inflation as measured by the GDP deflator. The terms and conditions attached to lending rates differ by country, however, limiting their comparability.\n\nStatistical concept and methodology: Many interest rates coexist in an economy, reflecting competitive conditions, the terms governing loans and deposits, and differences in the position and status of creditors and debtors. In some economies interest rates are set by regulation or administrative fiat. In economies with imperfect markets, or where reported nominal rates are not indicative of effective rates, it may be difficult to obtain data on interest rates that reflect actual market transactions. Deposit and lending rates are collected by the International Monetary Fund (IMF) as representative interest rates offered by banks to resident customers. The terms and conditions attached to these rates differ by country, however, limiting their comparability.\n\nReal interest rates are calculated by adjusting nominal rates by an estimate of the inflation rate in the economy. A negative real interest rate indicates a loss in the purchasing power of the principal. The real interest rates are calculated as (i - P) / (1 + P), where i is the nominal lending interest rate and P is the inflation rate (as measured by the GDP deflator).\n\nIn 2009 the IMF began publishing a new presentation of monetary statistics for countries that report data in accordance with its Monetary Financial Statistical Manual 2000. The presentation for countries that report data in accordance with its International Financial Statistics (IFS) remains the same.", "origins": [ { "producer": "International Monetary Fund and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "fr_inr_risk": { "title": "Risk premium on lending (lending rate minus treasury bill rate, %)", "description_from_producer": "Risk premium on lending is the interest rate charged by banks on loans to private sector customers minus the \"risk free\" treasury bill interest rate at which short-term government securities are issued or traded in the market. In some countries this spread may be negative, indicating that the market considers its best corporate clients to be lower risk than the government. The terms and conditions attached to lending rates differ by country, however, limiting their comparability.\n\nLimitations and exceptions: Countries use a variety of reporting formats, sample designs, interest compounding formulas, averaging methods, and data presentations for indices and other data series on interest rates. The IMF's Monetary and Financial Statistics Manual does not provide guidelines beyond the general recommendation that such data should reflect market prices and effective (rather than nominal) interest rates and should be representative of the financial assets and markets to be covered. For more information, please see http://www.imf.org/external/pubs/ft/mfs/manual/index.htm.\n\nStatistical concept and methodology: The risk premium on lending is the spread between the lending rate to the private sector and the \"risk-free\" government rate. Spreads are expressed as an annual average. A small spread indicates that the market considers its best corporate customers to be low risk; a negative value indicates that the market considers its best corporate clients to be lower risk than the government.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "lending rate minus treasury bill rate, %", "short_unit": "%" }, "fs_ast_cgov_gd_zs": { "title": "Claims on central government, etc. (% GDP)", "description_from_producer": "Claims on central government (IFS line 52AN or 32AN) include loans to central government institutions net of deposits.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% GDP", "short_unit": "%" }, "fs_ast_domo_gd_zs": { "title": "Claims on other sectors of the domestic economy (% of GDP)", "description_from_producer": "Claims on other sectors of the domestic economy (IFS line 52S or 32S) include gross credit from the financial system to households, nonprofit institutions serving households, nonfinancial corporations, state and local governments, and social security funds.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "fs_ast_doms_gd_zs": { "title": "Domestic credit provided by financial sector (% of GDP)", "description_from_producer": "Domestic credit provided by the financial sector includes all credit to various sectors on a gross basis, with the exception of credit to the central government, which is net. The financial sector includes monetary authorities and deposit money banks, as well as other financial corporations where data are available (including corporations that do not accept transferable deposits but do incur such liabilities as time and savings deposits). Examples of other financial corporations are finance and leasing companies, money lenders, insurance corporations, pension funds, and foreign exchange companies.\n\nLimitations and exceptions: In a few countries governments may hold international reserves as deposits in the banking system rather than in the central bank. Since claims on the central government are a net item (claims on the central government minus central government deposits), the figure may be negative, resulting in a negative figure for domestic credit provided by the banking sector.\n\nStatistical concept and methodology: Domestic credit provided by the financial sector as a share of GDP measures banking sector depth and financial sector development in terms of size. The data on domestic credit provided by the financial sector are taken from the financial corporations survey (line 52) of the International Monetary Fund's (IMF) International Financial Statistics or, when unavailable, from its depository corporations survey (line 32). The financial sector includes monetary authorities (the central bank) and deposit money banks, as well as other financial institutions where data are available (including institutions that do not accept transferable deposits but do incur such liabilities as time and savings deposits). Examples of other banking institutions are savings and mortgage loan institutions, finance companies, development banks, and building and loan associations.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "fs_ast_prvt_gd_zs": { "title": "Domestic credit to private sector (% of GDP)", "description_from_producer": "Domestic credit to private sector refers to financial resources provided to the private sector by financial corporations, such as through loans, purchases of nonequity securities, and trade credits and other accounts receivable, that establish a claim for repayment. For some countries these claims include credit to public enterprises. The financial corporations include monetary authorities and deposit money banks, as well as other financial corporations where data are available (including corporations that do not accept transferable deposits but do incur such liabilities as time and savings deposits). Examples of other financial corporations are finance and leasing companies, money lenders, insurance corporations, pension funds, and foreign exchange companies.\n\nLimitations and exceptions: Credit to the private sector may sometimes include credit to state-owned or partially state-owned enterprises.\n\nStatistical concept and methodology: Credit is an important link in money transmission; it finances production, consumption, and capital formation, which in turn affect economic activity. The data on domestic credit provided to the private sector are taken from the financial corporations survey (line 52D) of the International Monetary Fund's (IMF) International Financial Statistics or, when unavailable, from its depository survey (line 32D). The banking sector includes monetary authorities (the central bank) and deposit money banks, as well as other financial corporations where data are available (including institutions that do not accept transferable deposits but do incur such liabilities as time and savings deposits). Examples of other financial corporations are finance and leasing companies, money lenders, insurance corporations, pension funds, and foreign exchange companies.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "fx_own_totl_40_zs": { "title": "Account ownership at a financial institution or with a mobile-money-service provider, poorest 40% (% of population ages 15+)", "description_from_producer": "Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (poorest 40%, share of population ages 15+).", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population ages 15+", "short_unit": "%" }, "fx_own_totl_60_zs": { "title": "Account ownership at a financial institution or with a mobile-money-service provider, richest 60% (% of population ages 15+)", "description_from_producer": "Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population ages 15+", "short_unit": "%" }, "fx_own_totl_fe_zs": { "title": "Account ownership at a financial institution or with a mobile-money-service provider, female (% of population ages 15+)", "description_from_producer": "Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (female, % age 15+).", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population ages 15+", "short_unit": "%" }, "fx_own_totl_ma_zs": { "title": "Account ownership at a financial institution or with a mobile-money-service provider, male (% of population ages 15+)", "description_from_producer": "Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (male, % age 15+).", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population ages 15+", "short_unit": "%" }, "fx_own_totl_ol_zs": { "title": "Account ownership at a financial institution or with a mobile-money-service provider, older adults (% of population ages 25+)", "description_from_producer": "Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (older adults, % of population ages 25+).", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population ages 25+", "short_unit": "%" }, "fx_own_totl_pl_zs": { "title": "Account ownership at a financial institution or with a mobile-money-service provider, primary education or less (% of population ages 15+)", "description_from_producer": "Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (primary education or less, % of population ages 15+).", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population ages 15+", "short_unit": "%" }, "fx_own_totl_so_zs": { "title": "Account ownership at a financial institution or with a mobile-money-service provider, secondary education or more (% of population ages 15+)", "description_from_producer": "Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (secondary education or more, % of population ages 15+).", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population ages 15+", "short_unit": "%" }, "fx_own_totl_yg_zs": { "title": "Account ownership at a financial institution or with a mobile-money-service provider, young adults (% of population ages 15-24)", "description_from_producer": "Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (young adults, % of population ages 15-24).", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population ages 15-24", "short_unit": "%" }, "fx_own_totl_zs": { "title": "Account ownership at a financial institution or with a mobile-money-service provider (% of population ages 15+)", "description_from_producer": "Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (% age 15+).", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% age 15+", "short_unit": "%" }, "gb_xpd_rsdv_gd_zs": { "title": "Research and development expenditure (% of GDP)", "description_from_producer": "Gross domestic expenditures on research and development (R&D), expressed as a percent of GDP. They include both capital and current expenditures in the four main sectors: Business enterprise, Government, Higher education and Private non-profit. R&D covers basic research, applied research, and experimental development.\n\nLimitations and exceptions: Estimates of the resources allocated to R&D are affected by national characteristics such as the periodicity and coverage of national R&D surveys across institutional sectors and industries; and the use of different sampling and estimation methods. R&D typically involves a few large performers, hence R&D surveys use various techniques to maintain up-to-date registers of known performers, while attempting to identify new or occasional performers.\n\nR&D totals from SNA accounts may differ from these estimates, due in part to the different treatments of software R&D in the totals.\n\nStatistical concept and methodology: The gross domestic expenditure on R&D indicator consists of the total expenditure (current and capital) on R&D by all resident companies, research institutes, university and government laboratories, etc. It excludes R&D expenditures financed by domestic firms but performed abroad.\n\nThe OECD's Frascati Manual defines research and experimental development as \"creative work undertaken on a systemic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications.\" R&D covers basic research, applied research, and experimental development.\n\n(1) Basic research - Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundation of phenomena and observable facts, without any particular application or use in view\n\n(2) Applied research - Applied research is also original investigation undertaken in order to acquire new knowledge; it is, however, directed primarily towards a specific practical aim or objective.\n\n(3) Experimental development - Experimental development is systematic work, drawing on existing knowledge gained from research and/or practical experience, which is directed to producing new materials, products or devices, to installing new processes, systems and services, or to improving substantially those already produced or installed.\n\nThe fields of science and technology used to classify R&D according to the Revised Fields of Science and Technology Classification are:\n1. Natural sciences;\n2. Engineering and technology;\n3. Medical and health sciences;\n4. Agricultural sciences;\n5. Social sciences;\n6. Humanities and the arts.\n\nThe data are obtained through statistical surveys which are regularly conducted at national level covering R&D performing entities in the private and public sectors.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "gc_ast_totl_cn": { "title": "Net acquisition of financial assets (current LCU)", "description_from_producer": "Net acquisition of government financial assets includes domestic and foreign financial claims, SDRs, and gold bullion held by monetary authorities as a reserve asset. The net acquisition of financial assets should be offset by the net incurrence of liabilities.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_ast_totl_gd_zs": { "title": "Net acquisition of financial assets (% of GDP)", "description_from_producer": "Net acquisition of government financial assets includes domestic and foreign financial claims, SDRs, and gold bullion held by monetary authorities as a reserve asset. The net acquisition of financial assets should be offset by the net incurrence of liabilities.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "gc_dod_totl_cn": { "title": "Central government debt, total (current LCU)", "description_from_producer": "Debt is the entire stock of direct government fixed-term contractual obligations to others outstanding on a particular date. It includes domestic and foreign liabilities such as currency and money deposits, securities other than shares, and loans. It is the gross amount of government liabilities reduced by the amount of equity and financial derivatives held by the government. Because debt is a stock rather than a flow, it is measured as of a given date, usually the last day of the fiscal year.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_dod_totl_gd_zs": { "title": "Central government debt, total (% of GDP)", "description_from_producer": "Debt is the entire stock of direct government fixed-term contractual obligations to others outstanding on a particular date. It includes domestic and foreign liabilities such as currency and money deposits, securities other than shares, and loans. It is the gross amount of government liabilities reduced by the amount of equity and financial derivatives held by the government. Because debt is a stock rather than a flow, it is measured as of a given date, usually the last day of the fiscal year.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "gc_lbl_totl_cn": { "title": "Net incurrence of liabilities, total (current LCU)", "description_from_producer": "Net incurrence of government liabilities includes foreign financing (obtained from nonresidents) and domestic financing (obtained from residents), or the means by which a government provides financial resources to cover a budget deficit or allocates financial resources arising from a budget surplus. The net incurrence of liabilities should be offset by the net acquisition of financial assets.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_lbl_totl_gd_zs": { "title": "Net incurrence of liabilities, total (% of GDP)", "description_from_producer": "Net incurrence of government liabilities includes foreign financing (obtained from nonresidents) and domestic financing (obtained from residents), or the means by which a government provides financial resources to cover a budget deficit or allocates financial resources arising from a budget surplus. The net incurrence of liabilities should be offset by the net acquisition of financial assets.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "gc_nfn_totl_cn": { "title": "Net investment in nonfinancial assets (current LCU)", "description_from_producer": "Net investment in government nonfinancial assets includes fixed assets, inventories, valuables, and nonproduced assets. Nonfinancial assets are stores of value and provide benefits either through their use in the production of goods and services or in the form of property income and holding gains. Net investment in nonfinancial assets also includes consumption of fixed capital.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_nfn_totl_gd_zs": { "title": "Net investment in nonfinancial assets (% of GDP)", "description_from_producer": "Net investment in government nonfinancial assets includes fixed assets, inventories, valuables, and nonproduced assets. Nonfinancial assets are stores of value and provide benefits either through their use in the production of goods and services or in the form of property income and holding gains. Net investment in nonfinancial assets also includes consumption of fixed capital.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "gc_nld_totl_cn": { "title": "Net lending (+) / net borrowing (-) (current LCU)", "description_from_producer": "Net lending\u00a0(+) / net borrowing\u00a0(\u2013) equals government revenue minus expense, minus net investment in nonfinancial assets. It is also equal to the net result of transactions in financial assets and liabilities. Net lending/net borrowing is a summary measure indicating the extent to which government is either putting financial resources at the disposal of other sectors in the economy or abroad, or utilizing the financial resources generated by other sectors in the economy or from abroad.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_nld_totl_gd_zs": { "title": "Net lending (+) / net borrowing (-) (% of GDP)", "description_from_producer": "Net lending\u00a0(+) / net borrowing\u00a0(\u2013) equals government revenue minus expense, minus net investment in nonfinancial assets. It is also equal to the net result of transactions in financial assets and liabilities. Net lending/net borrowing is a summary measure indicating the extent to which government is either putting financial resources at the disposal of other sectors in the economy or abroad, or utilizing the financial resources generated by other sectors in the economy or from abroad.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "gc_rev_gotr_cn": { "title": "Grants and other revenue (current LCU)", "description_from_producer": "Grants and other revenue include grants from other foreign governments, international organizations, and other government units; interest; dividends; rent; requited, nonrepayable receipts for public purposes (such as fines, administrative fees, and entrepreneurial income from government owner\u00adship of property); and voluntary, unrequited, nonrepayable receipts other than grants.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_rev_gotr_zs": { "title": "Grants and other revenue (% of revenue)", "description_from_producer": "Grants and other revenue include grants from other foreign governments, international organizations, and other government units; interest; dividends; rent; requited, nonrepayable receipts for public purposes (such as fines, administrative fees, and entrepreneurial income from government owner\u00adship of property); and voluntary, unrequited, nonrepayable receipts other than grants.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of revenue", "short_unit": "%" }, "gc_rev_socl_cn": { "title": "Social contributions (current LCU)", "description_from_producer": "Social contributions include social security contributions by employees, employers, and self-employed individuals, and other contributions whose source cannot be determined. They also include actual or imputed contributions to social insurance schemes operated by governments.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_rev_socl_zs": { "title": "Social contributions (% of revenue)", "description_from_producer": "Social contributions include social security contributions by employees, employers, and self-employed individuals, and other contributions whose source cannot be determined. They also include actual or imputed contributions to social insurance schemes operated by governments.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of revenue", "short_unit": "%" }, "gc_rev_xgrt_cn": { "title": "Revenue, excluding grants (current LCU)", "description_from_producer": "Revenue is cash receipts from taxes, social contributions, and other revenues such as fines, fees, rent, and income from property or sales. Grants are also considered as revenue but are excluded here.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_rev_xgrt_gd_zs": { "title": "Revenue, excluding grants (% of GDP)", "description_from_producer": "Revenue is cash receipts from taxes, social contributions, and other revenues such as fines, fees, rent, and income from property or sales. Grants are also considered as revenue but are excluded here.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "gc_tax_expt_cn": { "title": "Taxes on exports (current LCU)", "description_from_producer": "Taxes on exports are all levies on goods being transported out of the country or services being delivered to nonresidents by residents. Rebates on exported goods that are repayments of previously paid general consumption taxes, excise taxes, or import duties are deducted from the gross amounts receivable from these taxes, not from amounts receivable from export taxes.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_tax_expt_zs": { "title": "Taxes on exports (% of tax revenue)", "description_from_producer": "Taxes on exports are all levies on goods being transported out of the country or services being delivered to nonresidents by residents. Rebates on exported goods that are repayments of previously paid general consumption taxes, excise taxes, or import duties are deducted from the gross amounts receivable from these taxes, not from amounts receivable from export taxes.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of tax revenue", "short_unit": "%" }, "gc_tax_gsrv_cn": { "title": "Taxes on goods and services (current LCU)", "description_from_producer": "Taxes on goods and services include general sales and turnover or value added taxes, selective excises on goods, selective taxes on services, taxes on the use of goods or property, taxes on extraction and production of minerals, and profits of fiscal monopolies.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_tax_gsrv_rv_zs": { "title": "Taxes on goods and services (% of revenue)", "description_from_producer": "Taxes on goods and services include general sales and turnover or value added taxes, selective excises on goods, selective taxes on services, taxes on the use of goods or property, taxes on extraction and production of minerals, and profits of fiscal monopolies.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of revenue", "short_unit": "%" }, "gc_tax_gsrv_va_zs": { "title": "Taxes on goods and services (% value added of industry and services)", "description_from_producer": "Taxes on goods and services include general sales and turnover or value added taxes, selective excises on goods, selective taxes on services, taxes on the use of goods or property, taxes on extraction and production of minerals, and profits of fiscal monopolies.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% value added of industry and services", "short_unit": "%" }, "gc_tax_impt_cn": { "title": "Customs and other import duties (current LCU)", "description_from_producer": "Customs and other import duties are all levies collected on goods that are entering the country or services delivered by nonresidents to residents. They include levies imposed for revenue or protection purposes and determined on a specific or ad valorem basis as long as they are restricted to imported goods or services.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_tax_impt_zs": { "title": "Customs and other import duties (% of tax revenue)", "description_from_producer": "Customs and other import duties are all levies collected on goods that are entering the country or services delivered by nonresidents to residents. They include levies imposed for revenue or protection purposes and determined on a specific or ad valorem basis as long as they are restricted to imported goods or services.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of tax revenue", "short_unit": "%" }, "gc_tax_intt_cn": { "title": "Taxes on international trade (current LCU)", "description_from_producer": "Taxes on international trade include import duties, export duties, profits of export or import monopolies, exchange profits, and exchange taxes.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_tax_intt_rv_zs": { "title": "Taxes on international trade (% of revenue)", "description_from_producer": "Taxes on international trade include import duties, export duties, profits of export or import monopolies, exchange profits, and exchange taxes.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of revenue", "short_unit": "%" }, "gc_tax_othr_cn": { "title": "Other taxes (current LCU)", "description_from_producer": "Other taxes include employer payroll or labor taxes, taxes on property, and taxes not allocable to other categories, such as penalties for late payment or nonpayment of taxes.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_tax_othr_rv_zs": { "title": "Other taxes (% of revenue)", "description_from_producer": "Other taxes include employer payroll or labor taxes, taxes on property, and taxes not allocable to other categories, such as penalties for late payment or nonpayment of taxes.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of revenue", "short_unit": "%" }, "gc_tax_totl_cn": { "title": "Tax revenue (current LCU)", "description_from_producer": "Tax revenue refers to compulsory transfers to the central government for public purposes. Certain compulsory transfers such as fines, penalties, and most social security contributions are excluded. Refunds and corrections of erroneously collected tax revenue are treated as negative revenue.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_tax_totl_gd_zs": { "title": "Tax revenue (% of GDP)", "description_from_producer": "Tax revenue refers to compulsory transfers to the central government for public purposes. Certain compulsory transfers such as fines, penalties, and most social security contributions are excluded. Refunds and corrections of erroneously collected tax revenue are treated as negative revenue.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "gc_tax_ypkg_cn": { "title": "Taxes on income, profits and capital gains (current LCU)", "description_from_producer": "Taxes on income, profits, and capital gains are levied on the actual or presumptive net income of individuals, on the profits of corporations and enterprises, and on capital gains, whether realized or not, on land, securities, and other assets. Intragovernmental payments are eliminated in consolidation.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_tax_ypkg_rv_zs": { "title": "Taxes on income, profits and capital gains (% of revenue)", "description_from_producer": "Taxes on income, profits, and capital gains are levied on the actual or presumptive net income of individuals, on the profits of corporations and enterprises, and on capital gains, whether realized or not, on land, securities, and other assets. Intragovernmental payments are eliminated in consolidation.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of revenue", "short_unit": "%" }, "gc_tax_ypkg_zs": { "title": "Taxes on income, profits and capital gains (% of total taxes)", "description_from_producer": "Taxes on income, profits, and capital gains are levied on the actual or presumptive net income of individuals, on the profits of corporations and enterprises, and on capital gains, whether realized or not, on land, securities, and other assets. Intragovernmental payments are eliminated in consolidation.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total taxes", "short_unit": "%" }, "gc_xpn_comp_cn": { "title": "Compensation of employees (current LCU)", "description_from_producer": "Compensation of employees consists of all payments in cash, as well as in kind (such as food and housing), to employees in return for services rendered, and government contributions to social insurance schemes such as social security and pensions that provide benefits to employees.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_xpn_comp_zs": { "title": "Compensation of employees (% of expense)", "description_from_producer": "Compensation of employees consists of all payments in cash, as well as in kind (such as food and housing), to employees in return for services rendered, and government contributions to social insurance schemes such as social security and pensions that provide benefits to employees.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of expense", "short_unit": "%" }, "gc_xpn_gsrv_cn": { "title": "Goods and services expense (current LCU)", "description_from_producer": "Goods and services include all government payments in exchange for goods and services used for the production of market and nonmarket goods and services. Own-account capital formation is excluded.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_xpn_gsrv_zs": { "title": "Goods and services expense (% of expense)", "description_from_producer": "Goods and services include all government payments in exchange for goods and services used for the production of market and nonmarket goods and services. Own-account capital formation is excluded.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of expense", "short_unit": "%" }, "gc_xpn_intp_cn": { "title": "Interest payments (current LCU)", "description_from_producer": "Interest payments include interest payments on government debt--including long-term bonds, long-term loans, and other debt instruments--to domestic and foreign residents.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_xpn_intp_rv_zs": { "title": "Interest payments (% of revenue)", "description_from_producer": "Interest payments include interest payments on government debt--including long-term bonds, long-term loans, and other debt instruments--to domestic and foreign residents.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of revenue", "short_unit": "%" }, "gc_xpn_intp_zs": { "title": "Interest payments (% of expense)", "description_from_producer": "Interest payments include interest payments on government debt--including long-term bonds, long-term loans, and other debt instruments--to domestic and foreign residents.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of expense", "short_unit": "%" }, "gc_xpn_othr_cn": { "title": "Other expense (current LCU)", "description_from_producer": "Other expense is spending on dividends, rent, and other miscellaneous expenses, including provision for consumption of fixed capital.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_xpn_othr_zs": { "title": "Other expense (% of expense)", "description_from_producer": "Other expense is spending on dividends, rent, and other miscellaneous expenses, including provision for consumption of fixed capital.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of expense", "short_unit": "%" }, "gc_xpn_totl_cn": { "title": "Expense (current LCU)", "description_from_producer": "Expense is cash payments for operating activities of the government in providing goods and services. It includes compensation of employees (such as wages and salaries), interest and subsidies, grants, social benefits, and other expenses such as rent and dividends.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_xpn_totl_gd_zs": { "title": "Expense (% of GDP)", "description_from_producer": "Expense is cash payments for operating activities of the government in providing goods and services. It includes compensation of employees (such as wages and salaries), interest and subsidies, grants, social benefits, and other expenses such as rent and dividends.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "gc_xpn_trft_cn": { "title": "Subsidies and other transfers (current LCU)", "description_from_producer": "Subsidies, grants, and other social benefits include all unrequited, nonrepayable transfers on current account to private and public enterprises; grants to foreign governments, international organizations, and other government units; and social security, social assistance benefits, and employer social benefits in cash and in kind.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "gc_xpn_trft_zs": { "title": "Subsidies and other transfers (% of expense)", "description_from_producer": "Subsidies, grants, and other social benefits include all unrequited, nonrepayable transfers on current account to private and public enterprises; grants to foreign governments, international organizations, and other government units; and social security, social assistance benefits, and employer social benefits in cash and in kind.\n\nLimitations and exceptions: For most countries central government finance data have been consolidated into one account, but for others only budgetary central government accounts are available. Countries reporting budgetary data are noted in the country metadata. Because budgetary accounts may not include all central government units (such as social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incomplete view of total public finance.\n\nData on government revenue and expense are collected by the IMF through questionnaires to member countries and by the Organisation for Economic Co-operation and Development (OECD). Despite IMF efforts to standardize data collection, statistics are often incomplete, untimely, and not comparable across countries.\n\nStatistical concept and methodology: The IMF's Government Finance Statistics Manual 2014, harmonized with the 2008 SNA, recommends an accrual accounting method, focusing on all economic events affecting assets, liabilities, revenues, and expenses, not just those represented by cash transactions. It accounts for all changes in stocks, so stock data at the end of an accounting period equal stock data at the beginning of the period plus flows over the period. The 1986 manual considered only debt stocks.\n\nGovernment finance statistics are reported in local currency. Many countries report government finance data by fiscal year; see country metadata for information on fiscal year end by country.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of expense", "short_unit": "%" }, "ge_est": { "title": "Government Effectiveness: Estimate", "description_from_producer": "Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Estimate gives the country's score on the aggregate indicator, in units of a standard normal distribution, i.e. ranging from approximately -2.5 to 2.5.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ge_no_src": { "title": "Government Effectiveness: Number of Sources", "description_from_producer": "Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ge_per_rnk": { "title": "Government Effectiveness: Percentile Rank", "description_from_producer": "Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ge_per_rnk_lower": { "title": "Government Effectiveness: Percentile Rank, Lower Bound of 90% Confidence Interval", "description_from_producer": "Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ge_per_rnk_upper": { "title": "Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval", "description_from_producer": "Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ge_std_err": { "title": "Government Effectiveness: Standard Error", "description_from_producer": "Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "gf_xpd_budg_zs": { "title": "Primary government expenditures as a proportion of original approved budget (%)", "description_from_producer": "Primary government expenditures as a proportion of original approved budget measures the extent to which aggregate budget expenditure outturn reflects the amount originally approved, as defined in government budget documentation and fiscal reports. The coverage is budgetary central government (BCG) and the time period covered is the last three completed fiscal years.", "origins": [ { "producer": "Public Expenditure and Financial Accountability program (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "hd_hci_ovrl": { "title": "Human capital index (HCI) (scale 0-1)", "description_from_producer": "The HCI calculates the contributions of health and education to worker productivity. The final index score ranges from zero to one and measures the productivity as a future worker of child born today relative to the benchmark of full health and complete education.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "hd_hci_ovrl_fe": { "title": "Human capital index (HCI), female (scale 0-1)", "description_from_producer": "The HCI calculates the contributions of health and education to worker productivity. The final index score ranges from zero to one and measures the productivity as a future worker of child born today relative to the benchmark of full health and complete education.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "hd_hci_ovrl_lb": { "title": "Human capital index (HCI), lower bound (scale 0-1)", "description_from_producer": "The HCI lower bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the lower bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "hd_hci_ovrl_lb_fe": { "title": "Human capital index (HCI), female, lower bound (scale 0-1)", "description_from_producer": "The HCI lower bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the lower bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "hd_hci_ovrl_lb_ma": { "title": "Human capital index (HCI), male, lower bound (scale 0-1)", "description_from_producer": "The HCI lower bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the lower bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "hd_hci_ovrl_ma": { "title": "Human capital index (HCI), male (scale 0-1)", "description_from_producer": "The HCI calculates the contributions of health and education to worker productivity. The final index score ranges from zero to one and measures the productivity as a future worker of child born today relative to the benchmark of full health and complete education.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "hd_hci_ovrl_ub": { "title": "Human capital index (HCI), upper bound (scale 0-1)", "description_from_producer": "The HCI upper bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the upper bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "hd_hci_ovrl_ub_fe": { "title": "Human capital index (HCI), female, upper bound (scale 0-1)", "description_from_producer": "The HCI upper bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the upper bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "hd_hci_ovrl_ub_ma": { "title": "Human capital index (HCI), male, upper bound (scale 0-1)", "description_from_producer": "The HCI upper bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the upper bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ic_bus_dfrn_xq": { "title": "Ease of doing business score (0 = lowest performance to 100 = best performance)", "description_from_producer": "The ease of doing business scores benchmark economies with respect to regulatory best practice, showing the proximity to the best regulatory performance on each Doing Business indicator. An economy\u2019s score is indicated on a scale from 0 to 100, where 0 represents the worst regulatory performance and 100 the best regulatory performance.\n\nStatistical concept and methodology: The aggregate ease of doing business score for each economy is the simple average of their scores on each of the 10 topics included in the ranking: starting a business, dealing with construction permits, getting electricity, registering property, getting credit, protecting minority investors, paying taxes, trading across borders, enforcing contracts and resolving insolvency. All topics are weighted equally. Please refer to the Doing Business website for a detailed description of the methodology: https://www.doingbusiness.org/en/methodology", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "0=lowest performance to 100=frontier" }, "ic_bus_disc_xq": { "title": "Business extent of disclosure index (0=less disclosure to 10=more disclosure)", "description_from_producer": "Disclosure index measures the extent to which investors are protected through disclosure of ownership and financial information. The index ranges from 0 to 10, with higher values indicating more disclosure.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures.\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nCorporations are instruments of entrepreneurship and growth. They can also be abused for personal gain. The indicator measures the strength of minority shareholder protections against directors' misuse of corporate assets for personal gain.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "0=less disclosure to 10=more disclosure" }, "ic_bus_ease_xq": { "title": "Ease of doing business rank (1=most business-friendly regulations)", "description_from_producer": "Ease of doing business ranks economies from 1 to 190, with first place being the best. The ranking of economies is determined by sorting the aggregate ease of doing business scores. A high ranking (a low numerical rank) means that the regulatory environment is conducive to business operation.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: The ranking of economies is determined by sorting the aggregate ease of doing business scores. The aggregate ease of doing business score for each economy is the simple average of their scores on each of the 10 topics included in the ranking: starting a business, dealing with construction permits, getting electricity, registering property, getting credit, protecting minority investors, paying taxes, trading across borders, enforcing contracts and resolving insolvency. All topics are weighted equally.\n\nData are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected. Please also refer to the Doing Business website for additional information: https://www.doingbusiness.org/en/methodology", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=most business-friendly regulations" }, "ic_bus_ndns_zs": { "title": "New business density (new registrations per 1,000 people ages 15-64)", "description_from_producer": "New businesses registered are the number of new limited liability corporations (or its equivalent) registered in the calendar year.\n\nLimitations and exceptions: The definition of entrepreneurship used is limited to the formal sector. Yet, it should be noted that the exclusion of the informal sector is based on the difficulties of quantifying the number of firms that compose it, rather than on its relevance for developing economies. The Entrepreneurship Database facilitates the analysis of the growth of the formal private sector and the identification of factors that encourage firms to begin operations in or transition to the formal sector. Data is collected all limited liability corporations regardless of size. Partnerships and sole proprietorships are not considered in the analysis due to the differences with respect to their definition and regulation worldwide. Data on the number of total or closed firms are not included due to heterogeneity in how these entities are defined and measured.\n\nThe Entrepreneurship Database is a critical source of data that facilitates the measurement of entrepreneurial activity across countries and over time. The data also allows for a deeper understanding of the relationship between new firm registration, the regulatory environment, and economic growth. Previous research using the Entrepreneurship Database has shown a significant relationship between the level of cost, time, and procedures required to start a business and new firm registration.\n\nTo facilitate cross-country comparability, the Entrepreneurship Database employs a consistent unit of measurement, source of information, and concept of entrepreneurship that is applicable and available among the diverse sample of participating economies.\n\nStatistical concept and methodology: To facilitate cross-country comparability, the Entrepreneurship Database employs a consistent unit of measurement, source of information, and concept of entrepreneurship that is applicable and available among the diverse sample of participating economies.\n\nThe data collection process involves telephone interviews and email correspondence with business registries in 170 economies. The main sources of information for this study are national business registries. In a limited number of cases where the business registry was unable to provide the data - most often due to an absence of digitized registration systems - the Entrepreneurship Database uses other alternatives sources, such as statistical agencies, tax and labor agencies, chambers of commerce, and private vendors or publicly available data.\n\nThe units of measurement are private, formal sector companies with limited liability.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "new registrations per 1,000 people ages 15-64", "short_unit": "new registrations" }, "ic_bus_nreg": { "title": "New businesses registered (number)", "description_from_producer": "New businesses registered are the number of new limited liability corporations (or its equivalent) registered in the calendar year.\n\nLimitations and exceptions: The definition of entrepreneurship used is limited to the formal sector. Yet, it should be noted that the exclusion of the informal sector is based on the difficulties of quantifying the number of firms that compose it, rather than on its relevance for developing economies. The Entrepreneurship Database facilitates the analysis of the growth of the formal private sector and the identification of factors that encourage firms to begin operations in or transition to the formal sector. Data is collected all limited liability corporations regardless of size. Partnerships and sole proprietorships are not considered in the analysis due to the differences with respect to their definition and regulation worldwide. Data on the number of total or closed firms are not included due to heterogeneity in how these entities are defined and measured.\n\nThe Entrepreneurship Database is a critical source of data that facilitates the measurement of entrepreneurial activity across countries and over time. The data also allows for a deeper understanding of the relationship between new firm registration, the regulatory environment, and economic growth. Previous research using the Entrepreneurship Database has shown a significant relationship between the level of cost, time, and procedures required to start a business and new firm registration.\n\nTo facilitate cross-country comparability, the Entrepreneurship Database employs a consistent unit of measurement, source of information, and concept of entrepreneurship that is applicable and available among the diverse sample of participating economies.\n\nStatistical concept and methodology: To facilitate cross-country comparability, the Entrepreneurship Database employs a consistent unit of measurement, source of information, and concept of entrepreneurship that is applicable and available among the diverse sample of participating economies.\n\nThe data collection process involves telephone interviews and email correspondence with business registries in 170 economies. The main sources of information for this study are national business registries. In a limited number of cases where the business registry was unable to provide the data - most often due to an absence of digitized registration systems - the Entrepreneurship Database uses other alternatives sources, such as statistical agencies, tax and labor agencies, chambers of commerce, and private vendors or publicly available data.\n\nThe units of measurement are private, formal sector companies with limited liability.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number", "short_unit": "number" }, "ic_crd_info_xq": { "title": "Depth of credit information index (0=low to 8=high)", "description_from_producer": "Depth of credit information index measures rules affecting the scope, accessibility, and quality of credit information available through public or private credit registries. The index ranges from 0 to 8, with higher values indicating the availability of more credit information, from either a public registry or a private bureau, to facilitate lending decisions.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: For Doing Business 2015, the credit information index has expanded with two new measurements, namely whether (1) banks and financial institutions access credit bureaus and credit registries' databases through an online platform or system-to-system connection; and (2) bureau or registry credit scores are offered as a value added service to help banks and financial institutions to assess the creditworthiness of borrowers. Furthermore, if the credit bureau or registry is not operational or covers less than 5% of the adult population, the score on the depth of credit information index is 0. (Previously, the coverage threshold to score on the credit information index was 0.1%. In Doing Business 2015 this threshold has been increased to 5%.)\n\nData are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected. For more information on methodology, see http://www.doingbusiness.org/Methodology/getting-credit#legalRights.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "0=low to 8=high" }, "ic_crd_prvt_zs": { "title": "Private credit bureau coverage (% of adults)", "description_from_producer": "Private credit bureau coverage reports the number of individuals or firms listed by a private credit bureau with current information on repayment history, unpaid debts, or credit outstanding. The number is expressed as a percentage of the adult population.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of adults", "short_unit": "%" }, "ic_crd_publ_zs": { "title": "Public credit registry coverage (% of adults)", "description_from_producer": "Public credit registry coverage reports the number of individuals and firms listed in a public credit registry with current information on repayment history, unpaid debts, or credit outstanding. The number is expressed as a percentage of the adult population.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: Please see: https://www.doingbusiness.org/en/methodology/getting-credit", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of adults", "short_unit": "%" }, "ic_cus_durs_ex": { "title": "Average time to clear exports through customs (days)", "description_from_producer": "Average time to clear exports through customs is the average number of days to clear direct exports through customs.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "ic_elc_durs": { "title": "Time to obtain an electrical connection (days)", "description_from_producer": "The average wait, in days, experienced to obtain an electrical connection from the day an establishment applies for it to the day it receives the service.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "ic_elc_outg": { "title": "Power outages in firms in a typical month (number)", "description_from_producer": "Power outages are the average number of power outages that establishments experience in a typical month.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number", "short_unit": "number" }, "ic_elc_outg_zs": { "title": "Firms experiencing electrical outages (% of firms)", "description_from_producer": "Percent of firms experiencing electrical outages during the previous fiscal year.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_elc_time": { "title": "Time required to get electricity (days)", "description_from_producer": "Time required to get electricity is the number of days to obtain a permanent electricity connection. The measure captures the median duration that the electricity utility and experts indicate is necessary in practice, rather than required by law, to complete a procedure.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nData records all procedures required for a business to obtain a permanent electricity connection. These procedures include applications and contracts with electricity utilities, all necessary inspections and clearances from the utility and other agencies and the external and final connection works.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected. Data starting in 2014 reflect the DB15-17 methodology change. Please also see: https://www.doingbusiness.org/en/methodology/getting-electricity", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "ic_exp_csbc_cd": { "title": "Cost to export, border compliance (US$)", "description_from_producer": "Border compliance captures the time and cost associated with compliance with the economy\u2019s customs regulations and with regulations relating to other inspections that are mandatory in order for the shipment to cross the economy\u2019s border, as well as the time and cost for handling that takes place at its port or border. The time and cost for this segment include time and cost for customs clearance and inspection procedures conducted by other government agencies.\n\nLimitations and exceptions: If inspections by agencies other than customs are conducted in 20% or fewer cases, the border compliance time and cost measures take into account only clearance and inspections by customs (the standard case). If inspections by other agencies take place in more than 20% of cases, the time and cost measures account for clearance and inspections by all agencies. Different types of inspections may take place with different probabilities\u2014for example, scanning may take place in 100% of cases while physical inspection occurs in 5% of cases. In situations like this, Doing Business would count the time only for scanning because it happens in more than 20% of cases while physical inspection does not. The border compliance time and cost for an economy do not include the time and cost for compliance with the regulations of any other economy.\n\nStatistical concept and methodology: The computation of border compliance time and cost depends on where the border compliance procedures take place, who requires and conducts the procedures and what is the probability that inspections will be conducted. If all customs clearance and other inspections take place at the port or border, the time estimate for border compliance takes this simultaneity into account. It is entirely possible that the border compliance time and cost could be negligible or zero, as in the case of trade between members of the European Union or other customs unions.\n\nIf some or all customs or other inspections take place at other locations, the time and cost for these procedures are added to the time and cost for those that take place at the port or border. In Kazakhstan, for example, all customs clearance and inspections take place at a customs post in Almaty that is not at the land border between Kazakhstan and China. In this case border compliance time is the sum of the time spent at the terminal in Almaty and the handling time at the border.\n\nDoing Business asks contributors to estimate the time and cost for clearance and inspections by customs agencies\u2014 defined as documentary and physical inspections for the purpose of calculating duties by verifying product classification, confirming quantity, determining origin and checking the veracity of other information on the customs declaration. (This category includes all inspections aimed at preventing smuggling.) These are clearance and inspection procedures that take place in the majority of cases and thus are considered the \"standard\" case. The time and cost estimates capture the efficiency of the customs agency of the economy.\n\nDoing Business also asks contributors to estimate the total time and cost for clearance and inspections by customs and all other government agencies for the specified product. These estimates account for inspections related to health, safety, phytosanitary standards, conformity and the like, and thus capture the efficiency of agencies that require and conduct these additional inspections.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "US$", "short_unit": "$" }, "ic_exp_csdc_cd": { "title": "Cost to export, documentary compliance (US$)", "description_from_producer": "Documentary compliance captures the time and cost associated with compliance with the documentary requirements of all government agencies of the origin economy, the destination economy and any transit economies. The aim is to measure the total burden of preparing the bundle of documents that will enable completion of the international trade for the product and partner pair assumed in the case study.\n\nStatistical concept and methodology: The time and cost for documentary compliance include the time and cost for obtaining documents (such as time spent to get the document issued and stamped); preparing documents (such as time spent gathering information to complete the customs declaration or certificate of origin); processing documents (such as time spent waiting for the relevant authority to issue a phytosanitary certificate); presenting documents (such as time spent showing a port terminal receipt to port authorities); and submitting documents (such as time spent submitting a customs declaration to the customs agency in person or electronically).\n\nAll electronic or paper submissions of information requested by any government agency in connection with the shipment are considered to be documents obtained, prepared and submitted during the export or import process. All documents prepared by the freight forwarder or customs broker for the product and partner pair assumed in the case study are included regardless of whether they are required by law or in practice. Any documents prepared and submitted so as to get access to preferential treatment\u2014 for example, a certificate of origin\u2014are included in the calculation of the time and cost for documentary compliance. Any documents prepared and submitted because of a perception that they ease the passage of the shipment are also included (for example, freight forwarders may prepare a packing list because in their experience this reduces the probability of physical or other intrusive inspections).\n\nIn addition, any documents that are mandatory for exporting or importing are included in the calculation of time and cost. Documents that need to be obtained only once are not counted, however. And Doing Business does not include documents needed to produce and sell in the domestic market\u2014such as certificates of third-party safety standards testing that may be required to sell toys domestically\u2014unless a government agency needs to see these documents during the export process.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "US$", "short_unit": "$" }, "ic_exp_tmbc": { "title": "Time to export, border compliance (hours)", "description_from_producer": "Border compliance captures the time and cost associated with compliance with the economy\u2019s customs regulations and with regulations relating to other inspections that are mandatory in order for the shipment to cross the economy\u2019s border, as well as the time and cost for handling that takes place at its port or border. The time and cost for this segment include time and cost for customs clearance and inspection procedures conducted by other government agencies.\n\nLimitations and exceptions: If inspections by agencies other than customs are conducted in 20% or fewer cases, the border compliance time and cost measures take into account only clearance and inspections by customs (the standard case). If inspections by other agencies take place in more than 20% of cases, the time and cost measures account for clearance and inspections by all agencies. Different types of inspections may take place with different probabilities\u2014for example, scanning may take place in 100% of cases while physical inspection occurs in 5% of cases. In situations like this, Doing Business would count the time only for scanning because it happens in more than 20% of cases while physical inspection does not. The border compliance time and cost for an economy do not include the time and cost for compliance with the regulations of any other economy.\n\nStatistical concept and methodology: The computation of border compliance time and cost depends on where the border compliance procedures take place, who requires and conducts the procedures and what is the probability that inspections will be conducted. If all customs clearance and other inspections take place at the port or border, the time estimate for border compliance takes this simultaneity into account. It is entirely possible that the border compliance time and cost could be negligible or zero, as in the case of trade between members of the European Union or other customs unions.\n\nIf some or all customs or other inspections take place at other locations, the time and cost for these procedures are added to the time and cost for those that take place at the port or border. In Kazakhstan, for example, all customs clearance and inspections take place at a customs post in Almaty that is not at the land border between Kazakhstan and China. In this case border compliance time is the sum of the time spent at the terminal in Almaty and the handling time at the border.\n\nDoing Business asks contributors to estimate the time and cost for clearance and inspections by customs agencies\u2014 defined as documentary and physical inspections for the purpose of calculating duties by verifying product classification, confirming quantity, determining origin and checking the veracity of other information on the customs declaration. (This category includes all inspections aimed at preventing smuggling.) These are clearance and inspection procedures that take place in the majority of cases and thus are considered the \"standard\" case. The time and cost estimates capture the efficiency of the customs agency of the economy.\n\nDoing Business also asks contributors to estimate the total time and cost for clearance and inspections by customs and all other government agencies for the specified product. These estimates account for inspections related to health, safety, phytosanitary standards, conformity and the like, and thus capture the efficiency of agencies that require and conduct these additional inspections.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours", "short_unit": "hours" }, "ic_exp_tmdc": { "title": "Time to export, documentary compliance (hours)", "description_from_producer": "Documentary compliance captures the time and cost associated with compliance with the documentary requirements of all government agencies of the origin economy, the destination economy and any transit economies. The aim is to measure the total burden of preparing the bundle of documents that will enable completion of the international trade for the product and partner pair assumed in the case study.\n\nStatistical concept and methodology: The time and cost for documentary compliance include the time and cost for obtaining documents (such as time spent to get the document issued and stamped); preparing documents (such as time spent gathering information to complete the customs declaration or certificate of origin); processing documents (such as time spent waiting for the relevant authority to issue a phytosanitary certificate); presenting documents (such as time spent showing a port terminal receipt to port authorities); and submitting documents (such as time spent submitting a customs declaration to the customs agency in person or electronically).\n\nAll electronic or paper submissions of information requested by any government agency in connection with the shipment are considered to be documents obtained, prepared and submitted during the export or import process. All documents prepared by the freight forwarder or customs broker for the product and partner pair assumed in the case study are included regardless of whether they are required by law or in practice. Any documents prepared and submitted so as to get access to preferential treatment\u2014 for example, a certificate of origin\u2014are included in the calculation of the time and cost for documentary compliance. Any documents prepared and submitted because of a perception that they ease the passage of the shipment are also included (for example, freight forwarders may prepare a packing list because in their experience this reduces the probability of physical or other intrusive inspections).\n\nIn addition, any documents that are mandatory for exporting or importing are included in the calculation of time and cost. Documents that need to be obtained only once are not counted, however. And Doing Business does not include documents needed to produce and sell in the domestic market\u2014such as certificates of third-party safety standards testing that may be required to sell toys domestically\u2014unless a government agency needs to see these documents during the export process.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours", "short_unit": "hours" }, "ic_frm_bkwc_zs": { "title": "Firms using banks to finance working capital (% of firms)", "description_from_producer": "Firms using banks to finance working capital are the percentage of firms using bank loans to finance working capital.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_bnks_zs": { "title": "Firms using banks to finance investment (% of firms)", "description_from_producer": "Firms using banks to finance investment are the percentage of firms using banks to finance investments.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_brib_zs": { "title": "Bribery incidence (% of firms experiencing at least one bribe payment request)", "description_from_producer": "Bribery incidence is the percentage of firms experiencing at least one bribe payment request across 6 public transactions dealing with utilities access, permits, licenses, and taxes.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms experiencing at least one bribe payment request", "short_unit": "%" }, "ic_frm_cmpu_zs": { "title": "Firms competing against unregistered firms (% of firms)", "description_from_producer": "Firms competing against unregistered firms are the percentage of firms competing against unregistered or informal firms.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_corr_zs": { "title": "Informal payments to public officials (% of firms)", "description_from_producer": "Informal payments to public officials are the percentage of firms expected to make informal payments to public officials to \"get things done\" with regard to customs, taxes, licenses, regulations, services, and the like.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_crim_zs": { "title": "Losses due to theft and vandalism (% of annual sales of affected firms)", "description_from_producer": "Average losses as a result of theft, robbery, vandalism or arson that occurred on the establishment\u2019s premises calculated as a percentage of annual sales. The value represents the average losses for all firms which reported losses (please see indicator IC.FRM.THEV.ZS).\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nPlease also refer to the methodology information on the Enterprise Surveys site: https://www.enterprisesurveys.org/en/methodology\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of annual sales for affected firms", "short_unit": "%" }, "ic_frm_durs": { "title": "Time required to obtain an operating license (days)", "description_from_producer": "Time required to obtain operating license is the average wait to obtain an operating license from the day the establishment applied for it to the day it was granted.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "ic_frm_femm_zs": { "title": "Firms with female top manager (% of firms)", "description_from_producer": "Firms with female top manager refers to the percentage of firms in the private sector who have females as top managers. Top manager refers to the highest ranking manager or CEO of the establishment. This person may be the owner if he/she works as the manager of the firm. The results are based on surveys of more than 100,000 private firms.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_femo_zs": { "title": "Firms with female participation in ownership (% of firms)", "description_from_producer": "Firms with female participation in ownership are the percentage of firms with a woman among the principal owners.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_freg_zs": { "title": "Firms formally registered when operations started (% of firms)", "description_from_producer": "Firms formally registered when operations started are the percentage of firms formally registered when they started operations in the country.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_infm_zs": { "title": "Firms that do not report all sales for tax purposes (% of firms)", "description_from_producer": "Firms that do not report all sales for tax purposes are the percentage of firms that expressed that a typical firm reports less than 100 percent of sales for tax purposes; such firms are termed \"informal firms.\"\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: Most surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org. For surveys which did not strictly adhere to the global Enterprise Surveys methodology, plus Afghanistan, any inference from one of these surveys is representative only for the data sample itself, not the country level.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_metg_zs": { "title": "Firms visited or required meetings with tax officials (% of firms)", "description_from_producer": "Percent of firms that were visited or required to meet with tax officials.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_outg_zs": { "title": "Value lost due to electrical outages (% of sales for affected firms)", "description_from_producer": "Average losses due to electrical outages, as percentage of total annual sales. The value represents average losses for all firms which reported outages (please see indicator IC.ELC.OUTG.ZS).\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of sales for affected firms", "short_unit": "%" }, "ic_frm_rsdv_zs": { "title": "Firms that spend on R&D (% of firms)", "description_from_producer": "Percent of firms that spend on research and development.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_thev_zs": { "title": "Firms experiencing losses due to theft and vandalism (% of firms)", "description_from_producer": "Percent of firms experiencing losses due to theft, robbery, vandalism or arson that occurred on the establishment's premises.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_frm_trng_zs": { "title": "Firms offering formal training (% of firms)", "description_from_producer": "Firms offering formal training are the percentage of firms offering formal training programs for their permanent, full-time employees.\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_gov_durs_zs": { "title": "Time spent dealing with the requirements of government regulations (% of senior management time)", "description_from_producer": "Time spent dealing with the requirements of government regulations is the proportion of senior management's time, in a typical week, that is spent dealing with the requirements imposed by government regulations (e.g., taxes, customs, labor regulations, licensing and registration, including dealings with officials, and completing forms).\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of senior management time", "short_unit": "%" }, "ic_imp_csbc_cd": { "title": "Cost to import, border compliance (US$)", "description_from_producer": "Border compliance captures the time and cost associated with compliance with the economy\u2019s customs regulations and with regulations relating to other inspections that are mandatory in order for the shipment to cross the economy\u2019s border, as well as the time and cost for handling that takes place at its port or border. The time and cost for this segment include time and cost for customs clearance and inspection procedures conducted by other government agencies.\n\nLimitations and exceptions: If inspections by agencies other than customs are conducted in 20% or fewer cases, the border compliance time and cost measures take into account only clearance and inspections by customs (the standard case). If inspections by other agencies take place in more than 20% of cases, the time and cost measures account for clearance and inspections by all agencies. Different types of inspections may take place with different probabilities\u2014for example, scanning may take place in 100% of cases while physical inspection occurs in 5% of cases. In situations like this, Doing Business would count the time only for scanning because it happens in more than 20% of cases while physical inspection does not. The border compliance time and cost for an economy do not include the time and cost for compliance with the regulations of any other economy.\n\nStatistical concept and methodology: The computation of border compliance time and cost depends on where the border compliance procedures take place, who requires and conducts the procedures and what is the probability that inspections will be conducted. If all customs clearance and other inspections take place at the port or border, the time estimate for border compliance takes this simultaneity into account. It is entirely possible that the border compliance time and cost could be negligible or zero, as in the case of trade between members of the European Union or other customs unions.\n\nIf some or all customs or other inspections take place at other locations, the time and cost for these procedures are added to the time and cost for those that take place at the port or border. In Kazakhstan, for example, all customs clearance and inspections take place at a customs post in Almaty that is not at the land border between Kazakhstan and China. In this case border compliance time is the sum of the time spent at the terminal in Almaty and the handling time at the border.\n\nDoing Business asks contributors to estimate the time and cost for clearance and inspections by customs agencies\u2014 defined as documentary and physical inspections for the purpose of calculating duties by verifying product classification, confirming quantity, determining origin and checking the veracity of other information on the customs declaration. (This category includes all inspections aimed at preventing smuggling.) These are clearance and inspection procedures that take place in the majority of cases and thus are considered the \"standard\" case. The time and cost estimates capture the efficiency of the customs agency of the economy.\n\nDoing Business also asks contributors to estimate the total time and cost for clearance and inspections by customs and all other government agencies for the specified product. These estimates account for inspections related to health, safety, phytosanitary standards, conformity and the like, and thus capture the efficiency of agencies that require and conduct these additional inspections.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "US$", "short_unit": "$" }, "ic_imp_csdc_cd": { "title": "Cost to import, documentary compliance (US$)", "description_from_producer": "Documentary compliance captures the time and cost associated with compliance with the documentary requirements of all government agencies of the origin economy, the destination economy and any transit economies. The aim is to measure the total burden of preparing the bundle of documents that will enable completion of the international trade for the product and partner pair assumed in the case study.\n\nStatistical concept and methodology: The time and cost for documentary compliance include the time and cost for obtaining documents (such as time spent to get the document issued and stamped); preparing documents (such as time spent gathering information to complete the customs declaration or certificate of origin); processing documents (such as time spent waiting for the relevant authority to issue a phytosanitary certificate); presenting documents (such as time spent showing a port terminal receipt to port authorities); and submitting documents (such as time spent submitting a customs declaration to the customs agency in person or electronically).\n\nAll electronic or paper submissions of information requested by any government agency in connection with the shipment are considered to be documents obtained, prepared and submitted during the export or import process. All documents prepared by the freight forwarder or customs broker for the product and partner pair assumed in the case study are included regardless of whether they are required by law or in practice. Any documents prepared and submitted so as to get access to preferential treatment\u2014 for example, a certificate of origin\u2014are included in the calculation of the time and cost for documentary compliance. Any documents prepared and submitted because of a perception that they ease the passage of the shipment are also included (for example, freight forwarders may prepare a packing list because in their experience this reduces the probability of physical or other intrusive inspections).\n\nIn addition, any documents that are mandatory for exporting or importing are included in the calculation of time and cost. Documents that need to be obtained only once are not counted, however. And Doing Business does not include documents needed to produce and sell in the domestic market\u2014such as certificates of third-party safety standards testing that may be required to sell toys domestically\u2014unless a government agency needs to see these documents during the export process.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "US$", "short_unit": "$" }, "ic_imp_tmbc": { "title": "Time to import, border compliance (hours)", "description_from_producer": "Border compliance captures the time and cost associated with compliance with the economy\u2019s customs regulations and with regulations relating to other inspections that are mandatory in order for the shipment to cross the economy\u2019s border, as well as the time and cost for handling that takes place at its port or border. The time and cost for this segment include time and cost for customs clearance and inspection procedures conducted by other government agencies.\n\nLimitations and exceptions: If inspections by agencies other than customs are conducted in 20% or fewer cases, the border compliance time and cost measures take into account only clearance and inspections by customs (the standard case). If inspections by other agencies take place in more than 20% of cases, the time and cost measures account for clearance and inspections by all agencies. Different types of inspections may take place with different probabilities\u2014for example, scanning may take place in 100% of cases while physical inspection occurs in 5% of cases. In situations like this, Doing Business would count the time only for scanning because it happens in more than 20% of cases while physical inspection does not. The border compliance time and cost for an economy do not include the time and cost for compliance with the regulations of any other economy.\n\nStatistical concept and methodology: The computation of border compliance time and cost depends on where the border compliance procedures take place, who requires and conducts the procedures and what is the probability that inspections will be conducted. If all customs clearance and other inspections take place at the port or border, the time estimate for border compliance takes this simultaneity into account. It is entirely possible that the border compliance time and cost could be negligible or zero, as in the case of trade between members of the European Union or other customs unions.\n\nIf some or all customs or other inspections take place at other locations, the time and cost for these procedures are added to the time and cost for those that take place at the port or border. In Kazakhstan, for example, all customs clearance and inspections take place at a customs post in Almaty that is not at the land border between Kazakhstan and China. In this case border compliance time is the sum of the time spent at the terminal in Almaty and the handling time at the border.\n\nDoing Business asks contributors to estimate the time and cost for clearance and inspections by customs agencies\u2014 defined as documentary and physical inspections for the purpose of calculating duties by verifying product classification, confirming quantity, determining origin and checking the veracity of other information on the customs declaration. (This category includes all inspections aimed at preventing smuggling.) These are clearance and inspection procedures that take place in the majority of cases and thus are considered the \"standard\" case. The time and cost estimates capture the efficiency of the customs agency of the economy.\n\nDoing Business also asks contributors to estimate the total time and cost for clearance and inspections by customs and all other government agencies for the specified product. These estimates account for inspections related to health, safety, phytosanitary standards, conformity and the like, and thus capture the efficiency of agencies that require and conduct these additional inspections.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours", "short_unit": "hours" }, "ic_imp_tmdc": { "title": "Time to import, documentary compliance (hours)", "description_from_producer": "Documentary compliance captures the time and cost associated with compliance with the documentary requirements of all government agencies of the origin economy, the destination economy and any transit economies. The aim is to measure the total burden of preparing the bundle of documents that will enable completion of the international trade for the product and partner pair assumed in the case study.\n\nStatistical concept and methodology: The time and cost for documentary compliance include the time and cost for obtaining documents (such as time spent to get the document issued and stamped); preparing documents (such as time spent gathering information to complete the customs declaration or certificate of origin); processing documents (such as time spent waiting for the relevant authority to issue a phytosanitary certificate); presenting documents (such as time spent showing a port terminal receipt to port authorities); and submitting documents (such as time spent submitting a customs declaration to the customs agency in person or electronically).\n\nAll electronic or paper submissions of information requested by any government agency in connection with the shipment are considered to be documents obtained, prepared and submitted during the export or import process. All documents prepared by the freight forwarder or customs broker for the product and partner pair assumed in the case study are included regardless of whether they are required by law or in practice. Any documents prepared and submitted so as to get access to preferential treatment\u2014 for example, a certificate of origin\u2014are included in the calculation of the time and cost for documentary compliance. Any documents prepared and submitted because of a perception that they ease the passage of the shipment are also included (for example, freight forwarders may prepare a packing list because in their experience this reduces the probability of physical or other intrusive inspections).\n\nIn addition, any documents that are mandatory for exporting or importing are included in the calculation of time and cost. Documents that need to be obtained only once are not counted, however. And Doing Business does not include documents needed to produce and sell in the domestic market\u2014such as certificates of third-party safety standards testing that may be required to sell toys domestically\u2014unless a government agency needs to see these documents during the export process.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours", "short_unit": "hours" }, "ic_isv_durs": { "title": "Time to resolve insolvency (years)", "description_from_producer": "Time to resolve insolvency is the number of years from the filing for insolvency in court until the resolution of distressed assets.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures.\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nThe indicator measures the time, cost, and outcome of insolvency proceedings involving domestic entities. The time required for creditors to recover their credit is recorded in calendar years. The cost of the proceedings is recorded as a percentage of the value of the debtor's estate.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "years", "short_unit": "years" }, "ic_lgl_cred_xq": { "title": "Strength of legal rights index (0=weak to 12=strong)", "description_from_producer": "Strength of legal rights index measures the degree to which collateral and bankruptcy laws protect the rights of borrowers and lenders and thus facilitate lending. The index ranges from 0 to 12, with higher scores indicating that these laws are better designed to expand access to credit.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures.\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected. Data starting in 2013 reflect the DB15-17 methodology change. For more information on methodology, see http://www.doingbusiness.org/Methodology/getting-credit#legalRights.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "0=weak to 12=strong" }, "ic_lgl_durs": { "title": "Time required to enforce a contract (days)", "description_from_producer": "Time required to enforce a contract is the number of calendar days from the filing of the lawsuit in court until the final determination and, in appropriate cases, payment.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures.\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nA judicial system that provides effective commercial dispute resolution is crucial to a healthy economy. Without one, firms risk finding themselves operating in an environment where compliance with contractual obligations is not the norm.\n\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "ic_prp_durs": { "title": "Time required to register property (days)", "description_from_producer": "Time required to register property is the number of calendar days needed for businesses to secure rights to property.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures.\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nThe indicator records the procedures necessary for a business to purchase a property from another business and to formally transfer the property title to the buyer's name. The process starts with obtaining the necessary documents, such as a copy of the seller's title, and ends when the buyer is registered as the new owner of the property. Every procedure required by law or necessary in practice is included, whether it is the responsibility of the seller or the buyer and even if it must be completed by a third party on their behalf.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "ic_prp_proc": { "title": "Procedures to register property (number)", "description_from_producer": "Number of procedures to register property is the number of procedures required for a businesses to secure rights to property.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nThe indicator records the procedures necessary for a business to purchase a property from another business and to formally transfer the property title to the buyer's name. The process starts with obtaining the necessary documents, such as a copy of the seller's title, and ends when the buyer is registered as the new owner of the property. Every procedure required by law or necessary in practice is included, whether it is the responsibility of the seller or the buyer and even if it must be completed by a third party on their behalf.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected. Data starting in 2015 reflect the DB15-17 methodology change. Please also see: https://www.doingbusiness.org/en/methodology/registering-property", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number", "short_unit": "number" }, "ic_reg_cost_pc_fe_zs": { "title": "Cost of business start-up procedures, female (% of GNI per capita)", "description_from_producer": "Cost to register a business is normalized by presenting it as a percentage of gross national income (GNI) per capita.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nEntrepreneurs around the world face a range of challenges. One of them is inefficient regulation. This indicator measures the number of procedures, time, cost and paid-in minimum capital requirement for a small- to medium-size limited liability company to start up and formally operate in each economy\u2019s largest business city. To make the data comparable across 190 economies, Doing Business uses a standardized business that is 100% domestically owned, has a start-up capital equivalent to 10 times the income per capita, engages in general industrial or commercial activities and employs between 10 and 50 people one month after the commencement of operations, all of whom are domestic nationals. The starting a business indicators consider two cases of local limited liability companies that are identical in all aspects, except that one company is owned by five married women and the other by five married men.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI per capita", "short_unit": "%" }, "ic_reg_cost_pc_ma_zs": { "title": "Cost of business start-up procedures, male (% of GNI per capita)", "description_from_producer": "Cost to register a business is normalized by presenting it as a percentage of gross national income (GNI) per capita.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nEntrepreneurs around the world face a range of challenges. One of them is inefficient regulation. This indicator measures the paid-in minimum capital requirement for a small- to medium-size limited liability company to start up and formally operate in each economy\u2019s largest business city. To make the data comparable across 190 economies, Doing Business uses a standardized business that is 100% domestically owned, has a start-up capital equivalent to 10 times the income per capita, engages in general industrial or commercial activities and employs between 10 and 50 people one month after the commencement of operations, all of whom are domestic nationals. The starting a business indicators consider two cases of local limited liability companies that are identical in all aspects, except that one company is owned by five married women and the other by five married men.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI per capita", "short_unit": "%" }, "ic_reg_cost_pc_zs": { "title": "Cost of business start-up procedures (% of GNI per capita)", "description_from_producer": "Cost to register a business is normalized by presenting it as a percentage of gross national income (GNI) per capita.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures.\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nEntrepreneurs around the world face a range of challenges. One of them is inefficient regulation. The indicator measures the procedures, time, cost and paid-in minimum capital required for a small or medium-size limited liability company to start up and formally operate.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI per capita", "short_unit": "%" }, "ic_reg_durs": { "title": "Time required to start a business (days)", "description_from_producer": "Time required to start a business is the number of calendar days needed to complete the procedures to legally operate a business. If a procedure can be speeded up at additional cost, the fastest procedure, independent of cost, is chosen.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures.\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nEntrepreneurs around the world face a range of challenges. One of them is inefficient regulation. The indicator measures the procedures, time, cost and paid-in minimum capital required for a small or medium-size limited liability company to start up and formally operate.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "ic_reg_durs_fe": { "title": "Time required to start a business, female (days)", "description_from_producer": "Time required to start a business is the number of calendar days needed to complete the procedures to legally operate a business. If a procedure can be speeded up at additional cost, the fastest procedure, independent of cost, is chosen.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nEntrepreneurs around the world face a range of challenges. One of them is inefficient regulation. This indicator measures the time for a small- to medium-size limited liability company to start up and formally operate in each economy\u2019s largest business city. To make the data comparable across 190 economies, Doing Business uses a standardized business that is 100% domestically owned, has a start-up capital equivalent to 10 times the income per capita, engages in general industrial or commercial activities and employs between 10 and 50 people one month after the commencement of operations, all of whom are domestic nationals. The starting a business indicators consider two cases of local limited liability companies that are identical in all aspects, except that one company is owned by five married women and the other by five married men.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "ic_reg_durs_ma": { "title": "Time required to start a business, male (days)", "description_from_producer": "Time required to start a business is the number of calendar days needed to complete the procedures to legally operate a business. If a procedure can be speeded up at additional cost, the fastest procedure, independent of cost, is chosen.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nEntrepreneurs around the world face a range of challenges. One of them is inefficient regulation. This indicator measures the time for a small- to medium-size limited liability company to start up and formally operate in each economy\u2019s largest business city. To make the data comparable across 190 economies, Doing Business uses a standardized business that is 100% domestically owned, has a start-up capital equivalent to 10 times the income per capita, engages in general industrial or commercial activities and employs between 10 and 50 people one month after the commencement of operations, all of whom are domestic nationals. The starting a business indicators consider two cases of local limited liability companies that are identical in all aspects, except that one company is owned by five married women and the other by five married men.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "ic_reg_proc": { "title": "Start-up procedures to register a business (number)", "description_from_producer": "Start-up procedures are those required to start a business, including interactions to obtain necessary permits and licenses and to complete all inscriptions, verifications, and notifications to start operations. Data are for businesses with specific characteristics of ownership, size, and type of production.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures.\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nEntrepreneurs around the world face a range of challenges. One of them is inefficient regulation. The indicator measures the procedures, time, cost and paid-in minimum capital required for a small or medium-size limited liability company to start up and formally operate.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number", "short_unit": "number" }, "ic_reg_proc_fe": { "title": "Start-up procedures to register a business, female (number)", "description_from_producer": "Start-up procedures are those required to start a business, including interactions to obtain necessary permits and licenses and to complete all inscriptions, verifications, and notifications to start operations. Data are for businesses with specific characteristics of ownership, size, and type of production.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nEntrepreneurs around the world face a range of challenges. One of them is inefficient regulation. This indicator measures the number of procedure for a small- to medium-size limited liability company to start up and formally operate in each economy\u2019s largest business city. To make the data comparable across 190 economies, Doing Business uses a standardized business that is 100% domestically owned, has a start-up capital equivalent to 10 times the income per capita, engages in general industrial or commercial activities and employs between 10 and 50 people one month after the commencement of operations, all of whom are domestic nationals. The starting a business indicators consider two cases of local limited liability companies that are identical in all aspects, except that one company is owned by five married women and the other by five married men.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number", "short_unit": "number" }, "ic_reg_proc_ma": { "title": "Start-up procedures to register a business, male (number)", "description_from_producer": "Start-up procedures are those required to start a business, including interactions to obtain necessary permits and licenses and to complete all inscriptions, verifications, and notifications to start operations. Data are for businesses with specific characteristics of ownership, size, and type of production.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: This indicator measures the number of procedures for a small- to medium-size limited liability company to start up and formally operate in each economy\u2019s largest business city. To make the data comparable across 190 economies, Doing Business uses a standardized business that is 100% domestically owned, has a start-up capital equivalent to 10 times the income per capita, engages in general industrial or commercial activities and employs between 10 and 50 people one month after the commencement of operations, all of whom are domestic nationals. The starting a business indicators consider two cases of local limited liability companies that are identical in all aspects, except that one company is owned by five married women and the other by five married men.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number", "short_unit": "number" }, "ic_tax_durs": { "title": "Time to prepare and pay taxes (hours)", "description_from_producer": "Time to prepare and pay taxes is the time, in hours per year, it takes to prepare, file, and pay (or withhold) three major types of taxes: the corporate income tax, the value added or sales tax, and labor taxes, including payroll taxes and social security contributions.\n\nLimitations and exceptions: To make the data comparable across countries, several assumptions are made about businesses. The main assumptions are that they are limited liability companies, they operate in the country's most populous city, they are domestically owned, they perform general industrial or commercial activities, and they have certain levels of start-up capital, employees, and turnover.\n\nThe Doing Business methodology on business taxes is consistent with the Total Tax Contribution framework developed by PricewaterhouseCoopers (now PwC), which measures the taxes that are borne by companies and that affect their income statements. However, PwC bases its calculation on data from the largest companies in the economy, while Doing Business focuses on a standardized medium-size company.\n\nStatistical concept and methodology: The data covering taxes payable by businesses, measure all taxes and contributions that are government mandated (at any level - federal, state, or local), apply to standardized businesses, and have an impact in their income statements. The taxes covered go beyond the definition of a tax for government national accounts (compulsory, unrequited payments to general government) and also measure any imposts that affect business accounts. The main differences are in labor contributions and value added taxes.\n\nThe data account for government-mandated contributions paid by the employer to a requited private pension fund or workers insurance fund but exclude value added taxes because they do not affect the accounting profits of the business - that is, they are not reflected in the income statement.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours", "short_unit": "hours" }, "ic_tax_gift_zs": { "title": "Firms expected to give gifts in meetings with tax officials (% of firms)", "description_from_producer": "Firms expected to give gifts in meetings with tax officials is the percentage of firms that answered positively to the question \"was a gift or informal payment expected or requested during a meeting with tax officials?\"\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of firms", "short_unit": "%" }, "ic_tax_labr_cp_zs": { "title": "Labor tax and contributions (% of commercial profits)", "description_from_producer": "Labor tax and contributions is the amount of taxes and mandatory contributions on labor paid by the business.\n\nLimitations and exceptions: To make the data comparable across countries, several assumptions are made about businesses. The main assumptions are that they are limited liability companies, they operate in the country's most populous city, they are domestically owned, they perform general industrial or commercial activities, and they have certain levels of start-up capital, employees, and turnover.\n\nThe Doing Business methodology on business taxes is consistent with the Total Tax Contribution framework developed by PricewaterhouseCoopers (now PwC), which measures the taxes that are borne by companies and that affect their income statements. However, PwC bases its calculation on data from the largest companies in the economy, while Doing Business focuses on a standardized medium-size company.\n\nStatistical concept and methodology: The data covering taxes payable by businesses, measure all taxes and contributions that are government mandated (at any level - federal, state, or local), apply to standardized businesses, and have an impact in their income statements. The taxes covered go beyond the definition of a tax for government national accounts (compulsory, unrequited payments to general government) and also measure any imposts that affect business accounts. The main differences are in labor contributions and value added taxes.\n\nThe data account for government-mandated contributions paid by the employer to a requited private pension fund or workers insurance fund but exclude value added taxes because they do not affect the accounting profits of the business - that is, they are not reflected in the income statement.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial profits", "short_unit": "%" }, "ic_tax_metg": { "title": "Number of visits or required meetings with tax officials (average for affected firms)", "description_from_producer": "Average number of visits or required meetings with tax officials during the year. The value represents the average number of visits for all firms which reported being visited or required to meet with tax officials (please see indicator IC.FRM.METG.ZS).\n\nLimitations and exceptions: The sampling methodology for Enterprise Surveys is stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. The sampling weights take care of the varying probabilities of selection across different strata. Under certain conditions, estimates' precision under stratified random sampling will be higher than under simple random sampling (lower standard errors may result from the estimation procedure).\n\nThe strata for Enterprise Surveys are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), 20-99 (medium), and 100+ employees (large-sized firms). Since in most economies, the majority of firms are small and medium-sized, Enterprise Surveys oversample large firms since larger firms tend to be engines of job creation. Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity.\n\nIdeally the survey sample frame is derived from the universe of eligible firms obtained from the country\u2019s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank \u201cmanually\u201d constructs a list of eligible firms after 1) partitioning a country\u2019s cities of major economic activity into clusters and blocks, 2) randomly selecting a subset of blocks which will then be enumerated. In surveys conducted since 2005-06, survey documentation which explains the source of the sample frame and any special circumstances encountered during survey fieldwork are included with the collected datasets.\n\nObtaining panel data, i.e. interviews with the same firms across multiple years, is a priority in current Enterprise Surveys. When conducting a new Enterprise Survey in a country where data was previously collected, maximal effort is expended to re-interview as many firms (from the prior survey) as possible. For these panel firms, sampling weights can be adjusted to take into account the resulting altered probabilities of inclusion in the sample frame.\n\nStatistical concept and methodology: Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country\u2019s business environment. The remaining questions assess the survey respondents\u2019 opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nPlease also refer to the methodology information on the Enterprise Surveys site: https://www.enterprisesurveys.org/en/methodology\n\nNotes from original source: All surveys were administered using the Enterprise Surveys methodology as outlined in the Methodology page which can be found from www.enterprisesurveys.org.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "average for affected firms" }, "ic_tax_othr_cp_zs": { "title": "Other taxes payable by businesses (% of commercial profits)", "description_from_producer": "Other taxes payable by businesses include the amounts paid for property taxes, turnover taxes, and other small taxes such as municipal fees and vehicle and fuel taxes.\n\nLimitations and exceptions: To make the data comparable across countries, several assumptions are made about businesses. The main assumptions are that they are limited liability companies, they operate in the country's most populous city, they are domestically owned, they perform general industrial or commercial activities, and they have certain levels of start-up capital, employees, and turnover.\n\nThe Doing Business methodology on business taxes is consistent with the Total Tax Contribution framework developed by PricewaterhouseCoopers (now PwC), which measures the taxes that are borne by companies and that affect their income statements. However, PwC bases its calculation on data from the largest companies in the economy, while Doing Business focuses on a standardized medium-size company.\n\nStatistical concept and methodology: The data covering taxes payable by businesses, measure all taxes and contributions that are government mandated (at any level - federal, state, or local), apply to standardized businesses, and have an impact in their income statements. The taxes covered go beyond the definition of a tax for government national accounts (compulsory, unrequited payments to general government) and also measure any imposts that affect business accounts. The main differences are in labor contributions and value added taxes.\n\nThe data account for government-mandated contributions paid by the employer to a requited private pension fund or workers insurance fund but exclude value added taxes because they do not affect the accounting profits of the business - that is, they are not reflected in the income statement.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial profits", "short_unit": "%" }, "ic_tax_paym": { "title": "Tax payments (number)", "description_from_producer": "Tax payments by businesses are the total number of taxes paid by businesses, including electronic filing. The tax is counted as paid once a year even if payments are more frequent.\n\nLimitations and exceptions: To make the data comparable across countries, several assumptions are made about businesses. The main assumptions are that they are limited liability companies, they operate in the country's most populous city, they are domestically owned, they perform general industrial or commercial activities, and they have certain levels of start-up capital, employees, and turnover.\n\nThe Doing Business methodology on business taxes is consistent with the Total Tax Contribution framework developed by PricewaterhouseCoopers (now PwC), which measures the taxes that are borne by companies and that affect their income statements. However, PwC bases its calculation on data from the largest companies in the economy, while Doing Business focuses on a standardized medium-size company.\n\nStatistical concept and methodology: The data covering taxes payable by businesses, measure all taxes and contributions that are government mandated (at any level - federal, state, or local), apply to standardized businesses, and have an impact in their income statements. The taxes covered go beyond the definition of a tax for government national accounts (compulsory, unrequited payments to general government) and also measure any imposts that affect business accounts. The main differences are in labor contributions and value added taxes.\n\nThe data account for government-mandated contributions paid by the employer to a requited private pension fund or workers insurance fund but exclude value added taxes because they do not affect the accounting profits of the business - that is, they are not reflected in the income statement.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number", "short_unit": "number" }, "ic_tax_prft_cp_zs": { "title": "Profit tax (% of commercial profits)", "description_from_producer": "Profit tax is the amount of taxes on profits paid by the business.\n\nLimitations and exceptions: To make the data comparable across countries, several assumptions are made about businesses. The main assumptions are that they are limited liability companies, they operate in the country's most populous city, they are domestically owned, they perform general industrial or commercial activities, and they have certain levels of start-up capital, employees, and turnover.\n\nThe Doing Business methodology on business taxes is consistent with the Total Tax Contribution framework developed by PricewaterhouseCoopers (now PwC), which measures the taxes that are borne by companies and that affect their income statements. However, PwC bases its calculation on data from the largest companies in the economy, while Doing Business focuses on a standardized medium-size company.\n\nStatistical concept and methodology: The data covering taxes payable by businesses, measure all taxes and contributions that are government mandated (at any level - federal, state, or local), apply to standardized businesses, and have an impact in their income statements. The taxes covered go beyond the definition of a tax for government national accounts (compulsory, unrequited payments to general government) and also measure any imposts that affect business accounts. The main differences are in labor contributions and value added taxes.\n\nThe data account for government-mandated contributions paid by the employer to a requited private pension fund or workers insurance fund but exclude value added taxes because they do not affect the accounting profits of the business - that is, they are not reflected in the income statement.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial profits", "short_unit": "%" }, "ic_tax_totl_cp_zs": { "title": "Total tax and contribution rate (% of profit)", "description_from_producer": "Total tax rate measures the amount of taxes and mandatory contributions payable by businesses after accounting for allowable deductions and exemptions as a share of commercial profits. Taxes withheld (such as personal income tax) or collected and remitted to tax authorities (such as value added taxes, sales taxes or goods and service taxes) are excluded.\n\nLimitations and exceptions: To make the data comparable across countries, several assumptions are made about businesses. The main assumptions are that they are limited liability companies, they operate in the country's most populous city, they are domestically owned, they perform general industrial or commercial activities, and they have certain levels of start-up capital, employees, and turnover.\n\nThe Doing Business methodology on business taxes is consistent with the Total Tax Contribution framework developed by PricewaterhouseCoopers (now PwC), which measures the taxes that are borne by companies and that affect their income statements. However, PwC bases its calculation on data from the largest companies in the economy, while Doing Business focuses on a standardized medium-size company.\n\nStatistical concept and methodology: The data covering taxes payable by businesses, measure all taxes and contributions that are government mandated (at any level - federal, state, or local), apply to standardized businesses, and have an impact in their income statements. The taxes covered go beyond the definition of a tax for government national accounts (compulsory, unrequited payments to general government) and also measure any imposts that affect business accounts. The main differences are in labor contributions and value added taxes.\n\nThe data account for government-mandated contributions paid by the employer to a requited private pension fund or workers insurance fund but exclude value added taxes because they do not affect the accounting profits of the business - that is, they are not reflected in the income statement.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial profits", "short_unit": "%" }, "ic_wrh_durs": { "title": "Time required to build a warehouse (days)", "description_from_producer": "Time required to build a warehouse is the number of calendar days needed to complete the required procedures for building a warehouse. If a procedure can be speeded up at additional cost, the fastest procedure, independent of cost, is chosen.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nTo build a simple commercial warehouse and connect it to water, sewerage and a fixed telephone line, many construction regulations are required. Construction regulation matters for public safety. If procedures are too complicated or costly, builders tend to proceed without a permit. By some estimates 60-80 percent of building projects in developing economies are undertaken without the proper permits and approvals. Good regulations help ensure the safety standards that protect the public while making the permitting process efficient, transparent and affordable. Time is recorded in calendar days. The measure captures the median duration that local experts indicate is necessary to complete a procedure in practice. It is assumed that the minimum time required for each procedure is one day, except for procedures that can be fully completed online, for which the time required is recorded as half a day. Although procedures may take place simultaneously, they cannot start on the same day (that is, simultaneous procedures start on consecutive days), again with the exception of procedures that can be fully completed online. If a procedure can be accelerated legally for an additional cost, the fastest procedure is chosen if that option is more bene?cial to the economy\u2019s score. It is assumed that BuildCo does not waste time and commits to completing each remaining procedure without delay. The time that BuildCo spends on gathering information is not taken into account. It is assumed that BuildCo follows all building requirements and their sequence as required. Data starting in 2014 reflect the DB15-17 methodology change.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected. Please also see: https://www.doingbusiness.org/en/methodology/dealing-with-construction-permits", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "ic_wrh_proc": { "title": "Procedures to build a warehouse (number)", "description_from_producer": "Number of procedures to build a warehouse is the number of interactions of a company's employees or managers with external parties, including government agency staff, public inspectors, notaries, land registry and cadastre staff, and technical experts apart from architects and engineers.\n\nLimitations and exceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq\n\nStatistical concept and methodology: Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.\n\nTo build a simple commercial warehouse and connect it to water, sewerage and a fixed telephone line, many construction regulations are required. Construction regulation matters for public safety. If procedures are too complicated or costly, builders tend to proceed without a permit. By some estimates 60-80 percent of building projects in developing economies are undertaken without the proper permits and approvals. Good regulations help ensure the safety standards that protect the public while making the permitting process efficient, transparent and affordable. A procedure is any interaction of the building company\u2019s employees, managers, or any party acting on behalf of the company, with external parties, including government agencies, notaries, the land registry, the cadastre, utility companies and public inspectors\u2014and the hiring of external private inspectors and technical experts where needed. Interactions between company employees, such as development of the warehouse plans and inspections by the in-house engineer, are not counted as procedures. However, interactions with external parties that are required for the architect to prepare the plans and drawings (such as obtaining topographic or geological surveys), or to have such documents approved or stamped by external parties, are counted as procedures. Procedures that the company undergoes to connect the warehouse to water and sewerage are included. All procedures that are legally required and that are done in practice by the majority of companies to build a warehouse are counted, even if they may be avoided in exceptional cases. For example, obtaining technical conditions for electricity or a clearance of the electrical plans are counted as separate procedures if they are required for obtaining a building permit. Data starting in 2014 reflect the DB15-17 methodology change.\n\nThe Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected. Please also see: https://www.doingbusiness.org/en/methodology/dealing-with-construction-permits", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number", "short_unit": "number" }, "ie_ppi_engy_cd": { "title": "Investment in energy with private participation (current US$)", "description_from_producer": "Investment in energy projects with private participation refers to commitments to infrastructure projects in energy (electricity and natural gas: generation, transmission and distribution) that have reached financial closure and directly or indirectly serve the public. Movable assets and small projects such as windmills are excluded. The types of projects included are management and lease contracts, operations and management contracts with major capital expenditure, greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility), and divestitures. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data is presented based on investment year. Data are in current U.S. dollars.\n\nLimitations and exceptions: The data on investment in infrastructure projects with private participation refer to all investment (public and private) in projects in which a private company assumes operating risk during the operating period or development and operating risk during the contract period. Investment refers to commitments not disbursements. Foreign state-owned companies are considered private entities for the purposes of this measure.\n\nInvestment commitments are the sum of investments in physical assets and payments to the government. Investments in physical assets are resources the project company commits to invest during the contract period in new facilities or in expansion and modernization of existing facilities. Payments to the government are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or use of specific radio spectrums. Data on the projects are compiled from publicly available information. The database aims to be as comprehensive as possible, but some projects - particularly those involving local and small-scale operators - may be omitted because they are not publicly reported.\n\nStatistical concept and methodology: The data are from the World Bank's Private Participation in Infrastructure (PPI) Project database, which tracks infrastructure projects with private participation in developing countries. It provides information on more than 5,000 infrastructure projects in 139 developing economies from 1984. The database contains more than 30 fields per project record, including country, financial closure year, infrastructure services provided, type of private participation, investment, technology, capacity, project location, contract duration, private sponsors, bidding process, and development bank support.\n\nThe database is a joint product of the World Bank's Finance, Economics, and Urban Development Department and the Public-Private Infrastructure Advisory Facility. Geographic and income aggregates are calculated by the World Bank's Development Data Group.\n\nData are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ie_ppi_icti_cd": { "title": "Investment in ICT with private participation (current US$)", "description_from_producer": "Investment in ICT projects with private participation refers to commitments to projects in ICT backbone infrastructure (including land based and submarine cables) that have reached financial closure and directly or indirectly serve the public. Movable assets and small projects are excluded. The types of projects included are operations and management contracts, operations and management contracts with major capital expenditure, greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility), and divestitures. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data is presented based on investment year. Data are in current U.S. dollars and available 2015 onwards only.\n\nLimitations and exceptions: The data on investment in infrastructure projects with private participation refer to all investment commitments (public and private) in projects in which a private company assumes operating risk during the operating period or development and operating risk during the contract period. Investment refers to commitments not disbursements. Foreign state-owned companies are considered private entities for the purposes of this measure.\n\nMovable assets and small projects are excluded. The types of projects included are operations and management contracts, operations and management contracts with major capital expenditure, greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility), and divestitures. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data on the projects are compiled from publicly available information. The database aims to be as comprehensive as possible, but some projects - particularly those involving local and small-scale operators - may be omitted because they are not publicly reported. Data are available 2015 onwards only for ICT.\n\nStatistical concept and methodology: The data are from the World Bank's Private Participation in Infrastructure (PPI) Project database, which tracks infrastructure projects with private participation in developing countries. It provides information on more than 6,400 infrastructure projects in 139 developing economies from 1984. The database contains more than 30 fields per project record, including country, financial closure year, infrastructure services provided, type of private participation, investment, technology, capacity, project location, contract duration, private sponsors, bidding process, and development bank support.\n\nThe database is a joint product of the World Bank's Finance, Economics, and Urban Development Department and the Public-Private Infrastructure Advisory Facility. Geographic and income aggregates are calculated by the World Bank's Development Data Group.\n\nData are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ie_ppi_tran_cd": { "title": "Investment in transport with private participation (current US$)", "description_from_producer": "Investment in transport projects with private participation refers to commitments to infrastructure projects in transport that have reached financial closure and directly or indirectly serve the public. Movable assets and small projects are excluded. The types of projects included are management and lease contracts, operations and management contracts with major capital expenditure, greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility), and divestitures. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data is presented based on investment year. Data are in current U.S. dollars.\n\nLimitations and exceptions: The data on investment in infrastructure projects with private participation refer to all investment (public and private) in projects in which a private company assumes operating risk during the operating period or development and operating risk during the contract period. Investment refers to commitments not disbursements. Foreign state-owned companies are considered private entities for the purposes of this measure.\n\nMovable assets and small projects are excluded. The types of projects included are operations and management contracts, operations and management contracts with major capital expenditure, greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility), and divestitures. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data on the projects are compiled from publicly available information. The database aims to be as comprehensive as possible, but some projects - particularly those involving local and small-scale operators - may be omitted because they are not publicly reported.\n\nStatistical concept and methodology: The data are from the World Bank's Private Participation in Infrastructure (PPI) Project database, which tracks infrastructure projects with private participation in developing countries. It provides information on more than 5,000 infrastructure projects in 139 developing economies from 1984. The database contains more than 30 fields per project record, including country, financial closure year, infrastructure services provided, type of private participation, investment, technology, capacity, project location, contract duration, private sponsors, bidding process, and development bank support.\n\nThe database is a joint product of the World Bank's Finance, Economics, and Urban Development Department and the Public-Private Infrastructure Advisory Facility. Geographic and income aggregates are calculated by the World Bank's Development Data Group.\n\nData are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ie_ppi_watr_cd": { "title": "Investment in water and sanitation with private participation (current US$)", "description_from_producer": "Investment in water and sanitation projects with private participation refers to commitments to infrastructure projects in water and sanitation that have reached financial closure and directly or indirectly serve the public. Movable assets, incinerators, standalone solid waste projects, and small projects are excluded. The types of projects included are management and lease contracts, operations and management contracts with major capital expenditure, greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility), and divestitures. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data is presented based on investment year. Data are in current U.S. dollars.\n\nLimitations and exceptions: The data on investment in infrastructure projects with private participation refer to all investment (public and private) in projects in which a private company assumes operating risk during the operating period or development and operating risk during the contract period. Investment refers to commitments not disbursements. Foreign state-owned companies are considered private entities for the purposes of this measure.\n\nInvestment commitments are the sum of investments in physical assets and payments to the government. Investments in physical assets are resources the project company commits to invest during the contract period in new facilities or in expansion and modernization of existing facilities. Payments to the government are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or use of specific radio spectrums. Data on the projects are compiled from publicly available information. The database aims to be as comprehensive as possible, but some projects - particularly those involving local and small-scale operators - may be omitted because they are not publicly reported.\n\nStatistical concept and methodology: The data are from the World Bank's Private Participation in Infrastructure (PPI) Project database, which tracks infrastructure projects with private participation in developing countries. It provides information on more than 5,000 infrastructure projects in 139 developing economies from 1984. The database contains more than 30 fields per project record, including country, financial closure year, infrastructure services provided, type of private participation, investment, technology, capacity, project location, contract duration, private sponsors, bidding process, and development bank support.\n\nThe database is a joint product of the World Bank's Finance, Economics, and Urban Development Department and the Public-Private Infrastructure Advisory Facility. Geographic and income aggregates are calculated by the World Bank's Development Data Group.\n\nData are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ie_ppn_engy_cd": { "title": "Public private partnerships investment in energy (current US$)", "description_from_producer": "Public Private Partnerships in energy (current US$) refers to commitments to infrastructure projects in energy (electricity and natural gas transmission and distribution) that have reached financial closure and directly or indirectly serve the public. Movable assets and small projects such as windmills are excluded. The types of projects included are management and lease contracts, operations and management contracts with major capital expenditure, and greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility). It excludes divestitures and merchant projects. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data is presented based on investment year. Data are in current U.S. dollars.\n\nLimitations and exceptions: The data on investment in infrastructure projects with private participation refer to all investment commitments (public and private) in projects in which a private company assumes operating risk during the operating period or development and operating risk during the contract period. Investment refers to commitments not disbursements. Foreign state-owned companies are considered private entities for the purposes of this measure.\n\nMovable assets and small projects are excluded. The types of projects included are operations and management contracts, operations and management contracts with major capital expenditure, greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility), and divestitures. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data on the projects are compiled from publicly available information. The database aims to be as comprehensive as possible, but some projects - particularly those involving local and small-scale operators - may be omitted because they are not publicly reported.\n\nStatistical concept and methodology: The data are from the World Bank's Private Participation in Infrastructure (PPI) Project database, which tracks infrastructure projects with private participation in developing countries. It provides information on more than 6,400 infrastructure projects in 139 developing economies from 1984. The database contains more than 30 fields per project record, including country, financial closure year, infrastructure services provided, type of private participation, investment, technology, capacity, project location, contract duration, private sponsors, bidding process, and development bank support.\n\nThe database is a joint product of the World Bank's Finance, Economics, and Urban Development Department and the Public-Private Infrastructure Advisory Facility. Geographic and income aggregates are calculated by the World Bank's Development Data Group.\n\nData are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ie_ppn_icti_cd": { "title": "Public private partnerships investment in ICT (current US$)", "description_from_producer": "Public Private Partnerships in ICT (current US$) refers to commitments to projects in ICT backbone infrastructure (including land based and submarine cables) that have reached financial closure and directly or indirectly serve the public. Movable assets and small projects are excluded. The types of projects included are management and lease contracts, operations and management contracts with major capital expenditure and greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility). It excludes divestitures and merchant projects. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data is presented based on investment year. Data are in current U.S. dollars and available 2015 onwards only.\n\nLimitations and exceptions: The data on investment in infrastructure projects with private participation refer to all investment commitments (public and private) in projects in which a private company assumes operating risk during the operating period or development and operating risk during the contract period. Investment refers to commitments not disbursements. Foreign state-owned companies are considered private entities for the purposes of this measure.\n\nMovable assets and small projects are excluded. The types of projects included are operations and management contracts, operations and management contracts with major capital expenditure, greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility), and divestitures. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data on the projects are compiled from publicly available information. The database aims to be as comprehensive as possible, but some projects - particularly those involving local and small-scale operators - may be omitted because they are not publicly reported. Data are available 2015 onwards only for ICT.\n\nStatistical concept and methodology: The data are from the World Bank's Private Participation in Infrastructure (PPI) Project database, which tracks infrastructure projects with private participation in developing countries. It provides information on more than 6,400 infrastructure projects in 139 developing economies from 1984. The database contains more than 30 fields per project record, including country, financial closure year, infrastructure services provided, type of private participation, investment, technology, capacity, project location, contract duration, private sponsors, bidding process, and development bank support.\n\nThe database is a joint product of the World Bank's Finance, Economics, and Urban Development Department and the Public-Private Infrastructure Advisory Facility. Geographic and income aggregates are calculated by the World Bank's Development Data Group.\n\nData are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ie_ppn_tran_cd": { "title": "Public private partnerships investment in transport (current US$)", "description_from_producer": "Public Private Partnerships in transport (current US$) refers to commitments to infrastructure projects in transport that have reached financial closure and directly or indirectly serve the public. Movable assets and small projects are excluded. The types of projects included are management and lease contracts, operations and management contracts with major capital expenditure, and greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility). It excludes divestitures and merchant projects. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data is presented based on investment year. Data are in current U.S. dollars.\n\nLimitations and exceptions: The data on investment in infrastructure projects with private participation refer to all investment commitments (public and private) in projects in which a private company assumes operating risk during the operating period or development and operating risk during the contract period. Investment refers to commitments not disbursements. Foreign state-owned companies are considered private entities for the purposes of this measure.\n\nMovable assets and small projects are excluded. The types of projects included are operations and management contracts, operations and management contracts with major capital expenditure, greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility), and divestitures. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data on the projects are compiled from publicly available information. The database aims to be as comprehensive as possible, but some projects - particularly those involving local and small-scale operators - may be omitted because they are not publicly reported.\n\nStatistical concept and methodology: The data are from the World Bank's Private Participation in Infrastructure (PPI) Project database, which tracks infrastructure projects with private participation in developing countries. It provides information on more than 6,400 infrastructure projects in 139 developing economies from 1984. The database contains more than 30 fields per project record, including country, financial closure year, infrastructure services provided, type of private participation, investment, technology, capacity, project location, contract duration, private sponsors, bidding process, and development bank support.\n\nThe database is a joint product of the World Bank's Finance, Economics, and Urban Development Department and the Public-Private Infrastructure Advisory Facility. Geographic and income aggregates are calculated by the World Bank's Development Data Group.\n\nData are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ie_ppn_watr_cd": { "title": "Public private partnerships investment in water and sanitation (current US$)", "description_from_producer": "Public Private Partnerships in water and sanitation (current US$) refers to commitments to infrastructure projects in water and sanitation that have reached financial closure and directly or indirectly serve the public. Movable assets, incinerators, standalone solid waste projects, and small projects are excluded. The types of projects included are management and lease contracts, operations and management contracts with major capital expenditure, and greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility). It excludes divestitures and merchant projects. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data is presented based on investment year. Data are in current U.S. dollars.\n\nLimitations and exceptions: The data on investment in infrastructure projects with private participation refer to all investment commitments (public and private) in projects in which a private company assumes operating risk during the operating period or development and operating risk during the contract period. Investment refers to commitments not disbursements. Foreign state-owned companies are considered private entities for the purposes of this measure.\n\nMovable assets and small projects are excluded. The types of projects included are operations and management contracts, operations and management contracts with major capital expenditure, greenfield projects (in which a private entity or a public-private joint venture builds and operates a new facility), and divestitures. Investment commitments are the sum of investments in facilities and investments in government assets. Investments in facilities are the resources the project company commits to invest during the contract period either in new facilities or in expansion and modernization of existing facilities. Investments in government assets are the resources the project company spends on acquiring government assets such as state-owned enterprises, rights to provide services in a specific area, or the use of specific radio spectrums. Data on the projects are compiled from publicly available information. The database aims to be as comprehensive as possible, but some projects - particularly those involving local and small-scale operators - may be omitted because they are not publicly reported.\n\nStatistical concept and methodology: The data are from the World Bank's Private Participation in Infrastructure (PPI) Project database, which tracks infrastructure projects with private participation in developing countries. It provides information on more than 6,400 infrastructure projects in 139 developing economies from 1984. The database contains more than 30 fields per project record, including country, financial closure year, infrastructure services provided, type of private participation, investment, technology, capacity, project location, contract duration, private sponsors, bidding process, and development bank support.\n\nThe database is a joint product of the World Bank's Finance, Economics, and Urban Development Department and the Public-Private Infrastructure Advisory Facility. Geographic and income aggregates are calculated by the World Bank's Development Data Group.\n\nData are in current U.S. dollars.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ip_ids_nrct": { "title": "Industrial design applications, nonresident, by count", "description_from_producer": "Industrial design applications are applications to register an industrial design with a national or regional Intellectual Property (IP) offices and designations received by relevant offices through the Hague System. Industrial designs are applied to a wide variety of industrial products and handicrafts. They refer to the ornamental or aesthetic aspects of a useful article, including compositions of lines or colors or any three-dimensional forms that give a special appearance to a product or handicraft. The holder of a registered industrial design has exclusive rights against unauthorized copying or imitation of the design by third parties. Industrial design registrations are valid for a limited period. The term of protection is usually 15 years for most jurisdictions. However, differences in legislation do exist, notably in China (which provides for a 10-year term from the application date). Non-resident application refers to an application filed with the IP office of or acting on behalf of a state or jurisdiction in which the first-named applicant in the application is not domiciled. Design count is used to render application data for industrial applications across offices comparable, as some offices follow a single-class/single-design filing system while other have a multiple class/design filing system.\n\nLimitations and exceptions: An industrial design right protects only the appearance or aesthetic features of a product, whereas a patent protects an invention that offers a new technical solution to a problem. In principle, an industrial design right does not protect the technical or functional features of a product. Industrial design registrations are valid for a limited period. The term of protection is usually 15 years for most jurisdictions. However, differences in legislation do exist, notably in China (which provides for a 10-year term from the application date). Data are based on information supplied to World Intellectual Property Organization (WIPO) by IP offices in annual surveys, supplemented by data in national IP office reports. Data may be missing for some offices or periods.", "origins": [ { "producer": "World Intellectual Property Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ip_ids_rsct": { "title": "Industrial design applications, resident, by count", "description_from_producer": "Industrial design applications are applications to register an industrial design with a national or regional Intellectual Property (IP) offices and designations received by relevant offices through the Hague System. Industrial designs are applied to a wide variety of industrial products and handicrafts. They refer to the ornamental or aesthetic aspects of a useful article, including compositions of lines or colors or any three-dimensional forms that give a special appearance to a product or handicraft. The holder of a registered industrial design has exclusive rights against unauthorized copying or imitation of the design by third parties. Industrial design registrations are valid for a limited period. The term of protection is usually 15 years for most jurisdictions. However, differences in legislation do exist, notably in China (which provides for a 10-year term from the application date). Resident application refers to an application filed with the IP office of or acting on behalf of the state or jurisdiction in which the first-named applicant in the application has residence. Design count is used to render application data for industrial applications across offices comparable, as some offices follow a single-class/single-design filing system while other have a multiple class/design filing system.\n\nLimitations and exceptions: An industrial design right protects only the appearance or aesthetic features of a product, whereas a patent protects an invention that offers a new technical solution to a problem. In principle, an industrial design right does not protect the technical or functional features of a product. Industrial design registrations are valid for a limited period. The term of protection is usually 15 years for most jurisdictions. However, differences in legislation do exist, notably in China (which provides for a 10-year term from the application date). Data are based on information supplied to World Intellectual Property Organization (WIPO) by IP offices in annual surveys, supplemented by data in national IP office reports. Data may be missing for some offices or periods.", "origins": [ { "producer": "World Intellectual Property Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ip_jrn_artc_sc": { "title": "Scientific and technical journal articles", "description_from_producer": "Scientific and technical journal articles refer to the number of scientific and engineering articles published in the following fields: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences.\n\nLimitations and exceptions: Scientific and technical article counts are from journals classified by the Institute for Scientific Information's Science Citation Index (SCI) and Social Sciences Citation Index (SSCI). Counts are based on fractional assignments; articles with authors from different countries are allocated proportionately to each country. The SCI and SSCI databases cover the core set of scientific journals but may exclude some of local importance and may reflect some bias toward English-language journals.\nArticles are classified by year of publication and assigned to region/country/economy on basis of institutional address(es) listed on the article. Articles are counted on a fractional-count basis that is, for articles with collaborating institutions from multiple countries/economies, each country/economy receives fractional credit on basis of proportion of its participating institutions. Details may not add to total because of rounding.\n\nStatistical concept and methodology: The number of scientific and engineering articles published in the following fields: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences. The NSF considers article counts from a set of journals covered by Science Citation Index (SCI) and Social Sciences Citation Index (SSCI).", "origins": [ { "producer": "National Science Foundation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ip_pat_nres": { "title": "Patent applications, nonresidents", "description_from_producer": "Patent applications are worldwide patent applications filed through the Patent Cooperation Treaty procedure or with a national patent office for exclusive rights for an invention--a product or process that provides a new way of doing something or offers a new technical solution to a problem. A patent provides protection for the invention to the owner of the patent for a limited period, generally 20 years.\n\nLimitations and exceptions: A patent is an exclusive right granted for a specified period (generally 20 years) for a new way of doing something or a new technical solution to a problem - an invention. The invention must be of practical use and display a characteristic unknown in the existing body of knowledge in its field. Most countries have systems to protect patentable inventions.\n\nUnless otherwise stated, statistics on the number of resident and non-resident patent applications include those filed via the PCT system as PCT national/regional phase entries.\n\nStatistical concept and methodology: Non-resident patent applications are from applicants outside the relevant State or region. Patent data cover applications and grants classified by field of technology. International applications series distinguish four subcategories: a) patents taken out by residents of a country in that country; b) patents taken out in a country by non-residents of that country; c) total patents registered in the country or naming it; d) patents taken out outside a country by its residents. Data on patents granted only distinguish between patents awarded to residents and to non-residents. A patent provides protection for the invention to the owner of the patent for a limited period, generally 20 years.\n\nPatent applications are worldwide patent applications filed through the Patent Cooperation Treaty procedure or with a national patent office for exclusive rights for an invention - a product or process that provides a new way of doing something or offers a new technical solution to a problem.", "origins": [ { "producer": "World Intellectual Property Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ip_pat_resd": { "title": "Patent applications, residents", "description_from_producer": "Patent applications are worldwide patent applications filed through the Patent Cooperation Treaty procedure or with a national patent office for exclusive rights for an invention--a product or process that provides a new way of doing something or offers a new technical solution to a problem. A patent provides protection for the invention to the owner of the patent for a limited period, generally 20 years.\n\nLimitations and exceptions: A patent is an exclusive right granted for a specified period (generally 20 years) for a new way of doing something or a new technical solution to a problem - an invention. The invention must be of practical use and display a characteristic unknown in the existing body of knowledge in its field. Most countries have systems to protect patentable inventions.\n\nStatistical concept and methodology: Resident patent applications are those for which the first-named applicant or assignee is a resident of the State or region concerned. In the case of regional offices such as the European Patent Office, a resident is an applicant from any of the member States of the regional patent convention.\n\nPatent data cover applications and grants classified by field of technology. International applications series distinguish four subcategories: a) patents taken out by residents of a country in that country; b) patents taken out in a country by non-residents of that country; c) total patents registered in the country or naming it; d) patents taken out outside a country by its residents. Data on patents granted only distinguish between patents awarded to residents and to non-residents. A patent provides protection for the invention to the owner of the patent for a limited period, generally 20 years.\n\nPatent applications are worldwide patent applications filed through the Patent Cooperation Treaty procedure or with a national patent office for exclusive rights for an invention - a product or process that provides a new way of doing something or offers a new technical solution to a problem.", "origins": [ { "producer": "World Intellectual Property Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ip_tmk_nrct": { "title": "Trademark applications, nonresident, by count", "description_from_producer": "Trademark applications filed are applications to register a trademark with a national or regional Intellectual Property (IP) offices and designations received by relevant offices through the Madrid System. A trademark is a distinctive sign which identifies certain goods or services as those produced or provided by a specific person or enterprise. A trademark provides protection to the owner of the mark by ensuring the exclusive right to use it to identify goods or services, or to authorize another to use it in return for payment. The period of protection varies, but a trademark can be renewed indefinitely beyond the time limit on payment of additional fees. Non-resident application refers to an application filed with the IP office of or acting on behalf of a state or jurisdiction in which the first-named applicant in the application is not domiciled. Class count is used to render application data for trademark applications across offices comparable, as some offices follow a single-class/single-design filing system while other have a multiple class/design filing system.\n\nLimitations and exceptions: Depending on different legal systems, one or more classes can be specified in a trademark application, with the intent to obtain protection of the mark across different goods and/or services. For cross country comparison purposes, users are advised to refer to the trademark data rendered by the class count in the database 2004 onwards. Data are based on information supplied to World Intellectual Property Organization (WIPO) by IP offices in annual surveys, supplemented by data in national IP office reports. Data may be missing for some offices or periods.", "origins": [ { "producer": "World Intellectual Property Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ip_tmk_rsct": { "title": "Trademark applications, resident, by count", "description_from_producer": "Trademark applications filed are applications to register a trademark with a national or regional Intellectual Property (IP) offices and designations received by relevant offices through the Madrid System. A trademark is a distinctive sign which identifies certain goods or services as those produced or provided by a specific person or enterprise. A trademark provides protection to the owner of the mark by ensuring the exclusive right to use it to identify goods or services, or to authorize another to use it in return for payment. The period of protection varies, but a trademark can be renewed indefinitely beyond the time limit on payment of additional fees. Resident application refers to an application filed with the IP office of or acting on behalf of the state or jurisdiction in which the first-named applicant in the application has residence. Class count is used to render application data for trademark applications across offices comparable, as some offices follow a single-class/single-design filing system while other have a multiple class/design filing system.\n\nLimitations and exceptions: Depending on different legal systems, one or more classes can be specified in a trademark application, with the intent to obtain protection of the mark across different goods and/or services. For cross country comparison purposes, users are advised to refer to the trademark data rendered by the class count in the database 2004 onwards. Data are based on information supplied to World Intellectual Property Organization (WIPO) by IP offices in annual surveys, supplemented by data in national IP office reports. Data may be missing for some offices or periods.", "origins": [ { "producer": "World Intellectual Property Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "iq_cpa_breg_xq": { "title": "CPIA business regulatory environment rating (1=low to 6=high)", "description_from_producer": "Business regulatory environment assesses the extent to which the legal, regulatory, and policy environments help or hinder private businesses in investing, creating jobs, and becoming more productive.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_debt_xq": { "title": "CPIA debt policy rating (1=low to 6=high)", "description_from_producer": "Debt policy assesses whether the debt management strategy is conducive to minimizing budgetary risks and ensuring long-term debt sustainability.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_econ_xq": { "title": "CPIA economic management cluster average (1=low to 6=high)", "description_from_producer": "The economic management cluster includes macroeconomic management, fiscal policy, and debt policy.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_envr_xq": { "title": "CPIA policy and institutions for environmental sustainability rating (1=low to 6=high)", "description_from_producer": "Policy and institutions for environmental sustainability assess the extent to which environmental policies foster the protection and sustainable use of natural resources and the management of pollution.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_finq_xq": { "title": "CPIA quality of budgetary and financial management rating (1=low to 6=high)", "description_from_producer": "Quality of budgetary and financial management assesses the extent to which there is a comprehensive and credible budget linked to policy priorities, effective financial management systems, and timely and accurate accounting and fiscal reporting, including timely and audited public accounts.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_fins_xq": { "title": "CPIA financial sector rating (1=low to 6=high)", "description_from_producer": "Financial sector assesses the structure of the financial sector and the policies and regulations that affect it.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_fisp_xq": { "title": "CPIA fiscal policy rating (1=low to 6=high)", "description_from_producer": "Fiscal policy assesses the short- and medium-term sustainability of fiscal policy (taking into account monetary and exchange rate policy and the sustainability of the public debt) and its impact on growth.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_gndr_xq": { "title": "CPIA gender equality rating (1=low to 6=high)", "description_from_producer": "Gender equality assesses the extent to which the country has installed institutions and programs to enforce laws and policies that promote equal access for men and women in education, health, the economy, and protection under law.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_hres_xq": { "title": "CPIA building human resources rating (1=low to 6=high)", "description_from_producer": "Building human resources assesses the national policies and public and private sector service delivery that affect the access to and quality of health and education services, including prevention and treatment of HIV/AIDS, tuberculosis, and malaria.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_irai_xq": { "title": "IDA resource allocation index (1=low to 6=high)", "description_from_producer": "IDA Resource Allocation Index is obtained by calculating the average score for each cluster and then by averaging those scores. For each of 16 criteria countries are rated on a scale of 1 (low) to 6 (high).\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_macr_xq": { "title": "CPIA macroeconomic management rating (1=low to 6=high)", "description_from_producer": "Macroeconomic management assesses the monetary, exchange rate, and aggregate demand policy framework.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_padm_xq": { "title": "CPIA quality of public administration rating (1=low to 6=high)", "description_from_producer": "Quality of public administration assesses the extent to which civilian central government staff is structured to design and implement government policy and deliver services effectively.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_pres_xq": { "title": "CPIA equity of public resource use rating (1=low to 6=high)", "description_from_producer": "Equity of public resource use assesses the extent to which the pattern of public expenditures and revenue collection affects the poor and is consistent with national poverty reduction priorities.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_prop_xq": { "title": "CPIA property rights and rule-based governance rating (1=low to 6=high)", "description_from_producer": "Property rights and rule-based governance assess the extent to which private economic activity is facilitated by an effective legal system and rule-based governance structure in which property and contract rights are reliably respected and enforced.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_prot_xq": { "title": "CPIA social protection rating (1=low to 6=high)", "description_from_producer": "Social protection and labor assess government policies in social protection and labor market regulations that reduce the risk of becoming poor, assist those who are poor to better manage further risks, and ensure a minimal level of welfare to all people.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_pubs_xq": { "title": "CPIA public sector management and institutions cluster average (1=low to 6=high)", "description_from_producer": "The public sector management and institutions cluster includes property rights and rule-based governance, quality of budgetary and financial management, efficiency of revenue mobilization, quality of public administration, and transparency, accountability, and corruption in the public sector.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_revn_xq": { "title": "CPIA efficiency of revenue mobilization rating (1=low to 6=high)", "description_from_producer": "Efficiency of revenue mobilization assesses the overall pattern of revenue mobilization--not only the de facto tax structure, but also revenue from all sources as actually collected.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_soci_xq": { "title": "CPIA policies for social inclusion/equity cluster average (1=low to 6=high)", "description_from_producer": "The policies for social inclusion and equity cluster includes gender equality, equity of public resource use, building human resources, social protection and labor, and policies and institutions for environmental sustainability.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_strc_xq": { "title": "CPIA structural policies cluster average (1=low to 6=high)", "description_from_producer": "The structural policies cluster includes trade, financial sector, and business regulatory environment.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_trad_xq": { "title": "CPIA trade rating (1=low to 6=high)", "description_from_producer": "Trade assesses how the policy framework fosters trade in goods.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_cpa_tran_xq": { "title": "CPIA transparency, accountability, and corruption in the public sector rating (1=low to 6=high)", "description_from_producer": "Transparency, accountability, and corruption in the public sector assess the extent to which the executive can be held accountable for its use of funds and for the results of its actions by the electorate and by the legislature and judiciary, and the extent to which public employees within the executive are required to account for administrative decisions, use of resources, and results obtained. The three main dimensions assessed here are the accountability of the executive to oversight institutions and of public employees for their performance, access of civil society to information on public affairs, and state capture by narrow vested interests.\n\nLimitations and exceptions: The CPIA exercise is intended to capture the quality of a country's policies and institutional arrangements, focusing on key elements that are within the country's control, rather than on outcomes (such as economic growth rates) that are influenced by events beyond the country's control. More specifically, the CPIA measures the extent to which a country's policy and institutional framework supports sustainable growth and poverty reduction and, consequently, the effective use of development assistance.\n\nStatistical concept and methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 6=high" }, "iq_sci_mthd": { "title": "Methodology assessment of statistical capacity (scale 0 - 100)", "description_from_producer": "The methodology indicator measures a country\u2019s ability to adhere to internationally recommended standards and methods. The methodology score is calculated as the weighted average of 10 underlying indicator scores. The final methodology score contributes 1/3 of the overall Statistical Capacity Indicator score.\n\nStatistical concept and methodology: The Practice score is calculated as weighted average of all 10 Practice indicator scores.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "scale 0 - 100" }, "iq_sci_ovrl": { "title": "Statistical Capacity Score (Overall Average) (scale 0 - 100)", "description_from_producer": "The Statistical Capacity Indicator is a composite score assessing the capacity of a country\u2019s statistical system. It is based on a diagnostic framework assessing the following areas: methodology; data sources; and periodicity and timeliness. Countries are scored against 25 criteria in these areas, using publicly available information and/or country input. The overall Statistical Capacity score is then calculated as a simple average of all three area scores on a scale of 0-100.\n\nStatistical concept and methodology: The Statistical Capacity Indicator score is calculated as the average of the scores of the 3 dimensions, i.e. Availability, Collection, Practice.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "", "display": { "numDecimalPlaces": 1 } }, "iq_sci_prdc": { "title": "Periodicity and timeliness assessment of statistical capacity (scale 0 - 100)", "description_from_producer": "The periodicity and timeliness indicator assesses the availability and periodicity of key socioeconomic indicators. It measures the extent to which data are made accessible to users through transformation of source data into timely statistical outputs. The periodicity score is calculated as the weighted average of 10 underlying indicator scores. The final periodicity score contributes 1/3 of the overall Statistical Capacity Indicator score.\n\nStatistical concept and methodology: The Availability score is calculated as weighted average of all 10 Availability indicator scores.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "scale 0 - 100" }, "iq_sci_srce": { "title": "Source data assessment of statistical capacity (scale 0 - 100)", "description_from_producer": "The source data indicator reflects whether a country conducts data collection activities in line with internationally recommended periodicity, and whether data from administrative systems are available. The source data score is calculated as the weighted average of 5 underlying indicator scores. The final source data score contributes 1/3 of the overall Statistical Capacity Indicator score.\n\nStatistical concept and methodology: The Collection score is calculated as weighted average of all 5 Collection indicator scores.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "scale 0 - 100" }, "iq_spi_ovrl": { "title": "Statistical performance indicators (SPI): Overall score (scale 0-100)", "description_from_producer": "The SPI overall score is a composite score measuing country performance across five pillars: data use, data services, data products, data sources, and data infrastructure. The new Statistical Performance Indicators (SPI) will replace the Statistical Capacity Index (SCI), which the World Bank has regularly published since 2004. Although the goals are the same, to offer a better tool to measure the statistical systems of countries, the new SPI framework has expanded into new areas including in the areas of data use, administrative data, geospatial data, data services, and data infrastructure. The SPI provides a framework that can help countries measure where they stand in several dimensions and offers an ambitious measurement agenda for the international community.\n\nStatistical concept and methodology: Weighted average of all statistical performance indicators. Scores range from 0-100 with 100 representing the best score.\n\nNotes from original source: The SPI draws on a variety of data sources to create the indicators. A guiding principle is that the SPI rely on openly available data from credible sources, such as international organizations and NSO websites. The SPI team used web scraping, accessed publicly available databases, or in some cases visited NSO websites to acquire the information. While greater detail for each specific indicator can be found in the technical documentation describing each indicator.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "iq_spi_pil1": { "title": "Statistical performance indicators (SPI): Pillar 1 data use score (scale 0-100)", "description_from_producer": "The data use overall score is a composite score measuring the demand side of the statistical system. The data use pillar is segmented by five types of users: (i) the legislature, (ii) the executive branch, (iii) civil society (including sub-national actors), (iv) academia and (v) international bodies. Each dimension would have associated indicators to measure performance. A mature system would score well across all dimensions whereas a less mature one would have weaker scores along certain dimensions. The gaps would give insights into prioritization among user groups and help answer questions as to why the existing services are not resulting in higher use of national statistics in a particular segment. Currently, the SPI only features indicators for one of the five dimensions of data use, which is data use by international organizations. Indicators on whether statistical systems are providing useful data to their national governments (legislature and executive branches), to civil society, and to academia are absent. Thus the dashboard does not yet assess if national statistical systems are meeting the data needs of a large swathe of users.\n\nLimitations and exceptions: Currently, the dashboard only features indicators for one of the five dimensions of data use, which is data use by international organizations. Indicators on whether statistical systems are providing useful data to their national governments (legislature and executive branches), to civil society, and to academia are absent. Thus the dashboard does not yet assess if national statistical systems are meeting the data needs of a large swathe of users.\n\nStatistical concept and methodology: Weighted average of statistical performance indicators related to data use. Scores range from 0-100 with 100 representing the best score.\n\nNotes from original source: For pillar 1 on data use, data is collected from four distinct sources. The World Bank supplies data for indicators on availability of comparable poverty data (from the World Bank\u2019s Povcalnet system), and the indicator on quality of debt service data (from the World Bank\u2019s World Development Indicators or WDI metadata). Data on the availability of under 5 child mortality data comes from the UN Inter-agency Group for Child Mortality Estimation. The indicator on availability of safely managed drinking water data is sourced from the WHO/UNICEF Joint Monitoring Programme. The indicator on the availability of source data for measuring labor force participation comes from the ILO. Each of these sources will be updated annually prior to each annual data release. The date the data is updated for each of these sources is available in our technical documentation.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "iq_spi_pil2": { "title": "Statistical performance indicators (SPI): Pillar 2 data services score (scale 0-100)", "description_from_producer": "The data services pillar overall score is a composite indicator based on four dimensions of data services: (i) the quality of data releases, (ii) the richness and openness of online access, (iii) the effectiveness of advisory and analytical services related to statistics, and (iv) the availability and use of data access services such as secure microdata access. Advisory and analytical services might incorporate elements related to data stewardship services including input to national data strategies, advice on data ethics and calling out misuse of data in accordance with the Fundamental Principles of Official Statistics.\n\nLimitations and exceptions: Under the pillar of data services an area that needs improvement is the measurement of advisory and analytical services provided by NSOs, such as data stewardship services. By measuring this type of work done by NSOs that goes beyond producing data, the international community and the NSOs themselves can better assess whether this type of support is in place.\n\nStatistical concept and methodology: Weighted average of statistical performance indicators related to data services. Scores range from 0-100 with 100 representing the best score.\n\nNotes from original source: For pillar 2 on data services, information on data dissemination subscription is collected from the IMF\u2019s Dissemination Standards Bulletin Board. This and the WDI metadata follow the same update schedule and the release these two sources are identical. The online access indicator is sourced from the Open Data Watch ODIN openness score. The date of the data download is available in the technical description for this indicator. The indicator for data access services is based on (i) whether a portal is available, (ii) compliant with the Data Documentation Initiative (DDI) and with Dublin Core\u2019s RDF metadata standards, and (iii) which has a listing of surveys and microdata sets that can provide the necessary data and reference for follow-up. This information is collected manually by visiting each NSO website.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "iq_spi_pil3": { "title": "Statistical performance indicators (SPI): Pillar 3 data products score (scale 0-100)", "description_from_producer": "The data products overall score is a composite score measureing whether the country is able to produce relevant indicators, primarily related to SDGs. The data products (internal process) pillar is segmented by four topics and organized into (i) social, (ii) economic, (iii) environmental, and (iv) institutional dimensions using the typology of the Sustainable Development Goals (SDGs). This approach anchors the national statistical system\u2019s performance around the essential data required to support the achievement of the 2030 global goals, and enables comparisons across countries so that a global view can be generated while enabling country specific emphasis to reflect the user needs of that country.\n\nStatistical concept and methodology: Weighted average of statistical performance indicators related to data products. Scores range from 0-100 with 100 representing the best score.\n\nNotes from original source: For the data products dimension, indicators are generated using the UN Global SDG monitoring database. For each SDG indicator, the database is checked to see whether a value is available within a five year window. (for instance, for 2019 if a value is available between 2015-2019. For OECD countries, the UN SDG database is supplemented with comparable data submitted to the OECD following the methodology in Measuring Distance to the SDG Targets 2019: An Assessment of Where OECD Countries Stand. The decision to supplement the UN Global SDG monitoring database using this OECD database was taken, because a clear methodology had been established to do so. The UN Global SDG monitoring database was chosen as a primary source, rather than individual NSO websites, because data submitted to the UN Global SDG monitoring database goes through a standardized process including quality control and detailed documentation.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "iq_spi_pil4": { "title": "Statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100)", "description_from_producer": "The data sources overall score is a composity measure of whether countries have data available from the following sources: Censuses and surveys, administrative data, geospatial data, and private sector/citizen generated data. The data sources (input) pillar is segmented by four types of sources generated by (i) the statistical office (censuses and surveys), and sources accessed from elsewhere such as (ii) administrative data, (iii) geospatial data, and (iv) private sector data and citizen generated data. The appropriate balance between these source types will vary depending on a country\u2019s institutional setting and the maturity of its statistical system. High scores should reflect the extent to which the sources being utilized enable the necessary statistical indicators to be generated. For example, a low score on environment statistics (in the data production pillar) may reflect a lack of use of (and low score for) geospatial data (in the data sources pillar). This type of linkage is inherent in the data cycle approach and can help highlight areas for investment required if country needs are to be met.\n\nLimitations and exceptions: In the data sources pillar, more information is needed in the areas of administrative data, geospatial data, and private and citizen generated data. On administrative data, the picture is incomplete with no measures of whether countries have administrative data systems in place to measure health, education, labor, and social protection program statistics. For the geospatial indicator, there is a proxy measure of whether the country is able to produce indicators at the sub-national level, but as yet, no understanding of how countries are using geospatial information in other ways, for instance using satellite data. And while the world is increasingly awash with private and citizen generated data (e.g., on mobility, job search, or social networking), on a global scale there is no reliable source to measure how national statistical systems are incorporating this information.\n\nStatistical concept and methodology: Weighted average of statistical performance indicators related to data sources. Scores range from 0-100 with 100 representing the best score.\n\nNotes from original source: For dimension 4, on censuses and surveys, two complementary approaches are taken to collecting data. The first is to make use of data submitted to the World Bank, IHSN, ILO, and FAO microdata libraries. Only surveys that are marked as nationally representative are used, and surveys are classified (as either health surveys, agriculture surveys, labor force surveys, etc.) using the classifications submitted to the microdata libraries. The contents of searches on these databases are available in the github repository. The second approach is a manual data collection effort, where NSO websites have been visited to be sure no surveys were missed. To be included in this search, the survey or census must be publicly available and accessible. If surveys or censuses are missed in this search, the easiest way for a country to get it included would be to create an entry for the survey at one of the microdata libraries. Information on the completeness of the Civil Registry and Vital Statistics (CRVS) is sourced from the UN SDG global monitoring database. Information on whether data is available at the 1st administrative level, for the geospatial indicator, is sourced from Open Data Watch, as is the data openness score.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "iq_spi_pil5": { "title": "Statistical performance indicators (SPI): Pillar 5 data infrastructure score (scale 0-100)", "description_from_producer": "The data infrastructure pillar overall score measures the hard and soft infrastructure segments, itemizing essential cross cutting requirements for an effective statistical system. The segments are: (i) legislation and governance covering the existence of laws and a functioning institutional framework for the statistical system; (ii) standards and methods addressing compliance with recognized frameworks and concepts; (iii) skills including level of skills within the statistical system and among users (statistical literacy); (iv) partnerships reflecting the need for the statistical system to be inclusive and coherent; and (v) finance mobilized both domestically and from donors.\n\nLimitations and exceptions: Finally, several of the \u2018soft\u2019 components of the data infrastructure pillar lack adequate data. This includes the areas of skills and of partnerships between entities in the national statistical system. The dashboard makes use of the PARIS21 led SDG indicator on whether the statistical legislations in countries met the standards of the UN Fundamental Principles of Statistics, but this was not incorporated into the overall SPI score, because of inadequate country coverage. This is also true of the PARIS21 led SDG indicator on whether the national statistical system is fully funded. Countries would need to be encouraged to report on this information.\n\nStatistical concept and methodology: Weighted average of statistical performance indicators related to data infrastructure. Scores range from 0-100 with 100 representing the best score.\n\nNotes from original source: For dimension 5, data on the legislation indicator and finance indicators (compiled by PARIS21) are pulled from the UN SDG global monitoring database. Indicators in the standards and methods pillar are sourced primarily through the IMF. Information on the system of national accounts in use and national accounts base year are sourced through the World Bank\u2019s WDI metadata. Data for the business process indicator is sourced through the United Nations Industrial Development Organization (UNIDO) and the United Nations Economic Commission for Europe (UNECE).", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "is_air_dprt": { "title": "Air transport, registered carrier departures worldwide", "description_from_producer": "Registered carrier departures worldwide are domestic takeoffs and takeoffs abroad of air carriers registered in the country.\n\nLimitations and exceptions: Countries submit air transport data to Civil Aviation Organization (ICAO) on the basis of standard instructions and definitions issued by ICAO. In many cases, however, the data include estimates by ICAO for nonreporting carriers. Where possible, these estimates are based on previous submissions supplemented by information published by the air carriers, such as flight schedules.\n\nThe data cover the air traffic carried on scheduled services, but changes in air transport regulations in Europe have made it more difficult to classify traffic as scheduled or nonscheduled. Thus recent increases shown for some European countries may be due to changes in the classification of air traffic rather than actual growth. In the case of multinational air carriers owned by partner States, traffic within each partner State is shown separately as domestic and all other traffic as international.\n\n\"Foreign\" cabotage traffic (i.e. traffic carried between city-pairs in a State other than the one where the reporting carrier has its principal place of business) is shown as international traffic.\n\nA technical stop does not result in any flight stage being classified differently than would have been the case had the technical stop not been made. For countries with few air carriers or only one, the addition or discontinuation of a home-based air carrier may cause significant changes in air traffic.\n\nData for transport sectors are not always internationally comparable. Unlike for demographic statistics, national income accounts, and international trade data, the collection of infrastructure data has not been \"internationalized.\"\n\nStatistical concept and methodology: The air transport data represent the total (international and domestic) scheduled traffic carried by the air carriers registered in a country. For statistical uses, departures are equal to the number of landings made or flight stages flown. A flight stage is the operation of an aircraft from take-off to its next landing. A flight stage is classified as either international or domestic. International flight stage is one or both terminals in the territory of a State, other than the State in which the air carrier has its principal place of business.\n\nDomestic flight stage is not classifiable as international. Domestic flight stages include all flight stages flown between points within the domestic boundaries of a State by an air carrier whose principal place of business is in that State. Flight stages between a State and territories belonging to it, as well as any flight stages between two such territories, should be classified as domestic. This applies even though a stage may cross international waters or over the territory of another State.", "origins": [ { "producer": "International Civil Aviation Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "is_air_good_mt_k1": { "title": "Air transport, freight (million ton-km)", "description_from_producer": "Air freight is the volume of freight, express, and diplomatic bags carried on each flight stage (operation of an aircraft from takeoff to its next landing), measured in metric tons times kilometers traveled.\n\nLimitations and exceptions: The air transport data represent the total (international and domestic) scheduled traffic carried by the air carriers registered in a country. Countries submit air transport data to International Civil Aviation Organization (ICAO) on the basis of standard instructions and definitions issued by ICAO. In many cases, however, the data include estimates by ICAO for nonreporting carriers. Where possible, these estimates are based on previous submissions supplemented by information published by the air carriers, such as flight schedules.\n\nThe data cover the air traffic carried on scheduled services, but changes in air transport regulations in Europe have made it more difficult to classify traffic as scheduled or nonscheduled. Thus recent increases shown for some European countries may be due to changes in the classification of air traffic rather than actual growth. In the case of multinational air carriers owned by partner States, traffic within each partner State is shown separately as domestic and all other traffic as international.\n\n\"Foreign\" cabotage traffic (i.e. traffic carried between city-pairs in a State other than the one where the reporting carrier has its principal place of business) is shown as international traffic.\n\nA technical stop does not result in any flight stage being classified differently than would have been the case had the technical stop not been made. For countries with few air carriers or only one, the addition or discontinuation of a home-based air carrier may cause significant changes in air traffic.\n\nData for transport sectors are not always internationally comparable. Unlike for demographic statistics, national income accounts, and international trade data, the collection of infrastructure data has not been \"internationalized.\"\n\nStatistical concept and methodology: For statistical uses, departures are equal to the number of landings made or flight stages flown. A flight stage is the operation of an aircraft from take-off to its next landing. A flight stage is classified as either international or domestic. International flight stage is one or both terminals in the territory of a State, other than the State in which the air carrier has its principal place of business.\n\nDomestic flight stage is not classifiable as international. Domestic flight stages include all flight stages flown between points within the domestic boundaries of a State by an air carrier whose principal place of business is in that State. Flight stages between a State and territories belonging to it, as well as any flight stages between two such territories, should be classified as domestic. This applies even though a stage may cross international waters or over the territory of another State.\n\nFreight tonne-kilometres performed measures a metric tonne of freight carried one kilometre. Freight tonne-kilometres equal the sum of the products obtained by multiplying the number of tonnes of freight, express, diplomatic bags carried on each flight stage by the stage distance. For ICAO statistical purposes freight includes express and diplomatic bags but not passenger baggage.", "origins": [ { "producer": "International Civil Aviation Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "million ton-km" }, "is_air_psgr": { "title": "Air transport, passengers carried", "description_from_producer": "Air passengers carried include both domestic and international aircraft passengers of air carriers registered in the country.\n\nLimitations and exceptions: The air transport data represent the total (international and domestic) scheduled traffic carried by the air carriers registered in a country. Countries submit air transport data to International Civil Aviation Organization (ICAO) on the basis of standard instructions and definitions issued by ICAO. In many cases, however, the data include estimates by ICAO for nonreporting carriers. Where possible, these estimates are based on previous submissions supplemented by information published by the air carriers, such as flight schedules.\n\nThe data cover the air traffic carried on scheduled services, but changes in air transport regulations in Europe have made it more difficult to classify traffic as scheduled or nonscheduled. Thus recent increases shown for some European countries may be due to changes in the classification of air traffic rather than actual growth. In the case of multinational air carriers owned by partner States, traffic within each partner State is shown separately as domestic and all other traffic as international.\n\n\"Foreign\" cabotage traffic (i.e. traffic carried between city-pairs in a State other than the one where the reporting carrier has its principal place of business) is shown as international traffic.\n\nA technical stop does not result in any flight stage being classified differently than would have been the case had the technical stop not been made. For countries with few air carriers or only one, the addition or discontinuation of a home-based air carrier may cause significant changes in air traffic.\n\nData for transport sectors are not always internationally comparable. Unlike for demographic statistics, national income accounts, and international trade data, the collection of infrastructure data has not been \"internationalized.\"\n\nStatistical concept and methodology: For statistical uses, departures are equal to the number of landings made or flight stages flown. A flight stage is the operation of an aircraft from take-off to its next landing. A flight stage is classified as either international or domestic. International flight stage is one or both terminals in the territory of a State, other than the State in which the air carrier has its principal place of business.\n\nDomestic flight stage is not classifiable as international. Domestic flight stages include all flight stages flown between points within the domestic boundaries of a State by an air carrier whose principal place of business is in that State. Flight stages between a State and territories belonging to it, as well as any flight stages between two such territories, should be classified as domestic. This applies even though a stage may cross international waters or over the territory of another State.\n\nThe number of passengers carried is obtained by counting each passenger on a particular flight (with one flight number) once only and not repeatedly on each individual stage of that flight, with a single exception that a passenger flying on both the international and domestic stages of the same flight should be counted as both a domestic and an international passenger.", "origins": [ { "producer": "International Civil Aviation Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "is_rrs_good_mt_k6": { "title": "Railways, goods transported (million ton-km)", "description_from_producer": "Goods transported by railway are the volume of goods transported by railway, measured in metric tons times kilometers traveled.\n\nLimitations and exceptions: Unlike the road sector, where numerous qualified motor vehicle operators can operate anywhere on the road network, railways are a restricted transport system with vehicles confined to a fixed guideway. Considering the cost and service characteristics, railways generally are best suited to carry - and can effectively compete for - bulk commodities and containerized freight for distances of 500-5,000 kilometers, and passengers for distances of 50-1,000 kilometers. Below these limits road transport tends to be more competitive, while above these limits air transport for passengers and freight and sea transport for freight tend to be more competitive.\n\nData for transport sectors are not always internationally comparable. Unlike for demographic statistics, national income accounts, and international trade data, the collection of infrastructure data has not been \"internationalized.\"\n\nStatistical concept and methodology: Freight traffic on any mode is typically measured in tons and ton-kilometers. A ton-kilometer equals cargo weight transported times distance transported. For railways, an important measure of work performed is gross ton-kilometers, this measure includes rail wagons' empty weight for both empty and loaded movements. This measure of gross ton-kilometers is also called \u2018trailing tons' or the total tons being hauled. Sometimes gross ton-kilometer measures include the weight of locomotives used to haul freight trains.", "origins": [ { "producer": "International Union of Railways and OECD (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "million ton-km" }, "is_rrs_pasg_km": { "title": "Railways, passengers carried (million passenger-km)", "description_from_producer": "Passengers carried by railway are the number of passengers transported by rail multiplied by kilometers traveled.\n\nLimitations and exceptions: Unlike the road sector, where numerous qualified motor vehicle operators can operate anywhere on the road network, railways are a restricted transport system with vehicles confined to a fixed guideway. Considering the cost and service characteristics, railways generally are best suited to carry - and can effectively compete for - bulk commodities and containerized freight for distances of 500-5,000 kilometers, and passengers for distances of 50-1,000 kilometers. Below these limits road transport tends to be more competitive, while above these limits air transport for passengers and freight and sea transport for freight tend to be more competitive.\n\nData for transport sectors are not always internationally comparable. Unlike for demographic statistics, national income accounts, and international trade data, the collection of infrastructure data has not been \"internationalized.\"\n\nStatistical concept and methodology: Passenger-kilometers are usually measured on the basis of the rail travel distance between origin and destination multiplied by the number of passengers traveling between each origin and destination.\n\nNotes from original source: Internation Union of Railways (UIC Railisa Database): Var 5113 Passenger.kilometers on the national territory of the railway undertaking. This variable relates to passengers, irrespective of the fare paid and also including free travelling passengers, but excluding members of the train crew. The number of passengers should be calculated as number of passenger journeys. A journey is the act of moving from one place (origin) to another (destination) using a given transport mode (e.g. railway). A journey may consist of one or several stages depending on whether one has to change transport means (e.g. using more than one train) in order to get from the origin to the destination. In other words, a journey consists either of a single stage or a sequence of stages using the same transport mode (e.g. railway), following each other in such a way that the destination of one stage coincides with the origin of the next. Journeys should be considered finished when an overnight stay occurs. For practical purposes, journeys can be considered finished when a change in transport mode or transport company occurs. Passenger-kilometres is the total distance travelled by all the passengers. For instance, one person travelling for 20km contributes for 20 passenger-kilometres; four people, travelling for 20km each, contribute for 80 passenger- kilometres.\nOECD Statistics: Rail passenger transport: any movement of passengers using a rail vehicle on a given rail network. National rail passenger transport: rail passenger transport between two places (a place of loading/embarkation and a place of unloading/disembarkation) located in the same country. It may involve transit through a second country. International rail passenger transport: rail passenger transport between a place (of loading/embarkation or unloading/disembarkation) in one country and a place (of loading/embarkation or unloading/disembarkation) in another country. It may involve transit through one or more additional countries. Rail passenger: any person, excluding members of the train crew, who makes a journey by rail. Passenger-kilometre by rail: unit of measurement representing the transport of one rail passenger by rail over a distance of one kilometre.", "origins": [ { "producer": "International Union of Railways", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "million passenger-km" }, "is_rrs_totl_km": { "title": "Rail lines (total route-km)", "description_from_producer": "Rail lines are the length of railway route available for train service, irrespective of the number of parallel tracks.\n\nLimitations and exceptions: Unlike the road sector, where numerous qualified motor vehicle operators can operate anywhere on the road network, railways are a restricted transport system with vehicles confined to a fixed guideway. Considering the cost and service characteristics, railways generally are best suited to carry - and can effectively compete for - bulk commodities and containerized freight for distances of 500-5,000 kilometers, and passengers for distances of 50-1,000 kilometers. Below these limits road transport tends to be more competitive, while above these limits air transport for passengers and freight and sea transport for freight tend to be more competitive.\n\nData for transport sectors are not always internationally comparable. Unlike for demographic statistics, national income accounts, and international trade data, the collection of infrastructure data has not been \"internationalized\". The data from IUC is based a reporting by the railway companies and it can show a drastic increase or decrease for some of the years because of no reporting by some of the companies of a country.\n\nStatistical concept and methodology: Rail lines are the length of railway route available for train service, irrespective of the number of parallel tracks. It includes railway routes that are open for public passenger and freight servies and excludes dedicated private resource railways.\n\nNotes from original source: Internation Union of Railways (UIC Railisa Database): Var 1112 Total length of lines worked at the end of the year. Gauge: N standard gauge (1,435 m) L broad gauge (exact rail gauge inserted); E narrow gauge (exact rail gauge inserted). The length of railway lines worked is obtained by taking these sections including main-line track listed in the Capital Expenditure Account. Sections not worked are deducted only in cases where they are permanently out of use that is to say, if they are no longer maintained in working order. Lines temporarily out of use continue to form part of the length of lines worked. The length of a section is measured in the middle of the section, from centre to centre of the passenger buildings, or of the corresponding service buildings, of stations which are shown as independent points of departure or arrival for the conveyance of passengers or freight. If the boundary of the rail network falls in open track, the length of the section is measured up to that point. The section situated between a station approach and the join to the main line of two lines or more which is used by all trains in either direction over these lines, is only counted once. However, if for one or more of these lines, tracks are normally allocated, the length of these lines is counted separately. On the other hand, if between two stations there are one or more parallel tracks (siding-lines) to the main line, only the length of the latter is counted. In the case of regular lines worked exclusively during part of the year (seasonal lines), their length is included in the end-of-year statement.", "origins": [ { "producer": "International Union of Railways (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "total route-km" }, "is_shp_gcnw_xq": { "title": "Liner shipping connectivity index (maximum value in 2004 = 100)", "description_from_producer": "The Liner Shipping Connectivity Index captures how well countries are connected to global shipping networks. It is computed by the United Nations Conference on Trade and Development (UNCTAD) based on five components of the maritime transport sector: number of ships, their container-carrying capacity, maximum vessel size, number of services, and number of companies that deploy container ships in a country's ports. For each component a country's value is divided by the maximum value of each component in 2004, the five components are averaged for each country, and the average is divided by the maximum average for 2004 and multiplied by 100. The index generates a value of 100 for the country with the highest average index in 2004. . The underlying data come from Containerisation International Online.\n\nLimitations and exceptions: Data on trade facilitation are drawn from research by private and international agencies. Most data are perception-based evaluations by business executives and professionals. Because of different backgrounds, values, and personalities, those surveyed may evaluate the same situation differently. Caution should thus be used when interpreting perception- based indicators. Nevertheless, they convey much needed information on trade facilitation.\n\nStatistical concept and methodology: The Liner Shipping Connectivity Index captures how well countries are connected to global shipping networks. Starting in 2020 the index was improved and is published as a quarterly series with the index set at 100 for the country with the highest average in the first quarter of 2006. It is computed by the United Nations Conference on Trade and Development (UNCTAD) based on six components of the maritime transport sector: number of ships, their container-carrying capacity, maximum vessel size, number of services, the number of country-pairs with a direct connection, and number of companies that deploy container ships in a country's ports. The data are derived from Containerisation International Online (www.ci-online.co.uk). For each of the six components, a country's value is divided by the maximum value of that component in Q1 2006, and for each country, the average of the six components is calculated. This average is then divided by the maximum average for Q1 2006 and multiplied by 100. In this way, the index generates the value 100 for the country with the highest average index of the six components in Q1 2006. Annual values of the index equal the values of the first quarter of the same corresponding year.", "origins": [ { "producer": "UN Conference on Trade and Development (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "maximum value in 2004 = 100" }, "is_shp_good_tu": { "title": "Container port traffic (TEU: 20 foot equivalent units)", "description_from_producer": "Port container traffic measures the flow of containers from land to sea transport modes, and vice versa, in twenty-foot equivalent units (TEUs), a standard-size container. Data refer to coastal shipping as well as international journeys. Transshipment traffic is counted as two lifts at the intermediate port (once to off-load and again as an outbound lift) and includes empty units.\n\nLimitations and exceptions: Measures of port container traffic, much of it commodities of medium to high value added, give some indication of economic growth in a country. But when traffic is merely transshipment, much of the economic benefit goes to the terminal operator and ancillary services for ships and containers rather than to the country more broadly. In transshipment centers empty containers may account for as much as 40 percent of traffic.\n\nData cover coastal shipping as well as international journeys. Transshipment traffic is counted as two lifts at the intermediate port (once to off-load and again as an outbound lift) and includes empty units. Data for transport sectors are not always internationally comparable. Unlike for demographic statistics, national income accounts, and international trade data, the collection of infrastructure data has not been \"internationalized.\"\n\nStatistical concept and methodology: TEU is the standard unit, referring to 20-foot equivalent units or 20-foot-long cargo container. The size of cargo containers range from 20 feet long to more than 50 feet long. The international measure is the smallest box, the 20-footer or 20-foot-equivalent unit (TEU). Two twenty-foot containers (TEUs) equal one FEU. Container vessel capacity and port throughput capacity are frequently referred to in TEUs.", "origins": [ { "producer": "UN Conference on Trade and Development (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "TEU: 20 foot equivalent units" }, "it_cel_sets": { "title": "Mobile cellular subscriptions", "description_from_producer": "Mobile cellular telephone subscriptions are subscriptions to a public mobile telephone service that provide access to the PSTN using cellular technology. The indicator includes (and is split into) the number of postpaid subscriptions, and the number of active prepaid accounts (i.e. that have been used during the last three months). The indicator applies to all mobile cellular subscriptions that offer voice communications. It excludes subscriptions via data cards or USB modems, subscriptions to public mobile data services, private trunked mobile radio, telepoint, radio paging and telemetry services.\n\nLimitations and exceptions: Operators have traditionally been the main source of telecommunications data, so information on subscriptions has been widely available for most countries. This gives a general idea of access, but a more precise measure is the penetration rate - the share of households with access to telecommunications. During the past few years more information on information and communication technology use has become available from household and business surveys. Also important are data on actual use of telecommunications services. Ideally, statistics on telecommunications (and other information and communications technologies) should be compiled for all three measures: subscriptions, access, and use. The quality of data varies among reporting countries as a result of differences in regulations covering data provision and availability.\n\nDiscrepancies between global and national figures may arise when countries use a different definition than the one used by ITU. For example, some countries do not include the number of ISDN channels when calculating the number of fixed telephone lines. Discrepancies may also arise in cases where the end of a fiscal year differs from that used by ITU, which is the end of December of every year. A number of countries have fiscal years that end in March or June of every year. Data are usually not adjusted but discrepancies in the definition, reference year or the break in comparability in between years are noted in a data note. For this reason, data are not always strictly comparable. Missing values are estimated by ITU.\n\nMobile subscriptions include both analogue and digital cellular systems (IMT-2000 (Third Generation, 3G) and 4G subscriptions, but excludes mobile broadband subscriptions via data cards or USB modems. Subscriptions to public mobile data services, private trunked mobile radio, telepoint or radio paging, and telemetry services are also excluded, but all mobile cellular subscriptions that offer voice communications are included. Both postpaid and prepaid subscriptions are included.\n\nStatistical concept and methodology: Refers to the subscriptions to a public mobile telephone service and provides access to Public Switched Telephone Network (PSTN) using cellular technology, including number of pre-paid SIM cards active during the past three months. This includes both analogue and digital cellular systems (IMT-2000 (Third Generation, 3G) and 4G subscriptions, but excludes mobile broadband subscriptions via data cards or USB modems. Subscriptions to public mobile data services, private trunked mobile radio, telepoint or radio paging, and telemetry services should also be excluded. This should include all mobile cellular subscriptions that offer voice communications.\n\nData on mobile cellular subscribers are derived using administrative data that countries (usually the regulatory telecommunication authority or the Ministry in charge of telecommunications) regularly, and at least annually, collect from telecommunications operators.\n\nData for this indicator are readily available for approximately 90 percent of countries, either through ITU's World Telecommunication Indicators questionnaires or from official information available on the Ministry or Regulator's website. For the rest, information can be aggregated through operators' data (mainly through annual reports) and complemented by market research reports. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx", "origins": [ { "producer": "International Telecommunication Union (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "", "display": { "numDecimalPlaces": 0 } }, "it_cel_sets_p2": { "title": "Mobile cellular subscriptions (per 100 people)", "description_from_producer": "Mobile cellular telephone subscriptions are subscriptions to a public mobile telephone service that provide access to the PSTN using cellular technology. The indicator includes (and is split into) the number of postpaid subscriptions, and the number of active prepaid accounts (i.e. that have been used during the last three months). The indicator applies to all mobile cellular subscriptions that offer voice communications. It excludes subscriptions via data cards or USB modems, subscriptions to public mobile data services, private trunked mobile radio, telepoint, radio paging and telemetry services.\n\nLimitations and exceptions: Operators have traditionally been the main source of telecommunications data, so information on subscriptions has been widely available for most countries. This gives a general idea of access, but a more precise measure is the penetration rate - the share of households with access to telecommunications. During the past few years more information on information and communication technology use has become available from household and business surveys. Also important are data on actual use of telecommunications services. Ideally, statistics on telecommunications (and other information and communications technologies) should be compiled for all three measures: subscriptions, access, and use. The quality of data varies among reporting countries as a result of differences in regulations covering data provision and availability.\n\nDiscrepancies between global and national figures may arise when countries use a different definition than the one used by ITU. For example, some countries do not include the number of ISDN channels when calculating the number of fixed telephone lines. Discrepancies may also arise in cases where the end of a fiscal year differs from that used by ITU, which is the end of December of every year. A number of countries have fiscal years that end in March or June of every year. Data are usually not adjusted but discrepancies in the definition, reference year or the break in comparability in between years are noted in a data note. For this reason, data are not always strictly comparable. Missing values are estimated by ITU.\n\nMobile subscriptions include both analogue and digital cellular systems (IMT-2000 (Third Generation, 3G) and 4G subscriptions, but excludes mobile broadband subscriptions via data cards or USB modems. Subscriptions to public mobile data services, private trunked mobile radio, telepoint or radio paging, and telemetry services are also excluded, but all mobile cellular subscriptions that offer voice communications are included. Both postpaid and prepaid subscriptions are included.\n\nStatistical concept and methodology: Refers to the subscriptions to a public mobile telephone service and provides access to Public Switched Telephone Network (PSTN) using cellular technology, including number of pre-paid SIM cards active during the past three months. This includes both analogue and digital cellular systems (IMT-2000 (Third Generation, 3G) and 4G subscriptions, but excludes mobile broadband subscriptions via data cards or USB modems. Subscriptions to public mobile data services, private trunked mobile radio, telepoint or radio paging, and telemetry services should also be excluded. This should include all mobile cellular subscriptions that offer voice communications.\n\nData on mobile cellular subscribers are derived using administrative data that countries (usually the regulatory telecommunication authority or the Ministry in charge of telecommunications) regularly, and at least annually, collect from telecommunications operators.\n\nData for this indicator are readily available for approximately 90 percent of countries, either through ITU's World Telecommunication Indicators questionnaires or from official information available on the Ministry or Regulator's website. For the rest, information can be aggregated through operators' data (mainly through annual reports) and complemented by market research reports.\n\nMobile cellular subscriptions (per 100 people) indicator is derived by all mobile subscriptions divided by the country's population and multiplied by 100. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx", "origins": [ { "producer": "International Telecommunication Union (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100 people" }, "it_mlt_main": { "title": "Fixed telephone subscriptions", "description_from_producer": "Fixed telephone subscriptions refers to the sum of active number of analogue fixed telephone lines, voice-over-IP (VoIP) subscriptions, fixed wireless local loop (WLL) subscriptions, ISDN voice-channel equivalents and fixed public payphones.\n\nLimitations and exceptions: Operators have traditionally been the main source of telecommunications data, so information on subscriptions has been widely available for most countries. This gives a general idea of access, but a more precise measure is the penetration rate - the share of households with access to telecommunications. During the past few years more information on information and communication technology use has become available from household and business surveys. Also important are data on actual use of telecommunications services. Ideally, statistics on telecommunications (and other information and communications technologies) should be compiled for all three measures: subscriptions, access, and use. The quality of data varies among reporting countries as a result of differences in regulations covering data provision and availability.\n\nDiscrepancies between global and national figures may arise when countries use a different definition than the one used by ITU. For example, some countries do not include the number of ISDN channels when calculating the number of fixed telephone lines. Discrepancies may also arise in cases where the end of a fiscal year differs from that used by ITU, which is the end of December of every year. A number of countries have fiscal years that end in March or June of every year. Data are usually not adjusted but discrepancies in the definition, reference year or the break in comparability in between years are noted in a data note. For this reason, data are not always strictly comparable. Missing values are estimated by ITU.\n\nStatistical concept and methodology: A fixed telephone line (previously called main telephone line in operation) is an active line connecting the subscriber's terminal equipment to the public switched telephone network (PSTN) and which has a dedicated port in the telephone exchange equipment. This term is synonymous with the terms main station or Direct Exchange Line (DEL) that are commonly used in telecommunication documents. It may not be the same as an access line or a subscriber. This should include the active number of analog fixed telephone lines, ISDN channels, fixed wireless, public payphones and VoIP subscriptions. Active lines are those that have registered an activity in the past three months.\n\nData on fixed telephone lines are derived using administrative data that countries (usually the regulatory telecommunication authority or the Ministry in charge of telecommunications) regularly, and at least annually, collect from telecommunications operators. Data are considered to be very reliable, timely, and complete.\n\nData for this indicator are readily available for approximately 90 percent of countries, either through ITU's World Telecommunication Indicators questionnaires or from official information available on the Ministry or Regulator's website. For the rest, information can be aggregated through operators' data (mainly through annual reports) and complemented by market research reports. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx", "origins": [ { "producer": "International Telecommunication Union (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "it_mlt_main_p2": { "title": "Fixed telephone subscriptions (per 100 people)", "description_from_producer": "Fixed telephone subscriptions refers to the sum of active number of analogue fixed telephone lines, voice-over-IP (VoIP) subscriptions, fixed wireless local loop (WLL) subscriptions, ISDN voice-channel equivalents and fixed public payphones.\n\nLimitations and exceptions: Operators have traditionally been the main source of telecommunications data, so information on subscriptions has been widely available for most countries. This gives a general idea of access, but a more precise measure is the penetration rate - the share of households with access to telecommunications. During the past few years more information on information and communication technology use has become available from household and business surveys. Also important are data on actual use of telecommunications services. Ideally, statistics on telecommunications (and other information and communications technologies) should be compiled for all three measures: subscriptions, access, and use. The quality of data varies among reporting countries as a result of differences in regulations covering data provision and availability.\n\nDiscrepancies between global and national figures may arise when countries use a different definition than the one used by ITU. For example, some countries do not include the number of ISDN channels when calculating the number of fixed telephone lines. Discrepancies may also arise in cases where the end of a fiscal year differs from that used by ITU, which is the end of December of every year. A number of countries have fiscal years that end in March or June of every year. Data are usually not adjusted but discrepancies in the definition, reference year or the break in comparability in between years are noted in a data note. For this reason, data are not always strictly comparable. Missing values are estimated by ITU.\n\nStatistical concept and methodology: A fixed telephone line (previously called main telephone line in operation) is an active line connecting the subscriber's terminal equipment to the public switched telephone network (PSTN) and which has a dedicated port in the telephone exchange equipment. This term is synonymous with the terms main station or Direct Exchange Line (DEL) that are commonly used in telecommunication documents. It may not be the same as an access line or a subscriber. This should include the active number of analog fixed telephone lines, ISDN channels, fixed wireless, public payphones and VoIP subscriptions. Active lines are those that have registered an activity in the past three months.\n\nData on fixed telephone lines are derived using administrative data that countries (usually the regulatory telecommunication authority or the Ministry in charge of telecommunications) regularly, and at least annually, collect from telecommunications operators. Data are considered to be very reliable, timely, and complete.\n\nData for this indicator are readily available for approximately 90 percent of countries, either through ITU's World Telecommunication Indicators questionnaires or from official information available on the Ministry or Regulator's website. For the rest, information can be aggregated through operators' data (mainly through annual reports) and complemented by market research reports.\n\nTelephone lines (per 100 people) indicator is derived by all telephone lines divided by the country's population and multiplied by 100. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx", "origins": [ { "producer": "International Telecommunication Union (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100 people" }, "it_net_bbnd": { "title": "Fixed broadband subscriptions", "description_from_producer": "Fixed broadband subscriptions refers to fixed subscriptions to high-speed access to the public Internet (a TCP/IP connection), at downstream speeds equal to, or greater than, 256 kbit/s. This includes cable modem, DSL, fiber-to-the-home/building, other fixed (wired)-broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It should include fixed WiMAX and any other fixed wireless technologies. It includes both residential subscriptions and subscriptions for organizations.", "origins": [ { "producer": "International Telecommunication Union (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "it_net_bbnd_p2": { "title": "Fixed broadband subscriptions (per 100 people)", "description_from_producer": "Fixed broadband subscriptions refers to fixed subscriptions to high-speed access to the public Internet (a TCP/IP connection), at downstream speeds equal to, or greater than, 256 kbit/s. This includes cable modem, DSL, fiber-to-the-home/building, other fixed (wired)-broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It should include fixed WiMAX and any other fixed wireless technologies. It includes both residential subscriptions and subscriptions for organizations.\n\nLimitations and exceptions: Data are collected by national statistics offices through household surveys. Because survey questions and definitions differ, the estimates may not be strictly comparable across countries.\n\nFixed broadband Internet includes cable modem, DSL, fibre and other fixed broadband technology (such as satellite broadband Internet, Ethernet LANs, fixed-wireless access, Wireless Local Area Network, WiMAX etc.). Subscribers with access to data communications (including the Internet) via mobile cellular networks are excluded.\n\nAdvertised and real speeds can differ substantially. In some countries, regulatory authorities monitor the speed and quality of broadband services and oblige operators to provide accurate quality-of-service information to end users. Regional and global totals are calculated as unweighted sums of the country values. Regional and global penetration rates (per 100 inhabitants) are weighted averages of the country values weighted by the population of the countries/regions.\n\nDiscrepancies between global and national figures may arise when countries use a different definition than the one used by ITU. Discrepancies may also arise in cases where the end of a fiscal year differs from that used by ITU, which is end of December of every year. A number of countries have fiscal years that end in March or June of every year.\n\nStatistical concept and methodology: Data refer to subscriptions to high-speed access to the public Internet (a TCP/IP connection), at downstream speeds equal to, or greater than, 256 kbit/s. This includes cable modem, DSL, fibre-to-the-home/building and other fixed (wired)-broadband subscriptions. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It excludes technologies listed under the wireless-broadband category.\n\nFixed broadband Internet subscribers per 100 people is obtained by dividing the number of fixed broadband Internet subscribers by the population and then multiplying by 100. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx", "origins": [ { "producer": "International Telecommunication Union (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100 people" }, "it_net_secr": { "title": "Secure Internet servers", "description_from_producer": "The number of distinct, publicly-trusted TLS/SSL certificates found in the Netcraft Secure Server Survey.\n\nStatistical concept and methodology: The survey examines the use of encrypted transactions through extensive automated exploration, tallying the number of web sites using HTTPS. This analysis relates to those sites found in the survey where the certificate is valid for the hostname, and the certificate has been issued from a publicly-trusted root. The indicator refers to valid, third-party certificates. Included are sites found in the survey where the common name in the certificate matched the hostname, and the certificate's digital signature was not detected as being self-signed. The location is derived from the hosting location of the sites using the certificates (rather than the countries indicated on the certificates themselves.) \"Netcraft's survey counts (unique) valid certificates issued by widely-trusted third-party certification authorities. A certificate must be valid, that is it must be within its validity period (certificates are usually valid for up to 39 months), and the digital signatures on the certificate must check successfully. It must be issued by third party certificate issuer that is recognised by Netcraft. Netcraft investigate new issuers each month and determine whether they are third party issuers that could be expected to be trusted by some user base; CAs that issue only for one company are generally excluded, as are self-signed certificates.\" Netcraft note on the term \u201cvalid certificates\": \u201cThere is nothing inherently \"invalid\" about private certification or self-signed certificates. But neither of these types of certificates are generally accepted by end-users' browsers, and browsers would typically report them as \"invalid\", so our terminology is consistent with normal user expectations.\u201d [https://www.netcraft.com/] The data reflects the December survey in that year.", "origins": [ { "producer": "Netcraft (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "it_net_secr_p6": { "title": "Secure Internet servers (per 1 million people)", "description_from_producer": "The number of distinct, publicly-trusted TLS/SSL certificates found in the Netcraft Secure Server Survey.\n\nStatistical concept and methodology: The survey examines the use of encrypted transactions through extensive automated exploration, tallying the number of web sites using HTTPS. This analysis relates to those sites found in the survey where the certificate is valid for the hostname, and the certificate has been issued from a publicly-trusted root. The indicator refers to valid, third-party certificates. Included are sites found in the survey where the common name in the certificate matched the hostname, and the certificate's digital signature was not detected as being self-signed. The location is derived from the hosting location of the sites using the certificates (rather than the countries indicated on the certificates themselves.) \"Netcraft's survey counts (unique) valid certificates issued by widely-trusted third-party certification authorities. A certificate must be valid, that is it must be within its validity period (certificates are usually valid for up to 39 months), and the digital signatures on the certificate must check successfully. It must be issued by third party certificate issuer that is recognised by Netcraft. Netcraft investigate new issuers each month and determine whether they are third party issuers that could be expected to be trusted by some user base; CAs that issue only for one company are generally excluded, as are self-signed certificates.\" Netcraft note on the term \u201cvalid certificates\": \u201cThere is nothing inherently \"invalid\" about private certification or self-signed certificates. But neither of these types of certificates are generally accepted by end-users' browsers, and browsers would typically report them as \"invalid\", so our terminology is consistent with normal user expectations.\u201d [https://www.netcraft.com/] The data reflects the December survey in that year.", "origins": [ { "producer": "Netcraft and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1 million people" }, "it_net_user_zs": { "title": "Individuals using the Internet (% of population)", "description_from_producer": "Internet users are individuals who have used the Internet (from any location) in the last 3 months. The Internet can be used via a computer, mobile phone, personal digital assistant, games machine, digital TV etc.\n\nLimitations and exceptions: Operators have traditionally been the main source of telecommunications data, so information on subscriptions has been widely available for most countries. This gives a general idea of access, but a more precise measure is the penetration rate - the share of households with access to telecommunications. During the past few years more information on information and communication technology use has become available from household and business surveys. Also important are data on actual use of telecommunications services. Ideally, statistics on telecommunications (and other information and communications technologies) should be compiled for all three measures: subscriptions, access, and use. The quality of data varies among reporting countries as a result of differences in regulations covering data provision and availability.\n\nDiscrepancies may also arise in cases where the end of a fiscal year differs from that used by ITU, which is the end of December of every year. A number of countries have fiscal years that end in March or June of every year.\n\nStatistical concept and methodology: The Internet is a world-wide public computer network. It provides access to a number of communication services including the World Wide Web and carries email, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer - it may also be by mobile phone, PDA, games machine, digital TV etc.). Access can be via a fixed or mobile network. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx", "origins": [ { "producer": "International Telecommunication Union (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population" }, "lp_exp_durs_md": { "title": "Lead time to export, median case (days)", "description_from_producer": "Lead time to export is the median time (the value for 50 percent of shipments) from shipment point to port of loading. Data are from the Logistics Performance Index survey. Respondents provided separate values for the best case (10 percent of shipments) and the median case (50 percent of shipments). The data are exponentiated averages of the logarithm of single value responses and of midpoint values of range responses for the median case.\n\nLimitations and exceptions: The Logistics Performance Index is an interactive benchmarking tool created to help countries identify the challenges and opportunities they face in their performance on trade logistics and what they can do to improve their performance. Feedback from operators is supplemented with quantitative data on the performance of key components of the logistics chain in the country of work. Thus, the LPI consists of both qualitative and quantitative measures.\n\nIn addition, despite being the most comprehensive data source for country logistics and trade facilitation, the LPI has two important limitations. First, the experience of international freight forwarders might not represent the broader logistics environment in poor countries, which often rely on traditional operators. And the international and traditional operators might differ in their interactions with government agencies - and in their service levels. Second, for landlocked countries and small-island states, the LPI might reflect access problems outside the country assessed, such as transit difficulties. The low rating of a landlocked country might not adequately reflect its trade facilitation efforts, which depend on the workings of complex international transit systems. Landlocked countries cannot eliminate transit inefficiencies with domestic reforms.\n\nStatistical concept and methodology: Data on lead time to export are from the Logistics Performance Index (LPI) survey. Respondents provided separate values for the best case (10 percent of shipments) and the median case (50 percent of shipments) of shipments from the point of origin (the seller's factory, typically located either in the capital city or in the largest commercial center) to the port of loading or equivalent (port/airport), and excluding international shipping.\n\nThe Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and at the main express carriers. The 2012 LPI data are based on the 2011 survey, which was administered to nearly 1,000 respondents at international logistics companies in 143 countries (domestic performance indicators). The international LPI covers 155 countries. The LPI assesses both large companies and small and medium enterprises. Most of the responses are from small and medium enterprises, with large companies (those with 250 employees or more) accounting for roughly 18 percent of responses. The respondents include groups of professionals who are directly involved in day-today operations, from company headquarters and from country offices such as senior executives, area or country managers, and department managers. Many of the respondents are at corporate or regional headquarters or at country branch offices. The rest are at local branch offices or independent firms. The majority of respondents are involved in providing most logistics services as their main line of work such as warehousing and distribution, customer-tailored logistics solutions, courier services, bulk or break bulk cargo transport, and less-than-full container, full-container, or full-trailer load transport.\n\nFor the lead time to export, respondents were asked for quantitative information on their countries' international supply chains by picking choices from a dropdown menu. When a response indicates a single value, the answer is coded as the logarithm of that value. When a response indicates a range, the answer is coded as the logarithm of the midpoint of that range. Country scores are produced by exponentiating the average of responses in logarithms across all respondents for a given country. This method is equivalent to taking a geometric average in levels. Scores for regions, income groups, and LPI quintiles are simple averages of the relevant country scores.", "origins": [ { "producer": "World Bank and Turku School of Economics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "lp_imp_durs_md": { "title": "Lead time to import, median case (days)", "description_from_producer": "Lead time to import is the median time (the value for 50 percent of shipments) from port of discharge to arrival at the consignee. Data are from the Logistics Performance Index survey. Respondents provided separate values for the best case (10 percent of shipments) and the median case (50 percent of shipments). The data are exponentiated averages of the logarithm of single value responses and of midpoint values of range responses for the median case.\n\nLimitations and exceptions: The Logistics Performance Index is an interactive benchmarking tool created to help countries identify the challenges and opportunities they face in their performance on trade logistics and what they can do to improve their performance. Feedback from operators is supplemented with quantitative data on the performance of key components of the logistics chain in the country of work. Thus, the LPI consists of both qualitative and quantitative measures.\n\nIn addition, despite being the most comprehensive data source for country logistics and trade facilitation, the LPI has two important limitations. First, the experience of international freight forwarders might not represent the broader logistics environment in poor countries, which often rely on traditional operators. And the international and traditional operators might differ in their interactions with government agencies - and in their service levels. Second, for landlocked countries and small-island states, the LPI might reflect access problems outside the country assessed, such as transit difficulties. The low rating of a landlocked country might not adequately reflect its trade facilitation efforts, which depend on the workings of complex international transit systems. Landlocked countries cannot eliminate transit inefficiencies with domestic reforms.\n\nStatistical concept and methodology: Data on lead time to import are from the Logistics Performance Index (LPI) survey. Respondents provided separate values for the best case (10 percent of shipments) and the median case (50 percent of shipments) of shipments from the port of discharge or equivalent to the buyer's warehouse.\n\nThe Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and at the main express carriers. The 2012 LPI data are based on the 2011 survey, which was administered to nearly 1,000 respondents at international logistics companies in 143 countries (domestic performance indicators). The international LPI covers 155 countries. The LPI assesses both large companies and small and medium enterprises. Most of the responses are from small and medium enterprises, with large companies (those with 250 employees or more) accounting for roughly 18 percent of responses. The respondents include groups of professionals who are directly involved in day-today operations, from company headquarters and from country offices such as senior executives, area or country managers, and department managers. Many of the respondents are at corporate or regional headquarters or at country branch offices. The rest are at local branch offices or independent firms. The majority of respondents are involved in providing most logistics services as their main line of work such as warehousing and distribution, customer-tailored logistics solutions, courier services, bulk or break bulk cargo transport, and less-than-full container, full-container, or full-trailer load transport.\n\nFor the lead time to import, respondents were asked for quantitative information on their countries' international supply chains by picking choices from a dropdown menu. When a response indicates a single value, the answer is coded as the logarithm of that value. When a response indicates a range, the answer is coded as the logarithm of the midpoint of that range. Country scores are produced by exponentiating the average of responses in logarithms across all respondents for a given country. This method is equivalent to taking a geometric average in levels. Scores for regions, income groups, and LPI quintiles are simple averages of the relevant country scores.", "origins": [ { "producer": "World Bank and Turku School of Economics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "days", "short_unit": "days" }, "lp_lpi_cust_xq": { "title": "Logistics performance index: Efficiency of customs clearance process (1=low to 5=high)", "description_from_producer": "Data are from the Logistics Performance Index survey conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. Respondents evaluate eight countries on six core dimensions on a scale from 1 (worst) to 5 (best). The eight countries are chosen based on the most important export and import markets of the respondent's country, random selection, and, for landlocked countries, neighboring countries that connect them with international markets. The 2023 LPI survey was conducted from September 6 to November 5, 2022. It provided 4,090 country assessments by 652 logistics professionals in 115 countries in all World Bank regions. Details of the survey methodology and index construction methodology are included in Appendix 5 of the 2023 LPI report available at: https://lpi.worldbank.org/report. Respondents evaluated efficiency of customs clearance processes (i.e. speed, simplicity and predictability of formalities), on a rating ranging from 1 (very low) to 5 (very high). Scores are averaged across all respondents.\n\nLimitations and exceptions: The Logistics Performance Index is an interactive benchmarking tool created to help countries identify the challenges and opportunities they face in their performance on trade logistics and what they can do to improve their performance. Despite being the most comprehensive data source for country logistics and trade facilitation, the LPI has two important limitations. First, the experience of international freight forwarders might not represent the broader logistics environment in poor countries, which often rely on traditional operators. And the international and traditional operators might differ in their interactions with government agencies - and in their service levels. Second, for landlocked countries and small-island states, the LPI might reflect access problems outside the country assessed, such as transit difficulties. The low rating of a landlocked country might not adequately reflect its trade facilitation efforts, which depend on the workings of complex international transit systems. Landlocked countries cannot eliminate transit inefficiencies with domestic reforms.\n\nStatistical concept and methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5. The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets. The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions. The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 5=high" }, "lp_lpi_infr_xq": { "title": "Logistics performance index: Quality of trade and transport-related infrastructure (1=low to 5=high)", "description_from_producer": "Data are from the Logistics Performance Index survey conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. Respondents evaluate eight countries on six core dimensions on a scale from 1 (worst) to 5 (best). The eight countries are chosen based on the most important export and import markets of the respondent's country, random selection, and, for landlocked countries, neighboring countries that connect them with international markets. The 2023 LPI survey was conducted from September 6 to November 5, 2022. It provided 4,090 country assessments by 652 logistics professionals in 115 countries in all World Bank regions. Details of the survey methodology and index construction methodology are included in Appendix 5 of the 2023 LPI report available at: https://lpi.worldbank.org/report. Respondents evaluated the quality of trade and transport related infrastructure (e.g. ports, railroads, roads, information technology), on a rating ranging from 1 (very low) to 5 (very high). Scores are averaged across all respondents.\n\nLimitations and exceptions: The Logistics Performance Index is an interactive benchmarking tool created to help countries identify the challenges and opportunities they face in their performance on trade logistics and what they can do to improve their performance. Despite being the most comprehensive data source for country logistics and trade facilitation, the LPI has two important limitations. First, the experience of international freight forwarders might not represent the broader logistics environment in poor countries, which often rely on traditional operators. And the international and traditional operators might differ in their interactions with government agencies - and in their service levels. Second, for landlocked countries and small-island states, the LPI might reflect access problems outside the country assessed, such as transit difficulties. The low rating of a landlocked country might not adequately reflect its trade facilitation efforts, which depend on the workings of complex international transit systems. Landlocked countries cannot eliminate transit inefficiencies with domestic reforms.\n\nStatistical concept and methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5. The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets. The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions. The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 5=high" }, "lp_lpi_itrn_xq": { "title": "Logistics performance index: Ease of arranging competitively priced shipments (1=low to 5=high)", "description_from_producer": "Data are from the Logistics Performance Index survey conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. Respondents evaluate eight countries on six core dimensions on a scale from 1 (worst) to 5 (best). The eight countries are chosen based on the most important export and import markets of the respondent's country, random selection, and, for landlocked countries, neighboring countries that connect them with international markets. The 2023 LPI survey was conducted from September 6 to November 5, 2022. It provided 4,090 country assessments by 652 logistics professionals in 115 countries in all World Bank regions. Details of the survey methodology and index construction methodology are included in Appendix 5 of the 2023 LPI report available at: https://lpi.worldbank.org/report. Respondents assessed the ease of arranging competitively priced shipments to markets, on a rating ranging from 1 (very difficult) to 5 (very easy). Scores are averaged across all respondents.\n\nLimitations and exceptions: The Logistics Performance Index is an interactive benchmarking tool created to help countries identify the challenges and opportunities they face in their performance on trade logistics and what they can do to improve their performance. Despite being the most comprehensive data source for country logistics and trade facilitation, the LPI has two important limitations. First, the experience of international freight forwarders might not represent the broader logistics environment in poor countries, which often rely on traditional operators. And the international and traditional operators might differ in their interactions with government agencies - and in their service levels. Second, for landlocked countries and small-island states, the LPI might reflect access problems outside the country assessed, such as transit difficulties. The low rating of a landlocked country might not adequately reflect its trade facilitation efforts, which depend on the workings of complex international transit systems. Landlocked countries cannot eliminate transit inefficiencies with domestic reforms.\n\nStatistical concept and methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5. The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets. The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions. The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 5=high" }, "lp_lpi_logs_xq": { "title": "Logistics performance index: Competence and quality of logistics services (1=low to 5=high)", "description_from_producer": "Data are from the Logistics Performance Index survey conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. Respondents evaluate eight countries on six core dimensions on a scale from 1 (worst) to 5 (best). The eight countries are chosen based on the most important export and import markets of the respondent's country, random selection, and, for landlocked countries, neighboring countries that connect them with international markets. The 2023 LPI survey was conducted from September 6 to November 5, 2022. It provided 4,090 country assessments by 652 logistics professionals in 115 countries in all World Bank regions. Details of the survey methodology and index construction methodology are included in Appendix 5 of the 2023 LPI report available at: https://lpi.worldbank.org/report. Respondents evaluated the overall level of competence and quality of logistics services (e.g. transport operators, customs brokers), on a rating ranging from 1 (very low) to 5 (very high). Scores are averaged across all respondents.\n\nLimitations and exceptions: The Logistics Performance Index is an interactive benchmarking tool created to help countries identify the challenges and opportunities they face in their performance on trade logistics and what they can do to improve their performance. Despite being the most comprehensive data source for country logistics and trade facilitation, the LPI has two important limitations. First, the experience of international freight forwarders might not represent the broader logistics environment in poor countries, which often rely on traditional operators. And the international and traditional operators might differ in their interactions with government agencies - and in their service levels. Second, for landlocked countries and small-island states, the LPI might reflect access problems outside the country assessed, such as transit difficulties. The low rating of a landlocked country might not adequately reflect its trade facilitation efforts, which depend on the workings of complex international transit systems. Landlocked countries cannot eliminate transit inefficiencies with domestic reforms.\n\nStatistical concept and methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5. The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets. The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions. The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 5=high" }, "lp_lpi_ovrl_xq": { "title": "Logistics performance index: Overall (1=low to 5=high)", "description_from_producer": "The Logistics Performance Index overall score reflects perceptions of a country's logistics based on the efficiency of customs clearance process, quality of trade- and transport-related infrastructure, ease of arranging competitively priced shipments, quality of logistics services, ability to track and trace consignments, and frequency with which shipments reach the consignee within the scheduled time. The index ranges from 1 to 5, with a higher score representing better performance.\nData are from the Logistics Performance Index survey conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. The 2023 LPI survey was conducted from September 6 to November 5, 2022. It provided 4,090 country assessments by 652 logistics professionals in 115 countries in all World Bank regions. Respondents evaluate eight countries on six core dimensions on a scale from 1 (worst) to 5 (best). The eight countries are chosen based on the most important export and import markets of the respondent's country, random selection, and, for landlocked countries, neighboring countries that connect them with international markets.\nScores for the six areas are averaged across all respondents and aggregated to a single score using principal components analysis.\nDetails of the survey methodology and index construction methodology are included in Appendix 5 of the 2023 LPI report available at: https://lpi.worldbank.org/report.\n\nLimitations and exceptions: The Logistics Performance Index is an interactive benchmarking tool created to help countries identify the challenges and opportunities they face in their performance on trade logistics and what they can do to improve their performance. Despite being the most comprehensive data source for country logistics and trade facilitation, the LPI has two important limitations. First, the experience of international freight forwarders might not represent the broader logistics environment in poor countries, which often rely on traditional operators. And the international and traditional operators might differ in their interactions with government agencies - and in their service levels. Second, for landlocked countries and small-island states, the LPI might reflect access problems outside the country assessed, such as transit difficulties. The low rating of a landlocked country might not adequately reflect its trade facilitation efforts, which depend on the workings of complex international transit systems. Landlocked countries cannot eliminate transit inefficiencies with domestic reforms.\n\nStatistical concept and methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5. The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets. The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions. The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 5=high" }, "lp_lpi_time_xq": { "title": "Logistics performance index: Frequency with which shipments reach consignee within scheduled or expected time (1=low to 5=high)", "description_from_producer": "Data are from the Logistics Performance Index survey conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. Respondents evaluate eight countries on six core dimensions on a scale from 1 (worst) to 5 (best). The eight countries are chosen based on the most important export and import markets of the respondent's country, random selection, and, for landlocked countries, neighboring countries that connect them with international markets. The 2023 LPI survey was conducted from September 6 to November 5, 2022. It provided 4,090 country assessments by 652 logistics professionals in 115 countries in all World Bank regions. Details of the survey methodology and index construction methodology are included in Appendix 5 of the 2023 LPI report available at: https://lpi.worldbank.org/report. Respondents assessed how often the shipments to assessed markets reach the consignee within the scheduled or expected delivery time, on a rating ranging from 1 (hardly ever) to 5 (nearly always). Scores are averaged across all respondents.\n\nLimitations and exceptions: The Logistics Performance Index is an interactive benchmarking tool created to help countries identify the challenges and opportunities they face in their performance on trade logistics and what they can do to improve their performance. Despite being the most comprehensive data source for country logistics and trade facilitation, the LPI has two important limitations. First, the experience of international freight forwarders might not represent the broader logistics environment in poor countries, which often rely on traditional operators. And the international and traditional operators might differ in their interactions with government agencies - and in their service levels. Second, for landlocked countries and small-island states, the LPI might reflect access problems outside the country assessed, such as transit difficulties. The low rating of a landlocked country might not adequately reflect its trade facilitation efforts, which depend on the workings of complex international transit systems. Landlocked countries cannot eliminate transit inefficiencies with domestic reforms.\n\nStatistical concept and methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5. The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets. The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions. The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 5=high" }, "lp_lpi_trac_xq": { "title": "Logistics performance index: Ability to track and trace consignments (1=low to 5=high)", "description_from_producer": "Data are from the Logistics Performance Index survey conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. Respondents evaluate eight countries on six core dimensions on a scale from 1 (worst) to 5 (best). The eight countries are chosen based on the most important export and import markets of the respondent's country, random selection, and, for landlocked countries, neighboring countries that connect them with international markets. The 2023 LPI survey was conducted from September 6 to November 5, 2022. It provided 4,090 country assessments by 652 logistics professionals in 115 countries in all World Bank regions. Details of the survey methodology and index construction methodology are included in Appendix 5 of the 2023 LPI report available at: https://lpi.worldbank.org/report. Respondents evaluated the ability to track and trace consignments when shipping to the market, on a rating ranging from 1 (very low) to 5 (very high). Scores are averaged across all respondents.\n\nLimitations and exceptions: The Logistics Performance Index is an interactive benchmarking tool created to help countries identify the challenges and opportunities they face in their performance on trade logistics and what they can do to improve their performance. Despite being the most comprehensive data source for country logistics and trade facilitation, the LPI has two important limitations. First, the experience of international freight forwarders might not represent the broader logistics environment in poor countries, which often rely on traditional operators. And the international and traditional operators might differ in their interactions with government agencies - and in their service levels. Second, for landlocked countries and small-island states, the LPI might reflect access problems outside the country assessed, such as transit difficulties. The low rating of a landlocked country might not adequately reflect its trade facilitation efforts, which depend on the workings of complex international transit systems. Landlocked countries cannot eliminate transit inefficiencies with domestic reforms.\n\nStatistical concept and methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5. The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets. The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions. The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1=low to 5=high" }, "ms_mil_mprt_kd": { "title": "Arms imports (SIPRI trend indicator values)", "description_from_producer": "Arms transfers cover the supply of military weapons through sales, aid, gifts, and those made through manufacturing licenses. Data cover major conventional weapons such as aircraft, armored vehicles, artillery, radar systems, missiles, and ships designed for military use. Excluded are transfers of other military equipment such as small arms and light weapons, trucks, small artillery, ammunition, support equipment, technology transfers, and other services. Figures are SIPRI Trend Indicator Values (TIVs) expressed in US$ m. A '0' indicates that the value of deliveries is less than US$0.5m.\n\nLimitations and exceptions: SIPRI calculates the volume of transfers to, from and between all parties using the TIV and the number of weapon systems or subsystems delivered in a given year. This data is intended to provide a common unit to allow the measurement if trends in the flow of arms to particular countries and regions over time. Therefore, the main priority is to ensure that the TIV system remains consistent over time, and that any changes introduced are backdated.\n\nSIPRI TIV figures do not represent sales prices for arms transfers. They should therefore not be directly compared with gross domestic product (GDP), military expenditure, sales values or the financial value of export licences in an attempt to measure the economic burden of arms imports or the economic benefits of exports. They are best used as the raw data for calculating trends in international arms transfers over periods of time, global percentages for suppliers and recipients, and percentages for the volume of transfers to or from particular states.\n\nStatistical concept and methodology: Stockholm International Peace Research Institute (SIPRI)'s Arms Transfers Program collects data on arms transfers from open sources. Since publicly available information is inadequate for tracking all weapons and other military equipment, SIPRI covers only what it terms major conventional weapons. Data cover the supply of weapons through sales, aid, gifts, and manufacturing licenses; therefore the term arms transfers rather than arms trade is used. SIPRI data also cover weapons supplied to or from rebel forces in an armed conflict as well as arms deliveries for which neither the supplier nor the recipient can be identified with acceptable certainty; these data are available in SIPRI's database.\n\nData cover major conventional weapons such as aircraft, armored vehicles, artillery, radar systems and other sensors, missiles, and ships designed for military use as well as some major components such as turrets for armored vehicles and engines. Excluded are other military equipment such as most small arms and light weapons, trucks, small artillery, ammunition, support equipment, technology transfers, and other services.\n\nNotes from original source: SIPRI statistical data on arms transfers relates to actual deliveries of major conventional weapons. To permit comparison between the data on such deliveries of different weapons and to identify general trends, SIPRI has developed a unique system to measure the volume of international transfers of major conventional weapons using a common unit, the trend-indicator value (TIV).\n\nThe TIV is based on the known unit production costs of a core set of weapons and is intended to represent the transfer of military resources rather than the financial value of the transfer. Weapons for which a production cost is not known are compared with core weapons based on: size and performance characteristics (weight, speed, range and payload); type of electronics, loading or unloading arrangements, engine, tracks or wheels, armament and materials; and the year in which the weapon was produced. A weapon that has been in service in another armed force is given a value 40 per cent of that of a new weapon. A used weapon that has been significantly refurbished or modified by the supplier before delivery is given a value of 66 per cent of that of a new weapon.", "origins": [ { "producer": "Stockholm International Peace Research Institute (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "SIPRI trend indicator values" }, "ms_mil_totl_p1": { "title": "Armed forces personnel, total", "description_from_producer": "Armed forces personnel are active duty military personnel, including paramilitary forces if the training, organization, equipment, and control suggest they may be used to support or replace regular military forces.\n\nLimitations and exceptions: Data excludes personnel not on active duty, therefore it underestimates the share of the labor force working for the defense establishment. The cooperation of governments of all countries listed in \u201cThe Military Balance\u201d has been sought by IISS and, in many cases, received. However, some data in \u201cThe Military Balance\u201d is estimated.\n\nStatistical concept and methodology: Military data on manpower represent quantitative assessment of the personnel strengths of the world's armed forces. The IISS collects the data from a wide variety of sources. The numbers are based on the most accurate data available to, or on the best estimate that can be made by the International Institute for Strategic Studies (IISS) at the time of its annual publication. The current WDI indicator includes active armed forces and active paramilitary (but not reservists). Armed forces personnel comprise all servicemen and women on full-time duty, including conscripts and long-term assignments from the Reserves (\u201cReserve\u201d describes formations and units not fully manned or operational in peacetime, but which can be mobilized by recalling reservists in an emergency). The indicator includes paramilitary forces. The source of the data (IISS) reports armed forces and paramilitary forces separately, however these figures are added for the purpose of computing this series. Home Guard units are counted as paramilitary.", "origins": [ { "producer": "International Institute for Strategic Studies (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ms_mil_totl_tf_zs": { "title": "Armed forces personnel (% of total labor force)", "description_from_producer": "Armed forces personnel are active duty military personnel, including paramilitary forces if the training, organization, equipment, and control suggest they may be used to support or replace regular military forces. Labor force comprises all people who meet the International Labour Organization's definition of the economically active population.\n\nLimitations and exceptions: Data exclude personnel not on active duty, therefore they underestimate the share of the labor force working for the defense establishment. Governments rarely report the size of their armed forces, so such data typically come from intelligence sources. Unless otherwise indicated, reserves includes all reservists committed to rejoining the armed forces in an emergency, except when national reserve service obligations following conscription last almost a lifetime.\n\nStatistical concept and methodology: Military data on manpower represent quantitative assessment of the personnel strengths of the world's armed forces. The numbers are based on the most accurate data available to, or, on the best estimate that can be made by the International Institute for Strategic Studies (IISS) at the time of its annual publication. The IISS collects the data from national governments.\n\nArmed forces personnel comprise all servicemen and women on full-time duty (including conscripts and long-term assignments from the Reserves). Reserve describes formations and units not fully manned or operational in peacetime, but which can be mobilized by recalling reservists in an emergency. IISS estimates of effective reservist strengths on the numbers available within five years of completing full-time service, unless there is good evidence that obligations are enforced for longer. Although paramilitary forces whose training, organization, equipment and control suggest they may be used to support or replace regular military forces, they are not included in the armed forces personnel. Home Guard units are counted as paramilitary.\n\nData are shown as percentage of total labor force. According to International Labour Organization (ILO armed forces occupations include all jobs held by members of the armed forces. Members of the armed forces are those personnel who are currently serving in the armed forces, including auxiliary services, whether on a voluntary or compulsory basis, and who are not free to accept civilian employment and are subject to military discipline. Included are regular members of the army, navy, air force and other military services, as well as conscripts enrolled for military training or other service for a specified period. Excluded are persons in civilian employment of government establishments concerned with defense issues; police (other than military police); customs inspectors and members of border or other armed civilian services; persons who have been temporarily withdrawn from civilian life for a short period of military training or retraining, according to national requirements, and members of military reserves not currently on active service.", "origins": [ { "producer": "International Institute for Strategic Studies (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%", "display": { "numDecimalPlaces": 1 } }, "ms_mil_xpnd_cd": { "title": "Military expenditure (current USD)", "description_from_producer": "Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, conversion, and destruction of weapons. This definition cannot be applied for all countries, however, since that would require much more detailed information than is available about what is included in military budgets and off-budget military expenditure items. (For example, military budgets might or might not cover civil defense, reserves and auxiliary forces, police and paramilitary forces, dual-purpose forces such as military and civilian police, military grants in kind, pensions for military personnel, and social security contributions paid by one part of government to another).\n\nLimitations and exceptions: Data on military expenditures are not compiled using standard definitions and are often incomplete and unreliable due to countries' reluctance to disclose military information. Even in countries where the parliament vigilantly reviews budgets and spending, military expenditures and arms transfers rarely receive close scrutiny or full, public disclosure (see Ball 1984 and Happe and Wakeman-Linn 1994). However, the Stockholm International Peace Research Institute (SIPRI) has adopted a definition of military expenditure derived from the North Atlantic Treaty Organization's (NATO) former definition (in use until 2002; see Definitions).\n\nData on military expenditures as a share of central government expenditures use data on central government expenditures from the International Monetary Fund (IMF). Therefore the data may differ from comparable data published by national governments.\n\nIn the many cases where SIPRI cannot make independent estimates, it uses the national data provided. Because of the differences in definitions and the difficulty in verifying the accuracy and completeness of data, data on military expenditures are not always comparable across countries. However, SIPRI puts a high priority on ensuring that the data series for each country is comparable over time.\n\nStatistical concept and methodology: SIPRI military expenditure data includes military and civil personnel, including retirement pensions and social services for military personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, and weapons conversion and destruction. This definition cannot be applied for all countries, however, since that would require more detailed information than is available about military budgets and off-budget military expenditures (for example, whether military budgets cover civil defense, reserves and auxiliary forces, police and paramilitary forces, and military pensions).\n\nSIPRI data for the most recent years include two types of estimate which apply to all countries: (a) figures for the most recent years are for adopted budgets, budget estimates or revised estimates, and are revised, more often than not, in subsequent years; and (b) the deflator used for the latest year in the series is an estimate.\n\nSIPRI's primary source of military expenditure data is official data provided by national governments. These data are derived from budget documents, defense white papers, and other public documents from official government agencies, including government responses to questionnaires sent by SIPRI, the UNODA, or the Organization for Security and Co-operation in Europe. Secondary sources include international statistics, such as those of NATO and the IMF's Government Finance Statistics Yearbook. Other secondary sources include country reports of the Economist Intelligence Unit, country reports by IMF staff, and specialist journals and newspapers.\n\nThe SIPRI military expenditure figures are presented on a calendar-year basis. The only exception is the USA, for which statistics report data on a fiscal-year basis. Calendar-year data are calculated on the assumption of an even rate of expenditure throughout the fiscal year.", "origins": [ { "producer": "Stockholm International Peace Research Institute (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current USD" }, "ms_mil_xpnd_cn": { "title": "Military expenditure (current LCU)", "description_from_producer": "Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, conversion, and destruction of weapons. This definition cannot be applied for all countries, however, since that would require much more detailed information than is available about what is included in military budgets and off-budget military expenditure items. (For example, military budgets might or might not cover civil defense, reserves and auxiliary forces, police and paramilitary forces, dual-purpose forces such as military and civilian police, military grants in kind, pensions for military personnel, and social security contributions paid by one part of government to another.)", "origins": [ { "producer": "Stockholm International Peace Research Institute (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ms_mil_xpnd_gd_zs": { "title": "Military expenditure (% of GDP)", "description_from_producer": "Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, conversion, and destruction of weapons. This definition cannot be applied for all countries, however, since that would require much more detailed information than is available about what is included in military budgets and off-budget military expenditure items. (For example, military budgets might or might not cover civil defense, reserves and auxiliary forces, police and paramilitary forces, dual-purpose forces such as military and civilian police, military grants in kind, pensions for military personnel, and social security contributions paid by one part of government to another.)\n\nLimitations and exceptions: Data on military expenditures are not compiled using standard definitions and are often incomplete and unreliable due to countries' reluctance to disclose military information. Even in countries where the parliament vigilantly reviews budgets and spending, military expenditures and arms transfers rarely receive close scrutiny or full, public disclosure (see Ball 1984 and Happe and Wakeman-Linn 1994). However, the Stockholm International Peace Research Institute (SIPRI) has adopted a definition of military expenditure derived from the North Atlantic Treaty Organization's (NATO) former definition (in use until 2002; see Definitions).\n\nIn the many cases where SIPRI cannot make independent estimates, it uses the national data provided. Because of the differences in definitions and the difficulty in verifying the accuracy and completeness of data, data on military expenditures are not always comparable across countries. However, SIPRI puts a high priority on ensuring that the data series for each country is comparable over time.\n\nStatistical concept and methodology: SIPRI military expenditure data includes military and civil personnel, including retirement pensions and social services for military personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, and weapons conversion and destruction. This definition cannot be applied for all countries, however, since that would require more detailed information than is available about military budgets and off-budget military expenditures (for example, whether military budgets cover civil defense, reserves and auxiliary forces, police and paramilitary forces, and military pensions).\n\nSIPRI data for the most recent years include two types of estimate which apply to all countries: (a) figures for the most recent years are for adopted budgets, budget estimates or revised estimates, and are revised, more often than not, in subsequent years; and (b) the deflator used for the latest year in the series is an estimate SIPRI's primary source of military expenditure data is official data provided by national governments. These data are derived from budget documents, defense white papers, and other public documents from official government agencies, including government responses to questionnaires sent by SIPRI, the UNODA, or the Organization for Security and Co-operation in Europe. Secondary sources include international statistics, such as those of NATO and the IMF's Government Finance Statistics Yearbook. Other secondary sources include country reports of the Economist Intelligence Unit, country reports by IMF staff, and specialist journals and newspapers.\n\nThe data on military expenditures as a share of GDP are SIPRI estimates. The SIPRI military expenditure figures are presented on a calendar-year basis. The only exception is the USA, for which statistics report data on a fiscal-year basis. Calendar-year data are calculated on the assumption of an even rate of expenditure throughout the fiscal year. The ratio of military expenditure to GDP is calculated in domestic currency at current prices and for calendar years.\n\nThe SIPRI military expenditure figures are presented on a calendar-year basis. The only exception is the USA, for which statistics report data on a fiscal-year basis. Calendar-year data are calculated on the assumption of an even rate of expenditure throughout the fiscal year.", "origins": [ { "producer": "Stockholm International Peace Research Institute (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ms_mil_xpnd_zs": { "title": "Military expenditure (% of general government expenditure)", "description_from_producer": "Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, conversion, and destruction of weapons. This definition cannot be applied for all countries, however, since that would require much more detailed information than is available about what is included in military budgets and off-budget military expenditure items. (For example, military budgets might or might not cover civil defense, reserves and auxiliary forces, police and paramilitary forces, dual-purpose forces such as military and civilian police, military grants in kind, pensions for military personnel, and social security contributions paid by one part of government to another.)\n\nLimitations and exceptions: Data on military expenditures are not compiled using standard definitions and are often incomplete and unreliable due to countries' reluctance to disclose military information. Even in countries where the parliament vigilantly reviews budgets and spending, military expenditures and arms transfers rarely receive close scrutiny or full, public disclosure (see Ball 1984 and Happe and Wakeman-Linn 1994). However, the Stockholm International Peace Research Institute (SIPRI) has adopted a definition of military expenditure derived from the North Atlantic Treaty Organization's (NATO) former definition (in use until 2002; see Definitions).\n\nData on military expenditures as a share of central government expenditures use data on central government expenditures from the International Monetary Fund (IMF). Therefore the data may differ from comparable data published by national governments.\n\nIn the many cases where SIPRI cannot make independent estimates, it uses the national data provided. Because of the differences in definitions and the difficulty in verifying the accuracy and completeness of data, data on military expenditures are not always comparable across countries. However, SIPRI puts a high priority on ensuring that the data series for each country is comparable over time.\n\nStatistical concept and methodology: SIPRI military expenditure data includes military and civil personnel, including retirement pensions and social services for military personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, and weapons conversion and destruction. This definition cannot be applied for all countries, however, since that would require more detailed information than is available about military budgets and off-budget military expenditures (for example, whether military budgets cover civil defense, reserves and auxiliary forces, police and paramilitary forces, and military pensions).\n\nSIPRI data for the most recent years include two types of estimate which apply to all countries: (a) figures for the most recent years are for adopted budgets, budget estimates or revised estimates, and are revised, more often than not, in subsequent years; and (b) the deflator used for the latest year in the series is an estimate.\n\nSIPRI's primary source of military expenditure data is official data provided by national governments. These data are derived from budget documents, defense white papers, and other public documents from official government agencies, including government responses to questionnaires sent by SIPRI, the UNODA, or the Organization for Security and Co-operation in Europe. Secondary sources include international statistics, such as those of NATO and the IMF's Government Finance Statistics Yearbook. Other secondary sources include country reports of the Economist Intelligence Unit, country reports by IMF staff, and specialist journals and newspapers.\n\nThe SIPRI military expenditure figures are presented on a calendar-year basis. The only exception is the USA, for which statistics report data on a fiscal-year basis. Calendar-year data are calculated on the assumption of an even rate of expenditure throughout the fiscal year.", "origins": [ { "producer": "Stockholm International Peace Research Institute (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of central government expenditure", "short_unit": "%" }, "ms_mil_xprt_kd": { "title": "Arms exports (SIPRI trend indicator values)", "description_from_producer": "Arms transfers cover the supply of military weapons through sales, aid, gifts, and those made through manufacturing licenses. Data cover major conventional weapons such as aircraft, armored vehicles, artillery, radar systems, missiles, and ships designed for military use. Excluded are transfers of other military equipment such as small arms and light weapons, trucks, small artillery, ammunition, support equipment, technology transfers, and other services. Figures are SIPRI Trend Indicator Values (TIVs) expressed in US$ m. A '0' indicates that the value of deliveries is less than US$0.5m\n\nLimitations and exceptions: SIPRI calculates the volume of transfers to, from and between all parties using the TIV and the number of weapon systems or subsystems delivered in a given year. This data is intended to provide a common unit to allow the measurement if trends in the flow of arms to particular countries and regions over time. Therefore, the main priority is to ensure that the TIV system remains consistent over time, and that any changes introduced are backdated.\n\nSIPRI TIV figures do not represent sales prices for arms transfers. They should therefore not be directly compared with gross domestic product (GDP), military expenditure, sales values or the financial value of export licences in an attempt to measure the economic burden of arms imports or the economic benefits of exports. They are best used as the raw data for calculating trends in international arms transfers over periods of time, global percentages for suppliers and recipients, and percentages for the volume of transfers to or from particular states.\n\nStatistical concept and methodology: Stockholm International Peace Research Institute (SIPRI)'s Arms Transfers Program collects data on arms transfers from open sources. Since publicly available information is inadequate for tracking all weapons and other military equipment, SIPRI covers only what it terms major conventional weapons. Data cover the supply of weapons through sales, aid, gifts, and manufacturing licenses; therefore the term arms transfers rather than arms trade is used. SIPRI data also cover weapons supplied to or from rebel forces in an armed conflict as well as arms deliveries for which neither the supplier nor the recipient can be identified with acceptable certainty; these data are available in SIPRI's database.\n\nData cover major conventional weapons such as aircraft, armored vehicles, artillery, radar systems and other sensors, missiles, and ships designed for military use as well as some major components such as turrets for armored vehicles and engines. Excluded are other military equipment such as most small arms and light weapons, trucks, small artillery, ammunition, support equipment, technology transfers, and other services.\n\nNotes from original source: SIPRI statistical data on arms transfers relates to actual deliveries of major conventional weapons. To permit comparison between the data on such deliveries of different weapons and to identify general trends, SIPRI has developed a unique system to measure the volume of international transfers of major conventional weapons using a common unit, the trend-indicator value (TIV).\n\nThe TIV is based on the known unit production costs of a core set of weapons and is intended to represent the transfer of military resources rather than the financial value of the transfer. Weapons for which a production cost is not known are compared with core weapons based on: size and performance characteristics (weight, speed, range and payload); type of electronics, loading or unloading arrangements, engine, tracks or wheels, armament and materials; and the year in which the weapon was produced. A weapon that has been in service in another armed force is given a value 40 per cent of that of a new weapon. A used weapon that has been significantly refurbished or modified by the supplier before delivery is given a value of 66 per cent of that of a new weapon.", "origins": [ { "producer": "Stockholm International Peace Research Institute (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "SIPRI trend indicator values" }, "ne_con_govt_cd": { "title": "General government final consumption expenditure (current US$)", "description_from_producer": "General government final consumption expenditure (formerly general government consumption) includes all government current expenditures for purchases of goods and services (including compensation of employees). It also includes most expenditures on national defense and security, but excludes government military expenditures that are part of government capital formation. Data are in current U.S. dollars.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ne_con_govt_cn": { "title": "General government final consumption expenditure (current LCU)", "description_from_producer": "General government final consumption expenditure (formerly general government consumption) includes all government current expenditures for purchases of goods and services (including compensation of employees). It also includes most expenditures on national defense and security, but excludes government military expenditures that are part of government capital formation. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ne_con_govt_kd": { "title": "General government final consumption expenditure (constant 2015 US$)", "description_from_producer": "General government final consumption expenditure (formerly general government consumption) includes all government current expenditures for purchases of goods and services (including compensation of employees). It also includes most expenditures on national defense and security, but excludes government military expenditures that are part of government capital formation. Data are in constant 2015 prices, expressed in U.S. dollars.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nMeasures of growth in consumption and capital formation are subject to two kinds of inaccuracy. The first stems from the difficulty of measuring expenditures at current price levels. The second arises in deflating current price data to measure volume growth, where results depend on the relevance and reliability of the price indexes and weights used. Measuring price changes is more difficult for investment goods than for consumption goods because of the one-time nature of many investments and because the rate of technological progress in capital goods makes capturing change in quality difficult. (An example is computers - prices have fallen as quality has improved.)\n\nTo obtain government consumption in constant prices, countries may deflate current values by applying a wage (price) index or extrapolate from the change in government employment. Neither technique captures improvements in productivity or changes in the quality of government services.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ne_con_govt_kd_zg": { "title": "General government final consumption expenditure (annual % growth)", "description_from_producer": "Annual percentage growth of general government final consumption expenditure based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. General government final consumption expenditure (general government consumption) includes all government current expenditures for purchases of goods and services (including compensation of employees). It also includes most expenditures on national defense and security, but excludes government military expenditures that are part of government capital formation.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "ne_con_govt_kn": { "title": "General government final consumption expenditure (constant LCU)", "description_from_producer": "General government final consumption expenditure (formerly general government consumption) includes all government current expenditures for purchases of goods and services (including compensation of employees). It also includes most expenditures on national defense and security, but excludes government military expenditures that are part of government capital formation. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ne_con_govt_zs": { "title": "General government final consumption expenditure (% of GDP)", "description_from_producer": "General government final consumption expenditure (formerly general government consumption) includes all government current expenditures for purchases of goods and services (including compensation of employees). It also includes most expenditures on national defense and security, but excludes government military expenditures that are part of government capital formation.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ne_con_prvt_cd": { "title": "Household and NPISHs Final consumption expenditure (current US$)", "description_from_producer": "Household and NPISHs final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. This indicator includes the expenditures of nonprofit institutions serving households even when reported separately by the country. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ne_con_prvt_cn": { "title": "Household and NPISHs Final consumption expenditure (current LCU)", "description_from_producer": "Household and NPISHs final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. This indicator includes the expenditures of nonprofit institutions serving households even when reported separately by the country. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ne_con_prvt_cn_ad": { "title": "Households and NPISHs final consumption expenditure: linked series (current LCU)", "description_from_producer": "Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. This series has been linked to produce a consistent time series to counteract breaks in series over time due to changes in base years, source data and methodologies. Thus, it may not be comparable with other national accounts series in the database for historical years. Data are in local currency, at current prices.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ne_con_prvt_kd": { "title": "Households and NPISHs Final consumption expenditure (constant 2015 US$)", "description_from_producer": "Household and NPISHs final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. This indicator includes the expenditures of nonprofit institutions serving households even when reported separately by the country. Data are in constant 2015 prices, expressed in U.S. dollars.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total. Household final consumption expenditure is often estimated as a residual, by subtracting all other known expenditures from GDP. The resulting aggregate may incorporate fairly large discrepancies. When household consumption is calculated separately, many of the estimates are based on household surveys, which tend to be one-year studies with limited coverage. Thus the estimates quickly become outdated and must be supplemented by estimates using price- and quantity-based statistical procedures. Complicating the issue, in many developing countries the distinction between cash outlays for personal business and those for household use may be blurred.\n\nInformal economic activities pose a particular measurement problem, especially in developing countries, where much economic activity is unrecorded. A complete picture of the economy requires estimating household outputs produced for home use, sales in informal markets, barter exchanges, and illicit or deliberately unreported activities. The consistency and completeness of such estimates depend on the skill and methods of the compiling statisticians.\n\nMeasures of growth in consumption and capital formation are subject to two kinds of inaccuracy. The first stems from the difficulty of measuring expenditures at current price levels. The second arises in deflating current price data to measure volume growth, where results depend on the relevance and reliability of the price indexes and weights used. Measuring price changes is more difficult for investment goods than for consumption goods because of the one-time nature of many investments and because the rate of technological progress in capital goods makes capturing change in quality difficult. (An example is computers - prices have fallen as quality has improved.)\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.\n\nDeflators for household consumption are usually calculated on the basis of the consumer price index.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ne_con_prvt_kd_zg": { "title": "Household and NPISHs Final consumption expenditure (annual % growth)", "description_from_producer": "Annual percentage growth of household and NPISHs final consumption expenditure based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Household and NPISHs final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. This indicator includes the expenditures of nonprofit institutions serving households even when reported separately by the country.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ne_con_prvt_kn": { "title": "Household and NPISHs Final consumption expenditure (constant LCU)", "description_from_producer": "Household and NPISHs final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. This indicator includes the expenditures of nonprofit institutions serving households even when reported separately by the country. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ne_con_prvt_pc_kd": { "title": "Households and NPISHs final consumption expenditure per capita (constant 2015 US$)", "description_from_producer": "Household final consumption expenditure per capita (private consumption per capita) is calculated using private consumption in constant 2015 prices and World Bank population estimates. Household final consumption expenditure is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. Data are in constant 2015 U.S. dollars.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total. Household final consumption expenditure is often estimated as a residual, by subtracting all other known expenditures from GDP. The resulting aggregate may incorporate fairly large discrepancies. When household consumption is calculated separately, many of the estimates are based on household surveys, which tend to be one-year studies with limited coverage. Thus the estimates quickly become outdated and must be supplemented by estimates using price- and quantity-based statistical procedures. Complicating the issue, in many developing countries the distinction between cash outlays for personal business and those for household use may be blurred.\n\nInformal economic activities pose a particular measurement problem, especially in developing countries, where much economic activity is unrecorded. A complete picture of the economy requires estimating household outputs produced for home use, sales in informal markets, barter exchanges, and illicit or deliberately unreported activities. The consistency and completeness of such estimates depend on the skill and methods of the compiling statisticians.\n\nMeasures of growth in consumption and capital formation are subject to two kinds of inaccuracy. The first stems from the difficulty of measuring expenditures at current price levels. The second arises in deflating current price data to measure volume growth, where results depend on the relevance and reliability of the price indexes and weights used. Measuring price changes is more difficult for investment goods than for consumption goods because of the one-time nature of many investments and because the rate of technological progress in capital goods makes capturing change in quality difficult. (An example is computers - prices have fallen as quality has improved.)\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.\n\nDeflators for household consumption are usually calculated on the basis of the consumer price index.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ne_con_prvt_pc_kd_zg": { "title": "Household final consumption expenditure per capita growth (annual %)", "description_from_producer": "Annual percentage growth of household final consumption expenditure per capita, which is calculated using household final consumption expenditure in constant 2010 prices and World Bank population estimates. Household final consumption expenditure (private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "ne_con_prvt_pp_cd": { "title": "Households and NPISHs Final consumption expenditure, PPP (current international $)", "description_from_producer": "This indicator provides values for households and NPISHs final consumption expenditure expressed in current international dollars converted by purchasing power parity (PPP) conversion factor.\n\nHousehold final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country.\n\nPPP conversion factor is a spatial price deflator and currency converter that eliminates the effects of the differences in price levels between countries.\n\nFrom July 2020, \u201cHouseholds and NPISHs final consumption expenditure: linked series (current LCU)\u201d [NE.CON.PRVT.CN.AD] is used as underlying expenditure in local currency unit so that it\u2019s in line with time series of PPP conversion factor, private consumption (LCU per international $), which are extrapolated with linked CPI.\n\nStatistical concept and methodology: Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.\n\nFor more information on underlying households and NPISHs final consumption expenditure in local currency, please refer to the metadata for \"Households and NPISHs Final consumption expenditure, PPP (current international $)\" [NE.CON.PRVT.PP.CD]. For more information on underlying PPP conversion factor, please refer to the metadata for \"PPP conversion factor, private consumption (LCU per international $)\" [PA.NUS.PRVT.PP].\n\nFor the concept and methodology of PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$" }, "ne_con_prvt_pp_kd": { "title": "Households and NPISHs Final consumption expenditure, PPP (constant 2017 international $)", "description_from_producer": "Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. Data are converted to constant 2017 international dollars using purchasing power parity rates.\n\nStatistical concept and methodology: For the concept and methodology of 2017 PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ne_con_prvt_zs": { "title": "Households and NPISHs final consumption expenditure (% of GDP)", "description_from_producer": "Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. This item also includes any statistical discrepancy in the use of resources relative to the supply of resources.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total. Household final consumption expenditure is often estimated as a residual, by subtracting all other known expenditures from GDP. The resulting aggregate may incorporate fairly large discrepancies. When household consumption is calculated separately, many of the estimates are based on household surveys, which tend to be one-year studies with limited coverage. Thus the estimates quickly become outdated and must be supplemented by estimates using price- and quantity-based statistical procedures. Complicating the issue, in many developing countries the distinction between cash outlays for personal business and those for household use may be blurred.\n\nInformal economic activities pose a particular measurement problem, especially in developing countries, where much economic activity is unrecorded. A complete picture of the economy requires estimating household outputs produced for home use, sales in informal markets, barter exchanges, and illicit or deliberately unreported activities. The consistency and completeness of such estimates depend on the skill and methods of the compiling statisticians.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ne_con_totl_cd": { "title": "Final consumption expenditure (current US$)", "description_from_producer": "Final consumption expenditure (formerly total consumption) is the sum of household final consumption expenditure (private consumption) and general government final consumption expenditure (general government consumption). Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ne_con_totl_cn": { "title": "Final consumption expenditure (current LCU)", "description_from_producer": "Final consumption expenditure (formerly total consumption) is the sum of household final consumption expenditure (private consumption) and general government final consumption expenditure (general government consumption). Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ne_con_totl_kd": { "title": "Final consumption expenditure (constant 2015 US$)", "description_from_producer": "Final consumption expenditure (formerly total consumption) is the sum of household final consumption expenditure (formerly private consumption) and general government final consumption expenditure (formerly general government consumption). Data are in constant 2015 prices, expressed in U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ne_con_totl_kd_zg": { "title": "Final consumption expenditure (annual % growth)", "description_from_producer": "Average annual growth of final consumption expenditure based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Final consumption expenditure (formerly total consumption) is the sum of household final consumption expenditure (formerly private consumption) and general government final consumption expenditure (formerly general government consumption). This estimate includes any statistical discrepancy in the use of resources relative to the supply of resources.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "ne_con_totl_kn": { "title": "Final consumption expenditure (constant LCU)", "description_from_producer": "Final consumption expenditure (formerly total consumption) is the sum of household final consumption expenditure (formerly private consumption) and general government final consumption expenditure (formerly general government consumption). Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ne_con_totl_zs": { "title": "Final consumption expenditure (% of GDP)", "description_from_producer": "Final consumption expenditure (formerly total consumption) is the sum of household final consumption expenditure (private consumption) and general government final consumption expenditure (general government consumption). This estimate includes any statistical discrepancy in the use of resources relative to the supply of resources.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ne_dab_defl_zs": { "title": "Gross national expenditure deflator (base year varies by country)", "description_from_producer": "Gross national expenditure (formerly domestic absorption) is the sum of household final consumption expenditure (formerly private consumption), general government final consumption expenditure (formerly general government consumption), and gross capital formation (formerly gross domestic investment).", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "base year varies by country" }, "ne_dab_totl_cd": { "title": "Gross national expenditure (current US$)", "description_from_producer": "Gross national expenditure (formerly domestic absorption) is the sum of household final consumption expenditure (formerly private consumption), general government final consumption expenditure (formerly general government consumption), and gross capital formation (formerly gross domestic investment). Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ne_dab_totl_cn": { "title": "Gross national expenditure (current LCU)", "description_from_producer": "Gross national expenditure (formerly domestic absorption) is the sum of household final consumption expenditure (formerly private consumption), general government final consumption expenditure (formerly general government consumption), and gross capital formation (formerly gross domestic investment). Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ne_dab_totl_kd": { "title": "Gross national expenditure (constant 2015 US$)", "description_from_producer": "Gross national expenditure (formerly domestic absorption) is the sum of household final consumption expenditure (formerly private consumption), general government final consumption expenditure (formerly general government consumption), and gross capital formation (formerly gross domestic investment). Data are in constant 2015 prices, expressed in U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ne_dab_totl_kn": { "title": "Gross national expenditure (constant LCU)", "description_from_producer": "Gross national expenditure (formerly domestic absorption) is the sum of household final consumption expenditure (formerly private consumption), general government final consumption expenditure (formerly general government consumption), and gross capital formation (formerly gross domestic investment). Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ne_dab_totl_zs": { "title": "Gross national expenditure (% of GDP)", "description_from_producer": "Gross national expenditure (formerly domestic absorption) is the sum of household final consumption expenditure (formerly private consumption), general government final consumption expenditure (formerly general government consumption), and gross capital formation (formerly gross domestic investment).", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ne_exp_gnfs_cd": { "title": "Exports of goods and services (current US$)", "description_from_producer": "Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments. Data are in current U.S. dollars.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nData on exports and imports are compiled from customs reports and balance of payments data. Although the data from the payments side provide reasonably reliable records of cross-border transactions, they may not adhere strictly to the appropriate definitions of valuation and timing used in the balance of payments or corresponds to the change-of ownership criterion. This issue has assumed greater significance with the increasing globalization of international business. Neither customs nor balance of payments data usually capture the illegal transactions that occur in many countries. Goods carried by travelers across borders in legal but unreported shuttle trade may further distort trade statistics.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ne_exp_gnfs_cn": { "title": "Exports of goods and services (current LCU)", "description_from_producer": "Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ne_exp_gnfs_kd": { "title": "Exports of goods and services (constant 2015 US$)", "description_from_producer": "Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments. Data are in constant 2015 prices, expressed in U.S. dollars.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nData on exports and imports are compiled from customs reports and balance of payments data. Although the data from the payments side provide reasonably reliable records of cross-border transactions, they may not adhere strictly to the appropriate definitions of valuation and timing used in the balance of payments or corresponds to the change-of ownership criterion. This issue has assumed greater significance with the increasing globalization of international business. Neither customs nor balance of payments data usually capture the illegal transactions that occur in many countries. Goods carried by travelers across borders in legal but unreported shuttle trade may further distort trade statistics.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ne_exp_gnfs_kd_zg": { "title": "Exports of goods and services (annual % growth)", "description_from_producer": "Annual growth rate of exports of goods and services based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "ne_exp_gnfs_kn": { "title": "Exports of goods and services (constant LCU)", "description_from_producer": "Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ne_exp_gnfs_zs": { "title": "Exports of goods and services (% of GDP)", "description_from_producer": "Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nData on exports and imports are compiled from customs reports and balance of payments data. Although the data from the payments side provide reasonably reliable records of cross-border transactions, they may not adhere strictly to the appropriate definitions of valuation and timing used in the balance of payments or corresponds to the change-of ownership criterion. This issue has assumed greater significance with the increasing globalization of international business. Neither customs nor balance of payments data usually capture the illegal transactions that occur in many countries. Goods carried by travelers across borders in legal but unreported shuttle trade may further distort trade statistics.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ne_gdi_fprv_cn": { "title": "Gross fixed capital formation, private sector (current LCU)", "description_from_producer": "Private investment covers gross outlays by the private sector (including private nonprofit agencies) on additions to its fixed domestic assets.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ne_gdi_fprv_zs": { "title": "Gross fixed capital formation, private sector (% of GDP)", "description_from_producer": "Private investment covers gross outlays by the private sector (including private nonprofit agencies) on additions to its fixed domestic assets.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ne_gdi_ftot_cd": { "title": "Gross fixed capital formation (current US$)", "description_from_producer": "Gross fixed capital formation (formerly gross domestic fixed investment) includes land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. According to the 1993 SNA, net acquisitions of valuables are also considered capital formation. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ne_gdi_ftot_cn": { "title": "Gross fixed capital formation (current LCU)", "description_from_producer": "Gross fixed capital formation (formerly gross domestic fixed investment) includes land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. According to the 1993 SNA, net acquisitions of valuables are also considered capital formation. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ne_gdi_ftot_kd": { "title": "Gross fixed capital formation (constant 2015 US$)", "description_from_producer": "Gross fixed capital formation (formerly gross domestic fixed investment) includes land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. According to the 2008 SNA, net acquisitions of valuables are also considered capital formation. Data are in constant 2015 prices, expressed in U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ne_gdi_ftot_kd_zg": { "title": "Gross fixed capital formation (annual % growth)", "description_from_producer": "Average annual growth of gross fixed capital formation based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Gross fixed capital formation (formerly gross domestic fixed investment) includes land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. According to the 2008 SNA, net acquisitions of valuables are also considered capital formation.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "ne_gdi_ftot_kn": { "title": "Gross fixed capital formation (constant LCU)", "description_from_producer": "Gross fixed capital formation (formerly gross domestic fixed investment) includes land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. According to the 1993 SNA, net acquisitions of valuables are also considered capital formation. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ne_gdi_ftot_zs": { "title": "Gross fixed capital formation (% of GDP)", "description_from_producer": "Gross fixed capital formation (formerly gross domestic fixed investment) includes land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. According to the 1993 SNA, net acquisitions of valuables are also considered capital formation.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ne_gdi_stkb_cd": { "title": "Changes in inventories (current US$)", "description_from_producer": "Inventories are stocks of goods held by firms to meet temporary or unexpected fluctuations in production or sales, and \"work in progress.\" Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ne_gdi_stkb_cn": { "title": "Changes in inventories (current LCU)", "description_from_producer": "Inventories are stocks of goods held by firms to meet temporary or unexpected fluctuations in production or sales, and \"work in progress.\" Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ne_gdi_stkb_kn": { "title": "Changes in inventories (constant LCU)", "description_from_producer": "Inventories are stocks of goods held by firms to meet temporary or unexpected fluctuations in production or sales, and \"work in progress.\" Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ne_gdi_totl_cd": { "title": "Gross capital formation (current US$)", "description_from_producer": "Gross capital formation (formerly gross domestic investment) consists of outlays on additions to the fixed assets of the economy plus net changes in the level of inventories. Fixed assets include land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. Inventories are stocks of goods held by firms to meet temporary or unexpected fluctuations in production or sales, and \"work in progress.\" According to the 1993 SNA, net acquisitions of valuables are also considered capital formation. Data are in current U.S. dollars.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nData on capital formation may be estimated from direct surveys of enterprises and administrative records or based on the commodity flow method using data from production, trade, and construction activities. The quality of data on government fixed capital formation depends on the quality of government accounting systems (which tend to be weak in developing countries). Measures of fixed capital formation by households and corporations - particularly capital outlays by small, unincorporated enterprises - are usually unreliable.\n\nEstimates of changes in inventories are rarely complete but usually include the most important activities or commodities. In some countries these estimates are derived as a composite residual along with household final consumption expenditure. According to national accounts conventions, adjustments should be made for appreciation of the value of inventory holdings due to price changes, but this is not always done. In highly inflationary economies this element can be substantial.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ne_gdi_totl_cn": { "title": "Gross capital formation (current LCU)", "description_from_producer": "Gross capital formation (formerly gross domestic investment) consists of outlays on additions to the fixed assets of the economy plus net changes in the level of inventories. Fixed assets include land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. Inventories are stocks of goods held by firms to meet temporary or unexpected fluctuations in production or sales, and \"work in progress.\" According to the 1993 SNA, net acquisitions of valuables are also considered capital formation. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ne_gdi_totl_kd": { "title": "Gross capital formation (constant 2015 US$)", "description_from_producer": "Gross capital formation (formerly gross domestic investment) consists of outlays on additions to the fixed assets of the economy plus net changes in the level of inventories. Fixed assets include land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. Inventories are stocks of goods held by firms to meet temporary or unexpected fluctuations in production or sales, and \"work in progress.\" According to the 2008 SNA, net acquisitions of valuables are also considered capital formation. Data are in constant 2015 prices, expressed in U.S. dollars.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nData on capital formation may be estimated from direct surveys of enterprises and administrative records or based on the commodity flow method using data from production, trade, and construction activities. The quality of data on government fixed capital formation depends on the quality of government accounting systems (which tend to be weak in developing countries). Measures of fixed capital formation by households and corporations - particularly capital outlays by small, unincorporated enterprises - are usually unreliable.\n\nEstimates of changes in inventories are rarely complete but usually include the most important activities or commodities. In some countries these estimates are derived as a composite residual along with household final consumption expenditure. According to national accounts conventions, adjustments should be made for appreciation of the value of inventory holdings due to price changes, but this is not always done. In highly inflationary economies this element can be substantial.\n\nMeasures of growth in consumption and capital formation are subject to two kinds of inaccuracy. The first stems from the difficulty of measuring expenditures at current price levels. The second arises in deflating current price data to measure volume growth, where results depend on the relevance and reliability of the price indexes and weights used. Measuring price changes is more difficult for investment goods than for consumption goods because of the one-time nature of many investments and because the rate of technological progress in capital goods makes capturing change in quality difficult. (An example is computers - prices have fallen as quality has improved.) Several countries estimate capital formation from the supply side, identifying capital goods entering an economy directly from detailed production and international trade statistics. This means that the price indexes used in deflating production and international trade, reflecting delivered or offered prices, will determine the deflator for capital formation expenditures on the demand side.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ne_gdi_totl_kd_zg": { "title": "Gross capital formation (annual % growth)", "description_from_producer": "Annual growth rate of gross capital formation based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Gross capital formation (formerly gross domestic investment) consists of outlays on additions to the fixed assets of the economy plus net changes in the level of inventories. Fixed assets include land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. Inventories are stocks of goods held by firms to meet temporary or unexpected fluctuations in production or sales, and \"work in progress.\" According to the 2008 SNA, net acquisitions of valuables are also considered capital formation.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "ne_gdi_totl_kn": { "title": "Gross capital formation (constant LCU)", "description_from_producer": "Gross capital formation (formerly gross domestic investment) consists of outlays on additions to the fixed assets of the economy plus net changes in the level of inventories. Fixed assets include land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. Inventories are stocks of goods held by firms to meet temporary or unexpected fluctuations in production or sales, and \"work in progress.\" According to the 1993 SNA, net acquisitions of valuables are also considered capital formation. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ne_gdi_totl_zs": { "title": "Gross capital formation (% of GDP)", "description_from_producer": "Gross capital formation (formerly gross domestic investment) consists of outlays on additions to the fixed assets of the economy plus net changes in the level of inventories. Fixed assets include land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. Inventories are stocks of goods held by firms to meet temporary or unexpected fluctuations in production or sales, and \"work in progress.\" According to the 1993 SNA, net acquisitions of valuables are also considered capital formation.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nData on capital formation may be estimated from direct surveys of enterprises and administrative records or based on the commodity flow method using data from production, trade, and construction activities. The quality of data on government fixed capital formation depends on the quality of government accounting systems (which tend to be weak in developing countries). Measures of fixed capital formation by households and corporations - particularly capital outlays by small, unincorporated enterprises - are usually unreliable.\n\nEstimates of changes in inventories are rarely complete but usually include the most important activities or commodities. In some countries these estimates are derived as a composite residual along with household final consumption expenditure. According to national accounts conventions, adjustments should be made for appreciation of the value of inventory holdings due to price changes, but this is not always done. In highly inflationary economies this element can be substantial.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ne_imp_gnfs_cd": { "title": "Imports of goods and services (current US$)", "description_from_producer": "Imports of goods and services represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments. Data are in current U.S. dollars.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nData on exports and imports are compiled from customs reports and balance of payments data. Although the data from the payments side provide reasonably reliable records of cross-border transactions, they may not adhere strictly to the appropriate definitions of valuation and timing used in the balance of payments or corresponds to the change-of ownership criterion. This issue has assumed greater significance with the increasing globalization of international business. Neither customs nor balance of payments data usually capture the illegal transactions that occur in many countries. Goods carried by travelers across borders in legal but unreported shuttle trade may further distort trade statistics.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ne_imp_gnfs_cn": { "title": "Imports of goods and services (current LCU)", "description_from_producer": "Imports of goods and services represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ne_imp_gnfs_kd": { "title": "Imports of goods and services (constant 2015 US$)", "description_from_producer": "Imports of goods and services represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments. Data are in constant 2015 prices, expressed in U.S. dollars.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nData on exports and imports are compiled from customs reports and balance of payments data. Although the data from the payments side provide reasonably reliable records of cross-border transactions, they may not adhere strictly to the appropriate definitions of valuation and timing used in the balance of payments or corresponds to the change-of ownership criterion. This issue has assumed greater significance with the increasing globalization of international business. Neither customs nor balance of payments data usually capture the illegal transactions that occur in many countries. Goods carried by travelers across borders in legal but unreported shuttle trade may further distort trade statistics.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ne_imp_gnfs_kd_zg": { "title": "Imports of goods and services (annual % growth)", "description_from_producer": "Annual growth rate of imports of goods and services based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Imports of goods and services represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "ne_imp_gnfs_kn": { "title": "Imports of goods and services (constant LCU)", "description_from_producer": "Imports of goods and services represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ne_imp_gnfs_zs": { "title": "Imports of goods and services (% of GDP)", "description_from_producer": "Imports of goods and services represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments.\n\nLimitations and exceptions: Because policymakers have tended to focus on fostering the growth of output, and because data on production are easier to collect than data on spending, many countries generate their primary estimate of GDP using the production approach. Moreover, many countries do not estimate all the components of national expenditures but instead derive some of the main aggregates indirectly using GDP (based on the production approach) as the control total.\n\nData on exports and imports are compiled from customs reports and balance of payments data. Although the data from the payments side provide reasonably reliable records of cross-border transactions, they may not adhere strictly to the appropriate definitions of valuation and timing used in the balance of payments or corresponds to the change-of ownership criterion. This issue has assumed greater significance with the increasing globalization of international business. Neither customs nor balance of payments data usually capture the illegal transactions that occur in many countries. Goods carried by travelers across borders in legal but unreported shuttle trade may further distort trade statistics.\n\nStatistical concept and methodology: Gross domestic product (GDP) from the expenditure side is made up of household final consumption expenditure, general government final consumption expenditure, gross capital formation (private and public investment in fixed assets, changes in inventories, and net acquisitions of valuables), and net exports (exports minus imports) of goods and services. Such expenditures are recorded in purchaser prices and include net taxes on products.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ne_rsb_gnfs_cd": { "title": "External balance on goods and services (current US$)", "description_from_producer": "External balance on goods and services (formerly resource balance) equals exports of goods and services minus imports of goods and services (previously nonfactor services). Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ne_rsb_gnfs_cn": { "title": "External balance on goods and services (current LCU)", "description_from_producer": "External balance on goods and services (formerly resource balance) equals exports of goods and services minus imports of goods and services (previously nonfactor services). Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ne_rsb_gnfs_kn": { "title": "External balance on goods and services (constant LCU)", "description_from_producer": "External balance on goods and services (formerly resource balance) equals exports of goods and services minus imports of goods and services (previously nonfactor services). Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ne_rsb_gnfs_zs": { "title": "External balance on goods and services (% of GDP)", "description_from_producer": "External balance on goods and services (formerly resource balance) equals exports of goods and services minus imports of goods and services (previously nonfactor services).", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ne_trd_gnfs_zs": { "title": "Trade (% of GDP)", "description_from_producer": "Trade is the sum of exports and imports of goods and services measured as a share of gross domestic product.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "nv_agr_empl_kd": { "title": "Agriculture, forestry, and fishing, value added per worker (constant 2015 US$)", "description_from_producer": "Value added per worker is a measure of labor productivity\u2014value added per unit of input. Value added denotes the net output of a sector after adding up all outputs and subtracting intermediate inputs. Data are in constant 2015 U.S. dollars. Agriculture corresponds to the International Standard Industrial Classification (ISIC) tabulation categories A and B (revision 3) or tabulation category A (revision 4), and includes forestry, hunting, and fishing as well as cultivation of crops and livestock production.\n\nLimitations and exceptions: For comparability of individual sectors labor productivity is estimated according to national accounts conventions. However, there are still significant limitations on the availability of reliable data. Information on consistent series of output is not easily available, especially in low- and middle-income countries, because the definition, coverage, and methodology are not always consistent across countries. For more details, see Agriculture, forestry, and fishing, value added (constant 2015 US$) [NV.AGR.TOTL.KD], Industry (including construction), value added (constant 2015 US$) [NV.IND.TOTL.KD], and Services, value added (constant 2015 US$) [NV.SRV.TOTL.KD].\n\nStatistical concept and methodology: Value added per worker is calculated by dividing value added of a sector by the number employed in the sector.\nGross domestic product (GDP) represents the sum of value added by all producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Value added by industry is normally measured at basic prices, while total GDP is measured at purchaser prices.\nData on employment are modeled estimates by the International Labour Organization (ILO) ILOSTAT database. The concept of employment generally refers to people above a certain age who worked, or who held a job, during a reference period. Employment data include both full-time and part-time workers.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "nv_agr_totl_cd": { "title": "Agriculture, forestry, and fishing, value added (current US$)", "description_from_producer": "Agriculture, forestry, and fishing corresponds to ISIC divisions 1-3 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Data are in current U.S. dollars.\n\nLimitations and exceptions: Among the difficulties faced by compilers of national accounts is the extent of unreported economic activity in the informal or secondary economy. In developing countries a large share of agricultural output is either not exchanged (because it is consumed within the household) or not exchanged for money. Agricultural production often must be estimated indirectly, using a combination of methods involving estimates of inputs, yields, and area under cultivation. This approach sometimes leads to crude approximations that can differ from the true values over time and across crops for reasons other than climate conditions or farming techniques. Similarly, agricultural inputs that cannot easily be allocated to specific outputs are frequently \"netted out\" using equally crude and ad hoc approximations.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "nv_agr_totl_cn": { "title": "Agriculture, forestry, and fishing, value added (current LCU)", "description_from_producer": "Agriculture, forestry, and fishing corresponds to ISIC divisions 1-3 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "nv_agr_totl_kd": { "title": "Agriculture, forestry, and fishing, value added (constant 2015 US$)", "description_from_producer": "Agriculture, forestry, and fishing corresponds to ISIC divisions 01-03 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Data are in constant 2015 prices, expressed in U.S. dollars.\n\nLimitations and exceptions: Among the difficulties faced by compilers of national accounts is the extent of unreported economic activity in the informal or secondary economy. In developing countries a large share of agricultural output is either not exchanged (because it is consumed within the household) or not exchanged for money. Agricultural production often must be estimated indirectly, using a combination of methods involving estimates of inputs, yields, and area under cultivation. This approach sometimes leads to crude approximations that can differ from the true values over time and across crops for reasons other than climate conditions or farming techniques. Similarly, agricultural inputs that cannot easily be allocated to specific outputs are frequently \"netted out\" using equally crude and ad hoc approximations.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "nv_agr_totl_kd_zg": { "title": "Agriculture, forestry, and fishing, value added (annual % growth)", "description_from_producer": "Annual growth rate for agricultural, forestry, and fishing value added based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Agriculture corresponds to ISIC divisions 01-03 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4.\n\nLimitations and exceptions: Among the difficulties faced by compilers of national accounts is the extent of unreported economic activity in the informal or secondary economy. In developing countries a large share of agricultural output is either not exchanged (because it is consumed within the household) or not exchanged for money. Agricultural production often must be estimated indirectly, using a combination of methods involving estimates of inputs, yields, and area under cultivation. This approach sometimes leads to crude approximations that can differ from the true values over time and across crops for reasons other than climate conditions or farming techniques. Similarly, agricultural inputs that cannot easily be allocated to specific outputs are frequently \"netted out\" using equally crude and ad hoc approximations.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "nv_agr_totl_kn": { "title": "Agriculture, forestry, and fishing, value added (constant LCU)", "description_from_producer": "Agriculture, forestry, and fishing corresponds to ISIC divisions 1-3 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "nv_agr_totl_zs": { "title": "Agriculture, forestry, and fishing, value added (% of GDP)", "description_from_producer": "Agriculture, forestry, and fishing corresponds to ISIC divisions 1-3 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Note: For VAB countries, gross value added at factor cost is used as the denominator.\n\nLimitations and exceptions: Among the difficulties faced by compilers of national accounts is the extent of unreported economic activity in the informal or secondary economy. In developing countries a large share of agricultural output is either not exchanged (because it is consumed within the household) or not exchanged for money. Agricultural production often must be estimated indirectly, using a combination of methods involving estimates of inputs, yields, and area under cultivation. This approach sometimes leads to crude approximations that can differ from the true values over time and across crops for reasons other than climate conditions or farming techniques. Similarly, agricultural inputs that cannot easily be allocated to specific outputs are frequently \"netted out\" using equally crude and ad hoc approximations.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "nv_fsm_totl_cn": { "title": "Financial intermediary services indirectly Measured (FISIM) (current LCU)", "description_from_producer": "Financial intermediation services indirectly measured (FISIM) is an indirect measure of the value of financial intermediation services (i.e. output) provided but for which financial institutions do not charge explicitly as compared to explicit bank charges. Although the 1993 SNA recommends that the FISIM are allocated as intermediate and final consumption to the users, many countries still make a global (negative) adjustment to the sum of gross value added.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "nv_fsm_totl_kn": { "title": "Financial intermediary services indirectly Measured (FISIM) (constant LCU)", "description_from_producer": "Financial intermediation services indirectly measured (FISIM) is an indirect measure of the value of financial intermediation services (i.e. output) provided but for which financial institutions do not charge explicitly as compared to explicit bank charges. Although the 1993 SNA recommends that the FISIM are allocated as intermediate and final consumption to the users, many countries still make a global (negative) adjustment to the sum of gross value added.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "nv_ind_empl_kd": { "title": "Industry (including construction), value added per worker (constant 2015 US$)", "description_from_producer": "Value added per worker is a measure of labor productivity\u2014value added per unit of input. Value added denotes the net output of a sector after adding up all outputs and subtracting intermediate inputs. Data are in constant 2015 U.S. dollars. Industry corresponds to the International Standard Industrial Classification (ISIC) tabulation categories C-F (revision 3) or tabulation categories B-F (revision 4), and includes mining and quarrying (including oil production), manufacturing, construction, and public utilities (electricity, gas, and water).\n\nLimitations and exceptions: For comparability of individual sectors labor productivity is estimated according to national accounts conventions. However, there are still significant limitations on the availability of reliable data. Information on consistent series of output is not easily available, especially in low- and middle-income countries, because the definition, coverage, and methodology are not always consistent across countries. For more details, see Agriculture, forestry, and fishing, value added (constant 2015 US$) [NV.AGR.TOTL.KD], Industry (including construction), value added (constant 2015 US$) [NV.IND.TOTL.KD], and Services, value added (constant 2015 US$) [NV.SRV.TOTL.KD].\n\nStatistical concept and methodology: Value added per worker is calculated by dividing value added of a sector by the number employed in the sector.\nGross domestic product (GDP) represents the sum of value added by all producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Value added by industry is normally measured at basic prices, while total GDP is measured at purchaser prices.\nData on employment are modeled estimates by the International Labour Organization (ILO) ILOSTAT database. The concept of employment generally refers to people above a certain age who worked, or who held a job, during a reference period. Employment data include both full-time and part-time workers.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "nv_ind_manf_cd": { "title": "Manufacturing, value added (current US$)", "description_from_producer": "Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current U.S. dollars.\n\nLimitations and exceptions: In establishing classifications systems compilers must define both the types of activities to be described and the units whose activities are to be reported. There are many possibilities, and the choices affect how the statistics can be interpreted and how useful they are in analyzing economic behavior. The ISIC emphasizes commonalities in the production process and is explicitly not intended to measure outputs (for which there is a newly developed Central Product Classification). Nevertheless, the ISIC views an activity as defined by \"a process resulting in a homogeneous set of products.\"\n\nStatistical concept and methodology: The data on manufacturing value added in U.S. dollars are from the World Bank's national accounts files and may differ from those UNIDO uses to calculate shares of value added by industry, in part because of differences in exchange rates. Thus value added in a particular industry estimated by applying the shares to total manufacturing value added will not match those from UNIDO sources. Classification of manufacturing industries accords with the United Nations International Standard Industrial Classification (ISIC) revision 3.\n\nData prior to 2008 used revision 2, first published in 1948. Revision 3 was completed in 1989, and many countries now use it. But revision 2 is still widely used for compiling cross-country data. UNIDO has converted these data to accord with revision 3. Concordances matching ISIC categories to national classification systems and to related systems such as the Standard International Trade Classification are available.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "nv_ind_manf_cn": { "title": "Manufacturing, value added (current LCU)", "description_from_producer": "Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "nv_ind_manf_kd": { "title": "Manufacturing, value added (constant 2015 US$)", "description_from_producer": "Manufacturing refers to industries belonging to ISIC divisions 10-33. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Data are in constant 2015 prices, expressed in U.S. dollars.\n\nLimitations and exceptions: Ideally, industrial output should be measured through regular censuses and surveys of firms. But in most developing countries such surveys are infrequent, so earlier survey results must be extrapolated using an appropriate indicator. The choice of sampling unit, which may be the enterprise (where responses may be based on financial records) or the establishment (where production units may be recorded separately), also affects the quality of the data. Moreover, much industrial production is organized in unincorporated or owner-operated ventures that are not captured by surveys aimed at the formal sector. Even in large industries, where regular surveys are more likely, evasion of excise and other taxes and nondisclosure of income lower the estimates of value added. Such problems become more acute as countries move from state control of industry to private enterprise, because new firms and growing numbers of established firms fail to report. In accordance with the System of National Accounts, output should include all such unreported activity as well as the value of illegal activities and other unrecorded, informal, or small-scale operations. Data on these activities need to be collected using techniques other than conventional surveys of firms.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "nv_ind_manf_kd_zg": { "title": "Manufacturing, value added (annual % growth)", "description_from_producer": "Annual growth rate for manufacturing value added based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Manufacturing refers to industries belonging to ISIC divisions 10-33. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4.\n\nLimitations and exceptions: Ideally, industrial output should be measured through regular censuses and surveys of firms. But in most developing countries such surveys are infrequent, so earlier survey results must be extrapolated using an appropriate indicator. The choice of sampling unit, which may be the enterprise (where responses may be based on financial records) or the establishment (where production units may be recorded separately), also affects the quality of the data. Moreover, much industrial production is organized in unincorporated or owner-operated ventures that are not captured by surveys aimed at the formal sector. Even in large industries, where regular surveys are more likely, evasion of excise and other taxes and nondisclosure of income lower the estimates of value added. Such problems become more acute as countries move from state control of industry to private enterprise, because new firms and growing numbers of established firms fail to report. In accordance with the System of National Accounts, output should include all such unreported activity as well as the value of illegal activities and other unrecorded, informal, or small-scale operations. Data on these activities need to be collected using techniques other than conventional surveys of firms.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "nv_ind_manf_kn": { "title": "Manufacturing, value added (constant LCU)", "description_from_producer": "Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "nv_ind_manf_zs": { "title": "Manufacturing, value added (% of GDP)", "description_from_producer": "Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Note: For VAB countries, gross value added at factor cost is used as the denominator.\n\nLimitations and exceptions: Ideally, industrial output should be measured through regular censuses and surveys of firms. But in most developing countries such surveys are infrequent, so earlier survey results must be extrapolated using an appropriate indicator. The choice of sampling unit, which may be the enterprise (where responses may be based on financial records) or the establishment (where production units may be recorded separately), also affects the quality of the data. Moreover, much industrial production is organized in unincorporated or owner-operated ventures that are not captured by surveys aimed at the formal sector. Even in large industries, where regular surveys are more likely, evasion of excise and other taxes and nondisclosure of income lower the estimates of value added. Such problems become more acute as countries move from state control of industry to private enterprise, because new firms and growing numbers of established firms fail to report. In accordance with the System of National Accounts, output should include all such unreported activity as well as the value of illegal activities and other unrecorded, informal, or small-scale operations. Data on these activities need to be collected using techniques other than conventional surveys of firms.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "nv_ind_totl_cd": { "title": "Industry (including construction), value added (current US$)", "description_from_producer": "Industry (including construction) corresponds to ISIC divisions 05-43 and includes manufacturing (ISIC divisions 10-33). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Data are in current U.S. dollars.\n\nLimitations and exceptions: Ideally, industrial output should be measured through regular censuses and surveys of firms. But in most developing countries such surveys are infrequent, so earlier survey results must be extrapolated using an appropriate indicator. The choice of sampling unit, which may be the enterprise (where responses may be based on financial records) or the establishment (where production units may be recorded separately), also affects the quality of the data. Moreover, much industrial production is organized in unincorporated or owner-operated ventures that are not captured by surveys aimed at the formal sector. Even in large industries, where regular surveys are more likely, evasion of excise and other taxes and nondisclosure of income lower the estimates of value added. Such problems become more acute as countries move from state control of industry to private enterprise, because new firms and growing numbers of established firms fail to report. In accordance with the System of National Accounts, output should include all such unreported activity as well as the value of illegal activities and other unrecorded, informal, or small-scale operations. Data on these activities need to be collected using techniques other than conventional surveys of firms.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "nv_ind_totl_cn": { "title": "Industry (including construction), value added (current LCU)", "description_from_producer": "Industry (including construction) corresponds to ISIC divisions 05-43 and includes manufacturing (ISIC divisions 10-33). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "nv_ind_totl_kd": { "title": "Industry (including construction), value added (constant 2015 US$)", "description_from_producer": "Industry (including construction) corresponds to ISIC divisions 05-43 and includes manufacturing (ISIC divisions 10-33). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Data are in constant 2015 prices, expressed in U.S. dollars.\n\nLimitations and exceptions: Ideally, industrial output should be measured through regular censuses and surveys of firms. But in most developing countries such surveys are infrequent, so earlier survey results must be extrapolated using an appropriate indicator. The choice of sampling unit, which may be the enterprise (where responses may be based on financial records) or the establishment (where production units may be recorded separately), also affects the quality of the data. Moreover, much industrial production is organized in unincorporated or owner-operated ventures that are not captured by surveys aimed at the formal sector. Even in large industries, where regular surveys are more likely, evasion of excise and other taxes and nondisclosure of income lower the estimates of value added. Such problems become more acute as countries move from state control of industry to private enterprise, because new firms and growing numbers of established firms fail to report. In accordance with the System of National Accounts, output should include all such unreported activity as well as the value of illegal activities and other unrecorded, informal, or small-scale operations. Data on these activities need to be collected using techniques other than conventional surveys of firms.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "nv_ind_totl_kd_zg": { "title": "Industry (including construction), value added (annual % growth)", "description_from_producer": "Annual growth rate for industrial (including construction) value added based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Industry corresponds to ISIC divisions 05-43 and includes manufacturing (ISIC divisions 10-33). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4.\n\nLimitations and exceptions: Ideally, industrial output should be measured through regular censuses and surveys of firms. But in most developing countries such surveys are infrequent, so earlier survey results must be extrapolated using an appropriate indicator. The choice of sampling unit, which may be the enterprise (where responses may be based on financial records) or the establishment (where production units may be recorded separately), also affects the quality of the data. Moreover, much industrial production is organized in unincorporated or owner-operated ventures that are not captured by surveys aimed at the formal sector. Even in large industries, where regular surveys are more likely, evasion of excise and other taxes and nondisclosure of income lower the estimates of value added. Such problems become more acute as countries move from state control of industry to private enterprise, because new firms and growing numbers of established firms fail to report. In accordance with the System of National Accounts, output should include all such unreported activity as well as the value of illegal activities and other unrecorded, informal, or small-scale operations. Data on these activities need to be collected using techniques other than conventional surveys of firms.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "nv_ind_totl_kn": { "title": "Industry (including construction), value added (constant LCU)", "description_from_producer": "Industry (including construction) corresponds to ISIC divisions 05-43 and includes manufacturing (ISIC divisions 10-33). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "nv_ind_totl_zs": { "title": "Industry (including construction), value added (% of GDP)", "description_from_producer": "Industry (including construction) corresponds to ISIC divisions 05-43 and includes manufacturing (ISIC divisions 10-33). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Note: For VAB countries, gross value added at factor cost is used as the denominator.\n\nLimitations and exceptions: Ideally, industrial output should be measured through regular censuses and surveys of firms. But in most developing countries such surveys are infrequent, so earlier survey results must be extrapolated using an appropriate indicator. The choice of sampling unit, which may be the enterprise (where responses may be based on financial records) or the establishment (where production units may be recorded separately), also affects the quality of the data. Moreover, much industrial production is organized in unincorporated or owner-operated ventures that are not captured by surveys aimed at the formal sector. Even in large industries, where regular surveys are more likely, evasion of excise and other taxes and nondisclosure of income lower the estimates of value added. Such problems become more acute as countries move from state control of industry to private enterprise, because new firms and growing numbers of established firms fail to report. In accordance with the System of National Accounts, output should include all such unreported activity as well as the value of illegal activities and other unrecorded, informal, or small-scale operations. Data on these activities need to be collected using techniques other than conventional surveys of firms.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "nv_mnf_chem_zs_un": { "title": "Chemicals (% of value added in manufacturing)", "description_from_producer": "Value added in manufacturing is the sum of gross output less the value of intermediate inputs used in production for industries classified in ISIC major division D. Chemicals correspond to ISIC division 24.\n\nLimitations and exceptions: In establishing classifications systems compilers must define both the types of activities to be described and the units whose activities are to be reported. There are many possibilities, and the choices affect how the statistics can be interpreted and how useful they are in analyzing economic behavior. The ISIC emphasizes commonalities in the production process and is explicitly not intended to measure outputs (for which there is a newly developed Central Product Classification). Nevertheless, the ISIC views an activity as defined by \"a process resulting in a homogeneous set of products.\"\n\nStatistical concept and methodology: The data on the distribution of manufacturing value added by industry are provided by the United Nations Industrial Development Organization (UNIDO). UNIDO obtains the data from a variety of national and international sources, including the United Nations Statistics Division, the World Bank, the Organisation for Economic Co-operation and Development, and the International Monetary Fund. To improve comparability over time and across countries, UNIDO supplements these data with information from industrial censuses, statistics from national and international organizations, unpublished data that it collects in the field, and estimates by the UNIDO Secretariat. Nevertheless, coverage may be incomplete, particularly for the informal sector. When direct information on inputs and outputs is not available, estimates may be used, which may result in errors in industry totals. Moreover, countries use different reference periods (calendar or fiscal year) and valuation methods (basic or producer prices) to estimate value added.", "origins": [ { "producer": "UN Industrial Development Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of value added in manufacturing", "short_unit": "%" }, "nv_mnf_fbto_zs_un": { "title": "Food, beverages and tobacco (% of value added in manufacturing)", "description_from_producer": "Value added in manufacturing is the sum of gross output less the value of intermediate inputs used in production for industries classified in ISIC major division D. Food, beverages, and tobacco correspond to ISIC divisions 15 and 16.\n\nLimitations and exceptions: In establishing classifications systems compilers must define both the types of activities to be described and the units whose activities are to be reported. There are many possibilities, and the choices affect how the statistics can be interpreted and how useful they are in analyzing economic behavior. The ISIC emphasizes commonalities in the production process and is explicitly not intended to measure outputs (for which there is a newly developed Central Product Classification). Nevertheless, the ISIC views an activity as defined by \"a process resulting in a homogeneous set of products.\"\n\nStatistical concept and methodology: The data on the distribution of manufacturing value added by industry are provided by the United Nations Industrial Development Organization (UNIDO). UNIDO obtains the data from a variety of national and international sources, including the United Nations Statistics Division, the World Bank, the Organisation for Economic Co-operation and Development, and the International Monetary Fund. To improve comparability over time and across countries, UNIDO supplements these data with information from industrial censuses, statistics from national and international organizations, unpublished data that it collects in the field, and estimates by the UNIDO Secretariat. Nevertheless, coverage may be incomplete, particularly for the informal sector. When direct information on inputs and outputs is not available, estimates may be used, which may result in errors in industry totals. Moreover, countries use different reference periods (calendar or fiscal year) and valuation methods (basic or producer prices) to estimate value added.", "origins": [ { "producer": "UN Industrial Development Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of value added in manufacturing", "short_unit": "%" }, "nv_mnf_mtrn_zs_un": { "title": "Machinery and transport equipment (% of value added in manufacturing)", "description_from_producer": "Value added in manufacturing is the sum of gross output less the value of intermediate inputs used in production for industries classified in ISIC major division D. Machinery and transport equipment correspond to ISIC divisions 29, 30, 32, 34, and 35.\n\nLimitations and exceptions: In establishing classifications systems compilers must define both the types of activities to be described and the units whose activities are to be reported. There are many possibilities, and the choices affect how the statistics can be interpreted and how useful they are in analyzing economic behavior. The ISIC emphasizes commonalities in the production process and is explicitly not intended to measure outputs (for which there is a newly developed Central Product Classification). Nevertheless, the ISIC views an activity as defined by \"a process resulting in a homogeneous set of products.\"\n\nStatistical concept and methodology: The data on the distribution of manufacturing value added by industry are provided by the United Nations Industrial Development Organization (UNIDO). UNIDO obtains the data from a variety of national and international sources, including the United Nations Statistics Division, the World Bank, the Organisation for Economic Co-operation and Development, and the International Monetary Fund. To improve comparability over time and across countries, UNIDO supplements these data with information from industrial censuses, statistics from national and international organizations, unpublished data that it collects in the field, and estimates by the UNIDO Secretariat. Nevertheless, coverage may be incomplete, particularly for the informal sector. When direct information on inputs and outputs is not available, estimates may be used, which may result in errors in industry totals. Moreover, countries use different reference periods (calendar or fiscal year) and valuation methods (basic or producer prices) to estimate value added.", "origins": [ { "producer": "UN Industrial Development Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of value added in manufacturing", "short_unit": "%" }, "nv_mnf_othr_zs_un": { "title": "Other manufacturing (% of value added in manufacturing)", "description_from_producer": "Value added in manufacturing is the sum of gross output less the value of intermediate inputs used in production for industries classified in ISIC major division D. Other manufacturing, a residual, covers wood and related products (ISIC division 20), paper and related products (ISIC divisions 21 and 22), petroleum and related products (ISIC division 23), basic metals and mineral products (ISIC division27), fabricated metal products and professional goods (ISIC division 28), and other industries (ISIC divisions 25, 26, 31, 33, 36, and 37). Includes unallocated data. When data for textiles, machinery, or chemicals are shown as not available, they are included in other manufacturing.\n\nLimitations and exceptions: In establishing classifications systems compilers must define both the types of activities to be described and the units whose activities are to be reported. There are many possibilities, and the choices affect how the statistics can be interpreted and how useful they are in analyzing economic behavior. The ISIC emphasizes commonalities in the production process and is explicitly not intended to measure outputs (for which there is a newly developed Central Product Classification). Nevertheless, the ISIC views an activity as defined by \"a process resulting in a homogeneous set of products.\"\n\nStatistical concept and methodology: The data on the distribution of manufacturing value added by industry are provided by the United Nations Industrial Development Organization (UNIDO). UNIDO obtains the data from a variety of national and international sources, including the United Nations Statistics Division, the World Bank, the Organisation for Economic Co-operation and Development, and the International Monetary Fund. To improve comparability over time and across countries, UNIDO supplements these data with information from industrial censuses, statistics from national and international organizations, unpublished data that it collects in the field, and estimates by the UNIDO Secretariat. Nevertheless, coverage may be incomplete, particularly for the informal sector. When direct information on inputs and outputs is not available, estimates may be used, which may result in errors in industry totals. Moreover, countries use different reference periods (calendar or fiscal year) and valuation methods (basic or producer prices) to estimate value added.", "origins": [ { "producer": "UN Industrial Development Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of value added in manufacturing", "short_unit": "%" }, "nv_mnf_tech_zs_un": { "title": "Medium and high-tech manufacturing value added (% manufacturing value added)", "description_from_producer": "The proportion of medium and high-tech industry value added in total value added of manufacturing\n\nLimitations and exceptions: Value added by economic activity should be reported at least at 3-digit ISIC for compiling MHT values. Missing values at country level are imputed based on the methodology from Competitive Industrial Performance Report (UNIDO, 2017. Conversion to USD or difference in ISIC combinations may cause discrepancy between national and international figures. For additional information please see UNIDO (2017): http://stat.unido.org/content/publications/volume-i%252c-competitive-industrial-performance-report-2016\n\nStatistical concept and methodology: The indicator is calculated as the share of the sum of the value added from medium and high-tech industry economic activities to manufacturing value added. The medium and high-tech industry is defined using OECD classification as the following by International Standard Industrial Classification of All Economic Activities (ISIC) Revision 3 and Revision 4 Division respectively: ISIC Rev. 3 (24, 29, 30, 31, 32, 33, 34, 35 excluding 351). Manufacturing value added is the value added of manufacturing industry, which is Section C of ISIC Rev.4, and Section D of ISIC Rev.3. Data can be found in UNIDO INDSTAT4 Database by ISIC Revision 3 and ISIC Revision 4 respectively. Data are collected using General Industrial Statistics Questionnaire which is filled by NSOs and submitted to UNIDO annually. Data for OECD countries are obtained directly from OECD. Country data are also collected from official publications and official web-sites. For additional information please see Table B.2.2 in Appendix B of UNIDO (2017): http://stat.unido.org/content/publications/volume-i%252c-competitive-industrial-performance-report-2016", "origins": [ { "producer": "UN Industrial Development Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "nv_mnf_txtl_zs_un": { "title": "Textiles and clothing (% of value added in manufacturing)", "description_from_producer": "Value added in manufacturing is the sum of gross output less the value of intermediate inputs used in production for industries classified in ISIC major division D. Textiles and clothing correspond to ISIC divisions 17-19.\n\nLimitations and exceptions: In establishing classifications systems compilers must define both the types of activities to be described and the units whose activities are to be reported. There are many possibilities, and the choices affect how the statistics can be interpreted and how useful they are in analyzing economic behavior. The ISIC emphasizes commonalities in the production process and is explicitly not intended to measure outputs (for which there is a newly developed Central Product Classification). Nevertheless, the ISIC views an activity as defined by \"a process resulting in a homogeneous set of products.\"\n\nStatistical concept and methodology: The data on the distribution of manufacturing value added by industry are provided by the United Nations Industrial Development Organization (UNIDO). UNIDO obtains the data from a variety of national and international sources, including the United Nations Statistics Division, the World Bank, the Organisation for Economic Co-operation and Development, and the International Monetary Fund. To improve comparability over time and across countries, UNIDO supplements these data with information from industrial censuses, statistics from national and international organizations, unpublished data that it collects in the field, and estimates by the UNIDO Secretariat. Nevertheless, coverage may be incomplete, particularly for the informal sector. When direct information on inputs and outputs is not available, estimates may be used, which may result in errors in industry totals. Moreover, countries use different reference periods (calendar or fiscal year) and valuation methods (basic or producer prices) to estimate value added.", "origins": [ { "producer": "UN Industrial Development Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of value added in manufacturing", "short_unit": "%" }, "nv_srv_empl_kd": { "title": "Services, value added per worker (constant 2015 US$)", "description_from_producer": "Value added per worker is a measure of labor productivity\u2014value added per unit of input. Value added denotes the net output of a sector after adding up all outputs and subtracting intermediate inputs. Data are in constant 2015 U.S. dollars. Services corresponds to the International Standard Industrial Classification (ISIC) tabulation categories G-P (revision 3) or tabulation categories G-U (revision 4), and includes wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social and personal services.\n\nLimitations and exceptions: For comparability of individual sectors labor productivity is estimated according to national accounts conventions. However, there are still significant limitations on the availability of reliable data. Information on consistent series of output is not easily available, especially in low- and middle-income countries, because the definition, coverage, and methodology are not always consistent across countries. For more details, see Agriculture, forestry, and fishing, value added (constant 2015 US$) [NV.AGR.TOTL.KD], Industry (including construction), value added (constant 2015 US$) [NV.IND.TOTL.KD], and Services, value added (constant 2015 US$) [NV.SRV.TOTL.KD].\n\nStatistical concept and methodology: Value added per worker is calculated by dividing value added of a sector by the number employed in the sector.\nGross domestic product (GDP) represents the sum of value added by all producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Value added by industry is normally measured at basic prices, while total GDP is measured at purchaser prices.\nData on employment are modeled estimates by the International Labour Organization (ILO) ILOSTAT database. The concept of employment generally refers to people above a certain age who worked, or who held a job, during a reference period. Employment data include both full-time and part-time workers.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "nv_srv_totl_cd": { "title": "Services, value added (current US$)", "description_from_producer": "Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges and import duties. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "nv_srv_totl_cn": { "title": "Services, value added (current LCU)", "description_from_producer": "Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges and import duties. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "nv_srv_totl_kd": { "title": "Services, value added (constant 2015 US$)", "description_from_producer": "Services correspond to ISIC divisions 45-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers as well as discrepancies arising from rescaling. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Data are in constant 2015 prices, expressed in U.S. dollars.\n\nLimitations and exceptions: In the services industries, including most of government, value added in constant prices is often imputed from labor inputs, such as real wages or number of employees. In the absence of well defined measures of output, measuring the growth of services remains difficult.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "nv_srv_totl_kd_zg": { "title": "Services, value added (annual % growth)", "description_from_producer": "Annual growth rate for value added in services based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Services correspond to ISIC divisions 45-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers as well as discrepancies arising from rescaling. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4.\n\nLimitations and exceptions: In the services industries, including most of government, value added in constant prices is often imputed from labor inputs, such as real wages or number of employees. In the absence of well defined measures of output, measuring the growth of services remains difficult.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "nv_srv_totl_kn": { "title": "Services, value added (constant LCU)", "description_from_producer": "Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges and import duties. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "nv_srv_totl_zs": { "title": "Services, value added (% of GDP)", "description_from_producer": "Services correspond to ISIC divisions 50-99 and they include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers as well as discrepancies arising from rescaling. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3 or 4.\n\nLimitations and exceptions: In the services industry the many self-employed workers and one-person businesses are sometimes difficult to locate, and they have little incentive to respond to surveys, let alone to report their full earnings. Compounding these problems are the many forms of economic activity that go unrecorded, including the work that women and children do for little or no pay.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.\nFinancial intermediation services indirectly measured (FISIM) is an indirect measure of the value of financial intermediation services (i.e. output) provided but for which financial institutions do not charge explicitly as compared to explicit bank charges. Although the 1993 SNA recommends that the FISIM are allocated as intermediate and final consumption to the users, many countries still make a global (negative) adjustment to the sum of gross value added.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ny_adj_aedu_cd": { "title": "Adjusted savings: education expenditure (current US$)", "description_from_producer": "Education expenditure refers to the current operating expenditures in education, including wages and salaries and excluding capital investments in buildings and equipment.", "origins": [ { "producer": "World Bank based on data from the UN Statistics Division and UNESCO", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_aedu_gn_zs": { "title": "Adjusted savings: education expenditure (% of GNI)", "description_from_producer": "Education expenditure refers to the current operating expenditures in education, including wages and salaries and excluding capital investments in buildings and equipment.\n\nLimitations and exceptions: Public education expenditures are considered an addition to savings. However, because of the wide variability in the effectiveness of public education expenditures, these figures cannot be construed as the value of investments in human capital. A current expenditure of $1 on education does not necessarily yield $1 of human capital. The calculation should also consider private education expenditure, but data are not available for a large number of countries.", "origins": [ { "producer": "World Bank based on data from the UN Statistics Division and UNESCO", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_dco2_cd": { "title": "Adjusted savings: carbon dioxide damage (current US$)", "description_from_producer": "Cost of damage due to carbon dioxide emissions from fossil fuel use and the manufacture of cement, estimated to be US$40 per ton of CO2 (the unit damage in 2017 US dollars for CO2 emitted in 2020) times the number of tons of CO2 emitted.\n\nStatistical concept and methodology: Pollution damage from emissions of carbon dioxide is calculated as the marginal social cost per unit multiplied by the increase in the stock of carbon dioxide. The unit damage figure represents the present value of global damage to economic assets and to human welfare over the time the unit of pollution remains in the atmosphere.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_dco2_gn_zs": { "title": "Adjusted savings: carbon dioxide damage (% of GNI)", "description_from_producer": "Cost of damage due to carbon dioxide emissions from fossil fuel use and the manufacture of cement, estimated to be US$40 per ton of CO2 (the unit damage in 2017 US dollars for CO2 emitted in 2020) times the number of tons of CO2 emitted.\n\nStatistical concept and methodology: Pollution damage from emissions of carbon dioxide is calculated as the marginal social cost per unit multiplied by the increase in the stock of carbon dioxide. The unit damage figure represents the present value of global damage to economic assets and to human welfare over the time the unit of pollution remains in the atmosphere.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_dfor_cd": { "title": "Adjusted savings: net forest depletion (current US$)", "description_from_producer": "Net forest depletion is calculated as the product of unit resource rents and the excess of roundwood harvest over natural growth.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_dfor_gn_zs": { "title": "Adjusted savings: net forest depletion (% of GNI)", "description_from_producer": "Net forest depletion is calculated as the product of unit resource rents and the excess of roundwood harvest over natural growth.\n\nLimitations and exceptions: A positive net depletion figure for forest resources implies that the harvest rate exceeds the rate of natural growth; this is not the same as deforestation, which represents a change in land use. In principle, there should be an addition to savings in countries where growth exceeds harvest, but empirical estimates suggest that most of this net growth is in forested areas that cannot currently be exploited economically. Because the depletion estimates reflect only timber values, they ignore all the external and nontimber benefits associated with standing forests.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_dkap_cd": { "title": "Adjusted savings: consumption of fixed capital (current US$)", "description_from_producer": "Consumption of fixed capital represents the replacement value of capital used up in the process of production.", "origins": [ { "producer": "World Bank based on data from the UN Statistics Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_dkap_gn_zs": { "title": "Adjusted savings: consumption of fixed capital (% of GNI)", "description_from_producer": "Consumption of fixed capital represents the replacement value of capital used up in the process of production.", "origins": [ { "producer": "World Bank based on data from the UN Statistics Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_dmin_cd": { "title": "Adjusted savings: mineral depletion (current US$)", "description_from_producer": "Mineral depletion is the ratio of the value of the stock of mineral resources to the remaining reserve lifetime (capped at 25 years). It covers tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_dmin_gn_zs": { "title": "Adjusted savings: mineral depletion (% of GNI)", "description_from_producer": "Mineral depletion is the ratio of the value of the stock of mineral resources to the remaining reserve lifetime (capped at 25 years). It covers tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_dngy_cd": { "title": "Adjusted savings: energy depletion (current US$)", "description_from_producer": "Energy depletion is the ratio of the value of the stock of energy resources to the remaining reserve lifetime (capped at 25 years). It covers coal, crude oil, and natural gas.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_dngy_gn_zs": { "title": "Adjusted savings: energy depletion (% of GNI)", "description_from_producer": "Energy depletion is the ratio of the value of the stock of energy resources to the remaining reserve lifetime (capped at 25 years). It covers coal, crude oil, and natural gas.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_dpem_cd": { "title": "Adjusted savings: particulate emission damage (current US$)", "description_from_producer": "Particulate emissions damage is the damage due to exposure of a country's population to ambient concentrations of particulates measuring less than 2.5 microns in diameter (PM2.5), ambient ozone pollution, and indoor concentrations of PM2.5 in households cooking with solid fuels. Damages are calculated as foregone labor income due to premature death. Estimates of health impacts from the Global Burden of Disease Study 2013 are for 1990, 1995, 2000, 2005, 2010, and 2013. Data for other years have been extrapolated from trends in mortality rates.", "origins": [ { "producer": "Institute for Health Metrics and Evaluation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_dpem_gn_zs": { "title": "Adjusted savings: particulate emission damage (% of GNI)", "description_from_producer": "Particulate emissions damage is the damage due to exposure of a country's population to ambient concentrations of particulates measuring less than 2.5 microns in diameter (PM2.5), ambient ozone pollution, and indoor concentrations of PM2.5 in households cooking with solid fuels. Damages are calculated as foregone labor income due to premature death. Estimates of health impacts from the Global Burden of Disease Study 2013 are for 1990, 1995, 2000, 2005, 2010, and 2013. Data for other years have been extrapolated from trends in mortality rates.\n\nLimitations and exceptions: Labor productivity losses, as calculated within the framework of adjusted net savings, represent only part of the economic costs of air pollution and should be interpreted as a lower-end estimate.\n\nStatistical concept and methodology: Within the national accounting framework, air pollution damages are estimated following a human capital approach. Damages from premature mortality are calculated as the present value of lost income during working age, 15-64. Premature mortality among children is valued by adjusting for years until working age and discounting more heavily into the future. Damages from morbidity (years lived with disability) are estimated for adults in working age only without discounting into the future. Estimates are for both urban and rural areas. Exposure to household air pollution is proxied by the number of households in each country cooking with solid fuels.", "origins": [ { "producer": "Institute for Health Metrics and Evaluation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_dres_gn_zs": { "title": "Adjusted savings: natural resources depletion (% of GNI)", "description_from_producer": "Natural resource depletion is the sum of net forest depletion, energy depletion, and mineral depletion. Net forest depletion is unit resource rents times the excess of roundwood harvest over natural growth. Energy depletion is the ratio of the value of the stock of energy resources to the remaining reserve lifetime (capped at 25 years). It covers coal, crude oil, and natural gas. Mineral depletion is the ratio of the value of the stock of mineral resources to the remaining reserve lifetime (capped at 25 years). It covers tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate.\n\nLimitations and exceptions: Net forest depletion is not the monetary value of deforestation. Roundwood and fuelwood production are different from deforestation, which represents a permanent change in land use and, thus, is not comparable. Areas logged out but intended for regeneration are not included in deforestation figures; rather, they are counted as producing timber depletion. Net forest depletion includes only timber values and does not include the loss of nontimber forest benefits and nonuse benefits.\n\nFor both energy and mineral depletion, unit resource rent is calculated as (unit world price - average cost) / unit world price. Marginal cost should be used instead of average cost in order to calculate the true opportunity cost of extraction; however, marginal cost is difficult to compute and data are not readily available. Unit prices refer to international rather than local prices to reflect the social cost of natural resources depletion. This differs from methodologies of national accounts, which may use local prices to measure energy or mineral GDP. This difference explains eventual discrepancies in the values for energy or mineral depletion, verses energy or mineral GDP.\n\nStatistical concept and methodology: Natural resources depletion is the sum of net forest depletion, energy depletion, and mineral depletion:\n\nNet forest depletion is the product of unit resource rents and the excess of roundwood harvest over natural growth. In a country where incremental growth exceeds wood extraction, net forest depletion would be zero, no matter the absolute volume or value of wood extracted.\n\nEnergy depletion is the ratio of the present value of energy resource rents, discounted at 4 percent, to the exhaustion time of the resource (capped at 25 years). Rent is calculated as the product of unit resource rents and the physical quantities of energy resources extracted. It covers hard and soft coal, crude oil, and natural gas.\n\nMineral depletion is the ratio of the present value of mineral resource rents, discounted at 4 percent, to the exhaustion time of the resource (capped at 25 years). Rent is calculated as the product of unit resource rents and the physical quantities of mineral extracted. It covers tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_ictr_gn_zs": { "title": "Adjusted savings: gross savings (% of GNI)", "description_from_producer": "Gross savings are the difference between gross national income and public and private consumption, plus net current transfers.\n\nLimitations and exceptions: Because gross savings is calculated as a residual it includes errors, which may not be offsetting, in its components.\n\nStatistical concept and methodology: Gross savings are calculated as a residual from the national accounts by taking the difference between income earned by residents (including income received from abroad and workers' remittances) and their consumption expenditures.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_nnat_cd": { "title": "Adjusted savings: net national savings (current US$)", "description_from_producer": "Net national savings are equal to gross national savings less the value of consumption of fixed capital.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_nnat_gn_zs": { "title": "Adjusted savings: net national savings (% of GNI)", "description_from_producer": "Net national savings are equal to gross national savings less the value of consumption of fixed capital.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_nnty_cd": { "title": "Adjusted net national income (current US$)", "description_from_producer": "Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.\n\nLimitations and exceptions: Adjusted net national income differs from the adjustments made in the calculation of adjusted net savings, by not accounting for investments in human capital or the damages from pollution. Thus, adjusted net national income remains within the boundaries of the United Nations System of National Accounts (SNA).\n\nThe SNA includes non-produced natural assets (such as land, mineral resources, and forests) within the asset boundary when they are under the effective control of institutional units. The calculation of adjusted net national income, which accounts for net forest, energy, and mineral depletion, as well as consumption of fixed capital, thus remains within the SNA boundaries. This point is critical because it allows for comparisons across GDP, GNI, and adjusted net national income; such comparisons reveal the impact of natural resource depletion, which is otherwise ignored by the popular economic indicators.\n\nStatistical concept and methodology: Adjusted net national income complements gross national income (GNI) in assessing economic progress (Hamilton and Ley 2010) by providing a broader measure of national income that accounts for the depletion of natural resources.\n\nAdjusted net national income is calculated by subtracting from GNI a charge for the consumption of fixed capital (a calculation that yields net national income) and for the depletion of natural resources. The deduction for the depletion of natural resources, which covers net forest depletion, energy depletion, and mineral depletion, reflects the decline in asset values associated with the extraction and harvesting of natural resources. This is analogous to depreciation of fixed assets.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_nnty_kd": { "title": "Adjusted net national income (constant 2015 US$)", "description_from_producer": "Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.\n\nLimitations and exceptions: Adjusted net national income differs from the adjustments made in the calculation of adjusted net savings, by not accounting for investments in human capital or the damages from pollution. Thus, adjusted net national income remains within the boundaries of the United Nations System of National Accounts (SNA).\n\nThe SNA includes non-produced natural assets (such as land, mineral resources, and forests) within the asset boundary when they are under the effective control of institutional units. The calculation of adjusted net national income, which accounts for net forest, energy, and mineral depletion, as well as consumption of fixed capital, thus remains within the SNA boundaries. This point is critical because it allows for comparisons across GDP, GNI, and adjusted net national income; such comparisons reveal the impact of natural resource depletion, which is otherwise ignored by the popular economic indicators.\n\nStatistical concept and methodology: Adjusted net national income complements gross national income (GNI) in assessing economic progress (Hamilton and Ley 2010) by providing a broader measure of national income that accounts for the depletion of natural resources.\n\nAdjusted net national income is calculated by subtracting from GNI a charge for the consumption of fixed capital (a calculation that yields net national income) and for the depletion of natural resources. The deduction for the depletion of natural resources, which covers net forest depletion, energy depletion, and mineral depletion, reflects the decline in asset values associated with the extraction and harvesting of natural resources. This is analogous to depreciation of fixed assets.\n\nGrowth rates of adjusted net national income are computed from constant price series deflated using the gross national expenditure (formerly domestic absorption) deflator.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ny_adj_nnty_kd_zg": { "title": "Adjusted net national income (annual % growth)", "description_from_producer": "Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.\n\nLimitations and exceptions: Adjusted net national income differs from the adjustments made in the calculation of adjusted net savings, by not accounting for investments in human capital or the damages from pollution. Thus, adjusted net national income remains within the boundaries of the United Nations System of National Accounts (SNA).\n\nThe SNA includes non-produced natural assets (such as land, mineral resources, and forests) within the asset boundary when they are under the effective control of institutional units. The calculation of adjusted net national income, which accounts for net forest, energy, and mineral depletion, as well as consumption of fixed capital, thus remains within the SNA boundaries. This point is critical because it allows for comparisons across GDP, GNI, and adjusted net national income; such comparisons reveal the impact of natural resource depletion, which is otherwise ignored by the popular economic indicators.\n\nStatistical concept and methodology: Adjusted net national income complements gross national income (GNI) in assessing economic progress (Hamilton and Ley 2010) by providing a broader measure of national income that accounts for the depletion of natural resources.\n\nAdjusted net national income is calculated by subtracting from GNI a charge for the consumption of fixed capital (a calculation that yields net national income) and for the depletion of natural resources. The deduction for the depletion of natural resources, which covers net forest depletion, energy depletion, and mineral depletion, reflects the decline in asset values associated with the extraction and harvesting of natural resources. This is analogous to depreciation of fixed assets.\n\nGrowth rates of adjusted net national income are computed from constant price series deflated using the gross national expenditure (formerly domestic absorption) deflator.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "ny_adj_nnty_pc_cd": { "title": "Adjusted net national income per capita (current US$)", "description_from_producer": "Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_nnty_pc_kd": { "title": "Adjusted net national income per capita (constant 2015 US$)", "description_from_producer": "Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.\n\nLimitations and exceptions: Adjusted net national income differs from the adjustments made in the calculation of adjusted net savings, by not accounting for investments in human capital or the damages from pollution. Thus, adjusted net national income remains within the boundaries of the United Nations System of National Accounts (SNA).\n\nThe SNA includes non-produced natural assets (such as land, mineral resources, and forests) within the asset boundary when they are under the effective control of institutional units. The calculation of adjusted net national income, which accounts for net forest, energy, and mineral depletion, as well as consumption of fixed capital, thus remains within the SNA boundaries. This point is critical because it allows for comparisons across GDP, GNI, and adjusted net national income; such comparisons reveal the impact of natural resource depletion, which is otherwise ignored by the popular economic indicators.\n\nStatistical concept and methodology: Adjusted net national income complements gross national income (GNI) in assessing economic progress (Hamilton and Ley 2010) by providing a broader measure of national income that accounts for the depletion of natural resources.\n\nAdjusted net national income is calculated by subtracting from GNI a charge for the consumption of fixed capital (a calculation that yields net national income) and for the depletion of natural resources. The deduction for the depletion of natural resources, which covers net forest depletion, energy depletion, and mineral depletion, reflects the decline in asset values associated with the extraction and harvesting of natural resources. This is analogous to depreciation of fixed assets.\n\nGrowth rates of adjusted net national income are computed from constant price series deflated using the gross national expenditure (formerly domestic absorption) deflator.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ny_adj_nnty_pc_kd_zg": { "title": "Adjusted net national income per capita (annual % growth)", "description_from_producer": "Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.\n\nLimitations and exceptions: Adjusted net national income differs from the adjustments made in the calculation of adjusted net savings, by not accounting for investments in human capital or the damages from pollution. Thus, adjusted net national income remains within the boundaries of the United Nations System of National Accounts (SNA).\n\nThe SNA includes non-produced natural assets (such as land, mineral resources, and forests) within the asset boundary when they are under the effective control of institutional units. The calculation of adjusted net national income, which accounts for net forest, energy, and mineral depletion, as well as consumption of fixed capital, thus remains within the SNA boundaries. This point is critical because it allows for comparisons across GDP, GNI, and adjusted net national income; such comparisons reveal the impact of natural resource depletion, which is otherwise ignored by the popular economic indicators.\n\nStatistical concept and methodology: Adjusted net national income complements gross national income (GNI) in assessing economic progress (Hamilton and Ley 2010) by providing a broader measure of national income that accounts for the depletion of natural resources.\n\nAdjusted net national income is calculated by subtracting from GNI a charge for the consumption of fixed capital (a calculation that yields net national income) and for the depletion of natural resources. The deduction for the depletion of natural resources, which covers net forest depletion, energy depletion, and mineral depletion, reflects the decline in asset values associated with the extraction and harvesting of natural resources. This is analogous to depreciation of fixed assets.\n\nGrowth rates of adjusted net national income are computed from constant price series deflated using the gross national expenditure (formerly domestic absorption) deflator.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual % growth", "short_unit": "%" }, "ny_adj_svng_cd": { "title": "Adjusted net savings, including particulate emission damage (current US$)", "description_from_producer": "Adjusted net savings are equal to net national savings plus education expenditure and minus energy depletion, mineral depletion, net forest depletion, and carbon dioxide and particulate emissions damage.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_svng_gn_zs": { "title": "Adjusted net savings, including particulate emission damage (% of GNI)", "description_from_producer": "Adjusted net savings are equal to net national savings plus education expenditure and minus energy depletion, mineral depletion, net forest depletion, and carbon dioxide and particulate emissions damage.\n\nLimitations and exceptions: The exercise treats public education expenditures as an addition to savings. However, because of the wide variability in the effectiveness of public education expenditures, these figures cannot be construed as the value of investments in human capital. A current expenditure of $1 on education does not necessarily yield $1 of human capital. The calculation should also consider private education expenditure, but data are not available for a large number of countries.\n\nWhile extensive, the accounting of natural resource depletion and pollution costs still has some gaps. Key estimates missing on the resource side include the value of fossil water extracted from aquifers, net depletion of fish stocks, and depletion and degradation of soils. Important pollutants affecting human health and economic assets are excluded because no internationally comparable data are widely available on damage from ground-level ozone or sulfur oxides.\n\nStatistical concept and methodology: Adjusted net savings are derived from standard national accounting measures of gross savings by making four adjustments. First, estimates of fixed capital consumption of produced assets are deducted to obtain net savings. Second, current public expenditures on education are added to net savings (in standard national accounting these expenditures are treated as consumption). Third, estimates of the depletion of a variety of natural resources are deducted to reflect the decline in asset values associated with their extraction and harvest. And fourth, deductions are made for damages from carbon dioxide emissions and local pollution.\n\nEstimates of resource depletion are based on the \"change in real wealth\" method described in Hamilton and Ruta (2008), which estimates depletion as the ratio between the total value of the resource and the remaining reserve lifetime. The total value of the resource is the present value of current and future rents from resource extractions. An economic rent represents an excess return to a given factor of production. Natural resources give rise to rents because they are not produced; in contrast, for produced goods and services competitive forces will expand supply until economic profits are driven to zero. For each type of resource and each country, unit resource rents are derived by taking the difference between world prices (to reflect the social opportunity cost of resource extraction) and the average unit extraction or harvest costs (including a \u201cnormal\u201d return on capital). Unit rents are then multiplied by the physical quantity extracted or harvested to arrive at total rent. To estimate the value of the resource, rents are assumed to be constant over the life of the resource (the El Serafy approach), and the present value of the rent flow is calculated using a 4 percent social discount rate.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_adj_svnx_cd": { "title": "Adjusted net savings, excluding particulate emission damage (current US$)", "description_from_producer": "Adjusted net savings are equal to net national savings plus education expenditure and minus energy depletion, mineral depletion, net forest depletion, and carbon dioxide. This series excludes particulate emissions damage.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_adj_svnx_gn_zs": { "title": "Adjusted net savings, excluding particulate emission damage (% of GNI)", "description_from_producer": "Adjusted net savings are equal to net national savings plus education expenditure and minus energy depletion, mineral depletion, net forest depletion, and carbon dioxide. This series excludes particulate emissions damage.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_exp_capm_kn": { "title": "Exports as a capacity to import (constant LCU)", "description_from_producer": "Exports as a capacity to import equals the current price value of exports of goods and services deflated by the import price index. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ny_gdp_coal_rt_zs": { "title": "Coal rents (% of GDP)", "description_from_producer": "Coal rents are the difference between the value of both hard and soft coal production at world prices and their total costs of production.\n\nStatistical concept and methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ny_gdp_defl_kd_zg": { "title": "Inflation, GDP deflator (annual %)", "description_from_producer": "Inflation as measured by the annual growth rate of the GDP implicit deflator shows the rate of price change in the economy as a whole. The GDP implicit deflator is the ratio of GDP in current local currency to GDP in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "ny_gdp_defl_kd_zg_ad": { "title": "Inflation, GDP deflator: linked series (annual %)", "description_from_producer": "Inflation as measured by the annual growth rate of the GDP implicit deflator shows the rate of price change in the economy as a whole. This series has been linked to produce a consistent time series to counteract breaks in series over time due to changes in base years, source data and methodologies. Thus, it may not be comparable with other national accounts series in the database for historical years.\n\nStatistical concept and methodology: The accuracy of national accounts estimates and their comparability across countries depend on timely revisions to data on GDP and its components. The frequency of revisions to GDP data varies: some countries revise numbers monthly, others quarterly or annually, and others less frequently. Such revisions are usually small and based on additional information received during the year. However, larger revisions are required from time to time to rebase the national accounts and allow for incorporation of new methodologies and data sources.\n\nComprehensive revisions of GDP data often (but not always) result in upward adjustments to GDP and other major aggregates as improved data sources increase the coverage of the economy. And estimates of GDP growth may change as new weights are introduced. These revisions will cause breaks in series unless they are applied consistently to historical data. For constant price series a break caused by rebasing can be eliminated by linking the old series to the new using historical growth rates.\n\nThis inflation series based on the implicit GDP deflator has been linked to produce a consistent time series. It has been calculated by utilizing the change in the implicit GDP deflator in the WDI Archive and IMF WEO databases. Thus, earlier years (linked years) will not be comparable with other national accounts series in the database. Data are available for World Bank operational countries only.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "ny_gdp_defl_zs": { "title": "GDP deflator (base year varies by country)", "description_from_producer": "The GDP implicit deflator is the ratio of GDP in current local currency to GDP in constant local currency. The base year varies by country.\n\nStatistical concept and methodology: Inflation is measured by the rate of increase in a price index, but actual price change can be negative. The index used depends on the prices being examined. The GDP deflator reflects price changes for total GDP. The most general measure of the overall price level, it accounts for changes in government consumption, capital formation (including inventory appreciation), international trade, and the main component, household final consumption expenditure. The GDP deflator is usually derived implicitly as the ratio of current to constant price GDP - or a Paasche index. It is defective as a general measure of inflation for policy use because of long lags in deriving estimates and because it is often an annual measure.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "base year varies by country" }, "ny_gdp_defl_zs_ad": { "title": "GDP deflator: linked series (base year varies by country)", "description_from_producer": "The GDP implicit deflator is calculated as the ratio of GDP in current local currency to GDP in constant local currency. This series has been linked to produce a consistent time series to counteract breaks in series over time due to changes in base years, source data and methodologies. Thus, it may not be comparable with other national accounts series in the database for historical years. The base year varies by country.\n\nStatistical concept and methodology: The accuracy of national accounts estimates and their comparability across countries depend on timely revisions to data on GDP and its components. The frequency of revisions to GDP data varies: some countries revise numbers monthly, others quarterly or annually, and others less frequently. Such revisions are usually small and based on additional information received during the year. However, larger revisions are required from time to time to rebase the national accounts and allow for incorporation of new methodologies and data sources.\n\nComprehensive revisions of GDP data often (but not always) result in upward adjustments to GDP and other major aggregates as improved data sources increase the coverage of the economy. And estimates of GDP growth may change as new weights are introduced. These revisions will cause breaks in series unless they are applied consistently to historical data. For constant price series a break caused by rebasing can be eliminated by linking the old series to the new using historical growth rates.\n\nThis implicit GDP deflator series has been linked to produce a consistent time series. It has been calculated by utilizing the change in the implicit GDP deflator in the WDI Archive and IMF WEO databases. Thus, earlier years (linked years) will not be comparable with other national accounts series in the database. Data are available for World Bank operational countries only.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "base year varies by country" }, "ny_gdp_disc_cn": { "title": "Discrepancy in expenditure estimate of GDP (current LCU)", "description_from_producer": "Discrepancy in expenditure estimate of GDP is the discrepancy included in final consumption expenditure, etc. (total consumption, etc.). This discrepancy is included to ensure that GDP from the expenditure side equals GDP measured by the income or output approach. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_gdp_disc_kn": { "title": "Discrepancy in expenditure estimate of GDP (constant LCU)", "description_from_producer": "A statistical discrepancy usually arises when the GDP components are estimated independently by industrial origin and by expenditure categories. This item represents the discrepancy in the use of resources (i.e., the estimate of GDP by expenditure categories). Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ny_gdp_fcst_cd": { "title": "Gross value added at basic prices (GVA) (current US$)", "description_from_producer": "Gross value added at basic prices (formerly GDP at factor cost) is derived as the sum of the value added in the agriculture, industry and services sectors. If the value added of these sectors is calculated at purchaser values, gross value added at basic prices is derived by subtracting net product taxes from GDP. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_gdp_fcst_cn": { "title": "Gross value added at basic prices (GVA) (current LCU)", "description_from_producer": "Gross value added at basic prices (formerly GDP at factor cost) is derived as the sum of the value added in the agriculture, industry and services sectors. If the value added of these sectors is calculated at purchaser values, gross value added at basic prices is derived by subtracting net product taxes from GDP. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_gdp_fcst_kd": { "title": "Gross value added at basic prices (GVA) (constant 2015 US$)", "description_from_producer": "Gross value added at basic prices (formerly GDP at factor cost) is derived as the sum of the value added in the agriculture, industry and services sectors. If the value added of these sectors is calculated at purchaser values, gross value added at basic prices is derived by subtracting net product taxes from GDP. Data are in constant 2015 prices, expressed in U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ny_gdp_fcst_kn": { "title": "Gross value added at basic prices (GVA) (constant LCU)", "description_from_producer": "Gross value added at basic prices (formerly GDP at factor cost) is derived as the sum of the value added in the agriculture, industry and services sectors. If the value added of these sectors is calculated at purchaser values, gross value added at basic prices is derived by subtracting net product taxes from GDP. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ny_gdp_frst_rt_zs": { "title": "Forest rents (% of GDP)", "description_from_producer": "Forest rents are roundwood harvest times the product of regional prices and a regional rental rate.\n\nStatistical concept and methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ny_gdp_minr_rt_zs": { "title": "Mineral rents (% of GDP)", "description_from_producer": "Mineral rents are the difference between the value of production for a stock of minerals at world prices and their total costs of production. Minerals included in the calculation are tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate.\n\nStatistical concept and methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ny_gdp_mktp_cd": { "title": "GDP (current US$)", "description_from_producer": "GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars. Dollar figures for GDP are converted from domestic currencies using single year official exchange rates. For a few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used.\n\nLimitations and exceptions: Gross domestic product (GDP), though widely tracked, may not always be the most relevant summary of aggregated economic performance for all economies, especially when production occurs at the expense of consuming capital stock.\n\nWhile GDP estimates based on the production approach are generally more reliable than estimates compiled from the income or expenditure side, different countries use different definitions, methods, and reporting standards. World Bank staff review the quality of national accounts data and sometimes make adjustments to improve consistency with international guidelines. Nevertheless, significant discrepancies remain between international standards and actual practice. Many statistical offices, especially those in developing countries, face severe limitations in the resources, time, training, and budgets required to produce reliable and comprehensive series of national accounts statistics.\n\nAmong the difficulties faced by compilers of national accounts is the extent of unreported economic activity in the informal or secondary economy. In developing countries a large share of agricultural output is either not exchanged (because it is consumed within the household) or not exchanged for money.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_gdp_mktp_cn": { "title": "GDP (current LCU)", "description_from_producer": "GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_gdp_mktp_cn_ad": { "title": "GDP: linked series (current LCU)", "description_from_producer": "GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. This series has been linked to produce a consistent time series to counteract breaks in series over time due to changes in base years, source data and methodologies. Thus, it may not be comparable with other national accounts series in the database for historical years. Data are in current local currency.\n\nStatistical concept and methodology: The accuracy of national accounts estimates and their comparability across countries depend on timely revisions to data on GDP and its components. The frequency of revisions to GDP data varies: some countries revise numbers monthly, others quarterly or annually, and others less frequently. Such revisions are usually small and based on additional information received during the year. However, larger revisions are required from time to time to rebase the national accounts and allow for incorporation of new methodologies and data sources.\n\nComprehensive revisions of GDP data often (but not always) result in upward adjustments to GDP and other major aggregates as improved data sources increase the coverage of the economy. And estimates of GDP growth may change as new weights are introduced. These revisions will cause breaks in series unless they are applied consistently to historical data. For constant price series a break caused by rebasing can be eliminated by linking the old series to the new using historical growth rates.\n\nThis current price GDP series has been linked to produce a consistent time series. It has been calculated by utilizing the change in the implicit GDP deflator in the WDI Archive and IMF WEO databases. Thus, earlier years (linked years) will not be comparable with other national accounts series in the database. Data are available for World Bank operational countries only.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_gdp_mktp_kd": { "title": "GDP (constant 2015 US$)", "description_from_producer": "GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2015 prices, expressed in U.S. dollars. Dollar figures for GDP are converted from domestic currencies using 2015 official exchange rates. For a few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used.\n\nLimitations and exceptions: Each industry's contribution to growth in the economy's output is measured by growth in the industry's value added. In principle, value added in constant prices can be estimated by measuring the quantity of goods and services produced in a period, valuing them at an agreed set of base year prices, and subtracting the cost of intermediate inputs, also in constant prices. This double-deflation method requires detailed information on the structure of prices of inputs and outputs.\n\nIn many industries, however, value added is extrapolated from the base year using single volume indexes of outputs or, less commonly, inputs. Particularly in the services industries, including most of government, value added in constant prices is often imputed from labor inputs, such as real wages or number of employees. In the absence of well defined measures of output, measuring the growth of services remains difficult.\n\nMoreover, technical progress can lead to improvements in production processes and in the quality of goods and services that, if not properly accounted for, can distort measures of value added and thus of growth. When inputs are used to estimate output, as for nonmarket services, unmeasured technical progress leads to underestimates of the volume of output. Similarly, unmeasured improvements in quality lead to underestimates of the value of output and value added. The result can be underestimates of growth and productivity improvement and overestimates of inflation.\n\nInformal economic activities pose a particular measurement problem, especially in developing countries, where much economic activity is unrecorded. A complete picture of the economy requires estimating household outputs produced for home use, sales in informal markets, barter exchanges, and illicit or deliberately unreported activities. The consistency and completeness of such estimates depend on the skill and methods of the compiling statisticians.\n\nRebasing of national accounts can alter the measured growth rate of an economy and lead to breaks in series that affect the consistency of data over time. When countries rebase their national accounts, they update the weights assigned to various components to better reflect current patterns of production or uses of output. The new base year should represent normal operation of the economy - it should be a year without major shocks or distortions. Some developing countries have not rebased their national accounts for many years. Using an old base year can be misleading because implicit price and volume weights become progressively less relevant and useful.\n\nTo obtain comparable series of constant price data for computing aggregates, the World Bank rescales GDP and value added by industrial origin to a common reference year. Because rescaling changes the implicit weights used in forming regional and income group aggregates, aggregate growth rates are not comparable with those from earlier editions with different base years. Rescaling may result in a discrepancy between the rescaled GDP and the sum of the rescaled components. To avoid distortions in the growth rates, the discrepancy is left unallocated. As a result, the weighted average of the growth rates of the components generally does not equal the GDP growth rate.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices. When value added is measured at producer prices.\n\nGrowth rates of GDP and its components are calculated using the least squares method and constant price data in the local currency. Constant price U.S. dollar series are used to calculate regional and income group growth rates. Local currency series are converted to constant U.S. dollars using an exchange rate in the common reference year.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ny_gdp_mktp_kd_zg": { "title": "GDP growth (annual %)", "description_from_producer": "Annual percentage growth rate of GDP at market prices based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.\n\nLimitations and exceptions: Each industry's contribution to growth in the economy's output is measured by growth in the industry's value added. In principle, value added in constant prices can be estimated by measuring the quantity of goods and services produced in a period, valuing them at an agreed set of base year prices, and subtracting the cost of intermediate inputs, also in constant prices. This double-deflation method requires detailed information on the structure of prices of inputs and outputs.\n\nIn many industries, however, value added is extrapolated from the base year using single volume indexes of outputs or, less commonly, inputs. Particularly in the services industries, including most of government, value added in constant prices is often imputed from labor inputs, such as real wages or number of employees. In the absence of well defined measures of output, measuring the growth of services remains difficult.\n\nMoreover, technical progress can lead to improvements in production processes and in the quality of goods and services that, if not properly accounted for, can distort measures of value added and thus of growth. When inputs are used to estimate output, as for nonmarket services, unmeasured technical progress leads to underestimates of the volume of output. Similarly, unmeasured improvements in quality lead to underestimates of the value of output and value added. The result can be underestimates of growth and productivity improvement and overestimates of inflation.\n\nInformal economic activities pose a particular measurement problem, especially in developing countries, where much economic activity is unrecorded. A complete picture of the economy requires estimating household outputs produced for home use, sales in informal markets, barter exchanges, and illicit or deliberately unreported activities. The consistency and completeness of such estimates depend on the skill and methods of the compiling statisticians.\n\nRebasing of national accounts can alter the measured growth rate of an economy and lead to breaks in series that affect the consistency of data over time. When countries rebase their national accounts, they update the weights assigned to various components to better reflect current patterns of production or uses of output. The new base year should represent normal operation of the economy - it should be a year without major shocks or distortions. Some developing countries have not rebased their national accounts for many years. Using an old base year can be misleading because implicit price and volume weights become progressively less relevant and useful.\n\nTo obtain comparable series of constant price data for computing aggregates, the World Bank rescales GDP and value added by industrial origin to a common reference year. Because rescaling changes the implicit weights used in forming regional and income group aggregates, aggregate growth rates are not comparable with those from earlier editions with different base years. Rescaling may result in a discrepancy between the rescaled GDP and the sum of the rescaled components. To avoid distortions in the growth rates, the discrepancy is left unallocated. As a result, the weighted average of the growth rates of the components generally does not equal the GDP growth rate.\n\nStatistical concept and methodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices. When value added is measured at producer prices.\n\nGrowth rates of GDP and its components are calculated using the least squares method and constant price data in the local currency. Constant price in U.S. dollar series are used to calculate regional and income group growth rates. Local currency series are converted to constant U.S. dollars using an exchange rate in the common reference year.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "ny_gdp_mktp_kn": { "title": "GDP (constant LCU)", "description_from_producer": "GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ny_gdp_mktp_pp_cd": { "title": "GDP, PPP (current international $)", "description_from_producer": "This indicator provides values for gross domestic product (GDP) expressed in current international dollars, converted by purchasing power parity (PPP) conversion factor.\nGDP is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. PPP conversion factor is a spatial price deflator and currency converter that eliminates the effects of the differences in price levels between countries.\nFrom April 2020, \u201cGDP: linked series (current LCU)\u201d [NY.GDP.MKTP.CN.AD] is used as underlying GDP in local currency unit so that it\u2019s in line with time series of PPP conversion factors for GDP, which are extrapolated with linked GDP deflators.\n\nStatistical concept and methodology: Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.\n\nFor more information on underlying GDP in local currency, please refer to the metadata for \u201cGDP: linked series (current LCU)\u201d [NY.GDP.MKTP.CN.AD]. For more information on underlying PPP conversion factor, please refer to the metadata for \"PPP conversion factor, GDP (LCU per international $)\" [PA.NUS.PPP].\n\nFor the concept and methodology of PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$" }, "ny_gdp_mktp_pp_kd": { "title": "GDP, PPP (constant 2017 international $)", "description_from_producer": "PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2017 international dollars.\n\nStatistical concept and methodology: For the concept and methodology of 2017 PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "international-$ in 2017 prices", "short_unit": "$" }, "ny_gdp_ngas_rt_zs": { "title": "Natural gas rents (% of GDP)", "description_from_producer": "Natural gas rents are the difference between the value of natural gas production at regional prices and total costs of production.\n\nStatistical concept and methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ny_gdp_pcap_cd": { "title": "GDP per capita (current US$)", "description_from_producer": "GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars.\n\nStatistical concept and methodology: For more information, see the metadata for current U.S. dollar GDP (NY.GDP.MKTP.CD) and total population (SP.POP.TOTL).", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$", "presentation": { "topic_tags": [ "Economic Growth" ] } }, "ny_gdp_pcap_cn": { "title": "GDP per capita (current LCU)", "description_from_producer": "GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU", "presentation": { "topic_tags": [ "Economic Growth" ] } }, "ny_gdp_pcap_kd": { "title": "GDP per capita (constant 2015 US$)", "description_from_producer": "GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2015 U.S. dollars.\n\nStatistical concept and methodology: For more information, see the metadata for constant U.S. dollar GDP (NY.GDP.MKTP.KD) and total population (SP.POP.TOTL).", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$", "presentation": { "topic_tags": [ "Economic Growth" ] } }, "ny_gdp_pcap_kd_zg": { "title": "GDP per capita growth (annual %)", "description_from_producer": "Annual percentage growth rate of GDP per capita based on constant local currency. GDP per capita is gross domestic product divided by midyear population. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.\n\nStatistical concept and methodology: For more information, see the metadata for constant U.S. dollar GDP (NY.GDP.MKTP.KD) and total population (SP.POP.TOTL).", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%", "presentation": { "topic_tags": [ "Economic Growth" ] } }, "ny_gdp_pcap_kn": { "title": "GDP per capita (constant LCU)", "description_from_producer": "GDP per capita is gross domestic product divided by midyear population. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU", "presentation": { "topic_tags": [ "Economic Growth" ] } }, "ny_gdp_pcap_pp_cd": { "title": "GDP per capita, PPP (current international $)", "description_from_producer": "This indicator provides per capita values for gross domestic product (GDP) expressed in current international dollars converted by purchasing power parity (PPP) conversion factor.\n\nGDP is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. conversion factor is a spatial price deflator and currency converter that controls for price level differences between countries. Total population is a mid-year population based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.\n\nStatistical concept and methodology: Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.\n\nFor more information on underlying GDP in current international dollar, please refer to the metadata for \"GDP, PPP (current international $)\" [NY.GDP.MKTP.PP.CD].\nFor more information on underlying population, please refer to the metadata for \"total population\u201d [SP.POP.TOTL].\nFor the concept and methodology of PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$", "display": { "name": "GDP per capita", "numDecimalPlaces": 0 }, "presentation": { "title_public": "GDP per capita", "title_variant": "In current international $", "topic_tags": [ "Economic Growth" ] } }, "ny_gdp_pcap_pp_kd": { "title": "GDP per capita, PPP (constant 2017 international $)", "description_from_producer": "GDP per capita based on purchasing power parity (PPP). PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser's prices is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2017 international dollars.\n\nStatistical concept and methodology: For the concept and methodology of 2017 PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "international-$ in 2017 prices", "short_unit": "$", "display": { "name": "GDP per capita", "tolerance": 5, "isProjection": false, "numDecimalPlaces": 0 }, "presentation": { "title_public": "GDP per capita", "title_variant": "In constant 2017 international $", "topic_tags": [ "Economic Growth" ] } }, "ny_gdp_petr_rt_zs": { "title": "Oil rents (% of GDP)", "description_from_producer": "Oil rents are the difference between the value of crude oil production at regional prices and total costs of production.\n\nStatistical concept and methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ny_gdp_totl_rt_zs": { "title": "Total natural resources rents (% of GDP)", "description_from_producer": "Total natural resources rents are the sum of oil rents, natural gas rents, coal rents (hard and soft), mineral rents, and forest rents.\n\nStatistical concept and methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ny_gds_totl_cd": { "title": "Gross domestic savings (current US$)", "description_from_producer": "Gross domestic savings are calculated as GDP less final consumption expenditure (total consumption). Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_gds_totl_cn": { "title": "Gross domestic savings (current LCU)", "description_from_producer": "Gross domestic savings are calculated as GDP less final consumption expenditure (total consumption). Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_gds_totl_zs": { "title": "Gross domestic savings (% of GDP)", "description_from_producer": "Gross domestic savings are calculated as GDP less final consumption expenditure (total consumption).", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ny_gdy_totl_kn": { "title": "Gross domestic income (constant LCU)", "description_from_producer": "Gross domestic income is derived as the sum of GDP and the terms of trade adjustment. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ny_gnp_atls_cd": { "title": "GNI, Atlas method (current US$)", "description_from_producer": "GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current U.S. dollars. GNI, calculated in national currency, is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, a special Atlas method of conversion is used by the World Bank. This applies a conversion factor that averages the exchange rate for a given year and the two preceding years, adjusted for differences in rates of inflation between the country, and through 2000, the G-5 countries (France, Germany, Japan, the United Kingdom, and the United States). From 2001, these countries include the Euro area, Japan, the United Kingdom, and the United States.\n\nStatistical concept and methodology: In calculating GNI and GNI per capita in U.S. dollars for certain operational purposes, the World Bank uses the Atlas conversion factor. The purpose of the Atlas conversion factor is to reduce the impact of exchange rate fluctuations in the cross-country comparison of national incomes.\n\nThe Atlas conversion factor for any year is the average of a country's exchange rate (or alternative conversion factor) for that year and its exchange rates for the two preceding years, adjusted for the difference between the rate of inflation in the country and that in Japan, the United Kingdom, the United States, and the Euro area. A country's inflation rate is measured by the change in its GDP deflator.\n\nThe inflation rate for Japan, the United Kingdom, the United States, and the Euro area, representing international inflation, is measured by the change in the SDR deflator. (Special drawing rights, or SDRs, are the International Monetary Fund's unit of account.) The SDR deflator is calculated as a weighted average of these countries' GDP deflators in SDR terms, the weights being the amount of each country's currency in one SDR unit. Weights vary over time because both the composition of the SDR and the relative exchange rates for each currency change. The SDR deflator is calculated in SDR terms first and then converted to U.S. dollars using the SDR to dollar Atlas conversion factor. The Atlas conversion factor is then applied to a country's GNI. The resulting GNI in U.S. dollars is divided by the midyear population to derive GNI per capita.\n\nThe World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. An alternative conversion factor is used in the Atlas formula when the official exchange rate is judged to diverge by an exceptionally large margin from the rate effectively applied to domestic transactions of foreign currencies and traded products. This applies to only a small number of countries, as shown in the country-level metadata. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_gnp_mktp_cd": { "title": "GNI (current US$)", "description_from_producer": "GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_gnp_mktp_cn": { "title": "GNI (current LCU)", "description_from_producer": "GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_gnp_mktp_cn_ad": { "title": "GNI: linked series (current LCU)", "description_from_producer": "GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. This series has been linked to produce a consistent time series to counteract breaks in series over time due to changes in base years, source data and methodologies. Thus, it may not be comparable with other national accounts series in the database for historical years. Data are in local currency, at current prices.", "origins": [ { "producer": "World Bank based on data from multiple sources", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "ny_gnp_mktp_kd": { "title": "GNI (constant 2015 US$)", "description_from_producer": "GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant 2015 prices, expressed in U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ny_gnp_mktp_kd_zg": { "title": "GNI growth (annual %)", "description_from_producer": "GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "ny_gnp_mktp_kn": { "title": "GNI (constant LCU)", "description_from_producer": "GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ny_gnp_mktp_pp_cd": { "title": "GNI, PPP (current international $)", "description_from_producer": "This indicator provides values for gross national income (GNI. Formerly GNP) expressed in current international dollars converted by purchasing power parity (PPP) conversion factor.\nGross national income is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. PPP conversion factor is a spatial price deflator and currency converter that eliminates the effects of the differences in price levels between countries.\n\nFrom July 2020, \u201cGNI: linked series (current LCU)\u201d [NY.GNP.MKTP.CN.AD] is used as underlying GNI in local currency unit so that it\u2019s in line with time series of PPP conversion factors, which are extrapolated with linked deflators.\n\nStatistical concept and methodology: Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.\n\nFor more information on underlying GNI in local currency, please refer to the metadata for \"GNI (current LCU)\" [NY.GNP.MKTP.CN]. For more information on underlying PPP conversion factor, please refer to the metadata for \"PPP conversion factor, GDP (LCU per international $)\" [PA.NUS.PPP].\n\nFor the concept and methodology of PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$" }, "ny_gnp_mktp_pp_kd": { "title": "GNI, PPP (constant 2017 international $)", "description_from_producer": "PPP GNI (formerly PPP GNP) is gross national income (GNI) converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GNI as a U.S. dollar has in the United States. Gross national income is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant 2017 international dollars.\n\nStatistical concept and methodology: For the concept and methodology of 2017 PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "international-$ in 2017 prices", "short_unit": "$" }, "ny_gnp_pcap_cd": { "title": "GNI per capita, Atlas method (current US$)", "description_from_producer": "GNI per capita (formerly GNP per capita) is the gross national income, converted to U.S. dollars using the World Bank Atlas method, divided by the midyear population. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. GNI, calculated in national currency, is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, a special Atlas method of conversion is used by the World Bank. This applies a conversion factor that averages the exchange rate for a given year and the two preceding years, adjusted for differences in rates of inflation between the country, and through 2000, the G-5 countries (France, Germany, Japan, the United Kingdom, and the United States). From 2001, these countries include the Euro area, Japan, the United Kingdom, and the United States.\n\nStatistical concept and methodology: The World Bank uses Atlas method GNI per capita in U.S. dollars to classify countries for analytical purposes and to determine borrowing eligibility. For more information, see the metadata for Atlas method GNI in current U.S. dollars (NY.GNP.ATLS.CD) and total population (SP.POP.TOTL).", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_gnp_pcap_cn": { "title": "GNI per capita (current LCU)", "description_from_producer": "GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_gnp_pcap_kd": { "title": "GNI per capita (constant 2015 US$)", "description_from_producer": "GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant 2015 U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2015 US$", "short_unit": "$" }, "ny_gnp_pcap_kd_zg": { "title": "GNI per capita growth (annual %)", "description_from_producer": "Annual percentage growth rate of GNI per capita based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "ny_gnp_pcap_kn": { "title": "GNI per capita (constant LCU)", "description_from_producer": "GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ny_gnp_pcap_pp_cd": { "title": "GNI per capita, PPP (current international $)", "description_from_producer": "This indicator provides per capita values for gross national income (GNI. Formerly GNP) expressed in current international dollars converted by purchasing power parity (PPP) conversion factor.\nGNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. PPP conversion factor is a spatial price deflator and currency converter that eliminates the effects of the differences in price levels between countries.\n\nStatistical concept and methodology: Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.\n\nFor more information on underlying GNI in current international dollar, please refer to the metadata for \"GNI, PPP (current international $)\" [NY.GNP.MKTP.PP.CD]. For more information on underlying population, please refer to the metadata for \"total population\" [SP.POP.TOTL].\nFor the concept and methodology of PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$" }, "ny_gnp_pcap_pp_kd": { "title": "GNI per capita, PPP (constant 2017 international $)", "description_from_producer": "GNI per capita based on purchasing power parity (PPP). PPP GNI is gross national income (GNI) converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GNI as a U.S. dollar has in the United States. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant 2017 international dollars.\n\nStatistical concept and methodology: For the concept and methodology of 2017 PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "international-$ in 2017 prices", "short_unit": "$", "display": { "name": "GNI per capita", "numDecimalPlaces": 0 }, "presentation": { "title_public": "GNI per capita, PPP (constant 2017 international $)" } }, "ny_gns_ictr_cd": { "title": "Gross savings (current US$)", "description_from_producer": "Gross savings are calculated as gross national income less total consumption, plus net transfers. Data are in current U.S. dollars.\n\nStatistical concept and methodology: Gross savings represent the difference between disposable income and consumption and replace gross domestic savings, a concept used by the World Bank and included in World Development Indicators editions before 2006. The change was made to conform to SNA concepts and definitions.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_gns_ictr_cn": { "title": "Gross savings (current LCU)", "description_from_producer": "Gross savings are calculated as gross national income less total consumption, plus net transfers. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_gns_ictr_gn_zs": { "title": "Gross savings (% of GNI)", "description_from_producer": "Gross savings are calculated as gross national income less total consumption, plus net transfers.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GNI", "short_unit": "%" }, "ny_gns_ictr_zs": { "title": "Gross savings (% of GDP)", "description_from_producer": "Gross savings are calculated as gross national income less total consumption, plus net transfers.\n\nStatistical concept and methodology: Gross savings represent the difference between disposable income and consumption and replace gross domestic savings, a concept used by the World Bank and included in World Development Indicators editions before 2006. The change was made to conform to SNA concepts and definitions.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "ny_gsr_nfcy_cd": { "title": "Net primary income (Net income from abroad) (current US$)", "description_from_producer": "Net primary income includes the net labor income and net property and entrepreneurial income components of the SNA. Labor income covers compensation of employees paid to nonresident workers. Property and entrepreneurial income covers investment income from the ownership of foreign financial claims (interest, dividends, rent, etc.) and nonfinancial property income (patents, copyrights, etc.). Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_gsr_nfcy_cn": { "title": "Net primary income (Net income from abroad) (current LCU)", "description_from_producer": "Net primary income includes the net labor income and net property and entrepreneurial income components of the SNA. Labor income covers compensation of employees paid to nonresident workers. Property and entrepreneurial income covers investment income from the ownership of foreign financial claims (interest, dividends, rent, etc.) and nonfinancial property income (patents, copyrights, etc.). Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_gsr_nfcy_kn": { "title": "Net primary income (Net income from abroad) (constant LCU)", "description_from_producer": "Net primary income includes the net labor income and net property and entrepreneurial income components of the SNA. Labor income covers compensation of employees paid to nonresident workers. Property and entrepreneurial income covers investment income from the ownership of foreign financial claims (interest, dividends, rent, etc.) and nonfinancial property income (patents, copyrights, etc.). Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ny_tax_nind_cd": { "title": "Taxes less subsidies on products (current US$)", "description_from_producer": "Taxes less subsidies on products (net indirect taxes) are the sum of product taxes less subsidies. Product taxes are those taxes payable by producers that relate to the production, sale, purchase or use of the goods and services. Subsidies are grants on the current account made by general government to private enterprises and unincorporated public enterprises. The grants may take the form of payments to ensure a guaranteed price or to enable maintenance of prices of goods and services below costs of production, and other forms of assistance to producers. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_tax_nind_cn": { "title": "Taxes less subsidies on products (current LCU)", "description_from_producer": "Taxes less subsidies on products (net indirect taxes) are the sum of product taxes less subsidies. Product taxes are those taxes payable by producers that relate to the production, sale, purchase or use of the goods and services. Subsidies are grants on the current account made by general government to private enterprises and unincorporated public enterprises. The grants may take the form of payments to ensure a guaranteed price or to enable maintenance of prices of goods and services below costs of production, and other forms of assistance to producers. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_tax_nind_kn": { "title": "Taxes less subsidies on products (constant LCU)", "description_from_producer": "Taxes less subsidies on products (net indirect taxes) are the sum of product taxes less subsidies. Product taxes are those taxes payable by producers that relate to the production, sale, purchase or use of the goods and services. Subsidies are grants on the current account made by general government to private enterprises and unincorporated public enterprises. The grants may take the form of payments to ensure a guaranteed price or to enable maintenance of prices of goods and services below costs of production, and other forms of assistance to producers. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ny_trf_nctr_cd": { "title": "Net secondary income (Net current transfers from abroad) (current US$)", "description_from_producer": "Net secondary income (from abroad) comprises transfers of income between residents of the reporting country and the rest of the world that carry no provisions for repayment. Net secondary income is equal to the unrequited transfers of income from nonresidents to residents minus the unrequited transfers from residents to nonresidents. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "ny_trf_nctr_cn": { "title": "Net secondary income (Net current transfers from abroad) (current LCU)", "description_from_producer": "Net secondary income (from abroad) comprises transfers of income between residents of the reporting country and the rest of the world that carry no provisions for repayment. Net secondary income is equal to the unrequited transfers of income from nonresidents to residents minus the unrequited transfers from residents to nonresidents. Data are in current local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current LCU" }, "ny_trf_nctr_kn": { "title": "Net secondary income (Net current transfers from abroad) (constant LCU)", "description_from_producer": "Net secondary income comprises transfers of income between residents of the reporting country and the rest of the world that carry no provisions for repayment. Net current transfers from abroad is equal to the unrequited transfers of income from nonresidents to residents minus the unrequited transfers from residents to nonresidents. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "ny_ttf_gnfs_kn": { "title": "Terms of trade adjustment (constant LCU)", "description_from_producer": "The terms of trade effect equals capacity to import less exports of goods and services in constant prices. Data are in constant local currency.", "origins": [ { "producer": "World Bank and OECD", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant LCU" }, "pa_nus_atls": { "title": "DEC alternative conversion factor (LCU per US$)", "description_from_producer": "The DEC alternative conversion factor is the underlying annual exchange rate used for the World Bank Atlas method. As a rule, it is the official exchange rate reported in the IMF's International Financial Statistics (line rf). Exceptions arise where further refinements are made by World Bank staff. It is expressed in local currency units per U.S. dollar.\n\nStatistical concept and methodology: The World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. In certain countries, multiple or dual exchange rate activity exists and must be accounted for appropriately in underlying statistics. Doing so better reflects economic reality and leads to more accurate cross-country comparisons and country classifications by income level. Consequently, an alternative conversion factor is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate effectively applied to domestic transactions of foreign currencies and traded products. This applies to only a small number of countries, as shown in the country-level metadata. An alternative conversion factor is also used when the period covered by national accounts differs from the calendar year and the alternative conversion factor will then cover the same period. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors.", "origins": [ { "producer": "International Monetary Fund and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "LCU per US$", "short_unit": "LCU" }, "pa_nus_fcrf": { "title": "Official exchange rate (LCU per US$, period average)", "description_from_producer": "Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).\n\nLimitations and exceptions: Official or market exchange rates are often used to convert economic statistics in local currencies to a common currency in order to make comparisons across countries. Since market rates reflect at best the relative prices of tradable goods, the volume of goods and services that a U.S. dollar buys in the United States may not correspond to what a U.S. dollar converted to another country's currency at the official exchange rate would buy in that country, particularly when nontradable goods and services account for a significant share of a country's output. An alternative exchange rate - the purchasing power parity (PPP) conversion factor - is preferred because it reflects differences in price levels for both tradable and nontradable goods and services and therefore provides a more meaningful comparison of real output.\n\nStatistical concept and methodology: The exchange rate is the price of one currency in terms of another. Official exchange rates and exchange rate arrangements are established by governments. Other exchange rates recognized by governments include market rates, which are determined largely by legal market forces, and for countries with multiple exchange arrangements, principal rates, secondary rates, and tertiary rates.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "LCU per US$, period average", "short_unit": "LCU" }, "pa_nus_ppp": { "title": "PPP conversion factor, GDP (LCU per international $)", "description_from_producer": "Purchasing power parity (PPP) conversion factor is a spatial price deflator and currency converter that controls for price level differences between countries, thereby allowing volume comparisons of gross domestic product (GDP) and its expenditure components. This conversion factor is for GDP.\n\nLimitations and exceptions: Global PPP estimates provided by ICP are produced by the ICP Global Office and regional implementing agencies, based on data supplied by participating countries, and in accordance with the methodology recommended by the ICP Technical Advisory Group and approved by the ICP Governing Board. As such, these results are not produced by participating countries as part of their national official statistics.\n\nPPPs are not recommended use: As a precise measure to establish strict rankings of countries | As a means of constructing national growth rates | As a measure to generate output and productivity comparisons by industry | As an indicator of the undervaluation or overvaluation of currencies | As an equilibrium exchange rate.\n\nStatistical concept and methodology: PPPs are both currency conversion factors and spatial price indexes. PPPs convert different currencies to a common currency and, in the process of conversion, equalize their purchasing power by controlling differences in price levels between countries.\n\nTypically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.\n\nThe International Comparison Program (ICP) estimates PPPs for the world\u2019s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The most recent 2017 ICP comparison covered 176 countries, including 47 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model.\n\nICP estimated PPPs cover years from 2011 to 2017. WDI extrapolates 2011 PPPs for years earlier years, and 2017 PPPs for later years. Description of WDI extrapolation approach is available here: https://datahelpdesk.worldbank.org/knowledgebase/articles/665452-how-do-you-extrapolate-the-ppp-conversion-factors\n\nFor the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations\u2019 databases. For Eurostat-OECD PPP Programme, please refer to the following websites.\n(http://www.oecd.org/sdd/prices-ppp/)\n(https://ec.europa.eu/eurostat/web/purchasing-power-parities/overview)\n\nFor more information on the ICP and PPPs, please refer to the ICP website at https://www.worldbank.org/en/programs/icp.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "LCU per international $", "short_unit": "LCU" }, "pa_nus_pppc_rf": { "title": "Price level ratio of PPP conversion factor (GDP) to market exchange rate", "description_from_producer": "Price level ratio is the ratio of a purchasing power parity (PPP) conversion factor to an exchange rate. It provides a measure of the differences in price levels between countries by indicating the number of units of the common currency needed to buy the same volume of the aggregation level in each country. At the level of GDP, they provide a measure of the differences in the general price levels of countries.\n\nStatistical concept and methodology: For more information on underlying GDP in current international dollar, please refer to the metadata for \"GDP, PPP (current international $)\" [NY.GDP.MKTP.PP.CD]. For more information on market exchange reate, please refer to the metadata for \"DEC alternative conversion factor (LCU per US$)\" [PA.NUS.ATLS].\nFor the concept and methodology of PPP, please refer to the International Comparison Program (ICP)\u2019s website (https://www.worldbank.org/en/programs/icp).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "GDP", "short_unit": "GDP" }, "pa_nus_prvt_pp": { "title": "PPP conversion factor, private consumption (LCU per international $)", "description_from_producer": "Purchasing power parity (PPP) conversion factor is a spatial price deflator and currency converter that controls for price level differences between countries, thereby allowing volume comparisons of gross domestic product (GDP) and its expenditure components. This conversion factor is for household final consumption expenditure.\n\nLimitations and exceptions: Global PPP estimates provided by ICP are produced by the ICP Global Office and regional implementing agencies, based on data supplied by participating countries, and in accordance with the methodology recommended by the ICP Technical Advisory Group and approved by the ICP Governing Board. As such, these results are not produced by participating countries as part of their national official statistics.\n\nPPPs are not recommended use: As a precise measure to establish strict rankings of countries | As a means of constructing national growth rates | As a measure to generate output and productivity comparisons by industry | As an indicator of the undervaluation or overvaluation of currencies | As an equilibrium exchange rate.\n\nStatistical concept and methodology: PPPs are both currency conversion factors and spatial price indexes. PPPs convert different currencies to a common currency and, in the process of conversion, equalize their purchasing power by controlling differences in price levels between countries.\n\nTypically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.\n\nThe International Comparison Program (ICP) estimates PPPs for the world\u2019s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The most recent 2017 ICP comparison covered 176 countries, including 47 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model.\n\nICP estimated PPPs cover years from 2011 to 2017. WDI extrapolates 2011 PPPs for years earlier years, and 2017 PPPs for later years. Description of WDI extrapolation approach is available here: https://datahelpdesk.worldbank.org/knowledgebase/articles/665452-how-do-you-extrapolate-the-ppp-conversion-factors\n\nFor the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations\u2019 databases. For Eurostat-OECD PPP Programme, please refer to the following websites.\n(http://www.oecd.org/sdd/prices-ppp/)\n(https://ec.europa.eu/eurostat/web/purchasing-power-parities/overview)\n\nFor more information on the ICP and PPPs, please refer to the ICP website at https://www.worldbank.org/en/programs/icp.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "LCU per international $", "short_unit": "LCU" }, "pv_est": { "title": "Political Stability and Absence of Violence/Terrorism: Estimate", "description_from_producer": "Political Stability and Absence of Violence/Terrorism measures perceptions of the likelihood of political instability and/or politically-motivated violence, including terrorism. Estimate gives the country's score on the aggregate indicator, in units of a standard normal distribution, i.e. ranging from approximately -2.5 to 2.5.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "pv_no_src": { "title": "Political Stability and Absence of Violence/Terrorism: Number of Sources", "description_from_producer": "Political Stability and Absence of Violence/Terrorism measures perceptions of the likelihood of political instability and/or politically-motivated violence, including terrorism. Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "pv_per_rnk": { "title": "Political Stability and Absence of Violence/Terrorism: Percentile Rank", "description_from_producer": "Political Stability and Absence of Violence/Terrorism measures perceptions of the likelihood of political instability and/or politically-motivated violence, including terrorism. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "pv_per_rnk_lower": { "title": "Political Stability and Absence of Violence/Terrorism: Percentile Rank, Lower Bound of 90% Confidence Interval", "description_from_producer": "Political Stability and Absence of Violence/Terrorism measures perceptions of the likelihood of political instability and/or politically-motivated violence, including terrorism. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "pv_per_rnk_upper": { "title": "Political Stability and Absence of Violence/Terrorism: Percentile Rank, Upper Bound of 90% Confidence Interval", "description_from_producer": "Political Stability and Absence of Violence/Terrorism measures perceptions of the likelihood of political instability and/or politically-motivated violence, including terrorism. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "pv_std_err": { "title": "Political Stability and Absence of Violence/Terrorism: Standard Error", "description_from_producer": "Political Stability and Absence of Violence/Terrorism measures perceptions of the likelihood of political instability and/or politically-motivated violence, including terrorism. Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "px_rex_reer": { "title": "Real effective exchange rate index (2010 = 100)", "description_from_producer": "Real effective exchange rate is the nominal effective exchange rate (a measure of the value of a currency against a weighted average of several foreign currencies) divided by a price deflator or index of costs.\n\nLimitations and exceptions: Because of conceptual and data limitations, changes in real effective exchange rates should be interpreted with caution.\n\nStatistical concept and methodology: The real effective exchange rate is a nominal effective exchange rate index adjusted for relative movements in national price or cost indicators of the home country, selected countries, and the euro area. A nominal effective exchange rate index is the ratio (expressed on the base 2010 = 100) of an index of a currency's period-average exchange rate to a weighted geometric average of exchange rates for currencies of selected countries and the euro area. For most high-income countries weights are derived from industrial country trade in manufactured goods. Data are compiled from the nominal effective exchange rate index and a cost indicator of relative normalized unit labor costs in manufacturing. For selected other countries the nominal effective exchange rate index is based on manufactured goods and primary products trade with partner or competitor countries. For these countries the real effective exchange rate index is the nominal index adjusted for relative changes in consumer prices; an increase represents an appreciation of the local currency.", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2010 = 100" }, "rl_est": { "title": "Rule of Law: Estimate", "description_from_producer": "Rule of Law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. Estimate gives the country's score on the aggregate indicator, in units of a standard normal distribution, i.e. ranging from approximately -2.5 to 2.5.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rl_no_src": { "title": "Rule of Law: Number of Sources", "description_from_producer": "Rule of Law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rl_per_rnk": { "title": "Rule of Law: Percentile Rank", "description_from_producer": "Rule of Law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rl_per_rnk_lower": { "title": "Rule of Law: Percentile Rank, Lower Bound of 90% Confidence Interval", "description_from_producer": "Rule of Law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rl_per_rnk_upper": { "title": "Rule of Law: Percentile Rank, Upper Bound of 90% Confidence Interval", "description_from_producer": "Rule of Law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rl_std_err": { "title": "Rule of Law: Standard Error", "description_from_producer": "Rule of Law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rq_est": { "title": "Regulatory Quality: Estimate", "description_from_producer": "Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Estimate gives the country's score on the aggregate indicator, in units of a standard normal distribution, i.e. ranging from approximately -2.5 to 2.5.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rq_no_src": { "title": "Regulatory Quality: Number of Sources", "description_from_producer": "Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. umber of sources indicates the number of underlying data sources on which the aggregate estimate is based.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rq_per_rnk": { "title": "Regulatory Quality: Percentile Rank", "description_from_producer": "Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rq_per_rnk_lower": { "title": "Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval", "description_from_producer": "Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rq_per_rnk_upper": { "title": "Regulatory Quality: Percentile Rank, Upper Bound of 90% Confidence Interval", "description_from_producer": "Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "rq_std_err": { "title": "Regulatory Quality: Standard Error", "description_from_producer": "Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_adt_1524_lt_fe_zs": { "title": "Literacy rate, youth female (% of females ages 15-24)", "description_from_producer": "Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.\n\nLimitations and exceptions: In practice, literacy is difficult to measure. Estimating literacy rates requires census or survey measurements under controlled conditions. Many countries report the number of literate people from self-reported data. Some use educational attainment data as a proxy but apply different lengths of school attendance or levels of completion. Ant there is a trend among recent national and international surveys toward using a direct reading test of literacy skills. Because definitions and methods of data collection differ across countries, data should be used cautiously.\n\nStatistical concept and methodology: Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.\n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of females ages 15-24", "short_unit": "%" }, "se_adt_1524_lt_fm_zs": { "title": "Literacy rate, youth (ages 15-24), gender parity index (GPI)", "description_from_producer": "Gender parity index for youth literacy rate is the ratio of females to males ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.\n\nLimitations and exceptions: In practice, literacy is difficult to measure. Estimating literacy rates requires census or survey measurements under controlled conditions. Many countries report the number of literate people from self-reported data. Some use educational attainment data as a proxy but apply different lengths of school attendance or levels of completion. Ant there is a trend among recent national and international surveys toward using a direct reading test of literacy skills. Because definitions and methods of data collection differ across countries, data should be used cautiously.\n\nStatistical concept and methodology: This indicator is calculated by dividing female youth literacy rate by male youth literacy rate.\n\nLiteracy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.\n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "GPI", "short_unit": "GPI" }, "se_adt_1524_lt_ma_zs": { "title": "Literacy rate, youth male (% of males ages 15-24)", "description_from_producer": "Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.\n\nLimitations and exceptions: In practice, literacy is difficult to measure. Estimating literacy rates requires census or survey measurements under controlled conditions. Many countries report the number of literate people from self-reported data. Some use educational attainment data as a proxy but apply different lengths of school attendance or levels of completion. Ant there is a trend among recent national and international surveys toward using a direct reading test of literacy skills. Because definitions and methods of data collection differ across countries, data should be used cautiously.\n\nStatistical concept and methodology: Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.\n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of males ages 15-24", "short_unit": "%" }, "se_adt_1524_lt_zs": { "title": "Literacy rate, youth total (% of people ages 15-24)", "description_from_producer": "Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.\n\nLimitations and exceptions: In practice, literacy is difficult to measure. Estimating literacy rates requires census or survey measurements under controlled conditions. Many countries report the number of literate people from self-reported data. Some use educational attainment data as a proxy but apply different lengths of school attendance or levels of completion. Ant there is a trend among recent national and international surveys toward using a direct reading test of literacy skills. Because definitions and methods of data collection differ across countries, data should be used cautiously.\n\nStatistical concept and methodology: Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.\n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of people ages 15-24", "short_unit": "%" }, "se_adt_litr_fe_zs": { "title": "Literacy rate, adult female (% of females ages 15 and above)", "description_from_producer": "Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.\n\nLimitations and exceptions: In practice, literacy is difficult to measure. Estimating literacy rates requires census or survey measurements under controlled conditions. Many countries report the number of literate people from self-reported data. Some use educational attainment data as a proxy but apply different lengths of school attendance or levels of completion. Ant there is a trend among recent national and international surveys toward using a direct reading test of literacy skills. Because definitions and methods of data collection differ across countries, data should be used cautiously.\n\nStatistical concept and methodology: Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.\n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of females ages 15 and above", "short_unit": "%" }, "se_adt_litr_ma_zs": { "title": "Literacy rate, adult male (% of males ages 15 and above)", "description_from_producer": "Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.\n\nLimitations and exceptions: In practice, literacy is difficult to measure. Estimating literacy rates requires census or survey measurements under controlled conditions. Many countries report the number of literate people from self-reported data. Some use educational attainment data as a proxy but apply different lengths of school attendance or levels of completion. Ant there is a trend among recent national and international surveys toward using a direct reading test of literacy skills. Because definitions and methods of data collection differ across countries, data should be used cautiously.\n\nStatistical concept and methodology: Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.\n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of males ages 15 and above", "short_unit": "%" }, "se_adt_litr_zs": { "title": "Literacy rate, adult total (% of people ages 15 and above)", "description_from_producer": "Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.\n\nLimitations and exceptions: In practice, literacy is difficult to measure. Estimating literacy rates requires census or survey measurements under controlled conditions. Many countries report the number of literate people from self-reported data. Some use educational attainment data as a proxy but apply different lengths of school attendance or levels of completion. Ant there is a trend among recent national and international surveys toward using a direct reading test of literacy skills. Because definitions and methods of data collection differ across countries, data should be used cautiously.\n\nStatistical concept and methodology: Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.\n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of people ages 15 and above", "short_unit": "%" }, "se_com_durs": { "title": "Compulsory education, duration (years)", "description_from_producer": "Duration of compulsory education is the number of years that children are legally obliged to attend school.\n\nStatistical concept and methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Aggregate data are based on World Bank estimates.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "years", "short_unit": "years" }, "se_enr_prim_fm_zs": { "title": "School enrollment, primary (gross), gender parity index (GPI)", "description_from_producer": "Gender parity index for gross enrollment ratio in primary education is the ratio of girls to boys enrolled at primary level in public and private schools.\n\nStatistical concept and methodology: This indicator is calculated by dividing female gross enrollment ratio in primary education by male gross enrollment ratio in primary education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "GPI", "short_unit": "GPI" }, "se_enr_prsc_fm_zs": { "title": "School enrollment, primary and secondary (gross), gender parity index (GPI)", "description_from_producer": "Gender parity index for gross enrollment ratio in primary and secondary education is the ratio of girls to boys enrolled at primary and secondary levels in public and private schools.\n\nStatistical concept and methodology: This indicator is calculated by dividing female gross enrollment ratio in primary and secondary education by male gross enrollment ratio in primary and secondary education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "GPI", "short_unit": "GPI" }, "se_enr_seco_fm_zs": { "title": "School enrollment, secondary (gross), gender parity index (GPI)", "description_from_producer": "Gender parity index for gross enrollment ratio in secondary education is the ratio of girls to boys enrolled at secondary level in public and private schools.\n\nStatistical concept and methodology: This indicator is calculated by dividing female gross enrollment ratio in secondary education by male gross enrollment ratio in secondary education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "GPI", "short_unit": "GPI" }, "se_enr_tert_fm_zs": { "title": "School enrollment, tertiary (gross), gender parity index (GPI)", "description_from_producer": "Gender parity index for gross enrollment ratio in tertiary education is the ratio of women to men enrolled at tertiary level in public and private schools.\n\nStatistical concept and methodology: This indicator is calculated by dividing female gross enrollment ratio in tertiary education by male gross enrollment ratio in tertiary education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "GPI", "short_unit": "GPI" }, "se_lpv_prim": { "title": "Learning poverty: Share of Children at the End-of-Primary age below minimum reading proficiency adjusted by Out-of-School Children (%)", "description_from_producer": "The share of 10-year-olds who cannot read and understand a short passage of age-appropriate material\u2014in other words, those who are below the \u201cminimum proficiency\u201d threshold for reading. This measure is defined as the union of two deprivations: 1) schooling deprivation and 2) learning deprivation. A child is considered schooling-deprived (SD) if he or she is of primary school age and out-of-school. The dimension of learning deprivation (LD) applies only for children in school, and identifies those pupils who are below the minimum proficiency level (MPL) for reading, as defined by the Global Alliance to Monitor Learning (GAML), measured in standard learning assessments, and reported in the context of the SDG 4.1.1b monitoring. This \u201cunion approach\u201d to measurement reflects the choice that, as presented in the SDGs, all age 10 children must be both in school and learning. The final learning poverty measure combines the two dimensions in a single indicator using the following formula: LP = SD + [(1-SD) x LD]\n\nLimitations and exceptions: The construct of \u201call children reading by age 10\u201d is an ideal that embodies normative statements about both learning and access. To achieve it, not only should all children be reading proficiently after 3 full years in primary education, but they should also have entered school at age 6 or 7.\nBy contrast, the actual indicators used to measure learning poverty are based on grade rather than age. Since the assessments are of 4th- through 6th-graders, the children tested will have had at least 3 to 5 years in school to reach what, according to the ideal, should 10 be an age-10 minimum proficiency, or even the entire primary-school-age segment for the out-of-school indicator.\nDue to different assessment availability within and between countries, data comparability, both within countries over time and across countries still poses a significant challenge. The additional out of school component further limits comparability.\nThe learning poverty indicator is based on data covering four-fifths of children at the end of primary school. In other words, a little more than 80 percent of children in low- and middle-income countries live in a country with at least one learning assessment at the end of primary, carried out in the past 9 years. For regional and global aggregates, weighted imputations affect regions with less data coverage. The major gaps are concentrated in countries where the learning crisis is most acute. Less than half of children in Sub-Saharan Africa live in a country with a National Large-Scale Learning Assessment (NLSA) or a international of regional large-scale learning assessment (ILSA or RLSA) of adequate quality to be used for this purpose.\nThis extensive coverage became possible only in recent years, with the progress in measuring learning in countries and the GAML\u2019s efforts to establish comparability, which has made possible the construction of a global indicator based on harmonized proficiency levels. Future efforts by coalition organizations are also ensuring more flexible assessment options are available for expanding data availability for countries, such as the Assessment of Minimum Proficiency Levels (AMPL) and policy linking exercises led by UIS.\n\nStatistical concept and methodology: The learning poverty indicator brings together schooling and learning indicators. It starts with the share of children in school who haven\u2019t achieved minimum reading proficiency (Learning Deprived) and adjusts it by the proportion of children who are out of school (Schooling Deprived).\nFormally, Learning Poverty is calculated as: [LD* (1-SD)] + [1 * SD]\nwhere LP = Learning poverty; LD = Learning deprivation or the share of children at the end of primary who read at below the minimum proficiency level, as defined by the Global Alliance to Monitor Learning (GAML) in the context of the SDG 4.1.1 monitoring; SD = Schooling deprivation or the share of primary-school-age children who are out-of-school (OOS) and in which all OOS are regarded as being below the minimum proficiency level.\nBecause out-of-school children are treated as non-proficient in reading, learning poverty will always be higher than the share of children in school who haven't achieved minimum reading proficiency. For countries with a very low schooling deprivation, the learning deprivation value will be very close to Learning Poverty.\nEstimating the current level of global and regional learning poverty requires deciding how to define \u201ccurrent.\u201d We include results of assessments within four years before or after a set anchor year. This decision is driven by data availability. International and regional large-scale learning assessments used for SDG 4.1.1b reporting are carried out only every 3 to 4 years. And even where assessments have been carried out recently, there is a lag of a couple of years before the data are available. This band is intended as a moving window. In the original 2019 release, the anchor year used was 2015 (Assessments between 2011 and 2019 are included in the learning poverty estimate). In the 2022 Global Update, the anchor year was moved to 2019 (assessments between 2015 and 2023 are included).\nAggregations for each region comprise the average learning poverty of countries with available data, weighted by their population ages 10\u201314 years old. To obtain a global estimate, we weight the regional aggregations by the 10\u201314-year-old population regardless of data availability. This is equivalent to imputing missing country data using regional values.", "origins": [ { "producer": "World Bank and UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_lpv_prim_fe": { "title": "Learning poverty: Share of Female Children at the End-of-Primary age below minimum reading proficiency adjusted by Out-of-School Children (%)", "description_from_producer": "The share of female 10-year-olds who cannot read and understand a short passage of age-appropriate material\u2014in other words, those who are below the \u201cminimum proficiency\u201d threshold for reading. This measure is defined as the union of two deprivations: 1) schooling deprivation and 2) learning deprivation. A child is considered schooling-deprived (SD) if he or she is of primary school age and out-of-school. The dimension of learning deprivation (LD) applies only for children in school, and identifies those pupils who are below the minimum proficiency level (MPL) for reading, as defined by the Global Alliance to Monitor Learning (GAML), measured in standard learning assessments, and reported in the context of the SDG 4.1.1b monitoring. This \u201cunion approach\u201d to measurement reflects the choice that, as presented in the SDGs, all age 10 children must be both in school and learning. The final learning poverty measure combines the two dimensions in a single indicator using the following formula: LP = SD + [(1-SD) x LD]\n\nLimitations and exceptions: The construct of \u201call children reading by age 10\u201d is an ideal that embodies normative statements about both learning and access. To achieve it, not only should all children be reading proficiently after 3 full years in primary education, but they should also have entered school at age 6 or 7.\nBy contrast, the actual indicators used to measure learning poverty are based on grade rather than age. Since the assessments are of 4th- through 6th-graders, the children tested will have had at least 3 to 5 years in school to reach what, according to the ideal, should 10 be an age-10 minimum proficiency, or even the entire primary-school-age segment for the out-of-school indicator.\nDue to different assessment availability within and between countries, data comparability, both within countries over time and across countries still poses a significant challenge. The additional out of school component further limits comparability.\nThe learning poverty indicator is based on data covering four-fifths of children at the end of primary school. In other words, a little more than 80 percent of children in low- and middle-income countries live in a country with at least one learning assessment at the end of primary, carried out in the past 9 years. For regional and global aggregates, weighted imputations affect regions with less data coverage. The major gaps are concentrated in countries where the learning crisis is most acute. Less than half of children in Sub-Saharan Africa live in a country with a National Large-Scale Learning Assessment (NLSA) or a international of regional large-scale learning assessment (ILSA or RLSA) of adequate quality to be used for this purpose.\nThis extensive coverage became possible only in recent years, with the progress in measuring learning in countries and the GAML\u2019s efforts to establish comparability, which has made possible the construction of a global indicator based on harmonized proficiency levels. Future efforts by coalition organizations are also ensuring more flexible assessment options are available for expanding data availability for countries, such as the Assessment of Minimum Proficiency Levels (AMPL) and policy linking exercises led by UIS.\n\nStatistical concept and methodology: The learning poverty indicator brings together schooling and learning indicators. It starts with the share of children in school who haven\u2019t achieved minimum reading proficiency (Learning Deprived) and adjusts it by the proportion of children who are out of school (Schooling Deprived).\nFormally, Learning Poverty is calculated as: [LD* (1-SD)] + [1 * SD]\nwhere LP = Learning poverty; LD = Learning deprivation or the share of children at the end of primary who read at below the minimum proficiency level, as defined by the Global Alliance to Monitor Learning (GAML) in the context of the SDG 4.1.1 monitoring; SD = Schooling deprivation or the share of primary-school-age children who are out-of-school (OOS) and in which all OOS are regarded as being below the minimum proficiency level.\nBecause out-of-school children are treated as non-proficient in reading, learning poverty will always be higher than the share of children in school who haven't achieved minimum reading proficiency. For countries with a very low schooling deprivation, the learning deprivation value will be very close to Learning Poverty.\nEstimating the current level of global and regional learning poverty requires deciding how to define \u201ccurrent.\u201d We include results of assessments within four years before or after a set anchor year. This decision is driven by data availability. International and regional large-scale learning assessments used for SDG 4.1.1b reporting are carried out only every 3 to 4 years. And even where assessments have been carried out recently, there is a lag of a couple of years before the data are available. This band is intended as a moving window. In the original 2019 release, the anchor year used was 2015 (Assessments between 2011 and 2019 are included in the learning poverty estimate). In the 2022 Global Update, the anchor year was moved to 2019 (assessments between 2015 and 2023 are included).\nAggregations for each region comprise the average learning poverty of countries with available data, weighted by their population ages 10\u201314 years old. To obtain a global estimate, we weight the regional aggregations by the 10\u201314-year-old population regardless of data availability. This is equivalent to imputing missing country data using regional values.", "origins": [ { "producer": "World Bank and UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_lpv_prim_ld": { "title": "Pupils below minimum reading proficiency at end of primary (%). Low GAML threshold", "description_from_producer": "The share of pupils at the end of primary schooling who are below the minimum proficiency level (MPL) for reading or learning deprived. The MPL in reading at the end of primary is defined by the Global Alliance to Monitor Learning (GAML), measured in standard learning assessments, and reported in the context of the SDG 4.1.1b monitoring. It is \u201cStudents independently and fluently read simple, short narrative and expository texts. They locate explicitly-stated information. They interpret and give some explanations about the key ideas in these texts. They provide simple, personal opinions or judgements about the information, events and characters in a text.\u201d (UIS and GAML 2019). In other words, a child \u201cattaining\u201d minimum proficiency has the ability to read and understand a short passage of age-appropriate material, whether a simple story or non-fiction narrative of a few paragraphs. In addition to this nutshell statement, the GAML has also proposed a common terminology to describe classifications in the context of the MPL. This is a critical first step toward linking cross-national and national learning assessments with a common benchmark.\n\nLimitations and exceptions: The process of equating proficiency levels on different assessments to the GAML definition is not straightforward. Even the long-running regional assessment initiatives like PASEC (West and Central Africa) and LLECE (Latin America and the Caribbean) use different definitions and a different number of levels than other assessments like PIRLS, and those might not even be the same over time. Their test development methodologies and test administration procedures also vary. Moreover, because not all countries participate in global or regional assessments, for some major countries we rely on their interim reporting using their national assessments; equating these assessments is even more challenging. UIS and the World Bank have mapped how proficiency levels between assessment can equate to one another, but they are not strictly comparable.\nAmong the differences across assessments, one important point concerns the age at which children are tested. The reference age for our exercise is age 10. However, all learning assessments used in this analysis are sampled based on specific grades rather than age. PIRLS and TIMSS are administered in Grade 4, meaning that the average student assessed is indeed 10 years old, but this is not the case for the regional assessments. PASEC and LLECE are administered in Grade 6, so the average age in those assessments is 12.8 and 12.4, respectively. National assessments are administered at different grades, so to incorporate those assessments, we chose for each country the grade between 4 and 6 (inclusive) for which relevant and reliable data were available. This is consistent with the SDG monitoring by UIS and GAML, which lists \u201cEnd of Primary (or Grades 4 to 6)\u201d as the relevant age category for the end-of-primary students (SDG 4.1.1b).\nIn some cases, National Learning Assessments that have not been policy linked are used for learning poverty, if country teams and experts determine that an assessment is of sufficiently quality or has undertaken steps to align their assessments with the Global Proficiency Framework. They will often be reported as interim learning poverty indicators, as they are not fully aligned with SDG 4.1.1b.\n\nStatistical concept and methodology: Learning assessments used to calculate Learning Poverty have a minimum proficiency level (MPL) benchmarked by Global Alliance to Monitor Learning (GAML) under the leadership of the UNESCO Institute of Statistics (UIS), which occurred within the reporting window. To operationalize this concept, the current SDG monitoring process is followed by defining \u201cproficiency\u201d as reaching at least the Low International Benchmark on the international PIRLS literacy assessment.\nPIRLS is the major global primary-age assessment focused on reading, and if all countries participated in it, the task of constructing global estimates of minimum proficiency would be trivial, as it would require aggregating results from a single cross-national assessment. However, most countries participating in PIRLS are high-income, and only a small minority of low- and middle-income countries participate in the assessment. One of the main contributions of the GAML process is that it has overcome this data gap by benchmarking several major cross-national assessments\u2014and increasingly national learning assessments as well\u2014against the standard.\nThe MPL for each learning assessment is used to calculate the reading proficiency rate for that country, which is the share of students scoring at or above the minimum proficiency level, and conversely to calculate the learning deprivation.\nThe Proficiency and Grade Levels used for each assessment is as follows: PIRLS (grade 4) - Level 2 (Low international benchmark, 400 points); TIMSS (grade 4) - Level 2 (Low international benchmark, 400 points); LLECE (SERCE, grade 6) - Level 3 (513.66 points); PASEC (grades 5 and 6) - Level 4 (595.1 points); SEA-PLM (grade 5) - Level 6 and above; National Learning Assessment (grade 4, 5 and 6) - Varies by country.\nWhen a given country had administered multiple types of learning assessments, a hierarchy is applied in the order listed below to ensure best comparability across countries: International or Regional Learning Assessment for Reading (PIRLS, LLECE, PASEC, SEA-PLM) > TIMSS Science > Statistical or Pairwise Linking Exercises > AMPL-bs, Policy Linked National Learning Assessments or Policy Linked Service Delivery Indicators (SDIs) > Non-Policy Linked NLAs (Interim Reporting).\nNote that as the GAML and joint coalitions continue their efforts to improve learning data coverage, the hierarchy may be revised.", "origins": [ { "producer": "World Bank and UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_lpv_prim_ld_fe": { "title": "Female pupils below minimum reading proficiency at end of primary (%). Low GAML threshold", "description_from_producer": "The share of female pupils at the end of primary schooling who are below the minimum proficiency level (MPL) for reading or learning deprived. The MPL in reading at the end of primary is defined by the Global Alliance to Monitor Learning (GAML), measured in standard learning assessments, and reported in the context of the SDG 4.1.1b monitoring. It is \u201cStudents independently and fluently read simple, short narrative and expository texts. They locate explicitly-stated information. They interpret and give some explanations about the key ideas in these texts. They provide simple, personal opinions or judgements about the information, events and characters in a text.\u201d (UIS and GAML 2019). In other words, a child \u201cattaining\u201d minimum proficiency has the ability to read and understand a short passage of age-appropriate material, whether a simple story or non-fiction narrative of a few paragraphs. In addition to this nutshell statement, the GAML has also proposed a common terminology to describe classifications in the context of the MPL. This is a critical first step toward linking cross-national and national learning assessments with a common benchmark.\n\nLimitations and exceptions: The process of equating proficiency levels on different assessments to the GAML definition is not straightforward. Even the long-running regional assessment initiatives like PASEC (West and Central Africa) and LLECE (Latin America and the Caribbean) use different definitions and a different number of levels than other assessments like PIRLS, and those might not even be the same over time. Their test development methodologies and test administration procedures also vary. Moreover, because not all countries participate in global or regional assessments, for some major countries we rely on their interim reporting using their national assessments; equating these assessments is even more challenging. UIS and the World Bank have mapped how proficiency levels between assessment can equate to one another, but they are not strictly comparable.\nAmong the differences across assessments, one important point concerns the age at which children are tested. The reference age for our exercise is age 10. However, all learning assessments used in this analysis are sampled based on specific grades rather than age. PIRLS and TIMSS are administered in Grade 4, meaning that the average student assessed is indeed 10 years old, but this is not the case for the regional assessments. PASEC and LLECE are administered in Grade 6, so the average age in those assessments is 12.8 and 12.4, respectively. National assessments are administered at different grades, so to incorporate those assessments, we chose for each country the grade between 4 and 6 (inclusive) for which relevant and reliable data were available. This is consistent with the SDG monitoring by UIS and GAML, which lists \u201cEnd of Primary (or Grades 4 to 6)\u201d as the relevant age category for the end-of-primary students (SDG 4.1.1b).\nIn some cases, National Learning Assessments that have not been policy linked are used for learning poverty, if country teams and experts determine that an assessment is of sufficiently quality or has undertaken steps to align their assessments with the Global Proficiency Framework. They will often be reported as interim learning poverty indicators, as they are not fully aligned with SDG 4.1.1b.\n\nStatistical concept and methodology: Learning assessments used to calculate Learning Poverty have a minimum proficiency level (MPL) benchmarked by Global Alliance to Monitor Learning (GAML) under the leadership of the UNESCO Institute of Statistics (UIS), which occurred within the reporting window. To operationalize this concept, the current SDG monitoring process is followed by defining \u201cproficiency\u201d as reaching at least the Low International Benchmark on the international PIRLS literacy assessment.\nPIRLS is the major global primary-age assessment focused on reading, and if all countries participated in it, the task of constructing global estimates of minimum proficiency would be trivial, as it would require aggregating results from a single cross-national assessment. However, most countries participating in PIRLS are high-income, and only a small minority of low- and middle-income countries participate in the assessment. One of the main contributions of the GAML process is that it has overcome this data gap by benchmarking several major cross-national assessments\u2014and increasingly national learning assessments as well\u2014against the standard.\nThe MPL for each learning assessment is used to calculate the reading proficiency rate for that country, which is the share of students scoring at or above the minimum proficiency level, and conversely to calculate the learning deprivation.\nThe Proficiency and Grade Levels used for each assessment is as follows: PIRLS (grade 4) - Level 2 (Low international benchmark, 400 points); TIMSS (grade 4) - Level 2 (Low international benchmark, 400 points); LLECE (SERCE, grade 6) - Level 3 (513.66 points); PASEC (grades 5 and 6) - Level 4 (595.1 points); SEA-PLM (grade 5) - Level 6 and above; National Learning Assessment (grade 4, 5 and 6) - Varies by country.\nWhen a given country had administered multiple types of learning assessments, a hierarchy is applied in the order listed below to ensure best comparability across countries: International or Regional Learning Assessment for Reading (PIRLS, LLECE, PASEC, SEA-PLM) > TIMSS Science > Statistical or Pairwise Linking Exercises > AMPL-bs, Policy Linked National Learning Assessments or Policy Linked Service Delivery Indicators (SDIs) > Non-Policy Linked NLAs (Interim Reporting).\nNote that as the GAML and joint coalitions continue their efforts to improve learning data coverage, the hierarchy may be revised.", "origins": [ { "producer": "World Bank and UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_lpv_prim_ld_ma": { "title": "Male pupils below minimum reading proficiency at end of primary (%). Low GAML threshold", "description_from_producer": "The share of male pupils at the end of primary schooling who are below the minimum proficiency level (MPL) for reading or learning deprived. The MPL in reading at the end of primary is defined by the Global Alliance to Monitor Learning (GAML), measured in standard learning assessments, and reported in the context of the SDG 4.1.1b monitoring. It is \u201cStudents independently and fluently read simple, short narrative and expository texts. They locate explicitly-stated information. They interpret and give some explanations about the key ideas in these texts. They provide simple, personal opinions or judgements about the information, events and characters in a text.\u201d (UIS and GAML 2019). In other words, a child \u201cattaining\u201d minimum proficiency has the ability to read and understand a short passage of age-appropriate material, whether a simple story or non-fiction narrative of a few paragraphs. In addition to this nutshell statement, the GAML has also proposed a common terminology to describe classifications in the context of the MPL. This is a critical first step toward linking cross-national and national learning assessments with a common benchmark.\n\nLimitations and exceptions: The process of equating proficiency levels on different assessments to the GAML definition is not straightforward. Even the long-running regional assessment initiatives like PASEC (West and Central Africa) and LLECE (Latin America and the Caribbean) use different definitions and a different number of levels than other assessments like PIRLS, and those might not even be the same over time. Their test development methodologies and test administration procedures also vary. Moreover, because not all countries participate in global or regional assessments, for some major countries we rely on their interim reporting using their national assessments; equating these assessments is even more challenging. UIS and the World Bank have mapped how proficiency levels between assessment can equate to one another, but they are not strictly comparable.\nAmong the differences across assessments, one important point concerns the age at which children are tested. The reference age for our exercise is age 10. However, all learning assessments used in this analysis are sampled based on specific grades rather than age. PIRLS and TIMSS are administered in Grade 4, meaning that the average student assessed is indeed 10 years old, but this is not the case for the regional assessments. PASEC and LLECE are administered in Grade 6, so the average age in those assessments is 12.8 and 12.4, respectively. National assessments are administered at different grades, so to incorporate those assessments, we chose for each country the grade between 4 and 6 (inclusive) for which relevant and reliable data were available. This is consistent with the SDG monitoring by UIS and GAML, which lists \u201cEnd of Primary (or Grades 4 to 6)\u201d as the relevant age category for the end-of-primary students (SDG 4.1.1b).\nIn some cases, National Learning Assessments that have not been policy linked are used for learning poverty, if country teams and experts determine that an assessment is of sufficiently quality or has undertaken steps to align their assessments with the Global Proficiency Framework. They will often be reported as interim learning poverty indicators, as they are not fully aligned with SDG 4.1.1b.\n\nStatistical concept and methodology: Learning assessments used to calculate Learning Poverty have a minimum proficiency level (MPL) benchmarked by Global Alliance to Monitor Learning (GAML) under the leadership of the UNESCO Institute of Statistics (UIS), which occurred within the reporting window. To operationalize this concept, the current SDG monitoring process is followed by defining \u201cproficiency\u201d as reaching at least the Low International Benchmark on the international PIRLS literacy assessment.\nPIRLS is the major global primary-age assessment focused on reading, and if all countries participated in it, the task of constructing global estimates of minimum proficiency would be trivial, as it would require aggregating results from a single cross-national assessment. However, most countries participating in PIRLS are high-income, and only a small minority of low- and middle-income countries participate in the assessment. One of the main contributions of the GAML process is that it has overcome this data gap by benchmarking several major cross-national assessments\u2014and increasingly national learning assessments as well\u2014against the standard.\nThe MPL for each learning assessment is used to calculate the reading proficiency rate for that country, which is the share of students scoring at or above the minimum proficiency level, and conversely to calculate the learning deprivation.\nThe Proficiency and Grade Levels used for each assessment is as follows: PIRLS (grade 4) - Level 2 (Low international benchmark, 400 points); TIMSS (grade 4) - Level 2 (Low international benchmark, 400 points); LLECE (SERCE, grade 6) - Level 3 (513.66 points); PASEC (grades 5 and 6) - Level 4 (595.1 points); SEA-PLM (grade 5) - Level 6 and above; National Learning Assessment (grade 4, 5 and 6) - Varies by country.\nWhen a given country had administered multiple types of learning assessments, a hierarchy is applied in the order listed below to ensure best comparability across countries: International or Regional Learning Assessment for Reading (PIRLS, LLECE, PASEC, SEA-PLM) > TIMSS Science > Statistical or Pairwise Linking Exercises > AMPL-bs, Policy Linked National Learning Assessments or Policy Linked Service Delivery Indicators (SDIs) > Non-Policy Linked NLAs (Interim Reporting).\nNote that as the GAML and joint coalitions continue their efforts to improve learning data coverage, the hierarchy may be revised.", "origins": [ { "producer": "World Bank and UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_lpv_prim_ma": { "title": "Learning poverty: Share of Male Children at the End-of-Primary age below minimum reading proficiency adjusted by Out-of-School Children (%)", "description_from_producer": "The share of male 10-year-olds who cannot read and understand a short passage of age-appropriate material\u2014in other words, those who are below the \u201cminimum proficiency\u201d threshold for reading. This measure is defined as the union of two deprivations: 1) schooling deprivation and 2) learning deprivation. A child is considered schooling-deprived (SD) if he or she is of primary school age and out-of-school. The dimension of learning deprivation (LD) applies only for children in school, and identifies those pupils who are below the minimum proficiency level (MPL) for reading, as defined by the Global Alliance to Monitor Learning (GAML), measured in standard learning assessments, and reported in the context of the SDG 4.1.1b monitoring. This \u201cunion approach\u201d to measurement reflects the choice that, as presented in the SDGs, all age 10 children must be both in school and learning. The final learning poverty measure combines the two dimensions in a single indicator using the following formula: LP = SD + [(1-SD) x LD]\n\nLimitations and exceptions: The construct of \u201call children reading by age 10\u201d is an ideal that embodies normative statements about both learning and access. To achieve it, not only should all children be reading proficiently after 3 full years in primary education, but they should also have entered school at age 6 or 7.\nBy contrast, the actual indicators used to measure learning poverty are based on grade rather than age. Since the assessments are of 4th- through 6th-graders, the children tested will have had at least 3 to 5 years in school to reach what, according to the ideal, should 10 be an age-10 minimum proficiency, or even the entire primary-school-age segment for the out-of-school indicator.\nDue to different assessment availability within and between countries, data comparability, both within countries over time and across countries still poses a significant challenge. The additional out of school component further limits comparability.\nThe learning poverty indicator is based on data covering four-fifths of children at the end of primary school. In other words, a little more than 80 percent of children in low- and middle-income countries live in a country with at least one learning assessment at the end of primary, carried out in the past 9 years. For regional and global aggregates, weighted imputations affect regions with less data coverage. The major gaps are concentrated in countries where the learning crisis is most acute. Less than half of children in Sub-Saharan Africa live in a country with a National Large-Scale Learning Assessment (NLSA) or a international of regional large-scale learning assessment (ILSA or RLSA) of adequate quality to be used for this purpose.\nThis extensive coverage became possible only in recent years, with the progress in measuring learning in countries and the GAML\u2019s efforts to establish comparability, which has made possible the construction of a global indicator based on harmonized proficiency levels. Future efforts by coalition organizations are also ensuring more flexible assessment options are available for expanding data availability for countries, such as the Assessment of Minimum Proficiency Levels (AMPL) and policy linking exercises led by UIS.\n\nStatistical concept and methodology: The learning poverty indicator brings together schooling and learning indicators. It starts with the share of children in school who haven\u2019t achieved minimum reading proficiency (Learning Deprived) and adjusts it by the proportion of children who are out of school (Schooling Deprived).\nFormally, Learning Poverty is calculated as: [LD* (1-SD)] + [1 * SD]\nwhere LP = Learning poverty; LD = Learning deprivation or the share of children at the end of primary who read at below the minimum proficiency level, as defined by the Global Alliance to Monitor Learning (GAML) in the context of the SDG 4.1.1 monitoring; SD = Schooling deprivation or the share of primary-school-age children who are out-of-school (OOS) and in which all OOS are regarded as being below the minimum proficiency level.\nBecause out-of-school children are treated as non-proficient in reading, learning poverty will always be higher than the share of children in school who haven't achieved minimum reading proficiency. For countries with a very low schooling deprivation, the learning deprivation value will be very close to Learning Poverty.\nEstimating the current level of global and regional learning poverty requires deciding how to define \u201ccurrent.\u201d We include results of assessments within four years before or after a set anchor year. This decision is driven by data availability. International and regional large-scale learning assessments used for SDG 4.1.1b reporting are carried out only every 3 to 4 years. And even where assessments have been carried out recently, there is a lag of a couple of years before the data are available. This band is intended as a moving window. In the original 2019 release, the anchor year used was 2015 (Assessments between 2011 and 2019 are included in the learning poverty estimate). In the 2022 Global Update, the anchor year was moved to 2019 (assessments between 2015 and 2023 are included).\nAggregations for each region comprise the average learning poverty of countries with available data, weighted by their population ages 10\u201314 years old. To obtain a global estimate, we weight the regional aggregations by the 10\u201314-year-old population regardless of data availability. This is equivalent to imputing missing country data using regional values.", "origins": [ { "producer": "World Bank and UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_lpv_prim_sd": { "title": "Primary school age children out-of-school (%)", "description_from_producer": "The share of children of primary-school age who are out of school or schooling deprived. This dimension is linked to the indicator 4.1.4 from the SDG 4 thematic framework. This element reflects the belief that all primary-age children should be learning in schools of some type, a belief that every country has enshrined in law and that is enshrined in the SDGs. In addition to fulfilling a universal right and serving as a necessary condition for sustained learning, schooling offers many benefits beyond learning. It contributes to children\u2019s health and well-being such as promoting safety, nutrition, and socialization, and facilitating parents' labor market participation and, at the macro level, schooling can help build social cohesion, democracy, and peace. All those complementary functions mean that schooling has value over and above the measured cognitive learning that it leads to, and they justify including schooling deprivation in the concept of learning poverty.\n\nLimitations and exceptions: The enrollment for a given learning poverty release are not strictly comparable between countries, due to the differences in enrollment years and definitions, which are determined by best-match with the assessment year and data availability of enrollment indicators.\nThe measure will also differ from out of school estimates using household survey data, which UIS reports for SDG 4.1.4. Households survey estimates are not used for Schooling Deprivation because data is typically reported for countries in various years and with time gaps. School surveys are more feasibly collected annually, while household data collection occurs every few years and can also depend on country demand. School surveys also allow more global consistency as the same survey and source data are used across countries. However, the source used to compute the total school-age population differ in some cases where a country provides their national estimates over the default UNDP population data. However, there are potential trade-offs in precision from school surveys as responses come from school representatives rather than using microdata.\nEnrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, enrolment rate (any definition) is affected by different age-reference points for enrollment. The length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced. The population data further affects the reference age.\nDue to the limitations described, in some cases, country specialists will provide a data point that better reflects enrollment in the country.\n\nStatistical concept and methodology: Schooling Deprivation is derived using enrollment rates computed by UIS using administrative records and follows the SDG 4.1.4 indicator. To ensure country coverage of data, we consider other enrollment definitions to use for learning poverty, if the first-best option is not available.\nWe construct an enrollment dataset from 1990 to the year of the current release, relying on multiple enrollment definitions. Our dataset is constructed from UIS (UNESCO Institute of Statistics), and other sources suggested by World Bank regional or country education specialists. Data sources are typically from administrative records (school registers or school censuses) for data on enrolment by age, and UNPD population estimates for school-age population (UIS). Enrolment by single years of age in all levels of education and the total primary-school-age population are used to compute enrollment rates.\nWe follow this hierarchy of enrollment definitions: Country specialist validated data > Adjusted Net Enrollment Rate (ANER) > Total Net Enrollment Rate (TNER) > Net enrollment rate (NER) > Gross Enrollment Rate (GER; if the gross enrollment rate is higher than 100%, it is adjusted to be 100%).\nOur preferred measure of school participation is ANER, because it accounts for some primary school aged children who might enter primary school early and advance to secondary school before they reach the official upper age limit of primary education. Adjusted net enrollment is a measure of both \u201cstock\u201d and \u201cflow\u201d and accounts for both age- and grade-based distortions, as it is the percent of primary school age children enrolled either in primary or secondary education, as opposed to gross enrollment which is the share of children of any age that are enrolled in primary school, or net enrollment which is the share of primary school age children that are enrolled in primary school. The next-best indicator is used if ANER is unavailable. In some cases, country specialists will provide a data point that reflects enrollment in the country better than UIS statistics which is used. In future Learning Poverty releases, the enrollment hierarchy may be adjusted as availability of indicator definitions change.\nThe enrollment year used is the one that best pairs with the assessment year used to compute Learning Deprivation. The year of the preferred assessment is the base. If the same enrollment year is not available, we use a step function to fill the data in with the value of the closest year. If there is data available for two years equally close to the year to fill, the older value is used. This procedure to extrapolate enrollment for missing values is required for us to pair the proficiency measure with enrollment measures from the same year, or its best proxy when enrollment is not available for the same year of the assessment.", "origins": [ { "producer": "World Bank and UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_lpv_prim_sd_fe": { "title": "Female primary school age children out-of-school (%)", "description_from_producer": "The share of female children of primary-school age who are out of school or schooling deprived. This dimension is linked to the indicator 4.1.4 from the SDG 4 thematic framework. This element reflects the belief that all primary-age children should be learning in schools of some type, a belief that every country has enshrined in law and that is enshrined in the SDGs. In addition to fulfilling a universal right and serving as a necessary condition for sustained learning, schooling offers many benefits beyond learning. It contributes to children\u2019s health and well-being such as promoting safety, nutrition, and socialization, and facilitating parents' labor market participation and, at the macro level, schooling can help build social cohesion, democracy, and peace. All those complementary functions mean that schooling has value over and above the measured cognitive learning that it leads to, and they justify including schooling deprivation in the concept of learning poverty.\n\nLimitations and exceptions: The enrollment for a given learning poverty release are not strictly comparable between countries, due to the differences in enrollment years and definitions, which are determined by best-match with the assessment year and data availability of enrollment indicators.\nThe measure will also differ from out of school estimates using household survey data, which UIS reports for SDG 4.1.4. Households survey estimates are not used for Schooling Deprivation because data is typically reported for countries in various years and with time gaps. School surveys are more feasibly collected annually, while household data collection occurs every few years and can also depend on country demand. School surveys also allow more global consistency as the same survey and source data are used across countries. However, the source used to compute the total school-age population differ in some cases where a country provides their national estimates over the default UNDP population data. However, there are potential trade-offs in precision from school surveys as responses come from school representatives rather than using microdata.\nEnrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, enrolment rate (any definition) is affected by different age-reference points for enrollment. The length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced. The population data further affects the reference age.\nDue to the limitations described, in some cases, country specialists will provide a data point that better reflects enrollment in the country.\n\nStatistical concept and methodology: Schooling Deprivation is derived using enrollment rates computed by UIS using administrative records and follows the SDG 4.1.4 indicator. To ensure country coverage of data, we consider other enrollment definitions to use for learning poverty, if the first-best option is not available.\nWe construct an enrollment dataset from 1990 to the year of the current release, relying on multiple enrollment definitions. Our dataset is constructed from UIS (UNESCO Institute of Statistics), and other sources suggested by World Bank regional or country education specialists. Data sources are typically from administrative records (school registers or school censuses) for data on enrolment by age, and UNPD population estimates for school-age population (UIS). Enrolment by single years of age in all levels of education and the total primary-school-age population are used to compute enrollment rates.\nWe follow this hierarchy of enrollment definitions: Country specialist validated data > Adjusted Net Enrollment Rate (ANER) > Total Net Enrollment Rate (TNER) > Net enrollment rate (NER) > Gross Enrollment Rate (GER; if the gross enrollment rate is higher than 100%, it is adjusted to be 100%).\nOur preferred measure of school participation is ANER, because it accounts for some primary school aged children who might enter primary school early and advance to secondary school before they reach the official upper age limit of primary education. Adjusted net enrollment is a measure of both \u201cstock\u201d and \u201cflow\u201d and accounts for both age- and grade-based distortions, as it is the percent of primary school age children enrolled either in primary or secondary education, as opposed to gross enrollment which is the share of children of any age that are enrolled in primary school, or net enrollment which is the share of primary school age children that are enrolled in primary school. The next-best indicator is used if ANER is unavailable. In some cases, country specialists will provide a data point that reflects enrollment in the country better than UIS statistics which is used. In future Learning Poverty releases, the enrollment hierarchy may be adjusted as availability of indicator definitions change.\nThe enrollment year used is the one that best pairs with the assessment year used to compute Learning Deprivation. The year of the preferred assessment is the base. If the same enrollment year is not available, we use a step function to fill the data in with the value of the closest year. If there is data available for two years equally close to the year to fill, the older value is used. This procedure to extrapolate enrollment for missing values is required for us to pair the proficiency measure with enrollment measures from the same year, or its best proxy when enrollment is not available for the same year of the assessment.", "origins": [ { "producer": "World Bank and UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_lpv_prim_sd_ma": { "title": "Male primary school age children out-of-school (%)", "description_from_producer": "The share of male children of primary-school age who are out of school or schooling deprived. This dimension is linked to the indicator 4.1.4 from the SDG 4 thematic framework. This element reflects the belief that all primary-age children should be learning in schools of some type, a belief that every country has enshrined in law and that is enshrined in the SDGs. In addition to fulfilling a universal right and serving as a necessary condition for sustained learning, schooling offers many benefits beyond learning. It contributes to children\u2019s health and well-being such as promoting safety, nutrition, and socialization, and facilitating parents' labor market participation and, at the macro level, schooling can help build social cohesion, democracy, and peace. All those complementary functions mean that schooling has value over and above the measured cognitive learning that it leads to, and they justify including schooling deprivation in the concept of learning poverty.\n\nLimitations and exceptions: The enrollment for a given learning poverty release are not strictly comparable between countries, due to the differences in enrollment years and definitions, which are determined by best-match with the assessment year and data availability of enrollment indicators.\nThe measure will also differ from out of school estimates using household survey data, which UIS reports for SDG 4.1.4. Households survey estimates are not used for Schooling Deprivation because data is typically reported for countries in various years and with time gaps. School surveys are more feasibly collected annually, while household data collection occurs every few years and can also depend on country demand. School surveys also allow more global consistency as the same survey and source data are used across countries. However, the source used to compute the total school-age population differ in some cases where a country provides their national estimates over the default UNDP population data. However, there are potential trade-offs in precision from school surveys as responses come from school representatives rather than using microdata.\nEnrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, enrolment rate (any definition) is affected by different age-reference points for enrollment. The length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced. The population data further affects the reference age.\nDue to the limitations described, in some cases, country specialists will provide a data point that better reflects enrollment in the country.\n\nStatistical concept and methodology: Schooling Deprivation is derived using enrollment rates computed by UIS using administrative records and follows the SDG 4.1.4 indicator. To ensure country coverage of data, we consider other enrollment definitions to use for learning poverty, if the first-best option is not available.\nWe construct an enrollment dataset from 1990 to the year of the current release, relying on multiple enrollment definitions. Our dataset is constructed from UIS (UNESCO Institute of Statistics), and other sources suggested by World Bank regional or country education specialists. Data sources are typically from administrative records (school registers or school censuses) for data on enrolment by age, and UNPD population estimates for school-age population (UIS). Enrolment by single years of age in all levels of education and the total primary-school-age population are used to compute enrollment rates.\nWe follow this hierarchy of enrollment definitions: Country specialist validated data > Adjusted Net Enrollment Rate (ANER) > Total Net Enrollment Rate (TNER) > Net enrollment rate (NER) > Gross Enrollment Rate (GER; if the gross enrollment rate is higher than 100%, it is adjusted to be 100%).\nOur preferred measure of school participation is ANER, because it accounts for some primary school aged children who might enter primary school early and advance to secondary school before they reach the official upper age limit of primary education. Adjusted net enrollment is a measure of both \u201cstock\u201d and \u201cflow\u201d and accounts for both age- and grade-based distortions, as it is the percent of primary school age children enrolled either in primary or secondary education, as opposed to gross enrollment which is the share of children of any age that are enrolled in primary school, or net enrollment which is the share of primary school age children that are enrolled in primary school. The next-best indicator is used if ANER is unavailable. In some cases, country specialists will provide a data point that reflects enrollment in the country better than UIS statistics which is used. In future Learning Poverty releases, the enrollment hierarchy may be adjusted as availability of indicator definitions change.\nThe enrollment year used is the one that best pairs with the assessment year used to compute Learning Deprivation. The year of the preferred assessment is the base. If the same enrollment year is not available, we use a step function to fill the data in with the value of the closest year. If there is data available for two years equally close to the year to fill, the older value is used. This procedure to extrapolate enrollment for missing values is required for us to pair the proficiency measure with enrollment measures from the same year, or its best proxy when enrollment is not available for the same year of the assessment.", "origins": [ { "producer": "World Bank and UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_pre_durs": { "title": "Preprimary education, duration (years)", "description_from_producer": "Preprimary duration refers to the number of grades (years) in preprimary school.\n\nStatistical concept and methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Aggregate data are based on World Bank estimates.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "years", "short_unit": "years" }, "se_pre_enrl_tc_zs": { "title": "Pupil-teacher ratio, preprimary", "description_from_producer": "Preprimary school pupil-teacher ratio is the average number of pupils per teacher in preprimary school.\n\nLimitations and exceptions: The comparability of pupil-teacher ratios across countries is affected by the definition of teachers and by differences in class size by grade and in the number of hours taught, as well as the different practices countries employ such as part-time teachers, school shifts, and multi-grade classes. Moreover, the underlying enrollment levels are subject to a variety of reporting errors.\n\nStatistical concept and methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_pre_enrr": { "title": "School enrollment, preprimary (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Preprimary education refers to programs at the initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment and to provide a bridge between home and school.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for pre-primary school is calculated by dividing the number of students enrolled in pre-primary education regardless of age by the population of the age group which officially corresponds to pre-primary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_pre_enrr_fe": { "title": "School enrollment, preprimary, female (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Preprimary education refers to programs at the initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment and to provide a bridge between home and school.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for pre-primary school is calculated by dividing the number of students enrolled in pre-primary education regardless of age by the population of the age group which officially corresponds to pre-primary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_pre_enrr_ma": { "title": "School enrollment, preprimary, male (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Preprimary education refers to programs at the initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment and to provide a bridge between home and school.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for pre-primary school is calculated by dividing the number of students enrolled in pre-primary education regardless of age by the population of the age group which officially corresponds to pre-primary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_pre_tcaq_fe_zs": { "title": "Trained teachers in preprimary education, female (% of female teachers)", "description_from_producer": "Trained teachers in preprimary education are the percentage of preprimary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female teachers", "short_unit": "%" }, "se_pre_tcaq_ma_zs": { "title": "Trained teachers in preprimary education, male (% of male teachers)", "description_from_producer": "Trained teachers in preprimary education are the percentage of preprimary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male teachers", "short_unit": "%" }, "se_pre_tcaq_zs": { "title": "Trained teachers in preprimary education (% of total teachers)", "description_from_producer": "Trained teachers in preprimary education are the percentage of preprimary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total teachers", "short_unit": "%" }, "se_prm_ages": { "title": "Primary school starting age (years)", "description_from_producer": "Primary school starting age is the age at which students would enter primary education, assuming they had started at the official entrance age for the lowest level of education, had studied full-time throughout and had progressed through the system without repeating or skipping a grade.\n\nLimitations and exceptions: The theoretical entrance age to a given programme or level is typically, but not always, the most common entrance age.\n\nStatistical concept and methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "years", "short_unit": "years" }, "se_prm_cmpt_fe_zs": { "title": "Primary completion rate, female (% of relevant age group)", "description_from_producer": "Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.\n\nLimitations and exceptions: Data limitations preclude adjusting for students who drop out during the final year of primary education. Thus this rate is a proxy that should be taken as an upper estimate of the actual primary completion rate.\n\nThere are many reasons why the primary completion rate can exceed 100 percent. The numerator may include late entrants and overage children who have repeated one or more grades of primary education as well as children who entered school early, while the denominator is the number of children at the entrance age for the last grade of primary education.\n\nStatistical concept and methodology: Primary completion rate is calculated by dividing the number of new entrants (enrollment minus repeaters) in the last grade of primary education, regardless of age, by the population at the entrance age for the last grade of primary education and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of relevant age group", "short_unit": "%" }, "se_prm_cmpt_ma_zs": { "title": "Primary completion rate, male (% of relevant age group)", "description_from_producer": "Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.\n\nLimitations and exceptions: Data limitations preclude adjusting for students who drop out during the final year of primary education. Thus this rate is a proxy that should be taken as an upper estimate of the actual primary completion rate.\n\nThere are many reasons why the primary completion rate can exceed 100 percent. The numerator may include late entrants and overage children who have repeated one or more grades of primary education as well as children who entered school early, while the denominator is the number of children at the entrance age for the last grade of primary education.\n\nStatistical concept and methodology: Primary completion rate is calculated by dividing the number of new entrants (enrollment minus repeaters) in the last grade of primary education, regardless of age, by the population at the entrance age for the last grade of primary education and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of relevant age group", "short_unit": "%" }, "se_prm_cmpt_zs": { "title": "Primary completion rate, total (% of relevant age group)", "description_from_producer": "Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.\n\nLimitations and exceptions: Data limitations preclude adjusting for students who drop out during the final year of primary education. Thus this rate is a proxy that should be taken as an upper estimate of the actual primary completion rate.\n\nThere are many reasons why the primary completion rate can exceed 100 percent. The numerator may include late entrants and overage children who have repeated one or more grades of primary education as well as children who entered school early, while the denominator is the number of children at the entrance age for the last grade of primary education.\n\nStatistical concept and methodology: Primary completion rate is calculated by dividing the number of new entrants (enrollment minus repeaters) in the last grade of primary education, regardless of age, by the population at the entrance age for the last grade of primary education and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of relevant age group", "short_unit": "%" }, "se_prm_cuat_fe_zs": { "title": "Educational attainment, at least completed primary, population 25+ years, female (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed primary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed primary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_prm_cuat_ma_zs": { "title": "Educational attainment, at least completed primary, population 25+ years, male (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed primary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed primary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_prm_cuat_zs": { "title": "Educational attainment, at least completed primary, population 25+ years, total (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed primary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed primary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_prm_durs": { "title": "Primary education, duration (years)", "description_from_producer": "Primary duration refers to the number of grades (years) in primary school.\n\nStatistical concept and methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Aggregate data are based on World Bank estimates.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "years", "short_unit": "years" }, "se_prm_enrl": { "title": "Primary education, pupils", "description_from_producer": "Primary education pupils is the total number of pupils enrolled at primary level in public and private schools.\n\nStatistical concept and methodology: Enrollment includes Individuals officially registered in a given educational programme, or stage or module thereof, regardless of age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_prm_enrl_fe_zs": { "title": "Primary education, pupils (% female)", "description_from_producer": "Female pupils as a percentage of total pupils at primary level include enrollments in public and private schools.\n\nLimitations and exceptions: The percentage of female enrollment is limited in assessing gender parity, because it's affected by the gender composition of population. Ratio of female to male in enrollment rate provides a population adjusted measure of gender parity.\n\nStatistical concept and methodology: Percentage of female enrollment is calculated by dividing the total number of female students at a given level of education by the total enrollment at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% female", "short_unit": "%" }, "se_prm_enrl_tc_zs": { "title": "Pupil-teacher ratio, primary", "description_from_producer": "Primary school pupil-teacher ratio is the average number of pupils per teacher in primary school.\n\nLimitations and exceptions: The comparability of pupil-teacher ratios across countries is affected by the definition of teachers and by differences in class size by grade and in the number of hours taught, as well as the different practices countries employ such as part-time teachers, school shifts, and multi-grade classes. Moreover, the underlying enrollment levels are subject to a variety of reporting errors.\n\nStatistical concept and methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_prm_enrr": { "title": "School enrollment, primary (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for primary school is calculated by dividing the number of students enrolled in primary education regardless of age by the population of the age group which officially corresponds to primary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_prm_enrr_fe": { "title": "School enrollment, primary, female (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for primary school is calculated by dividing the number of students enrolled in primary education regardless of age by the population of the age group which officially corresponds to primary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_prm_enrr_ma": { "title": "School enrollment, primary, male (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for primary school is calculated by dividing the number of students enrolled in primary education regardless of age by the population of the age group which officially corresponds to primary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_prm_gint_fe_zs": { "title": "Gross intake ratio in first grade of primary education, female (% of relevant age group)", "description_from_producer": "Gross intake ratio in first grade of primary education is the number of new entrants in the first grade of primary education regardless of age, expressed as a percentage of the population of the official primary entrance age.\n\nLimitations and exceptions: The quality of data is affected when new entrants and repeaters are not correctly distinguished in the first grade of primary education. Caution is also needed for countries with a total population under 100,000 since the United Nations Population Division neither publish nor endorse single-age data for those countries. The data are highly subject to fluctuations in migration and other factors.\n\nStatistical concept and methodology: Gross intake ratio in the first grade of primary education is calculated by dividing the number of new entrants (enrollments minus repeaters) in the first grade of primary education, regardless of age, by the population of the official primary entrance age and multiplying the result by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of relevant age group", "short_unit": "%" }, "se_prm_gint_ma_zs": { "title": "Gross intake ratio in first grade of primary education, male (% of relevant age group)", "description_from_producer": "Gross intake ratio in first grade of primary education is the number of new entrants in the first grade of primary education regardless of age, expressed as a percentage of the population of the official primary entrance age.\n\nLimitations and exceptions: The quality of data is affected when new entrants and repeaters are not correctly distinguished in the first grade of primary education. Caution is also needed for countries with a total population under 100,000 since the United Nations Population Division neither publish nor endorse single-age data for those countries. The data are highly subject to fluctuations in migration and other factors.\n\nStatistical concept and methodology: Gross intake ratio in the first grade of primary education is calculated by dividing the number of new entrants (enrollments minus repeaters) in the first grade of primary education, regardless of age, by the population of the official primary entrance age and multiplying the result by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of relevant age group", "short_unit": "%" }, "se_prm_gint_zs": { "title": "Gross intake ratio in first grade of primary education, total (% of relevant age group)", "description_from_producer": "Gross intake ratio in first grade of primary education is the number of new entrants in the first grade of primary education regardless of age, expressed as a percentage of the population of the official primary entrance age.\n\nLimitations and exceptions: The quality of data is affected when new entrants and repeaters are not correctly distinguished in the first grade of primary education. Caution is also needed for countries with a total population under 100,000 since the United Nations Population Division neither publish nor endorse single-age data for those countries. The data are highly subject to fluctuations in migration and other factors.\n\nStatistical concept and methodology: Gross intake ratio in the first grade of primary education is calculated by dividing the number of new entrants (enrollments minus repeaters) in the first grade of primary education, regardless of age, by the population of the official primary entrance age and multiplying the result by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of relevant age group", "short_unit": "%" }, "se_prm_nenr": { "title": "School enrollment, primary (% net)", "description_from_producer": "Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Net enrollment rate for primary school is calculated by dividing the number of students of official school age enrolled in primary education by the population of the age group which officially corresponds to primary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% net", "short_unit": "%" }, "se_prm_nenr_fe": { "title": "School enrollment, primary, female (% net)", "description_from_producer": "Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Net enrollment rate for primary school is calculated by dividing the number of students of official school age enrolled in primary education by the population of the age group which officially corresponds to primary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% net", "short_unit": "%" }, "se_prm_nenr_ma": { "title": "School enrollment, primary, male (% net)", "description_from_producer": "Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Net enrollment rate for primary school is calculated by dividing the number of students of official school age enrolled in primary education by the population of the age group which officially corresponds to primary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% net", "short_unit": "%" }, "se_prm_nint_fe_zs": { "title": "Net intake rate in grade 1, female (% of official school-age population)", "description_from_producer": "Net intake rate in grade 1 is the number of new entrants in the first grade of primary education who are of official primary school entrance age, expressed as a percentage of the population of the corresponding age.\n\nLimitations and exceptions: The quality of data is affected when new entrants and repeaters are not correctly distinguished in the first grade of primary education. Caution is also needed for countries with a total population under 100,000 since the United Nations Population Division neither publish nor endorse single-age data for those countries. The data are highly subject to fluctuations in migration and other factors.\n\nStatistical concept and methodology: Net intake rate in the first grade of primary education is calculated by dividing the number of children of official primary school entrance age who enter grade 1 of primary education for the first time by the population of the same age, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of official school-age population", "short_unit": "%" }, "se_prm_nint_ma_zs": { "title": "Net intake rate in grade 1, male (% of official school-age population)", "description_from_producer": "Net intake rate in grade 1 is the number of new entrants in the first grade of primary education who are of official primary school entrance age, expressed as a percentage of the population of the corresponding age.\n\nLimitations and exceptions: The quality of data is affected when new entrants and repeaters are not correctly distinguished in the first grade of primary education. Caution is also needed for countries with a total population under 100,000 since the United Nations Population Division neither publish nor endorse single-age data for those countries. The data are highly subject to fluctuations in migration and other factors.\n\nStatistical concept and methodology: Net intake rate in the first grade of primary education is calculated by dividing the number of children of official primary school entrance age who enter grade 1 of primary education for the first time by the population of the same age, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of official school-age population", "short_unit": "%" }, "se_prm_nint_zs": { "title": "Net intake rate in grade 1 (% of official school-age population)", "description_from_producer": "Net intake rate in grade 1 is the number of new entrants in the first grade of primary education who are of official primary school entrance age, expressed as a percentage of the population of the corresponding age.\n\nLimitations and exceptions: The quality of data is affected when new entrants and repeaters are not correctly distinguished in the first grade of primary education. Caution is also needed for countries with a total population under 100,000 since the United Nations Population Division neither publish nor endorse single-age data for those countries. The data are highly subject to fluctuations in migration and other factors.\n\nStatistical concept and methodology: Net intake rate in the first grade of primary education is calculated by dividing the number of children of official primary school entrance age who enter grade 1 of primary education for the first time by the population of the same age, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of official school-age population", "short_unit": "%" }, "se_prm_oenr_fe_zs": { "title": "Over-age students, primary, female (% of female enrollment)", "description_from_producer": "Over-age students are the percentage of those enrolled who are older than the official school-age range for primary education.\n\nStatistical concept and methodology: The percentage of over-age students is calculated by dividing the number of students who are older than the official school-age range for primary education by primary school enrollment, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female enrollment", "short_unit": "%" }, "se_prm_oenr_ma_zs": { "title": "Over-age students, primary, male (% of male enrollment)", "description_from_producer": "Over-age students are the percentage of those enrolled who are older than the official school-age range for primary education.\n\nStatistical concept and methodology: The percentage of over-age students is calculated by dividing the number of students who are older than the official school-age range for primary education by primary school enrollment, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male enrollment", "short_unit": "%" }, "se_prm_oenr_zs": { "title": "Over-age students, primary (% of enrollment)", "description_from_producer": "Over-age students are the percentage of those enrolled who are older than the official school-age range for primary education.\n\nStatistical concept and methodology: The percentage of over-age students is calculated by dividing the number of students who are older than the official school-age range for primary education by primary school enrollment, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of enrollment", "short_unit": "%" }, "se_prm_priv_zs": { "title": "School enrollment, primary, private (% of total primary)", "description_from_producer": "Private enrollment refers to pupils or students enrolled in institutions that are not operated by a public authority but controlled and managed, whether for profit or not, by a private body such as a nongovernmental organization, religious body, special interest group, foundation or business enterprise.\n\nLimitations and exceptions: Religious or private schools, which are not registered with the government or don't follow the common national curriculum, may not be captured.\n\nStatistical concept and methodology: The share of students in private primary school is calculated by dividing the number of students enrolled in private educational institutions at primary level by total enrollment (public and private) at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total primary", "short_unit": "%" }, "se_prm_prs5_fe_zs": { "title": "Persistence to grade 5, female (% of cohort)", "description_from_producer": "Persistence to grade 5 (percentage of cohort reaching grade 5) is the share of children enrolled in the first grade of primary school who eventually reach grade 5. The estimate is based on the reconstructed cohort method.\n\nLimitations and exceptions: The estimates have limitations in capturing real trend in that an observed rate will be applied to the underlying indicators such as repetition rate and promotion rate throughout the cohort life, and re-entrants, grade skipping, migration or transfers during a school year are not adequately captured.\n\nStatistical concept and methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of cohort", "short_unit": "%" }, "se_prm_prs5_ma_zs": { "title": "Persistence to grade 5, male (% of cohort)", "description_from_producer": "Persistence to grade 5 (percentage of cohort reaching grade 5) is the share of children enrolled in the first grade of primary school who eventually reach grade 5. The estimate is based on the reconstructed cohort method.\n\nLimitations and exceptions: The estimates have limitations in capturing real trend in that an observed rate will be applied to the underlying indicators such as repetition rate and promotion rate throughout the cohort life, and re-entrants, grade skipping, migration or transfers during a school year are not adequately captured.\n\nStatistical concept and methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of cohort", "short_unit": "%" }, "se_prm_prs5_zs": { "title": "Persistence to grade 5, total (% of cohort)", "description_from_producer": "Persistence to grade 5 (percentage of cohort reaching grade 5) is the share of children enrolled in the first grade of primary school who eventually reach grade 5. The estimate is based on the reconstructed cohort method.\n\nLimitations and exceptions: The estimates have limitations in capturing real trend in that an observed rate will be applied to the underlying indicators such as repetition rate and promotion rate throughout the cohort life, and re-entrants, grade skipping, migration or transfers during a school year are not adequately captured.\n\nStatistical concept and methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of cohort", "short_unit": "%" }, "se_prm_prsl_fe_zs": { "title": "Persistence to last grade of primary, female (% of cohort)", "description_from_producer": "Persistence to last grade of primary is the percentage of children enrolled in the first grade of primary school who eventually reach the last grade of primary education. The estimate is based on the reconstructed cohort method.\n\nLimitations and exceptions: The estimates have limitations in capturing real trend in that an observed rate will be applied to the underlying indicators such as repetition rate and promotion rate throughout the cohort life, and re-entrants, grade skipping, migration or transfers during a school year are not adequately captured.\n\nStatistical concept and methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of cohort", "short_unit": "%" }, "se_prm_prsl_ma_zs": { "title": "Persistence to last grade of primary, male (% of cohort)", "description_from_producer": "Persistence to last grade of primary is the percentage of children enrolled in the first grade of primary school who eventually reach the last grade of primary education. The estimate is based on the reconstructed cohort method.\n\nLimitations and exceptions: The estimates have limitations in capturing real trend in that an observed rate will be applied to the underlying indicators such as repetition rate and promotion rate throughout the cohort life, and re-entrants, grade skipping, migration or transfers during a school year are not adequately captured.\n\nStatistical concept and methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of cohort", "short_unit": "%" }, "se_prm_prsl_zs": { "title": "Persistence to last grade of primary, total (% of cohort)", "description_from_producer": "Persistence to last grade of primary is the percentage of children enrolled in the first grade of primary school who eventually reach the last grade of primary education. The estimate is based on the reconstructed cohort method.\n\nLimitations and exceptions: The estimates have limitations in capturing real trend in that an observed rate will be applied to the underlying indicators such as repetition rate and promotion rate throughout the cohort life, and re-entrants, grade skipping, migration or transfers during a school year are not adequately captured.\n\nStatistical concept and methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of cohort", "short_unit": "%" }, "se_prm_rept_fe_zs": { "title": "Repeaters, primary, female (% of female enrollment)", "description_from_producer": "Repeaters in primary school are the number of students enrolled in the same grade as in the previous year, as a percentage of all students enrolled in primary school.\n\nLimitations and exceptions: Country policies on repetition and promotion differ. In some cases the number of repeaters is controlled because of limited capacity. In other cases the number of repeaters is almost 0 because of automatic promotion \u2013 suggesting a system that is highly efficient but that may not be endowing students with enough cognitive skills.\n\nStatistical concept and methodology: Share of repeaters in primary school is calculated by dividing the sum of repeaters in all grades of primary school by the total number of students enrolled in primary school, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female enrollment", "short_unit": "%" }, "se_prm_rept_ma_zs": { "title": "Repeaters, primary, male (% of male enrollment)", "description_from_producer": "Repeaters in primary school are the number of students enrolled in the same grade as in the previous year, as a percentage of all students enrolled in primary school.\n\nLimitations and exceptions: Country policies on repetition and promotion differ. In some cases the number of repeaters is controlled because of limited capacity. In other cases the number of repeaters is almost 0 because of automatic promotion \u2013 suggesting a system that is highly efficient but that may not be endowing students with enough cognitive skills.\n\nStatistical concept and methodology: Share of repeaters in primary school is calculated by dividing the sum of repeaters in all grades of primary school by the total number of students enrolled in primary school, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male enrollment", "short_unit": "%" }, "se_prm_rept_zs": { "title": "Repeaters, primary, total (% of total enrollment)", "description_from_producer": "Repeaters in primary school are the number of students enrolled in the same grade as in the previous year, as a percentage of all students enrolled in primary school.\n\nLimitations and exceptions: Country policies on repetition and promotion differ. In some cases the number of repeaters is controlled because of limited capacity. In other cases the number of repeaters is almost 0 because of automatic promotion \u2013 suggesting a system that is highly efficient but that may not be endowing students with enough cognitive skills.\n\nStatistical concept and methodology: Share of repeaters in primary school is calculated by dividing the sum of repeaters in all grades of primary school by the total number of students enrolled in primary school, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total enrollment", "short_unit": "%" }, "se_prm_tcaq_fe_zs": { "title": "Trained teachers in primary education, female (% of female teachers)", "description_from_producer": "Trained teachers in primary education are the percentage of primary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female teachers", "short_unit": "%" }, "se_prm_tcaq_ma_zs": { "title": "Trained teachers in primary education, male (% of male teachers)", "description_from_producer": "Trained teachers in primary education are the percentage of primary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male teachers", "short_unit": "%" }, "se_prm_tcaq_zs": { "title": "Trained teachers in primary education (% of total teachers)", "description_from_producer": "Trained teachers in primary education are the percentage of primary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total teachers", "short_unit": "%" }, "se_prm_tchr": { "title": "Primary education, teachers", "description_from_producer": "Primary education teachers includes full-time and part-time teachers.\n\nStatistical concept and methodology: Teachers refer to persons employed full-time or part-time in an official capacity to guide and direct the learning experience of pupils and students, irrespective of their qualifications or the delivery mechanism, i.e. face-to-face and/or at a distance. This definition excludes educational personnel who have no active teaching duties (e.g. headmasters, headmistresses or principals who do not teach) or who work occasionally or in a voluntary capacity in educational institutions.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_prm_tchr_fe_zs": { "title": "Primary education, teachers (% female)", "description_from_producer": "Female teachers as a percentage of total primary education teachers includes full-time and part-time teachers.\n\nStatistical concept and methodology: The share of female teachers in primary education is calculated by dividing the total number of female teachers at primary level of education by the total number of teachers at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% female", "short_unit": "%" }, "se_prm_tenr": { "title": "Adjusted net enrollment rate, primary (% of primary school age children)", "description_from_producer": "Adjusted net enrollment is the number of pupils of the school-age group for primary education, enrolled either in primary or secondary education, expressed as a percentage of the total population in that age group.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Adjusted net enrollment rate in primary education is calculated by dividing the number of children in the official primary school age who are enrolled in primary or secondary education by the population of the same age group and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of primary school age children", "short_unit": "%" }, "se_prm_tenr_fe": { "title": "Adjusted net enrollment rate, primary, female (% of primary school age children)", "description_from_producer": "Adjusted net enrollment is the number of pupils of the school-age group for primary education, enrolled either in primary or secondary education, expressed as a percentage of the total population in that age group.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Adjusted net enrollment rate in primary education is calculated by dividing the number of children in the official primary school age who are enrolled in primary or secondary education by the population of the same age group and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of primary school age children", "short_unit": "%" }, "se_prm_tenr_ma": { "title": "Adjusted net enrollment rate, primary, male (% of primary school age children)", "description_from_producer": "Adjusted net enrollment is the number of pupils of the school-age group for primary education, enrolled either in primary or secondary education, expressed as a percentage of the total population in that age group.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Adjusted net enrollment rate in primary education is calculated by dividing the number of children in the official primary school age who are enrolled in primary or secondary education by the population of the same age group and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of primary school age children", "short_unit": "%" }, "se_prm_uner": { "title": "Children out of school, primary", "description_from_producer": "Children out of school are the number of primary-school-age children not enrolled in primary or secondary school.\n\nLimitations and exceptions: Due to different data sources for enrollment and population data, the number may not capture the actual number of children not attending in primary school.\n\nStatistical concept and methodology: The number of out-of-school children is calculated by subtracting the number of primary school-age children enrolled in primary or secondary school from the total population of the official primary school-age children.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_prm_uner_fe": { "title": "Children out of school, primary, female", "description_from_producer": "Children out of school are the number of primary-school-age children not enrolled in primary or secondary school.\n\nLimitations and exceptions: Due to different data sources for enrollment and population data, the number may not capture the actual number of children not attending in primary school.\n\nStatistical concept and methodology: The number of out-of-school children is calculated by subtracting the number of primary school-age children enrolled in primary or secondary school from the total population of the official primary school-age children.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_prm_uner_fe_zs": { "title": "Children out of school, female (% of female primary school age)", "description_from_producer": "Children out of school are the percentage of primary-school-age children who are not enrolled in primary or secondary school. Children in the official primary age group that are in preprimary education should be considered out of school.\n\nLimitations and exceptions: The administrative data used in the calculation of the rate of out-of-school children are based on enrolment at a specific date which can bias the results by either counting enrolled children who never attend school or by omitting those who enroll after the reference date for reporting enrolment data. Furthermore, children who drop out of school after the reference date are not counted as out of school. Discrepancies between enrolment and population data from different sources can also result in over- or underestimates of the rate. Lastly, the international comparability of this indicator can be affected by the use of different concepts of enrolment and out-of-school children across countries.\n\nStatistical concept and methodology: The rate of out-of-school children allows to compare across countries with different population sizes. It shows the share of official primary-school-age children who never attended school or dropped out to the population of official primary school age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female primary school age", "short_unit": "%" }, "se_prm_uner_ma": { "title": "Children out of school, primary, male", "description_from_producer": "Children out of school are the number of primary-school-age children not enrolled in primary or secondary school.\n\nLimitations and exceptions: Due to different data sources for enrollment and population data, the number may not capture the actual number of children not attending in primary school.\n\nStatistical concept and methodology: The number of out-of-school children is calculated by subtracting the number of primary school-age children enrolled in primary or secondary school from the total population of the official primary school-age children.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_prm_uner_ma_zs": { "title": "Children out of school, male (% of male primary school age)", "description_from_producer": "Children out of school are the percentage of primary-school-age children who are not enrolled in primary or secondary school. Children in the official primary age group that are in preprimary education should be considered out of school.\n\nLimitations and exceptions: The administrative data used in the calculation of the rate of out-of-school children are based on enrolment at a specific date which can bias the results by either counting enrolled children who never attend school or by omitting those who enroll after the reference date for reporting enrolment data. Furthermore, children who drop out of school after the reference date are not counted as out of school. Discrepancies between enrolment and population data from different sources can also result in over- or underestimates of the rate. Lastly, the international comparability of this indicator can be affected by the use of different concepts of enrolment and out-of-school children across countries.\n\nStatistical concept and methodology: The rate of out-of-school children allows to compare across countries with different population sizes. It shows the share of official primary-school-age children who never attended school or dropped out to the population of official primary school age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male primary school age", "short_unit": "%" }, "se_prm_uner_zs": { "title": "Children out of school (% of primary school age)", "description_from_producer": "Children out of school are the percentage of primary-school-age children who are not enrolled in primary or secondary school. Children in the official primary age group that are in preprimary education should be considered out of school.\n\nLimitations and exceptions: The administrative data used in the calculation of the rate of out-of-school children are based on enrolment at a specific date which can bias the results by either counting enrolled children who never attend school or by omitting those who enroll after the reference date for reporting enrolment data. Furthermore, children who drop out of school after the reference date are not counted as out of school. Discrepancies between enrolment and population data from different sources can also result in over- or underestimates of the rate. Lastly, the international comparability of this indicator can be affected by the use of different concepts of enrolment and out-of-school children across countries.\n\nStatistical concept and methodology: The rate of out-of-school children allows to compare across countries with different population sizes. It shows the share of official primary-school-age children who never attended school or dropped out to the population of official primary school age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of primary school age", "short_unit": "%" }, "se_sec_ages": { "title": "Lower secondary school starting age (years)", "description_from_producer": "Lower secondary school starting age is the age at which students would enter lower secondary education, assuming they had started at the official entrance age for the lowest level of education, had studied full-time throughout and had progressed through the system without repeating or skipping a grade.\n\nLimitations and exceptions: The theoretical entrance age to a given programme or level is typically, but not always, the most common entrance age.\n\nStatistical concept and methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "years", "short_unit": "years" }, "se_sec_cmpt_lo_fe_zs": { "title": "Lower secondary completion rate, female (% of relevant age group)", "description_from_producer": "Lower secondary education completion rate is measured as the gross intake ratio to the last grade of lower secondary education (general and pre-vocational). It is calculated as the number of new entrants in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.\n\nLimitations and exceptions: Data limitations preclude adjusting for students who drop out during the final year of lower secondary education. Thus this rate is a proxy that should be taken as an upper estimate of the actual lower secondary completion rate.\n\nThere are many reasons why the rate can exceed 100 percent. The numerator may include late entrants and overage children who have repeated one or more grades of lower secondary education as well as children who entered school early, while the denominator is the number of children at the entrance age for the last grade of lower secondary education.\n\nStatistical concept and methodology: Lower secondary completion rate is calculated as the number of new entrants (enrollment minus repeaters) in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of relevant age group", "short_unit": "%" }, "se_sec_cmpt_lo_ma_zs": { "title": "Lower secondary completion rate, male (% of relevant age group)", "description_from_producer": "Lower secondary education completion rate is measured as the gross intake ratio to the last grade of lower secondary education (general and pre-vocational). It is calculated as the number of new entrants in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.\n\nLimitations and exceptions: Data limitations preclude adjusting for students who drop out during the final year of lower secondary education. Thus this rate is a proxy that should be taken as an upper estimate of the actual lower secondary completion rate.\n\nThere are many reasons why the rate can exceed 100 percent. The numerator may include late entrants and overage children who have repeated one or more grades of lower secondary education as well as children who entered school early, while the denominator is the number of children at the entrance age for the last grade of lower secondary education.\n\nStatistical concept and methodology: Lower secondary completion rate is calculated as the number of new entrants (enrollment minus repeaters) in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of relevant age group", "short_unit": "%" }, "se_sec_cmpt_lo_zs": { "title": "Lower secondary completion rate, total (% of relevant age group)", "description_from_producer": "Lower secondary education completion rate is measured as the gross intake ratio to the last grade of lower secondary education (general and pre-vocational). It is calculated as the number of new entrants in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.\n\nLimitations and exceptions: Data limitations preclude adjusting for students who drop out during the final year of lower secondary education. Thus this rate is a proxy that should be taken as an upper estimate of the actual lower secondary completion rate.\n\nThere are many reasons why the rate can exceed 100 percent. The numerator may include late entrants and overage children who have repeated one or more grades of lower secondary education as well as children who entered school early, while the denominator is the number of children at the entrance age for the last grade of lower secondary education.\n\nStatistical concept and methodology: Lower secondary completion rate is calculated as the number of new entrants (enrollment minus repeaters) in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of relevant age group", "short_unit": "%" }, "se_sec_cuat_lo_fe_zs": { "title": "Educational attainment, at least completed lower secondary, population 25+, female (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed lower secondary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed lower secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_sec_cuat_lo_ma_zs": { "title": "Educational attainment, at least completed lower secondary, population 25+, male (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed lower secondary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed lower secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_sec_cuat_lo_zs": { "title": "Educational attainment, at least completed lower secondary, population 25+, total (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed lower secondary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed lower secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_sec_cuat_po_fe_zs": { "title": "Educational attainment, at least completed post-secondary, population 25+, female (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed post-secondary non-tertiary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed post-secondary non-tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_sec_cuat_po_ma_zs": { "title": "Educational attainment, at least completed post-secondary, population 25+, male (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed post-secondary non-tertiary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed post-secondary non-tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_sec_cuat_po_zs": { "title": "Educational attainment, at least completed post-secondary, population 25+, total (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed post-secondary non-tertiary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed post-secondary non-tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_sec_cuat_up_fe_zs": { "title": "Educational attainment, at least completed upper secondary, population 25+, female (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed upper secondary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed upper secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_sec_cuat_up_ma_zs": { "title": "Educational attainment, at least completed upper secondary, population 25+, male (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed upper secondary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed upper secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_sec_cuat_up_zs": { "title": "Educational attainment, at least completed upper secondary, population 25+, total (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed upper secondary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed upper secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_sec_durs": { "title": "Secondary education, duration (years)", "description_from_producer": "Secondary duration refers to the number of grades (years) in secondary school.\n\nStatistical concept and methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Aggregate data are based on World Bank estimates.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "years", "short_unit": "years" }, "se_sec_enrl": { "title": "Secondary education, pupils", "description_from_producer": "Secondary education pupils is the total number of pupils enrolled at secondary level in public and private schools.\n\nStatistical concept and methodology: Enrollment includes Individuals officially registered in a given educational programme, or stage or module thereof, regardless of age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_sec_enrl_fe_zs": { "title": "Secondary education, pupils (% female)", "description_from_producer": "Female pupils as a percentage of total pupils at secondary level includes enrollments in public and private schools.\n\nLimitations and exceptions: The percentage of female enrollment is limited in assessing gender parity, because it's affected by the gender composition of population. Ratio of female to male in enrollment rate provides a population adjusted measure of gender parity.\n\nStatistical concept and methodology: Percentage of female enrollment is calculated by dividing the total number of female students at a given level of education by the total enrollment at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% female", "short_unit": "%" }, "se_sec_enrl_gc": { "title": "Secondary education, general pupils", "description_from_producer": "Secondary general pupils are the number of secondary students enrolled in general education programs, including teacher training.\n\nStatistical concept and methodology: Enrollment includes Individuals officially registered in a given educational programme, or stage or module thereof, regardless of age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_sec_enrl_gc_fe_zs": { "title": "Secondary education, general pupils (% female)", "description_from_producer": "Secondary general pupils are the number of secondary students enrolled in general education programs, including teacher training.\n\nLimitations and exceptions: The percentage of female enrollment is limited in assessing gender parity, because it's affected by the gender composition of population. Ratio of female to male in enrollment rate provides a population adjusted measure of gender parity.\n\nStatistical concept and methodology: Percentage of female enrollment is calculated by dividing the total number of female students at a given level of education by the total enrollment at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% female", "short_unit": "%" }, "se_sec_enrl_lo_tc_zs": { "title": "Pupil-teacher ratio, lower secondary", "description_from_producer": "Lower secondary school pupil-teacher ratio is the average number of pupils per teacher in lower secondary school.\n\nLimitations and exceptions: The comparability of pupil-teacher ratios across countries is affected by the definition of teachers and by differences in class size by grade and in the number of hours taught, as well as the different practices countries employ such as part-time teachers, school shifts, and multi-grade classes. Moreover, the underlying enrollment levels are subject to a variety of reporting errors.\n\nStatistical concept and methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_sec_enrl_tc_zs": { "title": "Pupil-teacher ratio, secondary", "description_from_producer": "Secondary school pupil-teacher ratio is the average number of pupils per teacher in secondary school.\n\nLimitations and exceptions: The comparability of pupil-teacher ratios across countries is affected by the definition of teachers and by differences in class size by grade and in the number of hours taught, as well as the different practices countries employ such as part-time teachers, school shifts, and multi-grade classes. Moreover, the underlying enrollment levels are subject to a variety of reporting errors.\n\nStatistical concept and methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_sec_enrl_up_tc_zs": { "title": "Pupil-teacher ratio, upper secondary", "description_from_producer": "Upper secondary school pupil-teacher ratio is the average number of pupils per teacher in upper secondary school.\n\nLimitations and exceptions: The comparability of pupil-teacher ratios across countries is affected by the definition of teachers and by differences in class size by grade and in the number of hours taught, as well as the different practices countries employ such as part-time teachers, school shifts, and multi-grade classes. Moreover, the underlying enrollment levels are subject to a variety of reporting errors.\n\nStatistical concept and methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_sec_enrl_vo": { "title": "Secondary education, vocational pupils", "description_from_producer": "Secondary vocational pupils are the number of secondary students enrolled in technical and vocational education programs, including teacher training.\n\nStatistical concept and methodology: Enrollment includes Individuals officially registered in a given educational programme, or stage or module thereof, regardless of age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_sec_enrl_vo_fe_zs": { "title": "Secondary education, vocational pupils (% female)", "description_from_producer": "Secondary vocational pupils are the number of secondary students enrolled in technical and vocational education programs, including teacher training.\n\nLimitations and exceptions: The percentage of female enrollment is limited in assessing gender parity, because it's affected by the gender composition of population. Ratio of female to male in enrollment rate provides a population adjusted measure of gender parity.\n\nStatistical concept and methodology: Percentage of female enrollment is calculated by dividing the total number of female students at a given level of education by the total enrollment at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% female", "short_unit": "%" }, "se_sec_enrr": { "title": "School enrollment, secondary (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for secondary school is calculated by dividing the number of students enrolled in secondary education regardless of age by the population of the age group which officially corresponds to secondary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_sec_enrr_fe": { "title": "School enrollment, secondary, female (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for secondary school is calculated by dividing the number of students enrolled in secondary education regardless of age by the population of the age group which officially corresponds to secondary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_sec_enrr_ma": { "title": "School enrollment, secondary, male (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for secondary school is calculated by dividing the number of students enrolled in secondary education regardless of age by the population of the age group which officially corresponds to secondary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_sec_nenr": { "title": "School enrollment, secondary (% net)", "description_from_producer": "Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Net enrollment rate for secondary school is calculated by dividing the number of students of official school age enrolled in secondary education by the population of the age group which officially corresponds to secondary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% net", "short_unit": "%" }, "se_sec_nenr_fe": { "title": "School enrollment, secondary, female (% net)", "description_from_producer": "Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Net enrollment rate for secondary school is calculated by dividing the number of students of official school age enrolled in secondary education by the population of the age group which officially corresponds to secondary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% net", "short_unit": "%" }, "se_sec_nenr_ma": { "title": "School enrollment, secondary, male (% net)", "description_from_producer": "Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Net enrollment rate for secondary school is calculated by dividing the number of students of official school age enrolled in secondary education by the population of the age group which officially corresponds to secondary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% net", "short_unit": "%" }, "se_sec_priv_zs": { "title": "School enrollment, secondary, private (% of total secondary)", "description_from_producer": "Private enrollment refers to pupils or students enrolled in institutions that are not operated by a public authority but controlled and managed, whether for profit or not, by a private body such as a nongovernmental organization, religious body, special interest group, foundation or business enterprise.\n\nLimitations and exceptions: Religious or private schools, which are not registered with the government or don't follow the common national curriculum, may not be captured.\n\nStatistical concept and methodology: The share of students in private secondary school is calculated by dividing the number of students enrolled in private educational institutions at secondary level by total enrollment (public and private) at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total secondary", "short_unit": "%" }, "se_sec_prog_fe_zs": { "title": "Progression to secondary school, female (%)", "description_from_producer": "Progression to secondary school refers to the number of new entrants to the first grade of secondary school in a given year as a percentage of the number of students enrolled in the final grade of primary school in the previous year (minus the number of repeaters from the last grade of primary education in the given year).\n\nLimitations and exceptions: The quality of data on the transition rate is affected when new entrants and repeaters are not correctly distinguished. Students who interrupt their studies after completing primary education could also affect data quality.\n\nStatistical concept and methodology: Effective transition rate is calculated by dividing the number of new entrants in the first grade of secondary education in a given year (t) by the number of students who enrolled in the final grade of primary education in the previous school year (t-1) minus the number of repeaters from the last grade of primary education in the given year (t), and multiplying by 100.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "se_sec_prog_ma_zs": { "title": "Progression to secondary school, male (%)", "description_from_producer": "Progression to secondary school refers to the number of new entrants to the first grade of secondary school in a given year as a percentage of the number of students enrolled in the final grade of primary school in the previous year (minus the number of repeaters from the last grade of primary education in the given year).\n\nLimitations and exceptions: The quality of data on the transition rate is affected when new entrants and repeaters are not correctly distinguished. Students who interrupt their studies after completing primary education could also affect data quality.\n\nStatistical concept and methodology: Effective transition rate is calculated by dividing the number of new entrants in the first grade of secondary education in a given year (t) by the number of students who enrolled in the final grade of primary education in the previous school year (t-1) minus the number of repeaters from the last grade of primary education in the given year (t), and multiplying by 100.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "se_sec_prog_zs": { "title": "Progression to secondary school (%)", "description_from_producer": "Progression to secondary school refers to the number of new entrants to the first grade of secondary school in a given year as a percentage of the number of students enrolled in the final grade of primary school in the previous year (minus the number of repeaters from the last grade of primary education in the given year).\n\nLimitations and exceptions: The quality of data on the transition rate is affected when new entrants and repeaters are not correctly distinguished. Students who interrupt their studies after completing primary education could also affect data quality.\n\nStatistical concept and methodology: Effective transition rate is calculated by dividing the number of new entrants in the first grade of secondary education in a given year (t) by the number of students who enrolled in the final grade of primary education in the previous school year (t-1) minus the number of repeaters from the last grade of primary education in the given year (t), and multiplying by 100.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "se_sec_tcaq_fe_zs": { "title": "Trained teachers in secondary education, female (% of female teachers)", "description_from_producer": "Trained teachers in secondary education are the percentage of secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female teachers", "short_unit": "%" }, "se_sec_tcaq_lo_fe_zs": { "title": "Trained teachers in lower secondary education, female (% of female teachers)", "description_from_producer": "Trained teachers in lower secondary education are the percentage of lower secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female teachers", "short_unit": "%" }, "se_sec_tcaq_lo_ma_zs": { "title": "Trained teachers in lower secondary education, male (% of male teachers)", "description_from_producer": "Trained teachers in lower secondary education are the percentage of lower secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male teachers", "short_unit": "%" }, "se_sec_tcaq_lo_zs": { "title": "Trained teachers in lower secondary education (% of total teachers)", "description_from_producer": "Trained teachers in lower secondary education are the percentage of lower secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total teachers", "short_unit": "%" }, "se_sec_tcaq_ma_zs": { "title": "Trained teachers in secondary education, male (% of male teachers)", "description_from_producer": "Trained teachers in secondary education are the percentage of secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male teachers", "short_unit": "%" }, "se_sec_tcaq_up_fe_zs": { "title": "Trained teachers in upper secondary education, female (% of female teachers)", "description_from_producer": "Trained teachers in upper secondary education are the percentage of upper secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female teachers", "short_unit": "%" }, "se_sec_tcaq_up_ma_zs": { "title": "Trained teachers in upper secondary education, male (% of male teachers)", "description_from_producer": "Trained teachers in upper secondary education are the percentage of upper secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male teachers", "short_unit": "%" }, "se_sec_tcaq_up_zs": { "title": "Trained teachers in upper secondary education (% of total teachers)", "description_from_producer": "Trained teachers in upper secondary education are the percentage of upper secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total teachers", "short_unit": "%" }, "se_sec_tcaq_zs": { "title": "Trained teachers in secondary education (% of total teachers)", "description_from_producer": "Trained teachers in secondary education are the percentage of secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.\n\nLimitations and exceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.\n\nStatistical concept and methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total teachers", "short_unit": "%" }, "se_sec_tchr": { "title": "Secondary education, teachers", "description_from_producer": "Secondary education teachers includes full-time and part-time teachers.\n\nStatistical concept and methodology: Teachers refer to persons employed full-time or part-time in an official capacity to guide and direct the learning experience of pupils and students, irrespective of their qualifications or the delivery mechanism, i.e. face-to-face and/or at a distance. This definition excludes educational personnel who have no active teaching duties (e.g. headmasters, headmistresses or principals who do not teach) or who work occasionally or in a voluntary capacity in educational institutions.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_sec_tchr_fe": { "title": "Secondary education, teachers, female", "description_from_producer": "Secondary education teachers includes full-time and part-time teachers.\n\nStatistical concept and methodology: Teachers refer to persons employed full-time or part-time in an official capacity to guide and direct the learning experience of pupils and students, irrespective of their qualifications or the delivery mechanism, i.e. face-to-face and/or at a distance. This definition excludes educational personnel who have no active teaching duties (e.g. headmasters, headmistresses or principals who do not teach) or who work occasionally or in a voluntary capacity in educational institutions.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_sec_tchr_fe_zs": { "title": "Secondary education, teachers (% female)", "description_from_producer": "Female teachers as a percentage of total secondary education teachers includes full-time and part-time teachers.\n\nStatistical concept and methodology: The share of female teachers in secondary education is calculated by dividing the total number of female teachers at secondary level of education by the total number of teachers at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% female", "short_unit": "%" }, "se_sec_uner_lo_fe_zs": { "title": "Adolescents out of school, female (% of female lower secondary school age)", "description_from_producer": "Adolescents out of school are the percentage of lower secondary school age adolescents who are not enrolled in school.\n\nLimitations and exceptions: The administrative data used in the calculation of the rate of out-of-school children are based on enrolment at a specific date which can bias the results by either counting enrolled children who never attend school or by omitting those who enroll after the reference date for reporting enrolment data. Furthermore, children who drop out of school after the reference date are not counted as out of school. Discrepancies between enrolment and population data from different sources can also result in over- or underestimates of the rate. Lastly, the international comparability of this indicator can be affected by the use of different concepts of enrolment and out-of-school children across countries.\n\nStatistical concept and methodology: The rate of out-of-school adolescents allows to compare across countries with different population sizes. It shows the share of official lower secondary age adolescents who never attended school or dropped out to the population of official lower secondary school age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female lower secondary school age", "short_unit": "%" }, "se_sec_uner_lo_ma_zs": { "title": "Adolescents out of school, male (% of male lower secondary school age)", "description_from_producer": "Adolescents out of school are the percentage of lower secondary school age adolescents who are not enrolled in school.\n\nLimitations and exceptions: The administrative data used in the calculation of the rate of out-of-school children are based on enrolment at a specific date which can bias the results by either counting enrolled children who never attend school or by omitting those who enroll after the reference date for reporting enrolment data. Furthermore, children who drop out of school after the reference date are not counted as out of school. Discrepancies between enrolment and population data from different sources can also result in over- or underestimates of the rate. Lastly, the international comparability of this indicator can be affected by the use of different concepts of enrolment and out-of-school children across countries.\n\nStatistical concept and methodology: The rate of out-of-school adolescents allows to compare across countries with different population sizes. It shows the share of official lower secondary age adolescents who never attended school or dropped out to the population of official lower secondary school age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male lower secondary school age", "short_unit": "%" }, "se_sec_uner_lo_zs": { "title": "Adolescents out of school (% of lower secondary school age)", "description_from_producer": "Adolescents out of school are the percentage of lower secondary school age adolescents who are not enrolled in school.\n\nLimitations and exceptions: The administrative data used in the calculation of the rate of out-of-school children are based on enrolment at a specific date which can bias the results by either counting enrolled children who never attend school or by omitting those who enroll after the reference date for reporting enrolment data. Furthermore, children who drop out of school after the reference date are not counted as out of school. Discrepancies between enrolment and population data from different sources can also result in over- or underestimates of the rate. Lastly, the international comparability of this indicator can be affected by the use of different concepts of enrolment and out-of-school children across countries.\n\nStatistical concept and methodology: The rate of out-of-school adolescents allows to compare across countries with different population sizes. It shows the share of official lower secondary age adolescents who never attended school or dropped out to the population of official lower secondary school age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of lower secondary school age", "short_unit": "%" }, "se_ter_cuat_ba_fe_zs": { "title": "Educational attainment, at least Bachelor's or equivalent, population 25+, female (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed Bachelor's or equivalent.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Bachelor's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_ba_ma_zs": { "title": "Educational attainment, at least Bachelor's or equivalent, population 25+, male (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed Bachelor's or equivalent.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Bachelor's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_ba_zs": { "title": "Educational attainment, at least Bachelor's or equivalent, population 25+, total (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed Bachelor's or equivalent.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Bachelor's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_do_fe_zs": { "title": "Educational attainment, Doctoral or equivalent, population 25+, female (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed Doctoral or equivalent.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Doctoral or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_do_ma_zs": { "title": "Educational attainment, Doctoral or equivalent, population 25+, male (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed Doctoral or equivalent.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Doctoral or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_do_zs": { "title": "Educational attainment, Doctoral or equivalent, population 25+, total (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed Doctoral or equivalent.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Doctoral or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_ms_fe_zs": { "title": "Educational attainment, at least Master's or equivalent, population 25+, female (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed Master's or equivalent.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Master's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_ms_ma_zs": { "title": "Educational attainment, at least Master's or equivalent, population 25+, male (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed Master's or equivalent.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Master's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_ms_zs": { "title": "Educational attainment, at least Master's or equivalent, population 25+, total (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed Master's or equivalent.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Master's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_st_fe_zs": { "title": "Educational attainment, at least completed short-cycle tertiary, population 25+, female (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed short-cycle tertiary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed short-cycle tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_st_ma_zs": { "title": "Educational attainment, at least completed short-cycle tertiary, population 25+, male (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed short-cycle tertiary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed short-cycle tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_cuat_st_zs": { "title": "Educational attainment, at least completed short-cycle tertiary, population 25+, total (%) (cumulative)", "description_from_producer": "The percentage of population ages 25 and over that attained or completed short-cycle tertiary education.\n\nLimitations and exceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).\n\nStatistical concept and methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed short-cycle tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "cumulative" }, "se_ter_enrl_tc_zs": { "title": "Pupil-teacher ratio, tertiary", "description_from_producer": "Tertiary school pupil-teacher ratio is the average number of pupils per teacher in tertiary school.\n\nLimitations and exceptions: The comparability of pupil-teacher ratios across countries is affected by the definition of teachers and by differences in class size by grade and in the number of hours taught, as well as the different practices countries employ such as part-time teachers, school shifts, and multi-grade classes. Moreover, the underlying enrollment levels are subject to a variety of reporting errors.\n\nStatistical concept and methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "se_ter_enrr": { "title": "School enrollment, tertiary (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Tertiary education, whether or not to an advanced research qualification, normally requires, as a minimum condition of admission, the successful completion of education at the secondary level.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for tertiary school is calculated by dividing the number of students enrolled in tertiary education regardless of age by the population of the age group which officially corresponds to tertiary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_ter_enrr_fe": { "title": "School enrollment, tertiary, female (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Tertiary education, whether or not to an advanced research qualification, normally requires, as a minimum condition of admission, the successful completion of education at the secondary level.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for tertiary school is calculated by dividing the number of students enrolled in tertiary education regardless of age by the population of the age group which officially corresponds to tertiary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_ter_enrr_ma": { "title": "School enrollment, tertiary, male (% gross)", "description_from_producer": "Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Tertiary education, whether or not to an advanced research qualification, normally requires, as a minimum condition of admission, the successful completion of education at the secondary level.\n\nLimitations and exceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\nStatistical concept and methodology: Gross enrollment ratio for tertiary school is calculated by dividing the number of students enrolled in tertiary education regardless of age by the population of the age group which officially corresponds to tertiary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% gross", "short_unit": "%" }, "se_ter_tchr_fe_zs": { "title": "Tertiary education, academic staff (% female)", "description_from_producer": "Tertiary education, academic staff (% female) is the share of female academic staff in tertiary education.\n\nStatistical concept and methodology: The share of female academic staffs in tertiary education is calculated by dividing the total number of female academic staffs at tertiary level of education by the total number of academic staffs at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% female", "short_unit": "%" }, "se_xpd_cprm_zs": { "title": "Current education expenditure, primary (% of total expenditure in primary public institutions)", "description_from_producer": "Current expenditure is expressed as a percentage of direct expenditure in public educational institutions (instructional and non-instructional) of the specified level of education. Financial aid to students and other transfers are excluded from direct expenditure. Current expenditure is consumed within the current year and would have to be renewed if needed in the following year. It includes staff compensation and current expenditure other than for staff compensation (ex. on teaching materials, ancillary services and administration).\n\nStatistical concept and methodology: Current expenditure, primary is calculated by dividing all current expenditure in public institutions of primary education by total expenditure (current and capital) in public institutions of primary education, and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total expenditure in primary public institutions", "short_unit": "%" }, "se_xpd_csec_zs": { "title": "Current education expenditure, secondary (% of total expenditure in secondary public institutions)", "description_from_producer": "Current expenditure is expressed as a percentage of direct expenditure in public educational institutions (instructional and non-instructional) of the specified level of education. Financial aid to students and other transfers are excluded from direct expenditure. Current expenditure is consumed within the current year and would have to be renewed if needed in the following year. It includes staff compensation and current expenditure other than for staff compensation (ex. on teaching materials, ancillary services and administration).\n\nStatistical concept and methodology: Current expenditure, secondary is calculated by dividing all current expenditure in public institutions of secondary education by total expenditure (current and capital) in public institutions of secondary education, and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total expenditure in secondary public institutions", "short_unit": "%" }, "se_xpd_cter_zs": { "title": "Current education expenditure, tertiary (% of total expenditure in tertiary public institutions)", "description_from_producer": "Current expenditure is expressed as a percentage of direct expenditure in public educational institutions (instructional and non-instructional) of the specified level of education. Financial aid to students and other transfers are excluded from direct expenditure. Current expenditure is consumed within the current year and would have to be renewed if needed in the following year. It includes staff compensation and current expenditure other than for staff compensation (ex. on teaching materials, ancillary services and administration).\n\nStatistical concept and methodology: Current expenditure, tertiary is calculated by dividing all current expenditure in public institutions of tertiary education by total expenditure (current and capital) in public institutions of tertiary education, and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total expenditure in tertiary public institutions", "short_unit": "%" }, "se_xpd_ctot_zs": { "title": "Current education expenditure, total (% of total expenditure in public institutions)", "description_from_producer": "Current expenditure is expressed as a percentage of direct expenditure in public educational institutions (instructional and non-instructional) of the specified level of education. Financial aid to students and other transfers are excluded from direct expenditure. Current expenditure is consumed within the current year and would have to be renewed if needed in the following year. It includes staff compensation and current expenditure other than for staff compensation (ex. on teaching materials, ancillary services and administration).\n\nStatistical concept and methodology: Current expenditure, total is calculated by dividing all current expenditure in public institutions of all levels of education by total expenditure (current and capital) in public institutions of all levels of education, and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total expenditure in public institutions", "short_unit": "%" }, "se_xpd_prim_pc_zs": { "title": "Government expenditure per student, primary (% of GDP per capita)", "description_from_producer": "Government expenditure per student is the average general government expenditure (current, capital, and transfers) per student in the given level of education, expressed as a percentage of GDP per capita.\n\nStatistical concept and methodology: General government expenditure per student in primary education is calculated by dividing total government expenditure on primary education by the number of students at primary level, expressed as a percentage of GDP per capita. Aggregate data are World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Data on GDP per capita come from the World Bank.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP per capita", "short_unit": "%" }, "se_xpd_prim_zs": { "title": "Expenditure on primary education (% of government expenditure on education)", "description_from_producer": "Expenditure on primary education is expressed as a percentage of total general government expenditure on education. General government usually refers to local, regional and central governments.\n\nLimitations and exceptions: Data disaggregated by level of education are estimates in some instances. It is often difficult to separate lower from upper secondary education expenditure, or pre-primary from primary.\n\nStatistical concept and methodology: The share of expenditure on primary education to total government expenditure on education is calculated by dividing government expenditure on primary education by total government expenditure on education (all levels combined), and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of government expenditure on education", "short_unit": "%" }, "se_xpd_seco_pc_zs": { "title": "Government expenditure per student, secondary (% of GDP per capita)", "description_from_producer": "Government expenditure per student is the average general government expenditure (current, capital, and transfers) per student in the given level of education, expressed as a percentage of GDP per capita.\n\nStatistical concept and methodology: General government expenditure per student in secondary education is calculated by dividing total government expenditure on secondary education by the number of students at secondary level, expressed as a percentage of GDP per capita. Aggregate data are World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Data on GDP per capita come from the World Bank.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP per capita", "short_unit": "%" }, "se_xpd_seco_zs": { "title": "Expenditure on secondary education (% of government expenditure on education)", "description_from_producer": "Expenditure on secondary education is expressed as a percentage of total general government expenditure on education. General government usually refers to local, regional and central governments.\n\nLimitations and exceptions: Data disaggregated by level of education are estimates in some instances. It is often difficult to separate lower from upper secondary education expenditure, or pre-primary from primary.\n\nStatistical concept and methodology: The share of expenditure on secondary education to total government expenditure on education is calculated by dividing government expenditure on secondary education by total government expenditure on education (all levels combined), and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of government expenditure on education", "short_unit": "%" }, "se_xpd_tert_pc_zs": { "title": "Government expenditure per student, tertiary (% of GDP per capita)", "description_from_producer": "Government expenditure per student is the average general government expenditure (current, capital, and transfers) per student in the given level of education, expressed as a percentage of GDP per capita.\n\nStatistical concept and methodology: General government expenditure per student in tertiary education is calculated by dividing total government expenditure on tertiary education by the number of students at tertiary level, expressed as a percentage of GDP per capita. Aggregate data are World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Data on GDP per capita come from the World Bank.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP per capita", "short_unit": "%" }, "se_xpd_tert_zs": { "title": "Expenditure on tertiary education (% of government expenditure on education)", "description_from_producer": "Expenditure on tertiary education is expressed as a percentage of total general government expenditure on education. General government usually refers to local, regional and central governments.\n\nLimitations and exceptions: Data disaggregated by level of education are estimates in some instances. It is often difficult to separate lower from upper secondary education expenditure, or pre-primary from primary.\n\nStatistical concept and methodology: The share of expenditure on tertiary education to total government expenditure on education is calculated by dividing government expenditure on tertiary education by total government expenditure on education (all levels combined), and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of government expenditure on education", "short_unit": "%" }, "se_xpd_totl_gb_zs": { "title": "Government expenditure on education, total (% of government expenditure)", "description_from_producer": "General government expenditure on education (current, capital, and transfers) is expressed as a percentage of total general government expenditure on all sectors (including health, education, social services, etc.). It includes expenditure funded by transfers from international sources to government. General government usually refers to local, regional and central governments.\n\nLimitations and exceptions: Data on government expenditure on education may refer to spending by the ministry of education only (excluding spending on educational activities by other ministries). In addition, definitions and methods of data on total general government expenditure may differ across countries.\n\nStatistical concept and methodology: Expenditure on education, total (% of government expenditure) is calculated by dividing total government expenditure on education by the total government expenditure on all sectors and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Data on total general government expenditure were previously collected from countries through the annual questionnaire, but are from the International Monetary Fund's World Economic Outlook database since January 2014. Therefore, current data cannot be compared with data in earlier editions.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of government expenditure", "short_unit": "%" }, "se_xpd_totl_gd_zs": { "title": "Government expenditure on education, total (% of GDP)", "description_from_producer": "General government expenditure on education (current, capital, and transfers) is expressed as a percentage of GDP. It includes expenditure funded by transfers from international sources to government. General government usually refers to local, regional and central governments.\n\nLimitations and exceptions: Data may refer to spending by the ministry of education only (excluding spending on educational activities by other ministries).\n\nStatistical concept and methodology: Government expenditure on education, total (% of GDP) is calculated by dividing total government expenditure for all levels of education by the GDP, and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. GDP data come from the World Bank.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "sg_dmk_alld_fn_zs": { "title": "Women participating in the three decisions (own health care, major household purchases, and visiting family) (% of women age 15-49)", "description_from_producer": "Women participating in the three decisions (own health care, major household purchases, and visiting family) is the percentage of currently married women aged 15-49 who say that they alone or jointly have the final say in all of the three decisions (own health care, large purchases and visits to family, relatives, and friends).\n\nStatistical concept and methodology: Women participating in the three decisions (own health care, major household purchases, and visiting family) is the number of currently married women aged 15-49 who say they alone or jointly have the final say in the three decisions, expressed as percentage of currently married women age 15-49 who have been interviewed and It\u2019s derived by dividing the number of currently married women aged 15-49 who responded they alone or jointly have the final say in the three decisions by total number of currently married women age 15-49 who have been interviewed.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) via World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of women age 15-49", "short_unit": "%" }, "sg_dmk_srcr_fn_zs": { "title": "Women making their own informed decisions regarding sexual relations, contraceptive use and reproductive health care (% of women age 15-49)", "description_from_producer": "Proportion of women ages 15-49 years (married or in union) who make their own decision on all three selected areas i.e. can say no to sexual intercourse with their husband or partner if they do not want; decide on use of contraception; and decide on their own health care. Only women who provide a \u201cyes\u201d answer to all three components are considered as women who \u201cmake her own decisions regarding sexual and reproductive\u201d.\n\nLimitations and exceptions: Current estimates of the indicator are based on currently married or in union women of reproductive age (15-49 years old) who are using any type of contraception. In the current Demographic and Health Surveys (DHS), the question on decision-making on use of contraception is only asked to women who are currently using contraception. Because the questions on decision- making on sexual relations and health care are restricted to women (15-49) currently married or in union, the denominator for Indicator 5.6.1 is women 15-49, who are currently married or in union and currently using contraception. However, agreement has been reached with Macro/ICF for upcoming DHS surveys to ask the question on decision on use of contraception to all married/ in union women aged 15-49 years, whether they are currently using any contraception or not. The DHS model questionnaire for Phase 7 already includes the question on decision-making for women who are not currently using any contraception.\n\nStatistical concept and methodology: Numerator of the indicator is number of married or in union women ages 15-49 who have been interviewed and satisfy all three empowerment criteria: 1)who can say \"no\" to sex; and 2)for whom the decision on contraception is not mainly made by the husband/partner; and 3) for whom decision on health care for themselves ins not usually made by the husband/partner or someone else. Denominator of the indicator is the total number of women ages 15-49 who are married or in union and who have been interviewed.", "origins": [ { "producer": "United Nations Population Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of women age 15-49", "short_unit": "%" }, "sg_gen_parl_zs": { "title": "Proportion of seats held by women in national parliaments (%)", "description_from_producer": "Women in parliaments are the percentage of parliamentary seats in a single or lower chamber held by women.\n\nLimitations and exceptions: The number of countries covered varies with suspensions or dissolutions of parliaments. There can be difficulties in obtaining information on by-election results and replacements due to death or resignation. These changes are ad hoc events which are more difficult to keep track of. By-elections, for instance, are often not announced internationally as general elections are. Parliaments vary considerably in their internal workings and procedures, however, generally legislate, oversee government and represent the electorate. In terms of measuring women's contribution to political decision making, this indicator may not be sufficient because some women may face obstacles in fully and efficiently carrying out their parliamentary mandate.\n\nThe data is compiled by the Inter-Parliamentary Union on the basis of information provided by National Parliaments. The percentages do not take into account the case of parliaments for which no data was available at that date. Information is available in all countries where a national legislature exists and therefore does not include parliaments that have been dissolved or suspended for an indefinite period.\n\nStatistical concept and methodology: The proportion of seats held by women in national parliaments is the number of seats held by women members in single or lower chambers of national parliaments, expressed as a percentage of all occupied seats; it is derived by dividing the total number of seats occupied by women by the total number of seats in parliament.\n\nNational parliaments can be bicameral or unicameral. This indicator covers the single chamber in unicameral parliaments and the lower chamber in bicameral parliaments. It does not cover the upper chamber of bicameral parliaments. Seats are usually won by members in general parliamentary elections. Seats may also be filled by nomination, appointment, indirect election, rotation of members and by-election. Seats refer to the number of parliamentary mandates, or the number of members of parliament.", "origins": [ { "producer": "Inter-Parliamentary Union (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sg_law_indx": { "title": "Women Business and the Law Index Score (scale 1-100)", "description_from_producer": "The index measures how laws and regulations affect women\u2019s economic opportunity. Overall scores are calculated by taking the average score of each index (Mobility, Workplace, Pay, Marriage, Parenthood, Entrepreneurship, Assets and Pension), with 100 representing the highest possible score.\n\nLimitations and exceptions: The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research.\n\nStatistical concept and methodology: Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman\u2019s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sg_tim_uwrk_fe": { "title": "Proportion of time spent on unpaid domestic and care work, female (% of 24 hour day)", "description_from_producer": "The average time women spend on household provision of services for own consumption. Data are expressed as a proportion of time in a day. Domestic and care work includes food preparation, dishwashing, cleaning and upkeep of a dwelling, laundry, ironing, gardening, caring for pets, shopping, installation, servicing and repair of personal and household goods, childcare, and care of the sick, elderly or disabled household members, among others.\n\nLimitations and exceptions: Data may not be strictly comparable across countries as the methods and sampling involved for data collection may differ.\n\nStatistical concept and methodology: Proportion of time spent on unpaid domestic and care work is calculated by dividing the daily average number of hours spent on unpaid domestic and care work by 24 hours. Data presented for this indicator are expressed as a proportion of time in a day. Weekly data is averaged over seven days of the week to obtain the daily average time.", "origins": [ { "producer": "United Nations Statistics Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of 24 hour day", "short_unit": "%" }, "sg_tim_uwrk_ma": { "title": "Proportion of time spent on unpaid domestic and care work, male (% of 24 hour day)", "description_from_producer": "The average time men spend on household provision of services for own consumption. Data are expressed as a proportion of time in a day. Domestic and care work includes food preparation, dishwashing, cleaning and upkeep of a dwelling, laundry, ironing, gardening, caring for pets, shopping, installation, servicing and repair of personal and household goods, childcare, and care of the sick, elderly or disabled household members, among others.\n\nLimitations and exceptions: Data may not be strictly comparable across countries as the methods and sampling involved for data collection may differ.\n\nStatistical concept and methodology: Proportion of time spent on unpaid domestic and care work is calculated by dividing the daily average number of hours spent on unpaid domestic and care work by 24 hours. Data presented for this indicator are expressed as a proportion of time in a day. Weekly data is averaged over seven days of the week to obtain the daily average time.", "origins": [ { "producer": "United Nations Statistics Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of 24 hour day", "short_unit": "%" }, "sg_vaw_1549_zs": { "title": "Proportion of women subjected to physical and/or sexual violence in the last 12 months (% of ever-partnered women ages 15-49)", "description_from_producer": "Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women age 15-49 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.\n\nLimitations and exceptions: Collecting valid, reliable, and ethical data on domestic violence poses particular challenges because what constitutes violence or abuse varies across cultures and among individuals. In addition, a culture of silence usually surrounds domestic violence and can affect reporting.", "origins": [ { "producer": "UN Statistics Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of women age 15-49", "short_unit": "%" }, "sg_vaw_argu_zs": { "title": "Women who believe a husband is justified in beating his wife when she argues with him (%)", "description_from_producer": "Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she argues with him.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sg_vaw_burn_zs": { "title": "Women who believe a husband is justified in beating his wife when she burns the food (%)", "description_from_producer": "Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she burns the food.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sg_vaw_goes_zs": { "title": "Women who believe a husband is justified in beating his wife when she goes out without telling him (%)", "description_from_producer": "Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she goes out without telling him.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sg_vaw_negl_zs": { "title": "Women who believe a husband is justified in beating his wife when she neglects the children (%)", "description_from_producer": "Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she neglects the children.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sg_vaw_reas_zs": { "title": "Women who believe a husband is justified in beating his wife (any of five reasons) (%)", "description_from_producer": "Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner for any of the following five reasons: argues with him; refuses to have sex; burns the food; goes out without telling him; or when she neglects the children.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sg_vaw_refu_zs": { "title": "Women who believe a husband is justified in beating his wife when she refuses sex with him (%)", "description_from_producer": "Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she refuses sex with him.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_alc_pcap_fe_li": { "title": "Total alcohol consumption per capita, female (liters of pure alcohol, projected estimates, female 15+ years of age)", "description_from_producer": "Total alcohol per capita consumption is defined as the total (sum of recorded and unrecorded alcohol) amount of alcohol consumed per person (15 years of age or older) over a calendar year, in litres of pure alcohol, adjusted for tourist consumption.\n\nStatistical concept and methodology: The estimates for the total alcohol consumption are produced by summing up the 3-year average per capita (15+) recorded alcohol consumption and an estimate of per capita (15+) unrecorded alcohol consumption for a calendar year. Tourist consumption takes into account tourists visiting the country and inhabitants visiting other countries.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_alc_pcap_li": { "title": "Total alcohol consumption per capita (liters of pure alcohol, projected estimates, 15+ years of age)", "description_from_producer": "Total alcohol per capita consumption is defined as the total (sum of recorded and unrecorded alcohol) amount of alcohol consumed per person (15 years of age or older) over a calendar year, in litres of pure alcohol, adjusted for tourist consumption.\n\nStatistical concept and methodology: The estimates for the total alcohol consumption are produced by summing up the 3-year average per capita (15+) recorded alcohol consumption and an estimate of per capita (15+) unrecorded alcohol consumption for a calendar year. Tourist consumption takes into account tourists visiting the country and inhabitants visiting other countries.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "liters of pure alcohol, projected estimates, 15+ years of age", "display": { "name": "Alcohol consumption" }, "presentation": { "title_public": "Total alcohol consumption per capit", "title_variant": "In liters of pure alcohol, projected estimates, 15+ years of age" } }, "sh_alc_pcap_ma_li": { "title": "Total alcohol consumption per capita, male (liters of pure alcohol, projected estimates, male 15+ years of age)", "description_from_producer": "Total alcohol per capita consumption is defined as the total (sum of recorded and unrecorded alcohol) amount of alcohol consumed per person (15 years of age or older) over a calendar year, in litres of pure alcohol, adjusted for tourist consumption.\n\nStatistical concept and methodology: The estimates for the total alcohol consumption are produced by summing up the 3-year average per capita (15+) recorded alcohol consumption and an estimate of per capita (15+) unrecorded alcohol consumption for a calendar year. Tourist consumption takes into account tourists visiting the country and inhabitants visiting other countries.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_anm_allw_zs": { "title": "Prevalence of anemia among women of reproductive age (% of women ages 15-49)", "description_from_producer": "Prevalence of anemia among women of reproductive age refers to the combined prevalence of both non-pregnant with haemoglobin levels below 12 g/dL and pregnant women with haemoglobin levels below 11 g/dL.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of women ages 15-49", "short_unit": "%" }, "sh_anm_chld_zs": { "title": "Prevalence of anemia among children (% of children ages 6-59 months)", "description_from_producer": "Prevalence of anemia, children ages 6-59 months, is the percentage of children ages 6-59 months whose hemoglobin level is less than 110 grams per liter, adjusted for altitude.\n\nLimitations and exceptions: Data for blood haemoglobin concentrations are still limited, compared to other nutritional indicators such as hild anthropometry. As a result, the estimates may not capture the full variation across countries and regions.\n\nStatistical concept and methodology: Data on anemia are compiled by the WHO, and a statistical model was used to estimate trends. WHO\u2019s hemoglobin threshold concentration in blood was used.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_anm_nprg_zs": { "title": "Prevalence of anemia among non-pregnant women (% of women ages 15-49)", "description_from_producer": "Prevalence of anemia, non-pregnant women, is the percentage of non-pregnant women whose hemoglobin level is less than 120 grams per liter at sea level.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of women ages 15-49", "short_unit": "%" }, "sh_con_1524_fe_zs": { "title": "Condom use, population ages 15-24, female (% of females ages 15-24)", "description_from_producer": "Condom use, female is the percentage of the female population ages 15-24 who used a condom at last intercourse in the last 12 months.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) and UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of females ages 15-24", "short_unit": "%" }, "sh_con_1524_ma_zs": { "title": "Condom use, population ages 15-24, male (% of males ages 15-24)", "description_from_producer": "Condom use, male is the percentage of the male population ages 15-24 who used a condom at last intercourse in the last 12 months.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) and UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of males ages 15-24", "short_unit": "%" }, "sh_dth_0509": { "title": "Number of deaths ages 5-9 years", "description_from_producer": "Number of deaths of children ages 5-9 years\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dth_1014": { "title": "Number of deaths ages 10-14 years", "description_from_producer": "Number of deaths of adolescents ages 10-14 years\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dth_1519": { "title": "Number of deaths ages 15-19 years", "description_from_producer": "Number of deaths of adolescents ages 15-19 years\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dth_2024": { "title": "Number of deaths ages 20-24 years", "description_from_producer": "Number of deaths of youths ages 20-24 years\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dth_comm_zs": { "title": "Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total)", "description_from_producer": "Cause of death refers to the share of all deaths for all ages by underlying causes. Communicable diseases and maternal, prenatal and nutrition conditions include infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.\n\nLimitations and exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.\n\nStatistical concept and methodology: Data on cause of death are compiled by the WHO, based mainly on data from national vital registry systems, as well as sample registration systems, population laboratories, and epidemiological analysis of specific conditions. Data are classified based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision. Data have been carefully analyzed to take into account incomplete coverage of vital registration and the likely differences in cause of death patterns that would be expected in undercovered and often poorer subpopulations. Special attention has also been paid to misattribution or miscoding of causes of death in cardiovascular diseases, cancer, injuries, and general ill-defined categories. For further information, consult the original source.", "origins": [ { "producer": "World Bank based on data from the World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sh_dth_imrt": { "title": "Number of infant deaths", "description_from_producer": "Number of infants dying before reaching one year of age.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dth_injr_zs": { "title": "Cause of death, by injury (% of total)", "description_from_producer": "Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.\n\nLimitations and exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.\n\nStatistical concept and methodology: Data on cause of death are compiled by the WHO, based mainly on data from national vital registry systems, as well as sample registration systems, population laboratories, and epidemiological analysis of specific conditions. Data are classified based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision. Data have been carefully analyzed to take into account incomplete coverage of vital registration and the likely differences in cause of death patterns that would be expected in under-covered and often poorer subpopulations. Special attention has also been paid to misattribution or miscoding of causes of death in cardiovascular diseases, cancer, injuries, and general ill-defined categories. For further information, consult the original source.", "origins": [ { "producer": "World Bank based on data from the World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sh_dth_mort": { "title": "Number of under-five deaths", "description_from_producer": "Number of children dying before reaching age five.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dth_ncom_zs": { "title": "Cause of death, by non-communicable diseases (% of total)", "description_from_producer": "Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.\n\nLimitations and exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.\n\nStatistical concept and methodology: Data on cause of death are compiled by the WHO, based mainly on data from national vital registry systems, as well as sample registration systems, population laboratories, and epidemiological analysis of specific conditions. Data are classified based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision. Data have been carefully analyzed to take into account incomplete coverage of vital registration and the likely differences in cause of death patterns that would be expected in undercovered and often poorer subpopulations. Special attention has also been paid to misattribution or miscoding of causes of death in cardiovascular diseases, cancer, injuries, and general ill-defined categories. For further information, consult the original source.", "origins": [ { "producer": "World Bank based on data from the World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sh_dth_nmrt": { "title": "Number of neonatal deaths", "description_from_producer": "Number of neonates dying before reaching 28 days of age.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dyn_0509": { "title": "Probability of dying among children ages 5-9 years (per 1,000)", "description_from_producer": "Probability of dying between age 5-9 years of age expressed per 1,000 children aged 5, if subject to age-specific mortality rates of the specified year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dyn_1014": { "title": "Probability of dying among adolescents ages 10-14 years (per 1,000)", "description_from_producer": "Probability of dying between age 10-14 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dyn_1519": { "title": "Probability of dying among adolescents ages 15-19 years (per 1,000)", "description_from_producer": "Probability of dying between age 15-19 years of age expressed per 1,000 adolescents age 15, if subject to age-specific mortality rates of the specified year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dyn_2024": { "title": "Probability of dying among youth ages 20-24 years (per 1,000)", "description_from_producer": "Probability of dying between age 20-24 years of age expressed per 1,000 youths age 20, if subject to age-specific mortality rates of the specified year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dyn_aids_fe_zs": { "title": "Women's share of population ages 15+ living with HIV (%)", "description_from_producer": "Prevalence of HIV is the percentage of people who are infected with HIV. Female rate is as a percentage of the total population ages 15+ who are living with HIV.\n\nLimitations and exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information.\n\nStatistical concept and methodology: HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable.\n\nData on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_dyn_aids_zs": { "title": "Prevalence of HIV, total (% of population ages 15-49)", "description_from_producer": "Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.\n\nLimitations and exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information.\n\nStatistical concept and methodology: HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable.\n\nData on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population ages 15-49", "short_unit": "%" }, "sh_dyn_mort": { "title": "Mortality rate, under-5 (per 1,000 live births)", "description_from_producer": "Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 live births", "display": { "name": "Child mortality", "tolerance": 5, "isProjection": false, "conversionFactor": 0.1 }, "presentation": { "title_public": "Mortality rate, under-5 (per 1,000 live births)" } }, "sh_dyn_mort_fe": { "title": "Mortality rate, under-5, female (per 1,000 live births)", "description_from_producer": "Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female age-specific mortality rates of the specified year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 live births" }, "sh_dyn_mort_ma": { "title": "Mortality rate, under-5, male (per 1,000 live births)", "description_from_producer": "Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male age-specific mortality rates of the specified year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 live births", "display": { "name": "Child mortality rate of boys", "tolerance": 5, "conversionFactor": 0.1 }, "presentation": { "title_public": "Mortality rate, under-5, male (per 1,000 live births)" } }, "sh_dyn_ncom_fe_zs": { "title": "Mortality from CVD, cancer, diabetes or CRD between exact ages 30 and 70, female (%)", "description_from_producer": "Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dyn_ncom_ma_zs": { "title": "Mortality from CVD, cancer, diabetes or CRD between exact ages 30 and 70, male (%)", "description_from_producer": "Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_dyn_ncom_zs": { "title": "Mortality from CVD, cancer, diabetes or CRD between exact ages 30 and 70 (%)", "description_from_producer": "Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_dyn_nmrt": { "title": "Mortality rate, neonatal (per 1,000 live births)", "description_from_producer": "Neonatal mortality rate is the number of neonates dying before reaching 28 days of age, per 1,000 live births in a given year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 live births" }, "sh_fpl_satm_zs": { "title": "Demand for family planning satisfied by modern methods (% of married women with demand for family planning)", "description_from_producer": "Demand for family planning satisfied by modern methods refers to the percentage of married women ages 15-49 years whose need for family planning is satisfied with modern methods.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) via World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of married women with demand for family planning", "short_unit": "%" }, "sh_h2o_basw_ru_zs": { "title": "People using at least basic drinking water services, rural (% of rural population)", "description_from_producer": "The percentage of people using at least basic water services. This indicator encompasses both people using basic water services as well as those using safely managed water services. Basic drinking water services is defined as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.\n\nLimitations and exceptions: National, regional and income group estimates are made when data are available for at least 50 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines a basic drinking water service as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of rural population", "short_unit": "%" }, "sh_h2o_basw_ur_zs": { "title": "People using at least basic drinking water services, urban (% of urban population)", "description_from_producer": "The percentage of people using at least basic water services. This indicator encompasses both people using basic water services as well as those using safely managed water services. Basic drinking water services is defined as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.\n\nLimitations and exceptions: National, regional and income group estimates are made when data are available for at least 50 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines a basic drinking water service as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of urban population", "short_unit": "%" }, "sh_h2o_basw_zs": { "title": "People using at least basic drinking water services (% of population)", "description_from_producer": "The percentage of people using at least basic water services. This indicator encompasses both people using basic water services as well as those using safely managed water services. Basic drinking water services is defined as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.\n\nLimitations and exceptions: National, regional and income group estimates are made when data are available for at least 50 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines a basic drinking water service as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "sh_h2o_smdw_ru_zs": { "title": "People using safely managed drinking water services, rural (% of rural population)", "description_from_producer": "The percentage of people using drinking water from an improved source that is accessible on premises, available when needed and free from faecal and priority chemical contamination. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.\n\nLimitations and exceptions: In order to meet the criteria for a safely managed drinking water service, an improved water source should meet three criteria: it should be accessible on the premises (accessibility), water should be available when needed (availability), and the water supplied should be free from contamination (quality). Many countries lack data on one or more elements of safely managed drinking water. The WHO/UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygiene (JMP) provide national estimates only when data are available on drinking water quality and at least one of the other criteria (accessibility and availability). Regional and income group estimates are made when data are available for at least 30 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines a safely managed drinking water as an improved water source that is accessible on premises, available when needed and free from faecal and priority chemical contamination. Improved water sources include: piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of rural population", "short_unit": "%" }, "sh_h2o_smdw_ur_zs": { "title": "People using safely managed drinking water services, urban (% of urban population)", "description_from_producer": "The percentage of people using drinking water from an improved source that is accessible on premises, available when needed and free from faecal and priority chemical contamination. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.\n\nLimitations and exceptions: In order to meet the criteria for a safely managed drinking water service, an improved water source should meet three criteria: it should be accessible on the premises (accessibility), water should be available when needed (availability), and the water supplied should be free from contamination (quality). Many countries lack data on one or more elements of safely managed drinking water. The WHO/UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygiene (JMP) provide national estimates only when data are available on drinking water quality and at least one of the other criteria (accessibility and availability). Regional and income group estimates are made when data are available for at least 30 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines a safely managed drinking water as an improved water source that is accessible on premises, available when needed and free from faecal and priority chemical contamination. Improved water sources include: piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of urban population", "short_unit": "%" }, "sh_h2o_smdw_zs": { "title": "People using safely managed drinking water services (% of population)", "description_from_producer": "The percentage of people using drinking water from an improved source that is accessible on premises, available when needed and free from faecal and priority chemical contamination. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.\n\nLimitations and exceptions: In order to meet the criteria for a safely managed drinking water service, an improved water source should meet three criteria: it should be accessible on the premises (accessibility), water should be available when needed (availability), and the water supplied should be free from contamination (quality). Many countries lack data on one or more elements of safely managed drinking water. The WHO/UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygiene (JMP) provide national estimates only when data are available on drinking water quality and at least one of the other criteria (accessibility and availability). Regional and income group estimates are made when data are available for at least 30 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines a safely managed drinking water as an improved water source that is accessible on premises, available when needed and free from faecal and priority chemical contamination. Improved water sources include: piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "sh_hiv_0014": { "title": "Children (0-14) living with HIV", "description_from_producer": "Children living with HIV refers to the number of children ages 0-14 who are infected with HIV.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "0-14", "short_unit": "0-14" }, "sh_hiv_1524_fe_zs": { "title": "Prevalence of HIV, female (% ages 15-24)", "description_from_producer": "Prevalence of HIV, female is the percentage of females who are infected with HIV. Youth rates are as a percentage of the relevant age group.\n\nLimitations and exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information.\n\nStatistical concept and methodology: HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable.\n\nData on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% ages 15-24", "short_unit": "%" }, "sh_hiv_1524_ma_zs": { "title": "Prevalence of HIV, male (% ages 15-24)", "description_from_producer": "Prevalence of HIV, male is the percentage of males who are infected with HIV. Youth rates are as a percentage of the relevant age group.\n\nLimitations and exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information.\n\nStatistical concept and methodology: HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable.\n\nData on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% ages 15-24", "short_unit": "%" }, "sh_hiv_artc_zs": { "title": "Antiretroviral therapy coverage (% of people living with HIV)", "description_from_producer": "Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.\n\nLimitations and exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information.\n\nStatistical concept and methodology: Data on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS.\n\nAntiretroviral therapy has led to huge reductions in death and suffering of people with advanced HIV infection.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of people living with HIV", "short_unit": "%" }, "sh_hiv_incd": { "title": "Adults (ages 15-49) newly infected with HIV", "description_from_producer": "Number of adults (ages 15-49) newly infected with HIV.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "ages 15+", "short_unit": "ages 15+" }, "sh_hiv_incd_14": { "title": "Children (ages 0-14) newly infected with HIV", "description_from_producer": "Number of children (ages 0-14) newly infected with HIV.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "ages 0-14" }, "sh_hiv_incd_tl": { "title": "Adults (ages 15+) and children (ages 0-14) newly infected with HIV", "description_from_producer": "Number of adults (ages 15+) and children (ages 0-14) newly infected with HIV.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "ages 0-14" }, "sh_hiv_incd_tl_p3": { "title": "Incidence of HIV, all (per 1,000 uninfected population)", "description_from_producer": "Number of new HIV infections among uninfected populations expressed per 1,000 uninfected population in the year before the period.\n\nStatistical concept and methodology: Data on incidence of HIV are from the Joint United Nations Programme on HIV/AIDS. Because of challenges in collecting direct measures of HIV incidence, modelled estimates are used (the Spectrum software). The models incorporate data on HIV prevalence from surveys of the general population, antenatal clinic attendees, and populations at increased risk of contracting HIV (such as sex workers, men who have sex with men, and people who inject drugs) and on the number of people receiving antiretroviral therapy, which will increase the prevalence of HIV because people living with HIV now survive longer. In countries with high-quality health information systems the models are also informed by case reporting and vital registration data.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_hiv_incd_yg": { "title": "Young people (ages 15-24) newly infected with HIV", "description_from_producer": "Number of young people (ages 15-24) newly infected with HIV.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_hiv_incd_yg_p3": { "title": "Incidence of HIV, ages 15-24 (per 1,000 uninfected population ages 15-24)", "description_from_producer": "Number of new HIV infections among uninfected populations ages 15-24 expressed per 1,000 uninfected population ages 15-24 in the year before the period.\n\nStatistical concept and methodology: Data on incidence of HIV are from the Joint United Nations Programme on HIV/AIDS. Because of challenges in collecting direct measures of HIV incidence, modelled estimates are used (the Spectrum software). The models incorporate data on HIV prevalence from surveys of the general population, antenatal clinic attendees, and populations at increased risk of contracting HIV (such as sex workers, men who have sex with men, and people who inject drugs) and on the number of people receiving antiretroviral therapy, which will increase the prevalence of HIV because people living with HIV now survive longer. In countries with high-quality health information systems the models are also informed by case reporting and vital registration data.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_hiv_incd_zs": { "title": "Incidence of HIV, ages 15-49 (per 1,000 uninfected population ages 15-49)", "description_from_producer": "Number of new HIV infections among uninfected populations ages 15-49 expressed per 1,000 uninfected population in the year before the period.\n\nStatistical concept and methodology: Data on incidence of HIV are from the Joint United Nations Programme on HIV/AIDS. Because of challenges in collecting direct measures of HIV incidence, modelled estimates are used (the Spectrum software). The models incorporate data on HIV prevalence from surveys of the general population, antenatal clinic attendees, and populations at increased risk of contracting HIV (such as sex workers, men who have sex with men, and people who inject drugs) and on the number of people receiving antiretroviral therapy, which will increase the prevalence of HIV because people living with HIV now survive longer. In countries with high-quality health information systems the models are also informed by case reporting and vital registration data.", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of uninfected population ages 15-49", "short_unit": "%" }, "sh_hiv_pmtc_zs": { "title": "Antiretroviral therapy coverage for PMTCT (% of pregnant women living with HIV)", "description_from_producer": "Percentage of pregnant women with HIV who receive antiretroviral medicine for prevention of mother-to-child transmission (PMTCT).", "origins": [ { "producer": "UNAIDS (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of pregnant women living with HIV", "short_unit": "%" }, "sh_imm_hepb": { "title": "Immunization, HepB3 (% of one-year-old children)", "description_from_producer": "Child immunization rate, hepatitis B is the percentage of children ages 12-23 months who received hepatitis B vaccinations before 12 months or at any time before the survey. A child is considered adequately immunized after three doses.\n\nLimitations and exceptions: In many developing countries a lack of precise information on the size of the cohort of one-year-old children makes immunization coverage difficult to estimate from program statistics.\n\nStatistical concept and methodology: Governments in developing countries usually finance immunization against measles and diphtheria, pertussis (whooping cough), and tetanus (DTP) as part of the basic public health package. The data shown here are based on an assessment of national immunization coverage rates by the WHO and UNICEF. The assessment considered both administrative data from service providers and household survey data on children's immunization histories. Based on the data available, consideration of potential biases, and contributions of local experts, the most likely true level of immunization coverage was determined for each year.\n\nNotes on regional and global aggregates: When the vaccine is not introduced in a national immunization schedule, the missing value is assumed zero (or close to zero) in the relevant groups' averages.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of one-year-old children", "short_unit": "%" }, "sh_imm_idpt": { "title": "Immunization, DPT (% of children ages 12-23 months)", "description_from_producer": "Child immunization, DPT, measures the percentage of children ages 12-23 months who received DPT vaccinations before 12 months or at any time before the survey. A child is considered adequately immunized against diphtheria, pertussis (or whooping cough), and tetanus (DPT) after receiving three doses of vaccine.\n\nLimitations and exceptions: In many developing countries a lack of precise information on the size of the cohort of one-year-old children makes immunization coverage difficult to estimate from program statistics.\n\nStatistical concept and methodology: Governments in developing countries usually finance immunization against measles and diphtheria, pertussis (whooping cough), and tetanus (DTP) as part of the basic public health package. The data shown here are based on an assessment of national immunization coverage rates by the WHO and UNICEF. The assessment considered both administrative data from service providers and household survey data on children's immunization histories. Based on the data available, consideration of potential biases, and contributions of local experts, the most likely true level of immunization coverage was determined for each year.\n\nNotes on regional and global aggregates: When the vaccine is not introduced in a national immunization schedule, the missing value is assumed zero (or close to zero) in the relevant groups' averages.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children ages 12-23 months", "short_unit": "%" }, "sh_imm_meas": { "title": "Immunization, measles (% of children ages 12-23 months)", "description_from_producer": "Child immunization, measles, measures the percentage of children ages 12-23 months who received the measles vaccination before 12 months or at any time before the survey. A child is considered adequately immunized against measles after receiving one dose of vaccine.\n\nLimitations and exceptions: In many developing countries a lack of precise information on the size of the cohort of one-year-old children makes immunization coverage difficult to estimate from program statistics.\n\nStatistical concept and methodology: Governments in developing countries usually finance immunization against measles and diphtheria, pertussis (whooping cough), and tetanus (DTP) as part of the basic public health package. The data shown here are based on an assessment of national immunization coverage rates by the WHO and UNICEF. The assessment considered both administrative data from service providers and household survey data on children's immunization histories. Based on the data available, consideration of potential biases, and contributions of local experts, the most likely true level of immunization coverage was determined for each year.\n\nNotes on regional and global aggregates: When the vaccine is not introduced in a national immunization schedule, the missing value is assumed zero (or close to zero) in the relevant groups' averages.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children ages 12-23 months", "short_unit": "%" }, "sh_med_beds_zs": { "title": "Hospital beds (per 1,000 people)", "description_from_producer": "Hospital beds include inpatient beds available in public, private, general, and specialized hospitals and rehabilitation centers. In most cases beds for both acute and chronic care are included.\n\nLimitations and exceptions: Depending on the source and means of monitoring, data may not be exactly comparable across countries. For more information, see the original source.\n\nStatistical concept and methodology: Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.\n\nAvailability and use of health services, such as hospital beds per 1,000 people, reflect both demand- and supply-side factors. In the absence of a consistent definition this is a crude indicator of the extent of physical, financial, and other barriers to health care.\n\nNotes from original source: Depending on the source and means of monitoring, data may not be exactly comparable across countries. See listed source for country-specific details.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 people" }, "sh_med_cmhw_p3": { "title": "Community health workers (per 1,000 people)", "description_from_producer": "Community health workers include various types of community health aides, many with country-specific occupational titles such as community health officers, community health-education workers, family health workers, lady health visitors and health extension package workers.\n\nLimitations and exceptions: The WHO compiles data from household and labor force surveys, censuses, and administrative records. Data comparability is limited by differences in definitions and training of medical personnel varies. In addition, human resources tend to be concentrated in urban areas, so that average densities do not provide a full picture of health personnel available to the entire population.\n\nStatistical concept and methodology: Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.\n\nData on health worker (physicians, nurses and midwives, and community health workers) density show the availability of medical personnel.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 people" }, "sh_med_numw_p3": { "title": "Nurses and midwives (per 1,000 people)", "description_from_producer": "Nurses and midwives include professional nurses, professional midwives, auxiliary nurses, auxiliary midwives, enrolled nurses, enrolled midwives and other associated personnel, such as dental nurses and primary care nurses.\n\nLimitations and exceptions: The WHO compiles data from household and labor force surveys, censuses, and administrative records. Data comparability is limited by differences in definitions and training of medical personnel varies. In addition, human resources tend to be concentrated in urban areas, so that average densities do not provide a full picture of health personnel available to the entire population.\n\nStatistical concept and methodology: Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.\n\nData on health worker (physicians, nurses and midwives, and community health workers) density show the availability of medical personnel.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 people" }, "sh_med_phys_zs": { "title": "Physicians (per 1,000 people)", "description_from_producer": "Physicians include generalist and specialist medical practitioners.\n\nLimitations and exceptions: The WHO compiles data from household and labor force surveys, censuses, and administrative records. Data comparability is limited by differences in definitions and training of medical personnel varies. In addition, human resources tend to be concentrated in urban areas, so that average densities do not provide a full picture of health personnel available to the entire population.\n\nStatistical concept and methodology: Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.\n\nData on health worker (physicians, nurses and midwives, and community health workers) density show the availability of medical personnel.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 people" }, "sh_med_saop_p5": { "title": "Specialist surgical workforce (per 100,000 population)", "description_from_producer": "Specialist surgical workforce is the number of specialist surgical, anaesthetic, and obstetric (SAO) providers who are working in each country per 100,000 population.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 population" }, "sh_mlr_incd_p3": { "title": "Incidence of malaria (per 1,000 population at risk)", "description_from_producer": "Incidence of malaria is the number of new cases of malaria in a year per 1,000 population at risk.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 population at risk" }, "sh_mlr_nets_zs": { "title": "Use of insecticide-treated bed nets (% of under-5 population)", "description_from_producer": "Use of insecticide-treated bed nets refers to the percentage of children under age five who slept under an insecticide-treated bednet to prevent malaria.\n\nStatistical concept and methodology: Malaria is endemic to the poorest countries in the world, mainly in tropical and subtropical regions of Africa, Asia, and the Americas. Insecticide-treated nets, properly used and maintained, are one of the most important malaria-preventive strategies to limit human-mosquito contact.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of under-5 population", "short_unit": "%" }, "sh_mlr_tret_zs": { "title": "Children with fever receiving antimalarial drugs (% of children under age 5 with fever)", "description_from_producer": "Malaria treatment refers to the percentage of children under age five who were ill with fever in the last two weeks and received any appropriate (locally defined) anti-malarial drugs.\n\nStatistical concept and methodology: Malaria is endemic to the poorest countries in the world, mainly in tropical and subtropical regions of Africa, Asia, and the Americas. Prompt and effective treatment of malaria is a critical element of malaria control. It is vital that sufferers, especially children under age 5, start treatment within 24 hours of the onset of symptoms, to prevent progression - often rapid - to severe malaria and death. Data on malaria are from national-level surveys, including Multiple Indicator Cluster Surveys, Demographic and Health Surveys, and Malaria Indicator Surveys.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under age 5 with fever", "short_unit": "%" }, "sh_mmr_dths": { "title": "Number of maternal deaths", "description_from_producer": "A maternal death refers to the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_mmr_risk": { "title": "Lifetime risk of maternal death (1 in: rate varies by country)", "description_from_producer": "Life time risk of maternal death is the probability that a 15-year-old female will die eventually from a maternal cause assuming that current levels of fertility and mortality (including maternal mortality) do not change in the future, taking into account competing causes of death.\n\nLimitations and exceptions: The methodology differs from that used for previous estimates, so data should not be compared historically. Maternal mortality ratios are generally of unknown reliability, as are many other cause-specific mortality indicators. The probability cannot be assumed to provide an exact estimate of risk of maternal death.\n\nStatistical concept and methodology: Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\n\nMaternal mortality is generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation.\n\nThe estimates are based on an exercise by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) which consists of World Health Organization (WHO), United Nations Children's Fund (UNICEF), World Bank, and United Nations Population Fund (UNFPA), and include country-level time series data. For countries without complete registration data but with other types of data and for countries with no data, maternal mortality is estimated with a regression model using available national maternal mortality data and socioeconomic information.\n\nIn countries with a high risk of maternal death, many girls die before reaching reproductive age. Lifetime risk of maternal mortality refers to the probability that a 15-year-old girl will eventually die due to a maternal cause.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "1 in: rate varies by country" }, "sh_mmr_risk_zs": { "title": "Lifetime risk of maternal death (%)", "description_from_producer": "Life time risk of maternal death is the probability that a 15-year-old female will die eventually from a maternal cause assuming that current levels of fertility and mortality (including maternal mortality) do not change in the future, taking into account competing causes of death.\n\nLimitations and exceptions: The methodology differs from that used for previous estimates, so data should not be compared historically. Maternal mortality ratios are generally of unknown reliability, as are many other cause-specific mortality indicators. The probability cannot be assumed to provide an exact estimate of risk of maternal death.\n\nStatistical concept and methodology: Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\n\nMaternal mortality is generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation.\n\nThe estimates are based on an exercise by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) which consists of World Health Organization (WHO), United Nations Children's Fund (UNICEF), World Bank, and United Nations Population Fund (UNFPA), and include country-level time series data. For countries without complete registration data but with other types of data and for countries with no data, maternal mortality is estimated with a regression model using available national maternal mortality data and socioeconomic information.\n\nIn countries with a high risk of maternal death, many girls die before reaching reproductive age. Lifetime risk of maternal mortality refers to the probability that a 15-year-old girl will eventually die due to a maternal cause.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_prg_anem": { "title": "Prevalence of anemia among pregnant women (%)", "description_from_producer": "Prevalence of anemia, pregnant women, is the percentage of pregnant women whose hemoglobin level is less than 110 grams per liter at sea level.\n\nLimitations and exceptions: Data should be used with caution because surveys differ in quality, coverage, age group interviewed, and treatment of missing values across countries and over time.\n\nData on anemia are compiled by the WHO based mainly on nationally representative surveys, which measure hemoglobin in the blood. WHO's hemoglobin thresholds are then used to determine anemia status based on age, sex, and physiological status.\n\nStatistical concept and methodology: Anemia is a condition in which the number of red blood cells or their oxygen-carrying capacity is insufficient to meet physiologic needs, which vary by age, sex, altitude, smoking status, and pregnancy status. In its severe form it is associated with fatigue, weakness, dizziness, and drowsiness. Children under age 5 and pregnant women have the highest risk for anemia.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_prv_smok": { "title": "Prevalence of current tobacco use (% of adults)", "description_from_producer": "The percentage of the population ages 15 years and over who currently use any tobacco product (smoked and/or smokeless tobacco) on a daily or non-daily basis. Tobacco products include cigarettes, pipes, cigars, cigarillos, waterpipes (hookah, shisha), bidis, kretek, heated tobacco products, and all forms of smokeless (oral and nasal) tobacco. Tobacco products exclude e-cigarettes (which do not contain tobacco), \u201ce-cigars\u201d, \u201ce-hookahs\u201d, JUUL and \u201ce-pipes\u201d. The rates are age-standardized to the WHO Standard Population.\n\nLimitations and exceptions: Estimates for countries with irregular surveys or many data gaps have large uncertainty ranges, and such results should be interpreted with caution.\n\nStatistical concept and methodology: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.\n\nA statistical model based on a Bayesian negative binomial meta-regression is used to model prevalence of current tobacco use for each country, separately for men and women.\n\nThe model has two main components: (a) adjusting for missing indicators and age groups, and (b) generating an estimate of trends over time as well as the 95% credible interval around the estimate.\nDepending on the completeness/comprehensiveness of survey data from a particular country, the model at times makes use of data from other countries to fill information gaps. When a country has fewer than two nationally representative population-based surveys in different years, no attempt is made to fill data gaps and no estimates are calculated. To fill data gaps, information is \u201cborrowed\u201d from countries in the same UN subregion. The resulting trend lines are used to derive estimates for single years, so that a number can be reported even if the country did not run a survey in that year. In order to make the results comparable between countries, the prevalence rates are age-standardized to the WHO Standard Population. A full description of the method is available as a peer-reviewed article in The Lancet, volume 385, No. 9972, p966\u2013976 (2015).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of adults", "short_unit": "%", "display": { "name": "Adults who smoke" }, "presentation": { "title_public": "Prevalence of current tobacco use (% of adults)" } }, "sh_prv_smok_fe": { "title": "Prevalence of current tobacco use, females (% of female adults)", "description_from_producer": "The percentage of the female population ages 15 years and over who currently use any tobacco product (smoked and/or smokeless tobacco) on a daily or non-daily basis. Tobacco products include cigarettes, pipes, cigars, cigarillos, waterpipes (hookah, shisha), bidis, kretek, heated tobacco products, and all forms of smokeless (oral and nasal) tobacco. Tobacco products exclude e-cigarettes (which do not contain tobacco), \u201ce-cigars\u201d, \u201ce-hookahs\u201d, JUUL and \u201ce-pipes\u201d. The rates are age-standardized to the WHO Standard Population.\n\nLimitations and exceptions: Estimates for countries with irregular surveys or many data gaps have large uncertainty ranges, and such results should be interpreted with caution.\n\nStatistical concept and methodology: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.\n\nA statistical model based on a Bayesian negative binomial meta-regression is used to model prevalence of current tobacco use for each country, separately for men and women.\n\nThe model has two main components: (a) adjusting for missing indicators and age groups, and (b) generating an estimate of trends over time as well as the 95% credible interval around the estimate.\nDepending on the completeness/comprehensiveness of survey data from a particular country, the model at times makes use of data from other countries to fill information gaps. When a country has fewer than two nationally representative population-based surveys in different years, no attempt is made to fill data gaps and no estimates are calculated. To fill data gaps, information is \u201cborrowed\u201d from countries in the same UN subregion. The resulting trend lines are used to derive estimates for single years, so that a number can be reported even if the country did not run a survey in that year. In order to make the results comparable between countries, the prevalence rates are age-standardized to the WHO Standard Population. A full description of the method is available as a peer-reviewed article in The Lancet, volume 385, No. 9972, p966\u2013976 (2015).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of adults", "short_unit": "%" }, "sh_prv_smok_ma": { "title": "Prevalence of current tobacco use, males (% of male adults)", "description_from_producer": "The percentage of the male population ages 15 years and over who currently use any tobacco product (smoked and/or smokeless tobacco) on a daily or non-daily basis. Tobacco products include cigarettes, pipes, cigars, cigarillos, waterpipes (hookah, shisha), bidis, kretek, heated tobacco products, and all forms of smokeless (oral and nasal) tobacco. Tobacco products exclude e-cigarettes (which do not contain tobacco), \u201ce-cigars\u201d, \u201ce-hookahs\u201d, JUUL and \u201ce-pipes\u201d. The rates are age-standardized to the WHO Standard Population.\n\nLimitations and exceptions: Estimates for countries with irregular surveys or many data gaps have large uncertainty ranges, and such results should be interpreted with caution.\n\nStatistical concept and methodology: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.\n\nSmoking is the most common form of tobacco use and the prevalence of smoking is therefore a good measure of the tobacco epidemic. (Corrao MA, Guindon GE, Sharma N, Shokoohi DF (eds). Tobacco Control Country Profiles, 2000, American Cancer Society, Atlanta.) Tobacco use causes heart and other vascular diseases and cancers of the lung and other organs. Given the long delay between starting to smoke and the onset of disease, the health impact of smoking will increase rapidly only in the next few decades. The data presented are age-standardized rates for adults ages 15 and older from the WHO.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of adults", "short_unit": "%" }, "sh_sgr_crsk_zs": { "title": "Risk of catastrophic expenditure for surgical care (% of people at risk)", "description_from_producer": "The proportion of population at risk of catastrophic expenditure when surgical care is required. Catastrophic expenditure is defined as direct out of pocket payments for surgical and anaesthesia care exceeding 10% of total income.", "origins": [ { "producer": "Harvard Medical School Program in Global Surgery and Social Change (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of people at risk", "short_unit": "%" }, "sh_sgr_irsk_zs": { "title": "Risk of impoverishing expenditure for surgical care (% of people at risk)", "description_from_producer": "The proportion of population at risk of impoverishing expenditure when surgical care is required. Impoverishing expenditure is defined as direct out of pocket payments for surgical and anaesthesia care which drive people below a poverty threshold (using a threshold of $1.90 PPP/day).", "origins": [ { "producer": "Harvard Medical School Program in Global Surgery and Social Change (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of people at risk", "short_unit": "%" }, "sh_sgr_proc_p5": { "title": "Number of surgical procedures (per 100,000 population)", "description_from_producer": "The number of procedures undertaken in an operating theatre per 100,000 population per year in each country. A procedure is defined as the incision, excision, or manipulation of tissue that needs regional or general anaesthesia, or profound sedation to control pain.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 population" }, "sh_sta_airp_fe_p5": { "title": "Mortality rate attributed to household and ambient air pollution, age-standardized, female (per 100,000 female population)", "description_from_producer": "Mortality rate attributed to household and ambient air pollution is the number of deaths attributable to the joint effects of household and ambient air pollution in a year per 100,000 population. The rates are age-standardized. Following diseases are taken into account: acute respiratory infections (estimated for all ages); cerebrovascular diseases in adults (estimated above 25 years); ischaemic heart diseases in adults (estimated above 25 years); chronic obstructive pulmonary disease in adults (estimated above 25 years); and lung cancer in adults (estimated above 25 years).\n\nLimitations and exceptions: Estimates of the joint effects of air pollution are constrained by limited knowledge on the distribution of the population exposed to both household and ambient air pollution, correlation of exposures at individual level as household air pollution is a contributor to ambient air pollution, and non-linear interactions\n\nStatistical concept and methodology: Burden of disease (or in the present case attributable mortality) is calculated by first combining information on the increased (or relative) risk of a disease resulting from exposure, with information on how widespread the exposure is in the population (e.g. the annual mean concentration of particulate matter to which the population is exposed). This allows calculation of the 'population attributable fraction' (PAF), which is the fraction of disease seen in a given population that can be attributed to the exposure (e.g in this case the annual mean concentration of particulate matter). Applying this fraction to the total burden of disease (e.g. cardiopulmonary disease expressed as deaths or DALYs), gives the total number of deaths or DALYs that results from exposure to that particular risk factor (in the example given above, to ambient air pollution). To estimate the combined effects of risk factors, a joint population attributable fraction is calculated, as described in Ezzati et al (2003).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_sta_airp_ma_p5": { "title": "Mortality rate attributed to household and ambient air pollution, age-standardized, male (per 100,000 male population)", "description_from_producer": "Mortality rate attributed to household and ambient air pollution is the number of deaths attributable to the joint effects of household and ambient air pollution in a year per 100,000 population. The rates are age-standardized. Following diseases are taken into account: acute respiratory infections (estimated for all ages); cerebrovascular diseases in adults (estimated above 25 years); ischaemic heart diseases in adults (estimated above 25 years); chronic obstructive pulmonary disease in adults (estimated above 25 years); and lung cancer in adults (estimated above 25 years).\n\nLimitations and exceptions: Estimates of the joint effects of air pollution are constrained by limited knowledge on the distribution of the population exposed to both household and ambient air pollution, correlation of exposures at individual level as household air pollution is a contributor to ambient air pollution, and non-linear interactions\n\nStatistical concept and methodology: Burden of disease (or in the present case attributable mortality) is calculated by first combining information on the increased (or relative) risk of a disease resulting from exposure, with information on how widespread the exposure is in the population (e.g. the annual mean concentration of particulate matter to which the population is exposed). This allows calculation of the 'population attributable fraction' (PAF), which is the fraction of disease seen in a given population that can be attributed to the exposure (e.g in this case the annual mean concentration of particulate matter). Applying this fraction to the total burden of disease (e.g. cardiopulmonary disease expressed as deaths or DALYs), gives the total number of deaths or DALYs that results from exposure to that particular risk factor (in the example given above, to ambient air pollution). To estimate the combined effects of risk factors, a joint population attributable fraction is calculated, as described in Ezzati et al (2003).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_sta_airp_p5": { "title": "Mortality rate attributed to household and ambient air pollution, age-standardized (per 100,000 population)", "description_from_producer": "Mortality rate attributed to household and ambient air pollution is the number of deaths attributable to the joint effects of household and ambient air pollution in a year per 100,000 population. The rates are age-standardized. Following diseases are taken into account: acute respiratory infections (estimated for all ages); cerebrovascular diseases in adults (estimated above 25 years); ischaemic heart diseases in adults (estimated above 25 years); chronic obstructive pulmonary disease in adults (estimated above 25 years); and lung cancer in adults (estimated above 25 years).\n\nLimitations and exceptions: Estimates of the joint effects of air pollution are constrained by limited knowledge on the distribution of the population exposed to both household and ambient air pollution, correlation of exposures at individual level as household air pollution is a contributor to ambient air pollution, and non-linear interactions\n\nStatistical concept and methodology: Burden of disease (or in the present case attributable mortality) is calculated by first combining information on the increased (or relative) risk of a disease resulting from exposure, with information on how widespread the exposure is in the population (e.g. the annual mean concentration of particulate matter to which the population is exposed). This allows calculation of the 'population attributable fraction' (PAF), which is the fraction of disease seen in a given population that can be attributed to the exposure (e.g in this case the annual mean concentration of particulate matter). Applying this fraction to the total burden of disease (e.g. cardiopulmonary disease expressed as deaths or DALYs), gives the total number of deaths or DALYs that results from exposure to that particular risk factor (in the example given above, to ambient air pollution). To estimate the combined effects of risk factors, a joint population attributable fraction is calculated, as described in Ezzati et al (2003).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 population" }, "sh_sta_anvc_zs": { "title": "Pregnant women receiving prenatal care (%)", "description_from_producer": "Pregnant women receiving prenatal care are the percentage of women attended at least once during pregnancy by skilled health personnel for reasons related to pregnancy.\n\nLimitations and exceptions: For the indicators that are from household surveys, the year refers to the survey year. For more information, consult the original sources.\n\nStatistical concept and methodology: Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\n\nGood prenatal and postnatal care improves maternal health and reduces maternal and infant mortality. However, indicators on use of antenatal care services provide no information on the content or quality of the services. Data on antenatal care are obtained mostly from household surveys, which ask women who have had a live birth whether and from whom they received antenatal care.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_sta_aric_zs": { "title": "ARI treatment (% of children under 5 taken to a health provider)", "description_from_producer": "Children with acute respiratory infection (ARI) who are taken to a health provider refers to the percentage of children under age five with ARI in the last two weeks who were taken to an appropriate health provider, including hospital, health center, dispensary, village health worker, clinic, and private physician.\n\nStatistical concept and methodology: Acute respiratory infection continues to be a leading cause of death among young children. Data are drawn mostly from household health surveys in which mothers report on number of episodes and treatment for acute respiratory infection.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5 taken to a health provider", "short_unit": "%" }, "sh_sta_bass_ru_zs": { "title": "People using at least basic sanitation services, rural (% of rural population)", "description_from_producer": "The percentage of people using at least basic sanitation services, that is, improved sanitation facilities that are not shared with other households. This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.\n\nLimitations and exceptions: National, regional and income group estimates are made when data are available for at least 50 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines basic sanitation facilities as improved sanitation facilities that are not shared with other households. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of rural population", "short_unit": "%" }, "sh_sta_bass_ur_zs": { "title": "People using at least basic sanitation services, urban (% of urban population)", "description_from_producer": "The percentage of people using at least basic sanitation services, that is, improved sanitation facilities that are not shared with other households. This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.\n\nLimitations and exceptions: National, regional and income group estimates are made when data are available for at least 50 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines basic sanitation facilities as improved sanitation facilities that are not shared with other households. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of urban population", "short_unit": "%" }, "sh_sta_bass_zs": { "title": "People using at least basic sanitation services (% of population)", "description_from_producer": "The percentage of people using at least basic sanitation services, that is, improved sanitation facilities that are not shared with other households. This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.\n\nLimitations and exceptions: National, regional and income group estimates are made when data are available for at least 50 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines basic sanitation facilities as improved sanitation facilities that are not shared with other households. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "sh_sta_bfed_zs": { "title": "Exclusive breastfeeding (% of children under 6 months)", "description_from_producer": "Exclusive breastfeeding refers to the percentage of children less than six months old who are fed breast milk alone (no other liquids) in the past 24 hours.\n\nLimitations and exceptions: Most of the data on breastfeeding are derived from household surveys. For the data that are from household surveys, the year refers to the survey year.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 6 months", "short_unit": "%" }, "sh_sta_brtc_zs": { "title": "Births attended by skilled health staff (% of total)", "description_from_producer": "Births attended by skilled health staff are the percentage of deliveries attended by personnel trained to give the necessary supervision, care, and advice to women during pregnancy, labor, and the postpartum period; to conduct deliveries on their own; and to care for newborns.\n\nLimitations and exceptions: For the indicators that are from household surveys, the year refers to the survey year. For more information, consult the original sources.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sh_sta_brtw_zs": { "title": "Low-birthweight babies (% of births)", "description_from_producer": "Low-birthweight babies are newborns weighing less than 2,500 grams, with the measurement taken within the first hour of life, before significant postnatal weight loss has occurred.", "origins": [ { "producer": "UNICEF and World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of births", "short_unit": "%" }, "sh_sta_diab_zs": { "title": "Diabetes prevalence (% of population ages 20 to 79)", "description_from_producer": "Diabetes prevalence refers to the percentage of people ages 20-79 who have type 1 or type 2 diabetes. It is calculated by adjusting to a standard population age-structure.\n\nLimitations and exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information.", "origins": [ { "producer": "International Diabetes Federation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population ages 20 to 79", "short_unit": "%" }, "sh_sta_fgms_zs": { "title": "Female genital mutilation prevalence (%)", "description_from_producer": "Percentage of women aged 15\u201349 who have gone through partial or total removal of the female external genitalia or other injury to the female genital organs for cultural or other non-therapeutic reasons.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_sta_hygn_ru_zs": { "title": "People with basic handwashing facilities including soap and water, rural (% of rural population)", "description_from_producer": "The percentage of people living in households that have a handwashing facility with soap and water available on the premises. Handwashing facilities may be fixed or mobile and include a sink with tap water, buckets with taps, tippy-taps, and jugs or basins designated for handwashing. Soap includes bar soap, liquid soap, powder detergent, and soapy water but does not include ash, soil, sand or other handwashing agents.\n\nLimitations and exceptions: Presence of a handwashing station with soap and water does not guarantee that household members consistently wash hands at key times, but is accepted as the most suitable proxy. Data on handwashing facilities are available for a growing number of low- and middle-income countries after hygiene questions were standardized in international surveys. However, this type of information is not available from most high-income countries, where access to basic handwashing facilities is assumed to be nearly universal.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines a basic handwashing facility as a device to contain, transport or regulate the flow of water to facilitate handwashing with soap and water in the household.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of rural population", "short_unit": "%" }, "sh_sta_hygn_ur_zs": { "title": "People with basic handwashing facilities including soap and water, urban (% of urban population)", "description_from_producer": "The percentage of people living in households that have a handwashing facility with soap and water available on the premises. Handwashing facilities may be fixed or mobile and include a sink with tap water, buckets with taps, tippy-taps, and jugs or basins designated for handwashing. Soap includes bar soap, liquid soap, powder detergent, and soapy water but does not include ash, soil, sand or other handwashing agents.\n\nLimitations and exceptions: Presence of a handwashing station with soap and water does not guarantee that household members consistently wash hands at key times, but is accepted as the most suitable proxy. Data on handwashing facilities are available for a growing number of low- and middle-income countries after hygiene questions were standardized in international surveys. However, this type of information is not available from most high-income countries, where access to basic handwashing facilities is assumed to be nearly universal.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines a basic handwashing facility as a device to contain, transport or regulate the flow of water to facilitate handwashing with soap and water in the household.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of urban population", "short_unit": "%" }, "sh_sta_hygn_zs": { "title": "People with basic handwashing facilities including soap and water (% of population)", "description_from_producer": "The percentage of people living in households that have a handwashing facility with soap and water available on the premises. Handwashing facilities may be fixed or mobile and include a sink with tap water, buckets with taps, tippy-taps, and jugs or basins designated for handwashing. Soap includes bar soap, liquid soap, powder detergent, and soapy water but does not include ash, soil, sand or other handwashing agents.\n\nLimitations and exceptions: Presence of a handwashing station with soap and water does not guarantee that household members consistently wash hands at key times, but is accepted as the most suitable proxy. Data on handwashing facilities are available for a growing number of low- and middle-income countries after hygiene questions were standardized in international surveys. However, this type of information is not available from most high-income countries, where access to basic handwashing facilities is assumed to be nearly universal.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines a basic handwashing facility as a device to contain, transport or regulate the flow of water to facilitate handwashing with soap and water in the household.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "sh_sta_maln_fe_zs": { "title": "Prevalence of underweight, weight for age, female (% of children under 5)", "description_from_producer": "Prevalence of underweight, female, is the percentage of girls under age 5 whose weight for age is more than two standard deviations below the median for the international reference population ages 0-59 months. The data are based on the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_maln_ma_zs": { "title": "Prevalence of underweight, weight for age, male (% of children under 5)", "description_from_producer": "Prevalence of underweight, male, is the percentage of boys under age 5 whose weight for age is more than two standard deviations below the median for the international reference population ages 0-59 months. The data are based on the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_maln_zs": { "title": "Prevalence of underweight, weight for age (% of children under 5)", "description_from_producer": "Prevalence of underweight children is the percentage of children under age 5 whose weight for age is more than two standard deviations below the median for the international reference population ages 0-59 months. The data are based on the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_mmrt": { "title": "Maternal mortality ratio (modeled estimate, per 100,000 live births)", "description_from_producer": "Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births. The data are estimated with a regression model using information on the proportion of maternal deaths among non-AIDS deaths in women ages 15-49, fertility, birth attendants, and GDP measured using purchasing power parities (PPPs).\n\nLimitations and exceptions: The methodology differs from that used for previous estimates, so data should not be compared historically. Maternal mortality ratios are generally of unknown reliability, as are many other cause-specific mortality indicators. The ratios cannot be assumed to provide an exact estimate of maternal mortality.\n\nStatistical concept and methodology: Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\n\nMaternal mortality is generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation.\n\nThe estimates are based on an exercise by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) which consists of World Health Organization (WHO), United Nations Children's Fund (UNICEF), World Bank, and United Nations Population Fund (UNFPA), and include country-level time series data. For countries without complete registration data but with other types of data and for countries with no data, maternal mortality is estimated with a regression model using available national maternal mortality data and socioeconomic information.\n\nNotes from original source: Estimates of maternal mortality are presented along with upper and lower limits of intervals (see footnote) designed to depict the uncertainty of estimates. The intervals are the product of a detailed probabilistic evaluation of the uncertainty attributable to the various components of the estimation process. For estimates derived from the multilevel regression model, the components of uncertainty were divided into two groups: those reflected within the regression model (internal sources), and those due to assumptions or calculations that occur outside the model (external sources). Estimates of the total uncertainty reflect a combination of these various sources.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled estimate, per 100,000 live births", "short_unit": "modeled estimate," }, "sh_sta_mmrt_ne": { "title": "Maternal mortality ratio (national estimate, per 100,000 live births)", "description_from_producer": "Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births.\n\nLimitations and exceptions: Maternal mortality ratios are generally of unknown reliability, as are many other cause-specific mortality indicators. The ratios cannot be assumed to provide an exact estimate of maternal mortality. Some of the figures shown were adjusted by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) to enhance reliability, so that they may differ from the published figures from sources such as household surveys.\n\nStatistical concept and methodology: Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\n\nMaternal mortality ratios are generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation.\n\nThe national estimates of maternal mortality ratios are based on national surveys, vital registration records, and surveillance data or are derived from community and hospital records.", "origins": [ { "producer": "UN Maternal Mortality Estimation Inter-Agency Group (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate, per 100,000 live births", "short_unit": "national estimate," }, "sh_sta_odfc_ru_zs": { "title": "People practicing open defecation, rural (% of rural population)", "description_from_producer": "People practicing open defecation refers to the percentage of the population defecating in the open, such as in fields, forest, bushes, open bodies of water, on beaches, in other open spaces or disposed of with solid waste.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of rural population", "short_unit": "%" }, "sh_sta_odfc_ur_zs": { "title": "People practicing open defecation, urban (% of urban population)", "description_from_producer": "People practicing open defecation refers to the percentage of the population defecating in the open, such as in fields, forest, bushes, open bodies of water, on beaches, in other open spaces or disposed of with solid waste.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of urban population", "short_unit": "%" }, "sh_sta_odfc_zs": { "title": "People practicing open defecation (% of population)", "description_from_producer": "People practicing open defecation refers to the percentage of the population defecating in the open, such as in fields, forest, bushes, open bodies of water, on beaches, in other open spaces or disposed of with solid waste.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "sh_sta_orcf_zs": { "title": "Diarrhea treatment (% of children under 5 receiving oral rehydration and continued feeding)", "description_from_producer": "Children with diarrhea who received oral rehydration and continued feeding refer to the percentage of children under age five with diarrhea in the two weeks prior to the survey who received either oral rehydration therapy or increased fluids, with continued feeding.\n\nLimitations and exceptions: Recommendations for the use of oral rehydration therapy have changed over time based on scientific progress, so it is difficult to accurately compare use rates across countries. Until the current recommended method for home management of diarrhea is adopted and applied in all countries, the data should be used with caution. Also, the prevalence of diarrhea may vary by season. Since country surveys are administered at different times, data comparability is further affected.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5 receiving oral rehydration and continued feeding", "short_unit": "%" }, "sh_sta_orth": { "title": "Diarrhea treatment (% of children under 5 who received ORS packet)", "description_from_producer": "Percentage of children under age 5 with diarrhea in the two weeks preceding the survey who received oral rehydration salts (ORS packets or pre-packaged ORS fluids).", "origins": [ { "producer": "Demographic and Health Surveys (DHS) and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5 who received ORS packet", "short_unit": "%" }, "sh_sta_owgh_fe_zs": { "title": "Prevalence of overweight, weight for height, female (% of children under 5)", "description_from_producer": "Prevalence of overweight, female, is the percentage of girls under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_owgh_ma_zs": { "title": "Prevalence of overweight, weight for height, male (% of children under 5)", "description_from_producer": "Prevalence of overweight, male, is the percentage of boys under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_owgh_me_zs": { "title": "Prevalence of overweight (modeled estimate, % of children under 5)", "description_from_producer": "Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). The JME global estimates for overweight take into account estimates of sampling error around survey estimates. While non-sampling error cannot be accounted for or reviewed in full, when available, a data quality review of weight, height and age measurements from household surveys supports compilation of a time series that is comparable across countries and over time.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_sta_owgh_zs": { "title": "Prevalence of overweight, weight for height (% of children under 5)", "description_from_producer": "Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_pois_p5": { "title": "Mortality rate attributed to unintentional poisoning (per 100,000 population)", "description_from_producer": "Mortality rate attributed to unintentional poisonings is the number of deaths from unintentional poisonings in a year per 100,000 population. Unintentional poisoning can\nbe caused by household chemicals, pesticides, kerosene, carbon monoxide and medicines, or can be the result of environmental contamination or occupational chemical exposure.\n\nLimitations and exceptions: Some countries do not have death registration data or sample registration systems. The estimates on this indicator need to be completed with other type of information for these countries.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 population" }, "sh_sta_pois_p5_fe": { "title": "Mortality rate attributed to unintentional poisoning, female (per 100,000 female population)", "description_from_producer": "Mortality rate attributed to unintentional poisonings is the number of female deaths from unintentional poisonings in a year per 100,000 female population. Unintentional poisoning can be caused by household chemicals, pesticides, kerosene, carbon monoxide and medicines, or can be the result of environmental contamination or occupational chemical exposure.\n\nLimitations and exceptions: Some countries do not have death registration data or sample registration systems. The estimates on this indicator need to be completed with other type of information for these countries.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 female population" }, "sh_sta_pois_p5_ma": { "title": "Mortality rate attributed to unintentional poisoning, male (per 100,000 male population)", "description_from_producer": "Mortality rate attributed to unintentional poisonings is the number of male deaths from unintentional poisonings in a year per 100,000 male population. Unintentional poisoning can\nbe caused by household chemicals, pesticides, kerosene, carbon monoxide and medicines, or can be the result of environmental contamination or occupational chemical exposure.\n\nLimitations and exceptions: Some countries do not have death registration data or sample registration systems. The estimates on this indicator need to be completed with other type of information for these countries.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 male population" }, "sh_sta_smss_ru_zs": { "title": "People using safely managed sanitation services, rural (% of rural population)", "description_from_producer": "The percentage of people using improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.\n\nLimitations and exceptions: There are three main ways to meet the criteria for having a safely managed sanitation service (People should use improved sanitation facilities that are not shared with other households, and the excreta produced should either be: treated and disposed of in situ; stored temporality and then emptied, transported and treated off-site, or transported through a sewer with wastewater and then treated off-site). Many countries lack information on either wastewater treatment or the management of on-site sanitation. A national estimate is produced if information is available for the dominant type of sanitation system. If no information is available, it is assumed that 50 percent is safely managed. Regional and income group estimates are made when data are available for at least 30 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines safely managed sanitation facilities as improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of rural population", "short_unit": "%" }, "sh_sta_smss_ur_zs": { "title": "People using safely managed sanitation services, urban (% of urban population)", "description_from_producer": "The percentage of people using improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.\n\nLimitations and exceptions: There are three main ways to meet the criteria for having a safely managed sanitation service (People should use improved sanitation facilities that are not shared with other households, and the excreta produced should either be: treated and disposed of in situ; stored temporality and then emptied, transported and treated off-site, or transported through a sewer with wastewater and then treated off-site). Many countries lack information on either wastewater treatment or the management of on-site sanitation. A national estimate is produced if information is available for the dominant type of sanitation system. If no information is available, it is assumed that 50 percent is safely managed. Regional and income group estimates are made when data are available for at least 30 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines safely managed sanitation facilities as improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_sta_smss_zs": { "title": "People using safely managed sanitation services (% of population)", "description_from_producer": "The percentage of people using improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.\n\nLimitations and exceptions: There are three main ways to meet the criteria for having a safely managed sanitation service (People should use improved sanitation facilities that are not shared with other households, and the excreta produced should either be: treated and disposed of in situ; stored temporality and then emptied, transported and treated off-site, or transported through a sewer with wastewater and then treated off-site). Many countries lack information on either wastewater treatment or the management of on-site sanitation. A national estimate is produced if information is available for the dominant type of sanitation system. If no information is available, it is assumed that 50 percent is safely managed. Regional and income group estimates are made when data are available for at least 30 percent of the population.\n\nStatistical concept and methodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys. WHO/UNICEF defines safely managed sanitation facilities as improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "sh_sta_stnt_fe_zs": { "title": "Prevalence of stunting, height for age, female (% of children under 5)", "description_from_producer": "Prevalence of stunting, female, is the percentage of girls under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_stnt_ma_zs": { "title": "Prevalence of stunting, height for age, male (% of children under 5)", "description_from_producer": "Prevalence of stunting, male, is the percentage of boys under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_stnt_me_zs": { "title": "Prevalence of stunting, height for age (modeled estimate, % of children under 5)", "description_from_producer": "Prevalence of stunting is the percentage of children under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). The JME global estimates for overweight take into account estimates of sampling error around survey estimates. While non-sampling error cannot be accounted for or reviewed in full, when available, a data quality review of weight, height and age measurements from household surveys supports compilation of a time series that is comparable across countries and over time.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_sta_stnt_zs": { "title": "Prevalence of stunting, height for age (% of children under 5)", "description_from_producer": "Prevalence of stunting is the percentage of children under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's 2006 Child Growth Standards.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_suic_fe_p5": { "title": "Suicide mortality rate, female (per 100,000 female population)", "description_from_producer": "Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_sta_suic_ma_p5": { "title": "Suicide mortality rate, male (per 100,000 male population)", "description_from_producer": "Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_sta_suic_p5": { "title": "Suicide mortality rate (per 100,000 population)", "description_from_producer": "Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 population" }, "sh_sta_traf_p5": { "title": "Mortality caused by road traffic injury (per 100,000 population)", "description_from_producer": "Mortality caused by road traffic injury is estimated road traffic fatal injury deaths per 100,000 population.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 people" }, "sh_sta_wash_p5": { "title": "Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (per 100,000 population)", "description_from_producer": "Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.\n\nLimitations and exceptions: Some countries do not have death registration data or sample registration systems. The estimates on this indicator need to be completed with other type of information for these countries.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 population" }, "sh_sta_wast_fe_zs": { "title": "Prevalence of wasting, weight for height, female (% of children under 5)", "description_from_producer": "Prevalence of wasting, female, is the proportion of girls under age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59 months.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels. Surveys are carried out in a specific period of the year, usually over a few months. However, this indicator can be affected by seasonality, factors related to food availability (e.g., pre-harvest periods), disease (e.g.,rainy season and diarrhoea, malaria, etc.), and natural disasters and conflicts. Hence, country-year estimates may not necessarily be comparable over time. Consequently, only latest estimates are provided.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_wast_ma_zs": { "title": "Prevalence of wasting, weight for height, male (% of children under 5)", "description_from_producer": "Prevalence of wasting, male, is the proportion of boys under age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59 months.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels. Surveys are carried out in a specific period of the year, usually over a few months. However, this indicator can be affected by seasonality, factors related to food availability (e.g., pre-harvest periods), disease (e.g.,rainy season and diarrhoea, malaria, etc.), and natural disasters and conflicts. Hence, country-year estimates may not necessarily be comparable over time. Consequently, only latest estimates are provided.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_sta_wast_zs": { "title": "Prevalence of wasting, weight for height (% of children under 5)", "description_from_producer": "Prevalence of wasting is the proportion of children under age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59 months.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels. Surveys are carried out in a specific period of the year, usually over a few months. However, this indicator can be affected by seasonality, factors related to food availability (e.g., pre-harvest periods), disease (e.g.,rainy season and diarrhoea, malaria, etc.), and natural disasters and conflicts. Hence, country-year estimates may not necessarily be comparable over time. Consequently, only latest estimates are provided.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_svr_wast_fe_zs": { "title": "Prevalence of severe wasting, weight for height, female (% of children under 5)", "description_from_producer": "Prevalence of severe wasting, female, is the proportion of girls under age 5 whose weight for height is more than three standard deviations below the median for the international reference population ages 0-59 months.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels. Surveys are carried out in a specific period of the year, usually over a few months. However, this indicator can be affected by seasonality, factors related to food availability (e.g., pre-harvest periods), disease (e.g.,rainy season and diarrhoea, malaria, etc.), and natural disasters and conflicts. Hence, country-year estimates may not necessarily be comparable over time. Consequently, only latest estimates are provided.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_svr_wast_ma_zs": { "title": "Prevalence of severe wasting, weight for height, male (% of children under 5)", "description_from_producer": "Prevalence of severe wasting, male, is the proportion of boys under age 5 whose weight for height is more than three standard deviations below the median for the international reference population ages 0-59 months.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels. Surveys are carried out in a specific period of the year, usually over a few months. However, this indicator can be affected by seasonality, factors related to food availability (e.g., pre-harvest periods), disease (e.g.,rainy season and diarrhoea, malaria, etc.), and natural disasters and conflicts. Hence, country-year estimates may not necessarily be comparable over time. Consequently, only latest estimates are provided.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_svr_wast_zs": { "title": "Prevalence of severe wasting, weight for height (% of children under 5)", "description_from_producer": "Prevalence of severe wasting is the proportion of children under age 5 whose weight for height is more than three standard deviations below the median for the international reference population ages 0-59 months.\n\nLimitations and exceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels. Surveys are carried out in a specific period of the year, usually over a few months. However, this indicator can be affected by seasonality, factors related to food availability (e.g., pre-harvest periods), disease (e.g.,rainy season and diarrhoea, malaria, etc.), and natural disasters and conflicts. Hence, country-year estimates may not necessarily be comparable over time. Consequently, only latest estimates are provided.", "origins": [ { "producer": "UNICEF, WHO, World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children under 5", "short_unit": "%" }, "sh_tbs_cure_zs": { "title": "Tuberculosis treatment success rate (% of new cases)", "description_from_producer": "Tuberculosis treatment success rate is the percentage of all new tuberculosis cases (or new and relapse cases for some countries) registered under a national tuberculosis control programme in a given year that successfully completed treatment, with or without bacteriological evidence of success (\"cured\" and \"treatment completed\" respectively).\n\nStatistical concept and methodology: Tuberculosis is one of the main causes of adult deaths from a single infectious agent in developing countries. Data on the success rate of tuberculosis treatment are provided for countries that have submitted data to the WHO. The treatment success rate for tuberculosis provides a useful indicator of the quality of health services. A low rate suggests that infectious patients may not be receiving adequate treatment. An important complement to the tuberculosis treatment success rate is the case detection rate, which indicates whether there is adequate coverage by the recommended case detection and treatment strategy.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of new cases", "short_unit": "%" }, "sh_tbs_dtec_zs": { "title": "Tuberculosis case detection rate (%, all forms)", "description_from_producer": "Tuberculosis case detection rate (all forms) is the number of new and relapse tuberculosis cases notified to WHO in a given year, divided by WHO's estimate of the number of incident tuberculosis cases for the same year, expressed as a percentage. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.\n\nStatistical concept and methodology: Tuberculosis is one of the main causes of adult deaths from a single infectious agent in developing countries. This indicator shows the tuberculosis detection rate for all detection methods. Editions before 2010 included the tuberculosis detection rates by DOTS, the internationally recommended strategy for tuberculosis control. Thus data on the case detection rate from 2010 onward cannot be compared with data in previous editions.\n\nNotes from original source: Estimates are presented with uncertainty intervals (see footnote). When ranges are presented, the lower and higher numbers correspond to the 2.5th and 97.5th centiles of the outcome distributions (generally produced by simulations). For more detailed information, see the original source.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%, all forms", "short_unit": "%" }, "sh_tbs_incd": { "title": "Incidence of tuberculosis (per 100,000 people)", "description_from_producer": "Incidence of tuberculosis is the estimated number of new and relapse tuberculosis cases arising in a given year, expressed as the rate per 100,000 population. All forms of TB are included, including cases in people living with HIV. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.\n\nLimitations and exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.\n\nUncertainty bounds for the incidence are available at http://data.worldbank.org\n\nStatistical concept and methodology: Tuberculosis is one of the main causes of adult deaths from a single infectious agent in developing countries. In developed countries tuberculosis has reemerged largely as a result of cases among immigrants. Since tuberculosis incidence cannot be directly measured, estimates are obtained by eliciting expert opinion or are derived from measurements of prevalence or mortality.\n\nNotes from original source: Estimates are presented with uncertainty intervals (see footnote). When ranges are presented, the lower and higher numbers correspond to the 2.5th and 97.5th centiles of the outcome distributions (generally produced by simulations). For more detailed information, see the original source.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 people" }, "sh_uhc_fbp1_zs": { "title": "Proportion of population pushed further below the $2.15 ($ 2017 PPP) poverty line by out-of-pocket health care expenditure (%)", "description_from_producer": "This indicator shows the fraction of a country\u2019s population living in households whose non-health expenditures are already below the $2.15 poverty line and who as a result are pushed further into poverty by their out-of-pocket health spending. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. The \u201cPushed further below the poverty line by out-of-pocket health payments\u201d indicators were newly introduced in the 2021 edition of the Global Monitoring Report on Financial Protection in Health (GMR). They represent the number and population shares of people who live in households which have both (a) total consumption (including out-of-pocket health payments) beneath the poverty line and (b) any out-of-pocket payments. Because the households are already poor, any out-of-pocket payments are considered financial hardship. The new indicators replace the \u201cChange in poverty-gap due to out-of-pocket health payments\u201d-indicators used to measure the poverty deepening effect of out-of-pocket payments in previous GMR editions (e.g., SH.UHC.NOP1.ZG and SH.UHC.NOP1.CG). For the measurement of overall medical impoverishment, the new indicators are complementary to the \u201cPushed below the poverty line by out-of-pocket health payments\u201d indicators reported in all GMRs (e.g., SH.UHC.NOP1.TO and SH.UHC.NOP1.ZS), which represent the number and population share of people who live in households which lie above the poverty line when out-of-pocket health payments are included in consumption, but fall below the poverty line when out-of-pocket health payments are subtracted from consumption.\n\n2. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n3. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_uhc_fbp2_zs": { "title": "Proportion of population pushed further below the $3.65 ($ 2017 PPP) poverty line by out-of-pocket health care expenditure (%)", "description_from_producer": "This indicator shows the fraction of a country\u2019s population living in households whose non-health expenditures are already below the $3.65 poverty line and who as a result are pushed further into poverty by their out-of-pocket health spending. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. The \u201cPushed further below the poverty line by out-of-pocket health payments\u201d indicators were newly introduced in the 2021 edition of the Global Monitoring Report on Financial Protection in Health (GMR). They represent the number and population shares of people who live in households which have both (a) total consumption (including out-of-pocket health payments) beneath the poverty line and (b) any out-of-pocket payments. Because the households are already poor, any out-of-pocket payments are considered financial hardship. The new indicators replace the \u201cChange in poverty-gap due to out-of-pocket health payments\u201d-indicators used to measure the poverty deepening effect of out-of-pocket payments in previous GMR editions (e.g., SH.UHC.NOP1.ZG and SH.UHC.NOP1.CG). For the measurement of overall medical impoverishment, the new indicators are complementary to the \u201cPushed below the poverty line by out-of-pocket health payments\u201d indicators reported in all GMRs (e.g., SH.UHC.NOP1.TO and SH.UHC.NOP1.ZS), which represent the number and population share of people who live in households which lie above the poverty line when out-of-pocket health payments are included in consumption, but fall below the poverty line when out-of-pocket health payments are subtracted from consumption.\n\n2. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n3. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_uhc_fbpr_zs": { "title": "Proportion of population pushed further below the 60% median consumption poverty line by out-of-pocket health care expenditure (%)", "description_from_producer": "This indicator shows the fraction of a country\u2019s population living in households whose non-health expenditures are already below the 60% median consumption poverty line and who as a result are pushed further into poverty by their out-of-pocket health spending.\nOut-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. The \u201cPushed further below the poverty line by out-of-pocket health payments\u201d indicators were newly introduced in the 2021 edition of the Global Monitoring Report on Financial Protection in Health (GMR). They represent the number and population shares of people who live in households which have both (a) total consumption (including out-of-pocket health payments) beneath the poverty line and (b) any out-of-pocket payments. Because the households are already poor, any out-of-pocket payments are considered financial hardship. The new indicators replace the \u201cChange in poverty-gap due to out-of-pocket health payments\u201d-indicators used to measure the poverty deepening effect of out-of-pocket payments in previous GMR editions (e.g., SH.UHC.NOP1.ZG and SH.UHC.NOP1.CG). For the measurement of overall medical impoverishment, the new indicators are complementary to the \u201cPushed below the poverty line by out-of-pocket health payments\u201d indicators reported in all GMRs (e.g., SH.UHC.NOP1.TO and SH.UHC.NOP1.ZS), which represent the number and population share of people who live in households which lie above the poverty line when out-of-pocket health payments are included in consumption, but fall below the poverty line when out-of-pocket health payments are subtracted from consumption.\n\n2. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n3. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_uhc_nop1_zs": { "title": "Proportion of population pushed below the $2.15 ($ 2017 PPP) poverty line by out-of-pocket health care expenditure (%)", "description_from_producer": "This indicator shows the fraction of a country\u2019s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the $ 2.15 poverty line, but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n2. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_uhc_nop2_zs": { "title": "Proportion of population pushed below the $3.65 ($ 2017 PPP) poverty line by out-of-pocket health care expenditure (%)", "description_from_producer": "This indicator shows the fraction of a country\u2019s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the $3.65 poverty line, but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n2. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_uhc_nopr_zs": { "title": "Proportion of population pushed below the 60% median consumption poverty line by out-of-pocket health expenditure (%)", "description_from_producer": "This indicator shows the fraction of a country\u2019s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the 60% median consumption but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n2. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_uhc_oopc_10_zs": { "title": "Proportion of population spending more than 10% of household consumption or income on out-of-pocket health care expenditure (%)", "description_from_producer": "Proportion of population spending more than 10% of household consumption or income on out-of-pocket health care expenditure. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n2. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_uhc_oopc_25_zs": { "title": "Proportion of population spending more than 25% of household consumption or income on out-of-pocket health care expenditure (%)", "description_from_producer": "Proportion of population spending more than 25% of household consumption or income on out-of-pocket health care expenditure. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n2. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_uhc_srvs_cv_xd": { "title": "UHC service coverage index", "description_from_producer": "Coverage index for essential health services (based on tracer interventions that include reproductive, maternal, newborn and child health, infectious diseases, noncommunicable diseases and service capacity and access). It is presented on a scale of 0 to 100.\n\nStatistical concept and methodology: The Service Coverage Index used to track SDG 3.8.1 includes four indicator categories, namely (1) reproductive, manternal and newborn and child health, (2) infectious diseases, (3) non-communicable diseases and (4) service capacity and access. Each category contains several tracers. The index is constructed from geometric means of the tracer indicators; first, within each of the four categories, and then across the four category-specific means to obtain the final summary index. See Source for details about methodology.\n\nNotes from original source: For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_uhc_tot1_zs": { "title": "Proportion of population pushed or further pushed below the $2.15 ($ 2017 PPP) poverty line by out-of-pocket health care expenditure (%)", "description_from_producer": "This indicator shows the fraction of a country's population who is either (1) living in households whose non-health expenditures are already below the $2.15 poverty line and who as a result are pushed further into poverty by their out-of-pocket health spending or (2) live in households whose total expenditures are above the $2.15 poverty line but fall below the $2.15 poverty line when out-of-pocket health spending is subtracted from total expenditure. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. The \u201cPushed further below the poverty line by out-of-pocket health payments\u201d indicators were newly introduced in the 2021 edition of the Global Monitoring Report on Financial Protection in Health (GMR). They represent the number and population shares of people who live in households which have both (a) total consumption (including out-of-pocket health payments) beneath the poverty line and (b) any out-of-pocket payments. Because the households are already poor, any out-of-pocket payments are considered financial hardship. The new indicators replace the \u201cChange in poverty-gap due to out-of-pocket health payments\u201d-indicators used to measure the poverty deepening effect of out-of-pocket payments in previous GMR editions (e.g., SH.UHC.NOP1.ZG and SH.UHC.NOP1.CG). For the measurement of overall medical impoverishment, the new indicators are complementary to the \u201cPushed below the poverty line by out-of-pocket health payments\u201d indicators reported in all GMRs (e.g., SH.UHC.NOP1.TO and SH.UHC.NOP1.ZS), which represent the number and population share of people who live in households which lie above the poverty line when out-of-pocket health payments are included in consumption, but fall below the poverty line when out-of-pocket health payments are subtracted from consumption.\n\n2. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n3. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_uhc_tot2_zs": { "title": "Proportion of population pushed or further pushed below the $3.65 ($ 2017 PPP) poverty line by out-of-pocket health care expenditure (%)", "description_from_producer": "This indicator shows the fraction of a country's population who is either (1) living in households whose non-health expenditures are already below the $3.65 poverty line and who as a result are pushed further into poverty by their out-of-pocket health spending or (2) live in households whose total expenditures are above the $3.65 poverty line but fall below the $3.65 poverty line when out-of-pocket health spending is subtracted from total expenditure. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. The \u201cPushed further below the poverty line by out-of-pocket health payments\u201d indicators were newly introduced in the 2021 edition of the Global Monitoring Report on Financial Protection in Health (GMR). They represent the number and population shares of people who live in households which have both (a) total consumption (including out-of-pocket health payments) beneath the poverty line and (b) any out-of-pocket payments. Because the households are already poor, any out-of-pocket payments are considered financial hardship. The new indicators replace the \u201cChange in poverty-gap due to out-of-pocket health payments\u201d-indicators used to measure the poverty deepening effect of out-of-pocket payments in previous GMR editions (e.g., SH.UHC.NOP1.ZG and SH.UHC.NOP1.CG). For the measurement of overall medical impoverishment, the new indicators are complementary to the \u201cPushed below the poverty line by out-of-pocket health payments\u201d indicators reported in all GMRs (e.g., SH.UHC.NOP1.TO and SH.UHC.NOP1.ZS), which represent the number and population share of people who live in households which lie above the poverty line when out-of-pocket health payments are included in consumption, but fall below the poverty line when out-of-pocket health payments are subtracted from consumption.\n\n2. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n3. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_uhc_totr_zs": { "title": "Proportion of population pushed or further pushed below the 60% median consumption poverty line by out-of-pocket health expenditure (%)", "description_from_producer": "This indicator shows the fraction of a country's population who is either (1) living in households whose non-health expenditures are already below the relative poverty line and who as a result are pushed further into poverty by their out-of-pocket health spending or (2) live in households whose total expenditures are above the relative poverty line but fall below the relative poverty line when out-of-pocket health spending is subtracted from total expenditure. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).\n\nStatistical concept and methodology: Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.\n\nNotes from original source: 1. The \u201cPushed further below the poverty line by out-of-pocket health payments\u201d indicators were newly introduced in the 2021 edition of the Global Monitoring Report on Financial Protection in Health (GMR). They represent the number and population shares of people who live in households which have both (a) total consumption (including out-of-pocket health payments) beneath the poverty line and (b) any out-of-pocket payments. Because the households are already poor, any out-of-pocket payments are considered financial hardship. The new indicators replace the \u201cChange in poverty-gap due to out-of-pocket health payments\u201d-indicators used to measure the poverty deepening effect of out-of-pocket payments in previous GMR editions (e.g., SH.UHC.NOP1.ZG and SH.UHC.NOP1.CG). For the measurement of overall medical impoverishment, the new indicators are complementary to the \u201cPushed below the poverty line by out-of-pocket health payments\u201d indicators reported in all GMRs (e.g., SH.UHC.NOP1.TO and SH.UHC.NOP1.ZS), which represent the number and population share of people who live in households which lie above the poverty line when out-of-pocket health payments are included in consumption, but fall below the poverty line when out-of-pocket health payments are subtracted from consumption.\n\n2. For the aggregated data, World Bank\u2019s historical income classification that was based on data from each respective year was used. For example, the FY2002 income classification based on the 2000 GNI per capita was used for the 2000 aggregates, the FY2007 income classification based on the 2005 GNI per capita was used for the 2005 aggregates, and so on.\n\n3. For details of the definition for out-of-pocket health spending, please see the following publication: World Health Organization and World Bank. 2021. Global Monitoring Report on Financial Protection in Health 2021.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sh_vac_ttns_zs": { "title": "Newborns protected against tetanus (%)", "description_from_producer": "Newborns protected against tetanus are the percentage of births by women of child-bearing age who are immunized against tetanus.", "origins": [ { "producer": "World Health Organization and UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sh_xpd_chex_gd_zs": { "title": "Current health expenditure (% of GDP)", "description_from_producer": "Level of current health expenditure expressed as a percentage of GDP. Estimates of current health expenditures include healthcare goods and services consumed during each year. This indicator does not include capital health expenditures such as buildings, machinery, IT and stocks of vaccines for emergency or outbreaks.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "sh_xpd_chex_pc_cd": { "title": "Current health expenditure per capita (current US$)", "description_from_producer": "Current expenditures on health per capita in current US dollars. Estimates of current health expenditures include healthcare goods and services consumed during each year.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "sh_xpd_chex_pp_cd": { "title": "Current health expenditure per capita, PPP (current international $)", "description_from_producer": "Current expenditures on health per capita expressed in international dollars at purchasing power parity.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization (WHO) under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. WHO converted the expenditure data using PPP time series extracted from WDI (based on ICP 2017) and OECD data. Where WDI/OECD data were not available, IMF or WHO estimates were utilized. Detailed metadata are available at .\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$" }, "sh_xpd_ehex_ch_zs": { "title": "External health expenditure (% of current health expenditure)", "description_from_producer": "Share of current health expenditures funded from external sources. External sources compose of direct foreign transfers and foreign transfers distributed by government encompassing all financial inflows into the national health system from outside the country. External sources either flow through the government scheme or are channeled through non-governmental organizations or other schemes.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of current health expenditure", "short_unit": "%" }, "sh_xpd_ehex_pc_cd": { "title": "External health expenditure per capita (current US$)", "description_from_producer": "Current external expenditures on health per capita expressed in current US dollars. External sources are composed of direct foreign transfers and foreign transfers distributed by government encompassing all financial inflows into the national health system from outside the country.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "sh_xpd_ehex_pp_cd": { "title": "External health expenditure per capita, PPP (current international $)", "description_from_producer": "Current external expenditures on health per capita expressed in international dollars at purchasing power parity. External sources are composed of direct foreign transfers and foreign transfers distributed by government encompassing all financial inflows into the national health system from outside the country.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization (WHO) under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. WHO converted the expenditure data using PPP time series extracted from WDI (based on ICP 2017) and OECD data. Where WDI/OECD data were not available, IMF or WHO estimates were utilized. Detailed metadata are available at .\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$" }, "sh_xpd_ghed_ch_zs": { "title": "Domestic general government health expenditure (% of current health expenditure)", "description_from_producer": "Share of current health expenditures funded from domestic public sources for health. Domestic public sources include domestic revenue as internal transfers and grants, transfers, subsidies to voluntary health insurance beneficiaries, non-profit institutions serving households (NPISH) or enterprise financing schemes as well as compulsory prepayment and social health insurance contributions. They do not include external resources spent by governments on health.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of current health expenditure", "short_unit": "%" }, "sh_xpd_ghed_gd_zs": { "title": "Domestic general government health expenditure (% of GDP)", "description_from_producer": "Public expenditure on health from domestic sources as a share of the economy as measured by GDP.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "sh_xpd_ghed_ge_zs": { "title": "Domestic general government health expenditure (% of general government expenditure)", "description_from_producer": "Public expenditure on health from domestic sources as a share of total public expenditure. It indicates the priority of the government to spend on health from own domestic public resources.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of general government expenditure", "short_unit": "%" }, "sh_xpd_ghed_pc_cd": { "title": "Domestic general government health expenditure per capita (current US$)", "description_from_producer": "Public expenditure on health from domestic sources per capita expressed in current US dollars.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "sh_xpd_ghed_pp_cd": { "title": "Domestic general government health expenditure per capita, PPP (current international $)", "description_from_producer": "Public expenditure on health from domestic sources per capita expressed in international dollars at purchasing power parity.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization (WHO) under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. WHO converted the expenditure data using PPP time series extracted from WDI (based on ICP 2017) and OECD data. Where WDI/OECD data were not available, IMF or WHO estimates were utilized. Detailed metadata are available at .\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$" }, "sh_xpd_oopc_ch_zs": { "title": "Out-of-pocket expenditure (% of current health expenditure)", "description_from_producer": "Share of out-of-pocket payments of total current health expenditures. Out-of-pocket payments are spending on health directly out-of-pocket by households.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of current health expenditure", "short_unit": "%" }, "sh_xpd_oopc_pc_cd": { "title": "Out-of-pocket expenditure per capita (current US$)", "description_from_producer": "Health expenditure through out-of-pocket payments per capita in USD. Out of pocket payments are spending on health directly out of pocket by households in each country.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "sh_xpd_oopc_pp_cd": { "title": "Out-of-pocket expenditure per capita, PPP (current international $)", "description_from_producer": "Health expenditure through out-of-pocket payments per capita in international dollars at purchasing power parity.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization (WHO) under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. WHO converted the expenditure data using PPP time series extracted from WDI (based on ICP 2017) and OECD data. Where WDI/OECD data were not available, IMF or WHO estimates were utilized. Detailed metadata are available at .\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$" }, "sh_xpd_pvtd_ch_zs": { "title": "Domestic private health expenditure (% of current health expenditure)", "description_from_producer": "Share of current health expenditures funded from domestic private sources. Domestic private sources include funds from households, corporations and non-profit organizations. Such expenditures can be either prepaid to voluntary health insurance or paid directly to healthcare providers.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of current health expenditure", "short_unit": "%" }, "sh_xpd_pvtd_pc_cd": { "title": "Domestic private health expenditure per capita (current US$)", "description_from_producer": "Current private expenditures on health per capita expressed in current US dollars. Domestic private sources include funds from households, corporations and non-profit organizations. Such expenditures can be either prepaid to voluntary health insurance or paid directly to healthcare providers.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "sh_xpd_pvtd_pp_cd": { "title": "Domestic private health expenditure per capita, PPP (current international $)", "description_from_producer": "Current private expenditures on health per capita expressed in international dollars at purchasing power parity.\n\nStatistical concept and methodology: The health expenditure estimates have been prepared by the World Health Organization (WHO) under the framework of the System of Health Accounts 2011 (SHA 2011). The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. WHO converted the expenditure data using PPP time series extracted from WDI (based on ICP 2017) and OECD data. Where WDI/OECD data were not available, IMF or WHO estimates were utilized. Detailed metadata are available at .\n\nNotes from original source: The World Health Organization (WHO) has revised health expenditure data using the new international classification for health expenditures in the revised System of Health Accounts (SHA 2011). WHO\u2019s Global Health Expenditure Database in this new version is the reference source for health expenditure for international comparison imbedded in a standardized framework. The SHA 2011 clarifies the financing mechanisms and introduces new dimensions which improve the comparability of health expenditures in the perspective of universal health coverage.", "origins": [ { "producer": "World Health Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$" }, "si_dst_02nd_20": { "title": "Income share held by second 20%", "description_from_producer": "Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\n\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\n\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption.\n\nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\n\nPercentage shares by quintile may not sum to 100 because of rounding.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_dst_03rd_20": { "title": "Income share held by third 20%", "description_from_producer": "Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\n\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\n\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption.\n\nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\n\nPercentage shares by quintile may not sum to 100 because of rounding.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_dst_04th_20": { "title": "Income share held by fourth 20%", "description_from_producer": "Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\n\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\n\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption.\n\nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\n\nPercentage shares by quintile may not sum to 100 because of rounding.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_dst_05th_20": { "title": "Income share held by highest 20%", "description_from_producer": "Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\n\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\n\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption.\n\nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\n\nPercentage shares by quintile may not sum to 100 because of rounding.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_dst_10th_10": { "title": "Income share held by highest 10%", "description_from_producer": "Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\n\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\n\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption.\n\nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_dst_50md": { "title": "Proportion of people living below 50 percent of median income (%)", "description_from_producer": "The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\n\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\n\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption.\n\nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\n\nPercentage shares by quintile may not sum to 100 because of rounding.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "si_dst_frst_10": { "title": "Income share held by lowest 10%", "description_from_producer": "Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\n\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\n\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. No adjustment has been made for spatial differences in cost of living within countries, because the data needed for such calculations are generally unavailable. For further details on the estimation method for low- and middle-income economies, see Ravallion and Chen (1996).\n\nSurvey year is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_dst_frst_20": { "title": "Income share held by lowest 20%", "description_from_producer": "Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\n\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\n\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption.\n\nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\n\nPercentage shares by quintile may not sum to 100 because of rounding.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_pov_dday": { "title": "Poverty headcount ratio at $2.15 a day (2017 PPP) (% of population)", "description_from_producer": "Poverty headcount ratio at $2.15 a day is the percentage of the population living on less than $2.15 a day at 2017 purchasing power adjusted prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.\n\nSince World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $2.15 as the international poverty line using the 2017 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $3.65 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $6.85 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.\n\nEarly editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2017 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $2.15 a day in 2017 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.\n\nThe statistics reported here are based on consumption data or, when unavailable, on income surveys.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%", "display": { "name": "Share of the population living in extreme poverty", "tolerance": 5, "isProjection": false }, "presentation": { "title_public": "Poverty headcount ratio at $2.15 a day (2017 PPP) (% of population)" } }, "si_pov_gaps": { "title": "Poverty gap at $2.15 a day (2017 PPP) (%)", "description_from_producer": "Poverty gap at $2.15 a day (2017 PPP) is the mean shortfall in income or consumption from the poverty line $2.15 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.\n\nSince World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $2.15 as the international poverty line using the 2017 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $3.65 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $6.85 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.\n\nEarly editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2017 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $2.15 a day in 2017 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.\n\nThe statistics reported here are based on consumption data or, when unavailable, on income surveys.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_pov_gini": { "title": "Gini index", "description_from_producer": "Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.\n\nLimitations and exceptions: Gini coefficients are not unique. It is possible for two different Lorenz curves to give rise to the same Gini coefficient. Furthermore it is possible for the Gini coefficient of a developing country to rise (due to increasing inequality of income) while the number of people in absolute poverty decreases. This is because the Gini coefficient measures relative, not absolute, wealth.\n\nAnother limitation of the Gini coefficient is that it is not additive across groups, i.e. the total Gini of a society is not equal to the sum of the Gini's for its sub-groups. Thus, country-level Gini coefficients cannot be aggregated into regional or global Gini's, although a Gini coefficient can be computed for the aggregate.\n\nBecause the underlying household surveys differ in methods and types of welfare measures collected, data are not strictly comparable across countries or even across years within a country. Two sources of non-comparability should be noted for distributions of income in particular. First, the surveys can differ in many respects, including whether they use income or consumption expenditure as the living standard indicator. The distribution of income is typically more unequal than the distribution of consumption. In addition, the definitions of income used differ more often among surveys. Consumption is usually a much better welfare indicator, particularly in developing countries. Second, households differ in size (number of members) and in the extent of income sharing among members. And individuals differ in age and consumption needs. Differences among countries in these respects may bias comparisons of distribution.\n\nWorld Bank staff have made an effort to ensure that the data are as comparable as possible. Wherever possible, consumption has been used rather than income. Income distribution and Gini indexes for high-income economies are calculated directly from the Luxembourg Income Study database, using an estimation method consistent with that applied for developing countries.\n\nStatistical concept and methodology: The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.\n\nThe Gini index provides a convenient summary measure of the degree of inequality. Data on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\n\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption.\n\nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_pov_lmic": { "title": "Poverty headcount ratio at $3.65 a day (2017 PPP) (% of population)", "description_from_producer": "Poverty headcount ratio at $3.65 a day is the percentage of the population living on less than $3.65 a day at 2017 international prices.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.\n\nSince World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $2.15 as the international poverty line using the 2017 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $3.65 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $6.85 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.\n\nEarly editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2017 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $2.15 a day in 2017 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.\n\nThe statistics reported here are based on consumption data or, when unavailable, on income surveys.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_pov_lmic_gp": { "title": "Poverty gap at $3.65 a day (2017 PPP) (%)", "description_from_producer": "Poverty gap at $3.65 a day (2017 PPP) is the mean shortfall in income or consumption from the poverty line $3.65 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.\n\nSince World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $2.15 as the international poverty line using the 2017 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $3.65 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $6.85 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.\n\nEarly editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2017 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $2.15 a day in 2017 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.\n\nThe statistics reported here are based on consumption data or, when unavailable, on income surveys.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_pov_mdim": { "title": "Multidimensional poverty headcount ratio (% of total population)", "description_from_producer": "The percentage of people who are multidimensionally poor\n\nLimitations and exceptions: The compiled data of multidimensional poverty is not intended to be comparable across countries due to national definitions. For instance, key parameters to calculate the measure such as the number of indicators, the weight allocated to each indicator etc, are tailored to the country specific context.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "si_pov_mdim_17": { "title": "Multidimensional poverty headcount ratio, children (% of child population)", "description_from_producer": "The percentage of children who are multidimensionally poor\n\nLimitations and exceptions: The compiled data of multidimensional poverty is not intended to be comparable across countries due to national definitions. For instance, key parameters to calculate the measure such as the number of indicators, the weight allocated to each indicator etc, are tailored to the country specific context.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "si_pov_mdim_17_xq": { "title": "Multidimensional poverty index, children (scale 0-1)", "description_from_producer": "Proportion of the child population that is multidimensionally poor adjusted by the intensity of the deprivations\n\nLimitations and exceptions: The MPI here is a national MPI reported by each country and differs from the global MPI collected by the UNDP. Unlike the global MPI which uses the same dimensional and indicators, the national MPI is calculated using different dimensions and indicators by each country, therefore, it is not comparable across countries.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "si_pov_mdim_fe": { "title": "Multidimensional poverty headcount ratio, female (% of female population)", "description_from_producer": "The percentage of female population who are multidimensionally poor\n\nLimitations and exceptions: The compiled data of multidimensional poverty is not intended to be comparable across countries due to national definitions. For instance, key parameters to calculate the measure such as the number of indicators, the weight allocated to each indicator etc, are tailored to the country specific context.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "si_pov_mdim_hh": { "title": "Multidimensional poverty headcount ratio, household (% of total households)", "description_from_producer": "The percentage of households who are multidimensionally poor\n\nLimitations and exceptions: The compiled data of multidimensional poverty is not intended to be comparable across countries due to national definitions. For instance, key parameters to calculate the measure such as the number of indicators, the weight allocated to each indicator etc, are tailored to the country specific context.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "si_pov_mdim_it": { "title": "Multidimensional poverty intensity", "description_from_producer": "The average percentage of dimensions in which poor people are deprived\n\nLimitations and exceptions: It should be noted that the intensity is not comparable across diffferent countries as it depends on the parameters used in the methodology such as what kind of dimensions and indicators are used, and how the weight is constructed, which varies significantly across countries.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "si_pov_mdim_ma": { "title": "Multidimensional poverty headcount ratio, male (% of male population)", "description_from_producer": "The percentage of male population who are multidimensionally poor\n\nLimitations and exceptions: The compiled data of multidimensional poverty is not intended to be comparable across countries due to national definitions. For instance, key parameters to calculate the measure such as the number of indicators, the weight allocated to each indicator etc, are tailored to the country specific context.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "si_pov_mdim_xq": { "title": "Multidimensional poverty index (scale 0-1)", "description_from_producer": "Proportion of the population that is multidimensionally poor adjusted by the intensity of the deprivations\n\nLimitations and exceptions: The MPI here is a national MPI reported by each country and differs from the global MPI collected by the UNDP. Unlike the global MPI which uses the same dimensions and indicators, the national MPI is calculated using different dimensions and indicators by each country, therefore, it is not comparable across countries.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "si_pov_nahc": { "title": "Poverty headcount ratio at national poverty lines (% of population)", "description_from_producer": "National poverty headcount ratio is the percentage of the population living below the national poverty line(s). National estimates are based on population-weighted subgroup estimates from household surveys. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year.\n\nStatistical concept and methodology: Poverty headcount ratio among the population is measured based on national (i.e. country-specific) poverty lines. A country may have a unique national poverty line or separate poverty lines for rural and urban areas, or for different geographic areas to reflect differences in the cost of living or sometimes to reflect differences in diets and consumption baskets.\n\nPoverty estimates at national poverty lines are computed from household survey data collected from nationally representative samples of households. These data must contain sufficiently detailed information to compute a comprehensive estimate of total household income or consumption (including consumption or income from own production), from which it is possible to construct a correctly weighted distribution of per capita consumption or income.\n\nNational poverty lines are the benchmark for estimating poverty indicators that are consistent with the country's specific economic and social circumstances. National poverty lines reflect local perceptions of the level and composition of consumption or income needed to be non-poor. The perceived boundary between poor and non-poor typically rises with the average income of a country and thus does not provide a uniform measure for comparing poverty rates across countries. While poverty rates at national poverty lines should not be used for comparing poverty rates across countries, they are appropriate for guiding and monitoring the results of country-specific national poverty reduction strategies.\n\nAlmost all national poverty lines in developing economies are anchored to the cost of a food bundle - based on the prevailing national diet of the poor - that provides adequate nutrition for good health and normal activity, plus an allowance for nonfood spending. National poverty lines must be adjusted for inflation between survey years to remain constant in real terms and thus allow for meaningful comparisons of poverty over time. Because diets and consumption baskets change over time, countries periodically recalculate the poverty line based on new survey data. In such cases the new poverty lines should be deflated to obtain comparable poverty estimates from earlier years.\n\nThis series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year. For all other economies, the year reported is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which data collection started.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "si_pov_umic": { "title": "Poverty headcount ratio at $6.85 a day (2017 PPP) (% of population)", "description_from_producer": "Poverty headcount ratio at $6.85 a day is the percentage of the population living on less than $6.85 a day at 2017 international prices.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.\n\nSince World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $2.15 as the international poverty line using the 2017 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $3.65 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $6.85 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.\n\nEarly editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2017 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $2.15 a day in 2017 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.\n\nThe statistics reported here are based on consumption data or, when unavailable, on income surveys.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_pov_umic_gp": { "title": "Poverty gap at $6.85 a day (2017 PPP) (%)", "description_from_producer": "Poverty gap at $6.85 a day (2017 PPP) is the mean shortfall in income or consumption from the poverty line $6.85 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.\n\nLimitations and exceptions: Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.\n\nBesides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.\n\nHowever, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.\n\nStatistical concept and methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.\n\nSince World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $2.15 as the international poverty line using the 2017 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $3.65 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $6.85 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.\n\nEarly editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2017 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $2.15 a day in 2017 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.\n\nThe statistics reported here are based on consumption data or, when unavailable, on income surveys.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_spr_pc40": { "title": "Survey mean consumption or income per capita, bottom 40% of population (2017 PPP $ per day)", "description_from_producer": "Mean consumption or income per capita (2017 PPP $ per day) of the bottom 40%, used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.\n\nLimitations and exceptions: Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2017 PPP $", "short_unit": "$" }, "si_spr_pc40_zg": { "title": "Annualized average growth rate in per capita real survey mean consumption or income, bottom 40% of population (%)", "description_from_producer": "The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered.\n\nThe coverage and quality of the 2017 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2017 exercise of the International Comparison Program. See the Poverty and Inequality Platform for detailed explanations.\n\nLimitations and exceptions: Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "si_spr_pcap": { "title": "Survey mean consumption or income per capita, total population (2017 PPP $ per day)", "description_from_producer": "Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.\n\nLimitations and exceptions: Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2017 PPP $", "short_unit": "$" }, "si_spr_pcap_zg": { "title": "Annualized average growth rate in per capita real survey mean consumption or income, total population (%)", "description_from_producer": "The growth rate in the welfare aggregate of the total population is computed as the annualized average growth rate in per capita real consumption or income of the total population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered.\n\nThe coverage and quality of the 2017 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2017 exercise of the International Comparison Program. See the Poverty and Inequality Platform for detailed explanations.\n\nLimitations and exceptions: Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sl_agr_0714_fe_zs": { "title": "Child employment in agriculture, female (% of female economically active children ages 7-14)", "description_from_producer": "Employment by economic activity refers to the distribution of economically active children by the major industrial categories of the International Standard Industrial Classification (ISIC). Agriculture corresponds to division 1 (ISIC revision 2), categories A and B (ISIC revision 3), or category A (ISIC revision 4) and includes hunting, forestry, and fishing. Economically active children refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three sectors (Agriculture, Manufacturing and Services) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female economically active children ages 7-14", "short_unit": "%" }, "sl_agr_0714_ma_zs": { "title": "Child employment in agriculture, male (% of male economically active children ages 7-14)", "description_from_producer": "Employment by economic activity refers to the distribution of economically active children by the major industrial categories of the International Standard Industrial Classification (ISIC). Agriculture corresponds to division 1 (ISIC revision 2), categories A and B (ISIC revision 3), or category A (ISIC revision 4) and includes hunting, forestry, and fishing. Economically active children refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three sectors (Agriculture, Manufacturing and Services) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male economically active children ages 7-14", "short_unit": "%" }, "sl_agr_0714_zs": { "title": "Child employment in agriculture (% of economically active children ages 7-14)", "description_from_producer": "Employment by economic activity refers to the distribution of economically active children by the major industrial categories of the International Standard Industrial Classification (ISIC). Agriculture corresponds to division 1 (ISIC revision 2), categories A and B (ISIC revision 3), or category A (ISIC revision 4) and includes hunting, forestry, and fishing. Economically active children refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three sectors (Agriculture, Manufacturing and Services) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of economically active children ages 7-14", "short_unit": "%" }, "sl_agr_empl_fe_zs": { "title": "Employment in agriculture, female (% of female employment) (modeled ILO estimate)", "description_from_producer": "Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The agriculture sector consists of activities in agriculture, hunting, forestry and fishing, in accordance with division 1 (ISIC 2) or categories A-B (ISIC 3) or category A (ISIC 4).\n\nLimitations and exceptions: There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.\n\nCountries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.\n\nThe ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectorsdata.\n\nStatistical concept and methodology: The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_agr_empl_ma_zs": { "title": "Employment in agriculture, male (% of male employment) (modeled ILO estimate)", "description_from_producer": "Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The agriculture sector consists of activities in agriculture, hunting, forestry and fishing, in accordance with division 1 (ISIC 2) or categories A-B (ISIC 3) or category A (ISIC 4).\n\nLimitations and exceptions: There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.\n\nCountries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.\n\nThe ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectorsdata.\n\nStatistical concept and methodology: The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_agr_empl_zs": { "title": "Employment in agriculture (% of total employment) (modeled ILO estimate)", "description_from_producer": "Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The agriculture sector consists of activities in agriculture, hunting, forestry and fishing, in accordance with division 1 (ISIC 2) or categories A-B (ISIC 3) or category A (ISIC 4).\n\nLimitations and exceptions: There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.\n\nCountries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.\n\nThe ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectorsdata.\n\nStatistical concept and methodology: The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_1524_sp_fe_ne_zs": { "title": "Employment to population ratio, ages 15-24, female (%) (national estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment to population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment to population ratio can be seen as a positive sign, especially for young people, if it is caused by an increase in their education.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_emp_1524_sp_fe_zs": { "title": "Employment to population ratio, ages 15-24, female (%) (modeled ILO estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment-to-population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment-to-population ratio can be seen as a positive sign, especially for young people, if an increase in their education causes it.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_1524_sp_ma_ne_zs": { "title": "Employment to population ratio, ages 15-24, male (%) (national estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment to population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment to population ratio can be seen as a positive sign, especially for young people, if it is caused by an increase in their education.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_emp_1524_sp_ma_zs": { "title": "Employment to population ratio, ages 15-24, male (%) (modeled ILO estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment-to-population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment-to-population ratio can be seen as a positive sign, especially for young people, if an increase in their education causes it.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_1524_sp_ne_zs": { "title": "Employment to population ratio, ages 15-24, total (%) (national estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment to population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment to population ratio can be seen as a positive sign, especially for young people, if it is caused by an increase in their education.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_emp_1524_sp_zs": { "title": "Employment to population ratio, ages 15-24, total (%) (modeled ILO estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment-to-population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment-to-population ratio can be seen as a positive sign, especially for young people, if an increase in their education causes it.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_mpyr_fe_zs": { "title": "Employers, female (% of female employment) (modeled ILO estimate)", "description_from_producer": "Employers are those workers who, working on their own account or with one or a few partners, hold the type of jobs defined as a \"self-employment jobs\" i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced), and, in this capacity, have engaged, on a continuous basis, one or more persons to work for them as employee(s).\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_mpyr_ma_zs": { "title": "Employers, male (% of male employment) (modeled ILO estimate)", "description_from_producer": "Employers are those workers who, working on their own account or with one or a few partners, hold the type of jobs defined as a \"self-employment jobs\" i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced), and, in this capacity, have engaged, on a continuous basis, one or more persons to work for them as employee(s).\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_mpyr_zs": { "title": "Employers, total (% of total employment) (modeled ILO estimate)", "description_from_producer": "Employers are those workers who, working on their own account or with one or a few partners, hold the type of jobs defined as a \"self-employment jobs\" i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced), and, in this capacity, have engaged, on a continuous basis, one or more persons to work for them as employee(s).\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_self_fe_zs": { "title": "Self-employed, female (% of female employment) (modeled ILO estimate)", "description_from_producer": "Self-employed workers are those workers who, working on their own account or with one or a few partners or in cooperative, hold the type of jobs defined as a \"self-employment jobs.\" i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced. Self-employed workers include four sub-categories of employers, own-account workers, members of producers' cooperatives, and contributing family workers.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_self_ma_zs": { "title": "Self-employed, male (% of male employment) (modeled ILO estimate)", "description_from_producer": "Self-employed workers are those workers who, working on their own account or with one or a few partners or in cooperative, hold the type of jobs defined as a \"self-employment jobs.\" i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced. Self-employed workers include four sub-categories of employers, own-account workers, members of producers' cooperatives, and contributing family workers.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_self_zs": { "title": "Self-employed, total (% of total employment) (modeled ILO estimate)", "description_from_producer": "Self-employed workers are those workers who, working on their own account or with one or a few partners or in cooperative, hold the type of jobs defined as a \"self-employment jobs.\" i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced. Self-employed workers include four sub-categories of employers, own-account workers, members of producers' cooperatives, and contributing family workers.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_smgt_fe_zs": { "title": "Female share of employment in senior and middle management (%)", "description_from_producer": "The proportion of females in total employment in senior and middle management. It corresponds to major group 1 in both ISCO-08 and ISCO-88 minus category 14 in ISCO-08 (hospitality, retail and other services managers) and minus category 13 in ISCO-88 (general managers), since these comprise mainly managers of small enterprises.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sl_emp_totl_sp_fe_ne_zs": { "title": "Employment to population ratio, 15+, female (%) (national estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment to population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment to population ratio can be seen as a positive sign, especially for young people, if it is caused by an increase in their education.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_emp_totl_sp_fe_zs": { "title": "Employment to population ratio, 15+, female (%) (modeled ILO estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment-to-population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment-to-population ratio can be seen as a positive sign, especially for young people, if an increase in their education causes it.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_totl_sp_ma_ne_zs": { "title": "Employment to population ratio, 15+, male (%) (national estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment to population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment to population ratio can be seen as a positive sign, especially for young people, if it is caused by an increase in their education.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_emp_totl_sp_ma_zs": { "title": "Employment to population ratio, 15+, male (%) (modeled ILO estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment-to-population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment-to-population ratio can be seen as a positive sign, especially for young people, if an increase in their education causes it.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_totl_sp_ne_zs": { "title": "Employment to population ratio, 15+, total (%) (national estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment to population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment to population ratio can be seen as a positive sign, especially for young people, if it is caused by an increase in their education.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_emp_totl_sp_zs": { "title": "Employment to population ratio, 15+, total (%) (modeled ILO estimate)", "description_from_producer": "Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.\n\nLimitations and exceptions: Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.\n\nComparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.\n\nThis indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.\n\nStatistical concept and methodology: The employment-to-population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment-to-population ratio can be seen as a positive sign, especially for young people, if an increase in their education causes it.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_vuln_fe_zs": { "title": "Vulnerable employment, female (% of female employment) (modeled ILO estimate)", "description_from_producer": "Vulnerable employment is contributing family workers and own-account workers as a percentage of total employment.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "World Bank based on data from International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_vuln_ma_zs": { "title": "Vulnerable employment, male (% of male employment) (modeled ILO estimate)", "description_from_producer": "Vulnerable employment is contributing family workers and own-account workers as a percentage of total employment.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "World Bank based on data from International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_vuln_zs": { "title": "Vulnerable employment, total (% of total employment) (modeled ILO estimate)", "description_from_producer": "Vulnerable employment is contributing family workers and own-account workers as a percentage of total employment.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "World Bank based on data from International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_work_fe_zs": { "title": "Wage and salaried workers, female (% of female employment) (modeled ILO estimate)", "description_from_producer": "Wage and salaried workers (employees) are those workers who hold the type of jobs defined as \"paid employment jobs,\" where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_work_ma_zs": { "title": "Wage and salaried workers, male (% of male employment) (modeled ILO estimate)", "description_from_producer": "Wage and salaried workers (employees) are those workers who hold the type of jobs defined as \"paid employment jobs,\" where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_emp_work_zs": { "title": "Wage and salaried workers, total (% of total employment) (modeled ILO estimate)", "description_from_producer": "Wage and salaried workers (employees) are those workers who hold the type of jobs defined as \"paid employment jobs,\" where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_fam_0714_fe_zs": { "title": "Children in employment, unpaid family workers, female (% of female children in employment, ages 7-14)", "description_from_producer": "Unpaid family workers are people who work without pay in a market-oriented establishment operated by a related person living in the same household.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three categories (self-employed workers, wage workers, and unpaid family workers) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female children in employment, ages 7-14", "short_unit": "%" }, "sl_fam_0714_ma_zs": { "title": "Children in employment, unpaid family workers, male (% of male children in employment, ages 7-14)", "description_from_producer": "Unpaid family workers are people who work without pay in a market-oriented establishment operated by a related person living in the same household.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three categories (self-employed workers, wage workers, and unpaid family workers) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male children in employment, ages 7-14", "short_unit": "%" }, "sl_fam_0714_zs": { "title": "Children in employment, unpaid family workers (% of children in employment, ages 7-14)", "description_from_producer": "Unpaid family workers are people who work without pay in a market-oriented establishment operated by a related person living in the same household.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three categories (self-employed workers, wage workers, and unpaid family workers) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children in employment, ages 7-14", "short_unit": "%" }, "sl_fam_work_fe_zs": { "title": "Contributing family workers, female (% of female employment) (modeled ILO estimate)", "description_from_producer": "Contributing family workers are those workers who hold \"self-employment jobs\" as own-account workers in a market-oriented establishment operated by a related person living in the same household.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_fam_work_ma_zs": { "title": "Contributing family workers, male (% of male employment) (modeled ILO estimate)", "description_from_producer": "Contributing family workers are those workers who hold \"self-employment jobs\" as own-account workers in a market-oriented establishment operated by a related person living in the same household.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_fam_work_zs": { "title": "Contributing family workers, total (% of total employment) (modeled ILO estimate)", "description_from_producer": "Contributing family workers are those workers who hold \"self-employment jobs\" as own-account workers in a market-oriented establishment operated by a related person living in the same household.\n\nLimitations and exceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.\n\nStatistical concept and methodology: The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_gdp_pcap_em_kd": { "title": "GDP per person employed (constant 2017 PPP $)", "description_from_producer": "GDP per person employed is gross domestic product (GDP) divided by total employment in the economy. Purchasing power parity (PPP) GDP is GDP converted to 2017 constant international dollars using PPP rates. An international dollar has the same purchasing power over GDP that a U.S. dollar has in the United States.\n\nLimitations and exceptions: For comparability of individual sectors labor productivity is estimated according to national accounts conventions. However, there are still significant limitations on the availability of reliable data. Information on consistent series of output in both national currencies and purchasing power parity dollars is not easily available, especially in developing countries, because the definition, coverage, and methodology are not always consistent across countries. For example, countries employ different methodologies for estimating the missing values for the nonmarket service sectors and use different definitions of the informal sector.\n\nStatistical concept and methodology: GDP per person employed represents labor productivity\u2014output per unit of labor input. To compare labor productivity levels across countries, GDP is converted to international dollars using purchasing power parity rates which take account of differences in relative prices between countries.\n\nEstimates are based on employment, population, GDP, and PPP data obtained from International Labour Organization, United Nations Population Division, Eurostat, OECD, and World Bank. The employment rates are part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "constant 2017 PPP $", "short_unit": "$", "display": { "numDecimalPlaces": 0 } }, "sl_ind_empl_fe_zs": { "title": "Employment in industry, female (% of female employment) (modeled ILO estimate)", "description_from_producer": "Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4).\n\nLimitations and exceptions: There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.\n\nCountries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.\n\nThe ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectors data.\n\nStatistical concept and methodology: The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_ind_empl_ma_zs": { "title": "Employment in industry, male (% of male employment) (modeled ILO estimate)", "description_from_producer": "Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4).\n\nLimitations and exceptions: There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.\n\nCountries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.\n\nThe ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectors data.\n\nStatistical concept and methodology: The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_ind_empl_zs": { "title": "Employment in industry (% of total employment) (modeled ILO estimate)", "description_from_producer": "Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4).\n\nLimitations and exceptions: There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.\n\nCountries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.\n\nThe ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectors data.\n\nStatistical concept and methodology: The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_mnf_0714_fe_zs": { "title": "Child employment in manufacturing, female (% of female economically active children ages 7-14)", "description_from_producer": "Employment by economic activity refers to the distribution of economically active children by the major industrial categories of the International Standard Industrial Classification (ISIC). Manufacturing corresponds to division 3 (ISIC revision 2), category D (ISIC revision 3), or category C (ISIC revision 4). Economically active children refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three sectors (Agriculture, Manufacturing and Services) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female economically active children ages 7-14", "short_unit": "%" }, "sl_mnf_0714_ma_zs": { "title": "Child employment in manufacturing, male (% of male economically active children ages 7-14)", "description_from_producer": "Employment by economic activity refers to the distribution of economically active children by the major industrial categories of the International Standard Industrial Classification (ISIC). Manufacturing corresponds to division 3 (ISIC revision 2), category D (ISIC revision 3), or category C (ISIC revision 4). Economically active children refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three sectors (Agriculture, Manufacturing and Services) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male economically active children ages 7-14", "short_unit": "%" }, "sl_mnf_0714_zs": { "title": "Child employment in manufacturing (% of economically active children ages 7-14)", "description_from_producer": "Employment by economic activity refers to the distribution of economically active children by the major industrial categories of the International Standard Industrial Classification (ISIC). Manufacturing corresponds to division 3 (ISIC revision 2), category D (ISIC revision 3), or category C (ISIC revision 4). Economically active children refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three sectors (Agriculture, Manufacturing and Services) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of economically active children ages 7-14", "short_unit": "%" }, "sl_slf_0714_fe_zs": { "title": "Children in employment, self-employed, female (% of female children in employment, ages 7-14)", "description_from_producer": "Self-employed workers are people whose remuneration depends directly on the profits derived from the goods and services they produce, with or without other employees, and include employers, own-account workers, and members of producers cooperatives.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three categories (self-employed workers, wage workers, and unpaid family workers) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female children in employment, ages 7-14", "short_unit": "%" }, "sl_slf_0714_ma_zs": { "title": "Children in employment, self-employed, male (% of male children in employment, ages 7-14)", "description_from_producer": "Self-employed workers are people whose remuneration depends directly on the profits derived from the goods and services they produce, with or without other employees, and include employers, own-account workers, and members of producers cooperatives.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three categories (self-employed workers, wage workers, and unpaid family workers) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male children in employment, ages 7-14", "short_unit": "%" }, "sl_slf_0714_zs": { "title": "Children in employment, self-employed (% of children in employment, ages 7-14)", "description_from_producer": "Self-employed workers are people whose remuneration depends directly on the profits derived from the goods and services they produce, with or without other employees, and include employers, own-account workers, and members of producers cooperatives.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three categories (self-employed workers, wage workers, and unpaid family workers) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children in employment, ages 7-14", "short_unit": "%" }, "sl_srv_0714_fe_zs": { "title": "Child employment in services, female (% of female economically active children ages 7-14)", "description_from_producer": "Employment by economic activity refers to the distribution of economically active children by the major industrial categories of the International Standard Industrial Classification (ISIC). Services correspond to divisions 6-9 (ISIC revision 2), categories G-P (ISIC revision 3), or categories G-U (ISIC revision 4). Services include wholesale and retail trade, hotels and restaurants, transport, financial intermediation, real estate, public administration, education, health and social work, other community services, and private household activity. Economically active children refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three sectors (Agriculture, Manufacturing and Services) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female economically active children ages 7-14", "short_unit": "%" }, "sl_srv_0714_ma_zs": { "title": "Child employment in services, male (% of male economically active children ages 7-14)", "description_from_producer": "Employment by economic activity refers to the distribution of economically active children by the major industrial categories of the International Standard Industrial Classification (ISIC). Services correspond to divisions 6-9 (ISIC revision 2), categories G-P (ISIC revision 3), or categories G-U (ISIC revision 4). Services include wholesale and retail trade, hotels and restaurants, transport, financial intermediation, real estate, public administration, education, health and social work, other community services, and private household activity. Economically active children refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three sectors (Agriculture, Manufacturing and Services) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male economically active children ages 7-14", "short_unit": "%" }, "sl_srv_0714_zs": { "title": "Child employment in services (% of economically active children ages 7-14)", "description_from_producer": "Employment by economic activity refers to the distribution of economically active children by the major industrial categories of the International Standard Industrial Classification (ISIC). Services correspond to divisions 6-9 (ISIC revision 2), categories G-P (ISIC revision 3), or categories G-U (ISIC revision 4). Services include wholesale and retail trade, hotels and restaurants, transport, financial intermediation, real estate, public administration, education, health and social work, other community services, and private household activity. Economically active children refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three sectors (Agriculture, Manufacturing and Services) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of economically active children ages 7-14", "short_unit": "%" }, "sl_srv_empl_fe_zs": { "title": "Employment in services, female (% of female employment) (modeled ILO estimate)", "description_from_producer": "Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The services sector consists of wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services, in accordance with divisions 6-9 (ISIC 2) or categories G-Q (ISIC 3) or categories G-U (ISIC 4).\n\nLimitations and exceptions: There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.\n\nCountries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.\n\nThe ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of three broad sectors data.\n\nStatistical concept and methodology: The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_srv_empl_ma_zs": { "title": "Employment in services, male (% of male employment) (modeled ILO estimate)", "description_from_producer": "Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The services sector consists of wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services, in accordance with divisions 6-9 (ISIC 2) or categories G-Q (ISIC 3) or categories G-U (ISIC 4).\n\nLimitations and exceptions: There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.\n\nCountries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.\n\nThe ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of three broad sectors data.\n\nStatistical concept and methodology: The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_srv_empl_zs": { "title": "Employment in services (% of total employment) (modeled ILO estimate)", "description_from_producer": "Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The services sector consists of wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services, in accordance with divisions 6-9 (ISIC 2) or categories G-Q (ISIC 3) or categories G-U (ISIC 4).\n\nLimitations and exceptions: There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.\n\nCountries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.\n\nThe ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of three broad sectors data.\n\nStatistical concept and methodology: The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_0714_fe_zs": { "title": "Children in employment, female (% of female children ages 7-14)", "description_from_producer": "Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female children ages 7-14", "short_unit": "%" }, "sl_tlf_0714_ma_zs": { "title": "Children in employment, male (% of male children ages 7-14)", "description_from_producer": "Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male children ages 7-14", "short_unit": "%" }, "sl_tlf_0714_sw_fe_tm": { "title": "Average working hours of children, study and work, female, ages 7-14 (hours per week)", "description_from_producer": "Average working hours of children studying and working refer to the average weekly working hours of those children who are attending school in combination with economic activity.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours per week", "short_unit": "hours" }, "sl_tlf_0714_sw_fe_zs": { "title": "Children in employment, study and work, female (% of female children in employment, ages 7-14)", "description_from_producer": "Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey. Study and work refer to children attending school in combination with economic activity.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female children in employment, ages 7-14", "short_unit": "%" }, "sl_tlf_0714_sw_ma_tm": { "title": "Average working hours of children, study and work, male, ages 7-14 (hours per week)", "description_from_producer": "Average working hours of children studying and working refer to the average weekly working hours of those children who are attending school in combination with economic activity.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours per week", "short_unit": "hours" }, "sl_tlf_0714_sw_ma_zs": { "title": "Children in employment, study and work, male (% of male children in employment, ages 7-14)", "description_from_producer": "Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey. Study and work refer to children attending school in combination with economic activity.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male children in employment, ages 7-14", "short_unit": "%" }, "sl_tlf_0714_sw_tm": { "title": "Average working hours of children, study and work, ages 7-14 (hours per week)", "description_from_producer": "Average working hours of children studying and working refer to the average weekly working hours of those children who are attending school in combination with economic activity.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours per week", "short_unit": "hours" }, "sl_tlf_0714_sw_zs": { "title": "Children in employment, study and work (% of children in employment, ages 7-14)", "description_from_producer": "Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey. Study and work refer to children attending school in combination with economic activity.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children in employment, ages 7-14", "short_unit": "%" }, "sl_tlf_0714_wk_fe_tm": { "title": "Average working hours of children, working only, female, ages 7-14 (hours per week)", "description_from_producer": "Average working hours of children working only refers to the average weekly working hours of those children who are involved in economic activity and not attending school.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours per week", "short_unit": "hours" }, "sl_tlf_0714_wk_fe_zs": { "title": "Children in employment, work only, female (% of female children in employment, ages 7-14)", "description_from_producer": "Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey. Work only refers to children involved in economic activity and not attending school.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female children in employment, ages 7-14", "short_unit": "%" }, "sl_tlf_0714_wk_ma_tm": { "title": "Average working hours of children, working only, male, ages 7-14 (hours per week)", "description_from_producer": "Average working hours of children working only refers to the average weekly working hours of those children who are involved in economic activity and not attending school.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours per week", "short_unit": "hours" }, "sl_tlf_0714_wk_ma_zs": { "title": "Children in employment, work only, male (% of male children in employment, ages 7-14)", "description_from_producer": "Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey. Work only refers to children involved in economic activity and not attending school.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male children in employment, ages 7-14", "short_unit": "%" }, "sl_tlf_0714_wk_tm": { "title": "Average working hours of children, working only, ages 7-14 (hours per week)", "description_from_producer": "Average working hours of children working only refers to the average weekly working hours of those children who are involved in economic activity and not attending school.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "hours per week", "short_unit": "hours" }, "sl_tlf_0714_wk_zs": { "title": "Children in employment, work only (% of children in employment, ages 7-14)", "description_from_producer": "Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey. Work only refers to children involved in economic activity and not attending school.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children in employment, ages 7-14", "short_unit": "%" }, "sl_tlf_0714_zs": { "title": "Children in employment, total (% of children ages 7-14)", "description_from_producer": "Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children ages 7-14", "short_unit": "%" }, "sl_tlf_acti_1524_fe_ne_zs": { "title": "Labor force participation rate for ages 15-24, female (%) (national estimate)", "description_from_producer": "Labor force participation rate for ages 15-24 is the proportion of the population ages 15-24 that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_tlf_acti_1524_fe_zs": { "title": "Labor force participation rate for ages 15-24, female (%) (modeled ILO estimate)", "description_from_producer": "Labor force participation rate for ages 15-24 is the proportion of the population ages 15-24 that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_acti_1524_ma_ne_zs": { "title": "Labor force participation rate for ages 15-24, male (%) (national estimate)", "description_from_producer": "Labor force participation rate for ages 15-24 is the proportion of the population ages 15-24 that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_tlf_acti_1524_ma_zs": { "title": "Labor force participation rate for ages 15-24, male (%) (modeled ILO estimate)", "description_from_producer": "Labor force participation rate for ages 15-24 is the proportion of the population ages 15-24 that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_acti_1524_ne_zs": { "title": "Labor force participation rate for ages 15-24, total (%) (national estimate)", "description_from_producer": "Labor force participation rate for ages 15-24 is the proportion of the population ages 15-24 that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_tlf_acti_1524_zs": { "title": "Labor force participation rate for ages 15-24, total (%) (modeled ILO estimate)", "description_from_producer": "Labor force participation rate for ages 15-24 is the proportion of the population ages 15-24 that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_acti_fe_zs": { "title": "Labor force participation rate, female (% of female population ages 15-64) (modeled ILO estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15-64 that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_acti_ma_zs": { "title": "Labor force participation rate, male (% of male population ages 15-64) (modeled ILO estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15-64 that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_acti_zs": { "title": "Labor force participation rate, total (% of total population ages 15-64) (modeled ILO estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15-64 that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_advn_fe_zs": { "title": "Labor force with advanced education, female (% of female working-age population with advanced education)", "description_from_producer": "The ratio of the labor force with advanced education to the working-age population with advanced education. Advanced education comprises short-cycle tertiary education, a bachelor\u2019s degree or equivalent education level, a master\u2019s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female working-age population with advanced education", "short_unit": "%" }, "sl_tlf_advn_ma_zs": { "title": "Labor force with advanced education, male (% of male working-age population with advanced education)", "description_from_producer": "The ratio of the labor force with advanced education to the working-age population with advanced education. Advanced education comprises short-cycle tertiary education, a bachelor\u2019s degree or equivalent education level, a master\u2019s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male working-age population with advanced education", "short_unit": "%" }, "sl_tlf_advn_zs": { "title": "Labor force with advanced education (% of total working-age population with advanced education)", "description_from_producer": "The ratio of the labor force with advanced education to the working-age population with advanced education. Advanced education comprises short-cycle tertiary education, a bachelor\u2019s degree or equivalent education level, a master\u2019s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total working-age population with advanced education", "short_unit": "%" }, "sl_tlf_basc_fe_zs": { "title": "Labor force with basic education, female (% of female working-age population with basic education)", "description_from_producer": "The ratio of the labor force with basic education to the working-age population with basic education. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female working-age population with basic education", "short_unit": "%" }, "sl_tlf_basc_ma_zs": { "title": "Labor force with basic education, male (% of male working-age population with basic education)", "description_from_producer": "The ratio of the labor force with basic education to the working-age population with basic education. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male working-age population with basic education", "short_unit": "%" }, "sl_tlf_basc_zs": { "title": "Labor force with basic education (% of total working-age population with basic education)", "description_from_producer": "The ratio of the labor force with basic education to the working-age population with basic education. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total working-age population with basic education", "short_unit": "%" }, "sl_tlf_cact_fe_ne_zs": { "title": "Labor force participation rate, female (% of female population ages 15+) (national estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_tlf_cact_fe_zs": { "title": "Labor force participation rate, female (% of female population ages 15+) (modeled ILO estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_cact_fm_ne_zs": { "title": "Ratio of female to male labor force participation rate (%) (national estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.", "origins": [ { "producer": "World Bank based on data from International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_tlf_cact_fm_zs": { "title": "Ratio of female to male labor force participation rate (%) (modeled ILO estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "World Bank based on data from International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_cact_ma_ne_zs": { "title": "Labor force participation rate, male (% of male population ages 15+) (national estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_tlf_cact_ma_zs": { "title": "Labor force participation rate, male (% of male population ages 15+) (modeled ILO estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_cact_ne_zs": { "title": "Labor force participation rate, total (% of total population ages 15+) (national estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_tlf_cact_zs": { "title": "Labor force participation rate, total (% of total population ages 15+) (modeled ILO estimate)", "description_from_producer": "Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period.\n\nLimitations and exceptions: Data on the labor force are compiled by the ILO from labor force surveys, censuses, and establishment censuses and surveys. For some countries a combination of these sources is used. Labor force surveys are the most comprehensive source for internationally comparable labor force data. They can cover all non-institutionalized civilians, all branches and sectors of the economy, and all categories of workers, including people holding multiple jobs. By contrast, labor force data from population censuses are often based on a limited number of questions on the economic characteristics of individuals, with little scope to probe. The resulting data often differ from labor force survey data and vary considerably by country, depending on the census scope and coverage. Establishment censuses and surveys provide data only on the employed population, not unemployed workers, workers in small establishments, or workers in the informal sector.\n\nThe reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In countries, where the household is the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.\n\nDiffering definitions of employment age also affect comparability. For most countries the working age is 15 and older, but in some countries children younger than 15 work full- or part-time and are included in the estimates. Similarly, some countries have an upper age limit. As a result, calculations may systematically over- or underestimate actual rates.\n\nStatistical concept and methodology: The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_tlf_intm_fe_zs": { "title": "Labor force with intermediate education, female (% of female working-age population with intermediate education)", "description_from_producer": "The ratio of the labor force with intermediate education to the working-age population with intermediate education. Intermediate education comprises upper secondary or post-secondary non tertiary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female working-age population with intermediate education", "short_unit": "%" }, "sl_tlf_intm_ma_zs": { "title": "Labor force with intermediate education, male (% of male working-age population with intermediate education)", "description_from_producer": "The ratio of the labor force with intermediate education to the working-age population with intermediate education. Intermediate education comprises upper secondary or post-secondary non tertiary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male working-age population with intermediate education", "short_unit": "%" }, "sl_tlf_intm_zs": { "title": "Labor force with intermediate education (% of total working-age population with intermediate education)", "description_from_producer": "The ratio of the labor force with intermediate education to the working-age population with intermediate education. Intermediate education comprises upper secondary or post-secondary non tertiary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total working-age population with intermediate education", "short_unit": "%" }, "sl_tlf_part_fe_zs": { "title": "Part time employment, female (% of total female employment)", "description_from_producer": "Part time employment refers to regular employment in which working time is substantially less than normal. Definitions of part time employment differ by country.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total female employment", "short_unit": "%" }, "sl_tlf_part_ma_zs": { "title": "Part time employment, male (% of total male employment)", "description_from_producer": "Part time employment refers to regular employment in which working time is substantially less than normal. Definitions of part time employment differ by country.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total male employment", "short_unit": "%" }, "sl_tlf_part_zs": { "title": "Part time employment, total (% of total employment)", "description_from_producer": "Part time employment refers to regular employment in which working time is substantially less than normal. Definitions of part time employment differ by country.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total employment", "short_unit": "%" }, "sl_tlf_totl_fe_zs": { "title": "Labor force, female (% of total labor force)", "description_from_producer": "Female labor force as a percentage of the total show the extent to which women are active in the labor force. Labor force comprises people ages 15 and older who supply labor for the production of goods and services during a specified period.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or voluntarily left work. In addition, persons who did not look for work but have an arrangement for a future job are also counted as unemployed. Still, some unemployment is unavoidable\u2014at any time, some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. The labor force or the economically active portion of the population serves as the base for this indicator, not the total population.\n\nEstimates are based on labor force participation rates and population data from International Labour Organization and United Nations Population Division. The labor force participation rates are part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total labor force", "short_unit": "%" }, "sl_tlf_totl_in": { "title": "Labor force, total", "description_from_producer": "Labor force comprises people ages 15 and older who supply labor for the production of goods and services during a specified period. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or voluntarily left work. In addition, persons who did not look for work but have an arrangement for a future job are also counted as unemployed. Still, some unemployment is unavoidable\u2014at any time, some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. The labor force or the economically active portion of the population serves as the base for this indicator, not the total population.\n\nEstimates are based on labor force participation rates and population data from International Labour Organization and United Nations Population Division. The labor force participation rates are part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sl_uem_1524_fe_ne_zs": { "title": "Unemployment, youth female (% of female labor force ages 15-24) (national estimate)", "description_from_producer": "Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or who have voluntarily left work. Persons who did not look for work but have an arrangements for a future job are also counted as unemployed.\n\nSome unemployment is unavoidable. At any time some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. It is the labour force or the economically active portion of the population that serves as the base for this indicator, not the total population.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_uem_1524_fe_zs": { "title": "Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate)", "description_from_producer": "Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or voluntarily left work. In addition, persons who did not look for work but have an arrangement for a future job are also counted as unemployed. Still, some unemployment is unavoidable\u2014at any time, some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. The labor force or the economically active portion of the population serves as the base for this indicator, not the total population.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_uem_1524_ma_ne_zs": { "title": "Unemployment, youth male (% of male labor force ages 15-24) (national estimate)", "description_from_producer": "Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or who have voluntarily left work. Persons who did not look for work but have an arrangements for a future job are also counted as unemployed.\n\nSome unemployment is unavoidable. At any time some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. It is the labour force or the economically active portion of the population that serves as the base for this indicator, not the total population.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_uem_1524_ma_zs": { "title": "Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate)", "description_from_producer": "Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or voluntarily left work. In addition, persons who did not look for work but have an arrangement for a future job are also counted as unemployed. Still, some unemployment is unavoidable\u2014at any time, some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. The labor force or the economically active portion of the population serves as the base for this indicator, not the total population.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_uem_1524_ne_zs": { "title": "Unemployment, youth total (% of total labor force ages 15-24) (national estimate)", "description_from_producer": "Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or who have voluntarily left work. Persons who did not look for work but have an arrangements for a future job are also counted as unemployed.\n\nSome unemployment is unavoidable. At any time some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. It is the labour force or the economically active portion of the population that serves as the base for this indicator, not the total population.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_uem_1524_zs": { "title": "Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate)", "description_from_producer": "Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or voluntarily left work. In addition, persons who did not look for work but have an arrangement for a future job are also counted as unemployed. Still, some unemployment is unavoidable\u2014at any time, some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. The labor force or the economically active portion of the population serves as the base for this indicator, not the total population.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_uem_advn_fe_zs": { "title": "Unemployment with advanced education, female (% of female labor force with advanced education)", "description_from_producer": "The percentage of the labor force with an advanced level of education who are unemployed. Advanced education comprises short-cycle tertiary education, a bachelor\u2019s degree or equivalent education level, a master\u2019s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female labor force with advanced education", "short_unit": "%" }, "sl_uem_advn_ma_zs": { "title": "Unemployment with advanced education, male (% of male labor force with advanced education)", "description_from_producer": "The percentage of the labor force with an advanced level of education who are unemployed. Advanced education comprises short-cycle tertiary education, a bachelor\u2019s degree or equivalent education level, a master\u2019s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male labor force with advanced education", "short_unit": "%" }, "sl_uem_advn_zs": { "title": "Unemployment with advanced education (% of total labor force with advanced education)", "description_from_producer": "The percentage of the labor force with an advanced level of education who are unemployed. Advanced education comprises short-cycle tertiary education, a bachelor\u2019s degree or equivalent education level, a master\u2019s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total labor force with advanced education", "short_unit": "%" }, "sl_uem_basc_fe_zs": { "title": "Unemployment with basic education, female (% of female labor force with basic education)", "description_from_producer": "The percentage of the labor force with a basic level of education who are unemployed. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female labor force with basic education", "short_unit": "%" }, "sl_uem_basc_ma_zs": { "title": "Unemployment with basic education, male (% of male labor force with basic education)", "description_from_producer": "The percentage of the labor force with a basic level of education who are unemployed. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male labor force with basic education", "short_unit": "%" }, "sl_uem_basc_zs": { "title": "Unemployment with basic education (% of total labor force with basic education)", "description_from_producer": "The percentage of the labor force with a basic level of education who are unemployed. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total labor force with basic education", "short_unit": "%" }, "sl_uem_intm_fe_zs": { "title": "Unemployment with intermediate education, female (% of female labor force with intermediate education)", "description_from_producer": "The percentage of the labor force with an intermediate level of education who are unemployed. Intermediate education comprises upper secondary or post-secondary non tertiary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female labor force with intermediate education", "short_unit": "%" }, "sl_uem_intm_ma_zs": { "title": "Unemployment with intermediate education, male (% of male labor force with intermediate education)", "description_from_producer": "The percentage of the labor force with an intermediate level of education who are unemployed. Intermediate education comprises upper secondary or post-secondary non tertiary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male labor force with intermediate education", "short_unit": "%" }, "sl_uem_intm_zs": { "title": "Unemployment with intermediate education (% of total labor force with intermediate education)", "description_from_producer": "The percentage of the labor force with an intermediate level of education who are unemployed. Intermediate education comprises upper secondary or post-secondary non tertiary education according to the International Standard Classification of Education 2011 (ISCED 2011).", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total labor force with intermediate education", "short_unit": "%" }, "sl_uem_neet_fe_zs": { "title": "Share of youth not in education, employment or training, female (% of female youth population)", "description_from_producer": "Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.\n\nLimitations and exceptions: Data should be used cautiously because of differences in age coverage.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work in a recent past period, and currently available for and seeking for employment. But there may be persons who do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. NEET rates capture more broadly untapped potential youth, including such individuals who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\").\n\nYouth are defined as persons ages 15 to 24; young adults are those ages 25 to 29; and adults are those ages 25 and above. However, countries vary somewhat in their operational definitions. In particular, the lower age limit for young people is usually determined by the minimum age for leaving school, where this exists. When data are available for more than two age groups in a given year, one value for persons ages 15 to 29 is taken, considering that not all people complete their education by the age of 24.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female youth population", "short_unit": "%" }, "sl_uem_neet_ma_zs": { "title": "Share of youth not in education, employment or training, male (% of male youth population)", "description_from_producer": "Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.\n\nLimitations and exceptions: Data should be used cautiously because of differences in age coverage.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work in a recent past period, and currently available for and seeking for employment. But there may be persons who do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. NEET rates capture more broadly untapped potential youth, including such individuals who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\").\n\nYouth are defined as persons ages 15 to 24; young adults are those ages 25 to 29; and adults are those ages 25 and above. However, countries vary somewhat in their operational definitions. In particular, the lower age limit for young people is usually determined by the minimum age for leaving school, where this exists. When data are available for more than two age groups in a given year, one value for persons ages 15 to 29 is taken, considering that not all people complete their education by the age of 24.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male youth population", "short_unit": "%" }, "sl_uem_neet_zs": { "title": "Share of youth not in education, employment or training, total (% of youth population)", "description_from_producer": "Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.\n\nLimitations and exceptions: Data should be used cautiously because of differences in age coverage.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work in a recent past period, and currently available for and seeking for employment. But there may be persons who do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. NEET rates capture more broadly untapped potential youth, including such individuals who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\").\n\nYouth are defined as persons ages 15 to 24; young adults are those ages 25 to 29; and adults are those ages 25 and above. However, countries vary somewhat in their operational definitions. In particular, the lower age limit for young people is usually determined by the minimum age for leaving school, where this exists. When data are available for more than two age groups in a given year, one value for persons ages 15 to 29 is taken, considering that not all people complete their education by the age of 24.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of youth population", "short_unit": "%" }, "sl_uem_totl_fe_ne_zs": { "title": "Unemployment, female (% of female labor force) (national estimate)", "description_from_producer": "Unemployment refers to the share of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or who have voluntarily left work. Persons who did not look for work but have an arrangements for a future job are also counted as unemployed.\n\nSome unemployment is unavoidable. At any time some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. It is the labour force or the economically active portion of the population that serves as the base for this indicator, not the total population.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_uem_totl_fe_zs": { "title": "Unemployment, female (% of female labor force) (modeled ILO estimate)", "description_from_producer": "Unemployment refers to the share of the labor force that is without work but available for and seeking employment.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or voluntarily left work. In addition, persons who did not look for work but have an arrangement for a future job are also counted as unemployed. Still, some unemployment is unavoidable\u2014at any time, some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. The labor force or the economically active portion of the population serves as the base for this indicator, not the total population.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_uem_totl_ma_ne_zs": { "title": "Unemployment, male (% of male labor force) (national estimate)", "description_from_producer": "Unemployment refers to the share of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or who have voluntarily left work. Persons who did not look for work but have an arrangements for a future job are also counted as unemployed.\n\nSome unemployment is unavoidable. At any time some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. It is the labour force or the economically active portion of the population that serves as the base for this indicator, not the total population.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_uem_totl_ma_zs": { "title": "Unemployment, male (% of male labor force) (modeled ILO estimate)", "description_from_producer": "Unemployment refers to the share of the labor force that is without work but available for and seeking employment.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or voluntarily left work. In addition, persons who did not look for work but have an arrangement for a future job are also counted as unemployed. Still, some unemployment is unavoidable\u2014at any time, some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. The labor force or the economically active portion of the population serves as the base for this indicator, not the total population.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_uem_totl_ne_zs": { "title": "Unemployment, total (% of total labor force) (national estimate)", "description_from_producer": "Unemployment refers to the share of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or who have voluntarily left work. Persons who did not look for work but have an arrangements for a future job are also counted as unemployed.\n\nSome unemployment is unavoidable. At any time some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. It is the labour force or the economically active portion of the population that serves as the base for this indicator, not the total population.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "national estimate" }, "sl_uem_totl_zs": { "title": "Unemployment, total (% of total labor force) (modeled ILO estimate)", "description_from_producer": "Unemployment refers to the share of the labor force that is without work but available for and seeking employment.\n\nLimitations and exceptions: The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.\n\nThere may be also persons not currently in the labour market who want to work but do not actively \"seek\" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the \"hidden unemployed\" or \"discouraged workers\") is a criterion that will affect the unemployment count of both women and men.\n\nHowever, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.\n\nStatistical concept and methodology: The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or voluntarily left work. In addition, persons who did not look for work but have an arrangement for a future job are also counted as unemployed. Still, some unemployment is unavoidable\u2014at any time, some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. The labor force or the economically active portion of the population serves as the base for this indicator, not the total population.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\n\nNotes from original source: Given the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "origins": [ { "producer": "International Labour Organization", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "modeled ILO estimate" }, "sl_wag_0714_fe_zs": { "title": "Children in employment, wage workers, female (% of female children in employment, ages 7-14)", "description_from_producer": "Wage workers (also known as employees) are people who hold explicit (written or oral) or implicit employment contracts that provide basic remuneration that does not depend directly on the revenue of the unit for which they work.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three categories (self-employed workers, wage workers, and unpaid family workers) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female children in employment, ages 7-14", "short_unit": "%" }, "sl_wag_0714_ma_zs": { "title": "Children in employment, wage workers, male (% of male children in employment, ages 7-14)", "description_from_producer": "Wage workers (also known as employees) are people who hold explicit (written or oral) or implicit employment contracts that provide basic remuneration that does not depend directly on the revenue of the unit for which they work.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three categories (self-employed workers, wage workers, and unpaid family workers) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male children in employment, ages 7-14", "short_unit": "%" }, "sl_wag_0714_zs": { "title": "Children in employment, wage workers (% of children in employment, ages 7-14)", "description_from_producer": "Wage workers (also known as employees) are people who hold explicit (written or oral) or implicit employment contracts that provide basic remuneration that does not depend directly on the revenue of the unit for which they work.\n\nLimitations and exceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. In addition, the shares of three categories (self-employed workers, wage workers, and unpaid family workers) may not add up to 100 percent because of a residual category not included.\n\nStatistical concept and methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.", "origins": [ { "producer": "International Labour Organization, UNICEF and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children in employment, ages 7-14", "short_unit": "%" }, "sm_pop_netm": { "title": "Net migration", "description_from_producer": "Net migration is the net total of migrants during the period, that is, the number of immigrants minus the number of emigrants, including both citizens and noncitizens.\n\nLimitations and exceptions: International migration is the component of population change most difficult to measure and estimate reliably. Thus, the quality and quantity of the data used in the estimation and projection of net migration varies considerably by country. Furthermore, the movement of people across international boundaries, which is very often a response to changing socio-economic, political and environmental forces, is subject to a great deal of volatility. Refugee movements, for instance, may involve large numbers of people moving across boundaries in a short time. For these reasons, projections of future international migration levels are the least robust part of current population projections and reflect mainly a continuation of recent levels and trends in net migration.\n\nStatistical concept and methodology: The United Nations Population Division provides data on net migration and migrant stock. Because data on migrant stock is difficult for countries to collect, the United Nations Population Division takes into account the past migration history of a country or area, the migration policy of a country, and the influx of refugees in recent periods when deriving estimates of net migration. The data to calculate these estimates come from a variety of sources, including border statistics, administrative records, surveys, and censuses.\n\nWhen there is insufficient data, net migration is derived through the difference between the overall population growth rate and the rate of natural increase (the difference between the birth rate and the death rate) during the same period. Such calculations are usually made for intercensal periods. The estimates are also derived from the data on foreign-born population - people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population - that is, people who are citizens of a country other than the country in which they reside - are used as estimates.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sm_pop_refg": { "title": "Refugee population by country or territory of asylum", "description_from_producer": "Refugees are people who are recognized as refugees under the 1951 Convention Relating to the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity Convention Governing the Specific Aspects of Refugee Problems in Africa, people recognized as refugees in accordance with the UNHCR statute, people granted refugee-like humanitarian status, and people provided temporary protection. Asylum seekers--people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers--are excluded. Palestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict. Country of asylum is the country where an asylum claim was filed and granted.\n\nLimitations and exceptions: There are difficulties in collecting accurate statistics on refugees. Many refugees may not be aware of the need to register or may choose not to do so, and administrative records tend to overestimate the number of refugees because it is easier to register than to de-register. In addition, most industrialized countries lack a refugee register and are thus not in a position to provide accurate information on the number of refugees residing in their country. Many countries have registries that are only maintained at the local level, so the data is not centralized.\n\nAsylum-seekers are persons who have applied for asylum or refugee status, but who have not yet received a final decision on their application. A distinction should be made between the number of asylum-seekers who have submitted an individual request during a certain period (\"asylum applications submitted\") and the number of asylum-seekers whose individual asylum request has not yet been decided at a certain date (\"backlog of undecided or pending cases\"). Caution should therefore be exercised when interpreting data on asylum-seekers.\n\nThe United Nations High Commissioner for Refugees (UNHCR) collects and maintains data on refugees, except for Palestinian refugees residing in areas under the mandate of the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA). Registration is voluntary, and estimates by the UNRWA are not an accurate count of the Palestinian refugee population. The data shows estimates of refugees collected by the UNHCR, complemented by estimates of Palestinian refugees under the UNRWA mandate. Thus, the aggregates differ from those published by the UNHCR.\n\nStatistics concerning the former USSR have been reported under the Russian Federation, those concerning the former Czechoslovakia have been reported under the Czech Republic and those concerning the former Yugoslavia and 'Serbia and Montenegro' have been reported under Serbia. Since 2006, separate statistics are available for Serbia and for Montenegro. Prior to 2006, no separate statistics are available and both countries have been reported under Serbia.\n\nStatistical concept and methodology: The United Nations High Commissioner for Refugees (UNHCR) collects and maintains data on refugees in their Statistical Online Population Database. The refugee data does not include Palestinian refugees residing in areas under the mandate of the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA). However, the Palestinian refugees living outside the UNRWA areas of operation do fall under the responsibility of UNHCR and are thus included in the Statistical Online Population Database.\n\nRefugees are an important part of migrant stock. The refugee data refer to people who have crossed an international border to find sanctuary and have been granted refugee or refugee-like status or temporary protection. There are three main providers of refugee data: governmental agencies, UNHCR field offices and NGOs. Registrations, together with other sources - including estimates and surveys - are the main sources of refugee data. In the absence of Government estimates, UNHCR has estimated the refugee population in most industrialized countries, based on recognition of asylum-seekers. Prior to 2007, resettled refugees were included in these estimates.\n\nUp to and including 2006, to ensure that the refugee population in countries that lack a refugee registry is reflected in the global statistics, the number of refugees was estimated by UNHCR based on the arrival of refugees through resettlement programmes and the individual recognition of refugees over a 10-year (Europe and, since 2006, the United States) or 5-year (the United States before 2006, Canada and Oceania) period. Starting with the 2007 data, the cut-off period has been harmonized and now covers a 10-year period for Europe and non-European countries. Resettled refugees, however, are excluded from the refugee estimates in all countries.\n\nThe 2007-2011 refugee population category includes people in a refugee-like situation, most of who were previously included in the Others of concern group. This sub-category is descriptive in nature and includes groups of persons who are outside their country or territory of origin and who face protection risks similar to those of refugees, but for whom refugee status has, for practical or other reasons, not been ascertained.\n\nAsylum seekers - people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers - and internally displaced people - who are often confused with refugees - are not included in the data. Unlike refugees, internally displaced people remain under the protection of their own government, even if their reason for fleeing was similar to that of refugees.\n\nPalestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict.\n\nNotes from original source: The refugee population category from 2007 onwards also includes people in a refugee-like situation, most of who were previously included in the Others of concern group. This sub-category is descriptive in nature and includes groups of persons who are outside their country or territory of origin and who face protection risks similar to those of refugees, but for whom refugee status has, for practical or other reasons, not been ascertained.\n\nStatistics concerning the former USSR have been reported under the Russian Federation, those concerning the former Czechoslovakia have been reported under the Czech Republic and those concerning the former Yugoslavia and 'Serbia and Montenegro' have been reported under Serbia. Since 2006, separate statistics are available for Serbia and for Montenegro. Prior to 2006, no separate statistics are available and both countries have been reported under Serbia.", "origins": [ { "producer": "UN High Commissioner for Refugees (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sm_pop_refg_or": { "title": "Refugee population by country or territory of origin", "description_from_producer": "Refugees are people who are recognized as refugees under the 1951 Convention Relating to the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity Convention Governing the Specific Aspects of Refugee Problems in Africa, people recognized as refugees in accordance with the UNHCR statute, people granted refugee-like humanitarian status, and people provided temporary protection. Asylum seekers--people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers--are excluded. Palestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict. Country of origin generally refers to the nationality or country of citizenship of a claimant.\n\nLimitations and exceptions: There are difficulties in collecting accurate statistics on refugees. Many refugees may not be aware of the need to register or may choose not to do so, and administrative records tend to overestimate the number of refugees because it is easier to register than to de-register. In addition, most industrialized countries lack a refugee register and are thus not in a position to provide accurate information on the number of refugees residing in their country. Many countries have registries that are only maintained at the local level, so the data is not centralized.\n\nThe United Nations High Commissioner for Refugees (UNHCR) collects and maintains data on refugees, except for Palestinian refugees residing in areas under the mandate of the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA). Registration is voluntary, and estimates by the UNRWA are not an accurate count of the Palestinian refugee population. The data shows estimates of refugees collected by the UNHCR, complemented by estimates of Palestinian refugees under the UNRWA mandate. Thus, the aggregates differ from those published by the UNHCR.\n\nStatistics concerning the former USSR have been reported under the Russian Federation, those concerning the former Czechoslovakia have been reported under the Czech Republic and those concerning the former Yugoslavia and 'Serbia and Montenegro' have been reported under Serbia. Since 2006, separate statistics are available for Serbia and for Montenegro. Prior to 2006, no separate statistics are available and both countries have been reported under Serbia.\n\nStatistical concept and methodology: The United Nations High Commissioner for Refugees (UNHCR) collects and maintains data on refugees in their Statistical Online Population Database. The refugee data does not include Palestinian refugees residing in areas under the mandate of the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA). However, the Palestinian refugees living outside the UNRWA areas of operation do fall under the responsibility of UNHCR and are thus included in the Statistical Online Population Database.\n\nRefugees are an important part of migrant stock. The refugee data refer to people who have crossed an international border to find sanctuary and have been granted refugee or refugee-like status or temporary protection. There are three main providers of refugee data: governmental agencies, UNHCR field offices and NGOs. Registrations, together with other sources - including estimates and surveys - are the main sources of refugee data. In the absence of Government estimates, UNHCR has estimated the refugee population in most industrialized countries, based on recognition of asylum-seekers. Prior to 2007, resettled refugees were included in these estimates.\n\nUp to and including 2006, to ensure that the refugee population in countries that lack a refugee registry is reflected in the global statistics, the number of refugees was estimated by UNHCR based on the arrival of refugees through resettlement programmes and the individual recognition of refugees over a 10-year (Europe and, since 2006, the United States) or 5-year (the United States before 2006, Canada and Oceania) period. Starting with the 2007 data, the cut-off period has been harmonized and now covers a 10-year period for Europe and non-European countries. Resettled refugees, however, are excluded from the refugee estimates in all countries.\n\nThe 2007-2011 refugee population category includes people in a refugee-like situation, most of who were previously included in the Others of concern group. This sub-category is descriptive in nature and includes groups of persons who are outside their country or territory of origin and who face protection risks similar to those of refugees, but for whom refugee status has, for practical or other reasons, not been ascertained.\n\nAsylum seekers - people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers - and internally displaced people - who are often confused with refugees - are not included in the data. Unlike refugees, internally displaced people remain under the protection of their own government, even if their reason for fleeing was similar to that of refugees.\n\nPalestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict.\n\nNotes from original source: The refugee population category from 2007 onwards also includes people in a refugee-like situation, most of who were previously included in the Others of concern group. This sub-category is descriptive in nature and includes groups of persons who are outside their country or territory of origin and who face protection risks similar to those of refugees, but for whom refugee status has, for practical or other reasons, not been ascertained.\n\nStatistics concerning the former USSR have been reported under the Russian Federation, those concerning the former Czechoslovakia have been reported under the Czech Republic and those concerning the former Yugoslavia and 'Serbia and Montenegro' have been reported under Serbia. Since 2006, separate statistics are available for Serbia and for Montenegro. Prior to 2006, no separate statistics are available and both countries have been reported under Serbia.", "origins": [ { "producer": "UN High Commissioner for Refugees (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sm_pop_totl": { "title": "International migrant stock, total", "description_from_producer": "International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.\n\nLimitations and exceptions: In deriving the estimates, an international migrant was equated to a person living in a country other than that in which he or she was born. That is, the number of international migrants, also called the international migrant stock, would represent the number of foreign-born persons enumerated in the countries or areas constituting the world. However, because several countries lack data on the foreign-born, data on the number of foreigners, if available, were used instead as the basis of estimation. Consequently, the overall number of migrants in world regions or at the global level do not quite represent the overall number of foreign-born persons.\n\nThe disintegration and reunification of countries causes discontinuities in the change of the international migrant stock. Because an international migrant is equated with a person who was born outside the country in which he or she resides, when a country disintegrates, persons who had been internal migrants because they had moved from one part of the country to another may become, overnight, international migrants without having moved at that time. Such changes introduce artificial but unavoidable discontinuities in the trend of the international migrant stock. The reunification of States also introduces discontinuities, but in the opposite direction.\n\nStatistical concept and methodology: The basic data to estimate the international migrant stock were obtained mostly from population censuses held during the decennial rounds of censuses. Some of the data used were obtained from population registers and nationally representative surveys.\n\nIn the majority of cases, the sources available had gathered information on the place of birth of the enumerated population, thus allowing for the identification of the foreign-born population. In estimating the international migrant stock, international migrants have been equated with the foreign-born whenever possible. In most countries lacking data on place of birth, information on the country of citizenship of those enumerated was available and was used as the basis for the identification of international migrants, thus effectively equating international migrants with foreign citizens.\n\nAmong the 230 countries or areas that constituted the world in 2008, 91 percent had at least one data source on the international migrant stock, and of those 78 percent used the number of foreign-born persons as the basis for estimation. For about 18 percent of the countries, the number of international migrants was based on data regarding foreign citizens. There were nine countries with no information including China, the Democratic People's Republic of Korea, Eritrea and Somalia.\n\nFor countries having information on the international migrant stock for at least two points in time, interpolation or extrapolation using an exponential growth rate was used to estimate the international migrant stock on 1 July of the reference years. In some instances, the estimates were adjusted on the basis of other relevant information, including the size of the total population in the country, to ensure that the proportion of migrants in small populations did not increase to unacceptable levels.\n\nFor all other countries with only one data source, estimates for the reference years were derived by assuming growth rates of the migrant stock in the years preceding or following the only data source available. For the nine countries or areas for which no information was available on the international migrant stock, a model, based on the general observation that the proportion of international migrants tends to be inversely related to the size of the total population, was used.\n\nAfter the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union.", "origins": [ { "producer": "UN Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sm_pop_totl_zs": { "title": "International migrant stock (% of population)", "description_from_producer": "International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.\n\nLimitations and exceptions: In deriving the estimates, an international migrant was equated to a person living in a country other than that in which he or she was born. That is, the number of international migrants, also called the international migrant stock, would represent the number of foreign-born persons enumerated in the countries or areas constituting the world. However, because several countries lack data on the foreign-born, data on the number of foreigners, if available, were used instead as the basis of estimation. Consequently, the overall number of migrants in world regions or at the global level do not quite represent the overall number of foreign-born persons.\n\nThe disintegration and reunification of countries causes discontinuities in the change of the international migrant stock. Because an international migrant is equated with a person who was born outside the country in which he or she resides, when a country disintegrates, persons who had been internal migrants because they had moved from one part of the country to another may become, overnight, international migrants without having moved at that time. Such changes introduce artificial but unavoidable discontinuities in the trend of the international migrant stock. The reunification of States also introduces discontinuities, but in the opposite direction.\n\nStatistical concept and methodology: The basic data to estimate the international migrant stock were obtained mostly from population censuses held during the decennial rounds of censuses. Some of the data used were obtained from population registers and nationally representative surveys.\n\nIn the majority of cases, the sources available had gathered information on the place of birth of the enumerated population, thus allowing for the identification of the foreign-born population. In estimating the international migrant stock, international migrants have been equated with the foreign-born whenever possible. In most countries lacking data on place of birth, information on the country of citizenship of those enumerated was available and was used as the basis for the identification of international migrants, thus effectively equating international migrants with foreign citizens.\n\nAmong the 230 countries or areas that constituted the world in 2008, 91 percent had at least one data source on the international migrant stock, and of those 78 percent used the number of foreign-born persons as the basis for estimation. For about 18 percent of the countries, the number of international migrants was based on data regarding foreign citizens. There were nine countries with no information including China, the Democratic People's Republic of Korea, Eritrea and Somalia.\n\nFor countries having information on the international migrant stock for at least two points in time, interpolation or extrapolation using an exponential growth rate was used to estimate the international migrant stock on 1 July of the reference years. In some instances, the estimates were adjusted on the basis of other relevant information, including the size of the total population in the country, to ensure that the proportion of migrants in small populations did not increase to unacceptable levels.\n\nFor all other countries with only one data source, estimates for the reference years were derived by assuming growth rates of the migrant stock in the years preceding or following the only data source available. For the nine countries or areas for which no information was available on the international migrant stock, a model, based on the general observation that the proportion of international migrants tends to be inversely related to the size of the total population, was used.\n\nAfter the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union.", "origins": [ { "producer": "UN Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "sn_itk_defc_zs": { "title": "Prevalence of undernourishment (% of population)", "description_from_producer": "Prevalence of undernourishments is the percentage of the population whose habitual food consumption is insufficient to provide the dietary energy levels that are required to maintain a normal active and healthy life. Data showing as 2.5 may signify a prevalence of undernourishment below 2.5%.\n\nLimitations and exceptions: From a policy and program standpoint, this measure has its limits. First, food insecurity exists even where food availability is not a problem because of inadequate access of poor households to food. Second, food insecurity is an individual or household phenomenon, and the average food available to each person, even corrected for possible effects of low income, is not a good predictor of food insecurity among the population. And third, nutrition security is determined not only by food security but also by the quality of care of mothers and children and the quality of the household's health environment (Smith and Haddad 2000).\n\nStatistical concept and methodology: Data on undernourishment are from the Food and Agriculture Organization (FAO) of the United Nations and measure food deprivation based on average food available for human consumption per person, the level of inequality in access to food, and the minimum calories required for an average person.", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%", "display": { "numDecimalPlaces": 1 } }, "sn_itk_msfi_zs": { "title": "Prevalence of moderate or severe food insecurity in the population (%)", "description_from_producer": "The percentage of people in the population who live in households classified as moderately or severely food insecure. A household is classified as moderately or severely food insecure when at least one adult in the household has reported to have been exposed, at times during the year, to low quality diets and might have been forced to also reduce the quantity of food they would normally eat because of a lack of money or other resources.\n\nStatistical concept and methodology: The assessment is conducted using data collected with the Food Insecurity Experience Scale or a compatible experience-based food security measurement questionnaire (such as the HFSSM). The probability to be food insecure is estimated using the one-parameter logistic Item Response Theory model (the Rasch model) and thresholds for classification are made cross country comparable by calibrating the metrics obtained in each country against the FIES global reference scale, maintained by FAO. The threshold to classify \"moderate or severe\" food insecurity corresponds to the severity associated with the item \"having to eat less\" on the global FIES scale. It is an indicator of lack of food access.The indicator is calculated as an average over 3 years (eg. data for 2015 is the average of 2014-2016 data).", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sn_itk_salt_zs": { "title": "Consumption of iodized salt (% of households)", "description_from_producer": "Percentage of households which have salt they used for cooking that tested positive (>0ppm) for presence of iodine.\n\nStatistical concept and methodology: Most of the data on consumption of iodized salt are derived from household surveys. For the data that are from household surveys, the year refers to the survey year.", "origins": [ { "producer": "UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of households", "short_unit": "%" }, "sn_itk_svfi_zs": { "title": "Prevalence of severe food insecurity in the population (%)", "description_from_producer": "The percentage of people in the population who live in households classified as severely food insecure. A household is classified as severely food insecure when at least one adult in the household has reported to have been exposed, at times during the year, to several of the most severe experiences described in the FIES questions, such as to have been forced to reduce the quantity of the food, to have skipped meals, having gone hungry, or having to go for a whole day without eating because of a lack of money or other resources.\n\nStatistical concept and methodology: The assessment is conducted using data collected with the Food Insecurity Experience Scale or a compatible experience-based food security measurement questionnaire (such as the HFSSM). The probability to be food insecure is estimated using the one-parameter logistic Item Response Theory model (the Rasch model) and thresholds for classification are made cross country comparable by calibrating the metrics obtained in each country against the FIES global reference scale, maintained by FAO. The threshold to classify \"severe\" food insecurity corresponds to the severity associated with the item \"having not eaten for an entire day\" on the global FIES scale. It is an indicator of lack of food access.The indicator is calculated as an average over 3 years (eg. data for 2015 is the average of 2014-2016 data).", "origins": [ { "producer": "Food and Agriculture Organization of the United Nations (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sn_itk_vita_zs": { "title": "Vitamin A supplementation coverage rate (% of children ages 6-59 months)", "description_from_producer": "Vitamin A supplementation coverage rate refers to the percentage of children ages 6-59 months old receiving two high-dose vitamin A supplements in a calendar year.\n\nNotes from original source: Only UNICEF's current vitamin A supplementation priority countries for national level programmes are included.", "origins": [ { "producer": "UNICEF (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of children ages 6-59 months", "short_unit": "%" }, "sp_ado_tfrt": { "title": "Adolescent fertility rate (births per 1,000 women ages 15-19)", "description_from_producer": "Adolescent fertility rate is the number of births per 1,000 women ages 15-19.\n\nStatistical concept and methodology: Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\n\nAdolescent fertility rates are based on data on registered live births from vital registration systems or, in the absence of such systems, from censuses or sample surveys. The estimated rates are generally considered reliable measures of fertility in the recent past. Where no empirical information on age-specific fertility rates is available, a model is used to estimate the share of births to adolescents. For countries without vital registration systems fertility rates are generally based on extrapolations from trends observed in censuses or surveys from earlier years.", "origins": [ { "producer": "UN Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "births per 1,000 women ages 15-19", "short_unit": "births" }, "sp_dyn_amrt_fe": { "title": "Mortality rate, adult, female (per 1,000 female adults)", "description_from_producer": "Adult mortality rate, female, is the probability of dying between the ages of 15 and 60--that is, the probability of a 15-year-old female dying before reaching age 60, if subject to age-specific mortality rates of the specified year between those ages.\n\nLimitations and exceptions: Data from United Nations Population Division's World Populaton Prospects are originally 5-year period data and the presented are linearly interpolated by the World Bank for annual series. Therefore they may not reflect real events as much as observed data.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data. Where reliable age-specific mortality data are available, life tables can be constructed from age-specific mortality data, and adult mortality rates can be calculated from life tables.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 female adults" }, "sp_dyn_amrt_ma": { "title": "Mortality rate, adult, male (per 1,000 male adults)", "description_from_producer": "Adult mortality rate, male, is the probability of dying between the ages of 15 and 60--that is, the probability of a 15-year-old male dying before reaching age 60, if subject to age-specific mortality rates of the specified year between those ages.\n\nLimitations and exceptions: Data from United Nations Population Division's World Populaton Prospects are originally 5-year period data and the presented are linearly interpolated by the World Bank for annual series. Therefore they may not reflect real events as much as observed data.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data. Where reliable age-specific mortality data are available, life tables can be constructed from age-specific mortality data, and adult mortality rates can be calculated from life tables.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 male adults" }, "sp_dyn_cbrt_in": { "title": "Birth rate, crude (per 1,000 people)", "description_from_producer": "Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.\n\nLimitations and exceptions: Vital registers are the preferred source for these data, but in many developing countries systems for registering births and deaths are absent or incomplete because of deficiencies in the coverage of events or geographic areas. Many developing countries carry out special household surveys that ask respondents about recent births and deaths. Estimates derived in this way are subject to sampling errors and recall errors.\n\nStatistical concept and methodology: Vital rates are based on data from birth and death registration systems, censuses, and sample surveys by national statistical offices and other organizations, or on demographic analysis. Data for the most recent year for some high-income countries are provisional estimates based on vital registers. The estimates for many countries are projections based on extrapolations of levels and trends from earlier years or interpolations of population estimates and projections from the United Nations Population Division.", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 people" }, "sp_dyn_cdrt_in": { "title": "Death rate, crude (per 1,000 people)", "description_from_producer": "Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.\n\nLimitations and exceptions: Vital registers are the preferred source for these data, but in many developing countries systems for registering births and deaths are absent or incomplete because of deficiencies in the coverage of events or geographic areas. Many developing countries carry out special household surveys that ask respondents about recent births and deaths. Estimates derived in this way are subject to sampling errors and recall errors.\n\nStatistical concept and methodology: The crude death rate is calculated as the number of deaths in a given period divided by the population exposed to risk of death in that period. For human populations the period is usually one year and, if the population changes in size over the year, the divisor is taken as the population at the mid-year. The rate is usually expressed in terms of 1,000 people: for example, a crude death rate of 9.5 (per 1000 people) in a population of 1 million would imply 9500 deaths per year in the entire population. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.\n\nVital rates are based on data from birth and death registration systems, censuses, and sample surveys by national statistical offices and other organizations, or on demographic analysis. Data for the most recent year for some high-income countries are provisional estimates based on vital registers. The estimates for many countries are projections based on extrapolations of levels and trends from earlier years or interpolations of population estimates and projections from the United Nations Population Division.", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 people" }, "sp_dyn_conm_zs": { "title": "Contraceptive prevalence, any modern method (% of married women ages 15-49)", "description_from_producer": "Contraceptive prevalence, any modern method is the percentage of married women ages 15-49 who are practicing, or whose sexual partners are practicing, at least one modern method of contraception. Modern methods of contraception include female and male sterilization, oral hormonal pills, the intra-uterine device (IUD), the male condom, injectables, the implant (including Norplant), vaginal barrier methods, the female condom and emergency contraception.\n\nLimitations and exceptions: While the data availability on contraceptive use has increased, in many countries the contraceptive use data are available only for married women.\n\nThe time frame used to assess contraceptive prevalence may vary. In many surveys, it is left to the respondent to determine what is meant by \u201ccurrently using\u201d a method of contraception.\n\nStatistical concept and methodology: Contraceptive prevalence rates are obtained mainly from nationally representative household surveys, including: Demographic and Health Surveys; Multiple Indicator Cluster Surveys; Contraceptive Prevalence Surveys; Gender and Generations Survey; Reproductive Health Surveys; and World Fertility Surveys. Additional information was provided by other international survey programs and national surveys.\n\nMarried women refer to women who are married (defined in relation to the marriage laws or customs of a country) and to women in a union, which refers to women living with their partner in the same household (also referred to as cohabiting unions, consensual unions, unmarried unions, or \u201cliving together\u201d).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of women ages 15-49", "short_unit": "%" }, "sp_dyn_conu_zs": { "title": "Contraceptive prevalence, any method (% of married women ages 15-49)", "description_from_producer": "Contraceptive prevalence, any method is the percentage of married women ages 15-49 who are practicing, or whose sexual partners are practicing, any method of contraception (modern or traditional). Modern methods of contraception include female and male sterilization, oral hormonal pills, the intra-uterine device (IUD), the male condom, injectables, the implant (including Norplant), vaginal barrier methods, the female condom and emergency contraception. Traditional methods of contraception include rhythm (e.g., fertility awareness based methods, periodic abstinence), withdrawal and other traditional methods.\n\nLimitations and exceptions: While the data availability on contraceptive use has increased, in many countries the contraceptive use data are available only for married women.\n\nThe time frame used to assess contraceptive prevalence may vary. In many surveys, it is left to the respondent to determine what is meant by \u201ccurrently using\u201d a method of contraception.\n\nStatistical concept and methodology: Contraceptive prevalence rates are obtained mainly from nationally representative household surveys, including: Demographic and Health Surveys; Multiple Indicator Cluster Surveys; Contraceptive Prevalence Surveys; Gender and Generations Survey; Reproductive Health Surveys; and World Fertility Surveys. Additional information was provided by other international survey programs and national surveys.\n\nMarried women refer to women who are married (defined in relation to the marriage laws or customs of a country) and to women in a union, which refers to women living with their partner in the same household (also referred to as cohabiting unions, consensual unions, unmarried unions, or \u201cliving together\u201d).", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of women ages 15-49", "short_unit": "%" }, "sp_dyn_imrt_fe_in": { "title": "Mortality rate, infant, female (per 1,000 live births)", "description_from_producer": "Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female live births in a given year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 live births" }, "sp_dyn_imrt_in": { "title": "Mortality rate, infant (per 1,000 live births)", "description_from_producer": "Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 live births" }, "sp_dyn_imrt_ma_in": { "title": "Mortality rate, infant, male (per 1,000 live births)", "description_from_producer": "Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male live births in a given year.\n\nLimitations and exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.\n\nStatistical concept and methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.\n\nEstimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.", "origins": [ { "producer": "UN Inter-agency Group for Child Mortality Estimation (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 1,000 live births" }, "sp_dyn_le00_fe_in": { "title": "Life expectancy at birth, female (years)", "description_from_producer": "Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.\n\nLimitations and exceptions: Annual data series from United Nations Population Division's World Population Prospects are interpolated data from 5-year period data. Therefore they may not reflect real events as much as observed data.\n\nStatistical concept and methodology: Life expectancy at birth used here is the average number of years a newborn is expected to live if mortality patterns at the time of its birth remain constant in the future. It reflects the overall mortality level of a population, and summarizes the mortality pattern that prevails across all age groups in a given year. It is calculated in a period life table which provides a snapshot of a population's mortality pattern at a given time. It therefore does not reflect the mortality pattern that a person actually experiences during his/her life, which can be calculated in a cohort life table.\n\nHigh mortality in young age groups significantly lowers the life expectancy at birth. But if a person survives his/her childhood of high mortality, he/she may live much longer. For example, in a population with a life expectancy at birth of 50, there may be few people dying at age 50. The life expectancy at birth may be low due to the high childhood mortality so that once a person survives his/her childhood, he/she may live much longer than 50 years.", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "years", "short_unit": "years" }, "sp_dyn_le00_in": { "title": "Life expectancy at birth, total (years)", "description_from_producer": "Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.\n\nLimitations and exceptions: Annual data series from United Nations Population Division's World Population Prospects are interpolated data from 5-year period data. Therefore they may not reflect real events as much as observed data.\n\nStatistical concept and methodology: Life expectancy at birth used here is the average number of years a newborn is expected to live if mortality patterns at the time of its birth remain constant in the future. It reflects the overall mortality level of a population, and summarizes the mortality pattern that prevails across all age groups in a given year. It is calculated in a period life table which provides a snapshot of a population's mortality pattern at a given time. It therefore does not reflect the mortality pattern that a person actually experiences during his/her life, which can be calculated in a cohort life table.\n\nHigh mortality in young age groups significantly lowers the life expectancy at birth. But if a person survives his/her childhood of high mortality, he/she may live much longer. For example, in a population with a life expectancy at birth of 50, there may be few people dying at age 50. The life expectancy at birth may be low due to the high childhood mortality so that once a person survives his/her childhood, he/she may live much longer than 50 years.", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "years", "short_unit": "years" }, "sp_dyn_le00_ma_in": { "title": "Life expectancy at birth, male (years)", "description_from_producer": "Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.\n\nLimitations and exceptions: Annual data series from United Nations Population Division's World Population Prospects are interpolated data from 5-year period data. Therefore they may not reflect real events as much as observed data.\n\nStatistical concept and methodology: Life expectancy at birth used here is the average number of years a newborn is expected to live if mortality patterns at the time of its birth remain constant in the future. It reflects the overall mortality level of a population, and summarizes the mortality pattern that prevails across all age groups in a given year. It is calculated in a period life table which provides a snapshot of a population's mortality pattern at a given time. It therefore does not reflect the mortality pattern that a person actually experiences during his/her life, which can be calculated in a cohort life table.\n\nHigh mortality in young age groups significantly lowers the life expectancy at birth. But if a person survives his/her childhood of high mortality, he/she may live much longer. For example, in a population with a life expectancy at birth of 50, there may be few people dying at age 50. The life expectancy at birth may be low due to the high childhood mortality so that once a person survives his/her childhood, he/she may live much longer than 50 years.", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "years", "short_unit": "years" }, "sp_dyn_tfrt_in": { "title": "Fertility rate, total (births per woman)", "description_from_producer": "Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.\n\nLimitations and exceptions: Annual data series from United Nations Population Division's World Population Prospects are interpolated data from 5-year period data. Therefore they may not reflect real events as much as observed data.\n\nStatistical concept and methodology: Total fertility rates are based on data on registered live births from vital registration systems or, in the absence of such systems, from censuses or sample surveys. The estimated rates are generally considered reliable measures of fertility in the recent past. Where no empirical information on age-specific fertility rates is available, a model is used to estimate the share of births to adolescents. For countries without vital registration systems fertility rates are generally based on extrapolations from trends observed in censuses or surveys from earlier years.", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "births per woman", "short_unit": "births" }, "sp_dyn_to65_fe_zs": { "title": "Survival to age 65, female (% of cohort)", "description_from_producer": "Survival to age 65 refers to the percentage of a cohort of newborn infants that would survive to age 65, if subject to age specific mortality rates of the specified year.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of cohort", "short_unit": "%" }, "sp_dyn_to65_ma_zs": { "title": "Survival to age 65, male (% of cohort)", "description_from_producer": "Survival to age 65 refers to the percentage of a cohort of newborn infants that would survive to age 65, if subject to age specific mortality rates of the specified year.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of cohort", "short_unit": "%" }, "sp_dyn_wfrt": { "title": "Wanted fertility rate (births per woman)", "description_from_producer": "Wanted fertility rate is an estimate of what the total fertility rate would be if all unwanted births were avoided.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) via World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "births per woman", "short_unit": "births" }, "sp_hou_fema_zs": { "title": "Female headed households (% of households with a female head)", "description_from_producer": "Female headed households shows the percentage of households with a female head.\n\nLimitations and exceptions: The definition of female-headed household differs greatly across countries, making cross-country comparison difficult. In some cases it is assumed that a woman cannot be the head of any household with an adult male, because of sex-biased stereotype. Caution should be used in interpreting the data.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) via World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of households with a female head", "short_unit": "%" }, "sp_m15_2024_fe_zs": { "title": "Women who were first married by age 15 (% of women ages 20-24)", "description_from_producer": "Women who were first married by age 15 refers to the percentage of women ages 20-24 who were first married by age 15.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of women ages 20-24", "short_unit": "%" }, "sp_m18_2024_fe_zs": { "title": "Women who were first married by age 18 (% of women ages 20-24)", "description_from_producer": "Women who were first married by age 18 refers to the percentage of women ages 20-24 who were first married by age 18.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of women ages 20-24", "short_unit": "%" }, "sp_mtr_1519_zs": { "title": "Teenage mothers (% of women ages 15-19 who have had children or are currently pregnant)", "description_from_producer": "Teenage mothers are the percentage of women ages 15-19 who already have children or are currently pregnant.", "origins": [ { "producer": "Demographic and Health Surveys (DHS) via World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of women ages 15-19 who have had children or are currently pregnant", "short_unit": "%" }, "sp_pop_0004_fe_5y": { "title": "Population ages 00-04, female (% of female population)", "description_from_producer": "Female population between the ages 0 to 4 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_0004_ma_5y": { "title": "Population ages 00-04, male (% of male population)", "description_from_producer": "Male population between the ages 0 to 4 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_0014_fe_in": { "title": "Population ages 0-14, female", "description_from_producer": "Female population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_0014_fe_zs": { "title": "Population ages 0-14, female (% of female population)", "description_from_producer": "Female population between the ages 0 to 14 as a percentage of the total female population. Population is based on the de facto definition of population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sp_pop_0014_ma_in": { "title": "Population ages 0-14, male", "description_from_producer": "Male population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_0014_ma_zs": { "title": "Population ages 0-14, male (% of male population)", "description_from_producer": "Male population between the ages 0 to 14 as a percentage of the total male population. Population is based on the de facto definition of population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sp_pop_0014_to": { "title": "Population ages 0-14, total", "description_from_producer": "Total population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_0014_to_zs": { "title": "Population ages 0-14 (% of total population)", "description_from_producer": "Population between the ages 0 to 14 as a percentage of the total population. Population is based on the de facto definition of population.\n\nLimitations and exceptions: Because the five-year age group is the cohort unit and five-year period data are used in the United Nations Population Division's World Population Prospects, interpolations to obtain annual data or single age structure may not reflect actual events or age composition. For more information, see the original source.\n\nStatistical concept and methodology: Age structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects. For more information, see the original source.\n\nTotal population is based on the de facto population including all residents regardless of legal status or citizenship. The values shown are midyear estimates. For more information see metadata for total population (SP.POP.TOTL).", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. 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It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_0509_ma_5y": { "title": "Population ages 05-09, male (% of male population)", "description_from_producer": "Male population between the ages 5 to 9 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_1014_fe_5y": { "title": "Population ages 10-14, female (% of female population)", "description_from_producer": "Female population between the ages 10 to 14 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. 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It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_1564_fe_in": { "title": "Population ages 15-64, female", "description_from_producer": "Female population between the ages 15 to 64. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. 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Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. 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Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_1564_ma_zs": { "title": "Population ages 15-64, male (% of male population)", "description_from_producer": "Male population between the ages 15 to 64 as a percentage of the total male population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. 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Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_1564_to_zs": { "title": "Population ages 15-64 (% of total population)", "description_from_producer": "Total population between the ages 15 to 64 as a percentage of the total population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.\n\nLimitations and exceptions: Because the five-year age group is the cohort unit and five-year period data are used in the United Nations Population Division's World Population Prospects, interpolations to obtain annual data or single age structure may not reflect actual events or age composition. For more information, see the original source.\n\nStatistical concept and methodology: Age structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects. For more information, see the original source.\n\nTotal population is based on the de facto population including all residents regardless of legal status or citizenship. The values shown are midyear estimates. For more information see metadata for total population (SP.POP.TOTL).", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. 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It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_2024_ma_5y": { "title": "Population ages 20-24, male (% of male population)", "description_from_producer": "Male population between the ages 20 to 24 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_2529_fe_5y": { "title": "Population ages 25-29, female (% of female population)", "description_from_producer": "Female population between the ages 25 to 29 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_2529_ma_5y": { "title": "Population ages 25-29, male (% of male population)", "description_from_producer": "Male population between the ages 25 to 29 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_3034_fe_5y": { "title": "Population ages 30-34, female (% of female population)", "description_from_producer": "Female population between the ages 30 to 34 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_3034_ma_5y": { "title": "Population ages 30-34, male (% of male population)", "description_from_producer": "Male population between the ages 30 to 34 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_3539_fe_5y": { "title": "Population ages 35-39, female (% of female population)", "description_from_producer": "Female population between the ages 35 to 39 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_3539_ma_5y": { "title": "Population ages 35-39, male (% of male population)", "description_from_producer": "Male population between the ages 35 to 39 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_4044_fe_5y": { "title": "Population ages 40-44, female (% of female population)", "description_from_producer": "Female population between the ages 40 to 44 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_4044_ma_5y": { "title": "Population ages 40-44, male (% of male population)", "description_from_producer": "Male population between the ages 40 to 44 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_4549_fe_5y": { "title": "Population ages 45-49, female (% of female population)", "description_from_producer": "Female population between the ages 45 to 49 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_4549_ma_5y": { "title": "Population ages 45-49, male (% of male population)", "description_from_producer": "Male population between the ages 45 to 49 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_5054_fe_5y": { "title": "Population ages 50-54, female (% of female population)", "description_from_producer": "Female population between the ages 50 to 54 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_5054_ma_5y": { "title": "Population ages 50-54, male (% of male population)", "description_from_producer": "Male population between the ages 50 to 54 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_5559_fe_5y": { "title": "Population ages 55-59, female (% of female population)", "description_from_producer": "Female population between the ages 55 to 59 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_5559_ma_5y": { "title": "Population ages 55-59, male (% of male population)", "description_from_producer": "Male population between the ages 55 to 59 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_6064_fe_5y": { "title": "Population ages 60-64, female (% of female population)", "description_from_producer": "Female population between the ages 60 to 64 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_6064_ma_5y": { "title": "Population ages 60-64, male (% of male population)", "description_from_producer": "Male population between the ages 60 to 64 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_6569_fe_5y": { "title": "Population ages 65-69, female (% of female population)", "description_from_producer": "Female population between the ages 65 to 69 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_6569_ma_5y": { "title": "Population ages 65-69, male (% of male population)", "description_from_producer": "Male population between the ages 65 to 69 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_65up_fe_in": { "title": "Population ages 65 and above, female", "description_from_producer": "Female population 65 years of age or older. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_65up_fe_zs": { "title": "Population ages 65 and above, female (% of female population)", "description_from_producer": "Female population 65 years of age or older as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sp_pop_65up_ma_in": { "title": "Population ages 65 and above, male", "description_from_producer": "Male population 65 years of age or older. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_65up_ma_zs": { "title": "Population ages 65 and above, male (% of male population)", "description_from_producer": "Male population 65 years of age or older as a percentage of the total male population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sp_pop_65up_to": { "title": "Population ages 65 and above, total", "description_from_producer": "Total population 65 years of age or older. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_65up_to_zs": { "title": "Population ages 65 and above (% of total population)", "description_from_producer": "Population ages 65 and above as a percentage of the total population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.\n\nLimitations and exceptions: Because the five-year age group is the cohort unit and five-year period data are used in the United Nations Population Division's World Population Prospects, interpolations to obtain annual data or single age structure may not reflect actual events or age composition. For more information, see the original source.\n\nStatistical concept and methodology: Age structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects. For more information, see the original source. Total population is based on the de facto population including all residents regardless of legal status or citizenship. The values shown are midyear estimates. For more information see metadata for total population (SP.POP.TOTL).", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sp_pop_7074_fe_5y": { "title": "Population ages 70-74, female (% of female population)", "description_from_producer": "Female population between the ages 70 to 74 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_7074_ma_5y": { "title": "Population ages 70-74, male (% of male population)", "description_from_producer": "Male population between the ages 70 to 74 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_7579_fe_5y": { "title": "Population ages 75-79, female (% of female population)", "description_from_producer": "Female population between the ages 75 to 79 as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_7579_ma_5y": { "title": "Population ages 75-79, male (% of male population)", "description_from_producer": "Male population between the ages 75 to 79 as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_80up_fe_5y": { "title": "Population ages 80 and above, female (% of female population)", "description_from_producer": "Female population between the ages 80 and above as a percentage of the total female population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of female population", "short_unit": "%" }, "sp_pop_80up_ma_5y": { "title": "Population ages 80 and above, male (% of male population)", "description_from_producer": "Male population between the ages 80 and above as a percentage of the total male population.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of male population", "short_unit": "%" }, "sp_pop_brth_mf": { "title": "Sex ratio at birth (male births per female births)", "description_from_producer": "Sex ratio at birth refers to male births per female births. The data are 5 year averages.", "origins": [ { "producer": "United Nations Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "male births per female births", "short_unit": "male births" }, "sp_pop_dpnd": { "title": "Age dependency ratio (% of working-age population)", "description_from_producer": "Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.\n\nLimitations and exceptions: Because the five-year age group is the cohort unit and five-year period data are used in the United Nations Population Division's World Population Prospects, interpolations to obtain annual data or single age structure may not reflect actual events or age composition. For more information, see the original source.\n\nStatistical concept and methodology: Dependency ratios capture variations in the proportions of children, elderly people, and working-age people in the population that imply the dependency burden that the working-age population bears in relation to children and the elderly. But dependency ratios show only the age composition of a population, not economic dependency. Some children and elderly people are part of the labor force, and many working-age people are not.\n\nAge structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects. For more information, see the original source.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of working-age population", "short_unit": "%" }, "sp_pop_dpnd_ol": { "title": "Age dependency ratio, old (% of working-age population)", "description_from_producer": "Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.\n\nLimitations and exceptions: Because the five-year age group is the cohort unit and five-year period data are used in the United Nations Population Division's World Population Prospects, interpolations to obtain annual data or single age structure may not reflect actual events or age composition. For more information, see the original source.\n\nStatistical concept and methodology: Dependency ratios capture variations in the proportions of children, elderly people, and working-age people in the population that imply the dependency burden that the working-age population bears in relation to children and the elderly. But dependency ratios show only the age composition of a population, not economic dependency. Some children and elderly people are part of the labor force, and many working-age people are not.\n\nAge structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects. For more information, see the original source.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of working-age population", "short_unit": "%" }, "sp_pop_dpnd_yg": { "title": "Age dependency ratio, young (% of working-age population)", "description_from_producer": "Age dependency ratio, young, is the ratio of younger dependents--people younger than 15--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.\n\nLimitations and exceptions: Because the five-year age group is the cohort unit and five-year period data are used in the United Nations Population Division's World Population Prospects, interpolations to obtain annual data or single age structure may not reflect actual events or age composition. For more information, see the original source.\n\nStatistical concept and methodology: Dependency ratios capture variations in the proportions of children, elderly people, and working-age people in the population that imply the dependency burden that the working-age population bears in relation to children and the elderly. But dependency ratios show only the age composition of a population, not economic dependency. Some children and elderly people are part of the labor force, and many working-age people are not.\n\nAge structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects. For more information, see the original source.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of working-age population", "short_unit": "%", "display": { "name": "Age dependency ratio, young" }, "presentation": { "title_public": "Age dependency ratio, young (% of working-age population)" } }, "sp_pop_grow": { "title": "Population growth (annual %)", "description_from_producer": "Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.\n\nStatistical concept and methodology: Total population growth rates are calculated on the assumption that rate of growth is constant between two points in time. The growth rate is computed using the exponential growth formula:\n\nr = ln(pn/p0)/n,\n\nwhere r is the exponential rate of growth, ln() is the natural logarithm, pn is the end period population, p0 is the beginning period population, and n is the number of years in between. Note that this is not the geometric growth rate used to compute compound growth over discrete periods.\n\nFor information on total population from which the growth rates are calculated, see total population (SP.POP.TOTL).", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "sp_pop_scie_rd_p6": { "title": "Researchers in R&D (per million people)", "description_from_producer": "The number of researchers engaged in Research &Development (R&D), expressed as per million. Researchers are professionals who conduct research and improve or develop concepts, theories, models techniques instrumentation, software of operational methods. R&D covers basic research, applied research, and experimental development.\n\nLimitations and exceptions: Estimates of the resources allocated to R&D are affected by national characteristics such as the periodicity and coverage of national R&D surveys across institutional sectors and industries; and the use of different sampling and estimation methods. R&D typically involves a few large performers, hence R&D surveys use various techniques to maintain up-to-date registers of known performers, while attempting to identify new or occasional performers.\n\nStatistical concept and methodology: Researchers are professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems, as well as in the management of these projects. Students studying at the master\u2019s or doctoral level (ISCED2011 level 7 or 8) engaged in R&D are included.\n\nThe OECD's Frascati Manual defines research and experimental development as \"creative work undertaken on a systemic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications.\" R&D covers basic research, applied research, and experimental development.\n\n(1) Basic research - Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundation of phenomena and observable facts, without any particular application or use in view.\n\n(2) Applied research - Applied research is also original investigation undertaken in order to acquire new knowledge; it is, however, directed primarily towards a specific practical aim or objective.\n\n(3) Experimental development - Experimental development is systematic work, drawing on existing knowledge gained from research and/or practical experience, which is directed to producing new materials, products or devices, to installing new processes, systems and services, or to improving substantially those already produced or installed.\n\nThe fields of science and technology used to classify R&D according to the Revised Fields of Science and Technology Classification are:\n1. Natural sciences;\n2. Engineering and technology;\n3. Medical and health sciences;\n4. Agricultural sciences;\n5. Social sciences;\n6. Humanities and the arts.\n\nData are for full-time equivalent (FTE); the FTE of R&D personnel is defined as the ratio of working hours actually spent on R&D during a specific reference period (usually a calendar year) divided by the total number of hours conventionally worked in the same period by an individual or by a group.\n\nThe data are obtained through statistical surveys which are regularly conducted at national level covering R&D performing entities in the private and public sectors.", "origins": [ { "producer": "UNESCO Institute for Statistics", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per million people" }, "sp_pop_tech_rd_p6": { "title": "Technicians in R&D (per million people)", "description_from_producer": "The number of technicians participated in Research & Development (R&D), expressed as per million. Technicians and equivalent staff are people who perform scientific and technical tasks involving the application of concepts and operational methods, normally under the supervision of researchers. R&D covers basic research, applied research, and experimental development.\n\nLimitations and exceptions: Estimates of the resources allocated to R&D are affected by national characteristics such as the periodicity and coverage of national R&D surveys across institutional sectors and industries; and the use of different sampling and estimation methods. R&D typically involves a few large performers, hence R&D surveys use various techniques to maintain up-to-date registers of known performers, while attempting to identify new or occasional performers.\n\nStatistical concept and methodology: Technicians in research and development (R&D) are persons whose main tasks require technical knowledge and experience in one or more fields of engineering, physical and life sciences, or social sciences and humanities.\n\nThe OECD's Frascati Manual defines research and experimental development as \"creative work undertaken on a systemic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications.\" R&D covers basic research, applied research, and experimental development.\n\n(1) Basic research - Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundation of phenomena and observable facts, without any particular application or use in view.\n\n(2) Applied research - Applied research is also original investigation undertaken in order to acquire new knowledge; it is, however, directed primarily towards a specific practical aim or objective.\n\n(3) Experimental development - Experimental development is systematic work, drawing on existing knowledge gained from research and/or practical experience, which is directed to producing new materials, products or devices, to installing new processes, systems and services, or to improving substantially those already produced or installed.\n\nThe fields of science and technology used to classify R&D according to the Revised Fields of Science and Technology Classification are:\n1. Natural sciences;\n2. Engineering and technology;\n3. Medical and health sciences;\n4. Agricultural sciences;\n5. Social sciences;\n6. Humanities and the arts.\n\nData are for full-time equivalent (FTE); the FTE of R&D personnel is defined as the ratio of working hours actually spent on R&D during a specific reference period (usually a calendar year) divided by the total number of hours conventionally worked in the same period by an individual or by a group.\n\nThe data are obtained through statistical surveys which are regularly conducted at national level covering R&D performing entities in the private and public sectors.", "origins": [ { "producer": "UNESCO Institute for Statistics (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per million people" }, "sp_pop_totl": { "title": "Population, total", "description_from_producer": "Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.\n\nLimitations and exceptions: Current population estimates for developing countries that lack (i) reliable recent census data, and (ii) pre- and post-census estimates for countries with census data, are provided by the United Nations Population Division and other agencies.\n\nThe cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in both the model and the data. In the UN estimates the five-year age group is the cohort unit and five-year period data are used; therefore interpolations to obtain annual data or single age structure may not reflect actual events or age composition.\n\nBecause future trends cannot be known with certainty, population projections have a wide range of uncertainty.\n\nStatistical concept and methodology: Population estimates are usually based on national population censuses. Estimates for the years before and after the census are interpolations or extrapolations based on demographic models.\n\nErrors and undercounting occur even in high-income countries. In developing countries errors may be substantial because of limits in the transport, communications, and other resources required to conduct and analyze a full census.\n\nThe quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data.\n\nThe currentness of a census and the availability of complementary data from surveys or registration systems are objective ways to judge demographic data quality. Some European countries' registration systems offer complete information on population in the absence of a census.\n\nThe United Nations Statistics Division monitors the completeness of vital registration systems. Some developing countries have made progress over the last 60 years, but others still have deficiencies in civil registration systems.\n\nInternational migration is the only other factor besides birth and death rates that directly determines a country's population growth. Estimating migration is difficult. At any time many people are located outside their home country as tourists, workers, or refugees or for other reasons. Standards for the duration and purpose of international moves that qualify as migration vary, and estimates require information on flows into and out of countries that is difficult to collect.\n\nPopulation projections, starting from a base year are projected forward using assumptions of mortality, fertility, and migration by age and sex through 2050, based on the UN Population Division's World Population Prospects database medium variant.", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_totl_fe_in": { "title": "Population, female", "description_from_producer": "Female population is based on the de facto definition of population, which counts all female residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_totl_fe_zs": { "title": "Population, female (% of total population)", "description_from_producer": "Female population is the percentage of the population that is female. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.\n\nStatistical concept and methodology: Population structure by age and sex in the World Bank's estimates is based on the population structure by age and sex in United Nations Population Division's World Population Prospects. For more information, see the original source.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sp_pop_totl_ma_in": { "title": "Population, male", "description_from_producer": "Male population is based on the de facto definition of population, which counts all male residents regardless of legal status or citizenship.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_pop_totl_ma_zs": { "title": "Population, male (% of total population)", "description_from_producer": "Male population is the percentage of the population that is male. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.\n\nStatistical concept and methodology: Population structure by age and sex in the World Bank's estimates is based on the population structure by age and sex in United Nations Population Division's World Population Prospects. For more information, see the original source.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sp_reg_brth_fe_zs": { "title": "Completeness of birth registration, female (%)", "description_from_producer": "Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.\n\nLimitations and exceptions: Data on the prevalence of birth registration is collected mainly through censuses, civil registration systems (CRVS) and household surveys. Civil registration systems that are functioning effectively compile vital statistics that are used to compare the estimated total number of births in a country with the absolute number of registered births during a given period. However, the systematic recording of births in many countries remains a serious challenge. In the absence of reliable administrative data, household surveys have become a key source of data to monitor levels and trends in birth registration. In most low- and middle-income countries, such surveys represent the sole source of this information.\n\nSubstantial differences can exist between CRVS coverage and birth registration levels as captured by household surveys. The differences are primarily because data from CRVS typically refer to the percentage of all births that have been registered (often within a specific timeframe) whereas household surveys often represent the percentage of children under age five whose births are registered. The latter (the level of registration among children under 5) is specified in the SDG indicator (16.9).\n\nStatistical concept and methodology: Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.\n\nBirth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).", "origins": [ { "producer": "UNICEF", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sp_reg_brth_ma_zs": { "title": "Completeness of birth registration, male (%)", "description_from_producer": "Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.\n\nLimitations and exceptions: Data on the prevalence of birth registration is collected mainly through censuses, civil registration systems (CRVS) and household surveys. Civil registration systems that are functioning effectively compile vital statistics that are used to compare the estimated total number of births in a country with the absolute number of registered births during a given period. However, the systematic recording of births in many countries remains a serious challenge. In the absence of reliable administrative data, household surveys have become a key source of data to monitor levels and trends in birth registration. In most low- and middle-income countries, such surveys represent the sole source of this information.\n\nSubstantial differences can exist between CRVS coverage and birth registration levels as captured by household surveys. The differences are primarily because data from CRVS typically refer to the percentage of all births that have been registered (often within a specific timeframe) whereas household surveys often represent the percentage of children under age five whose births are registered. The latter (the level of registration among children under 5) is specified in the SDG indicator (16.9).\n\nStatistical concept and methodology: Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.\n\nBirth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).", "origins": [ { "producer": "UNICEF", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sp_reg_brth_ru_zs": { "title": "Completeness of birth registration, rural (%)", "description_from_producer": "Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.\n\nLimitations and exceptions: Data on the prevalence of birth registration is collected mainly through censuses, civil registration systems (CRVS) and household surveys. Civil registration systems that are functioning effectively compile vital statistics that are used to compare the estimated total number of births in a country with the absolute number of registered births during a given period. However, the systematic recording of births in many countries remains a serious challenge. In the absence of reliable administrative data, household surveys have become a key source of data to monitor levels and trends in birth registration. In most low- and middle-income countries, such surveys represent the sole source of this information.\n\nSubstantial differences can exist between CRVS coverage and birth registration levels as captured by household surveys. The differences are primarily because data from CRVS typically refer to the percentage of all births that have been registered (often within a specific timeframe) whereas household surveys often represent the percentage of children under age five whose births are registered. The latter (the level of registration among children under 5) is specified in the SDG indicator (16.9).\n\nStatistical concept and methodology: Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.\n\nBirth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).", "origins": [ { "producer": "UNICEF", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sp_reg_brth_ur_zs": { "title": "Completeness of birth registration, urban (%)", "description_from_producer": "Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.\n\nLimitations and exceptions: Data on the prevalence of birth registration is collected mainly through censuses, civil registration systems (CRVS) and household surveys. Civil registration systems that are functioning effectively compile vital statistics that are used to compare the estimated total number of births in a country with the absolute number of registered births during a given period. However, the systematic recording of births in many countries remains a serious challenge. In the absence of reliable administrative data, household surveys have become a key source of data to monitor levels and trends in birth registration. In most low- and middle-income countries, such surveys represent the sole source of this information.\n\nSubstantial differences can exist between CRVS coverage and birth registration levels as captured by household surveys. The differences are primarily because data from CRVS typically refer to the percentage of all births that have been registered (often within a specific timeframe) whereas household surveys often represent the percentage of children under age five whose births are registered. The latter (the level of registration among children under 5) is specified in the SDG indicator (16.9).\n\nStatistical concept and methodology: Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.\n\nBirth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).", "origins": [ { "producer": "UNICEF", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sp_reg_brth_zs": { "title": "Completeness of birth registration (%)", "description_from_producer": "Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.\n\nLimitations and exceptions: Data on the prevalence of birth registration is collected mainly through censuses, civil registration systems (CRVS) and household surveys. Civil registration systems that are functioning effectively compile vital statistics that are used to compare the estimated total number of births in a country with the absolute number of registered births during a given period. However, the systematic recording of births in many countries remains a serious challenge. In the absence of reliable administrative data, household surveys have become a key source of data to monitor levels and trends in birth registration. In most low- and middle-income countries, such surveys represent the sole source of this information.\n\nSubstantial differences can exist between CRVS coverage and birth registration levels as captured by household surveys. The differences are primarily because data from CRVS typically refer to the percentage of all births that have been registered (often within a specific timeframe) whereas household surveys often represent the percentage of children under age five whose births are registered. The latter (the level of registration among children under 5) is specified in the SDG indicator (16.9).\n\nStatistical concept and methodology: Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.\n\nBirth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).", "origins": [ { "producer": "UNICEF", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%", "display": { "numDecimalPlaces": 1 } }, "sp_reg_dths_zs": { "title": "Completeness of death registration with cause-of-death information (%)", "description_from_producer": "Completeness of death registration is the estimated percentage of deaths that are registered with their cause of death information in the vital registration system of a country.", "origins": [ { "producer": "World Health Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "sp_rur_totl": { "title": "Rural population", "description_from_producer": "Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.\n\nLimitations and exceptions: Aggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.\n\nEstimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers.\n\nBecause the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.\n\nStatistical concept and methodology: Rural population is calculated as the difference between the total population and the urban population. Rural population is approximated as the midyear nonurban population. While a practical means of identifying the rural population, it is not a precise measure.\n\nThe United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_rur_totl_zg": { "title": "Rural population growth (annual %)", "description_from_producer": "Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.\n\nLimitations and exceptions: Aggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.\n\nEstimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers.\n\nBecause the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.\n\nStatistical concept and methodology: Rural population is calculated as the difference between the total population and the urban population. Rural population is approximated as the midyear nonurban population. While a practical means of identifying the rural population, it is not a precise measure.\n\nThe United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "sp_rur_totl_zs": { "title": "Rural population (% of total population)", "description_from_producer": "Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.\n\nLimitations and exceptions: Aggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.\n\nEstimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers.\n\nBecause the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.\n\nStatistical concept and methodology: Rural population is calculated as the difference between the total population and the urban population. Rural population is approximated as the midyear nonurban population. While a practical means of identifying the rural population, it is not a precise measure.\n\nThe United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total population", "short_unit": "%" }, "sp_urb_grow": { "title": "Urban population growth (annual %)", "description_from_producer": "Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects.\n\nLimitations and exceptions: There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.\n\nMost countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries.\n\nEstimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers.\n\nBecause the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution.\n\nStatistical concept and methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" The population of a city or metropolitan area depends on the boundaries chosen.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "annual %", "short_unit": "%" }, "sp_urb_totl": { "title": "Urban population", "description_from_producer": "Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.\n\nLimitations and exceptions: Aggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.\n\nMost countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries.\n\nEstimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers.\n\nBecause the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution.\n\nStatistical concept and methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" The population of a city or metropolitan area depends on the boundaries chosen.", "origins": [ { "producer": "World Bank based on data from the UN Population Division", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "sp_urb_totl_in_zs": { "title": "Urban population (% of total population)", "description_from_producer": "Urban population refers to people living in urban areas as defined by national statistical offices. The data are collected and smoothed by United Nations Population Division.\n\nLimitations and exceptions: Aggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.\n\nMost countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries.\n\nEstimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers.\n\nBecause the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution.\n\nStatistical concept and methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects.\n\nPercentages urban are the numbers of persons residing in an area defined as ''urban'' per 100 total population. They are calculated by the Statistics Division of the United Nations Department of Economic and Social Affairs. Particular caution should be used in interpreting the figures for percentage urban for different countries.\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" The population of a city or metropolitan area depends on the boundaries chosen.", "origins": [ { "producer": "UN Population Division (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total", "short_unit": "%" }, "sp_uwt_tfrt": { "title": "Unmet need for contraception (% of married women ages 15-49)", "description_from_producer": "Unmet need for contraception is the percentage of fertile, married women of reproductive age who do not want to become pregnant and are not using contraception.\n\nStatistical concept and methodology: Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\n\nMany couples in developing countries want to limit or postpone childbearing but are not using effective contraception. These couples have an unmet need for contraception. Common reasons are lack of knowledge about contraceptive methods and concerns about possible side effects. This indicator excludes women not exposed to the risk of unintended pregnancy because of menopause, infertility, or postpartum anovulation.", "origins": [ { "producer": "Data compiled from multiple sources by World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of married women ages 15-49", "short_unit": "%" }, "st_int_arvl": { "title": "International tourism, number of arrivals", "description_from_producer": "International inbound tourists (overnight visitors) are the number of tourists who travel to a country other than that in which they have their usual residence, but outside their usual environment, for a period not exceeding 12 months and whose main purpose in visiting is other than an activity remunerated from within the country visited. When data on number of tourists are not available, the number of visitors, which includes tourists, same-day visitors, cruise passengers, and crew members, is shown instead. Sources and collection methods for arrivals differ across countries. In some cases data are from border statistics (police, immigration, and the like) and supplemented by border surveys. In other cases data are from tourism accommodation establishments. For some countries number of arrivals is limited to arrivals by air and for others to arrivals staying in hotels. Some countries include arrivals of nationals residing abroad while others do not. Caution should thus be used in comparing arrivals across countries. The data on inbound tourists refer to the number of arrivals, not to the number of people traveling. Thus a person who makes several trips to a country during a given period is counted each time as a new arrival.\n\nLimitations and exceptions: Tourism can be either domestic or international. The data refers to international tourism, where the traveler's country of residence differs from the visiting country. International tourism consists of inbound (arrival) and outbound (departures) tourism.\n\nThe data are from the World Tourism Organization (WTO), a United Nations agency. The data on inbound and outbound tourists refer to the number of arrivals and departures, not to the number of people traveling. Thus a person who makes several trips to a country during a given period is counted each time as a new arrival. The data on inbound tourism show the arrivals of nonresident tourists (overnight visitors) at national borders. When data on international tourists are unavailable or incomplete, the data show the arrivals of international visitors, which include tourists, same-day visitors, cruise passengers, and crew members.\n\nSources and collection methods for arrivals differ across countries. In some cases data are from border statistics (police, immigration, and the like) and supplemented by border surveys. In other cases data are from tourism accommodation establishments. For some countries number of arrivals is limited to arrivals by air and for others to arrivals staying in hotels. Some countries include arrivals of nationals residing abroad while others do not. Caution should thus be used in comparing arrivals across countries.\n\nStatistical concept and methodology: Statistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nArrivals data measure the flows of international visitors to the country of reference: each arrival corresponds to one in inbound tourism trip. If a person visits several countries during the course of a single trip, his/her arrival in each country is recorded separately. In an accounting period, arrivals are not necessarily equal to the number of persons travelling (when a person visits the same country several times a year, each trip by the same person is counted as a separate arrival).\n\nArrivals data should correspond to inbound visitors by including both tourists and same-day non-resident visitors. All other types of travelers (such as border, seasonal and other short-term workers, long-term students and others) should be excluded as they do not qualify as visitors.\n\nData are obtained from different sources: administrative records (immigration, traffic counts, and other possible types of controls), border surveys or a mix of them. If data are obtained from accommodation surveys, the number of guests is used as estimate of arrival figures; consequently, in this case, breakdowns by regions, main purpose of the trip, modes of transport used or forms of organization of the trip are based on complementary visitor surveys.", "origins": [ { "producer": "World Tourism Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "st_int_dprt": { "title": "International tourism, number of departures", "description_from_producer": "International outbound tourists are the number of departures that people make from their country of usual residence to any other country for any purpose other than a remunerated activity in the country visited. The data on outbound tourists refer to the number of departures, not to the number of people traveling. Thus a person who makes several trips from a country during a given period is counted each time as a new departure.\n\nLimitations and exceptions: Tourism can be either domestic or international. The data refers to international tourism, where the traveler's country of residence differs from the visiting country. International tourism consists of inbound (arrival) and outbound (departures) tourism.\n\nThe data are from the World Tourism Organization (WTO), a United Nations agency. The data on inbound and outbound tourists refer to the number of arrivals and departures, not to the number of people traveling.\n\nStatistical concept and methodology: Statistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nDepartures data measure the flows of resident visitors leaving the country of reference. Departures are not necessarily equal to the number of arrivals reported by international destinations for the country of reference.\n\nIn many countries, the characteristics of trips and visitors are established through questions on the entry/departure cards, in surveys at the borders, at destination (accommodation surveys) or as part of household surveys (for domestic and outbound tourism). The entry/departure cards, or records of entry and departure, captured and reconciled by the immigration authorities are often the basic source for establishing the flows of inbound and outbound visitors. These cards usually collect information on a census basis on name, sex, age, nationality, current address, date of arrival (or departure in the departure card), purpose of trip, main destination visited and length of stay (expected on arrival and actual on departure for inbound visitors; expected on departure and actual on arrival for outbound visitors).\n\nData is collected using one of three methods, or a combination of these to determine the flows of outbound visitors: using an entry/departure card; a specific survey at the border, or observing them from household surveys because they belong to resident households. In the latter case, the information on outbound trips is usually collected at the same time as that on domestic trips.", "origins": [ { "producer": "World Tourism Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "st_int_rcpt_cd": { "title": "International tourism, receipts (current US$)", "description_from_producer": "International tourism receipts are expenditures by international inbound visitors, including payments to national carriers for international transport. These receipts include any other prepayment made for goods or services received in the destination country. They also may include receipts from same-day visitors, except when these are important enough to justify separate classification. For some countries they do not include receipts for passenger transport items. Data are in current U.S. dollars.\n\nLimitations and exceptions: Tourism can be either domestic or international. The data refers to international tourism, where the traveler's country of residence differs from the visiting country. International tourism consists of inbound (arrival) and outbound (departures) tourism.\n\nThe data are from the World Tourism Organization (WTO), a United Nations agency. The data on inbound and outbound tourists refer to the number of arrivals and departures, not to the number of people traveling. Thus a person who makes several trips to a country during a given period is counted each time as a new arrival. The data on inbound tourism show the arrivals of nonresident tourists (overnight visitors) at national borders. When data on international tourists are unavailable or incomplete, the data show the arrivals of international visitors, which include tourists, same-day visitors, cruise passengers, and crew members.\n\nSources and collection methods for arrivals differ across countries. In some cases data are from border statistics (police, immigration, and the like) and supplemented by border surveys. In other cases data are from tourism accommodation establishments. For some countries number of arrivals is limited to arrivals by air and for others to arrivals staying in hotels. Some countries include arrivals of nationals residing abroad while others do not. Caution should thus be used in comparing arrivals across countries.\n\nExpenditure associated with the activity of international visitors has been traditionally identified with the travel item of the Balance of Payments (BOP): in the case of inbound tourism, those expenditures associated with inbound visitors are registered as \"credits\" in the BOP and refers to \"travel receipts\".\n\nThe 2008 International Recommendations for Tourism Statistics consider that \"tourism industries and products\" includes transport of passengers. Consequently, a better estimate of tourism-related expenditure by inbound and outbound visitors in an international scenario would be, in terms of the BOP, the value of the travel item plus that of the passenger transport item.\n\nNevertheless, users should be aware that BOP estimates include, in addition to expenditures associated to visitors, those related to other types of travelers (these might be substantial in some countries; for instance, long-term students or patients, border and seasonal workers, etc.). Also data on expenditure by main purpose of the trip are BOP data.\n\nStatistical concept and methodology: Inbound tourism expenditures may include receipts from same-day visitors, except when these are important enough to justify separate classification. For some countries they do not include receipts for passenger transport items. Their share in exports is calculated as a ratio to exports of goods and services (all transactions between residents of a country and the rest of the world involving a change of ownership from residents to nonresidents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services).\n\nStatistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization (WTO) reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nThe World Tourism Organization is improving its coverage of tourism expenditure data, using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. These data include travel and passenger transport items as defined in the IMF's Balance of Payments. When the IMF does not report data on passenger transport items, expenditure data for travel items are shown.\n\nThe aggregates are calculated using the World Bank's weighted aggregation methodology and differ from the World Tourism Organization's aggregates.", "origins": [ { "producer": "World Tourism Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "st_int_rcpt_xp_zs": { "title": "International tourism, receipts (% of total exports)", "description_from_producer": "International tourism receipts are expenditures by international inbound visitors, including payments to national carriers for international transport. These receipts include any other prepayment made for goods or services received in the destination country. They also may include receipts from same-day visitors, except when these are important enough to justify separate classification. For some countries they do not include receipts for passenger transport items. Their share in exports is calculated as a ratio to exports of goods and services, which comprise all transactions between residents of a country and the rest of the world involving a change of ownership from residents to nonresidents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services.\n\nLimitations and exceptions: Tourism can be either domestic or international. The data refers to international tourism, where the traveler's country of residence differs from the visiting country. International tourism consists of inbound (arrival) and outbound (departures) tourism.\n\nThe data are from the World Tourism Organization (WTO), a United Nations agency. The data on inbound and outbound tourists refer to the number of arrivals and departures, not to the number of people traveling. Thus a person who makes several trips to a country during a given period is counted each time as a new arrival. The data on inbound tourism show the arrivals of nonresident tourists (overnight visitors) at national borders. When data on international tourists are unavailable or incomplete, the data show the arrivals of international visitors, which include tourists, same-day visitors, cruise passengers, and crew members.\n\nSources and collection methods for arrivals differ across countries. In some cases data are from border statistics (police, immigration, and the like) and supplemented by border surveys. In other cases data are from tourism accommodation establishments. For some countries number of arrivals is limited to arrivals by air and for others to arrivals staying in hotels. Some countries include arrivals of nationals residing abroad while others do not. Caution should thus be used in comparing arrivals across countries.\n\nExpenditure associated with the activity of international visitors has been traditionally identified with the travel item of the Balance of Payments (BOP): in the case of inbound tourism, those expenditures associated with inbound visitors are registered as \"credits\" in the BOP and refers to \"travel receipts\".\n\nThe 2008 International Recommendations for Tourism Statistics consider that \"tourism industries and products\" includes transport of passengers. Consequently, a better estimate of tourism-related expenditure by inbound and outbound visitors in an international scenario would be, in terms of the BOP, the value of the travel item plus that of the passenger transport item.\n\nNevertheless, users should be aware that BOP estimates include, in addition to expenditures associated to visitors, those related to other types of travelers (these might be substantial in some countries; for instance, long-term students or patients, border and seasonal workers, etc.). Also data on expenditure by main purpose of the trip are BOP data.\n\nStatistical concept and methodology: Inbound tourism expenditures may include receipts from same-day visitors, except when these are important enough to justify separate classification. For some countries they do not include receipts for passenger transport items. Their share in exports is calculated as a ratio to exports of goods and services (all transactions between residents of a country and the rest of the world involving a change of ownership from residents to nonresidents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services).\n\nInternational tourism expenditures' share in exports is calculated as a ratio to exports of goods and services, which comprise all transactions between residents of a country and the rest of the world involving a change of ownership from residents to nonresidents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services.\n\nStatistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization (WTO) reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nThe World Tourism Organization is improving its coverage of tourism expenditure data, using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. These data include travel and passenger transport items as defined in the IMF's Balance of Payments. When the IMF does not report data on passenger transport items, expenditure data for travel items are shown.\n\nThe aggregates are calculated using the World Bank's weighted aggregation methodology and differ from the World Tourism Organization's aggregates.", "origins": [ { "producer": "World Tourism Organization, International Monetary Fund and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total exports", "short_unit": "%" }, "st_int_trnr_cd": { "title": "International tourism, receipts for passenger transport items (current US$)", "description_from_producer": "International tourism receipts for passenger transport items are expenditures by international inbound visitors for all services provided in the international transportation by resident carriers. Also included are passenger services performed within an economy by nonresident carriers. Excluded are passenger services provided to nonresidents by resident carriers within the resident economies; these are included in travel items. In addition to the services covered by passenger fares--including fares that are a part of package tours but excluding cruise fares, which are included in travel--passenger services include such items as charges for excess baggage, vehicles, or other personal accompanying effects and expenditures for food, drink, or other items for which passengers make expenditures while on board carriers. Data are in current U.S. dollars.", "origins": [ { "producer": "World Tourism Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "st_int_trnx_cd": { "title": "International tourism, expenditures for passenger transport items (current US$)", "description_from_producer": "International tourism expenditures for passenger transport items are expenditures of international outbound visitors in other countries for all services provided during international transportation by nonresident carriers. Also included are passenger services performed within an economy by nonresident carriers. Excluded are passenger services provided to nonresidents by resident carriers within the resident economies; these are included in travel items. In addition to the services covered by passenger fares--including fares that are a part of package tours but excluding cruise fares, which are included in travel--passenger services include such items as charges for excess baggage, vehicles, or other personal accompanying effects and expenditures for food, drink, or other items for which passengers make expenditures while on board carriers. Data are in current U.S. dollars.", "origins": [ { "producer": "World Tourism Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "st_int_tvlr_cd": { "title": "International tourism, receipts for travel items (current US$)", "description_from_producer": "International tourism receipts for travel items are expenditures by international inbound visitors in the reporting economy. The goods and services are purchased by, or on behalf of, the traveler or provided, without a quid pro quo, for the traveler to use or give away. These receipts should include any other prepayment made for goods or services received in the destination country. They also may include receipts from same-day visitors, except in cases where these are so important as to justify a separate classification. Excluded is the international carriage of travelers, which is covered in passenger travel items. Data are in current U.S. dollars.", "origins": [ { "producer": "World Tourism Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "st_int_tvlx_cd": { "title": "International tourism, expenditures for travel items (current US$)", "description_from_producer": "International tourism expenditures are expenditures of international outbound visitors in other countries. The goods and services are purchased by, or on behalf of, the traveler or provided, without a quid pro quo, for the traveler to use or give away. These may include expenditures by residents traveling abroad as same-day visitors, except in cases where these are so important as to justify a separate classification. Excluded is the international carriage of travelers, which is covered in passenger travel items. Data are in current U.S. dollars.", "origins": [ { "producer": "World Tourism Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "st_int_xpnd_cd": { "title": "International tourism, expenditures (current US$)", "description_from_producer": "International tourism expenditures are expenditures of international outbound visitors in other countries, including payments to foreign carriers for international transport. These expenditures may include those by residents traveling abroad as same-day visitors, except in cases where these are important enough to justify separate classification. For some countries they do not include expenditures for passenger transport items. Data are in current U.S. dollars.\n\nLimitations and exceptions: Tourism can be either domestic or international. The data refers to international tourism, where the traveler's country of residence differs from the visiting country. International tourism consists of inbound (arrival) and outbound (departures) tourism.\n\nThe data are from the World Tourism Organization (WTO), a United Nations agency. The data on inbound and outbound tourists refer to the number of arrivals and departures, not to the number of people traveling.\n\nExpenditure associated with the activity of international visitors has been traditionally identified with the travel item of the Balance of Payments (BOP).\n\nThe 2008 International Recommendations for Tourism Statistics consider that \"tourism industries and products\" includes transport of passengers. Consequently, a better estimate of tourism-related expenditure by inbound and outbound visitors in an international scenario would be, in terms of the BOP, the value of the travel item plus that of the passenger transport item.\n\nNevertheless, users should be aware that BOP estimates include, in addition to expenditures associated to visitors, those related to other types of travelers (these might be substantial in some countries; for instance, long-term students or patients, border and seasonal workers, etc.). Also data on expenditure by main purpose of the trip are BOP data.\n\nStatistical concept and methodology: Outbound tourism expenditures may include those by residents traveling abroad as same-day visitors, except when these are important enough to justify separate classification. For some countries they do not include expenditures for passenger transport items. Their share in imports is calculated as a ratio to imports of goods and services (all transactions between residents of a country and the rest of the world involving a change of ownership from nonresidents to residents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services).\n\nStatistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nThe World Tourism Organization is improving its coverage of tourism expenditure data, using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. These data include travel and passenger transport items as defined in the IMF's Balance of Payments. When the IMF does not report data on passenger transport items, expenditure data for travel items are shown.\n\nThe aggregates are calculated using the World Bank's weighted aggregation methodology and differ from the World Tourism Organization's aggregates.", "origins": [ { "producer": "World Tourism Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "st_int_xpnd_mp_zs": { "title": "International tourism, expenditures (% of total imports)", "description_from_producer": "International tourism expenditures are expenditures of international outbound visitors in other countries, including payments to foreign carriers for international transport. These expenditures may include those by residents traveling abroad as same-day visitors, except in cases where these are important enough to justify separate classification. For some countries they do not include expenditures for passenger transport items. Their share in imports is calculated as a ratio to imports of goods and services, which comprise all transactions between residents of a country and the rest of the world involving a change of ownership from nonresidents to residents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services.\n\nLimitations and exceptions: Tourism can be either domestic or international. The data refers to international tourism, where the traveler's country of residence differs from the visiting country. International tourism consists of inbound (arrival) and outbound (departures) tourism.\n\nThe data are from the World Tourism Organization (WTO), a United Nations agency. The data on inbound and outbound tourists refer to the number of arrivals and departures, not to the number of people traveling.\n\nExpenditure associated with the activity of international visitors has been traditionally identified with the travel item of the Balance of Payments (BOP).\n\nThe 2008 International Recommendations for Tourism Statistics consider that \"tourism industries and products\" includes transport of passengers. Consequently, a better estimate of tourism-related expenditure by inbound and outbound visitors in an international scenario would be, in terms of the BOP, the value of the travel item plus that of the passenger transport item.\n\nNevertheless, users should be aware that BOP estimates include, in addition to expenditures associated to visitors, those related to other types of travelers (these might be substantial in some countries; for instance, long-term students or patients, border and seasonal workers, etc.). Also data on expenditure by main purpose of the trip are BOP data.\n\nStatistical concept and methodology: Outbound tourism expenditures may include those by residents traveling abroad as same-day visitors, except when these are important enough to justify separate classification. For some countries they do not include expenditures for passenger transport items. Their share in imports is calculated as a ratio to imports of goods and services (all transactions between residents of a country and the rest of the world involving a change of ownership from nonresidents to residents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services).\n\nInternational tourism expenditures' share in imports is calculated as a ratio to imports of goods and services, which comprise all transactions between residents of a country and the rest of the world involving a change of ownership from nonresidents to residents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services.\n\nStatistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nThe World Tourism Organization is improving its coverage of tourism expenditure data, using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. These data include travel and passenger transport items as defined in the IMF's Balance of Payments. When the IMF does not report data on passenger transport items, expenditure data for travel items are shown.\n\nThe aggregates are calculated using the World Bank's weighted aggregation methodology and differ from the World Tourism Organization's aggregates.", "origins": [ { "producer": "World Tourism Organization, International Monetary Fund and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total imports", "short_unit": "%" }, "tg_val_totl_gd_zs": { "title": "Merchandise trade (% of GDP)", "description_from_producer": "Merchandise trade as a share of GDP is the sum of merchandise exports and imports divided by the value of GDP, all in current U.S. dollars.", "origins": [ { "producer": "World Trade Organization and World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "tm_qty_mrch_xd_wd": { "title": "Import volume index (2015 = 100)", "description_from_producer": "Import volume indexes are derived from UNCTAD's volume index series and are the ratio of the import value indexes to the corresponding unit value indexes. Unit value indexes are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD's estimates using the previous year's trade values at the Standard International Trade Classification three-digit level as weights.", "origins": [ { "producer": "United Nations Conference on Trade and Development", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2015 = 100" }, "tm_tax_manf_bc_zs": { "title": "Binding coverage, manufactured products (%)", "description_from_producer": "Binding coverage is the percentage of product lines with an agreed bound rate. Bound rates result from trade negotiations incorporated into a country's schedule of concessions and are thus enforceable. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "tm_tax_manf_br_zs": { "title": "Bound rate, simple mean, manufactured products (%)", "description_from_producer": "Simple mean bound rate is the unweighted average of all the lines in the tariff schedule in which bound rates have been set. Bound rates result from trade negotiations incorporated into a country's schedule of concessions and are thus enforceable. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "tm_tax_manf_ip_zs": { "title": "Share of tariff lines with international peaks, manufactured products (%)", "description_from_producer": "Share of tariff lines with international peaks is the share of lines in the tariff schedule with tariff rates that exceed 15 percent. It provides an indication of how selectively tariffs are applied. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. 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Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of weighted mean tariffs. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. Primary products are commodities classified in SITC revision 3 sections 0-4 plus division 68 (nonferrous metals).", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "tm_tax_tcom_wm_fn_zs": { "title": "Tariff rate, most favored nation, weighted mean, primary products (%)", "description_from_producer": "Weighted mean most favored nations tariff is the average of most favored nation rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Primary products are commodities classified in SITC revision 3 sections 0-4 plus division 68 (nonferrous metals).", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%" }, "tm_uvi_mrch_xd_wd": { "title": "Import unit value index (2015 = 100)", "description_from_producer": "Import unit value indices come from UNCTAD's trade database. Unit value indices are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD\u2019s estimates using the previous year\u2019s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD\u2019s Commodity Price Statistics, interna\u00actional and national sources, and UNCTAD secretariat estimates.", "origins": [ { "producer": "UN Conference on Trade and Development (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2015 = 100" }, "tm_val_agri_zs_un": { "title": "Agricultural raw materials imports (% of merchandise imports)", "description_from_producer": "Agricultural raw materials comprise SITC section 2 (crude materials except fuels) excluding divisions 22, 27 (crude fertilizers and minerals excluding coal, petroleum, and precious stones), and 28 (metalliferous ores and scrap).\n\nLimitations and exceptions: Previous editions contained data based on the SITC revision 1. Data for earlier years in previous editions may differ because of the change in methodology. Concordance tables are available to convert data reported in one system to another.\n\nStatistical concept and methodology: The classification of commodity groups is based on the Standard International Trade Classification (SITC) revision 3.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of merchandise imports", "short_unit": "%" }, "tm_val_food_zs_un": { "title": "Food imports (% of merchandise imports)", "description_from_producer": "Food comprises the commodities in SITC sections 0 (food and live animals), 1 (beverages and tobacco), and 4 (animal and vegetable oils and fats) and SITC division 22 (oil seeds, oil nuts, and oil kernels).\n\nLimitations and exceptions: Previous editions contained data based on the SITC revision 1. Data for earlier years in previous editions may differ because of the change in methodology. Concordance tables are available to convert data reported in one system to another.\n\nStatistical concept and methodology: The classification of commodity groups is based on the Standard International Trade Classification (SITC) revision 3.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of merchandise imports", "short_unit": "%" }, "tm_val_fuel_zs_un": { "title": "Fuel imports (% of merchandise imports)", "description_from_producer": "Fuels comprise the commodities in SITC section 3 (mineral fuels, lubricants and related materials).\n\nLimitations and exceptions: Previous editions contained data based on the SITC revision 1. Data for earlier years in previous editions may differ because of the change in methodology. Concordance tables are available to convert data reported in one system to another.\n\nStatistical concept and methodology: The classification of commodity groups is based on the Standard International Trade Classification (SITC) revision 3.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of merchandise imports", "short_unit": "%" }, "tm_val_ictg_zs_un": { "title": "ICT goods imports (% total goods imports)", "description_from_producer": "Information and communication technology goods imports include computers and peripheral equipment, communication equipment, consumer electronic equipment, electronic components, and other information and technology goods (miscellaneous).\n\nLimitations and exceptions: Detailed trade data are widely available from country trade statistics. These are collected by the UNSD and published in their UN COMTRADE database. The ICT goods trade indicators are usually compiled by interested international and national agencies using COMTRADE data. Concepts are therefore consistent with those applying to the COMTRADE database.\n\nThe main statistical issue associated with this indicator appears to be the different treatment of re-exports and re-imports by countries, depending on whether the Special or General Trade System is used.2 Re-imports are separately reported for some countries and the value of ICT re-imports (which is included in the value of ICT imports for those countries) is generally small.\n\nStatistical concept and methodology: Information and communication technology goods imports include computers and peripheral equipment, communication equipment, consumer electronic equipment, electronic components, and other information and technology goods (miscellaneous). Software is generally excluded, as there is a preference to record it under services (not an ICT good but an ICT product) to the extent possible. However it is hard to completely exclude embedded software from certain types of ICT goods, such as video game consoles (see for example the discussion on page 30 of the OECD guide cited below). ICT goods imports as a percentage of total imports is calculated for each country by dividing the value of its ICT goods imports by the total value of its goods imports. The result is then multiplied by 100 to be expressed as a percentage.\n\nICT goods are defined according to the OECD\u2019s Guide on Measuring the Information Society 2011 for Harmonized System (HS) 2007 and adapted to HS12 by UNCTAD in collaboration with UNSD (United Nations Statistics Division). This new list consists of 93 goods defined at the 6 digit level of the 2012 version of the HS. The technical note is available online at: http://unctad.org/en/PublicationsLibrary/tn_unctad_ict4d02_en.pdf\nData were downloaded from COMTRADE according to the reported classification (HS92, 96, 02, 07, 12) and aggregated into ICT groups by UNCTAD.", "origins": [ { "producer": "UN Conference on Trade and Development (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% total goods imports", "short_unit": "%" }, "tm_val_insf_zs_wt": { "title": "Insurance and financial services (% of commercial service imports)", "description_from_producer": "Insurance and financial services cover freight insurance on goods imported and other direct insurance such as life insurance; financial intermediation services such as commissions, foreign exchange transactions, and brokerage services; and auxiliary services such as financial market operational and regulatory services.\n\nLimitations and exceptions: Balance of payments statistics, the main source of information on international trade in services, have many weaknesses. Disaggregation of important components may be limited and varies considerably across countries. There are inconsistencies in the methods used to report items. And the recording of major flows as net items is common (for example, insurance transactions are often recorded as premiums less claims). These factors contribute to a downward bias in the value of the service trade reported in the balance of payments.\n\nEfforts are being made to improve the coverage, quality, and consistency of these data. Eurostat and the Organisation for Economic Co-operation and Development, for example, are working together to improve the collection of statistics on trade in services in member countries.\n\nStill, difficulties in capturing all the dimensions of international trade in services mean that the record is likely to remain incomplete. Cross-border intrafirm service transactions, which are usually not captured in the balance of payments, have increased in recent years. An example is transnational corporations' use of mainframe computers around the clock for data processing, exploiting time zone differences between their home country and the host countries of their affiliates. Another important dimension of service trade not captured by conventional balance of payments statistics is establishment trade - sales in the host country by foreign affiliates. By contrast, cross-border intrafirm transactions in merchandise may be reported as exports or imports in the balance of payments.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial service imports", "short_unit": "%" }, "tm_val_manf_zs_un": { "title": "Manufactures imports (% of merchandise imports)", "description_from_producer": "Manufactures comprise the commodities in SITC sections 5 (chemicals), 6 (basic manufactures), 7 (machinery and transport equipment), and 8 (miscellaneous manufactured goods), excluding division 68 (nonferrous metals).\n\nLimitations and exceptions: Previous editions contained data based on the SITC revision 1. Data for earlier years in previous editions may differ because of the change in methodology. Concordance tables are available to convert data reported in one system to another.\n\nStatistical concept and methodology: The classification of commodity groups is based on the Standard International Trade Classification (SITC) revision 3.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of merchandise imports", "short_unit": "%" }, "tm_val_mmtl_zs_un": { "title": "Ores and metals imports (% of merchandise imports)", "description_from_producer": "Ores and metals comprise commodities in SITC sections 27 (crude fertilizer, minerals nes); 28 (metalliferous ores, scrap); and 68 (non-ferrous metals).\n\nLimitations and exceptions: Previous editions contained data based on the SITC revision 1. Data for earlier years in previous editions may differ because of the change in methodology. Concordance tables are available to convert data reported in one system to another.\n\nStatistical concept and methodology: The classification of commodity groups is based on the Standard International Trade Classification (SITC) revision 3.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of merchandise imports", "short_unit": "%" }, "tm_val_mrch_al_zs": { "title": "Merchandise imports from economies in the Arab World (% of total merchandise imports)", "description_from_producer": "Merchandise imports from economies in the Arab World are the sum of merchandise imports by the reporting economy from economies in the Arab World. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_cd_wt": { "title": "Merchandise imports (current US$)", "description_from_producer": "Merchandise imports show the c.i.f. value of goods received from the rest of the world valued in current U.S. dollars.\n\nLimitations and exceptions: The value of imports is generally recorded as the cost of the goods when purchased by the importer plus the cost of transport and insurance to the frontier of the importing country - the cost, insurance, and freight (c.i.f.) value, corresponding to the landed cost at the point of entry of foreign goods into the country. A few countries collect import data on a free on board (f.o.b.) basis and adjust them for freight and insurance costs.\n\nCountries may report trade according to the general or special system of trade. Under the general system imports include goods imported for domestic consumption and imports into bonded warehouses and free trade zones. Under the special system imports comprise goods imported for domestic consumption (including transformation and repair) and withdrawals for domestic consumption from bonded warehouses and free trade zones. Goods transported through a country en route to another are excluded.\n\nData on imports of goods are derived from the same sources as data on exports. In principle, world exports and imports should be identical. Similarly, exports from an economy should equal the sum of imports by the rest of the world from that economy. But differences in timing and definitions result in discrepancies in reported values at all levels.\n\nStatistical concept and methodology: Merchandise trade data are from customs reports of goods moving into or out of an economy or from reports of financial transactions related to merchandise trade recorded in the balance of payments. Because of differences in timing and definitions, trade flow estimates from customs reports and balance of payments may differ. Several international agencies process trade data, each correcting unreported or misreported data, leading to other differences.\n\nThe data on total imports of goods (merchandise) are from the World Trade Organization (WTO), which obtains data from national statistical offices and the IMF's International Financial Statistics, supplemented by the Comtrade database and publications or databases of regional organizations, specialized agencies, economic groups, and private sources (such as Eurostat, the Food and Agriculture Organization, and country reports of the Economist Intelligence Unit). Country websites and email contact have improved collection of up-to-date statistics, reducing the proportion of estimates. The WTO database now covers most major traders in Africa, Asia, and Latin America, which together with high-income countries account for nearly 95 percent of world trade. Reliability of data for countries in Europe and Central Asia has also improved.", "origins": [ { "producer": "World Trade Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "tm_val_mrch_hi_zs": { "title": "Merchandise imports from high-income economies (% of total merchandise imports)", "description_from_producer": "Merchandise imports from high-income economies are the sum of merchandise imports by the reporting economy from high-income economies according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.\n\nLimitations and exceptions: Data on exports and imports are from the International Monetary Fund's (IMF) Direction of Trade database and should be broadly consistent with data from other sources, such as the United Nations Statistics Division's Commodity Trade (Comtrade) database. All high-income economies and major low- and middle-income economies report trade data to the IMF on a timely basis, covering about 85 percent of trade for recent years. Trade data for less timely reporters and for countries that do not report are estimated using reports of trading partner countries. Therefore, data on trade between developing and high-income economies should be generally complete. But trade flows between many low- and middle-income economies - particularly those in Sub-Saharan Africa - are not well recorded, and the value of trade among low- and middle-income economies may be understated.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_or_zs": { "title": "Merchandise imports from low- and middle-income economies outside region (% of total merchandise imports)", "description_from_producer": "Merchandise imports from low- and middle-income economies outside region are the sum of merchandise imports by the reporting economy from other low- and middle-income economies in other World Bank regions according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.\n\nLimitations and exceptions: Data on exports and imports are from the International Monetary Fund's (IMF) Direction of Trade database and should be broadly consistent with data from other sources, such as the United Nations Statistics Division's Commodity Trade (Comtrade) database. All high-income economies and major low- and middle-income economies report trade data to the IMF on a timely basis, covering about 85 percent of trade for recent years. Trade data for less timely reporters and for countries that do not report are estimated using reports of trading partner countries. Therefore, data on trade between developing and high-income economies should be generally complete. But trade flows between many low- and middle-income economies - particularly those in Sub-Saharan Africa - are not well recorded, and the value of trade among low- and middle-income economies may be understated.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_r1_zs": { "title": "Merchandise imports from low- and middle-income economies in East Asia & Pacific (% of total merchandise imports)", "description_from_producer": "Merchandise imports from low- and middle-income economies in East Asia and Pacific are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the East Asia and Pacific region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_r2_zs": { "title": "Merchandise imports from low- and middle-income economies in Europe & Central Asia (% of total merchandise imports)", "description_from_producer": "Merchandise imports from low- and middle-income economies in Europe and Central Asia are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Europe and Central Asia region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_r3_zs": { "title": "Merchandise imports from low- and middle-income economies in Latin America & the Caribbean (% of total merchandise imports)", "description_from_producer": "Merchandise imports from low- and middle-income economies in Latin America and the Caribbean are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Latin America and the Caribbean region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_r4_zs": { "title": "Merchandise imports from low- and middle-income economies in Middle East & North Africa (% of total merchandise imports)", "description_from_producer": "Merchandise imports from low- and middle-income economies in Middle East and North Africa are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Middle East and North Africa region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_r5_zs": { "title": "Merchandise imports from low- and middle-income economies in South Asia (% of total merchandise imports)", "description_from_producer": "Merchandise imports from low- and middle-income economies in South Asia are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the South Asia region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_r6_zs": { "title": "Merchandise imports from low- and middle-income economies in Sub-Saharan Africa (% of total merchandise imports)", "description_from_producer": "Merchandise imports from low- and middle-income economies in Sub-Saharan Africa are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Sub-Saharan Africa region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_rs_zs": { "title": "Merchandise imports by the reporting economy, residual (% of total merchandise imports)", "description_from_producer": "Merchandise imports by the reporting economy residuals are the total merchandise imports by the reporting economy from the rest of the world as reported in the IMF's Direction of trade database, less the sum of imports by the reporting economy from high-, low-, and middle-income economies according to the World Bank classification of economies. Includes trade with unspecified partners or with economies not covered by World Bank classification. Data are as a percentage of total merchandise imports by the economy.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_wl_cd": { "title": "Merchandise imports by the reporting economy (current US$)", "description_from_producer": "Merchandise imports by the reporting economy are the total merchandise imports by the reporting economy from the rest of the world, as reported in the IMF's Direction of trade database. Data are in current U.S. dollars.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "tm_val_mrch_wr_zs": { "title": "Merchandise imports from low- and middle-income economies within region (% of total merchandise imports)", "description_from_producer": "Merchandise imports from low- and middle-income economies within region are the sum of merchandise imports by the reporting economy from other low- and middle-income economies in the same World Bank region according to the World Bank classification of economies. Data are as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data. No figures are shown for high-income economies, because they are a separate category in the World Bank classification of economies.\n\nLimitations and exceptions: Data on exports and imports are from the International Monetary Fund's (IMF) Direction of Trade database and should be broadly consistent with data from other sources, such as the United Nations Statistics Division's Commodity Trade (Comtrade) database. All high-income economies and major low- and middle-income economies report trade data to the IMF on a timely basis, covering about 85 percent of trade for recent years. Trade data for less timely reporters and for countries that do not report are estimated using reports of trading partner countries. Therefore, data on trade between developing and high-income economies should be generally complete. But trade flows between many low- and middle-income economies - particularly those in Sub-Saharan Africa - are not well recorded, and the value of trade among low- and middle-income economies may be understated.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise imports", "short_unit": "%" }, "tm_val_mrch_xd_wd": { "title": "Import value index (2015 = 100)", "description_from_producer": "Import value indexes are the current value of imports (c.i.f.) converted to U.S. dollars and expressed as a percentage of the average for the base period (2015). UNCTAD's import value indexes are reported for most economies.", "origins": [ { "producer": "United Nations Conference on Trade and Development", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2015 = 100" }, "tm_val_othr_zs_wt": { "title": "Computer, communications and other services (% of commercial service imports)", "description_from_producer": "Computer, communications and other services (% of commercial service imports) include such activities as international telecommunications, and postal and courier services; computer data; news-related service transactions between residents and nonresidents; construction services; royalties and license fees; miscellaneous business, professional, and technical services; and personal, cultural, and recreational services.\n\nLimitations and exceptions: Balance of payments statistics, the main source of information on international trade in services, have many weaknesses. Disaggregation of important components may be limited and varies considerably across countries. There are inconsistencies in the methods used to report items. And the recording of major flows as net items is common (for example, insurance transactions are often recorded as premiums less claims). These factors contribute to a downward bias in the value of the service trade reported in the balance of payments.\n\nEfforts are being made to improve the coverage, quality, and consistency of these data. Eurostat and the Organisation for Economic Co-operation and Development, for example, are working together to improve the collection of statistics on trade in services in member countries.\n\nStill, difficulties in capturing all the dimensions of international trade in services mean that the record is likely to remain incomplete. Cross-border intrafirm service transactions, which are usually not captured in the balance of payments, have increased in recent years. An example is transnational corporations' use of mainframe computers around the clock for data processing, exploiting time zone differences between their home country and the host countries of their affiliates. Another important dimension of service trade not captured by conventional balance of payments statistics is establishment trade - sales in the host country by foreign affiliates. By contrast, cross-border intrafirm transactions in merchandise may be reported as exports or imports in the balance of payments.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial service imports", "short_unit": "%" }, "tm_val_serv_cd_wt": { "title": "Commercial service imports (current US$)", "description_from_producer": "Commercial service imports are total service imports minus imports of government services not included elsewhere. International transactions in services are defined by the IMF's Balance of Payments Manual (1993) as the economic output of intangible commodities that may be produced, transferred, and consumed at the same time. Definitions may vary among reporting economies.\n\nLimitations and exceptions: Balance of payments statistics, the main source of information on international trade in services, have many weaknesses. Disaggregation of important components may be limited and varies considerably across countries. There are inconsistencies in the methods used to report items. And the recording of major flows as net items is common (for example, insurance transactions are often recorded as premiums less claims). These factors contribute to a downward bias in the value of the service trade reported in the balance of payments.\n\nEfforts are being made to improve the coverage, quality, and consistency of these data. Eurostat and the Organisation for Economic Co-operation and Development, for example, are working together to improve the collection of statistics on trade in services in member countries.\n\nStill, difficulties in capturing all the dimensions of international trade in services mean that the record is likely to remain incomplete. Cross-border intrafirm service transactions, which are usually not captured in the balance of payments, have increased in recent years. An example is transnational corporations' use of mainframe computers around the clock for data processing, exploiting time zone differences between their home country and the host countries of their affiliates. Another important dimension of service trade not captured by conventional balance of payments statistics is establishment trade - sales in the host country by foreign affiliates. By contrast, cross-border intrafirm transactions in merchandise may be reported as exports or imports in the balance of payments.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "tm_val_tran_zs_wt": { "title": "Transport services (% of commercial service imports)", "description_from_producer": "Transport services (% of commercial service imports) covers all transport services (sea, air, land, internal waterway, space, and pipeline) performed by residents of one economy for those of another and involving the carriage of passengers, movement of goods (freight), rental of carriers with crew, and related support and auxiliary services. Excluded are freight insurance, which is included in insurance services; goods procured in ports by nonresident carriers and repairs of transport equipment, which are included in goods; repairs of railway facilities, harbors, and airfield facilities, which are included in construction services; and rental of carriers without crew, which is included in other services.\n\nLimitations and exceptions: Balance of payments statistics, the main source of information on international trade in services, have many weaknesses. Disaggregation of important components may be limited and varies considerably across countries. There are inconsistencies in the methods used to report items. And the recording of major flows as net items is common (for example, insurance transactions are often recorded as premiums less claims). These factors contribute to a downward bias in the value of the service trade reported in the balance of payments.\n\nEfforts are being made to improve the coverage, quality, and consistency of these data. Eurostat and the Organisation for Economic Co-operation and Development, for example, are working together to improve the collection of statistics on trade in services in member countries.\n\nStill, difficulties in capturing all the dimensions of international trade in services mean that the record is likely to remain incomplete. Cross-border intrafirm service transactions, which are usually not captured in the balance of payments, have increased in recent years. An example is transnational corporations' use of mainframe computers around the clock for data processing, exploiting time zone differences between their home country and the host countries of their affiliates. Another important dimension of service trade not captured by conventional balance of payments statistics is establishment trade - sales in the host country by foreign affiliates. By contrast, cross-border intrafirm transactions in merchandise may be reported as exports or imports in the balance of payments.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial service imports", "short_unit": "%" }, "tm_val_trvl_zs_wt": { "title": "Travel services (% of commercial service imports)", "description_from_producer": "Travel services (% of commercial service imports) covers goods and services acquired from an economy by travelers in that economy for their own use during visits of less than one year for business or personal purposes. Travel services include the goods and services consumed by travelers, such as lodging, meals, and transport (within the economy visited).\n\nLimitations and exceptions: Balance of payments statistics, the main source of information on international trade in services, have many weaknesses. Disaggregation of important components may be limited and varies considerably across countries. There are inconsistencies in the methods used to report items. And the recording of major flows as net items is common (for example, insurance transactions are often recorded as premiums less claims). These factors contribute to a downward bias in the value of the service trade reported in the balance of payments.\n\nEfforts are being made to improve the coverage, quality, and consistency of these data. Eurostat and the Organisation for Economic Co-operation and Development, for example, are working together to improve the collection of statistics on trade in services in member countries.\n\nStill, difficulties in capturing all the dimensions of international trade in services mean that the record is likely to remain incomplete. Cross-border intrafirm service transactions, which are usually not captured in the balance of payments, have increased in recent years. An example is transnational corporations' use of mainframe computers around the clock for data processing, exploiting time zone differences between their home country and the host countries of their affiliates. Another important dimension of service trade not captured by conventional balance of payments statistics is establishment trade - sales in the host country by foreign affiliates. By contrast, cross-border intrafirm transactions in merchandise may be reported as exports or imports in the balance of payments.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial service imports", "short_unit": "%" }, "tt_pri_mrch_xd_wd": { "title": "Net barter terms of trade index (2015 = 100)", "description_from_producer": "Net barter terms of trade index is calculated as the percentage ratio of the export unit value indexes to the import unit value indexes, measured relative to the base year 2015.", "origins": [ { "producer": "United Nations Conference on Trade and Development", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2015 = 100" }, "tx_mnf_tech_zs_un": { "title": "Medium and high-tech exports (% manufactured exports)", "description_from_producer": "Share of medium and high-tech manufactured exports in total manufactured exports.\n\nLimitations and exceptions: Missing values at country level are imputed based on the methodology from Competitive Industrial Performance Report (UNIDO, 2017).\n\nStatistical concept and methodology: The data from UN COMTRADE is downloaded in SITC Revision 3, 3-digit, by reporting country, year, partner code, commodity and flow (export and re-export). SITC medium technology: 266, 267, 512, 513, 533, 553, 554, 562, 571, 572, 573, 574, 575, 579, 581, 582, 583, 591, 593, 597, 598, 653, 671, 672, 678, 711, 712,713, 714, 721, 722, 723, 724, 725, 726, 727, 728, 731, 733, 735, 737, 741, 742, 743, 744, 745, 746, 747, 748, 749, 761, 762, 763, 772, 773, 775, 778, 781, 782, 783, 784, 785, 786, 791, 793, 811, 812, 813, 872, 873, 882, 884, 885; SITC high technology: 525, 541, 542, 716, 718, 751, 752, 759, 764, 771, 774, 776, 792, 871, 874, 881, 891. Net-exports are calculated as exports minus re-exports. Manufactured exports, is the sum of the four categories resource-based exports, low-tech exports, medium tech exports and high-tech exports; and medium-high technology exports, is the sum of medium tech exports and high-tech exports. The world value of manufacturing exports is the sum of all manufacturing net exports. For additional information please see Table B.2.1 in Appendix B of UNIDO (2017): http://stat.unido.org/content/publications/volume-i%252c-competitive-industrial-performance-report-2016", "origins": [ { "producer": "UN Industrial Development Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% manufactured exports", "short_unit": "%" }, "tx_qty_mrch_xd_wd": { "title": "Export volume index (2015 = 100)", "description_from_producer": "Export volume indexes are derived from UNCTAD's volume index series and are the ratio of the export value indexes to the corresponding unit value indexes. Unit value indexes are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD's estimates using the previous year's trade values at the Standard International Trade Classification three-digit level as weights.", "origins": [ { "producer": "United Nations Conference on Trade and Development", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2015 = 100" }, "tx_uvi_mrch_xd_wd": { "title": "Export unit value index (2015 = 100)", "description_from_producer": "Export unit value indices come from UNCTAD's trade database. Unit value indices are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD\u2019s estimates using the previous year\u2019s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD\u2019s Commodity Price Statistics, interna\u00actional and national sources, and UNCTAD secretariat estimates.", "origins": [ { "producer": "UN Conference on Trade and Development (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2015 = 100" }, "tx_val_agri_zs_un": { "title": "Agricultural raw materials exports (% of merchandise exports)", "description_from_producer": "Agricultural raw materials comprise SITC section 2 (crude materials except fuels) excluding divisions 22, 27 (crude fertilizers and minerals excluding coal, petroleum, and precious stones), and 28 (metalliferous ores and scrap).\n\nLimitations and exceptions: Previous editions contained data based on the SITC revision 1. Data for earlier years in previous editions may differ because of the change in methodology. Concordance tables are available to convert data reported in one system to another.\n\nStatistical concept and methodology: The classification of commodity groups is based on the Standard International Trade Classification (SITC) revision 3.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of merchandise exports", "short_unit": "%" }, "tx_val_food_zs_un": { "title": "Food exports (% of merchandise exports)", "description_from_producer": "Food comprises the commodities in SITC sections 0 (food and live animals), 1 (beverages and tobacco), and 4 (animal and vegetable oils and fats) and SITC division 22 (oil seeds, oil nuts, and oil kernels).\n\nLimitations and exceptions: Previous editions contained data based on the SITC revision 1. Data for earlier years in previous editions may differ because of the change in methodology. Concordance tables are available to convert data reported in one system to another.\n\nStatistical concept and methodology: The classification of commodity groups is based on the Standard International Trade Classification (SITC) revision 3.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of merchandise exports", "short_unit": "%" }, "tx_val_fuel_zs_un": { "title": "Fuel exports (% of merchandise exports)", "description_from_producer": "Fuels comprise the commodities in SITC section 3 (mineral fuels, lubricants and related materials).\n\nLimitations and exceptions: Previous editions contained data based on the SITC revision 1. Data for earlier years in previous editions may differ because of the change in methodology. Concordance tables are available to convert data reported in one system to another.\n\nStatistical concept and methodology: The classification of commodity groups is based on the Standard International Trade Classification (SITC) revision 3.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of merchandise exports", "short_unit": "%" }, "tx_val_ictg_zs_un": { "title": "ICT goods exports (% of total goods exports)", "description_from_producer": "Information and communication technology goods exports include computers and peripheral equipment, communication equipment, consumer electronic equipment, electronic components, and other information and technology goods (miscellaneous).\n\nLimitations and exceptions: Detailed trade data are widely available from country trade statistics. These are collected by the UNSD and published in their UN COMTRADE database. The ICT goods trade indicators are usually compiled by interested international and national agencies using COMTRADE data. Concepts are therefore consistent with those applying to the COMTRADE database.\n\nThe main statistical issue associated with this indicator appears to be the different treatment of re-exports and re-imports by countries, depending on whether the Special or General Trade System is used.2 Re-imports are separately reported for some countries and the value of ICT re-imports (which is included in the value of ICT imports for those countries) is generally small.\n\nStatistical concept and methodology: Information and communication technology goods exports include computers and peripheral equipment, communication equipment, consumer electronic equipment, electronic components, and other information and technology goods (miscellaneous). Software is generally excluded, as there is a preference to record it under services (not an ICT good but an ICT product) to the extent possible. However it is hard to completely exclude embedded software from certain types of ICT goods, such as video game consoles (see for example the discussion on page 30 of the OECD guide cited below). ICT goods exports as a percentage of total goods exports is calculated for each country by dividing the value of its ICT goods exports by the total value of its goods exports. The result is then multiplied by 100 to be expressed as a percentage.\n\nICT goods are defined according to the OECD\u2019s Guide on Measuring the Information Society 2011 for Harmonized System (HS) 2007 and adapted to HS12 by UNCTAD in collaboration with UNSD (United Nations Statistics Division). This new list consists of 93 goods defined at the 6 digit level of the 2012 version of the HS. The technical note is available online at: http://unctad.org/en/PublicationsLibrary/tn_unctad_ict4d02_en.pdf\nData were downloaded from COMTRADE according to the reported classification (HS92, 96, 02, 07, 12) and aggregated into ICT groups by UNCTAD.", "origins": [ { "producer": "UN Conference on Trade and Development (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total goods exports", "short_unit": "%" }, "tx_val_insf_zs_wt": { "title": "Insurance and financial services (% of commercial service exports)", "description_from_producer": "Insurance and financial services cover freight insurance on goods exported and other direct insurance such as life insurance; financial intermediation services such as commissions, foreign exchange transactions, and brokerage services; and auxiliary services such as financial market operational and regulatory services.\n\nLimitations and exceptions: Balance of payments statistics, the main source of information on international trade in services, have many weaknesses. Disaggregation of important components may be limited and varies considerably across countries. There are inconsistencies in the methods used to report items. And the recording of major flows as net items is common (for example, insurance transactions are often recorded as premiums less claims). These factors contribute to a downward bias in the value of the service trade reported in the balance of payments.\n\nEfforts are being made to improve the coverage, quality, and consistency of these data. Eurostat and the Organisation for Economic Co-operation and Development, for example, are working together to improve the collection of statistics on trade in services in member countries.\n\nStill, difficulties in capturing all the dimensions of international trade in services mean that the record is likely to remain incomplete. Cross-border intrafirm service transactions, which are usually not captured in the balance of payments, have increased in recent years. An example is transnational corporations' use of mainframe computers around the clock for data processing, exploiting time zone differences between their home country and the host countries of their affiliates. Another important dimension of service trade not captured by conventional balance of payments statistics is establishment trade - sales in the host country by foreign affiliates. By contrast, cross-border intrafirm transactions in merchandise may be reported as exports or imports in the balance of payments.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial service exports", "short_unit": "%" }, "tx_val_manf_zs_un": { "title": "Manufactures exports (% of merchandise exports)", "description_from_producer": "Manufactures comprise commodities in SITC sections 5 (chemicals), 6 (basic manufactures), 7 (machinery and transport equipment), and 8 (miscellaneous manufactured goods), excluding division 68 (non-ferrous metals).\n\nLimitations and exceptions: Previous editions contained data based on the SITC revision 1. Data for earlier years in previous editions may differ because of the change in methodology. Concordance tables are available to convert data reported in one system to another.\n\nStatistical concept and methodology: The classification of commodity groups is based on the Standard International Trade Classification (SITC) revision 3.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of merchandise exports", "short_unit": "%" }, "tx_val_mmtl_zs_un": { "title": "Ores and metals exports (% of merchandise exports)", "description_from_producer": "Ores and metals comprise the commodities in SITC sections 27 (crude fertilizer, minerals nes); 28 (metalliferous ores, scrap); and 68 (non-ferrous metals).\n\nLimitations and exceptions: Previous editions contained data based on the SITC revision 1. Data for earlier years in previous editions may differ because of the change in methodology. Concordance tables are available to convert data reported in one system to another.\n\nStatistical concept and methodology: The classification of commodity groups is based on the Standard International Trade Classification (SITC) revision 3.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of merchandise exports", "short_unit": "%" }, "tx_val_mrch_al_zs": { "title": "Merchandise exports to economies in the Arab World (% of total merchandise exports)", "description_from_producer": "Merchandise exports to economies in the Arab World are the sum of merchandise exports by the reporting economy to economies in the Arab World. Data are expressed as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_cd_wt": { "title": "Merchandise exports (current US$)", "description_from_producer": "Merchandise exports show the f.o.b. value of goods provided to the rest of the world valued in current U.S. dollars.\n\nLimitations and exceptions: Exports are recorded as the cost of the goods delivered to the frontier of the exporting country for shipment - the free on board (f.o.b.) value.\n\nCountries may report trade according to the general or special system of trade. Under the general system exports comprise outward-moving goods that are (a) goods wholly or partly produced in the country; (b) foreign goods, neither transformed nor declared for domestic consumption in the country, that move outward from customs storage; and (c) goods previously included as imports for domestic consumption but subsequently exported without transformation. Under the special system exports comprise categories a and c. In some compilations categories b and c are classified as re-exports. Because of differences in reporting practices, data on exports may not be fully comparable across economies.\n\nData on exports of goods are derived from the same sources as data on imports. In principle, world exports and imports should be identical. Similarly, exports from an economy should equal the sum of imports by the rest of the world from that economy. But differences in timing and definitions result in discrepancies in reported values at all levels.\n\nStatistical concept and methodology: Merchandise trade data are from customs reports of goods moving into or out of an economy or from reports of financial transactions related to merchandise trade recorded in the balance of payments. Because of differences in timing and definitions, trade flow estimates from customs reports and balance of payments may differ. Several international agencies process trade data, each correcting unreported or misreported data, leading to other differences.\n\nThe data on total exports of goods (merchandise) are from the World Trade Organization (WTO), which obtains data from national statistical offices and the IMF's International Financial Statistics, supplemented by the Comtrade database and publications or databases of regional organizations, specialized agencies, economic groups, and private sources (such as Eurostat, the Food and Agriculture Organization, and country reports of the Economist Intelligence Unit). Country websites and email contact have improved collection of up-to-date statistics, reducing the proportion of estimates. The WTO database now covers most major traders in Africa, Asia, and Latin America, which together with high-income countries account for nearly 95 percent of world trade. Reliability of data for countries in Europe and Central Asia has also improved.", "origins": [ { "producer": "World Trade Organization (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "tx_val_mrch_hi_zs": { "title": "Merchandise exports to high-income economies (% of total merchandise exports)", "description_from_producer": "Merchandise exports to high-income economies are the sum of merchandise exports from the reporting economy to high-income economies according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.\n\nLimitations and exceptions: Data on exports and imports are from the International Monetary Fund's (IMF) Direction of Trade database and should be broadly consistent with data from other sources, such as the United Nations Statistics Division's Commodity Trade (Comtrade) database. All high-income economies and major low- and middle-income economies report trade data to the IMF on a timely basis, covering about 85 percent of trade for recent years. Trade data for less timely reporters and for countries that do not report are estimated using reports of trading partner countries. Therefore, data on trade between developing and high-income economies should be generally complete. But trade flows between many low- and middle-income economies - particularly those in Sub-Saharan Africa - are not well recorded, and the value of trade among low- and middle-income economies may be understated.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_or_zs": { "title": "Merchandise exports to low- and middle-income economies outside region (% of total merchandise exports)", "description_from_producer": "Merchandise exports to low- and middle-income economies outside region are the sum of merchandise exports from the reporting economy to other low- and middle-income economies in other World Bank regions according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.\n\nLimitations and exceptions: Data on exports and imports are from the International Monetary Fund's (IMF) Direction of Trade database and should be broadly consistent with data from other sources, such as the United Nations Statistics Division's Commodity Trade (Comtrade) database. All high-income economies and major low- and middle-income economies report trade data to the IMF on a timely basis, covering about 85 percent of trade for recent years. Trade data for less timely reporters and for countries that do not report are estimated using reports of trading partner countries. Therefore, data on trade between developing and high-income economies should be generally complete. But trade flows between many low- and middle-income economies - particularly those in Sub-Saharan Africa - are not well recorded, and the value of trade among low- and middle-income economies may be understated.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_r1_zs": { "title": "Merchandise exports to low- and middle-income economies in East Asia & Pacific (% of total merchandise exports)", "description_from_producer": "Merchandise exports to low- and middle-income economies in East Asia and Pacific are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the East Asia and Pacific region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_r2_zs": { "title": "Merchandise exports to low- and middle-income economies in Europe & Central Asia (% of total merchandise exports)", "description_from_producer": "Merchandise exports to low- and middle-income economies in Europe and Central Asia are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Europe and Central Asia region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_r3_zs": { "title": "Merchandise exports to low- and middle-income economies in Latin America & the Caribbean (% of total merchandise exports)", "description_from_producer": "Merchandise exports to low- and middle-income economies in Latin America and the Caribbean are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Latin America and the Caribbean region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_r4_zs": { "title": "Merchandise exports to low- and middle-income economies in Middle East & North Africa (% of total merchandise exports)", "description_from_producer": "Merchandise exports to low- and middle-income economies in Middle East and North Africa are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Middle East and North Africa region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_r5_zs": { "title": "Merchandise exports to low- and middle-income economies in South Asia (% of total merchandise exports)", "description_from_producer": "Merchandise exports to low- and middle-income economies in South Asia are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the South Asia region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_r6_zs": { "title": "Merchandise exports to low- and middle-income economies in Sub-Saharan Africa (% of total merchandise exports)", "description_from_producer": "Merchandise exports to low- and middle-income economies in Sub-Saharan Africa are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Sub-Saharan Africa region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_rs_zs": { "title": "Merchandise exports by the reporting economy, residual (% of total merchandise exports)", "description_from_producer": "Merchandise exports by the reporting economy residuals are the total merchandise exports by the reporting economy to the rest of the world as reported in the IMF's Direction of trade database, less the sum of exports by the reporting economy to high-, low-, and middle-income economies according to the World Bank classification of economies. Includes trade with unspecified partners or with economies not covered by World Bank classification. Data are as a percentage of total merchandise exports by the economy.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_wl_cd": { "title": "Merchandise exports by the reporting economy (current US$)", "description_from_producer": "Merchandise exports by the reporting economy are the total merchandise exports by the reporting economy to the rest of the world, as reported in the IMF's Direction of trade database. Data are in current US$.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "tx_val_mrch_wr_zs": { "title": "Merchandise exports to low- and middle-income economies within region (% of total merchandise exports)", "description_from_producer": "Merchandise exports to low- and middle-income economies within region are the sum of merchandise exports from the reporting economy to other low- and middle-income economies in the same World Bank region as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data. No figures are shown for high-income economies, because they are a separate category in the World Bank classification of economies.\n\nLimitations and exceptions: Data on exports and imports are from the International Monetary Fund's (IMF) Direction of Trade database and should be broadly consistent with data from other sources, such as the United Nations Statistics Division's Commodity Trade (Comtrade) database. All high-income economies and major low- and middle-income economies report trade data to the IMF on a timely basis, covering about 85 percent of trade for recent years. Trade data for less timely reporters and for countries that do not report are estimated using reports of trading partner countries. Therefore, data on trade between developing and high-income economies should be generally complete. But trade flows between many low- and middle-income economies - particularly those in Sub-Saharan Africa - are not well recorded, and the value of trade among low- and middle-income economies may be understated.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total merchandise exports", "short_unit": "%" }, "tx_val_mrch_xd_wd": { "title": "Export value index (2015 = 100)", "description_from_producer": "Export values are the current value of exports (f.o.b.) converted to U.S. dollars and expressed as a percentage of the average for the base period (2015). UNCTAD's export value indexes are reported for most economies.", "origins": [ { "producer": "United Nations Conference on Trade and Development", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "2015 = 100" }, "tx_val_othr_zs_wt": { "title": "Computer, communications and other services (% of commercial service exports)", "description_from_producer": "Computer, communications and other services (% of commercial service exports) include such activities as international telecommunications, and postal and courier services; computer data; news-related service transactions between residents and nonresidents; construction services; royalties and license fees; miscellaneous business, professional, and technical services; and personal, cultural, and recreational services.\n\nLimitations and exceptions: Balance of payments statistics, the main source of information on international trade in services, have many weaknesses. Disaggregation of important components may be limited and varies considerably across countries. There are inconsistencies in the methods used to report items. And the recording of major flows as net items is common (for example, insurance transactions are often recorded as premiums less claims). These factors contribute to a downward bias in the value of the service trade reported in the balance of payments.\n\nEfforts are being made to improve the coverage, quality, and consistency of these data. Eurostat and the Organisation for Economic Co-operation and Development, for example, are working together to improve the collection of statistics on trade in services in member countries.\n\nStill, difficulties in capturing all the dimensions of international trade in services mean that the record is likely to remain incomplete. Cross-border intrafirm service transactions, which are usually not captured in the balance of payments, have increased in recent years. An example is transnational corporations' use of mainframe computers around the clock for data processing, exploiting time zone differences between their home country and the host countries of their affiliates. Another important dimension of service trade not captured by conventional balance of payments statistics is establishment trade - sales in the host country by foreign affiliates. By contrast, cross-border intrafirm transactions in merchandise may be reported as exports or imports in the balance of payments.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial service exports", "short_unit": "%" }, "tx_val_serv_cd_wt": { "title": "Commercial service exports (current US$)", "description_from_producer": "Commercial service exports are total service exports minus exports of government services not included elsewhere. International transactions in services are defined by the IMF's Balance of Payments Manual (1993) as the economic output of intangible commodities that may be produced, transferred, and consumed at the same time. Definitions may vary among reporting economies.\n\nLimitations and exceptions: Balance of payments statistics, the main source of information on international trade in services, have many weaknesses. Disaggregation of important components may be limited and varies considerably across countries. There are inconsistencies in the methods used to report items. And the recording of major flows as net items is common (for example, insurance transactions are often recorded as premiums less claims). These factors contribute to a downward bias in the value of the service trade reported in the balance of payments.\n\nEfforts are being made to improve the coverage, quality, and consistency of these data. Eurostat and the Organisation for Economic Co-operation and Development, for example, are working together to improve the collection of statistics on trade in services in member countries.\n\nStill, difficulties in capturing all the dimensions of international trade in services mean that the record is likely to remain incomplete. Cross-border intrafirm service transactions, which are usually not captured in the balance of payments, have increased in recent years. An example is transnational corporations' use of mainframe computers around the clock for data processing, exploiting time zone differences between their home country and the host countries of their affiliates. Another important dimension of service trade not captured by conventional balance of payments statistics is establishment trade - sales in the host country by foreign affiliates. By contrast, cross-border intrafirm transactions in merchandise may be reported as exports or imports in the balance of payments.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "tx_val_tech_cd": { "title": "High-technology exports (current US$)", "description_from_producer": "High-technology exports are products with high R&D intensity, such as aerospace, computers, pharmaceuticals, scientific instruments, and electrical machinery. Data are in current U.S. dollars.\n\nLimitations and exceptions: Because industrial sectors specializing in a few high-technology products may also produce low-technology products, the product approach is more appropriate for international trade. The method takes only R&D intensity into account, but other characteristics of high technology are also important, such as knowhow, scientific personnel, and technology embodied in patents. Considering these characteristics would yield a different list (see Hatzichronoglou 1997). The indicator is based on data reported by countries to COMTRADE. The export values presented in the World Development Indicators represent Gross Exports less Re-Exports. The values may be impacted in cases of reporting errors or missing data, for example if countries do not report Re-Exports for one or more periods.\n\nStatistical concept and methodology: High technology products are defined according to SITC Rev.4 as the sum of the following products: Aerospace, Computers-office machines, Electronics-telecommunications, Pharmacy, Scientific instruments, Electrical machinery, Chemistry, Non-electrical machinery, Armament. The following product codes are used: Aerospace: (714 \u2013 71489 -71499)+7921+7922+7924+7925+79291+79293+87411; Computers-office machines: 75194+75195+752+75997; Electronics-communication: 76331+7638+(764-76493-76499)+7722+77261+77318+77625+77627+7763+7764+7768+89844+89846; Pharmacy: 5413+5415+5416+5421+5422; Scientific instruments: 774+871+87211+(874-87411-8742)+88111+88121+88411+88419+(8996-89965-89969); Electrical machinery: (7786-77861-777866-77869)+7787+77884; Chemistry: 52222+52223+52229+52269+525+531+57433+591; Non-electrical machinery: 71489+71499+7187+72847+7311+73131+73135+73142+73144+73151+73153+73161+73163+73165+73312+73314+73316+7359+73733+73735; Armament: 891\nThe list can also be accessed on the Eurostat website. This list, based on the OECD definition, contains technical products of which the manufacturing involved a high intensity of R&D. The original high-tech products classification is based on SITC Rev. 3 and is taken from Table 4 of Annex 2 of the 1997 working paper of Thomas Hatzichronouglou, OECD. In September 2019 the definition in the World Development Indicators database was updated to SITC Rev.4 from SITC Rev. 3. The data are in current U.S. dollars and are sourced from the UN's Comtrade database.", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "tx_val_tech_mf_zs": { "title": "High-technology exports (% of manufactured exports)", "description_from_producer": "High-technology exports are products with high R&D intensity, such as in aerospace, computers, pharmaceuticals, scientific instruments, and electrical machinery.\n\nLimitations and exceptions: Because industrial sectors specializing in a few high-technology products may also produce low-technology products, the product approach is more appropriate for international trade. The method takes only R&D intensity into account, but other characteristics of high technology are also important, such as knowhow, scientific personnel, and technology embodied in patents. Considering these characteristics would yield a different list (see Hatzichronoglou 1997).\n\nStatistical concept and methodology: The method for determining high-technology exports was developed by the Organisation for Economic Co-operation and Development in collaboration with Eurostat. It takes a \"product approach\" (rather than a \"sectoral approach\") based on R&D intensity (expenditure divided by total sales) for groups of products from Germany, Italy, Japan, the Netherlands, Sweden, and the United States.\n\nThe original high-tech products classification is based on SITC Rev. 3 and is taken from Table 4 of Annex 2 of the 1997 working paper of Thomas Hatzichronouglou, OECD. The methodology used to determine high-tech exports takes the \"product approach\" based on R&D intensity on products from Germany, Italy, Japan, the Netherlands, Sweden, and the United States.\n\nHigh Technology Products List - SITC Rev. 3:\n1 Aerospace 7921+7922+7923+7924+7925+79291+79293+(714-71489-71499)+87411\n2 Computers-office machines 75113+75131+75132+75134+(752-7529)+75997\n3 Electronics-telecommunications 76381+76383+(764-76493-76499)\n+7722+77261+77318+77625+77627+7763+7764+7768+89879\n4 Pharmacy 5413+5415+5416+5421+5422\n5 Scientific instruments 774+8711+8713+8714+8719+87211+(874-87411-8742)\n+88111+88121+88411+88419+89961+89963+89966+89967\n6 Electrical machinery 77862+77863+77864+77865+7787+77884\n7 Chemistry 52222+52223+52229+52269+525+531+57433+591\n8 Non-electrical machinery 71489+71499+71871+71877+71878+72847+7311+73131+73135\n+73142+73144+73151+73153+73161+73163+73165\n+73312+73314+73316+7359+73733+73735\n9 Armament 891", "origins": [ { "producer": "World Bank based on data from the World Integrated Trade Solution platform", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of manufactured exports", "short_unit": "%" }, "tx_val_tran_zs_wt": { "title": "Transport services (% of commercial service exports)", "description_from_producer": "Transport services (% of commercial service exports) covers all transport services (sea, air, land, internal waterway, space, and pipeline) performed by residents of one economy for those of another and involving the carriage of passengers, movement of goods (freight), rental of carriers with crew, and related support and auxiliary services. Excluded are freight insurance, which is included in insurance services; goods procured in ports by nonresident carriers and repairs of transport equipment, which are included in goods; repairs of railway facilities, harbors, and airfield facilities, which are included in construction services; and rental of carriers without crew, which is included in other services.\n\nLimitations and exceptions: Balance of payments statistics, the main source of information on international trade in services, have many weaknesses. Disaggregation of important components may be limited and varies considerably across countries. There are inconsistencies in the methods used to report items. And the recording of major flows as net items is common (for example, insurance transactions are often recorded as premiums less claims). These factors contribute to a downward bias in the value of the service trade reported in the balance of payments.\n\nEfforts are being made to improve the coverage, quality, and consistency of these data. Eurostat and the Organisation for Economic Co-operation and Development, for example, are working together to improve the collection of statistics on trade in services in member countries.\n\nStill, difficulties in capturing all the dimensions of international trade in services mean that the record is likely to remain incomplete. Cross-border intrafirm service transactions, which are usually not captured in the balance of payments, have increased in recent years. An example is transnational corporations' use of mainframe computers around the clock for data processing, exploiting time zone differences between their home country and the host countries of their affiliates. Another important dimension of service trade not captured by conventional balance of payments statistics is establishment trade - sales in the host country by foreign affiliates. By contrast, cross-border intrafirm transactions in merchandise may be reported as exports or imports in the balance of payments.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial service exports", "short_unit": "%" }, "tx_val_trvl_zs_wt": { "title": "Travel services (% of commercial service exports)", "description_from_producer": "Travel services (% of commercial service exports) covers goods and services acquired from an economy by travelers in that economy for their own use during visits of less than one year for business or personal purposes. Travel services include the goods and services consumed by travelers, such as lodging and meals and transport (within the economy visited).\n\nLimitations and exceptions: Balance of payments statistics, the main source of information on international trade in services, have many weaknesses. Disaggregation of important components may be limited and varies considerably across countries. There are inconsistencies in the methods used to report items. And the recording of major flows as net items is common (for example, insurance transactions are often recorded as premiums less claims). These factors contribute to a downward bias in the value of the service trade reported in the balance of payments.\n\nEfforts are being made to improve the coverage, quality, and consistency of these data. Eurostat and the Organisation for Economic Co-operation and Development, for example, are working together to improve the collection of statistics on trade in services in member countries.\n\nStill, difficulties in capturing all the dimensions of international trade in services mean that the record is likely to remain incomplete. Cross-border intrafirm service transactions, which are usually not captured in the balance of payments, have increased in recent years. An example is transnational corporations' use of mainframe computers around the clock for data processing, exploiting time zone differences between their home country and the host countries of their affiliates. Another important dimension of service trade not captured by conventional balance of payments statistics is establishment trade - sales in the host country by foreign affiliates. By contrast, cross-border intrafirm transactions in merchandise may be reported as exports or imports in the balance of payments.\n\nStatistical concept and methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual (BPM6). Balance of payments data for 2005 onward will be presented in accord with the BPM6. The historical BPM5 data series will end with data for 2008, which can be accessed through the World Development Indicators archives.\n\nThe complete balance of payments methodology can be accessed through the International Monetary Fund website (www.imf.org/external/np/sta/bop/bop.htm).", "origins": [ { "producer": "International Monetary Fund (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of commercial service exports", "short_unit": "%" }, "va_est": { "title": "Voice and Accountability: Estimate", "description_from_producer": "Voice and Accountability captures perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media. Estimate gives the country's score on the aggregate indicator, in units of a standard normal distribution, i.e. ranging from approximately -2.5 to 2.5.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "va_no_src": { "title": "Voice and Accountability: Number of Sources", "description_from_producer": "Voice and Accountability captures perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media. Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "va_per_rnk": { "title": "Voice and Accountability: Percentile Rank", "description_from_producer": "Voice and Accountability captures perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "va_per_rnk_lower": { "title": "Voice and Accountability: Percentile Rank, Lower Bound of 90% Confidence Interval", "description_from_producer": "Voice and Accountability captures perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "va_per_rnk_upper": { "title": "Voice and Accountability: Percentile Rank, Upper Bound of 90% Confidence Interval", "description_from_producer": "Voice and Accountability captures perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "va_std_err": { "title": "Voice and Accountability: Standard Error", "description_from_producer": "Voice and Accountability captures perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media. Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "" }, "vc_btl_deth": { "title": "Battle-related deaths (number of people)", "description_from_producer": "Battle-related deaths are deaths in battle-related conflicts between warring parties in the conflict dyad (two conflict units that are parties to a conflict). Typically, battle-related deaths occur in warfare involving the armed forces of the warring parties. This includes traditional battlefield fighting, guerrilla activities, and all kinds of bombardments of military units, cities, and villages, etc. The targets are usually the military itself and its installations or state institutions and state representatives, but there is often substantial collateral damage in the form of civilians being killed in crossfire, in indiscriminate bombings, etc. All deaths--military as well as civilian--incurred in such situations, are counted as battle-related deaths.\n\nLimitations and exceptions: An armed conflict is a contested incompatibility that concerns a government or territory where the use of armed force between two parties (one of them the government) results in at least 25 battle related deaths in a calendar year.\n\nData is from the Uppsala Conflict Data Program (UCDP) Battle-Related Deaths Dataset which focuses on the incompatibility and lists the country, as well as the battle location and territory where battle-related deaths are reported. When more than one country is listed in the dataset, the assignment of battle-related deaths is determined by the battle location. User can refer to the ICDP dataset where they have split the deaths for the actual location of the fighting when the fighting occurred on the disputed border.\n\nStatistical concept and methodology: During warfare, targets are usually the military and its installations or state institutions and state representatives, but there is often substantial collateral damage of civilians killed in crossfire, indiscriminate bombings, and other military activities. All deaths - civilian as well as military - incurred in such situations are counted as battle-related deaths.", "origins": [ { "producer": "Uppsala Conflict Data Program (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number of people" }, "vc_idp_nwcv": { "title": "Internally displaced persons, new displacement associated with conflict and violence (number of cases)", "description_from_producer": "Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. \"New Displacement\" refers to the number of new cases or incidents of displacement recorded over the specified year, rather than the number of people displaced. This is done because people may have been displaced more than once.\n\nLimitations and exceptions: Please note that most of the figures are estimates. The definition highlights two issues:\n\n1) The coercive or otherwise involuntary character of movement. The definition mentions some of the most common causes of involuntary movements, such as armed conflict, violence, human rights violations and disasters. These causes have in common that they give no choice to people but to leave their homes and deprive them of the most essential protection mechanisms, such as community networks, access to services, livelihoods. Displacement severely affects the physical, socio-economic and legal safety of people and should be systematically regarded as an indicator of potential vulnerability.\n\n2) The fact that such movement takes place within national borders. Unlike refugees, who have been deprived of the protection of their state of origin, IDPs remain legally under the protection of national authorities of their country of habitual residence. IDPs should therefore enjoy the same rights as the rest of the population. The Guiding Principles on Internal Displacement remind national authorities and other relevant actors of their responsibility to ensure that IDPs' rights are respected and fulfilled, despite the vulnerability generated by their displacement.\n\nStatistical concept and methodology: Internally displaced persons are \"persons or groups of persons who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of or in order to avoid the effects of armed conflict, situations of generalized violence, violations of human rights or natural or human-made disasters, and who have not crossed an internationally recognized state border.\" Internally displaced people are often confused with refugees. Unlike refugees, internally displaced people remain under the protection of their own government, even if their reason for fleeing was similar to that of refugees. Refugees are people who have crossed an international border to find sanctuary and have been granted refugee or refugee-like status or temporary protection. For more information on methodology, please refer to the information published by IDMC: http://www.internal-displacement.org/database/", "origins": [ { "producer": "Internal Displacement Monitoring Centre (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number of cases" }, "vc_idp_nwds": { "title": "Internally displaced persons, new displacement associated with disasters (number of cases)", "description_from_producer": "Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. \"New Displacement\" refers to the number of new cases or incidents of displacement recorded over the specified year, rather than the number of people displaced. This is done because people may have been displaced more than once.\n\nLimitations and exceptions: Please note that most of the figures are estimates. The definition highlights two issues:\n\n1) The coercive or otherwise involuntary character of movement. The definition mentions some of the most common causes of involuntary movements, such as armed conflict, violence, human rights violations and disasters. These causes have in common that they give no choice to people but to leave their homes and deprive them of the most essential protection mechanisms, such as community networks, access to services, livelihoods. Displacement severely affects the physical, socio-economic and legal safety of people and should be systematically regarded as an indicator of potential vulnerability.\n\n2) The fact that such movement takes place within national borders. Unlike refugees, who have been deprived of the protection of their state of origin, IDPs remain legally under the protection of national authorities of their country of habitual residence. IDPs should therefore enjoy the same rights as the rest of the population. The Guiding Principles on Internal Displacement remind national authorities and other relevant actors of their responsibility to ensure that IDPs' rights are respected and fulfilled, despite the vulnerability generated by their displacement.\n\nStatistical concept and methodology: Internally displaced persons are \"persons or groups of persons who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of or in order to avoid the effects of armed conflict, situations of generalized violence, violations of human rights or natural or human-made disasters, and who have not crossed an internationally recognized state border.\" Internally displaced people are often confused with refugees. Unlike refugees, internally displaced people remain under the protection of their own government, even if their reason for fleeing was similar to that of refugees. Refugees are people who have crossed an international border to find sanctuary and have been granted refugee or refugee-like status or temporary protection.", "origins": [ { "producer": "Internal Displacement Monitoring Centre (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number of cases" }, "vc_idp_tocv": { "title": "Internally displaced persons, total displaced by conflict and violence (number of people)", "description_from_producer": "Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. \u201cPeople displaced\u201d refers to the number of people living in displacement as of the end of each year, and reflects the stock of people displaced at the end of the previous year, plus inflows of new cases arriving over the year as well as births over the year to those displaced, minus outflows which may include returnees, those who settled elsewhere, those who integrated locally, those who travelled over borders, and deaths.\n\nLimitations and exceptions: Please note that most of the figures are estimates. The definition highlights two issues:\n\n1) The coercive or otherwise involuntary character of movement. The definition mentions some of the most common causes of involuntary movements, such as armed conflict, violence, human rights violations and disasters. These causes have in common that they give no choice to people but to leave their homes and deprive them of the most essential protection mechanisms, such as community networks, access to services, livelihoods. Displacement severely affects the physical, socio-economic and legal safety of people and should be systematically regarded as an indicator of potential vulnerability.\n\n2) The fact that such movement takes place within national borders. Unlike refugees, who have been deprived of the protection of their state of origin, IDPs remain legally under the protection of national authorities of their country of habitual residence. IDPs should therefore enjoy the same rights as the rest of the population. The Guiding Principles on Internal Displacement remind national authorities and other relevant actors of their responsibility to ensure that IDPs' rights are respected and fulfilled, despite the vulnerability generated by their displacement.\n\nStatistical concept and methodology: Internally displaced persons are \"persons or groups of persons who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of or in order to avoid the effects of armed conflict, situations of generalized violence, violations of human rights or natural or human-made disasters, and who have not crossed an internationally recognized state border.\" Internally displaced people are often confused with refugees. Unlike refugees, internally displaced people remain under the protection of their own government, even if their reason for fleeing was similar to that of refugees. Refugees are people who have crossed an international border to find sanctuary and have been granted refugee or refugee-like status or temporary protection. \u201cPeople displaced\u201d refers to the number of people living in displacement as of the end of each year, and reflects the stock of people displaced at the end of the previous year, plus inflows of new cases arriving over the year as well as births over the year to those displaced, minus outflows which may include returnees, those who settled elsewhere, those who integrated locally, those who travelled over borders, and deaths.", "origins": [ { "producer": "Internal Displacement Monitoring Centre (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "number of people" }, "vc_ihr_psrc_fe_p5": { "title": "Intentional homicides, female (per 100,000 female)", "description_from_producer": "Intentional homicides, female are estimates of unlawful female homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.\n\nLimitations and exceptions: Statistics reported to the United Nations in the context of its various surveys on crime levels and criminal justice trends are incidents of victimization that have been reported to the authorities in any given country. That means that this data is subject to the problems of accuracy of all official crime data. The survey results provide an overview of trends and interrelationships between various parts of the criminal justice system to promote informed decision-making in administration, nationally and internationally.\n\nThe degree to which different societies apportion the level of culpability to acts resulting in death is also subject to variation. Consequently, the comparison between countries and regions of \"intentional homicide\", or unlawful death purposefully inflicted on a person by another person, is also a comparison of the extent to which different countries deem that a killing be classified as such, as well as the capacity of their legal systems to record it. Caution should therefore be applied when evaluating and comparing homicide data.\n\nStatistical concept and methodology: The definitions used to produce data are in line with the homicide definition used in the UNODC Homicide Statistics dataset. On the basis of these selection criteria and subject to data availability, a long and continuous time series including recent data on homicide counts and rates has been identified or created at country level. Data are adjusted to conform to the total number of victims of intentional homicide. The adjustment is carried out by applying the sex ratio of reported victims to the total number of victims of intentional homicide.\n\nThe intentional killing of a human being by another is the ultimate crime. Its indisputable physical consequences manifested in the form of a dead body also make it the most categorical and calculable. All existing data sources on intentional homicides, both at national and international level, stem from either criminal justice or public health systems. In the former case, data are generated by law enforcement or criminal justice authorities in the process of recording and investigating a crime event. In the latter, data are produced by health authorities certifying the cause of death of an individual.\n\nCriminal justice data were collected through UNODC regular collections of crime data from Member States, through publicly available data produced by national government sources and from data compiled by other international and regional agencies, including from Interpol, Eurostat, the Organization of American States and UNICEF. Public health data on homicides were mainly derived from databases on deaths by cause disseminated by the World Health Organization (WHO).\n\nThe inclusion of recent data was given a higher priority in the selection process than the length of the time series (number of years covered). An analysis of official reports and research literature is regularly carried out to verify homicide data used by government agencies and the scientific community.\n\nAs a result of the data collection and validation process, in many countries several homicide datasets have become available from different or multiple sources. Therefore, data series have been selected to provide the most appropriate reference counts.", "origins": [ { "producer": "UN Office on Drugs and Crime (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 female" }, "vc_ihr_psrc_ma_p5": { "title": "Intentional homicides, male (per 100,000 male)", "description_from_producer": "Intentional homicides, male are estimates of unlawful male homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.\n\nLimitations and exceptions: Statistics reported to the United Nations in the context of its various surveys on crime levels and criminal justice trends are incidents of victimization that have been reported to the authorities in any given country. That means that this data is subject to the problems of accuracy of all official crime data. The survey results provide an overview of trends and interrelationships between various parts of the criminal justice system to promote informed decision-making in administration, nationally and internationally.\n\nThe degree to which different societies apportion the level of culpability to acts resulting in death is also subject to variation. Consequently, the comparison between countries and regions of \"intentional homicide\", or unlawful death purposefully inflicted on a person by another person, is also a comparison of the extent to which different countries deem that a killing be classified as such, as well as the capacity of their legal systems to record it. Caution should therefore be applied when evaluating and comparing homicide data.\n\nStatistical concept and methodology: The definitions used to produce data are in line with the homicide definition used in the UNODC Homicide Statistics dataset. On the basis of these selection criteria and subject to data availability, a long and continuous time series including recent data on homicide counts and rates has been identified or created at country level. Data are adjusted to conform to the total number of victims of intentional homicide. The adjustment is carried out by applying the sex ratio of reported victims to the total number of victims of intentional homicide.\n\nThe intentional killing of a human being by another is the ultimate crime. Its indisputable physical consequences manifested in the form of a dead body also make it the most categorical and calculable. All existing data sources on intentional homicides, both at national and international level, stem from either criminal justice or public health systems. In the former case, data are generated by law enforcement or criminal justice authorities in the process of recording and investigating a crime event. In the latter, data are produced by health authorities certifying the cause of death of an individual.\n\nCriminal justice data were collected through UNODC regular collections of crime data from Member States, through publicly available data produced by national government sources and from data compiled by other international and regional agencies, including from Interpol, Eurostat, the Organization of American States and UNICEF. Public health data on homicides were mainly derived from databases on deaths by cause disseminated by the World Health Organization (WHO).\n\nThe inclusion of recent data was given a higher priority in the selection process than the length of the time series (number of years covered). An analysis of official reports and research literature is regularly carried out to verify homicide data used by government agencies and the scientific community.\n\nAs a result of the data collection and validation process, in many countries several homicide datasets have become available from different or multiple sources. Therefore, data series have been selected to provide the most appropriate reference counts.", "origins": [ { "producer": "UN Office on Drugs and Crime (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 male" }, "vc_ihr_psrc_p5": { "title": "Intentional homicides (per 100,000 people)", "description_from_producer": "Intentional homicides are estimates of unlawful homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.\n\nLimitations and exceptions: Statistics reported to the United Nations in the context of its various surveys on crime levels and criminal justice trends are incidents of victimization that have been reported to the authorities in any given country. That means that this data is subject to the problems of accuracy of all official crime data. The survey results provide an overview of trends and interrelationships between various parts of the criminal justice system to promote informed decision-making in administration, nationally and internationally.\n\nThe degree to which different societies apportion the level of culpability to acts resulting in death is also subject to variation. Consequently, the comparison between countries and regions of \"intentional homicide\", or unlawful death purposefully inflicted on a person by another person, is also a comparison of the extent to which different countries deem that a killing be classified as such, as well as the capacity of their legal systems to record it. Caution should therefore be applied when evaluating and comparing homicide data.\n\nStatistical concept and methodology: The definitions used to produce data are in line with the homicide definition used in the UNODC Homicide Statistics dataset. On the basis of these selection criteria and subject to data availability, a long and continuous time series including recent data on homicide counts and rates has been identified or created at country level. Data included in the dataset correspond to the original value provided by the source of origin, since no statistical procedure or modeling was used to change collected values or to create new or revised figures.\n\nThe intentional killing of a human being by another is the ultimate crime. Its indisputable physical consequences manifested in the form of a dead body also make it the most categorical and calculable. All existing data sources on intentional homicides, both at national and international level, stem from either criminal justice or public health systems. In the former case, data are generated by law enforcement or criminal justice authorities in the process of recording and investigating a crime event. In the latter, data are produced by health authorities certifying the cause of death of an individual.\n\nCriminal justice data were collected through UNODC regular collections of crime data from Member States, through publicly available data produced by national government sources and from data compiled by other international and regional agencies, including from Interpol, Eurostat, the Organization of American States and UNICEF. Public health data on homicides were mainly derived from databases on deaths by cause disseminated by the World Health Organization (WHO).\n\nThe inclusion of recent data was given a higher priority in the selection process than the length of the time series (number of years covered). An analysis of official reports and research literature is regularly carried out to verify homicide data used by government agencies and the scientific community.\n\nAs a result of the data collection and validation process, in many countries several homicide datasets have become available from different or multiple sources. Therefore, data series have been selected to provide the most appropriate reference counts.", "origins": [ { "producer": "UN Office on Drugs and Crime (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "per 100,000 people" }, "per_allsp_adq_pop_tot": { "title": "Adequacy of social protection and labor programs (% of total welfare of beneficiary households)", "description_from_producer": "Adequacy of social protection and labor programs (SPL) is measured by the total transfer amount received by the population participating in social insurance, social safety net, and unemployment benefits and active labor market programs as a share of their total welfare. Welfare is defined as the total income or total expenditure of beneficiary households. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total welfare of beneficiary households", "short_unit": "%" }, "per_allsp_ben_q1_tot": { "title": "Benefit incidence of social protection and labor programs to poorest quintile (% of total SPL benefits)", "description_from_producer": "Benefit incidence of social protection and labor programs (SPL) to poorest quintile shows the percentage of total social protection and labor programs benefits received by the poorest 20% of the population. Social protection and labor programs include social insurance, social safety nets, and unemployment benefits and active labor market programs. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total SPL benefits", "short_unit": "%" }, "per_allsp_cov_pop_tot": { "title": "Coverage of social protection and labor programs (% of population)", "description_from_producer": "Coverage of social protection and labor programs (SPL) shows the percentage of population participating in social insurance, social safety net, and unemployment benefits and active labor market programs. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_lm_alllm_adq_pop_tot": { "title": "Adequacy of unemployment benefits and ALMP (% of total welfare of beneficiary households)", "description_from_producer": "Adequacy of unemployment benefits and active labor market programs (ALMP) is measured by the total transfer amount received by the population participating in unemployment benefits and active labor market programs as a share of their total welfare. Welfare is defined as the total income or total expenditure of beneficiary households. Unemployment benefits and active labor market programs include unemployment compensation, severance pay, and early retirement due to labor market reasons, labor market services (intermediation), training (vocational, life skills, and cash for training), job rotation and job sharing, employment incentives and wage subsidies, supported employment and rehabilitation, and employment measures for the disabled. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total welfare of beneficiary households", "short_unit": "%" }, "per_lm_alllm_ben_q1_tot": { "title": "Benefit incidence of unemployment benefits and ALMP to poorest quintile (% of total U/ALMP benefits)", "description_from_producer": "Benefit incidence of unemployment benefits and active labor market programs (ALMP) to poorest quintile shows the percentage of total unemployment and active labor market programs benefits received by the poorest 20% of the population. Unemployment benefits and active labor market programs include unemployment compensation, severance pay, and early retirement due to labor market reasons, labor market services (intermediation), training (vocational, life skills, and cash for training), job rotation and job sharing, employment incentives and wage subsidies, supported employment and rehabilitation, and employment measures for the disabled. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total U/ALMP benefits", "short_unit": "%" }, "per_lm_alllm_cov_pop_tot": { "title": "Coverage of unemployment benefits and ALMP (% of population)", "description_from_producer": "Coverage of unemployment benefits and active labor market programs (ALMP) shows the percentage of population participating in unemployment compensation, severance pay, and early retirement due to labor market reasons, labor market services (intermediation), training (vocational, life skills, and cash for training), job rotation and job sharing, employment incentives and wage subsidies, supported employment and rehabilitation, and employment measures for the disabled. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_lm_alllm_cov_q1_tot": { "title": "Coverage of unemployment benefits and ALMP in poorest quintile (% of population)", "description_from_producer": "Coverage of unemployment benefits and active labor market programs (ALMP) shows the percentage of population participating in unemployment compensation, severance pay, and early retirement due to labor market reasons, labor market services (intermediation), training (vocational, life skills, and cash for training), job rotation and job sharing, employment incentives and wage subsidies, supported employment and rehabilitation, and employment measures for the disabled. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_lm_alllm_cov_q2_tot": { "title": "Coverage of unemployment benefits and ALMP in 2nd quintile (% of population)", "description_from_producer": "Coverage of unemployment benefits and active labor market programs (ALMP) shows the percentage of population participating in unemployment compensation, severance pay, and early retirement due to labor market reasons, labor market services (intermediation), training (vocational, life skills, and cash for training), job rotation and job sharing, employment incentives and wage subsidies, supported employment and rehabilitation, and employment measures for the disabled. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_lm_alllm_cov_q3_tot": { "title": "Coverage of unemployment benefits and ALMP in 3rd quintile (% of population)", "description_from_producer": "Coverage of unemployment benefits and active labor market programs (ALMP) shows the percentage of population participating in unemployment compensation, severance pay, and early retirement due to labor market reasons, labor market services (intermediation), training (vocational, life skills, and cash for training), job rotation and job sharing, employment incentives and wage subsidies, supported employment and rehabilitation, and employment measures for the disabled. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_lm_alllm_cov_q4_tot": { "title": "Coverage of unemployment benefits and ALMP in 4th quintile (% of population)", "description_from_producer": "Coverage of unemployment benefits and active labor market programs (ALMP) shows the percentage of population participating in unemployment compensation, severance pay, and early retirement due to labor market reasons, labor market services (intermediation), training (vocational, life skills, and cash for training), job rotation and job sharing, employment incentives and wage subsidies, supported employment and rehabilitation, and employment measures for the disabled. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_lm_alllm_cov_q5_tot": { "title": "Coverage of unemployment benefits and ALMP in richest quintile (% of population)", "description_from_producer": "Coverage of unemployment benefits and active labor market programs (ALMP) shows the percentage of population participating in unemployment compensation, severance pay, and early retirement due to labor market reasons, labor market services (intermediation), training (vocational, life skills, and cash for training), job rotation and job sharing, employment incentives and wage subsidies, supported employment and rehabilitation, and employment measures for the disabled. Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_sa_allsa_adq_pop_tot": { "title": "Adequacy of social safety net programs (% of total welfare of beneficiary households)", "description_from_producer": "Adequacy of social safety net programs is measured by the total transfer amount received by the population participating in social safety net programs as a share of their total welfare. Welfare is defined as the total income or total expenditure of beneficiary households. Social safety net programs include cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total welfare of beneficiary households", "short_unit": "%" }, "per_sa_allsa_ben_q1_tot": { "title": "Benefit incidence of social safety net programs to poorest quintile (% of total safety net benefits)", "description_from_producer": "Benefit incidence of social safety net programs to poorest quintile shows the percentage of total social safety net benefits received by the poorest 20% of the population. Social safety net programs include cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total safety net benefits", "short_unit": "%" }, "per_sa_allsa_cov_pop_tot": { "title": "Coverage of social safety net programs (% of population)", "description_from_producer": "Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_sa_allsa_cov_q1_tot": { "title": "Coverage of social safety net programs in poorest quintile (% of population)", "description_from_producer": "Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_sa_allsa_cov_q2_tot": { "title": "Coverage of social safety net programs in 2nd quintile (% of population)", "description_from_producer": "Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_sa_allsa_cov_q3_tot": { "title": "Coverage of social safety net programs in 3rd quintile (% of population)", "description_from_producer": "Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_sa_allsa_cov_q4_tot": { "title": "Coverage of social safety net programs in 4th quintile (% of population)", "description_from_producer": "Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_sa_allsa_cov_q5_tot": { "title": "Coverage of social safety net programs in richest quintile (% of population)", "description_from_producer": "Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_si_allsi_adq_pop_tot": { "title": "Adequacy of social insurance programs (% of total welfare of beneficiary households)", "description_from_producer": "Adequacy of social insurance programs is measured by the total transfer amount received by the population participating in social insurance programs as a share of their total welfare. Welfare is defined as the total income or total expenditure of beneficiary households. Social insurance programs include old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total welfare of beneficiary households", "short_unit": "%" }, "per_si_allsi_ben_q1_tot": { "title": "Benefit incidence of social insurance programs to poorest quintile (% of total social insurance benefits)", "description_from_producer": "Benefit incidence of social insurance programs to poorest quintile shows the percentage of total social insurance benefits received by the poorest 20% of the population. Social insurance programs include old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of total social insurance benefits", "short_unit": "%" }, "per_si_allsi_cov_pop_tot": { "title": "Coverage of social insurance programs (% of population)", "description_from_producer": "Coverage of social insurance programs shows the percentage of population participating in programs that provide old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_si_allsi_cov_q1_tot": { "title": "Coverage of social insurance programs in poorest quintile (% of population)", "description_from_producer": "Coverage of social insurance programs shows the percentage of population participating in programs that provide old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_si_allsi_cov_q2_tot": { "title": "Coverage of social insurance programs in 2nd quintile (% of population)", "description_from_producer": "Coverage of social insurance programs shows the percentage of population participating in programs that provide old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_si_allsi_cov_q3_tot": { "title": "Coverage of social insurance programs in 3rd quintile (% of population)", "description_from_producer": "Coverage of social insurance programs shows the percentage of population participating in programs that provide old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_si_allsi_cov_q4_tot": { "title": "Coverage of social insurance programs in 4th quintile (% of population)", "description_from_producer": "Coverage of social insurance programs shows the percentage of population participating in programs that provide old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "per_si_allsi_cov_q5_tot": { "title": "Coverage of social insurance programs in richest quintile (% of population)", "description_from_producer": "Coverage of social insurance programs shows the percentage of population participating in programs that provide old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries.\n\nLimitations and exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of population", "short_unit": "%" }, "omm_urb_pop_slum": { "title": "Urban population living in slums", "description": "Total urban population living in slums. This variable is calculated by Our World in Data based on the following variables from United Nations Population Division and others (via World Bank): \"Urban population\" and \"Population living in slums (% of urban population)\"\n\n----\nUrban population: \n\n----\nPopulation living in slums (% of urban population): ", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "United Nations Population Division and others (via World Bank) - World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "", "short_unit": "" }, "omm_urb_pop_nonslum": { "title": "Urban population not living in slums", "description": "Total urban population not living in slums. This variable is calculated by Our World in Data based on the following variables from United Nations Population Division and others (via World Bank): \"Urban population\" and \"Population living in slums (% of urban population)\"\n\n----\nUrban population: \n\n----\nPopulation living in slums (% of urban population): ", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "United Nations Population Division and others (via World Bank) - World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "", "short_unit": "" }, "omm_share_service_exports": { "title": "Share of services in total goods and services exports", "description": "Service exports as a share of total exports of goods and services. This variable is calculated by Our World in Data based on the following variables from United Nations Population Division and others (via World Bank): \"Service exports (BoP, current US$)\" and \"Goods exports (BoP, current US$)\"\n\n----\nService exports (BoP, current US$): \n\n----\nGoods exports (BoP, current US$): ", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "United Nations Population Division and others (via World Bank) - World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of goods and services exports", "short_unit": "%" }, "omm_merch_exp_share_gdp": { "title": "Merchandise exports as a share of GDP", "description": "Merchandise exports as a share of GDP. This variable is calculated by Our World in Data based on the following variables from United Nations Population Division and others (via World Bank): \"Merchandise exports (current US$)\" and \"GDP (current US$)\"\n\n----\nMerchandise exports (current US$): \n\n----\nGDP (current US$): ", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "United Nations Population Division and others (via World Bank) - World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "omm_goods_exp_share_gdp": { "title": "Goods exports as a share of GDP", "description": "Goods exports as a share of GDP. This variable is calculated by Our World in Data based on the following variables from United Nations Population Division and others (via World Bank): \"Goods exports (BoP, current US$)\" and \"GDP (current US$)\"\n\n----\nGoods exports (BoP, current US$): \n\n----\nGDP (current US$): ", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "United Nations Population Division and others (via World Bank) - World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "% of GDP", "short_unit": "%" }, "omm_tax_rev_percap": { "title": "Tax revenues per capita (current international $)", "description": "Tax revenues per capita, expressed in current international $. This variable is calculated by Our World in Data based on the following variables from United Nations Population Division and others (via World Bank): \"Tax revenue (% of GDP)\" and \"GDP per capita, PPP (current international $)\"\n\n----\nTax revenue (% of GDP): \n\n----\nGDP per capita, PPP (current international $): ", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "United Nations Population Division and others (via World Bank) - World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current international $", "short_unit": "$" }, "omm_net_savings_percap": { "title": "Adjusted net savings per capita, excluding particulate emission damage (current US$)", "description": "Adjusted net savings per capita (excluding particulate emission damage), expressed in current US$. This variable is calculated by Our World in Data based on the following variables from United Nations Population Division and others (via World Bank): \"Adjusted net savings, excluding particulate emission damage (current US$)\" and \"Population, total\"\n\n----\nAdjusted net savings, excluding particulate emission damage (current US$): \n\n----\nPopulation, total: ", "origins": [ { "producer": "United Nations Population Division and others (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "United Nations Population Division and others (via World Bank) - World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "armed_forces_share_population": { "title": "Armed forces personnel (% of total population)", "description_from_producer": "Armed forces personnel are active duty military personnel, including paramilitary forces if the training, organization, equipment, and control suggest they may be used to support or replace regular military forces.\n\nLimitations and exceptions: Data excludes personnel not on active duty, therefore it underestimates the share of the labor force working for the defense establishment. The cooperation of governments of all countries listed in \u201cThe Military Balance\u201d has been sought by IISS and, in many cases, received. However, some data in \u201cThe Military Balance\u201d is estimated.\n\nStatistical concept and methodology: Military data on manpower represent quantitative assessment of the personnel strengths of the world's armed forces. The IISS collects the data from a wide variety of sources. The numbers are based on the most accurate data available to, or on the best estimate that can be made by the International Institute for Strategic Studies (IISS) at the time of its annual publication. The current WDI indicator includes active armed forces and active paramilitary (but not reservists). Armed forces personnel comprise all servicemen and women on full-time duty, including conscripts and long-term assignments from the Reserves (\u201cReserve\u201d describes formations and units not fully manned or operational in peacetime, but which can be mobilized by recalling reservists in an emergency). The indicator includes paramilitary forces. The source of the data (IISS) reports armed forces and paramilitary forces separately, however these figures are added for the purpose of computing this series. Home Guard units are counted as paramilitary.", "origins": [ { "producer": "International Institute for Strategic Studies (via World Bank)", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } }, { "producer": "Various sources", "title": "Population", "description": "Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on various sources.\n\nYou can find more information on these sources and how our time series is constructed on this page: https://ourworldindata.org/population-sources", "citation_full": "The long-run data on population is based on various sources, described on this page: https://ourworldindata.org/population-sources", "attribution": "Population based on various sources (2024)", "attribution_short": "Population", "url_main": "https://ourworldindata.org/population-sources", "date_accessed": "2026-03-31", "date_published": "2024-07-15", "license": { "name": "CC BY 4.0", "url": "https://creativecommons.org/licenses/by/4.0/" } } ], "unit": "%", "short_unit": "%", "display": { "numDecimalPlaces": 1 }, "processing_level": "minor", "description_processing": "We estimated this indicator by dividing the total number of armed forces personnel by the total population. The population estimates come from a long-run dataset [maintained by Our World in Data](https://ourworldindata.org/population-sources)." }, "si_rmt_cost_ib_zs": { "title": "Average transaction cost of sending remittances to a specific country (%)", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } }, { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%", "description_processing": "We calculated the average transaction cost for sending money to a region by calculating total volume of incoming transactions and the total associated costs (assuming average transaction costs). We then divided the total costs by the total volume of transactions to get the average transaction cost. This indicator is only available if cost data is available for more than 75% of the total volume of transactions." }, "si_rmt_cost_ob_zs": { "title": "Average transaction cost of sending remittances from a specific country (%)", "origins": [ { "producer": "World Bank", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } }, { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "%", "short_unit": "%", "description_processing": "We calculated the average transaction cost for sending money from a region by calculating total volume of outgoing transactions and the total associated costs (assuming average transaction costs). We then divided the total costs by the total volume of transactions to get the average transaction cost. This indicator is only available if cost data is available for more than 75% of the total volume of transactions." }, "bx_trf_pwkr_cd_dt": { "title": "Personal remittances, received (current US$)", "description_from_producer": "Personal remittances comprise personal transfers and compensation of employees. Personal transfers consist of all current transfers in cash or in kind made or received by resident households to or from nonresident households. Personal transfers thus include all current transfers between resident and nonresident individuals. Compensation of employees refers to the income of border, seasonal, and other short-term workers who are employed in an economy where they are not resident and of residents employed by nonresident entities. Data are the sum of two items defined in the sixth edition of the IMF's Balance of Payments Manual: personal transfers and compensation of employees. Data are in current U.S. dollars.\n\nLimitations and exceptions: Remittance transactions have grown in importance over the past decade. In a number of developing economies, receipts of remittances have become an important and stable source of funds that exceeds receipts from exports of goods and services or from financial inflows on foreign direct investment. But the quality of statistical remittance data is not high. Remittances are a challenge to measure because of their nature. They are heterogeneous with numerous small transactions conducted by individuals through a wide variety of channels: formal channels, such as electronic wire, or through informal channels, such as cash or goods carried across borders. The large number of remittance transactions and the multitude of channels pose challenges to the compilation of comprehensive statistics. The small size of individual transactions means that they often go undetected by typical data source systems, although the aggregate level of transactions may be substantial.\n\nBecause of difficulties in obtaining data on informal remittance transactions, the remittance transactions undertaken through informal channels are sometimes not well covered in current balance of payments data. As a result, even though direct measurement of remittances - through transactions reporting or surveys - may be considered preferable if feasible, some countries instead combine different sources and estimation methods to achieve better coverage, by using direct measurements where practical and supplemented estimates where they are not. Model-based approaches are used in some countries as they are flexible. Compilers can design models to fill gaps in data sources or to provide global totals.\n\nHowever, only reliable input data can lead to sound estimates, regardless of the sophistication of an estimation method or econometric model. Indirect data are converted to remittance estimates using a set of assumptions. These assumptions should be plausible, but it is often not possible to test or verify these assumptions and also the results in practice.\n\nStatistical concept and methodology: The two main components of personal remittances, \"personal transfers\" and \"compensation of employees\", are items in the balance of payments (BPM6) framework. Both of these standard components are recorded in the current account.\n\"Personal transfers\", a new item in the Balance of Payments (BPM6) represents a broader definition of worker remittances. Personal transfers include all current transfers in cash or in kind between resident and nonresident individuals, independent of the source of income of the sender (irrespective of whether the sender receives income from labor, entrepreneurial or property income, social benefits, and any other types of transfers; or disposes assets) and the relationship between the households (irrespective of whether they are related or unrelated individuals).\n\nCompensation of employees refers to the income of border, seasonal, and other short-term workers who are employed in an economy where they are not resident and of residents employed by nonresident entities. Compensation of employees represents remuneration in return for the labor input to the production process contributed by an individual in an employer-employee relationship with the enterprise. Compensation of employees is recorded gross and includes amounts paid by the employee as taxes or for other purposes in the economy where the work is performed. Compensation of employees has three main components: wages and salaries in cash, wages and salaries in kind, and employers' social contributions.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" }, "bm_trf_pwkr_cd_dt": { "title": "Personal remittances, paid (current US$)", "description_from_producer": "Personal remittances comprise personal transfers and compensation of employees. Personal transfers consist of all current transfers in cash or in kind made or received by resident households to or from nonresident households. Personal transfers thus include all current transfers between resident and nonresident individuals. Compensation of employees refers to the income of border, seasonal, and other short-term workers who are employed in an economy where they are not resident and of residents employed by nonresident entities. Data are the sum of two items defined in the sixth edition of the IMF's Balance of Payments Manual: personal transfers and compensation of employees. Data are in current U.S. dollars.\n\nLimitations and exceptions: Remittance transactions have grown in importance over the past decade. In a number of developing economies, receipts of remittances have become an important and stable source of funds that exceeds receipts from exports of goods and services or from financial inflows on foreign direct investment. But the quality of statistical remittance data is not high. Remittances are a challenge to measure because of their nature. They are heterogeneous with numerous small transactions conducted by individuals through a wide variety of channels: formal channels, such as electronic wire, or through informal channels, such as cash or goods carried across borders. The large number of remittance transactions and the multitude of channels pose challenges to the compilation of comprehensive statistics. The small size of individual transactions means that they often go undetected by typical data source systems, although the aggregate level of transactions may be substantial.\n\nBecause of difficulties in obtaining data on informal remittance transactions, the remittance transactions undertaken through informal channels are sometimes not well covered in current balance of payments data. As a result, even though direct measurement of remittances - through transactions reporting or surveys - may be considered preferable if feasible, some countries instead combine different sources and estimation methods to achieve better coverage, by using direct measurements where practical and supplemented estimates where they are not. Model-based approaches are used in some countries as they are flexible. Compilers can design models to fill gaps in data sources or to provide global totals.\n\nHowever, only reliable input data can lead to sound estimates, regardless of the sophistication of an estimation method or econometric model. Indirect data are converted to remittance estimates using a set of assumptions. These assumptions should be plausible, but it is often not possible to test or verify these assumptions and also the results in practice.\n\nStatistical concept and methodology: The two main components of personal remittances, \"personal transfers\" and \"compensation of employees\", are items in the balance of payments (BPM6) framework. Both of these standard components are recorded in the current account.\n\"Personal transfers,\" a new item in the Balance of Payments (BPM6) represents a broader definition of worker remittances. Personal transfers include all current transfers in cash or in kind between resident and nonresident individuals, independent of the source of income of the sender (irrespective of whether the sender receives income from labor, entrepreneurial or property income, social benefits, and any other types of transfers; or disposes assets) and the relationship between the households (irrespective of whether they are related or unrelated individuals).\n\nCompensation of employees refers to the income of border, seasonal, and other short-term workers who are employed in an economy where they are not resident and of residents employed by nonresident entities. Compensation of employees represents remuneration in return for the labor input to the production process contributed by an individual in an employer-employee relationship with the enterprise. Compensation of employees is recorded gross and includes amounts paid by the employee as taxes or for other purposes in the economy where the work is performed. Compensation of employees has three main components: wages and salaries in cash, wages and salaries in kind, and employers' social contributions.", "origins": [ { "producer": "World Bank based on data from the International Monetary Fund", "title": "World Development Indicators", "description": "The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.", "citation_full": "World Bank's World Development Indicators (WDI).", "attribution": "Multiple sources compiled by World Bank (2024)", "url_main": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "url_download": "http://databank.worldbank.org/data/download/WDI_csv.zip", "date_accessed": "2024-05-20", "date_published": "2024-05-20", "license": { "name": "Creative Commons Attribution 4.0" } } ], "unit": "current US$", "short_unit": "$" } } }