placestats

Aid given vs. Women in a union

Holds up after adjusting for income

Across 47 countries, Aid given and Women in a union rise and fall together at r = +0.11 (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 = +0.17, q = 0.013, allowing for the many pairs tested).

Comparing countries across the middle half of aid given, 0.134% to 0.432% of GNI, women in a union is 0.573% of women aged 15-49 higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1.24% of women aged 15-49.

Link before adjusting (r)+0.105p = 0.482 · 47 countries
After adjusting for national income+0.169p = 0.262 · likely range [-0.13, +0.44]
p, allowing for regions0.000standard error 0.010 · 4 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.

Aid given · % of GNIlink with income +0.68 · high
Women in a union · % of women aged 15-49link with income -0.44 · moderate

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

Every country as a dot

Aid given · % of GNI →Women in a union · % of women aged 15-49 →0.0118%1.03%47.1%67.4%United Arab Emirates: 0.613% of GNI, 67.4% of women aged 15-49Australia: 0.184% of GNI, 54% of women aged 15-49Austria: 0.329% of GNI, 56.6% of women aged 15-49Azerbaijan: 0.0633% of GNI, 59.7% of women aged 15-49Belgium: 0.37% of GNI, 52.4% of women aged 15-49Bulgaria: 0.117% of GNI, 56.6% of women aged 15-49Canada: 0.316% of GNI, 51.6% of women aged 15-49Switzerland: 0.46% of GNI, 57.5% of women aged 15-49Cyprus: 0.0384% of GNI, 52.3% of women aged 15-49Czechia: 0.116% of GNI, 53.7% of women aged 15-49Germany: 0.558% of GNI, 54.4% of women aged 15-49Denmark: 0.723% of GNI, 54.3% of women aged 15-49Spain: 0.271% of GNI, 50.2% of women aged 15-49Estonia: 0.193% of GNI, 54.1% of women aged 15-49Finland: 0.443% of GNI, 57.1% of women aged 15-49France: 0.423% of GNI, 54.9% of women aged 15-49United Kingdom: 0.432% of GNI, 49.7% of women aged 15-49Greece: 0.13% of GNI, 52.4% of women aged 15-49Croatia: 0.236% of GNI, 50.1% of women aged 15-49Hungary: 0.139% of GNI, 52.3% of women aged 15-49Ireland: 0.425% of GNI, 47.1% of women aged 15-49Iceland: 0.337% of GNI, 48.5% of women aged 15-49Israel: 0.0512% of GNI, 50.4% of women aged 15-49Italy: 0.296% of GNI, 51.8% of women aged 15-49Japan: 0.345% of GNI, 50% of women aged 15-49Kazakhstan: 0.0188% of GNI, 63.8% of women aged 15-49Korea, Rep.: 0.203% of GNI, 49.8% of women aged 15-49Kuwait: 0.113% of GNI, 59.5% of women aged 15-49Lithuania: 0.212% of GNI, 51.8% of women aged 15-49Luxembourg: 0.993% of GNI, 51.1% of women aged 15-49Latvia: 0.18% of GNI, 49.6% of women aged 15-49Malta: 0.205% of GNI, 52% of women aged 15-49Netherlands: 0.58% of GNI, 53.5% of women aged 15-49Norway: 1.03% of GNI, 57.4% of women aged 15-49New Zealand: 0.273% of GNI, 57.7% of women aged 15-49Poland: 0.162% of GNI, 58.6% of women aged 15-49Portugal: 0.178% of GNI, 50.6% of women aged 15-49Qatar: 0.432% of GNI, 64.6% of women aged 15-49Romania: 0.135% of GNI, 56% of women aged 15-49Russian Federation: 0.0667% of GNI, 57.6% of women aged 15-49Saudi Arabia: 0.447% of GNI, 55.3% of women aged 15-49Slovak Republic: 0.133% of GNI, 49.2% of women aged 15-49Slovenia: 0.216% of GNI, 47.2% of women aged 15-49Sweden: 0.849% of GNI, 53.6% of women aged 15-49Thailand: 0.0118% of GNI, 52.4% of women aged 15-49Turkiye: 0.501% of GNI, 59.6% of women aged 15-49United States: 0.094% of GNI, 52.1% of women aged 15-49AREAZEISRKAZKWTLUXNORQATSVKSVNSWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.1050.48247
By rank (Spearman), not adjusted+0.0530.72347
Standard (Pearson), adjusted for national income+0.1690.26247
By rank (Spearman), adjusted for national income+0.1250.41047

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 47 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: -0.064 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.112 (without ARE) to +0.259 (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: QAT (+0.091).

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
Europe & Central Asia34+0.28

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 third16+0.07
Middle third15-0.05
Richest third16+0.17

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
Christians33+0.24

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 = +0.077 after dropping 3 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 = -0.023, 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 aid given moved did not tend to see their women in a union move with it.

Across countries (adjusted)+0.169for comparison
Within countries-0.263each country vs itself
…and vs the same year elsewhere-0.023q = 0.904 · 47 countries
Year-on-year changes-0.007q = 0.872
Read with care.
  • 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.

1,128 country-years (one country in one year), 47 countries, 1990–2024, about 24 years each on average. Share of the variation that happens within countries over time: 18% for Aid given, 33% for Women in a union. 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 in a union trails Aid given →lag -10: r = 0.027 (n = 1,066)lag -9: r = 0.031 (n = 1,090)lag -8: r = 0.031 (n = 1,109)lag -7: r = 0.018 (n = 1,131)lag -6: r = 0.001 (n = 1,150)lag -5: r = -0.010 (n = 1,168)lag -4: r = -0.015 (n = 1,183)lag -3: r = -0.010 (n = 1,180)lag -2: r = -0.005 (n = 1,167)lag -1: r = -0.005 (n = 1,149)lag +0: r = -0.023 (n = 1,128)lag +1: r = -0.020 (n = 1,078)lag +2: r = -0.010 (n = 1,028)lag +3: r = 0.001 (n = 979)lag +4: r = 0.019 (n = 935)lag +5: r = 0.042 (n = 887)lag +6: r = 0.073 (n = 836)lag +7: r = 0.081 (n = 795)lag +8: r = 0.089 (n = 750)lag +9: r = 0.081 (n = 706)lag +10: r = 0.060 (n = 655)

Same year (lag 0): -0.023. 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 (+0.09 at lag +8) is higher than the same-year one by 0.07. 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 GNI
% of women aged 15-49		Years
Norway NOR1.03%57.4%2025, 2021
Luxembourg LUX0.993%51.1%2025, 2022
Sweden SWE0.849%53.6%2025, 2023
Denmark DNK0.723%54.3%2025, 2024
United Arab Emirates ARE0.613%67.4%2025, 2018
Netherlands NLD0.58%53.5%2025, 2023
Germany DEU0.558%54.4%2025, 2023
Turkiye TUR0.501%59.6%2025, 2021
Switzerland CHE0.46%57.5%2025, 2022
Saudi Arabia SAU0.447%55.3%2024, 2022
Finland FIN0.443%57.1%2025, 2023
Qatar QAT0.432%64.6%2025, 2020
United Kingdom GBR0.432%49.7%2025, 2021
Ireland IRL0.425%47.1%2025, 2022
France FRA0.423%54.9%2025, 2020

OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics
United Nations, Department of Economic and Social Affairs, Population Division: World Population Prospects 2024 and Estimates and Projections of Women of Reproductive Age Who Are Married or in a Union

Sources

Aid given

Official development assistance given

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator

Donor countries only, about fifty. Countries that receive aid do not appear, so any link with this is a link among rich countries. No "better" direction is set.

Women in a union

Share of women aged 15 to 49 who are married or in a union

United Nations Department of Economic and Social Affairs, Population Division · via Our World in Data · CC BY 3.0 IGO · updated biennial

A snapshot of how many women are in a union at one time, not a count of new unions each year. It counts couples living together as a union, which the OECD marriage rate does not. So the two can disagree without either being wrong, and their pair is worth reading for exactly that. The UN estimates it with a statistical model from survey and census data, for over two hundred countries. No "better" direction is set.

How this was computed

Data used: most recent value in 2010-2025; values come from 2011–2025. 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 4 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 Aid given and Women in a union

This page shows that two measures go together. It does not show that Aid given changes Women in a union, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Aid given or Women in a union