{"id": 1291244, "name": "Share of employment in agriculture", "unit": "%", "createdAt": "2026-07-14T15:28:11.000Z", "updatedAt": "2026-07-14T15:28:11.000Z", "coverage": "", "timespan": "1300-2025", "datasetId": 8065, "shortUnit": "%", "columnOrder": 0, "shortName": "share_employed_agriculture", "catalogPath": "grapher/growth/2026-07-02/structural_transformation_omm/structural_transformation_omm#share_employed_agriculture", "descriptionShort": "Share of working people employed in agriculture, including hunting, forestry and fishing.", "descriptionFromProducer": "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\n### Aggregation method:\nWeighted average\n\n### Statistical concept and methodology:\nMethodology: The 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\nStatistical concept(s): 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\n### Development relevance:\nSectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labor flows from agriculture and other labor-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas.\n\nThe breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment.\nSegregating one sex in a narrow range of occupations significantly reduces economic efficiency by reducing labor market flexibility and thus the economy's ability to adapt to change. This segregation is particularly harmful for women, who have a much narrower range of labor market choices and lower levels of pay than men. But it is also detrimental to men when job losses are concentrated in industries dominated by men and job growth is centered in service occupations, where women have better chances, as has been the recent experience in many countries.\n\n### Limitations and exceptions:\nThere 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.", "descriptionProcessing": "This indicator combines two series published by the World Bank's World Development Indicators: ILO-modeled employment shares, available from 1991 onwards, and \u2014 for France, Italy, the Netherlands, Poland and the United Kingdom \u2014 employment shares around 1980 from an archived edition, which the World Bank later replaced with the ILO-modeled series.\n\nFor the same five countries, benchmark estimates of the share of the labor force employed in agriculture between 1300 and 1800 come from Broadberry and Gardner (2013).", "type": "float", "datasetName": "Long-run data on employment by economic sector", "updatePeriodDays": 365, "datasetVersion": "2026-07-02", "nonRedistributable": false, "display": {"name": "Agriculture", "unit": "%", "shortUnit": "%", "numDecimalPlaces": 1}, "schemaVersion": 2, "processingLevel": "major", "presentation": {"titlePublic": "Share of employment in agriculture", "attributionShort": "ILO", "topicTagsLinks": ["Employment in Agriculture", "Economic Growth"]}, "descriptionKey": ["Recent estimates (from 1991) are ILO-modeled estimates published by the World Bank, measuring agricultural employment as a share of total employment.", "For five European countries (France, Italy, the Netherlands, Poland and the United Kingdom), earlier values around 1980 come from an archived edition of the World Development Indicators, which the World Bank later replaced with the ILO-modeled series.", "For the same five countries, benchmark estimates between 1300 and 1800 come from Broadberry and Gardner (2013); these measure the share of the total labor force, which also includes unemployed people."], "dimensions": {"years": {"values": [{"id": 1991}, {"id": 1992}, {"id": 1993}, {"id": 1994}, {"id": 1995}, {"id": 1996}, {"id": 1997}, {"id": 1998}, {"id": 1999}, {"id": 2000}, {"id": 2001}, {"id": 2002}, {"id": 2003}, {"id": 2004}, {"id": 2005}, {"id": 2006}, {"id": 2007}, {"id": 2008}, {"id": 2009}, {"id": 2010}, {"id": 2011}, {"id": 2012}, {"id": 2013}, {"id": 2014}, {"id": 2015}, {"id": 2016}, {"id": 2017}, {"id": 2018}, {"id": 2019}, {"id": 2020}, {"id": 2021}, {"id": 2022}, {"id": 2023}, {"id": 2024}, {"id": 2025}, {"id": 1400}, {"id": 1500}, {"id": 1600}, {"id": 1700}, {"id": 1750}, {"id": 1800}, {"id": 1980}, {"id": 1300}, {"id": 1981}]}, "entities": {"values": [{"id": 15, "name": "Afghanistan", "code": "AFG"}, {"id": 16, "name": "Albania", "code": "ALB"}, {"id": 17, "name": "Algeria", "code": "DZA"}, {"id": 19, "name": "Angola", "code": "AGO"}, {"id": 21, "name": "Argentina", "code": "ARG"}, {"id": 22, "name": "Armenia", "code": "ARM"}, {"id": 23, "name": "Australia", "code": "AUS"}, {"id": 24, "name": "Austria", "code": "AUT"}, {"id": 25, "name": "Azerbaijan", "code": "AZE"}, {"id": 26, "name": "Bahamas", "code": "BHS"}, {"id": 27, "name": "Bahrain", "code": "BHR"}, {"id": 28, "name": "Bangladesh", "code": "BGD"}, {"id": 29, "name": "Barbados", "code": "BRB"}, {"id": 30, "name": "Belarus", "code": "BLR"}, {"id": 4, "name": "Belgium", "code": "BEL"}, {"id": 31, "name": "Belize", "code": "BLZ"}, {"id": 32, "name": "Benin", "code": "BEN"}, {"id": 33, "name": "Bhutan", "code": "BTN"}, {"id": 34, "name": "Bolivia", "code": "BOL"}, {"id": 35, "name": "Bosnia and Herzegovina", "code": "BIH"}, {"id": 36, "name": "Botswana", "code": "BWA"}, {"id": 37, "name": "Brazil", "code": "BRA"}, {"id": 38, "name": "Brunei", "code": "BRN"}, {"id": 39, "name": "Bulgaria", "code": "BGR"}, {"id": 40, "name": "Burkina Faso", "code": "BFA"}, {"id": 41, "name": "Burundi", "code": "BDI"}, {"id": 42, "name": "Cambodia", "code": "KHM"}, {"id": 43, "name": "Cameroon", "code": "CMR"}, {"id": 44, "name": "Canada", "code": "CAN"}, {"id": 45, "name": "Cape Verde", "code": "CPV"}, {"id": 174, "name": "Central African Republic", "code": "CAF"}, {"id": 173, "name": "Chad", "code": "TCD"}, {"id": 304, "name": "Channel Islands", "code": "OWID_CIS"}, {"id": 172, "name": "Chile", "code": "CHL"}, {"id": 171, "name": "China", "code": "CHN"}, {"id": 170, "name": "Colombia", "code": "COL"}, {"id": 169, "name": "Comoros", "code": "COM"}, {"id": 168, "name": "Congo", "code": "COG"}, {"id": 166, "name": "Costa Rica", "code": "CRI"}, {"id": 143, "name": "Cote d'Ivoire", "code": "CIV"}, {"id": 165, "name": "Croatia", "code": "HRV"}, {"id": 164, "name": "Cuba", "code": "CUB"}, {"id": 163, "name": "Cyprus", "code": "CYP"}, {"id": 162, "name": "Czechia", "code": "CZE"}, {"id": 167, "name": "Democratic Republic of Congo", "code": "COD"}, {"id": 161, "name": "Denmark", "code": "DNK"}, {"id": 154, "name": "Djibouti", "code": "DJI"}, {"id": 160, "name": "Dominican Republic", "code": "DOM"}, {"id": 349172, "name": "East Asia and Pacific (WB)", "code": "WB_EAP"}, {"id": 225, "name": "East Timor", "code": "TLS"}, {"id": 201, "name": "Ecuador", "code": "ECU"}, {"id": 65, "name": "Egypt", "code": "EGY"}, {"id": 259, "name": "El Salvador", "code": "SLV"}, {"id": 159, "name": "Equatorial Guinea", "code": "GNQ"}, {"id": 157, "name": "Eritrea", "code": "ERI"}, {"id": 156, "name": "Estonia", "code": "EST"}, {"id": 78, "name": "Eswatini", "code": "SWZ"}, {"id": 158, "name": "Ethiopia", "code": "ETH"}, {"id": 349171, "name": "Europe and Central Asia (WB)", "code": "WB_ECA"}, {"id": 115117, "name": "European Union (27)", "code": "OWID_EU27"}, {"id": 202, "name": "Fiji", "code": "FJI"}, {"id": 155, "name": "Finland", "code": "FIN"}, {"id": 3, "name": "France", "code": "FRA"}, {"id": 203, "name": "French Polynesia", "code": "PYF"}, {"id": 153, "name": "Gabon", "code": "GAB"}, {"id": 151, "name": "Gambia", "code": "GMB"}, {"id": 152, "name": "Georgia", "code": "GEO"}, {"id": 6, "name": "Germany", "code": "DEU"}, {"id": 150, "name": "Ghana", "code": "GHA"}, {"id": 149, "name": "Greece", "code": "GRC"}, {"id": 254, "name": "Guam", "code": "GUM"}, {"id": 148, "name": "Guatemala", "code": "GTM"}, {"id": 147, "name": "Guinea", "code": "GIN"}, {"id": 94, "name": "Guinea-Bissau", "code": "GNB"}, {"id": 146, "name": "Guyana", "code": "GUY"}, {"id": 145, "name": "Haiti", "code": "HTI"}, {"id": 457, "name": "High-income countries", "code": "OWID_HIC"}, {"id": 139, "name": "Honduras", "code": "HND"}, {"id": 144, "name": "Hong Kong", "code": "HKG"}, {"id": 138, "name": "Hungary", "code": "HUN"}, {"id": 207, "name": "Iceland", "code": "ISL"}, {"id": 137, "name": "India", "code": "IND"}, {"id": 136, "name": "Indonesia", "code": "IDN"}, {"id": 135, "name": "Iran", "code": "IRN"}, {"id": 134, "name": "Iraq", "code": "IRQ"}, {"id": 2, "name": "Ireland", "code": "IRL"}, {"id": 133, "name": "Israel", "code": "ISR"}, {"id": 8, "name": "Italy", "code": "ITA"}, {"id": 132, "name": "Jamaica", "code": "JAM"}, {"id": 14, "name": "Japan", "code": "JPN"}, {"id": 130, "name": "Jordan", "code": "JOR"}, {"id": 131, "name": "Kazakhstan", "code": "KAZ"}, {"id": 129, "name": "Kenya", "code": "KEN"}, {"id": 208, "name": "Kuwait", "code": "KWT"}, {"id": 126, "name": "Kyrgyzstan", "code": "KGZ"}, {"id": 125, "name": "Laos", "code": "LAO"}, {"id": 349170, "name": "Latin America and Caribbean (WB)", "code": "WB_LAC"}, {"id": 122, "name": "Latvia", "code": "LVA"}, {"id": 124, "name": "Lebanon", "code": "LBN"}, {"id": 123, "name": "Lesotho", "code": "LSO"}, {"id": 121, "name": "Liberia", "code": "LBR"}, {"id": 120, "name": "Libya", "code": "LBY"}, {"id": 119, "name": "Lithuania", "code": "LTU"}, {"id": 461, "name": "Low-income countries", "code": "OWID_LIC"}, {"id": 460, "name": "Lower-middle-income countries", "code": "OWID_LMC"}, {"id": 210, "name": "Luxembourg", "code": "LUX"}, {"id": 262, "name": "Macao", "code": "MAC"}, {"id": 118, "name": "Madagascar", "code": "MDG"}, {"id": 117, "name": "Malawi", "code": "MWI"}, {"id": 116, "name": "Malaysia", "code": "MYS"}, {"id": 211, "name": "Maldives", "code": "MDV"}, {"id": 115, "name": "Mali", "code": "MLI"}, {"id": 212, "name": "Malta", "code": "MLT"}, {"id": 114, "name": "Mauritania", "code": "MRT"}, {"id": 213, "name": "Mauritius", "code": "MUS"}, {"id": 113, "name": "Mexico", "code": "MEX"}, {"id": 372001, "name": "Middle East, North Africa, Afghanistan and Pakistan (WB)", "code": "WB_MENAP"}, {"id": 111, "name": "Moldova", "code": "MDA"}, {"id": 112, "name": "Mongolia", "code": "MNG"}, {"id": 215, "name": "Montenegro", "code": "MNE"}, {"id": 110, "name": "Morocco", "code": "MAR"}, {"id": 109, "name": "Mozambique", "code": "MOZ"}, {"id": 142, "name": "Myanmar", "code": "MMR"}, {"id": 108, "name": "Namibia", "code": "NAM"}, {"id": 107, "name": "Nepal", "code": "NPL"}, {"id": 5, "name": "Netherlands", "code": "NLD"}, {"id": 220, "name": "New Caledonia", "code": "NCL"}, {"id": 106, "name": "New Zealand", "code": "NZL"}, {"id": 105, "name": "Nicaragua", "code": "NIC"}, {"id": 104, "name": "Niger", "code": "NER"}, {"id": 103, "name": "Nigeria", "code": "NGA"}, {"id": 278896, "name": "North America (WB)", "code": "WB_NA"}, {"id": 128, "name": "North Korea", "code": "PRK"}, {"id": 66, "name": "North Macedonia", "code": "MKD"}, {"id": 102, "name": "Norway", "code": "NOR"}, {"id": 217, "name": "Oman", "code": "OMN"}, {"id": 101, "name": "Pakistan", "code": "PAK"}, {"id": 140, "name": "Palestine", "code": "PSE"}, {"id": 100, "name": "Panama", "code": "PAN"}, {"id": 99, "name": "Papua New Guinea", "code": "PNG"}, {"id": 98, "name": "Paraguay", "code": "PRY"}, {"id": 97, "name": "Peru", "code": "PER"}, {"id": 96, "name": "Philippines", "code": "PHL"}, {"id": 11, "name": "Poland", "code": "POL"}, {"id": 95, "name": "Portugal", "code": "PRT"}, {"id": 93, "name": "Puerto Rico", "code": "PRI"}, {"id": 226, "name": "Qatar", "code": "QAT"}, {"id": 92, "name": "Romania", "code": "ROU"}, {"id": 12, "name": "Russia", "code": "RUS"}, {"id": 91, "name": "Rwanda", "code": "RWA"}, {"id": 229, "name": "Saint Lucia", "code": "LCA"}, {"id": 230, "name": "Saint Vincent and the Grenadines", "code": "VCT"}, {"id": 239, "name": "Samoa", "code": "WSM"}, {"id": 232, "name": "Sao Tome and Principe", "code": "STP"}, {"id": 90, "name": "Saudi Arabia", "code": "SAU"}, {"id": 89, "name": "Senegal", "code": "SEN"}, {"id": 88, "name": "Serbia", "code": "SRB"}, {"id": 87, "name": "Sierra Leone", "code": "SLE"}, {"id": 86, "name": "Singapore", "code": "SGP"}, {"id": 85, "name": "Slovakia", "code": "SVK"}, {"id": 83, "name": "Slovenia", "code": "SVN"}, {"id": 195, "name": "Solomon Islands", "code": "SLB"}, {"id": 82, "name": "Somalia", "code": "SOM"}, {"id": 81, "name": "South Africa", "code": "ZAF"}, {"id": 277956, "name": "South Asia (WB)", "code": "WB_SA"}, {"id": 127, "name": "South Korea", "code": "KOR"}, {"id": 258, "name": "South Sudan", "code": "SSD"}, {"id": 9, "name": "Spain", "code": "ESP"}, {"id": 141, "name": "Sri Lanka", "code": "LKA"}, {"id": 277950, "name": "Sub-Saharan Africa (WB)", "code": "WB_SSA"}, {"id": 79, "name": "Sudan", "code": "SDN"}, {"id": 234, "name": "Suriname", "code": "SUR"}, {"id": 10, "name": "Sweden", "code": "SWE"}, {"id": 7, "name": "Switzerland", "code": "CHE"}, {"id": 77, "name": "Syria", "code": "SYR"}, {"id": 76, "name": "Tajikistan", "code": "TJK"}, {"id": 64, "name": "Tanzania", "code": "TZA"}, {"id": 75, "name": "Thailand", "code": "THA"}, {"id": 74, "name": "Togo", "code": "TGO"}, {"id": 235, "name": "Tonga", "code": "TON"}, {"id": 73, "name": "Trinidad and Tobago", "code": "TTO"}, {"id": 71, "name": "Tunisia", "code": "TUN"}, {"id": 70, "name": "Turkey", "code": "TUR"}, {"id": 69, "name": "Turkmenistan", "code": "TKM"}, {"id": 68, "name": "Uganda", "code": "UGA"}, {"id": 67, "name": "Ukraine", "code": "UKR"}, {"id": 72, "name": "United Arab Emirates", "code": "ARE"}, {"id": 1, "name": "United Kingdom", "code": "GBR"}, {"id": 13, "name": "United States", "code": "USA"}, {"id": 256, "name": "United States Virgin Islands", "code": "VIR"}, {"id": 459, "name": "Upper-middle-income countries", "code": "OWID_UMC"}, {"id": 63, "name": "Uruguay", "code": "URY"}, {"id": 62, "name": "Uzbekistan", "code": "UZB"}, {"id": 221, "name": "Vanuatu", "code": "VUT"}, {"id": 238, "name": "Venezuela", "code": "VEN"}, {"id": 84, "name": "Vietnam", "code": "VNM"}, {"id": 355, "name": "World", "code": "OWID_WRL"}, {"id": 61, "name": "Yemen", "code": "YEM"}, {"id": 60, "name": "Zambia", "code": "ZMB"}, {"id": 80, "name": "Zimbabwe", "code": "ZWE"}]}}, "origins": [{"id": 13741, "title": "World Development Indicators", "description": "The World Development Indicators (WDI) database, published by the World Bank, is a comprehensive collection of global development data, providing key economic, social, and environmental statistics. It includes over 1,500 indicators covering more than 200 countries and territories, with data spanning several decades.WDI serves as a vital resource for policymakers, researchers, businesses, and analysts seeking to understand global trends and make data-driven decisions. The database covers a wide range of topics, including economic growth, education, health, poverty, trade, energy, infrastructure, governance, and environmental sustainability.The indicators are sourced from reputable national and international agencies, ensuring high-quality, consistent, and comparable data. Users can access the database through interactive online tools, API services, and downloadable datasets, facilitating detailed analysis and visualization.WDI is also used for tracking progress on the Sustainable Development Goals (SDGs) and other global development initiatives. By providing accessible and reliable statistics, it helps to inform policy discussions and strategies globally.Whether for academic research, policy planning, or economic analysis, the World Development Indicators database is an essential tool for understanding and addressing global development challenges.", "producer": "ILO Modelled Estimates, via World Bank", "citationFull": "ILO Modelled Estimates database (ILOEST), International Labour Organization (ILO), uri: https://ilostat.ilo.org/data/bulk/, publisher: ILOSTAT, type: external database, date accessed: January 17, 2026. Indicator SL.AGR.EMPL.ZS (https://data.worldbank.org/indicator/SL.AGR.EMPL.ZS). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.", "versionProducer": "125", "urlMain": "https://data.worldbank.org/indicator/SL.AGR.EMPL.ZS", "urlDownload": "https://databankfiles.worldbank.org/public/ddpext_download/WDI_CSV.zip", "dateAccessed": "2026-02-27", "datePublished": "2026-01-28", "license": {"url": "https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators", "name": "CC BY 4.0"}}, {"id": 15766, "titleSnapshot": "Africa's Growth Prospects in a European Mirror - Agricultural labor force shares", "title": "Africa's Growth Prospects in a European Mirror", "descriptionSnapshot": "Benchmark estimates of the share of the labor force employed in agriculture in five European countries (Great Britain, France, Italy, the Netherlands and Poland) between 1300 and 1800, as reported in Table 3 of the paper. The estimates draw on historical reconstructions of the sectoral distribution of the labor force: Broadberry, Campbell and van Leeuwen (2013) for Britain and Allen (2000) for other European countries.\n\nThe estimates were transcribed from the paper by Our World in Data. Estimates for England/Great Britain are labeled as United Kingdom.", "description": "Drawing on recent quantitative research on Europe reaching back to the medieval period, and noting a relationship between the quality of institutions and economic growth, this paper offers a reassessment of Africa's growth prospects. Periods of positive growth driven by trade, followed by growth reversals which wiped out the gains of the previous boom, characterized pre-modern Europe as well as twentieth century Africa. Since per capita incomes in much of sub-Saharan Africa are currently at the level of medieval Europe, which did not make the breakthrough to modern economic growth until the nineteenth century, we caution against too optimistic a reading of Africa's recent growth experience. Without the institutional changes necessary to facilitate structural change, growth reversals continue to pose a serious threat to African prosperity. Only if growth continues after a downturn in Africa's terms of trade can we be sure that the corner has been turned.", "producer": "Broadberry and Gardner", "citationFull": "Broadberry, Stephen and Gardner, Leigh (2013) Africa's growth prospects in a European mirror: a historical perspective. Working Paper. Coventry, UK: Department of Economics, University of Warwick. (CAGE Online Working Paper Series No. 172).", "urlMain": "https://wrap.warwick.ac.uk/59340/", "dateAccessed": "2026-07-13", "datePublished": "2013-09-27", "license": {"url": "https://wrap.warwick.ac.uk/59340/", "name": "\u00a9 Broadberry and Gardner (2013)"}}, {"id": 15767, "titleSnapshot": "World Development Indicators (archived release) - Employment shares by sector around 1980", "title": "World Development Indicators (archived release)", "descriptionSnapshot": "Employment shares in agriculture, industry and services used to connect pre-industrial benchmark estimates with the modern series: the earliest values available around 1980 for France, Italy and the United Kingdom (1980) and for the Netherlands and Poland (1981, with 1980 unavailable). All values verified against the April 2013 edition in the World Bank's WDI Database Archives; the same values also appear in the World Development Indicators extract preserved in the data files of Herrendorf, Rogerson and Valentinyi (2014) (WDISectorData.xls, saved in September 2011).", "description": "The indicators \"Employment in agriculture (% of total employment)\", \"Employment in industry (% of total employment)\" and \"Employment in services (% of total employment)\" as published in archived editions of the World Bank's World Development Indicators, based on the International Labor Organization's labor force statistics. The World Bank later replaced these series with ILO-modeled estimates that begin in 1991, removing the earlier observations from the current World Development Indicators; the superseded editions remain available in the WDI Database Archives.", "producer": "International Labor Organization (via World Bank)", "citationFull": "International Labor Organization, \"Employment in agriculture/industry/services (% of total employment),\" World Development Indicators, The World Bank (archived edition of April 2013, WDI Database Archives).", "urlMain": "https://databank.worldbank.org/source/wdi-database-archives", "dateAccessed": "2026-07-13", "datePublished": "2013", "license": {"url": "https://datacatalog.worldbank.org/public-licenses", "name": "CC BY 4.0"}}]}