placestats

Female labor participation vs. Vulnerable employment

Holds up after adjusting for income

Across 177 countries, Female labor participation and Vulnerable employment rise and fall together at r = +0.19 (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 = 0.013, allowing for the many pairs tested).

Comparing countries across the middle half of female labor participation, 44.1% to 60.8% of women 15+, vulnerable employment is worse by 5.18% of employment at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 6.74% of employment.

Link before adjusting (r)+0.186p = 0.013 · 177 countries
After adjusting for national income+0.461p = 1.2e-10 · likely range [+0.34, +0.57]
p, allowing for regions0.000standard error 0.067 · 7 regions
Check for luck (q)0.013across 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
Vulnerable employment · % of employmentlink with income -0.87 · proxy

“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+ →Vulnerable employment · % of employment →5.09%82.9%0.456%90.2%Afghanistan: 5.09% of women 15+, 81.8% of employmentAngola: 72.2% of women 15+, 66.3% of employmentAlbania: 58.6% of women 15+, 46% of employmentUnited Arab Emirates: 53% of women 15+, 1.5% of employmentArgentina: 52.5% of women 15+, 22.3% of employmentArmenia: 51.1% of women 15+, 32.8% of employmentAustralia: 62.5% of women 15+, 9.12% of employmentAustria: 55.1% of women 15+, 7.85% of employmentAzerbaijan: 60.8% of women 15+, 53.8% of employmentBurundi: 79.5% of women 15+, 83.7% of employmentBelgium: 49.8% of women 15+, 11% of employmentBenin: 75.2% of women 15+, 78.5% of employmentBurkina Faso: 64.1% of women 15+, 80.6% of employmentBangladesh: 38.6% of women 15+, 57.3% of employmentBulgaria: 50.4% of women 15+, 6.92% of employmentBahrain: 42.3% of women 15+, 0.749% of employmentBahamas, The: 70.7% of women 15+, 15.9% of employmentBosnia and Herzegovina: 39.2% of women 15+, 18.1% of employmentBelarus: 56.8% of women 15+, 6.33% of employmentBelize: 46.5% of women 15+, 29.8% of employmentBolivia: 72.9% of women 15+, 62.7% of employmentBrazil: 53.4% of women 15+, 26.1% of employmentBarbados: 61% of women 15+, 18.8% of employmentBrunei Darussalam: 54.4% of women 15+, 4.48% of employmentBhutan: 56.7% of women 15+, 69% of employmentBotswana: 63.7% of women 15+, 25.6% of employmentCentral African Republic: 65.5% of women 15+, 79.4% of employmentCanada: 60.2% of women 15+, 9.56% of employmentSwitzerland: 62.2% of women 15+, 9.6% of employmentChile: 52.9% of women 15+, 20.9% of employmentChina: 59.1% of women 15+, 33.4% of employmentCote d'Ivoire: 59.5% of women 15+, 69.4% of employmentCameroon: 56.6% of women 15+, 67.6% of employmentCongo, Dem. Rep.: 61.8% of women 15+, 81.5% of employmentCongo, Rep.: 65.6% of women 15+, 75.9% of employmentColombia: 51.6% of women 15+, 43% of employmentComoros: 47.6% of women 15+, 56.8% of employmentCabo Verde: 50.5% of women 15+, 34.3% of employmentCosta Rica: 46% of women 15+, 23.4% of employmentCyprus: 61.2% of women 15+, 8.38% of employmentCzechia: 53.5% of women 15+, 13.5% of employmentGermany: 55.3% of women 15+, 4.34% of employmentDjibouti: 19.4% of women 15+, 30.3% of employmentDenmark: 60.8% of women 15+, 5.4% of employmentDominican Republic: 53.7% of women 15+, 38% of employmentAlgeria: 14.1% of women 15+, 25.6% of employmentEcuador: 52.4% of women 15+, 50.1% of employmentEgypt, Arab Rep.: 18.5% of women 15+, 23.9% of employmentSpain: 52.8% of women 15+, 10.1% of employmentEstonia: 61% of women 15+, 7.09% of employmentEthiopia: 58.5% of women 15+, 84.1% of employmentFinland: 56.5% of women 15+, 9.46% of employmentFiji: 38.5% of women 15+, 32.8% of employmentFrance: 51.5% of women 15+, 8.5% of employmentGabon: 41.6% of women 15+, 29.8% of employmentUnited Kingdom: 57.3% of women 15+, 11.5% of employmentGeorgia: 56.7% of women 15+, 42.4% of employmentGhana: 55.3% of women 15+, 60% of employmentGuinea: 42.6% of women 15+, 79.2% of employmentGambia, The: 45.5% of women 15+, 63.5% of employmentGuinea-Bissau: 60.3% of women 15+, 74.9% of employmentEquatorial Guinea: 52.6% of women 15+, 23.1% of employmentGreece: 44.7% of women 15+, 23.1% of employmentGuatemala: 38.3% of women 15+, 36.2% of employmentGuyana: 47.4% of women 15+, 25.3% of employmentHong Kong SAR, China: 51.8% of women 15+, 5.76% of employmentHonduras: 39.6% of women 15+, 33.9% of employmentCroatia: 47.4% of women 15+, 6.35% of employmentHaiti: 58.3% of women 15+, 76% of employmentHungary: 54.3% of women 15+, 7.83% of employmentIndonesia: 53.7% of women 15+, 50% of employmentIndia: 32.4% of women 15+, 71.6% of employmentIreland: 59.8% of women 15+, 9.64% of employmentIran, Islamic Rep.: 14% of women 15+, 39.5% of employmentIraq: 10.9% of women 15+, 27.1% of employmentIceland: 70% of women 15+, 8.4% of employmentIsrael: 62.3% of women 15+, 7.7% of employmentItaly: 40.8% of women 15+, 14.3% of employmentJamaica: 63% of women 15+, 31.6% of employmentJordan: 16% of women 15+, 7.86% of employmentJapan: 55.9% of women 15+, 7.49% of employmentKazakhstan: 62.6% of women 15+, 24.8% of employmentKenya: 63% of women 15+, 63.8% of employmentKyrgyz Republic: 44.1% of women 15+, 29% of employmentCambodia: 77.4% of women 15+, 52.3% of employmentKorea, Rep.: 56.8% of women 15+, 17.7% of employmentKuwait: 47.2% of women 15+, 2.4% of employmentLao PDR: 61.6% of women 15+, 76.4% of employmentLebanon: 22.2% of women 15+, 19.4% of employmentLiberia: 72% of women 15+, 76.9% of employmentLibya: 33% of women 15+, 21.6% of employmentSt. Lucia: 62% of women 15+, 22% of employmentSri Lanka: 31% of women 15+, 39.2% of employmentLesotho: 48.1% of women 15+, 32.6% of employmentLithuania: 57.7% of women 15+, 10.4% of employmentLuxembourg: 57.5% of women 15+, 6.95% of employmentLatvia: 55.2% of women 15+, 8.62% of employmentMacao SAR, China: 63.1% of women 15+, 3.33% of employmentMorocco: 19.7% of women 15+, 35.5% of employmentMoldova: 72.3% of women 15+, 58.6% of employmentMadagascar: 82.9% of women 15+, 84.4% of employmentMaldives: 40.7% of women 15+, 16.9% of employmentMexico: 47.5% of women 15+, 25.3% of employmentNorth Macedonia: 42.7% of women 15+, 12.3% of employmentMali: 52.8% of women 15+, 75.8% of employmentMalta: 55.8% of women 15+, 10.1% of employmentMyanmar: 40.9% of women 15+, 62.9% of employmentMontenegro: 51.2% of women 15+, 14.3% of employmentMongolia: 51.5% of women 15+, 38.4% of employmentMozambique: 77.1% of women 15+, 83.7% of employmentMauritania: 26.2% of women 15+, 53.3% of employmentMauritius: 47.5% of women 15+, 14.9% of employmentMalawi: 58.2% of women 15+, 59.9% of employmentMalaysia: 51.6% of women 15+, 21.9% of employmentNamibia: 54.9% of women 15+, 29.9% of employmentNiger: 72.8% of women 15+, 83.7% of employmentNigeria: 80.7% of women 15+, 66.5% of employmentNicaragua: 51.3% of women 15+, 38.9% of employmentNetherlands: 62.7% of women 15+, 13.4% of employmentNorway: 62.1% of women 15+, 4.17% of employmentNepal: 27.5% of women 15+, 77% of employmentNew Zealand: 66.1% of women 15+, 12.6% of employmentOman: 30% of women 15+, 3.81% of employmentPakistan: 24% of women 15+, 55.5% of employmentPanama: 54.9% of women 15+, 37.9% of employmentPeru: 65% of women 15+, 47.5% of employmentPhilippines: 50.5% of women 15+, 33.6% of employmentPapua New Guinea: 50.8% of women 15+, 71.2% of employmentPoland: 51.6% of women 15+, 15% of employmentPuerto Rico (US): 36.9% of women 15+, 10.3% of employmentPortugal: 54.6% of women 15+, 9.66% of employmentParaguay: 59% of women 15+, 36.1% of employmentWest Bank and Gaza: 18.9% of women 15+, 18.4% of employmentQatar: 61.9% of women 15+, 0.456% of employmentRomania: 41.8% of women 15+, 13% of employmentRussian Federation: 54.5% of women 15+, 4.93% of employmentRwanda: 57.3% of women 15+, 39.4% of employmentSaudi Arabia: 33.6% of women 15+, 1.66% of employmentSudan: 14.5% of women 15+, 39.7% of employmentSenegal: 38.2% of women 15+, 63% of employmentSingapore: 63.6% of women 15+, 9.3% of employmentSolomon Islands: 82.3% of women 15+, 68.7% of employmentSierra Leone: 51.6% of women 15+, 86% of employmentEl Salvador: 49.1% of women 15+, 30.8% of employmentSomalia, Fed. Rep.: 20.7% of women 15+, 46% of employmentSerbia: 52.6% of women 15+, 23.9% of employmentSao Tome and Principe: 22.7% of women 15+, 35% of employmentSuriname: 44.9% of women 15+, 18.4% of employmentSlovak Republic: 55.1% of women 15+, 11.8% of employmentSlovenia: 52.3% of women 15+, 10.6% of employmentSweden: 61.5% of women 15+, 6.87% of employmentEswatini: 48.5% of women 15+, 28.4% of employmentSyrian Arab Republic: 12.7% of women 15+, 38.9% of employmentChad: 47.3% of women 15+, 90.2% of employmentTogo: 56.6% of women 15+, 75% of employmentThailand: 59% of women 15+, 48% of employmentTajikistan: 21.9% of women 15+, 28% of employmentTurkmenistan: 38.2% of women 15+, 28.3% of employmentTimor-Leste: 61.7% of women 15+, 58.6% of employmentTonga: 42.3% of women 15+, 33.7% of employmentTrinidad and Tobago: 47.8% of women 15+, 21.2% of employmentTunisia: 26.5% of women 15+, 17.9% of employmentTurkiye: 37.1% of women 15+, 23.9% of employmentTanzania: 80.3% of women 15+, 83.7% of employmentUganda: 75.6% of women 15+, 74.4% of employmentUkraine: 47.7% of women 15+, 19% of employmentUruguay: 57.3% of women 15+, 24.4% of employmentUnited States: 56.3% of women 15+, 3.81% of employmentUzbekistan: 41.2% of women 15+, 33.3% of employmentSt. Vincent and the Grenadines: 59.2% of women 15+, 22% of employmentVirgin Islands (U.S.): 52.8% of women 15+, 5.47% of employmentViet Nam: 68.6% of women 15+, 51.4% of employmentVanuatu: 53.3% of women 15+, 58% of employmentSamoa: 30.7% of women 15+, 41.6% of employmentSouth Africa: 49.9% of women 15+, 11.7% of employmentZambia: 56.4% of women 15+, 70.2% of employmentZimbabwe: 62.2% of women 15+, 68.2% of employmentAFGBDIBHSDZAIRQISLJORMDGNPLQATSYRTZA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.1860.013177
By rank (Spearman), not adjusted+0.1220.105177
Standard (Pearson), adjusted for national income+0.4611.2e-10177
By rank (Spearman), adjusted for national income+0.3762.7e-7177

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: -0.275 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.442 (without SDN) to +0.484 (without AFG). 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 (+0.023).

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+0.30
Europe & Central Asia48+0.45
Latin America & Caribbean29+0.33
Middle East, North Africa, Afghanistan & Pakistan22+0.04
Sub-Saharan Africa45+0.54

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+0.57
Middle third59+0.43
Richest third59+0.12

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+0.45
Muslims49+0.66

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+0.67
Never a European colony21+0.33
Spain19+0.56
United Kingdom55+0.41

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 = +0.415 after dropping 9 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.

Within countries over time, there is no link that is clearly more than chance (r = +0.118, 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 vulnerable employment move with it.

Across countries (adjusted)+0.461for comparison
Within countries-0.000each country vs itself
…and vs the same year elsewhere+0.118q = 0.180 · 187 countries
Year-on-year changes+0.088q = 0.016
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 Female labor participation, 2% for Vulnerable employment. 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

0.20−0.2-100+10years Vulnerable employment trails Female labor participation →lag -10: r = 0.049 (n = 4,661)lag -9: r = 0.059 (n = 4,848)lag -8: r = 0.068 (n = 5,035)lag -7: r = 0.073 (n = 5,222)lag -6: r = 0.081 (n = 5,409)lag -5: r = 0.086 (n = 5,596)lag -4: r = 0.092 (n = 5,783)lag -3: r = 0.098 (n = 5,970)lag -2: r = 0.102 (n = 6,157)lag -1: r = 0.110 (n = 6,344)lag +0: r = 0.118 (n = 6,531)lag +1: r = 0.120 (n = 6,531)lag +2: r = 0.129 (n = 6,344)lag +3: r = 0.137 (n = 6,157)lag +4: r = 0.145 (n = 5,970)lag +5: r = 0.151 (n = 5,783)lag +6: r = 0.159 (n = 5,596)lag +7: r = 0.167 (n = 5,409)lag +8: r = 0.171 (n = 5,222)lag +9: r = 0.172 (n = 5,035)lag +10: r = 0.170 (n = 4,848)

Same year (lag 0): +0.118. 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 largest value on this curve (+0.17 at lag +9) is higher than the same-year one by 0.05. That gap is not a finding. It is the largest of 21 closely related estimates, and picking the biggest of many tests always makes it look bigger. That is exactly why nothing on this site is ranked or chosen by lag.

The data


% of women 15+
% of employment		Years
Madagascar MDG82.9%84.4%2025
Solomon Islands SLB82.3%68.7%2025
Nigeria NGA80.7%66.5%2025
Tanzania TZA80.3%83.7%2025
Burundi BDI79.5%83.7%2025
Cambodia KHM77.4%52.3%2025
Mozambique MOZ77.1%83.7%2025
Uganda UGA75.6%74.4%2025
Benin BEN75.2%78.5%2025
Bolivia BOL72.9%62.7%2025
Niger NER72.8%83.7%2025
Moldova MDA72.3%58.6%2025
Angola AGO72.2%66.3%2025
Liberia LBR72%76.9%2025
Bahamas, The BHS70.7%15.9%2025

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

Sources

Female labor participation

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

International Labour Organization · CC BY 4.0 · updated quarterly

Vulnerable employment

Vulnerable employment, total (% of total employment)

International Labour Organization · CC BY 4.0 · updated quarterly

Self-employed workers and unpaid family workers, who have no employer and usually no protection. The ILO estimates it with a model for every country and year, which is why it is complete where surveys are not.

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 Vulnerable employment

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

More links with Female labor participation or Vulnerable employment