Do Age at childbearing and Researchers go together across countries?

Across 131 countries the link before adjusting for anything is r = +0.72, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives +0.64.

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

Comparing each country only with itself across 1996-2023, and setting aside what happened worldwide in each year, the link is +0.367 (100 countries, 1,839 country-years). Using year-to-year changes, it is +0.051.

Does Age at childbearing cause Researchers?

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.

Age at childbearing vs. Researchers

Holds up after adjusting for income

Across 131 countries, Age at childbearing and Researchers rise and fall together at r = +0.72 (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 = 0.0060, allowing for the many pairs tested).

Comparing countries across the middle half of age at childbearing, 28.3 to 30.9 years, researchers is better by 2,826 per million people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1,947 per million people.

Link before adjusting (r)+0.721p = 2.7e-22 · 131 countries

After adjusting for national income+0.577p = 6.8e-13 · likely range [+0.45, +0.68]

p, allowing for regions0.000standard error 0.066 · 7 regions

Check for luck (q)0.006across 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.

Age at childbearing · yearslink with income +0.44 · moderate

Researchers · per million peoplelink with income +0.85 · 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	+0.721	2.7e-22	131
By rank (Spearman), not adjusted	+0.643	1.3e-16	131
Standard (Pearson), adjusted for national income	+0.577	6.8e-13	131
By rank (Spearman), adjusted for national income	+0.298	0.001	131

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 131 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: +0.144 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.553 (without KOR) to +0.595 (without OMN). 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: KOR (-0.024).

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	18	+0.61
Europe & Central Asia	45	+0.24
Latin America & Caribbean	17	+0.52
Middle East, North Africa, Afghanistan & Pakistan	17	+0.34
Sub-Saharan Africa	29	+0.17

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	44	+0.51
Middle third	43	+0.25
Richest third	44	+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	80	+0.66
Muslims	32	+0.04

By last european coloniser

	n	r
France	13	+0.80
Never a European colony	15	+0.57
Spain	16	+0.68
United Kingdom	36	+0.37

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 = +0.553 after dropping 5 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 28years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

The link shows up within countries over time (r = +0.367) but mostly disappears in year-to-year changes (r = +0.051). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)+0.577for comparison

Within countries+0.710each country vs itself

…and vs the same year elsewhere+0.367q = 0.002 · 100 countries

Year-on-year changes+0.051q = 0.424

Read with care.

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.
The association is much weaker in year-on-year changes than in levels, which points to shared country-specific trends.

1,839 country-years (one country in one year), 100 countries, 1996–2023, about 18 years each on average. Share of the variation that happens within countries over time: 23% for Age at childbearing, 14% for Researchers. 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): +0.367. 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

	years	per million people	Years
Korea, Rep. KOR	33.4	9,472	2023
Hong Kong SAR, China HKG	32.9	5,874	2023, 2024
Ireland IRL	32.7	5,753	2023
Spain ESP	32.5	3,654	2023
Luxembourg LUX	32.3	5,359	2023
Italy ITA	32.3	2,855	2023
Switzerland CHE	32.3	6,108	2023
Singapore SGP	32.3	8,782	2023, 2022
Macao SAR, China MAC	32.1	4,634	2023, 2024
Greece GRC	32	5,283	2023
Japan JPN	31.9	5,609	2023
United Arab Emirates ARE	31.9	2,607	2023, 2021
Netherlands NLD	31.8	6,563	2023
Portugal PRT	31.7	5,983	2023
Cyprus CYP	31.7	1,686	2023

United Nations, Department of Economic and Social Affairs, Population Division: World Population Prospects 2024 and Estimates and Projections of Women of Reproductive Age Who Are Married or in a Union
World Bank, World Development Indicators

Sources

Age at childbearing

Mean age of mothers at childbearing

United Nations Department of Economic and Social Affairs, Population Division · via Our World in Data · CC BY 3.0 IGO · updated biennial

The average age of women giving birth in the year, based on how many births women of each age have. Later childbearing goes with fewer births, but not one for one. A country can have late but plentiful births, or early but few. No "better" direction is set.

Researchers

Researchers in R&D (per million people)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

Researchers counted as full-time equivalents (two half-time researchers count as one), from national research surveys that many countries run only now and then. So coverage is thin outside the OECD.

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 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Age at childbearing and Researchers

This page shows that two measures go together. It does not show that Age at childbearing changes Researchers, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.