Across 177 countries, Health spending and Out of school, primary rise and fall together at r = -0.20 (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 = -0.13, q = 0.050, allowing for the many pairs tested). Caution: correlation moves sharply once outliers are trimmed.
Comparing countries across the middle half of health spending, 4.44% to 8.82% of GDP, out of school, primary is better by 2.89% of primary-age children at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1.7% of primary-age children.
Link before adjusting (r)-0.198p = 0.008 · 177 countries
After adjusting for national income-0.133p = 0.079 · likely range [-0.28, +0.02]
p, allowing for regions0.005standard error 0.031 · 7 regions
Check for luck (q)0.050across 13,797 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.
Health spending · % of GDPlink with income +0.29 · 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
-0.198
0.008
177
By rank (Spearman), not adjusted
-0.324
1.1e-5
177
Standard (Pearson), adjusted for national income
-0.133
0.079
177
By rank (Spearman), adjusted for national income
-0.222
0.003
177
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 177 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: +0.066 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from -0.163 (without LBR) to -0.098 (without TUV). 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: TUV (+0.035).
Fragile: this link may not hold up.
correlation moves sharply once outliers are trimmed
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
28
-0.14
Europe & Central Asia
50
-0.31
Latin America & Caribbean
29
-0.21
Middle East, North Africa, Afghanistan & Pakistan
18
-0.48
Sub-Saharan Africa
44
+0.00
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
59
-0.10
Middle third
59
-0.25
Richest third
59
-0.46
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
106
-0.08
Muslims
44
-0.30
By last european coloniser
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
France
23
+0.08
Never a European colony
19
+0.25
Spain
20
-0.31
United Kingdom
59
-0.18
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 = -0.322 after dropping 23 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 25years. 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 = +0.052, 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 health spending moved did not tend to see their out of school, primary move with it.
Across countries (adjusted)-0.133for comparison
Within countries-0.016each country vs itself
…and vs the same year elsewhere+0.052q = 0.563 · 176 countries
Year-on-year changes+0.008q = 0.853
2,984 country-years (one country in one year), 176 countries, 2000–2024, about 17 years each on average. Share of the variation that happens within countries over time: 14% for Health spending, 19% 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): +0.052. 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 GDP
% of primary-age children
Years
Tuvalu TUV
27.1%
0.537%
2023, 2024
Naoero NRU
18.2%
6.6%
2023, 2025
United States USA
16.7%
3.98%
2023, 2022
Marshall Islands MHL
13.4%
1.48%
2023, 2024
Liberia LBR
13%
38.3%
2023, 2022
Micronesia, Fed. Sts. FSM
12.9%
23.1%
2023, 2024
Lesotho LSO
12.6%
32.2%
2023, 2024
Germany DEU
12.3%
0.274%
2024
Austria AUT
11.8%
1.43%
2024
Switzerland CHE
11.7%
0.143%
2023, 2024
France FRA
11.5%
0.204%
2024
Canada CAN
11.3%
4.99%
2024, 2023
Sweden SWE
11.2%
0.57%
2024
United Kingdom GBR
11.1%
0.0698%
2024, 2023
Kiribati KIR
10.9%
8.71%
2023, 2024
World Bank, World Development Indicators World Bank, World Development Indicators
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 2010–2025. 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 7 World Bank regions. The q-value corrects for testing all 13,797 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Health spending and Out of school, primary
This page shows that two measures go together. It does not show that Health spending changes Out of school, primary, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Health spending or Out of school, primary