placestats

Fertility rate vs. PISA science

Holds up after adjusting for income

Across 87 countries, Fertility rate and PISA science rise and fall together at r = -0.65 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.38 (q = 0.0076, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak negative link remains.

Comparing countries across the middle half of pisa science, 403 to 491 PISA points, fertility rate is 0.563 births per woman lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.425 births per woman.

Link before adjusting (r)-0.648p = 1.2e-11 · 87 countries
After adjusting for national income-0.380p = 0.000 · likely range [-0.55, -0.18]
p, allowing for regions0.002standard error 0.052 · 5 regions
Check for luck (q)0.008across 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.

Fertility rate · births per womanlink with income -0.81 · 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

Fertility rate · births per woman →PISA science · PISA points →0.5823.49347561Albania: 1.34 births per woman, 376 PISA pointsUnited Arab Emirates: 1.21 births per woman, 432 PISA pointsArgentina: 1.5 births per woman, 406 PISA pointsAustralia: 1.48 births per woman, 507 PISA pointsAustria: 1.31 births per woman, 491 PISA pointsBelgium: 1.44 births per woman, 491 PISA pointsBulgaria: 1.72 births per woman, 421 PISA pointsBosnia and Herzegovina: 1.49 births per woman, 398 PISA pointsBelarus: 1.22 births per woman, 471 PISA pointsBrazil: 1.61 births per woman, 403 PISA pointsBrunei Darussalam: 1.73 births per woman, 446 PISA pointsCanada: 1.25 births per woman, 515 PISA pointsSwitzerland: 1.29 births per woman, 503 PISA pointsChile: 1.14 births per woman, 444 PISA pointsColombia: 1.63 births per woman, 411 PISA pointsCosta Rica: 1.32 births per woman, 411 PISA pointsCyprus: 1.38 births per woman, 411 PISA pointsCzechia: 1.36 births per woman, 498 PISA pointsGermany: 1.36 births per woman, 492 PISA pointsDenmark: 1.47 births per woman, 494 PISA pointsDominican Republic: 2.22 births per woman, 360 PISA pointsAlgeria: 2.72 births per woman, 376 PISA pointsSpain: 1.1 births per woman, 485 PISA pointsEstonia: 1.18 births per woman, 526 PISA pointsFinland: 1.25 births per woman, 511 PISA pointsFrance: 1.61 births per woman, 487 PISA pointsUnited Kingdom: 1.55 births per woman, 500 PISA pointsGeorgia: 1.8 births per woman, 384 PISA pointsGreece: 1.24 births per woman, 441 PISA pointsGuatemala: 2.29 births per woman, 373 PISA pointsHong Kong SAR, China: 0.841 births per woman, 520 PISA pointsCroatia: 1.46 births per woman, 483 PISA pointsHungary: 1.41 births per woman, 486 PISA pointsIndonesia: 2.12 births per woman, 383 PISA pointsIreland: 1.47 births per woman, 504 PISA pointsIceland: 1.56 births per woman, 447 PISA pointsIsrael: 2.87 births per woman, 465 PISA pointsItaly: 1.18 births per woman, 477 PISA pointsJamaica: 1.35 births per woman, 403 PISA pointsJordan: 2.6 births per woman, 375 PISA pointsJapan: 1.15 births per woman, 547 PISA pointsKazakhstan: 2.98 births per woman, 423 PISA pointsCambodia: 2.55 births per woman, 347 PISA pointsKorea, Rep.: 0.748 births per woman, 528 PISA pointsLebanon: 2.23 births per woman, 384 PISA pointsLithuania: 1.11 births per woman, 484 PISA pointsLuxembourg: 1.25 births per woman, 477 PISA pointsLatvia: 1.24 births per woman, 494 PISA pointsMacao SAR, China: 0.582 births per woman, 543 PISA pointsMorocco: 2.21 births per woman, 365 PISA pointsMoldova: 1.73 births per woman, 417 PISA pointsMexico: 1.89 births per woman, 410 PISA pointsNorth Macedonia: 1.4 births per woman, 380 PISA pointsMalta: 1.01 births per woman, 466 PISA pointsMontenegro: 1.8 births per woman, 403 PISA pointsMongolia: 2.5 births per woman, 412 PISA pointsMalaysia: 1.54 births per woman, 416 PISA pointsNetherlands: 1.43 births per woman, 488 PISA pointsNorway: 1.45 births per woman, 478 PISA pointsNew Zealand: 1.57 births per woman, 504 PISA pointsPanama: 2.11 births per woman, 388 PISA pointsPeru: 1.97 births per woman, 408 PISA pointsPhilippines: 1.89 births per woman, 356 PISA pointsPoland: 1.14 births per woman, 499 PISA pointsPortugal: 1.41 births per woman, 484 PISA pointsParaguay: 2.42 births per woman, 368 PISA pointsWest Bank and Gaza: 3.25 births per woman, 369 PISA pointsQatar: 1.72 births per woman, 432 PISA pointsRomania: 1.39 births per woman, 428 PISA pointsRussian Federation: 1.42 births per woman, 478 PISA pointsSaudi Arabia: 2.31 births per woman, 390 PISA pointsSingapore: 0.97 births per woman, 561 PISA pointsEl Salvador: 1.77 births per woman, 373 PISA pointsSerbia: 1.64 births per woman, 447 PISA pointsSlovak Republic: 1.46 births per woman, 462 PISA pointsSlovenia: 1.52 births per woman, 500 PISA pointsSweden: 1.43 births per woman, 494 PISA pointsThailand: 1.2 births per woman, 409 PISA pointsTrinidad and Tobago: 1.54 births per woman, 425 PISA pointsTunisia: 1.82 births per woman, 386 PISA pointsTurkiye: 1.48 births per woman, 476 PISA pointsUkraine: 0.988 births per woman, 450 PISA pointsUruguay: 1.4 births per woman, 435 PISA pointsUnited States: 1.63 births per woman, 499 PISA pointsUzbekistan: 3.49 births per woman, 355 PISA pointsViet Nam: 1.9 births per woman, 472 PISA pointsKosovo: 1.54 births per woman, 357 PISA pointsALBISRKAZKHMKORMACMKDPSESGPUZBXKX

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6481.2e-1187
By rank (Spearman), not adjusted-0.6451.5e-1187
Standard (Pearson), adjusted for national income-0.3800.00087
By rank (Spearman), adjusted for national income-0.4402.3e-587

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: +0.268 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.422 (without PSE) to -0.336 (without SAU). 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: SAU (+0.044).

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 & Pacific15-0.35
Europe & Central Asia44-0.36
Latin America & Caribbean15-0.81

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 third29-0.37
Middle third29-0.55
Richest third29-0.65

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
Christians55-0.54
Muslims18-0.14

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 Kingdom14-0.17

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 = -0.484 after dropping 6 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.

Within countries over time, there is no link that is clearly more than chance (r = -0.142, 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 fertility rate moved did not tend to see their pisa science move with it.

Across countries (adjusted)-0.380for comparison
Within countries+0.021each country vs itself
…and vs the same year elsewhere-0.142q = 0.333 · 55 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.

324 country-years (one country in one year), 55 countries, 2006–2022, about 6 years each on average. Share of the variation that happens within countries over time: 5% for Fertility rate, 12% 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

0.40−0.4-60+10years PISA science trails Fertility rate →lag -6: r = -0.118 (n = 255)lag -5: r = -0.110 (n = 255)lag -4: r = -0.103 (n = 255)lag -3: r = -0.175 (n = 255)lag -2: r = -0.140 (n = 324)lag -1: r = -0.138 (n = 324)lag +0: r = -0.142 (n = 324)lag +1: r = -0.190 (n = 324)lag +2: r = -0.194 (n = 324)lag +3: r = -0.232 (n = 324)lag +4: r = -0.229 (n = 324)lag +5: r = -0.255 (n = 324)lag +6: r = -0.273 (n = 324)lag +7: r = -0.304 (n = 324)lag +8: r = -0.337 (n = 324)lag +9: r = -0.342 (n = 324)lag +10: r = -0.344 (n = 324)

Same year (lag 0): -0.142. 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.

This curve peaks at the edge of the window (lag +10), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.

The data


births per woman
PISA points		Years
Uzbekistan UZB3.493552024, 2022
West Bank and Gaza PSE3.253692024, 2022
Kazakhstan KAZ2.984232024, 2022
Israel ISR2.874652024, 2022
Algeria DZA2.723762024, 2015
Jordan JOR2.63752024, 2022
Cambodia KHM2.553472024, 2022
Mongolia MNG2.54122024, 2022
Paraguay PRY2.423682024, 2022
Saudi Arabia SAU2.313902024, 2022
Guatemala GTM2.293732024, 2022
Lebanon LBN2.233842024, 2018
Dominican Republic DOM2.223602024, 2022
Morocco MAR2.213652024, 2022
Indonesia IDN2.123832024, 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

Fertility rate

Fertility rate, total (births per woman)

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 2015–2024. 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 Fertility rate and PISA science

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

More links with Fertility rate or PISA science