placestats

Married by 18 vs. Vulnerable employment

Holds up after adjusting for income

Across 131 countries, Married by 18 and Vulnerable employment rise and fall together at r = +0.69 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.40 (q = 0.025, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak positive link remains. Caution: direction is not consistent across regions.

Comparing countries across the middle half of vulnerable employment, 23.6% to 65% of employment, married by 18 is worse by 16.5% of women aged 20-24 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 12.6% of women aged 20-24.

Link before adjusting (r)+0.686p = 1.5e-19 · 131 countries
After adjusting for national income+0.399p = 2.6e-6 · likely range [+0.24, +0.53]
p, allowing for regions0.032standard error 0.135 · 6 regions
Check for luck (q)0.025across 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.

Married by 18 · % of women aged 20-24link with income -0.60 · moderate
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

Married by 18 · % of women aged 20-24 →Vulnerable employment · % of employment →0%76.3%0.456%90.2%Afghanistan: 28.7% of women aged 20-24, 81.8% of employmentAngola: 23.1% of women aged 20-24, 66.3% of employmentAlbania: 11.8% of women aged 20-24, 46% of employmentArgentina: 15.5% of women aged 20-24, 22.3% of employmentArmenia: 5.3% of women aged 20-24, 32.8% of employmentAzerbaijan: 15% of women aged 20-24, 53.8% of employmentBurundi: 19% of women aged 20-24, 83.7% of employmentBelgium: 0.1% of women aged 20-24, 11% of employmentBenin: 27.5% of women aged 20-24, 78.5% of employmentBurkina Faso: 38.2% of women aged 20-24, 80.6% of employmentBangladesh: 47.2% of women aged 20-24, 57.3% of employmentBosnia and Herzegovina: 3.5% of women aged 20-24, 18.1% of employmentBelarus: 4.7% of women aged 20-24, 6.33% of employmentBelize: 33.5% of women aged 20-24, 29.8% of employmentBolivia: 14.5% of women aged 20-24, 62.7% of employmentBarbados: 29.2% of women aged 20-24, 18.8% of employmentBhutan: 9% of women aged 20-24, 69% of employmentCentral African Republic: 61% of women aged 20-24, 79.4% of employmentChile: 0% of women aged 20-24, 20.9% of employmentChina: 2.8% of women aged 20-24, 33.4% of employmentCote d'Ivoire: 25.8% of women aged 20-24, 69.4% of employmentCameroon: 29.8% of women aged 20-24, 67.6% of employmentCongo, Dem. Rep.: 29.9% of women aged 20-24, 81.5% of employmentCongo, Rep.: 27.3% of women aged 20-24, 75.9% of employmentColombia: 23.4% of women aged 20-24, 43% of employmentComoros: 20.7% of women aged 20-24, 56.8% of employmentCabo Verde: 8.4% of women aged 20-24, 34.3% of employmentCosta Rica: 17.1% of women aged 20-24, 23.4% of employmentDjibouti: 6.5% of women aged 20-24, 30.3% of employmentDenmark: 0.7% of women aged 20-24, 5.4% of employmentDominican Republic: 31.5% of women aged 20-24, 38% of employmentAlgeria: 3.8% of women aged 20-24, 25.6% of employmentEcuador: 22.2% of women aged 20-24, 50.1% of employmentEgypt, Arab Rep.: 15.8% of women aged 20-24, 23.9% of employmentEthiopia: 40.3% of women aged 20-24, 84.1% of employmentFinland: 0.1% of women aged 20-24, 9.46% of employmentFiji: 4% of women aged 20-24, 32.8% of employmentGabon: 13.3% of women aged 20-24, 29.8% of employmentUnited Kingdom: 0% of women aged 20-24, 11.5% of employmentGeorgia: 9.4% of women aged 20-24, 42.4% of employmentGhana: 16.1% of women aged 20-24, 60% of employmentGuinea: 46.5% of women aged 20-24, 79.2% of employmentGambia, The: 23.1% of women aged 20-24, 63.5% of employmentGuinea-Bissau: 25.7% of women aged 20-24, 74.9% of employmentEquatorial Guinea: 29.5% of women aged 20-24, 23.1% of employmentGuatemala: 29.5% of women aged 20-24, 36.2% of employmentGuyana: 32.3% of women aged 20-24, 25.3% of employmentHonduras: 34% of women aged 20-24, 33.9% of employmentHaiti: 14.9% of women aged 20-24, 76% of employmentIndonesia: 16.3% of women aged 20-24, 50% of employmentIndia: 22.3% of women aged 20-24, 71.6% of employmentIran, Islamic Rep.: 16.7% of women aged 20-24, 39.5% of employmentIraq: 27.9% of women aged 20-24, 27.1% of employmentIsrael: 0.8% of women aged 20-24, 7.7% of employmentJamaica: 26.9% of women aged 20-24, 31.6% of employmentJordan: 9.9% of women aged 20-24, 7.86% of employmentKazakhstan: 6.1% of women aged 20-24, 24.8% of employmentKenya: 12.5% of women aged 20-24, 63.8% of employmentKyrgyz Republic: 9.2% of women aged 20-24, 29% of employmentCambodia: 17.9% of women aged 20-24, 52.3% of employmentLao PDR: 30.5% of women aged 20-24, 76.4% of employmentLebanon: 6% of women aged 20-24, 19.4% of employmentLiberia: 24.9% of women aged 20-24, 76.9% of employmentLibya: 4.1% of women aged 20-24, 21.6% of employmentSt. Lucia: 24% of women aged 20-24, 22% of employmentSri Lanka: 9.8% of women aged 20-24, 39.2% of employmentLesotho: 13.4% of women aged 20-24, 32.6% of employmentLithuania: 0.2% of women aged 20-24, 10.4% of employmentMorocco: 13.7% of women aged 20-24, 35.5% of employmentMoldova: 12.2% of women aged 20-24, 58.6% of employmentMadagascar: 38.8% of women aged 20-24, 84.4% of employmentMaldives: 2.2% of women aged 20-24, 16.9% of employmentMexico: 18.2% of women aged 20-24, 25.3% of employmentNorth Macedonia: 7.5% of women aged 20-24, 12.3% of employmentMali: 48.5% of women aged 20-24, 75.8% of employmentMyanmar: 16% of women aged 20-24, 62.9% of employmentMontenegro: 5.8% of women aged 20-24, 14.3% of employmentMongolia: 8.1% of women aged 20-24, 38.4% of employmentMozambique: 48.4% of women aged 20-24, 83.7% of employmentMauritania: 36.6% of women aged 20-24, 53.3% of employmentMalawi: 38.7% of women aged 20-24, 59.9% of employmentNamibia: 6.9% of women aged 20-24, 29.9% of employmentNiger: 76.3% of women aged 20-24, 83.7% of employmentNigeria: 33.4% of women aged 20-24, 66.5% of employmentNicaragua: 35.2% of women aged 20-24, 38.9% of employmentNorway: 0% of women aged 20-24, 4.17% of employmentNepal: 34.9% of women aged 20-24, 77% of employmentOman: 4% of women aged 20-24, 3.81% of employmentPakistan: 18.3% of women aged 20-24, 55.5% of employmentPanama: 26.4% of women aged 20-24, 37.9% of employmentPeru: 17.9% of women aged 20-24, 47.5% of employmentPhilippines: 9.4% of women aged 20-24, 33.6% of employmentPapua New Guinea: 27.3% of women aged 20-24, 71.2% of employmentParaguay: 21.6% of women aged 20-24, 36.1% of employmentWest Bank and Gaza: 13.4% of women aged 20-24, 18.4% of employmentQatar: 1.7% of women aged 20-24, 0.456% of employmentRomania: 6.9% of women aged 20-24, 13% of employmentRussian Federation: 6.2% of women aged 20-24, 4.93% of employmentRwanda: 5.5% of women aged 20-24, 39.4% of employmentSaudi Arabia: 3.4% of women aged 20-24, 1.66% of employmentSudan: 34.2% of women aged 20-24, 39.7% of employmentSenegal: 30.2% of women aged 20-24, 63% of employmentSingapore: 0.1% of women aged 20-24, 9.3% of employmentSolomon Islands: 21.3% of women aged 20-24, 68.7% of employmentSierra Leone: 29.6% of women aged 20-24, 86% of employmentEl Salvador: 19.7% of women aged 20-24, 30.8% of employmentSerbia: 5.5% of women aged 20-24, 23.9% of employmentSao Tome and Principe: 28% of women aged 20-24, 35% of employmentSuriname: 36% of women aged 20-24, 18.4% of employmentEswatini: 1.9% of women aged 20-24, 28.4% of employmentChad: 60.6% of women aged 20-24, 90.2% of employmentTogo: 24.8% of women aged 20-24, 75% of employmentThailand: 17% of women aged 20-24, 48% of employmentTajikistan: 8.8% of women aged 20-24, 28% of employmentTurkmenistan: 6.1% of women aged 20-24, 28.3% of employmentTimor-Leste: 14.9% of women aged 20-24, 58.6% of employmentTonga: 10.1% of women aged 20-24, 33.7% of employmentTrinidad and Tobago: 4.2% of women aged 20-24, 21.2% of employmentTunisia: 2.4% of women aged 20-24, 17.9% of employmentTurkiye: 14.7% of women aged 20-24, 23.9% of employmentTanzania: 29.1% of women aged 20-24, 83.7% of employmentUganda: 34% of women aged 20-24, 74.4% of employmentUkraine: 9.1% of women aged 20-24, 19% of employmentUruguay: 24.6% of women aged 20-24, 24.4% of employmentUzbekistan: 3.4% of women aged 20-24, 33.3% of employmentViet Nam: 14.6% of women aged 20-24, 51.4% of employmentVanuatu: 20.9% of women aged 20-24, 58% of employmentSamoa: 7.4% of women aged 20-24, 41.6% of employmentSouth Africa: 3.6% of women aged 20-24, 11.7% of employmentZambia: 23.9% of women aged 20-24, 70.2% of employmentZimbabwe: 33.7% of women aged 20-24, 68.2% of employmentBDIBRBBTNCAFDNKHTINERNORQATSURTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6861.5e-19131
By rank (Spearman), not adjusted+0.7055.9e-21131
Standard (Pearson), adjusted for national income+0.3992.6e-6131
By rank (Spearman), adjusted for national income+0.4421.4e-7131

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 131 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: +0.287 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.382 (without LSO) to +0.420 (without SUR). 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: SUR (+0.022).

Fragile: this link may not hold up.
  • direction is not consistent across regions

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 & Pacific17+0.89
Europe & Central Asia25+0.60
Latin America & Caribbean24-0.20
Middle East, North Africa, Afghanistan & Pakistan17+0.52
Sub-Saharan Africa42+0.44

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 third44+0.42
Middle third43+0.42
Richest third44+0.33

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
Christians75+0.28
Muslims42+0.61

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
France24+0.45
Never a European colony19+0.75
Spain19+0.03
United Kingdom40+0.33

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 = +0.423 after dropping 2 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 = +0.320) but mostly disappears in year-to-year changes (r = —). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)+0.399for comparison
Within countries+0.645each country vs itself
…and vs the same year elsewhere+0.320q = 0.024 · 31 countries
Year-on-year changes—q = —
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.
  • Much of the within-country association disappears once shared global year effects are removed, which points to a common worldwide trend rather than a country-level relationship.

202 country-years (one country in one year), 31 countries, 1991–2025, about 7 years each on average. Share of the variation that happens within countries over time: 3% for Married by 18, 14% 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

The data


% of women aged 20-24

% of employment
Years
Niger NER76.3%83.7%2012, 2025
Central African Republic CAF61%79.4%2019, 2025
Chad TCD60.6%90.2%2019, 2025
Mali MLI48.5%75.8%2024, 2025
Mozambique MOZ48.4%83.7%2023, 2025
Bangladesh BGD47.2%57.3%2025
Guinea GIN46.5%79.2%2018, 2025
Ethiopia ETH40.3%84.1%2016, 2025
Madagascar MDG38.8%84.4%2021, 2025
Malawi MWI38.7%59.9%2024, 2025
Burkina Faso BFA38.2%80.6%2021, 2025
Mauritania MRT36.6%53.3%2021, 2025
Suriname SUR36%18.4%2018, 2025
Nicaragua NIC35.2%38.9%2012, 2025
Nepal NPL34.9%77%2022, 2025

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

Sources

Married by 18

Women who were first married by age 18 (% of women ages 20-24)

UNICEF · CC BY 4.0 · updated quarterly

From household surveys, mostly in lower-income countries, and only in years a survey ran. No year reaches sixty countries, so the latest value used is up to a decade old for some. Rich countries rarely report it at all, which shapes any link with income.

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 2010–2025. 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 6 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 Married by 18 and Vulnerable employment

This page shows that two measures go together. It does not show that Married by 18 changes Vulnerable employment, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Married by 18 or Vulnerable employment