Do Births outside marriage and Homicide rate go together across countries?

Across 43 countries the link before adjusting for anything is r = +0.52, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives +0.33.

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

Comparing each country only with itself across 1990-2023, and setting aside what happened worldwide in each year, the link is +0.125 (43 countries, 1,248 country-years). Using year-to-year changes, it is +0.060.

Does Births outside marriage cause Homicide rate?

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. Homicide rate

Fades after adjusting for income

Across 43 countries, Births outside marriage and Homicide rate rise and fall together at r = +0.52 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) leaves r = +0.48, which could easily be chance (q = 0.25, allowing for the many pairs tested, and allowing for countries in the same region being alike). Caution: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of births outside marriage, 28.2% to 55.6% of live births, homicide rate is worse by 3.96 per 100,000 population at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 2.96 per 100,000 population.

Link before adjusting (r)+0.517p = 0.000 · 43 countries

After adjusting for national income+0.481p = 0.001 · likely range [+0.21, +0.68]

p, allowing for regions0.092standard error 0.218 · 5 regions

Check for luck (q)0.253across 14,952 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 -0.09 · independent

Homicide rate · per 100,000 populationlink with income -0.38 · moderate

“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	+0.517	0.000	43
By rank (Spearman), not adjusted	+0.334	0.029	43
Standard (Pearson), adjusted for national income	+0.481	0.001	43
By rank (Spearman), adjusted for national income	+0.324	0.037	43

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 43 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: +0.037 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.411 (without COL) to +0.512 (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: COL (-0.070).

Fragile: this link may not hold up.

correlation moves sharply once outliers are trimmed
much weaker within income groups than across them (mostly a gap between richer and poorer countries)

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	-0.26

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	15	+0.07
Middle third	14	+0.02
Richest third	14	+0.00

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	36	+0.50

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 = +0.113 after dropping 6 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 34years. 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 = +0.125, 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 homicide rate move with it.

Across countries (adjusted)+0.481for comparison

Within countries-0.111each country vs itself

…and vs the same year elsewhere+0.125q = 0.359 · 43 countries

Year-on-year changes+0.060q = 0.103

1,248 country-years (one country in one year), 43 countries, 1990–2023, about 29 years each on average. Share of the variation that happens within countries over time: 19% for Births outside marriage, 17% for Homicide rate. 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): +0.125. 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 data

	% of live births	per 100,000 population	Years
Colombia COL	87%	24.9	2023
Chile CHL	78.1%	6.35	2022, 2023
Costa Rica CRI	74%	17.7	2023
Mexico MEX	73.7%	24.9	2024, 2023
Iceland ISL	69.4%	1.29	2019, 2023
Norway NOR	61.2%	0.725	2023
Bulgaria BGR	59.7%	1.09	2023
Portugal PRT	59.5%	0.72	2023, 2022
France FRA	58.5%	1.35	2023, 2024
Sweden SWE	57.4%	1.15	2023
Slovenia SVN	56.5%	0.566	2023
Denmark DNK	54.7%	0.841	2021, 2023
Estonia EST	53.8%	1.54	2023
Belgium BEL	52.4%	1.08	2018, 2021
Spain ESP	50%	0.691	2023

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
UN Office on Drugs and Crime, Intentional Homicide Victims

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.

Homicide rate

Intentional homicide rate (per 100,000 population)

United Nations Office on Drugs and Crime · via Our World in Data · CC BY 3.0 IGO · updated annual

Counts victims of intentional homicide (murder). Homicide is the crime least often left unreported. So it is the only crime figure similar enough across countries to use here. Rates of assault, theft and rape reflect how often people report crimes and how police record them, at least as much as how much crime there is, so they are left out on purpose. Even homicide figures shift when a country switches between police records and public-health records.

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 14,952 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Births outside marriage and Homicide rate

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