Do Births outside marriage and Women ministers go together across countries?

Across 42 countries the link before adjusting for anything is r = +0.55, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives +0.52.

Does the link hold within countries over time, not just across countries?

Comparing each country only with itself across 2005-2020, and setting aside what happened worldwide in each year, the link is +0.111 (41 countries, 396 country-years). Using year-to-year changes, it is —.

Does Births outside marriage cause Women ministers?

This analysis cannot answer that. It shows only that the two go together. A link between two country measures, adjusted or not, does not show that either one changes the other. Country figures also say nothing about individual people.

Births outside marriage vs. Women ministers

Holds up after adjusting for income

Across 42 countries, Births outside marriage and Women ministers rise and fall together at r = +0.55 (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 = +0.58, q = 0.0024, allowing for the many pairs tested).

Comparing countries across the middle half of births outside marriage, 28.4% to 54.1% of live births, women ministers is better by 12.1% of ministers at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 12.6% of ministers.

Link before adjusting (r)+0.548p = 0.000 · 42 countries

After adjusting for national income+0.576p = 8.1e-5 · likely range [+0.33, +0.75]

p, allowing for regions2.8e-5standard error 0.027 · 5 regions

Check for luck (q)0.002across 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.

Births outside marriage · % of live birthslink with income -0.00 · independent

Women ministers · % of ministerslink with income +0.20 · independent

Neither of these is closely tied to national income, so adjusting for income is a real test here, not a formality.

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

Every country as a dot

best-fit line line after adjusting

Four ways to measure the link

Method	r	p	Countries
Standard (Pearson), not adjusted	+0.548	0.000	42
By rank (Spearman), not adjusted	+0.521	0.000	42
Standard (Pearson), adjusted for national income	+0.576	8.1e-5	42
By rank (Spearman), adjusted for national income	+0.544	0.000	42

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 42 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: -0.028 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.542 (without TUR) to +0.636 (without BGR). 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: BGR (+0.060).

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.

	n	r
Europe & Central Asia	31	+0.45

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.

	n	r
Poorest third	14	+0.55
Middle third	14	+0.61
Richest third	14	+0.55

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.

	n	r
Christians	35	+0.49

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 = +0.576 after dropping 0 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 16years. 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 = +0.111, 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 births outside marriage moved did not tend to see their women ministers move with it.

Across countries (adjusted)+0.576for comparison

Within countries+0.319each country vs itself

…and vs the same year elsewhere+0.111q = 0.213 · 41 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.

396 country-years (one country in one year), 41 countries, 2005–2020, about 10 years each on average. Share of the variation that happens within countries over time: 4% for Births outside marriage, 35% for Women ministers. 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

Same year (lag 0): +0.111. 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 +3) is higher than the same-year one by 0.06. That gap is not a finding. It is the largest of 16 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 live births	% of ministers	Years
Chile CHL	75.1%	50%	2019, 2024
Costa Rica CRI	72.5%	33.3%	2020, 2024
Mexico MEX	70.4%	45%	2020, 2024
Iceland ISL	69.4%	60%	2019, 2024
France FRA	62.2%	40%	2020, 2024
Bulgaria BGR	59.6%	5.26%	2020, 2024
Norway NOR	58.5%	47.4%	2020, 2024
Portugal PRT	57.9%	41.2%	2020, 2024
Slovenia SVN	56.5%	36.8%	2020, 2024
Sweden SWE	55.2%	47.8%	2020, 2024
Denmark DNK	54.2%	30.4%	2020, 2024
Estonia EST	53.7%	58.3%	2019, 2024
Netherlands NLD	53.5%	40%	2020, 2024
Belgium BEL	52.4%	42.9%	2018, 2024
United Kingdom GBR	51.3%	50%	2021, 2024

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
World Bank Gender Statistics, from Inter-Parliamentary Union and UN Women, Women in Politics

Sources

Births outside marriage

Share of births outside marriage

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

Live births to mothers who were not married at the time of the birth. A registered partnership counts as unmarried. So where couples register a partnership rather than marry, this partly measures which legal option is on offer. No "better" direction is set.

Women ministers

Proportion of women in ministerial positions

Inter-Parliamentary Union and UN Women · via Our World in Data · CC BY 4.0 · updated annual

Counted on 1 January each year, so a cabinet change in February shows up a year late. Ministers are appointed, not elected, so this is a different measure from women in parliament. A head of government can change it alone, and some do.

How this was computed

Data used: most recent value in 2010-2025; values come from 2013–2024. 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 5 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 Births outside marriage and Women ministers

This page shows that two measures go together. It does not show that Births outside marriage changes Women ministers, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.