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Government spending per capita vs. PISA maths

Fades after adjusting for income

Across 43 countries, Government spending per capita and PISA maths rise and fall together at r = +0.55 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.26, which could easily be chance (q = 0.18, 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: leave-one-out range spans 0.34 in r.

Comparing countries across the middle half of pisa maths, 458 to 488 PISA points, government spending per capita is $5,252 higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap reverses, to $1,908 the other way.

Link before adjusting (r)+0.552p = 0.000 · 43 countries
After adjusting for national income-0.263p = 0.092 · likely range [-0.53, +0.04]
p, allowing for regions0.227standard error 0.185 · 5 regions
Check for luck (q)0.182across 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.

Government spending per capita · current international dollarslink with income +0.92 · proxy
PISA maths · PISA pointslink with income +0.79 · high

Both of these rise and fall closely with national income, so a strong link between them before adjusting was close to certain. Read the adjusted figure, not the first one.

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

Government spending per capita · current international dollars →PISA maths · PISA points →$3,279$72,957366536Australia: $29,639, 487 PISA pointsAustria: $41,817, 487 PISA pointsBelgium: $40,194, 489 PISA pointsBulgaria: $16,433, 417 PISA pointsBrazil: $10,810, 379 PISA pointsCanada: $29,521, 497 PISA pointsSwitzerland: $32,409, 508 PISA pointsChile: $9,208, 412 PISA pointsColombia: $11,382, 383 PISA pointsCosta Rica: $11,794, 385 PISA pointsCzechia: $24,719, 487 PISA pointsGermany: $36,555, 475 PISA pointsDenmark: $38,309, 489 PISA pointsSpain: $26,400, 473 PISA pointsEstonia: $22,116, 510 PISA pointsFinland: $37,614, 484 PISA pointsFrance: $35,798, 474 PISA pointsUnited Kingdom: $29,093, 489 PISA pointsGreece: $21,055, 430 PISA pointsCroatia: $23,743, 463 PISA pointsHungary: $22,871, 473 PISA pointsIndonesia: $3,279, 366 PISA pointsIreland: $31,581, 492 PISA pointsIceland: $39,385, 459 PISA pointsIsrael: $25,449, 458 PISA pointsItaly: $31,377, 471 PISA pointsJapan: $20,594, 536 PISA pointsKorea, Rep.: $21,401, 527 PISA pointsLithuania: $21,954, 475 PISA pointsLuxembourg: $72,957, 483 PISA pointsLatvia: $19,891, 483 PISA pointsMexico: $7,585, 395 PISA pointsNetherlands: $37,878, 493 PISA pointsNorway: $50,329, 468 PISA pointsNew Zealand: $23,949, 479 PISA pointsPoland: $24,692, 489 PISA pointsPortugal: $22,321, 472 PISA pointsRomania: $21,349, 428 PISA pointsSlovak Republic: $22,559, 464 PISA pointsSlovenia: $26,764, 485 PISA pointsSweden: $35,854, 482 PISA pointsTurkiye: $10,287, 453 PISA pointsUnited States: $34,073, 465 PISA pointsAUTBRACOLESTIDNISLJPNKORLUXNOR

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5520.00043
By rank (Spearman), not adjusted+0.5070.00143
Standard (Pearson), adjusted for national income-0.2630.09243
By rank (Spearman), adjusted for national income-0.2840.06943

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 43 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: +0.288 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.464 (without IRL) to -0.124 (without LUX). 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: IRL (-0.200).

Fragile: this link may not hold up.
  • leave-one-out range spans 0.34 in r
  • correlation moves sharply once outliers are trimmed
  • much weaker within regions than across them (largely a between-region difference)

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.

nr
Europe & Central Asia30-0.08

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.

nr
Poorest third15+0.25
Middle third14-0.70
Richest third14-0.29

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.

nr
Christians35-0.12

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 = -0.083 after dropping 8 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


current international dollars
PISA points		Years
Luxembourg LUX$72,9574832024, 2018
Norway NOR$50,3294682024, 2022
Austria AUT$41,8174872024, 2022
Belgium BEL$40,1944892024, 2022
Iceland ISL$39,3854592024, 2022
Denmark DNK$38,3094892024, 2022
Netherlands NLD$37,8784932024, 2022
Finland FIN$37,6144842024, 2022
Germany DEU$36,5554752024, 2022
Sweden SWE$35,8544822024, 2022
France FRA$35,7984742024, 2022
United States USA$34,0734652024, 2022
Switzerland CHE$32,4095082024, 2022
Ireland IRL$31,5814922024, 2022
Italy ITA$31,3774712024, 2022

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
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

Government spending per capita

General government expenditure per capita

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

All levels of government, in current dollars adjusted for what money buys in each country (purchasing power). So it grows over time with inflation as well as differing across countries. Where it is used for adjusting, it is measured in percentage terms (on a log scale), like income. Compared with national income, this measure answers a question nobody is asking. It is money per person set against money per person. So it moves with GDP per capita at about +0.86. Its development loading, which shows how much a measure just reflects how developed a country is, is +0.92. Rich countries spend far more per person because they have far more per person, and almost all of that figure comes from dividing by people. To ask whether government is a larger part of what a country has, you need a share of GDP, not an amount per head. Three measures here do that: government consumption, government expense and tax revenue. Against income those run +0.12, +0.29 and +0.32. That is a much smaller answer, and the real one.

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 2018–2024. 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 Government spending per capita and PISA maths

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

More links with Government spending per capita or PISA maths