placestats

Equality score vs. PISA maths

Fades after adjusting for income

Across 79 countries, Equality score and PISA maths 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) leaves r = +0.44, which could easily be chance (q = 0.25, allowing for the many pairs tested, and allowing for countries in the same region being alike). Caution: much weaker within regions than across them (largely a between-region difference).

Comparing countries across the middle half of pisa maths, 387 to 478 PISA points, equality score is better by 0.387 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.426 typical gaps.

Link before adjusting (r)+0.563p = 6.5e-8 · 79 countries
After adjusting for national income+0.437p = 6.3e-5 · likely range [+0.24, +0.60]
p, allowing for regions0.003standard error 0.071 · 5 regions
Check for luck (q)0.252across 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.

Equality score · typical gaps (standard deviations)link with income +0.64 · high
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

Equality score · typical gaps (standard deviations) →PISA maths · PISA points →-0.9061.06338536Albania: 0.741 typical gaps (standard deviations), 368 PISA pointsUnited Arab Emirates: 0.921 typical gaps (standard deviations), 431 PISA pointsArgentina: -0.0236 typical gaps (standard deviations), 378 PISA pointsAustralia: 0.473 typical gaps (standard deviations), 487 PISA pointsAustria: 0.632 typical gaps (standard deviations), 487 PISA pointsBelgium: 0.895 typical gaps (standard deviations), 489 PISA pointsBulgaria: 0.143 typical gaps (standard deviations), 417 PISA pointsBosnia and Herzegovina: 0.689 typical gaps (standard deviations), 406 PISA pointsBelarus: 1.04 typical gaps (standard deviations), 472 PISA pointsBrazil: -0.529 typical gaps (standard deviations), 379 PISA pointsCanada: 0.62 typical gaps (standard deviations), 497 PISA pointsSwitzerland: 0.491 typical gaps (standard deviations), 508 PISA pointsChile: -0.0426 typical gaps (standard deviations), 412 PISA pointsColombia: -0.906 typical gaps (standard deviations), 383 PISA pointsCosta Rica: -0.196 typical gaps (standard deviations), 385 PISA pointsCyprus: 0.611 typical gaps (standard deviations), 418 PISA pointsCzechia: 0.961 typical gaps (standard deviations), 487 PISA pointsGermany: 0.484 typical gaps (standard deviations), 475 PISA pointsDenmark: 0.709 typical gaps (standard deviations), 489 PISA pointsDominican Republic: 0.177 typical gaps (standard deviations), 339 PISA pointsAlgeria: 0.852 typical gaps (standard deviations), 360 PISA pointsSpain: 0.498 typical gaps (standard deviations), 473 PISA pointsEstonia: 0.666 typical gaps (standard deviations), 510 PISA pointsFinland: 0.858 typical gaps (standard deviations), 484 PISA pointsFrance: 0.608 typical gaps (standard deviations), 474 PISA pointsUnited Kingdom: 0.566 typical gaps (standard deviations), 489 PISA pointsGeorgia: 0.382 typical gaps (standard deviations), 390 PISA pointsGreece: 0.503 typical gaps (standard deviations), 430 PISA pointsGuatemala: -0.409 typical gaps (standard deviations), 344 PISA pointsCroatia: 0.701 typical gaps (standard deviations), 463 PISA pointsHungary: 0.656 typical gaps (standard deviations), 473 PISA pointsIndonesia: 0.358 typical gaps (standard deviations), 366 PISA pointsIreland: 0.769 typical gaps (standard deviations), 492 PISA pointsIceland: 0.895 typical gaps (standard deviations), 459 PISA pointsIsrael: 0.227 typical gaps (standard deviations), 458 PISA pointsItaly: 0.444 typical gaps (standard deviations), 471 PISA pointsJamaica: 0.11 typical gaps (standard deviations), 377 PISA pointsJordan: 0.499 typical gaps (standard deviations), 361 PISA pointsJapan: 0.551 typical gaps (standard deviations), 536 PISA pointsKazakhstan: 0.76 typical gaps (standard deviations), 425 PISA pointsKorea, Rep.: 0.545 typical gaps (standard deviations), 527 PISA pointsLebanon: 0.249 typical gaps (standard deviations), 393 PISA pointsLithuania: 0.341 typical gaps (standard deviations), 475 PISA pointsLuxembourg: 0.505 typical gaps (standard deviations), 483 PISA pointsLatvia: 0.474 typical gaps (standard deviations), 483 PISA pointsMorocco: 0.0733 typical gaps (standard deviations), 365 PISA pointsMoldova: 0.895 typical gaps (standard deviations), 414 PISA pointsMexico: -0.0506 typical gaps (standard deviations), 395 PISA pointsNorth Macedonia: 0.413 typical gaps (standard deviations), 389 PISA pointsMalta: 0.6 typical gaps (standard deviations), 466 PISA pointsMontenegro: 0.403 typical gaps (standard deviations), 406 PISA pointsMongolia: 0.623 typical gaps (standard deviations), 425 PISA pointsMalaysia: 0.0997 typical gaps (standard deviations), 409 PISA pointsNetherlands: 0.958 typical gaps (standard deviations), 493 PISA pointsNorway: 0.91 typical gaps (standard deviations), 468 PISA pointsPanama: -0.497 typical gaps (standard deviations), 357 PISA pointsPeru: 0.00275 typical gaps (standard deviations), 391 PISA pointsPhilippines: 0.0435 typical gaps (standard deviations), 355 PISA pointsPoland: 0.795 typical gaps (standard deviations), 489 PISA pointsPortugal: 0.48 typical gaps (standard deviations), 472 PISA pointsParaguay: -0.155 typical gaps (standard deviations), 338 PISA pointsWest Bank and Gaza: 0.292 typical gaps (standard deviations), 366 PISA pointsQatar: 0.421 typical gaps (standard deviations), 414 PISA pointsRomania: 0.708 typical gaps (standard deviations), 428 PISA pointsRussian Federation: 0.539 typical gaps (standard deviations), 488 PISA pointsEl Salvador: 0.0329 typical gaps (standard deviations), 343 PISA pointsSerbia: 0.525 typical gaps (standard deviations), 440 PISA pointsSlovak Republic: 1.06 typical gaps (standard deviations), 464 PISA pointsSlovenia: 1.02 typical gaps (standard deviations), 485 PISA pointsSweden: 0.734 typical gaps (standard deviations), 482 PISA pointsThailand: 0.525 typical gaps (standard deviations), 394 PISA pointsTunisia: 0.484 typical gaps (standard deviations), 367 PISA pointsTurkiye: -0.0777 typical gaps (standard deviations), 453 PISA pointsUkraine: 0.967 typical gaps (standard deviations), 441 PISA pointsUruguay: 0.135 typical gaps (standard deviations), 409 PISA pointsUnited States: 0.00824 typical gaps (standard deviations), 465 PISA pointsUzbekistan: 0.5 typical gaps (standard deviations), 364 PISA pointsViet Nam: 0.323 typical gaps (standard deviations), 469 PISA pointsKosovo: -0.0202 typical gaps (standard deviations), 355 PISA pointsALBCOLCZEDZAGTMMDANLDPANSVNTURUSA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5636.5e-879
By rank (Spearman), not adjusted+0.5675.0e-879
Standard (Pearson), adjusted for national income+0.4376.3e-579
By rank (Spearman), adjusted for national income+0.3860.00079

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 79 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: +0.126 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.386 (without PAN) to +0.466 (without DZA). 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: PAN (-0.051).

Fragile: this link may not hold up.
  • 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 Asia44+0.32
Latin America & Caribbean14+0.09

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 third27+0.36
Middle third26+0.63
Richest third26+0.07

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
Christians54+0.60
Muslims16-0.23

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+0.10

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 = +0.451 after dropping 1 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


typical gaps (standard deviations)
PISA points		Years
Slovak Republic SVK1.064642023, 2022
Belarus BLR1.044722020, 2018
Slovenia SVN1.024852023, 2022
Ukraine UKR0.9674412020, 2022
Czechia CZE0.9614872023, 2022
Netherlands NLD0.9584932021, 2022
United Arab Emirates ARE0.9214312018, 2022
Norway NOR0.914682023, 2022
Moldova MDA0.8954142023, 2022
Iceland ISL0.8954592019, 2022
Belgium BEL0.8954892023, 2022
Finland FIN0.8584842023, 2022
Algeria DZA0.8523602011, 2015
Poland POL0.7954892023, 2022
Ireland IRL0.7694922023, 2022

wdi
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

Equality score

Equality score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 2 measures from 1 publisher. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Extreme poverty rate, Gini index.

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 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 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 Equality score and PISA maths

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

More links with Equality score or PISA maths