Do Divorce rate and Out of school, primary go together across countries?

Across 44 countries the link before adjusting for anything is r = -0.07, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives -0.12.

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

Comparing each country only with itself across 1994-2022, and setting aside what happened worldwide in each year, the link is +0.030 (43 countries, 738 country-years). Using year-to-year changes, it is +0.000.

Does Divorce rate cause Out of school, primary?

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.

Divorce rate vs. Out of school, primary

Holds up after adjusting for income

Across 44 countries, Divorce rate and Out of school, primary rise and fall together at r = -0.07 (on a scale from −1 to +1, where 0 means no link). There is almost no link to explain.

Comparing countries across the middle half of divorce rate, 1.46 to 1.93 divorces per 1,000 people, out of school, primary is better by 0.12% of primary-age children at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.189% of primary-age children.

Link before adjusting (r)-0.069p = 0.654 · 44 countries

After adjusting for national income-0.114p = 0.468 · likely range [-0.40, +0.19]

p, allowing for regions0.001standard error 0.013 · 5 regions

Check for luck (q)0.020across 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.

Divorce rate · divorces per 1,000 peoplelink with income -0.04 · independent

Out of school, primary · % of primary-age childrenlink with income -0.45 · 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	-0.069	0.654	44
By rank (Spearman), not adjusted	-0.123	0.425	44
Standard (Pearson), adjusted for national income	-0.114	0.468	44
By rank (Spearman), adjusted for national income	-0.140	0.369	44

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 44 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: -0.044 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.258 (without RUS) to -0.002 (without ROU). 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: RUS (-0.145).

Fragile: this link may not hold up.

leave-one-out range spans 0.26 in r

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	32	-0.11

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	-0.14
Middle third	14	-0.34
Richest third	15	-0.24

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	37	-0.12

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 = -0.245 after dropping 7 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 29years. 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 = +0.030, 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 divorce rate moved did not tend to see their out of school, primary move with it.

Across countries (adjusted)-0.114for comparison

Within countries-0.054each country vs itself

…and vs the same year elsewhere+0.030q = 0.728 · 43 countries

Year-on-year changes+0.000q = 0.997

738 country-years (one country in one year), 43 countries, 1994–2022, about 17 years each on average. Share of the variation that happens within countries over time: 17% for Divorce rate, 38% for Out of school, primary. 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): +0.030. 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 (-0.10 at lag -7) 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

	divorces per 1,000 people	% of primary-age children	Years
Russian Federation RUS	4.7	4.94%	2013, 2023
Chile CHL	3.63	2.12%	2021, 2024
Latvia LVA	2.9	2.74%	2022, 2024
Costa Rica CRI	2.8	4.49%	2021, 2024
Lithuania LTU	2.6	0.13%	2022, 2024
Cyprus CYP	2.6	0.425%	2019, 2023
United States USA	2.5	3.98%	2021, 2022
Turkiye TUR	2.1	0.603%	2022, 2023
Sweden SWE	2.1	0.57%	2022, 2024
Denmark DNK	2.08	0.893%	2022, 2024
Finland FIN	2	1.77%	2022, 2024
Luxembourg LUX	1.9	0.256%	2022, 2024
Iceland ISL	1.9	1.82%	2020, 2023
France FRA	1.9	0.204%	2016, 2024
Estonia EST	1.9	3.39%	2022, 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, World Development Indicators

Sources

Divorce rate

Crude divorce rate

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

Divorces granted in the year per 1,000 people (counted at mid-year). From the same OECD Family Database table as the marriage rate, and for the same forty-odd OECD countries. It is a crude rate, not adjusted for how many people are married. So a country where few people marry can have few divorces without its marriages lasting any longer. No "better" direction is set.

Out of school, primary

Children out of school (% of primary school age)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

Children of primary-school age not enrolled at any level. Treated as measuring the same thing as gross primary enrolment, which is on the site. They are two ways of asking whether children are in school, so their agreement is not a finding.

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 Divorce rate and Out of school, primary

This page shows that two measures go together. It does not show that Divorce rate changes Out of school, primary, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.