placestats

Extreme poverty rate vs. PISA science

Fades after adjusting for income

Across 79 countries, Extreme poverty rate and PISA science rise and fall together at r = -0.53 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.24, which could easily be chance (q = 0.19, 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: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of pisa science, 403 to 488 PISA points, extreme poverty rate is better by 1.86% of population at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1.12% of population.

Link before adjusting (r)-0.529p = 5.3e-7 · 79 countries
After adjusting for national income-0.239p = 0.035 · likely range [-0.44, -0.02]
p, allowing for regions0.143standard error 0.132 · 5 regions
Check for luck (q)0.191across 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.

Extreme poverty rate · % of populationlink with income -0.83 · proxy
PISA science · PISA pointslink with income +0.78 · 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

Extreme poverty rate · % of population →PISA science · PISA points →0%10%355547Albania: 0.3% of population, 376 PISA pointsUnited Arab Emirates: 0% of population, 432 PISA pointsArgentina: 1% of population, 406 PISA pointsAustralia: 0.9% of population, 507 PISA pointsAustria: 0.5% of population, 491 PISA pointsBelgium: 0.1% of population, 491 PISA pointsBulgaria: 1% of population, 421 PISA pointsBosnia and Herzegovina: 0.3% of population, 398 PISA pointsBelarus: 0% of population, 471 PISA pointsBrazil: 3% of population, 403 PISA pointsCanada: 0.3% of population, 515 PISA pointsSwitzerland: 0.2% of population, 503 PISA pointsChile: 0.4% of population, 444 PISA pointsColombia: 8.5% of population, 411 PISA pointsCosta Rica: 0.8% of population, 411 PISA pointsCyprus: 0% of population, 411 PISA pointsCzechia: 0% of population, 498 PISA pointsGermany: 0.7% of population, 492 PISA pointsDenmark: 0.4% of population, 494 PISA pointsDominican Republic: 0.8% of population, 360 PISA pointsAlgeria: 0% of population, 376 PISA pointsSpain: 0.8% of population, 485 PISA pointsEstonia: 0.3% of population, 526 PISA pointsFinland: 0.2% of population, 511 PISA pointsFrance: 0.1% of population, 487 PISA pointsUnited Kingdom: 0.4% of population, 500 PISA pointsGeorgia: 4.2% of population, 384 PISA pointsGreece: 0.6% of population, 441 PISA pointsGuatemala: 9.7% of population, 373 PISA pointsCroatia: 0.3% of population, 483 PISA pointsHungary: 0.9% of population, 486 PISA pointsIndonesia: 4% of population, 383 PISA pointsIreland: 0.1% of population, 504 PISA pointsIceland: 0.1% of population, 447 PISA pointsIsrael: 0.4% of population, 465 PISA pointsItaly: 0.9% of population, 477 PISA pointsJamaica: 1.4% of population, 403 PISA pointsJordan: 0.1% of population, 375 PISA pointsJapan: 1.2% of population, 547 PISA pointsKazakhstan: 0% of population, 423 PISA pointsKorea, Rep.: 0.1% of population, 528 PISA pointsLebanon: 5.8% of population, 384 PISA pointsLithuania: 1.1% of population, 484 PISA pointsLuxembourg: 0.1% of population, 477 PISA pointsLatvia: 0.4% of population, 494 PISA pointsMorocco: 3.7% of population, 365 PISA pointsMoldova: 0.1% of population, 417 PISA pointsMexico: 1.6% of population, 410 PISA pointsNorth Macedonia: 3.9% of population, 380 PISA pointsMalta: 0.4% of population, 466 PISA pointsMontenegro: 2.5% of population, 403 PISA pointsMongolia: 0.4% of population, 412 PISA pointsMalaysia: 0% of population, 416 PISA pointsNetherlands: 0.1% of population, 488 PISA pointsNorway: 0.2% of population, 478 PISA pointsPanama: 3.1% of population, 388 PISA pointsPeru: 5.1% of population, 408 PISA pointsPhilippines: 5.3% of population, 356 PISA pointsPoland: 0.2% of population, 499 PISA pointsPortugal: 0.4% of population, 484 PISA pointsParaguay: 2.1% of population, 368 PISA pointsWest Bank and Gaza: 2.1% of population, 369 PISA pointsQatar: 0% of population, 432 PISA pointsRomania: 0.7% of population, 428 PISA pointsRussian Federation: 0.1% of population, 478 PISA pointsEl Salvador: 4.6% of population, 373 PISA pointsSerbia: 1.1% of population, 447 PISA pointsSlovak Republic: 0.5% of population, 462 PISA pointsSlovenia: 0% of population, 500 PISA pointsSweden: 0.8% of population, 494 PISA pointsThailand: 0% of population, 409 PISA pointsTunisia: 0.7% of population, 386 PISA pointsTurkiye: 0.2% of population, 476 PISA pointsUkraine: 0% of population, 450 PISA pointsUruguay: 0.2% of population, 435 PISA pointsUnited States: 1.1% of population, 499 PISA pointsUzbekistan: 2.3% of population, 355 PISA pointsViet Nam: 1.6% of population, 472 PISA pointsKosovo: 10% of population, 357 PISA pointsCOLDOMDZAESTGTMJORJPNKORXKX

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5295.3e-779
By rank (Spearman), not adjusted-0.4375.7e-579
Standard (Pearson), adjusted for national income-0.2390.03579
By rank (Spearman), adjusted for national income-0.0860.45579

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: +0.290 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.262 (without COL) to -0.190 (without XKX). 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: XKX (+0.049).

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.

nr
Europe & Central Asia44-0.43
Latin America & Caribbean14-0.11

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 third27-0.27
Middle third26-0.35
Richest third26+0.26

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
Christians54-0.30
Muslims16-0.34

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+0.09

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 = -0.030 after dropping 12 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 17years. 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 = -0.176) but mostly disappears in year-to-year changes (r = —). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)-0.239for comparison
Within countries-0.085each country vs itself
…and vs the same year elsewhere-0.176q = 0.031 · 41 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.

236 country-years (one country in one year), 41 countries, 2006–2022, about 6 years each on average. Share of the variation that happens within countries over time: 4% for Extreme poverty rate, 22% for PISA science. 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

0.40−0.4-20+6years PISA science trails Extreme poverty rate →lag -2: r = -0.094 (n = 212)lag -1: r = -0.159 (n = 232)lag +0: r = -0.176 (n = 236)lag +1: r = -0.211 (n = 248)lag +2: r = -0.220 (n = 247)lag +3: r = -0.299 (n = 239)lag +4: r = -0.375 (n = 233)lag +5: r = -0.319 (n = 225)lag +6: r = -0.308 (n = 213)

Same year (lag 0): -0.176. 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 largest value on this curve (-0.38 at lag +4) is higher than the same-year one by 0.20. That gap is not a finding. It is the largest of 9 closely related estimates, and picking the biggest of many tests always makes it look bigger. That is exactly why nothing on this site is ranked or chosen by lag.

The data


% of population
PISA points		Years
Kosovo XKX10%3572022
Guatemala GTM9.7%3732023, 2022
Colombia COL8.5%4112024, 2022
Lebanon LBN5.8%3842022, 2018
Philippines PHL5.3%3562023, 2022
Peru PER5.1%4082024, 2022
El Salvador SLV4.6%3732023, 2022
Georgia GEO4.2%3842024, 2022
Indonesia IDN4%3832025, 2022
North Macedonia MKD3.9%3802019, 2022
Morocco MAR3.7%3652013, 2022
Panama PAN3.1%3882024, 2022
Brazil BRA3%4032024, 2022
Montenegro MNE2.5%4032021, 2022
Uzbekistan UZB2.3%3552025, 2022

World Bank, World Development Indicators
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

Extreme poverty rate

Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population)

World Bank · CC BY 4.0 · updated quarterly

PISA science

PISA mean science score

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

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 Extreme poverty rate and PISA science

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

More links with Extreme poverty rate or PISA science