{"id": 1289239, "name": "Share of employment in agriculture", "unit": "%", "createdAt": "2026-07-02T15:12:05.000Z", "updatedAt": "2026-07-03T14:12:58.000Z", "coverage": "", "timespan": "1300-2025", "datasetId": 8031, "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 sources: recent estimates from the World Bank's World Development Indicators, and a compilation of historical sources built by Our World in Data, based on the dataset published by Herrendorf, Rogerson and Valentinyi (2014) and updated with the GGDC 10-Sector Database (January 2015 release) and the Swedish Historical National Accounts. For each country, World Bank data is used from its first available year onwards; historical sources only inform earlier years. To preserve a consistent series between the historical estimates and the World Bank data available from 1991 onwards, the years 1986-1990 are not included.\n\nEmployment shares before the first World Bank year are calculated from the compilation's employment numbers, as agricultural employment divided by total employment across the three sectors. Benchmark estimates of the share of the labor force in agriculture from Broadberry and Gardner (2013) are used for years and countries the compilation does not cover.", "type": "float", "dataChecksum": "2736895420623096020", "metadataChecksum": "-4435304717586940558", "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.", "Earlier estimates for ten of today's rich countries are derived from historical reconstructions of the number of people working in each sector. For five European countries, benchmark estimates from Broadberry and Gardner (2013) reach back as far as 1300; 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": 1846}, {"id": 1856}, {"id": 1866}, {"id": 1880}, {"id": 1890}, {"id": 1900}, {"id": 1910}, {"id": 1920}, {"id": 1930}, {"id": 1947}, {"id": 1961}, {"id": 1970}, {"id": 1971}, {"id": 1972}, {"id": 1973}, {"id": 1974}, {"id": 1975}, {"id": 1976}, {"id": 1977}, {"id": 1978}, {"id": 1979}, {"id": 1980}, {"id": 1981}, {"id": 1982}, {"id": 1983}, {"id": 1984}, {"id": 1985}, {"id": 1805}, {"id": 1940}, {"id": 1950}, {"id": 1960}, {"id": 1400}, {"id": 1500}, {"id": 1600}, {"id": 1700}, {"id": 1750}, {"id": 1800}, {"id": 1886}, {"id": 1896}, {"id": 1901}, {"id": 1906}, {"id": 1911}, {"id": 1921}, {"id": 1926}, {"id": 1931}, {"id": 1936}, {"id": 1946}, {"id": 1954}, {"id": 1962}, {"id": 1968}, {"id": 1300}, {"id": 1872}, {"id": 1953}, {"id": 1955}, {"id": 1956}, {"id": 1957}, {"id": 1958}, {"id": 1959}, {"id": 1963}, {"id": 1964}, {"id": 1965}, {"id": 1966}, {"id": 1967}, {"id": 1969}, {"id": 1807}, {"id": 1849}, {"id": 1859}, {"id": 1889}, {"id": 1899}, {"id": 1909}, {"id": 1949}, {"id": 1860}, {"id": 1877}, {"id": 1887}, {"id": 1850}, {"id": 1851}, {"id": 1852}, {"id": 1853}, {"id": 1854}, {"id": 1855}, {"id": 1857}, {"id": 1858}, {"id": 1861}, {"id": 1862}, {"id": 1863}, {"id": 1864}, {"id": 1865}, {"id": 1867}, {"id": 1868}, {"id": 1869}, {"id": 1870}, {"id": 1871}, {"id": 1873}, {"id": 1874}, {"id": 1875}, {"id": 1876}, {"id": 1878}, {"id": 1879}, {"id": 1881}, {"id": 1882}, {"id": 1883}, {"id": 1884}, {"id": 1885}, {"id": 1888}, {"id": 1891}, {"id": 1892}, {"id": 1893}, {"id": 1894}, {"id": 1895}, {"id": 1897}, {"id": 1898}, {"id": 1902}, {"id": 1903}, {"id": 1904}, {"id": 1905}, {"id": 1907}, {"id": 1908}, {"id": 1912}, {"id": 1913}, {"id": 1914}, {"id": 1915}, {"id": 1916}, {"id": 1917}, {"id": 1918}, {"id": 1919}, {"id": 1922}, {"id": 1923}, {"id": 1924}, {"id": 1925}, {"id": 1927}, {"id": 1928}, {"id": 1929}, {"id": 1932}, {"id": 1933}, {"id": 1934}, {"id": 1935}, {"id": 1937}, {"id": 1938}, {"id": 1939}, {"id": 1941}, {"id": 1942}, {"id": 1943}, {"id": 1944}, {"id": 1945}, {"id": 1948}, {"id": 1951}, {"id": 1952}, {"id": 1801}, {"id": 1841}, {"id": 1840}]}, "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": 15633, "titleSnapshot": "Growth and Structural Transformation - dataset", "title": "Growth and Structural Transformation", "descriptionSnapshot": "Data files accompanying the chapter, including long-run historical time series of employment and value added (at current prices) by sector for ten currently rich countries: Belgium, Finland, France, Japan, the Netherlands, South Korea, Spain, Sweden, the United Kingdom and the United States. Economic activities are classified into agriculture, industry and services; following the authors' convention, utilities are included within services rather than industry.\n\nThe authors' website hosting the data is no longer online, so the file is retrieved from the Internet Archive's capture of it.", "description": "Structural transformation refers to the reallocation of economic activity across the broad sectors agriculture, manufacturing and services. This review article synthesizes and evaluates recent advances in the research on structural transformation. We begin by presenting the stylized facts of structural transformation across time and space. We then develop a multi-sector extension of the one-sector growth model that encompasses the main existing theories of structural transformation. We argue that this multi-sector model serves as a natural benchmark to study structural transformation and that it is able to account for many salient features of structural transformation. We also argue that this multi-sector model delivers new and sharper insights for understanding economic development, regional income convergence, aggregate productivity trends, hours worked, business cycles, and wage inequality. We conclude by suggesting several directions for future research on structural transformation.", "producer": "Herrendorf, Rogerson and Valentinyi", "citationFull": "Berthold Herrendorf, Richard Rogerson, and \u00c1kos Valentinyi, \"Growth and Structural Transformation,\" NBER Working Paper 18996 (2013), https://doi.org/10.3386/w18996.\n\nPublished as: Herrendorf, B., Rogerson, R., & Valentinyi, \u00c1. (2014). Growth and Structural Transformation. In P. Aghion & S. N. Durlauf (Eds.), Handbook of Economic Growth (Vol. 2, pp. 855-941). Elsevier.", "urlMain": "https://www.nber.org/papers/w18996", "urlDownload": "https://web.archive.org/web/20201012224826id_/https://sites.google.com/site/valentinyiakos/Home/files/Handbook_data.zip?attredirects=0&d=1", "dateAccessed": "2026-07-02", "datePublished": "2014", "license": {"url": "https://www.sciencedirect.com/science/article/abs/pii/B9780444535405000069", "name": "\u00a9 Herrendorf, Rogerson and Valentinyi (2014)"}}, {"id": 15630, "title": "GGDC 10-Sector Database", "description": "The GGDC 10-Sector Database provides a long-run internationally comparable dataset on sectoral productivity performance in Africa, Asia, and Latin America. Variables covered in the data set are annual series of value added, output deflators, and persons employed for 10 broad sectors.\n\nThe GGDC 10-Sector Database gives sector detail to the historical macro data in Maddison (2003) from 1950 onwards. It consists of series for 11 countries in Africa, 11 countries in Asia, 2 countries in the Middle East and North Africa, and 9 in Latin-America. For comparison, we have also added data for the US and several European countries.\n\nIt should be stressed that the estimates for the total economy are aggregated across sectors and that, because of adjustments at the sector level, the aggregate results are not fully consistent with the national accounts aggregates (see the sources and methods document). Also note that value added data in this database are expressed in local currencies.", "producer": "Timmer et al.", "citationFull": "Timmer, M. P., de Vries, G. J., & de Vries, K. (2015). \u201cPatterns of Structural Change in Developing Countries.\u201d . In J. Weiss, & M. Tribe (Eds.), Routledge Handbook of Industry and Development. (pp. 65-83). Routledge.", "attribution": "Timmer et al. \u2013 GGDC 10-Sector Database 2014", "attributionShort": "GGDC 10-Sector Database", "versionProducer": "2014 release, updated January 2015", "urlMain": "https://www.rug.nl/ggdc/structuralchange/previous-sector-database/10-sector-2014", "urlDownload": "https://www.rug.nl/ggdc/docs/10sd_jan15_2014.xlsx", "dateAccessed": "2026-07-02", "datePublished": "2015-01-01", "license": {"url": "https://www.rug.nl/ggdc/structuralchange/previous-sector-database/10-sector-2014", "name": "Free to use with citation"}}, {"id": 15634, "titleSnapshot": "Swedish Historical National Accounts - Employment by sector", "title": "Swedish Historical National Accounts", "descriptionSnapshot": "This file is Table VIII of the database: employment (number of persons) in the main sectors of the Swedish economy, 1850-2022. The main sectors are agriculture, manufacturing industry, building and construction, transport and communication, private services, and public services.", "description": "The Swedish Historical National Accounts 1560\u20132010, released in 2015 and updated in 2020, 2023 and 2025, presents a database with an extended and revised version of SHNA 1560\u20132022. Principles for revisions and extension of data 1560-1800 are found in Sch\u00f6n & Krantz (2015), \"New Swedish Historical National Accounts since the 16th Century in Constant and Current Prices\", Lund Papers in Economic History 140, Lund University.\n\nComprehensive accounts of data and revisions of the 2007 version of SHNA 1800-2000 are to be found as well in Sch\u00f6n & Krantz (2012), \"Swedish Historical National Accounts 1560\u20132010\", Lund Papers in Economic History 123, Lund University. Description and specification of the latest 2023 update can be found in Nilsson, et al. (2023), \"Swedish Historical National Accounts. 2023 Update, Revision and Underlying Principles\".", "producer": "Sch\u00f6n and Krantz", "citationFull": "Krantz, O. & Sch\u00f6n, L. (2007), Swedish Historical National Accounts 1800-2000, Lund Studies in Economic History 41, Lund.\n\nSch\u00f6n, L. & Krantz, O. (2012), \"Swedish Historical National Accounts 1560-2010.\" Lund Papers in Economic History 123, Lund University.\n\nSch\u00f6n, L. & Krantz, O. (2015), \"New Swedish Historical National Accounts since the 16th Century in Constant and Current Prices.\" Lund Papers in Economic History 140, Lund University.\n\nNilsson, C., Enflo, K., Lobell, H. and Krantz, O. (2023) \"Swedish Historical National Accounts. 2023 Update, Revision and Underlying Principles.\" Mimeo, Department of Economic History, Lund University.\n\nLobell, H. (2025) \"On the 2025 Update of SHNA 1993-2022.\" Mimeo, Department of Economic History, Lund University.", "versionProducer": "2025 update", "urlMain": "https://www.lusem.lu.se/organisation/department-economic-history/research-department-economic-history/databases-department-economic-history/economic-history-data/swedish-historical-national-accounts-1300-2022", "urlDownload": "https://lu.box.com/index.php?rm=box_download_shared_file&shared_name=j4p2qqem7wle8i6i8lppe96vexoya510&file_id=f_1799866718143", "dateAccessed": "2026-07-02", "datePublished": "2025", "license": {"url": "https://www.lusem.lu.se/organisation/department-economic-history/research-department-economic-history/databases-department-economic-history/economic-history-data/swedish-historical-national-accounts-1300-2022", "name": "Free to use with citation"}}, {"id": 15635, "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 1981, as reported in the paper. The estimates draw on historical reconstructions of the sectoral distribution of the labor force, including 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": "2026-07-02", "datePublished": "2013-09-27", "license": {"url": "https://wrap.warwick.ac.uk/59340/", "name": "\u00a9 Broadberry and Gardner (2013)"}}]}