placestats

Employment in agriculture vs. Female labor participation

Holds up after adjusting for income

Across 177 countries, Employment in agriculture and Female labor participation rise and fall together at r = +0.21 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = +0.48, q = 0.033, allowing for the many pairs tested). Caution: direction is not consistent across regions.

Comparing countries across the middle half of female labor participation, 44.1% to 60.8% of women 15+, employment in agriculture is 4.77% of employment higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 5.98% of employment.

Link before adjusting (r)+0.214p = 0.004 · 177 countries
After adjusting for national income+0.483p = 1.1e-11 · likely range [+0.36, +0.59]
p, allowing for regions0.017standard error 0.147 · 7 regions
Check for luck (q)0.033across 12,497 pairs

How to read these.r runs from −1 (one goes up as the other goes down) to +1 (they rise together), and 0 means no link. Adjusting for national income means comparing countries with the same GDP per person, so differences in wealth can’t explain the link. Income is used in percentage terms, since an extra $1,000 means more to a poor country than to a rich one. p is how likely a link this strong would be if there were really none. Below 0.05 means it is unlikely to be chance. Very small values are written in short form: 1.1e-32 means a decimal point followed by 31 zeros and then 11, so very close to zero. The likely range is where the true figure probably lies, and a range that crosses zero means the link could easily be chance. Countries in the same region tend to resemble each other, so the third figure allows for that, which gives a fairer p. The standard error is the typical size of the error in r. Finally, testing this many pairs means some will look strong by luck alone. A q below 0.05 means this link is unlikely to be one of those.

Employment in agriculture · % of employmentlink with income -0.86 · proxy
Female labor participation · % of women 15+link with income +0.07 · independent

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

Employment in agriculture · % of employment →Female labor participation · % of women 15+ →0.0954%85.3%5.09%82.9%Afghanistan: 51.6% of employment, 5.09% of women 15+Angola: 51.9% of employment, 72.2% of women 15+Albania: 30.8% of employment, 58.6% of women 15+United Arab Emirates: 1.44% of employment, 53% of women 15+Argentina: 7% of employment, 52.5% of women 15+Armenia: 27% of employment, 51.1% of women 15+Australia: 2.18% of employment, 62.5% of women 15+Austria: 2.77% of employment, 55.1% of women 15+Azerbaijan: 34.2% of employment, 60.8% of women 15+Burundi: 85.3% of employment, 79.5% of women 15+Belgium: 0.985% of employment, 49.8% of women 15+Benin: 40.2% of employment, 75.2% of women 15+Burkina Faso: 51.8% of employment, 64.1% of women 15+Bangladesh: 44.3% of employment, 38.6% of women 15+Bulgaria: 4.69% of employment, 50.4% of women 15+Bahrain: 0.834% of employment, 42.3% of women 15+Bahamas, The: 0.775% of employment, 70.7% of women 15+Bosnia and Herzegovina: 16.7% of employment, 39.2% of women 15+Belarus: 9.48% of employment, 56.8% of women 15+Belize: 16.1% of employment, 46.5% of women 15+Bolivia: 24.7% of employment, 72.9% of women 15+Brazil: 7.63% of employment, 53.4% of women 15+Barbados: 1.25% of employment, 61% of women 15+Brunei Darussalam: 1.2% of employment, 54.4% of women 15+Bhutan: 42.4% of employment, 56.7% of women 15+Botswana: 18% of employment, 63.7% of women 15+Central African Republic: 66.1% of employment, 65.5% of women 15+Canada: 1.1% of employment, 60.2% of women 15+Switzerland: 2.24% of employment, 62.2% of women 15+Chile: 6.07% of employment, 52.9% of women 15+China: 21.7% of employment, 59.1% of women 15+Cote d'Ivoire: 45.4% of employment, 59.5% of women 15+Cameroon: 41.9% of employment, 56.6% of women 15+Congo, Dem. Rep.: 58.5% of employment, 61.8% of women 15+Congo, Rep.: 36.4% of employment, 65.6% of women 15+Colombia: 14.2% of employment, 51.6% of women 15+Comoros: 33.6% of employment, 47.6% of women 15+Cabo Verde: 9.25% of employment, 50.5% of women 15+Costa Rica: 11.5% of employment, 46% of women 15+Cyprus: 2.15% of employment, 61.2% of women 15+Czechia: 2.71% of employment, 53.5% of women 15+Germany: 1.07% of employment, 55.3% of women 15+Djibouti: 1.15% of employment, 19.4% of women 15+Denmark: 1.62% of employment, 60.8% of women 15+Dominican Republic: 7.01% of employment, 53.7% of women 15+Algeria: 9.48% of employment, 14.1% of women 15+Ecuador: 32.5% of employment, 52.4% of women 15+Egypt, Arab Rep.: 17.5% of employment, 18.5% of women 15+Spain: 3.37% of employment, 52.8% of women 15+Estonia: 2.96% of employment, 61% of women 15+Ethiopia: 60.1% of employment, 58.5% of women 15+Finland: 3.49% of employment, 56.5% of women 15+Fiji: 35.6% of employment, 38.5% of women 15+France: 2.33% of employment, 51.5% of women 15+Gabon: 28.9% of employment, 41.6% of women 15+United Kingdom: 0.851% of employment, 57.3% of women 15+Georgia: 34% of employment, 56.7% of women 15+Ghana: 34.6% of employment, 55.3% of women 15+Guinea: 47.4% of employment, 42.6% of women 15+Gambia, The: 27.6% of employment, 45.5% of women 15+Guinea-Bissau: 61.1% of employment, 60.3% of women 15+Equatorial Guinea: 55.3% of employment, 52.6% of women 15+Greece: 10.7% of employment, 44.7% of women 15+Guatemala: 29.1% of employment, 38.3% of women 15+Guyana: 12.2% of employment, 47.4% of women 15+Hong Kong SAR, China: 0.182% of employment, 51.8% of women 15+Honduras: 22.4% of employment, 39.6% of women 15+Croatia: 4.33% of employment, 47.4% of women 15+Haiti: 46.6% of employment, 58.3% of women 15+Hungary: 4.11% of employment, 54.3% of women 15+Indonesia: 27.3% of employment, 53.7% of women 15+India: 41.6% of employment, 32.4% of women 15+Ireland: 3.85% of employment, 59.8% of women 15+Iran, Islamic Rep.: 13.6% of employment, 14% of women 15+Iraq: 8.17% of employment, 10.9% of women 15+Iceland: 3.61% of employment, 70% of women 15+Israel: 0.76% of employment, 62.3% of women 15+Italy: 3.35% of employment, 40.8% of women 15+Jamaica: 13.9% of employment, 63% of women 15+Jordan: 3.12% of employment, 16% of women 15+Japan: 2.81% of employment, 55.9% of women 15+Kazakhstan: 11.3% of employment, 62.6% of women 15+Kenya: 45.8% of employment, 63% of women 15+Kyrgyz Republic: 15.4% of employment, 44.1% of women 15+Cambodia: 33.4% of employment, 77.4% of women 15+Korea, Rep.: 5.1% of employment, 56.8% of women 15+Kuwait: 1.89% of employment, 47.2% of women 15+Lao PDR: 68.6% of employment, 61.6% of women 15+Lebanon: 3.51% of employment, 22.2% of women 15+Liberia: 41.1% of employment, 72% of women 15+Libya: 10% of employment, 33% of women 15+St. Lucia: 7.47% of employment, 62% of women 15+Sri Lanka: 25.9% of employment, 31% of women 15+Lesotho: 30.9% of employment, 48.1% of women 15+Lithuania: 4.66% of employment, 57.7% of women 15+Luxembourg: 0.878% of employment, 57.5% of women 15+Latvia: 6.66% of employment, 55.2% of women 15+Macao SAR, China: 0.374% of employment, 63.1% of women 15+Morocco: 27.9% of employment, 19.7% of women 15+Moldova: 50.5% of employment, 72.3% of women 15+Madagascar: 69.2% of employment, 82.9% of women 15+Maldives: 11.3% of employment, 40.7% of women 15+Mexico: 11.4% of employment, 47.5% of women 15+North Macedonia: 8.5% of employment, 42.7% of women 15+Mali: 63% of employment, 52.8% of women 15+Malta: 0.877% of employment, 55.8% of women 15+Myanmar: 45% of employment, 40.9% of women 15+Montenegro: 4.19% of employment, 51.2% of women 15+Mongolia: 27% of employment, 51.5% of women 15+Mozambique: 73% of employment, 77.1% of women 15+Mauritania: 32.1% of employment, 26.2% of women 15+Mauritius: 4.71% of employment, 47.5% of women 15+Malawi: 65% of employment, 58.2% of women 15+Malaysia: 9.18% of employment, 51.6% of women 15+Namibia: 22.3% of employment, 54.9% of women 15+Niger: 73% of employment, 72.8% of women 15+Nigeria: 33.5% of employment, 80.7% of women 15+Nicaragua: 30.5% of employment, 51.3% of women 15+Netherlands: 1.7% of employment, 62.7% of women 15+Norway: 2.5% of employment, 62.1% of women 15+Nepal: 22.9% of employment, 27.5% of women 15+New Zealand: 5.42% of employment, 66.1% of women 15+Oman: 5.95% of employment, 30% of women 15+Pakistan: 36.2% of employment, 24% of women 15+Panama: 16% of employment, 54.9% of women 15+Peru: 23.1% of employment, 65% of women 15+Philippines: 20.5% of employment, 50.5% of women 15+Papua New Guinea: 36.9% of employment, 50.8% of women 15+Poland: 6.22% of employment, 51.6% of women 15+Puerto Rico (US): 1.14% of employment, 36.9% of women 15+Portugal: 2.78% of employment, 54.6% of women 15+Paraguay: 16% of employment, 59% of women 15+West Bank and Gaza: 6.34% of employment, 18.9% of women 15+Qatar: 1.62% of employment, 61.9% of women 15+Romania: 10.9% of employment, 41.8% of women 15+Russian Federation: 5.11% of employment, 54.5% of women 15+Rwanda: 35.1% of employment, 57.3% of women 15+Saudi Arabia: 2.5% of employment, 33.6% of women 15+Sudan: 39.8% of employment, 14.5% of women 15+Senegal: 29.6% of employment, 38.2% of women 15+Singapore: 0.0954% of employment, 63.6% of women 15+Solomon Islands: 42.5% of employment, 82.3% of women 15+Sierra Leone: 44.5% of employment, 51.6% of women 15+El Salvador: 13.9% of employment, 49.1% of women 15+Somalia, Fed. Rep.: 30% of employment, 20.7% of women 15+Serbia: 18% of employment, 52.6% of women 15+Sao Tome and Principe: 12.1% of employment, 22.7% of women 15+Suriname: 6.98% of employment, 44.9% of women 15+Slovak Republic: 2.16% of employment, 55.1% of women 15+Slovenia: 3.66% of employment, 52.3% of women 15+Sweden: 1.77% of employment, 61.5% of women 15+Eswatini: 14.5% of employment, 48.5% of women 15+Syrian Arab Republic: 16.3% of employment, 12.7% of women 15+Chad: 71.7% of employment, 47.3% of women 15+Togo: 37.6% of employment, 56.6% of women 15+Thailand: 28.6% of employment, 59% of women 15+Tajikistan: 43.3% of employment, 21.9% of women 15+Turkmenistan: 21.9% of employment, 38.2% of women 15+Timor-Leste: 46% of employment, 61.7% of women 15+Tonga: 23.6% of employment, 42.3% of women 15+Trinidad and Tobago: 4.49% of employment, 47.8% of women 15+Tunisia: 12.5% of employment, 26.5% of women 15+Turkiye: 14.2% of employment, 37.1% of women 15+Tanzania: 64.6% of employment, 80.3% of women 15+Uganda: 64.9% of employment, 75.6% of women 15+Ukraine: 14.1% of employment, 47.7% of women 15+Uruguay: 8.07% of employment, 57.3% of women 15+United States: 1.52% of employment, 56.3% of women 15+Uzbekistan: 25.2% of employment, 41.2% of women 15+St. Vincent and the Grenadines: 9.07% of employment, 59.2% of women 15+Virgin Islands (U.S.): 1.59% of employment, 52.8% of women 15+Viet Nam: 25% of employment, 68.6% of women 15+Vanuatu: 44.5% of employment, 53.3% of women 15+Samoa: 26.9% of employment, 30.7% of women 15+South Africa: 5.41% of employment, 49.9% of women 15+Zambia: 54.5% of employment, 56.4% of women 15+Zimbabwe: 54.3% of employment, 62.2% of women 15+AFGBDIBHSDJIIRQISLJORMDGMOZSDNSGPTJK

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.2140.004177
By rank (Spearman), not adjusted+0.0910.231177
Standard (Pearson), adjusted for national income+0.4831.1e-11177
By rank (Spearman), adjusted for national income+0.2985.9e-5177

The rank version uses only each country’s place in line, from lowest to highest, so a few extreme countries count for less. The adjusted and unadjusted versions use the same 177 countries: those that report both measures and GDP per person. So the gap between them comes from the adjustment, not from a change in which countries are counted. Drop in the size of r after adjusting: -0.269 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.466 (without PSE) to +0.498 (without LBR). The bar above shows that range on a scale from −1 to +1, with the solid line at the full result. The single country that moves r most: PSE (-0.017).

Fragile: this link may not hold up.
  • direction is not consistent across regions
  • much weaker within regions than across them (largely a between-region difference)

Within each region

Countries are not separate, unrelated cases, and neighbors share a lot. A link that holds inside each region is far more believable than one that shows up only when comparing regions.

nr
East Asia & Pacific25+0.07
Europe & Central Asia48+0.37
Latin America & Caribbean29-0.09
Middle East, North Africa, Afghanistan & Pakistan22+0.07
Sub-Saharan Africa45+0.57

By income third

If the link shows up only in the richest third of countries, it is a feature of rich countries, not a general pattern.

nr
Poorest third59+0.59
Middle third59+0.34
Richest third59-0.16

By largest religious group

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

nr
Christians106+0.40
Muslims49+0.63

By last european coloniser

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

nr
France25+0.60
Never a European colony21+0.29
Spain19+0.07
United Kingdom55+0.38

Without outliers (countries far outside the middle half of countries on either measure, by more than one and a half times the width of that middle half): r = +0.397 after dropping 10 countries.

Two series, one country

Both measures over the years for one country you pick. The two charts are stacked so they share only the years along the bottom.

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Over time, within countries

Everything above compares countries with each other at one moment. This section compares each country only with itself over 35years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

The link shows up within countries over time (r = +0.253) but mostly disappears in year-to-year changes (r = +0.081). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)+0.483for comparison
Within countries+0.067each country vs itself
…and vs the same year elsewhere+0.253q = 4.0e-5 · 187 countries
Year-on-year changes+0.081q = 0.056
Read with care.
  • Almost all of this indicator's variation is between countries, not within them, so the within-country estimate rests on a small part of the data.

6,531 country-years (one country in one year), 187 countries, 1991–2025, about 35 years each on average. Share of the variation that happens within countries over time: 6% for Employment in agriculture, 5% for Female labor participation. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

0.30−0.3-100+10years Female labor participation trails Employment in agriculture →lag -10: r = 0.273 (n = 4,848)lag -9: r = 0.280 (n = 5,035)lag -8: r = 0.286 (n = 5,222)lag -7: r = 0.289 (n = 5,409)lag -6: r = 0.285 (n = 5,596)lag -5: r = 0.281 (n = 5,783)lag -4: r = 0.280 (n = 5,970)lag -3: r = 0.276 (n = 6,157)lag -2: r = 0.269 (n = 6,344)lag -1: r = 0.259 (n = 6,531)lag +0: r = 0.253 (n = 6,531)lag +1: r = 0.243 (n = 6,344)lag +2: r = 0.232 (n = 6,157)lag +3: r = 0.223 (n = 5,970)lag +4: r = 0.211 (n = 5,783)lag +5: r = 0.198 (n = 5,596)lag +6: r = 0.182 (n = 5,409)lag +7: r = 0.164 (n = 5,222)lag +8: r = 0.145 (n = 5,035)lag +9: r = 0.125 (n = 4,848)lag +10: r = 0.106 (n = 4,661)

Same year (lag 0): +0.253. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

The data


% of employment
% of women 15+		Years
Burundi BDI85.3%79.5%2025
Mozambique MOZ73%77.1%2025
Niger NER73%72.8%2025
Chad TCD71.7%47.3%2025
Madagascar MDG69.2%82.9%2025
Lao PDR LAO68.6%61.6%2025
Central African Republic CAF66.1%65.5%2025
Malawi MWI65%58.2%2025
Uganda UGA64.9%75.6%2025
Tanzania TZA64.6%80.3%2025
Mali MLI63%52.8%2025
Guinea-Bissau GNB61.1%60.3%2025
Ethiopia ETH60.1%58.5%2025
Congo, Dem. Rep. COD58.5%61.8%2025
Equatorial Guinea GNQ55.3%52.6%2025

World Bank, World Development Indicators
World Bank, World Development Indicators

Sources

Employment in agriculture

Employment in agriculture (% of total employment)

International Labour Organization · CC BY 4.0 · updated quarterly

Estimated with a model by the ILO. The classic measure of a country moving from farming to industry and services. It is one of the measures most closely linked to income on the site. No "better" direction is set, because a farming country is not doing badly by farming.

Female labor participation

Labor force participation rate, female (% of female population 15+)

International Labour Organization · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2021–2025. To adjust for income, each measure is first predicted from GDP per person (in percentage terms, on a log scale) with a straight-line fit. Only what is left over is then compared. This is called a partial correlation. The line is drawn the standard way (ordinary least squares), which picks the line that comes closest to all the countries at once. The error margins allow for countries in the same region resembling each other, using 7 World Bank regions. The q-value corrects for testing all 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Employment in agriculture and Female labor participation

This page shows that two measures go together. It does not show that Employment in agriculture changes Female labor participation, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Employment in agriculture or Female labor participation