placestats

Female labor participation vs. Women's political empowerment

Holds up after adjusting for income

Across 166 countries, Female labor participation and Women's political empowerment rise and fall together at r = +0.43 (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 = +0.46, q = 0.027, allowing for the many pairs tested). Caution: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of women's political empowerment, 0.625 to 0.872 points, female labor participation is 8.99% of women 15+ higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 10.8% of women 15+.

Link before adjusting (r)+0.426p = 1.1e-8 · 166 countries
After adjusting for national income+0.459p = 5.9e-10 · likely range [+0.33, +0.57]
p, allowing for regions0.002standard error 0.087 · 7 regions
Check for luck (q)0.027across 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.

Female labor participation · % of women 15+link with income +0.07 · independent
Women's political empowerment · index (0-1)link with income +0.54 · moderate

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

Every country as a dot

Female labor participation · % of women 15+ →Women's political empowerment · index (0-1) →5.09%82.9%0.0280.954Afghanistan: 5.09% of women 15+, 0.028 index (0-1)Angola: 72.2% of women 15+, 0.77 index (0-1)Albania: 58.6% of women 15+, 0.893 index (0-1)United Arab Emirates: 53% of women 15+, 0.614 index (0-1)Argentina: 52.5% of women 15+, 0.832 index (0-1)Armenia: 51.1% of women 15+, 0.875 index (0-1)Australia: 62.5% of women 15+, 0.906 index (0-1)Austria: 55.1% of women 15+, 0.905 index (0-1)Azerbaijan: 60.8% of women 15+, 0.649 index (0-1)Burundi: 79.5% of women 15+, 0.653 index (0-1)Belgium: 49.8% of women 15+, 0.952 index (0-1)Benin: 75.2% of women 15+, 0.882 index (0-1)Burkina Faso: 64.1% of women 15+, 0.602 index (0-1)Bangladesh: 38.6% of women 15+, 0.537 index (0-1)Bulgaria: 50.4% of women 15+, 0.907 index (0-1)Bahrain: 42.3% of women 15+, 0.568 index (0-1)Bosnia and Herzegovina: 39.2% of women 15+, 0.821 index (0-1)Belarus: 56.8% of women 15+, 0.657 index (0-1)Bolivia: 72.9% of women 15+, 0.84 index (0-1)Brazil: 53.4% of women 15+, 0.818 index (0-1)Barbados: 61% of women 15+, 0.895 index (0-1)Bhutan: 56.7% of women 15+, 0.675 index (0-1)Botswana: 63.7% of women 15+, 0.699 index (0-1)Central African Republic: 65.5% of women 15+, 0.556 index (0-1)Canada: 60.2% of women 15+, 0.872 index (0-1)Switzerland: 62.2% of women 15+, 0.93 index (0-1)Chile: 52.9% of women 15+, 0.913 index (0-1)China: 59.1% of women 15+, 0.587 index (0-1)Cote d'Ivoire: 59.5% of women 15+, 0.696 index (0-1)Cameroon: 56.6% of women 15+, 0.76 index (0-1)Congo, Dem. Rep.: 61.8% of women 15+, 0.55 index (0-1)Congo, Rep.: 65.6% of women 15+, 0.466 index (0-1)Colombia: 51.6% of women 15+, 0.777 index (0-1)Comoros: 47.6% of women 15+, 0.556 index (0-1)Cabo Verde: 50.5% of women 15+, 0.855 index (0-1)Costa Rica: 46% of women 15+, 0.907 index (0-1)Cyprus: 61.2% of women 15+, 0.856 index (0-1)Czechia: 53.5% of women 15+, 0.93 index (0-1)Germany: 55.3% of women 15+, 0.942 index (0-1)Djibouti: 19.4% of women 15+, 0.584 index (0-1)Denmark: 60.8% of women 15+, 0.954 index (0-1)Dominican Republic: 53.7% of women 15+, 0.825 index (0-1)Algeria: 14.1% of women 15+, 0.625 index (0-1)Ecuador: 52.4% of women 15+, 0.79 index (0-1)Egypt, Arab Rep.: 18.5% of women 15+, 0.547 index (0-1)Spain: 52.8% of women 15+, 0.943 index (0-1)Estonia: 61% of women 15+, 0.941 index (0-1)Ethiopia: 58.5% of women 15+, 0.691 index (0-1)Finland: 56.5% of women 15+, 0.932 index (0-1)Fiji: 38.5% of women 15+, 0.644 index (0-1)France: 51.5% of women 15+, 0.929 index (0-1)Gabon: 41.6% of women 15+, 0.798 index (0-1)United Kingdom: 57.3% of women 15+, 0.838 index (0-1)Georgia: 56.7% of women 15+, 0.816 index (0-1)Ghana: 55.3% of women 15+, 0.767 index (0-1)Guinea: 42.6% of women 15+, 0.532 index (0-1)Gambia, The: 45.5% of women 15+, 0.813 index (0-1)Guinea-Bissau: 60.3% of women 15+, 0.502 index (0-1)Equatorial Guinea: 52.6% of women 15+, 0.449 index (0-1)Greece: 44.7% of women 15+, 0.896 index (0-1)Guatemala: 38.3% of women 15+, 0.722 index (0-1)Guyana: 47.4% of women 15+, 0.81 index (0-1)Hong Kong SAR, China: 51.8% of women 15+, 0.801 index (0-1)Honduras: 39.6% of women 15+, 0.789 index (0-1)Croatia: 47.4% of women 15+, 0.913 index (0-1)Haiti: 58.3% of women 15+, 0.403 index (0-1)Hungary: 54.3% of women 15+, 0.818 index (0-1)Indonesia: 53.7% of women 15+, 0.726 index (0-1)India: 32.4% of women 15+, 0.658 index (0-1)Ireland: 59.8% of women 15+, 0.927 index (0-1)Iran, Islamic Rep.: 14% of women 15+, 0.32 index (0-1)Iraq: 10.9% of women 15+, 0.555 index (0-1)Iceland: 70% of women 15+, 0.883 index (0-1)Israel: 62.3% of women 15+, 0.862 index (0-1)Italy: 40.8% of women 15+, 0.929 index (0-1)Jamaica: 63% of women 15+, 0.929 index (0-1)Jordan: 16% of women 15+, 0.669 index (0-1)Japan: 55.9% of women 15+, 0.844 index (0-1)Kazakhstan: 62.6% of women 15+, 0.682 index (0-1)Kenya: 63% of women 15+, 0.804 index (0-1)Kyrgyz Republic: 44.1% of women 15+, 0.733 index (0-1)Cambodia: 77.4% of women 15+, 0.534 index (0-1)Korea, Rep.: 56.8% of women 15+, 0.878 index (0-1)Kuwait: 47.2% of women 15+, 0.357 index (0-1)Lao PDR: 61.6% of women 15+, 0.508 index (0-1)Lebanon: 22.2% of women 15+, 0.608 index (0-1)Liberia: 72% of women 15+, 0.823 index (0-1)Libya: 33% of women 15+, 0.412 index (0-1)Sri Lanka: 31% of women 15+, 0.742 index (0-1)Lesotho: 48.1% of women 15+, 0.809 index (0-1)Lithuania: 57.7% of women 15+, 0.926 index (0-1)Luxembourg: 57.5% of women 15+, 0.896 index (0-1)Latvia: 55.2% of women 15+, 0.95 index (0-1)Morocco: 19.7% of women 15+, 0.712 index (0-1)Moldova: 72.3% of women 15+, 0.898 index (0-1)Madagascar: 82.9% of women 15+, 0.704 index (0-1)Maldives: 40.7% of women 15+, 0.532 index (0-1)Mexico: 47.5% of women 15+, 0.801 index (0-1)North Macedonia: 42.7% of women 15+, 0.824 index (0-1)Mali: 52.8% of women 15+, 0.706 index (0-1)Malta: 55.8% of women 15+, 0.917 index (0-1)Myanmar: 40.9% of women 15+, 0.33 index (0-1)Montenegro: 51.2% of women 15+, 0.866 index (0-1)Mongolia: 51.5% of women 15+, 0.806 index (0-1)Mozambique: 77.1% of women 15+, 0.725 index (0-1)Mauritania: 26.2% of women 15+, 0.541 index (0-1)Mauritius: 47.5% of women 15+, 0.814 index (0-1)Malawi: 58.2% of women 15+, 0.755 index (0-1)Malaysia: 51.6% of women 15+, 0.772 index (0-1)Namibia: 54.9% of women 15+, 0.855 index (0-1)Niger: 72.8% of women 15+, 0.709 index (0-1)Nigeria: 80.7% of women 15+, 0.732 index (0-1)Nicaragua: 51.3% of women 15+, 0.531 index (0-1)Netherlands: 62.7% of women 15+, 0.903 index (0-1)Norway: 62.1% of women 15+, 0.926 index (0-1)Nepal: 27.5% of women 15+, 0.792 index (0-1)New Zealand: 66.1% of women 15+, 0.937 index (0-1)Oman: 30% of women 15+, 0.357 index (0-1)Pakistan: 24% of women 15+, 0.524 index (0-1)Panama: 54.9% of women 15+, 0.742 index (0-1)Peru: 65% of women 15+, 0.775 index (0-1)Philippines: 50.5% of women 15+, 0.81 index (0-1)Papua New Guinea: 50.8% of women 15+, 0.48 index (0-1)Poland: 51.6% of women 15+, 0.878 index (0-1)Portugal: 54.6% of women 15+, 0.811 index (0-1)Paraguay: 59% of women 15+, 0.669 index (0-1)Qatar: 61.9% of women 15+, 0.388 index (0-1)Romania: 41.8% of women 15+, 0.872 index (0-1)Russian Federation: 54.5% of women 15+, 0.546 index (0-1)Rwanda: 57.3% of women 15+, 0.626 index (0-1)Saudi Arabia: 33.6% of women 15+, 0.347 index (0-1)Sudan: 14.5% of women 15+, 0.219 index (0-1)Senegal: 38.2% of women 15+, 0.855 index (0-1)Singapore: 63.6% of women 15+, 0.785 index (0-1)Solomon Islands: 82.3% of women 15+, 0.675 index (0-1)Sierra Leone: 51.6% of women 15+, 0.801 index (0-1)El Salvador: 49.1% of women 15+, 0.587 index (0-1)Somalia, Fed. Rep.: 20.7% of women 15+, 0.337 index (0-1)Serbia: 52.6% of women 15+, 0.864 index (0-1)Sao Tome and Principe: 22.7% of women 15+, 0.843 index (0-1)Suriname: 44.9% of women 15+, 0.877 index (0-1)Slovak Republic: 55.1% of women 15+, 0.878 index (0-1)Slovenia: 52.3% of women 15+, 0.94 index (0-1)Sweden: 61.5% of women 15+, 0.923 index (0-1)Eswatini: 48.5% of women 15+, 0.391 index (0-1)Syrian Arab Republic: 12.7% of women 15+, 0.29 index (0-1)Chad: 47.3% of women 15+, 0.625 index (0-1)Togo: 56.6% of women 15+, 0.692 index (0-1)Thailand: 59% of women 15+, 0.688 index (0-1)Tajikistan: 21.9% of women 15+, 0.431 index (0-1)Turkmenistan: 38.2% of women 15+, 0.437 index (0-1)Timor-Leste: 61.7% of women 15+, 0.768 index (0-1)Trinidad and Tobago: 47.8% of women 15+, 0.874 index (0-1)Tunisia: 26.5% of women 15+, 0.765 index (0-1)Turkiye: 37.1% of women 15+, 0.558 index (0-1)Tanzania: 80.3% of women 15+, 0.834 index (0-1)Uganda: 75.6% of women 15+, 0.636 index (0-1)Ukraine: 47.7% of women 15+, 0.888 index (0-1)Uruguay: 57.3% of women 15+, 0.875 index (0-1)United States: 56.3% of women 15+, 0.829 index (0-1)Uzbekistan: 41.2% of women 15+, 0.643 index (0-1)Viet Nam: 68.6% of women 15+, 0.808 index (0-1)Vanuatu: 53.3% of women 15+, 0.715 index (0-1)South Africa: 49.9% of women 15+, 0.83 index (0-1)Zambia: 56.4% of women 15+, 0.791 index (0-1)Zimbabwe: 62.2% of women 15+, 0.727 index (0-1)AFGBENCOGJORKHMMARMDAQATSDNSTPSYRTZA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.4261.1e-8166
By rank (Spearman), not adjusted+0.2780.000166
Standard (Pearson), adjusted for national income+0.4595.9e-10166
By rank (Spearman), adjusted for national income+0.3066.5e-5166

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 166 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: -0.033 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.422 (without AFG) to +0.484 (without QAT). 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: AFG (-0.037).

Fragile: this link may not hold up.
  • correlation moves sharply once outliers are trimmed

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 & Pacific21+0.29
Europe & Central Asia48+0.25
Latin America & Caribbean23+0.15
Middle East, North Africa, Afghanistan & Pakistan21+0.22
Sub-Saharan Africa45+0.39

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 third56+0.52
Middle third55+0.46
Richest third55+0.49

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
Christians98+0.13
Muslims47+0.49

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+0.36
Never a European colony21+0.77
Spain19-0.02
United Kingdom48+0.52

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 = +0.293 after dropping 11 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 36years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Within countries over time, there is no link that is clearly more than chance (r = -0.024, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose female labor participation moved did not tend to see their women's political empowerment move with it.

Across countries (adjusted)+0.459for comparison
Within countries+0.093each country vs itself
…and vs the same year elsewhere-0.024q = 0.798 · 172 countries
Year-on-year changes+0.028q = 0.366
Read with care.
  • Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.

6,120 country-years (one country in one year), 172 countries, 1990–2025, about 36 years each on average. Share of the variation that happens within countries over time: 13% for Female labor participation, 6% for Women's political empowerment. 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

0.10−0.1-100+10years Women's political empowerment trails Female labor participation →lag -10: r = -0.076 (n = 4,400)lag -9: r = -0.075 (n = 4,572)lag -8: r = -0.070 (n = 4,744)lag -7: r = -0.068 (n = 4,916)lag -6: r = -0.069 (n = 5,088)lag -5: r = -0.068 (n = 5,260)lag -4: r = -0.058 (n = 5,432)lag -3: r = -0.048 (n = 5,604)lag -2: r = -0.041 (n = 5,776)lag -1: r = -0.032 (n = 5,948)lag +0: r = -0.024 (n = 6,120)lag +1: r = -0.017 (n = 5,957)lag +2: r = -0.013 (n = 5,793)lag +3: r = -0.012 (n = 5,628)lag +4: r = -0.015 (n = 5,461)lag +5: r = -0.017 (n = 5,293)lag +6: r = -0.019 (n = 5,125)lag +7: r = -0.022 (n = 4,957)lag +8: r = -0.020 (n = 4,789)lag +9: r = -0.020 (n = 4,620)lag +10: r = -0.023 (n = 4,452)

Same year (lag 0): -0.024. 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.

This curve peaks at the edge of the window (lag -10), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.

The data


% of women 15+

index (0-1)
Years
Madagascar MDG82.9%0.7042025
Solomon Islands SLB82.3%0.6752025
Nigeria NGA80.7%0.7322025
Tanzania TZA80.3%0.8342025
Burundi BDI79.5%0.6532025
Cambodia KHM77.4%0.5342025
Mozambique MOZ77.1%0.7252025
Uganda UGA75.6%0.6362025
Benin BEN75.2%0.8822025
Bolivia BOL72.9%0.842025
Niger NER72.8%0.7092025
Moldova MDA72.3%0.8982025
Angola AGO72.2%0.772025
Liberia LBR72%0.8232025
Iceland ISL70%0.8832025

World Bank, World Development Indicators
Coppedge, M. et al., V-Dem Dataset, Varieties of Democracy (V-Dem) Project

Sources

Female labor participation

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

International Labour Organization · CC BY 4.0 · updated quarterly

Women's political empowerment

Women's political empowerment index

V-Dem Institute, University of Gothenburg · via Our World in Data · CC BY 4.0 · updated annual

Women's civil liberties, their part in civic groups, and their political representation. It is built from its own set of questions, not from the parts of the democracy indices, so it is not tagged as measuring the same thing. Still, read its links with them carefully. Whether women take part in politics is partly built into whether real political participation exists at all. So a strong link with general democracy measures is closer to definitional (true by how the terms are defined) than to a finding about the world.

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 Female labor participation and Women's political empowerment

This page shows that two measures go together. It does not show that Female labor participation changes Women's political empowerment, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Female labor participation or Women's political empowerment