Do Married by 18 and PISA maths go together across countries?

Across 51 countries the link before adjusting for anything is r = -0.59, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives -0.60.

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

There are not enough years of data within countries to check this over time.

Does Married by 18 cause PISA maths?

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.

Married by 18 vs. PISA maths

Fades after adjusting for income

Across 51 countries, Married by 18 and PISA maths rise and fall together at r = -0.59 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.41, which could easily be chance (q = 0.45, allowing for the many pairs tested, and allowing for countries in the same region being alike). So the first figure mostly shows richer countries differing from poorer ones, not a link between these two things.

Comparing countries across the middle half of pisa maths, 366 to 440 PISA points, married by 18 is better by 7.37% of women aged 20-24 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 6.59% of women aged 20-24.

Link before adjusting (r)-0.587p = 6.0e-6 · 51 countries

After adjusting for national income-0.413p = 0.003 · likely range [-0.62, -0.15]

p, allowing for regions0.011standard error 0.074 · 4 regions

Check for luck (q)0.450across 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

PISA maths · PISA pointslink with income +0.79 · high

“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	-0.587	6.0e-6	51
By rank (Spearman), not adjusted	-0.598	3.5e-6	51
Standard (Pearson), adjusted for national income	-0.413	0.003	51
By rank (Spearman), adjusted for national income	-0.380	0.007	51

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 51 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: +0.174 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.450 (without VNM) to -0.347 (without DOM). 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: DOM (+0.066).

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	21	-0.07
Latin America & Caribbean	14	-0.61

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	17	-0.06
Middle third	17	-0.70
Richest third	17	-0.44

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	29	-0.67
Muslims	15	+0.31

By last european coloniser

	n	r
Spain	14	-0.59

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 = -0.433 after dropping 1 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 0years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Not enough history inside each country to look at this over time. That needs countries measured for several years in a row, and at least one of these measures is measured too rarely.

The data

	% of women aged 20-24	PISA points	Years
Dominican Republic DOM	31.5%	339	2019, 2022
Guatemala GTM	29.5%	344	2015, 2022
Jamaica JAM	26.9%	377	2022
Panama PAN	26.4%	357	2013, 2022
Uruguay URY	24.6%	409	2013, 2022
Colombia COL	23.4%	383	2015, 2022
Paraguay PRY	21.6%	338	2016, 2022
El Salvador SLV	19.7%	343	2021, 2022
Mexico MEX	18.2%	395	2023, 2022
Peru PER	17.9%	391	2024, 2022
Cambodia KHM	17.9%	336	2022
Costa Rica CRI	17.1%	385	2018, 2022
Thailand THA	17%	394	2022
Indonesia IDN	16.3%	366	2017, 2022
Argentina ARG	15.5%	378	2020, 2022

World Bank, World Development Indicators
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

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.

PISA maths

PISA mean mathematics score

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

The average score of 15-year-olds on the same test in every country taking part. It is scaled so the OECD average in the starting year was 500, with a standard deviation (a typical gap between students) of 100. Held every three years. The 2021 round was held in 2022, and the OECD says it can still be compared with earlier rounds despite the pandemic. The three subjects are treated as measuring the same thing. Their links with each other are above 0.95, and that close match is a fact about the test, not about schooling.

How this was computed

Data used: most recent value in 2010-2025; values come from 2012–2025. 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 Married by 18 and PISA maths

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