{"id": 1205258, "name": "Employment to population ratio, 15+, female (%) (modeled ILO estimate)", "unit": "%", "createdAt": "2026-03-01T08:24:40.000Z", "updatedAt": "2026-03-01T08:24:40.000Z", "coverage": "", "timespan": "1991-2025", "datasetId": 7396, "shortUnit": "%", "columnOrder": 0, "shortName": "sl_emp_totl_sp_fe_zs", "catalogPath": "grapher/worldbank_wdi/2026-02-27/wdi/wdi#sl_emp_totl_sp_fe_zs", "descriptionShort": "Share of the female working-age population (ages 15 and older) who are employed.", "descriptionFromProducer": "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\n### Limitations and exceptions:\nData 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\n### Statistical concept and methodology:\nThe 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\n### Notes from original source:\nGiven the exceptional situation, including the scarcity of relevant data, the ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.", "type": "float", "grapherConfigIdETL": "019ca87f-e7d4-776e-81e9-3641f4707195", "datasetName": "World Development Indicators", "updatePeriodDays": 365, "datasetVersion": "2026-02-27", "nonRedistributable": false, "display": {"name": "Female employment rate", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1}, "schemaVersion": 2, "presentation": {"attributionShort": "ILO", "topicTagsLinks": ["Work & Employment"]}, "descriptionKey": ["This indicator is defined as the proportion of a country\u2019s working-age population that is employed. It is also known as the employment-to-population ratio. Employment refers to people who worked for at least an hour during the reference period (typically a week), whether in paid employment or self-employment. This indicator gives a broad sense of how many people in a country are working, regardless of the kind of job they have or how many hours they work.", "When defining the working-age population, the definition of \u201cworking age\u201d varies across countries, depending on national laws and practices. In the ILO modeled estimates shown here, this is harmonized to refer to people aged 15 and older.", "This data comes from the ILO Modelled Estimates series. [The International Labour Organization (ILO)](#dod:ilo) combines countries' own reported estimates with statistically modeled estimates when observations are missing. This improves comparability across countries and over time and allows the ILO to calculate regional and global aggregates for every year. You can read more about how the ILO produces these estimates in the [Modelled Estimates documentation](https://ilostat.ilo.org/methods/concepts-and-definitions/ilo-modelled-estimates/).", "This data follows the standards of the [13th International Classification of Labour Statisticians (ICLS)](#dod:13-icls). Under this framework, employment includes work for pay or profit, including self-employment, as well as the production of goods for own use (such as subsistence farming). Changes in the definition of employment also affect who is counted as unemployed or outside the labor force. Because definitions were updated under the [19th ICLS](#dod:19-icls), data using the newer definitions is not fully comparable with data based on the 13th ICLS. You can read more about the definitions in [this explainer by the ILO](https://www.ilo.org/publications/quick-guide-understanding-impact-new-statistical-standards-ilostat)."], "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}]}, "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": 13756, "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.EMP.TOTL.SP.FE.ZS (https://data.worldbank.org/indicator/SL.EMP.TOTL.SP.FE.ZS). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.", "versionProducer": "125", "urlMain": "https://data.worldbank.org/indicator/SL.EMP.TOTL.SP.FE.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"}}]}