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What you should know about this indicator

Historical estimates count the number of persons engaged in each sector, based on national historical statistics. Recent estimates (from 1991) are ILO-modeled estimates published by the World Bank, based on employment of people aged 15 and over.

Number of people employed in agriculture
Number of people working in agriculture, including hunting, forestry and fishing.
Source
ILO Modelled Estimates, via World Bank (2026); UN, World Population Prospects (2024); Herrendorf, Rogerson and Valentinyi (2014); Timmer et al. – GGDC 10-Sector Database 2014 – with major processing by Our World in Data
Last updated
July 2, 2026
Next expected update
July 2027
Date range
1801–2025
Unit
people

Sources and processing

This data is based on the following sources

ILO Modelled Estimates, via World Bank – World Development Indicators

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.

Retrieved on
February 27, 2026
Retrieved from
https://data.worldbank.org/indicator/SL.AGR.EMPL.ZS
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
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.

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.

Retrieved on
February 27, 2026
Retrieved from
https://data.worldbank.org/indicator/SL.AGR.EMPL.ZS
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
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.

United Nations – World Population Prospects

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

Retrieved on
July 11, 2024
Retrieved from
https://population.un.org/wpp/downloads/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

Retrieved on
July 11, 2024
Retrieved from
https://population.un.org/wpp/downloads/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

United Nations – World Population Prospects - Interim Update

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

This is an interim update containing revised medium-variant estimates and projections for Togo.

Retrieved on
March 31, 2026
Retrieved from
https://population.un.org/wpp/downloads/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

This is an interim update containing revised medium-variant estimates and projections for Togo.

Retrieved on
March 31, 2026
Retrieved from
https://population.un.org/wpp/downloads/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

Herrendorf, Rogerson and Valentinyi – Growth and Structural Transformation

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.

Retrieved on
July 2, 2026
Retrieved from
https://www.nber.org/papers/w18996
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Berthold Herrendorf, Richard Rogerson, and Ákos Valentinyi, "Growth and Structural Transformation," NBER Working Paper 18996 (2013), https://doi.org/10.3386/w18996.
Published as: Herrendorf, B., Rogerson, R., & Valentinyi, Á. (2014). Growth and Structural Transformation. In P. Aghion & S. N. Durlauf (Eds.), Handbook of Economic Growth (Vol. 2, pp. 855-941). Elsevier.

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.

Retrieved on
July 2, 2026
Retrieved from
https://www.nber.org/papers/w18996
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Berthold Herrendorf, Richard Rogerson, and Ákos Valentinyi, "Growth and Structural Transformation," NBER Working Paper 18996 (2013), https://doi.org/10.3386/w18996.
Published as: Herrendorf, B., Rogerson, R., & Valentinyi, Á. (2014). Growth and Structural Transformation. In P. Aghion & S. N. Durlauf (Eds.), Handbook of Economic Growth (Vol. 2, pp. 855-941). Elsevier.

Timmer et al. – GGDC 10-Sector Database

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.

The 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.

It 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.

Retrieved on
July 2, 2026
Retrieved from
https://www.rug.nl/ggdc/structuralchange/previous-sector-database/10-sector-2014
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Timmer, M. P., de Vries, G. J., & de Vries, K. (2015). “Patterns of Structural Change in Developing Countries.” . In J. Weiss, & M. Tribe (Eds.), Routledge Handbook of Industry and Development. (pp. 65-83). Routledge.

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.

The 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.

It 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.

Retrieved on
July 2, 2026
Retrieved from
https://www.rug.nl/ggdc/structuralchange/previous-sector-database/10-sector-2014
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Timmer, M. P., de Vries, G. J., & de Vries, K. (2015). “Patterns of Structural Change in Developing Countries.” . In J. Weiss, & M. Tribe (Eds.), Routledge Handbook of Industry and Development. (pp. 65-83). Routledge.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline
Notes on our processing step for this indicator

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). 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.

For recent years, the number is calculated as the World Bank's agricultural share of employment multiplied by the total number of employed people, which is derived in turn from the ILO-modeled employment-to-population ratio and the United Nations estimate of the population aged 15 and over.

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Number of people employed in agriculture”, part of the following publication: Max Roser (2023) - “Employment in Agriculture”. Data adapted from ILO Modelled Estimates, via World Bank, United Nations, Herrendorf, Rogerson and Valentinyi, Timmer et al.. Retrieved from https://archive.ourworldindata.org/20260714-153658/grapher/number-of-people-employed-in-agriculture.html [online resource] (archived on July 14, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

ILO Modelled Estimates, via World Bank (2026) and other sources – with major processing by Our World in Data

Full citation

ILO Modelled Estimates, via World Bank (2026); UN, World Population Prospects (2024); Herrendorf, Rogerson and Valentinyi (2014); Timmer et al. – GGDC 10-Sector Database 2014 – with major processing by Our World in Data. “Number of people employed in agriculture” [dataset]. ILO Modelled Estimates, via World Bank, “World Development Indicators 125”; United Nations, “World Population Prospects”; United Nations, “World Population Prospects - Interim Update”; Herrendorf, Rogerson and Valentinyi, “Growth and Structural Transformation”; Timmer et al., “GGDC 10-Sector Database 2014 release, updated January 2015” [original data]. Retrieved July 14, 2026 from https://archive.ourworldindata.org/20260714-153658/grapher/number-of-people-employed-in-agriculture.html (archived on July 14, 2026).

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