placestats

PISA maths vs. Population 65+

Fades after adjusting for income

Across 87 countries, PISA maths and Population 65+ rise and fall together at r = +0.69 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) leaves r = +0.56, which could easily be chance (q = 0.10, allowing for the many pairs tested, and allowing for countries in the same region being alike).

Comparing countries across the middle half of pisa maths, 389 to 482 PISA points, population 65+ is 7.55% of population higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 8.46% of population.

Link before adjusting (r)+0.688p = 1.9e-13 · 87 countries
After adjusting for national income+0.556p = 2.7e-8 · likely range [+0.39, +0.69]
p, allowing for regions0.018standard error 0.144 · 5 regions
Check for luck (q)0.101across 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.

PISA maths · PISA pointslink with income +0.79 · high
Population 65+ · % of populationlink with income +0.76 · 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

PISA maths · PISA points →Population 65+ · % of population →3365751.7%30%Albania: 368 PISA points, 17.6% of populationUnited Arab Emirates: 431 PISA points, 1.79% of populationArgentina: 378 PISA points, 12.6% of populationAustralia: 487 PISA points, 18.1% of populationAustria: 487 PISA points, 21.1% of populationBelgium: 489 PISA points, 21% of populationBulgaria: 417 PISA points, 22.2% of populationBosnia and Herzegovina: 406 PISA points, 22.9% of populationBelarus: 472 PISA points, 18.3% of populationBrazil: 379 PISA points, 11.5% of populationBrunei Darussalam: 442 PISA points, 7.24% of populationCanada: 497 PISA points, 20.3% of populationSwitzerland: 508 PISA points, 20.4% of populationChile: 412 PISA points, 14.6% of populationColombia: 383 PISA points, 10.2% of populationCosta Rica: 385 PISA points, 12.8% of populationCyprus: 418 PISA points, 14.9% of populationCzechia: 487 PISA points, 21.2% of populationGermany: 475 PISA points, 23.7% of populationDenmark: 489 PISA points, 21.1% of populationDominican Republic: 339 PISA points, 8.19% of populationAlgeria: 360 PISA points, 6.81% of populationSpain: 473 PISA points, 21.6% of populationEstonia: 510 PISA points, 21.8% of populationFinland: 484 PISA points, 24.2% of populationFrance: 474 PISA points, 22.5% of populationUnited Kingdom: 489 PISA points, 19.7% of populationGeorgia: 390 PISA points, 16% of populationGreece: 430 PISA points, 24.4% of populationGuatemala: 344 PISA points, 4.96% of populationHong Kong SAR, China: 540 PISA points, 23.7% of populationCroatia: 463 PISA points, 23.6% of populationHungary: 473 PISA points, 21.2% of populationIndonesia: 366 PISA points, 7.54% of populationIreland: 492 PISA points, 16.2% of populationIceland: 459 PISA points, 16% of populationIsrael: 458 PISA points, 12.7% of populationItaly: 471 PISA points, 25.1% of populationJamaica: 377 PISA points, 8.58% of populationJordan: 361 PISA points, 4.75% of populationJapan: 536 PISA points, 30% of populationKazakhstan: 425 PISA points, 9% of populationCambodia: 336 PISA points, 6.38% of populationKorea, Rep.: 527 PISA points, 20.3% of populationLebanon: 393 PISA points, 10.4% of populationLithuania: 475 PISA points, 20.7% of populationLuxembourg: 483 PISA points, 15.8% of populationLatvia: 483 PISA points, 22.2% of populationMacao SAR, China: 552 PISA points, 15.1% of populationMorocco: 365 PISA points, 8.45% of populationMoldova: 414 PISA points, 16.9% of populationMexico: 395 PISA points, 8.52% of populationNorth Macedonia: 389 PISA points, 18.5% of populationMalta: 466 PISA points, 20.5% of populationMontenegro: 406 PISA points, 18.3% of populationMongolia: 425 PISA points, 5.43% of populationMalaysia: 409 PISA points, 8.03% of populationNetherlands: 493 PISA points, 20.9% of populationNorway: 468 PISA points, 19.1% of populationNew Zealand: 479 PISA points, 17.6% of populationPanama: 357 PISA points, 9.66% of populationPeru: 391 PISA points, 9.47% of populationPhilippines: 355 PISA points, 5.72% of populationPoland: 489 PISA points, 20.8% of populationPortugal: 472 PISA points, 24.9% of populationParaguay: 338 PISA points, 6.72% of populationWest Bank and Gaza: 366 PISA points, 3.85% of populationQatar: 414 PISA points, 1.7% of populationRomania: 428 PISA points, 20.1% of populationRussian Federation: 488 PISA points, 17.8% of populationSaudi Arabia: 389 PISA points, 3.06% of populationSingapore: 575 PISA points, 14.2% of populationEl Salvador: 343 PISA points, 8.31% of populationSerbia: 440 PISA points, 23.1% of populationSlovak Republic: 464 PISA points, 19% of populationSlovenia: 485 PISA points, 22.2% of populationSweden: 482 PISA points, 20.9% of populationThailand: 394 PISA points, 16% of populationTrinidad and Tobago: 417 PISA points, 12.9% of populationTunisia: 367 PISA points, 9.94% of populationTurkiye: 453 PISA points, 10.6% of populationUkraine: 441 PISA points, 19% of populationUruguay: 409 PISA points, 16.3% of populationUnited States: 465 PISA points, 18.4% of populationUzbekistan: 364 PISA points, 6.07% of populationViet Nam: 469 PISA points, 9.49% of populationKosovo: 355 PISA points, 10.5% of populationALBAREBIHGRCGTMHKGJPNKHMKORMACPRYSGP

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6881.9e-1387
By rank (Spearman), not adjusted+0.6842.7e-1387
Standard (Pearson), adjusted for national income+0.5562.7e-887
By rank (Spearman), adjusted for national income+0.5833.8e-987

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 87 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: +0.131 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.507 (without QAT) to +0.595 (without SGP). 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: QAT (-0.049).

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
East Asia & Pacific15+0.58
Europe & Central Asia44+0.44
Latin America & Caribbean15+0.72

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 third29+0.39
Middle third29+0.59
Richest third29+0.72

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
Christians55+0.67
Muslims18+0.18

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.

nr
Spain14+0.74
United Kingdom14+0.70

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 = +0.556 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.

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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 20years. 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 = -0.204, 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 pisa maths moved did not tend to see their population 65+ move with it.

Across countries (adjusted)+0.556for comparison
Within countries-0.286each country vs itself
…and vs the same year elsewhere-0.204q = 0.122 · 56 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.

367 country-years (one country in one year), 56 countries, 2003–2022, about 7 years each on average. Share of the variation that happens within countries over time: 5% for PISA maths, 10% for Population 65+. 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

0.30−0.3-100+7years Population 65+ trails PISA maths →lag -10: r = 0.007 (n = 367)lag -9: r = -0.012 (n = 367)lag -8: r = -0.033 (n = 367)lag -7: r = -0.059 (n = 367)lag -6: r = -0.090 (n = 367)lag -5: r = -0.120 (n = 367)lag -4: r = -0.150 (n = 367)lag -3: r = -0.175 (n = 367)lag -2: r = -0.189 (n = 367)lag -1: r = -0.201 (n = 367)lag +0: r = -0.204 (n = 367)lag +1: r = -0.195 (n = 367)lag +2: r = -0.186 (n = 367)lag +3: r = -0.179 (n = 367)lag +4: r = -0.202 (n = 298)lag +5: r = -0.184 (n = 298)lag +6: r = -0.171 (n = 298)lag +7: r = -0.154 (n = 298)

Same year (lag 0): -0.204. 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


PISA points
% of population		Years
Singapore SGP57514.2%2022, 2025
Macao SAR, China MAC55215.1%2022, 2025
Hong Kong SAR, China HKG54023.7%2022, 2025
Japan JPN53630%2022, 2025
Korea, Rep. KOR52720.3%2022, 2025
Estonia EST51021.8%2022, 2025
Switzerland CHE50820.4%2022, 2025
Canada CAN49720.3%2022, 2025
Netherlands NLD49320.9%2022, 2025
Ireland IRL49216.2%2022, 2025
Belgium BEL48921%2022, 2025
Denmark DNK48921.1%2022, 2025
United Kingdom GBR48919.7%2022, 2025
Poland POL48920.8%2022, 2025
Russian Federation RUS48817.8%2018, 2025

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
World Bank, World Development Indicators

Sources

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.

Population 65+

Population ages 65 and above (% of total)

World Bank · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2015–2025. 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 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 PISA maths and Population 65+

This page shows that two measures go together. It does not show that PISA maths changes Population 65+, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with PISA maths or Population 65+