{"chart":{"title":"Fertility rate versus female labor force participation rate","subtitle":"The total fertility rate, in a given year. The labor force participation rate is the share of the female working-age population who are economically active (employed or unemployed).","note":"Labor figures refer to national estimates and may not be fully comparable across countries.","citation":"Labour Force Statistics, via World Bank (2026); UN, World Population Prospects (2024)","originalChartUrl":"https://ourworldindata.org/grapher/fertility-and-female-labor-force-participation","selection":[]},"columns":{"Labor force participation rate, female (% of female population ages 15+) (national estimate)":{"titleShort":"Female labor force participation rate","titleLong":"Female labor force participation rate","descriptionShort":"Share of the female working-age population who are economically active (employed or unemployed). Figures refer to national estimates and may not be fully comparable across countries.","descriptionKey":"- The labor force participation rate shows the share of working-age people who are either employed (working for pay or profit) or unemployed (not working, but actively looking for work and available to start). This indicator shows the share of the population that is economically active.\n- People who are not seeking work or are not available, such as students, retired people, or unpaid caregivers, are excluded as they are considered to be outside the labor force.\n- When defining the labor force, the working-age population includes all people above the legal working age for employment in each country. The ILO’s guidelines define it as people aged 15 and older, but national definitions vary, depending on local laws. Some countries also set an upper age limit.\n- This data comes from the International Labour Organization’s ILOSTAT database, which compiles labor statistics from national sources. Underlying national surveys differ in design and coverage, so cross-country comparisons should be made with some caution.\n- This data follows the standards of the 13th International Classification of Labour Statisticians (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, 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).","shortUnit":"%","unit":"%","timespan":"1960-2025","type":"Numeric","owidVariableId":1294782,"shortName":"sl_tlf_cact_fe_ne_zs","lastUpdated":"2026-07-27","nextUpdate":"2027-01-23","citationShort":"Labour Force Statistics, via World Bank (2026) – processed by Our World in Data","citationLong":"Labour Force Statistics, via World Bank (2026) – processed by Our World in Data. “Female labor force participation rate – ILO” [dataset]. Labour Force Statistics, via World Bank, “World Development Indicators 129” [original data].","fullMetadata":"https://api.ourworldindata.org/v1/indicators/1294782.metadata.json"},"Fertility rate - Sex: all - Age: all - Variant: estimates":{"titleShort":"Fertility rate","titleLong":"Fertility rate - UN WPP","descriptionShort":"Total fertility rate: the average number of children a woman would have if she experienced the year's age-specific birth rates throughout her childbearing years.","descriptionKey":"The UN's projections come in several scenarios. The medium scenario is the central estimate; the high and low scenarios are designed to fully reach 0.5 births per woman above and below the medium from the mid-2030s onward (e.g. medium 2.1 → high 2.6, low 1.6). In the first decade of the projection the gap is narrower (about ±0.25 in 2024–2028, ±0.4 in 2029–2033). The constant-fertility scenario keeps fertility at its current level, and the zero-migration scenario uses the same fertility as the medium scenario.","descriptionProcessing":"The UN doesn't publish a total fertility rate for our continental aggregates (Africa, Asia, Europe, North America, South America, Oceania), since its own regional groupings differ. We derive these by summing the age-specific fertility rates across the 5-year reproductive age groups (15–19 to 45–49) and multiplying by 5, where each age-specific rate uses regional totals for births and female population.","unit":"live births per woman","timespan":"1950-2023","type":"Numeric","owidVariableId":950920,"shortName":"fertility_rate__sex_all__age_all__variant_estimates","lastUpdated":"2024-07-12","nextUpdate":"2027-07-12","citationShort":"UN, World Population Prospects (2024) – processed by Our World in Data","citationLong":"UN, World Population Prospects (2024) – processed by Our World in Data. “Fertility rate – UN WPP” [dataset]. United Nations, “World Population Prospects”; United Nations, “World Population Prospects – Interim Update” [original data].","fullMetadata":"https://api.ourworldindata.org/v1/indicators/950920.metadata.json"},"Population (historical)":{"titleShort":"Population","titleLong":"Population","descriptionShort":"Population by country, available from 10,000 BCE to 2023, based on data and estimates from different sources.","descriptionKey":"- Population is the most commonly used metric throughout Our World in Data. It is used directly to understand population growth over time, and indirectly to calculate per-capita indicators, making it easier to compare countries of different sizes.\n- We construct this indicator by combining multiple sources covering different periods.\n  - HYDE v3.3 (2023): historical estimates from 10,000 BCE to 1799.\n  - Gapminder v7 (2022): for 1800-1949.\n  - UN World Population Prospects (2024): for 1950 onwards, including 2100 projections.\n  - Gapminder Systema Globalis (2023): additional source for former countries (Yugoslavia, USSR, etc.)\n- Breaks in the data may occur at the boundaries between sources due to their methodological differences.\n- You can read more about the sources and methodology in our [dedicated article](https://ourworldindata.org/population-sources). We also provide a table of sources showing the source we use for each country-year.\n- We calculate geographical aggregates (continents, income groups, etc.) by summing individual country populations. For years before 1800, we rely directly on HYDE's values for continents to ensure historical consistency.","descriptionProcessing":"### Combination of different sources\nWe construct our long-run population data by combining multiple sources:\n\n- 10,000 BCE–1799: historical estimates by HYDE (v3.3).\n\n- 1800–1949: historical estimates by Gapminder (v7).\n\n- 1950–2023: population records from the United Nations World Population Prospects (2024 revision).\n\n**Geographical aggregates**\n\n- For most years, we calculate aggregates by summing the population of member countries.\n- We do this based on [our definition of continents](https://ourworldindata.org/world-region-map-definitions#our-world-in-data) and the [World Bank’s income groups](https://ourworldindata.org/grapher/world-bank-income-groups).\n- The only exception is before 1800, where we use HYDE's estimates for continents (but not income groups).\n\nFor most of the years, we've estimated regional aggregates by summing the population of countries in each region. We've relied on [our continents](https://ourworldindata.org/world-region-map-definitions#our-world-in-data) and [World Bank income group definitions](https://ourworldindata.org/grapher/world-bank-income-groups). The only exception is before 1800, where we've used HYDE's estimates on continents (but not income groups).\n\n**World**\n- Before 1800: we use data from HYDE.\n- 1800-1950: we estimate the global population by summing all available countries in the dataset.\n- After 1950, we rely on estimates from the United Nations World Population Prospects.","shortUnit":"","unit":"people","timespan":"-10000-2023","type":"Integer","owidVariableId":953903,"shortName":"population_historical","lastUpdated":"2024-07-15","nextUpdate":"2026-12-15","citationShort":"HYDE (2023); Gapminder (2022); UN WPP (2024) – with major processing by Our World in Data","citationLong":"HYDE (2023); Gapminder (2022); UN WPP (2024) – with major processing by Our World in Data. “Population – HYDE, Gapminder, UN – Long-run data” [dataset]. PBL Netherlands Environmental Assessment Agency, “History Database of the Global Environment 3.3”; Gapminder, “Population v7”; United Nations, “World Population Prospects”; United Nations, “World Population Prospects – Interim Update”; Gapminder, “Systema Globalis” [original data].","fullMetadata":"https://api.ourworldindata.org/v1/indicators/953903.metadata.json"},"World region according to OWID":{"titleShort":"World region according to OWID","titleLong":"World region according to OWID","descriptionShort":"Regions defined by Our World in Data, which are used in OWID charts and maps.","unit":"","timespan":"2023-2023","type":"Continent","owidVariableId":900801,"shortName":"owid_region","lastUpdated":"2023-01-01","citationShort":"Our World in Data","citationLong":"Our World in Data. “World region according to OWID” [dataset]. Our World in Data, “Regions” [original data].","fullMetadata":"https://api.ourworldindata.org/v1/indicators/900801.metadata.json"}},"dateDownloaded":"2026-10-31"}