Do Contraceptive use (any method) and Mean years of schooling go together across countries?

Across 146 countries the link before adjusting for anything is r = +0.56, 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 1990-2023, and setting aside what happened worldwide in each year, the link is -0.023 (92 countries, 746 country-years). Using year-to-year changes, it is —.

Does Contraceptive use (any method) cause Mean years of schooling?

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.

Contraceptive use (any method) vs. Mean years of schooling

Fades after adjusting for income

Across 146 countries, Contraceptive use (any method) and Mean years of schooling rise and fall together at r = +0.56 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.21, which could easily be chance (q = 0.55, 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. Caution: direction is not consistent across regions.

Comparing countries across the middle half of mean years of schooling, 6.07 to 11 years, contraceptive use (any method) is 18.4% higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 9.28%.

Link before adjusting (r)+0.564p = 1.3e-13 · 146 countries

After adjusting for national income+0.205p = 0.013 · likely range [+0.04, +0.36]

p, allowing for regions0.282standard error 0.174 · 7 regions

Check for luck (q)0.548across 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.

Contraceptive use (any method) · %link with income +0.56 · moderate

Mean years of schooling · yearslink with income +0.82 · proxy

“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	+0.564	1.3e-13	146
By rank (Spearman), not adjusted	+0.522	1.3e-11	146
Standard (Pearson), adjusted for national income	+0.205	0.013	146
By rank (Spearman), adjusted for national income	+0.126	0.130	146

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 146 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: +0.358 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.173 (without GUY) to +0.234 (without WSM). 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: GUY (-0.032).

Fragile: this link may not hold up.

direction is not consistent across regions

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
East Asia & Pacific	23	-0.63
Europe & Central Asia	32	-0.06
Latin America & Caribbean	24	+0.41
Middle East, North Africa, Afghanistan & Pakistan	15	+0.51
Sub-Saharan Africa	45	+0.50

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	49	+0.43
Middle third	48	-0.05
Richest third	49	+0.16

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	86	+0.12
Muslims	43	+0.39

By last european coloniser

	n	r
France	23	+0.26
Never a European colony	21	-0.28
Spain	18	+0.23
United Kingdom	46	+0.27

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 = +0.205 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.

Loading…

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 = -0.023, 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 contraceptive use (any method) moved did not tend to see their mean years of schooling move with it.

Across countries (adjusted)+0.205for comparison

Within countries+0.467each country vs itself

…and vs the same year elsewhere-0.023q = 0.851 · 92 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.

746 country-years (one country in one year), 92 countries, 1990–2023, about 8 years each on average. Share of the variation that happens within countries over time: 9% for Contraceptive use (any method), 10% for Mean years of schooling. 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): -0.023. 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.

This curve peaks at the edge of the window (lag -10), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.

The data

	%	years	Years
Finland FIN	85.5%	13	2015, 2023
China CHN	84.5%	8.04	2017, 2023
Korea, Rep. KOR	84.2%	12.7	2021, 2023
Colombia COL	81%	9.03	2015, 2023
Nicaragua NIC	80.4%	9.93	2012, 2023
Germany DEU	80.3%	14.3	2011, 2023
Brazil BRA	80.2%	8.43	2013, 2023
France FRA	78.4%	11.8	2010, 2023
Ecuador ECU	77.9%	8.97	2018, 2023
Iran, Islamic Rep. IRN	77.4%	10.8	2010, 2023
Peru PER	77.3%	10.2	2023
Chile CHL	76.3%	11.3	2016, 2023
United Kingdom GBR	76.1%	13.5	2012, 2023
Estonia EST	75.1%	13.6	2014, 2023
United States USA	73.9%	13.9	2019, 2023

World Bank, World Development Indicators
United Nations Development Programme, Human Development Report 2025

Sources

Contraceptive use (any method)

Contraceptive prevalence, any method (% of married women ages 15-49)

World Bank · CC BY 4.0 · updated quarterly

The share of married women aged 15 to 49 who use any form of birth control, including traditional ones such as withdrawal, from national surveys. Only married women (and women living with a partner) are counted. Most countries have a survey only every few years.

Mean years of schooling

Mean years of schooling, adults aged 25 and over

United Nations Development Programme, Human Development Report Office · via Our World in Data · CC BY 3.0 IGO · updated annual

The schooling adults actually completed, decades ago for most of them. Expected schooling looks ahead at children; this looks back at adults. It is the one to read for the education of the workforce rather than of children.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2024. 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 7 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 Contraceptive use (any method) and Mean years of schooling

This page shows that two measures go together. It does not show that Contraceptive use (any method) changes Mean years of schooling, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.