placestats

PISA science vs. Youth not in work or study

Fades after adjusting for income

Across 84 countries, PISA science and Youth not in work or study rise and fall together at r = -0.51 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.15, which could easily be chance (q = 0.40, 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 0.26 in r.

Comparing countries across the middle half of pisa science, 403 to 491 PISA points, youth not in work or study is better by 7.34% of 15 to 24 year olds at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 2.88% of 15 to 24 year olds.

Link before adjusting (r)-0.512p = 6.6e-7 · 84 countries
After adjusting for national income-0.149p = 0.180 · likely range [-0.35, +0.07]
p, allowing for regions0.204standard error 0.098 · 5 regions
Check for luck (q)0.401across 14,952 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 science · PISA pointslink with income +0.78 · high
Youth not in work or study · % of 15 to 24 year oldslink with income -0.66 · 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 science · PISA points →Youth not in work or study · % of 15 to 24 year olds →3475613.14%65.7%Albania: 376 PISA points, 21% of 15 to 24 year oldsUnited Arab Emirates: 432 PISA points, 7.46% of 15 to 24 year oldsArgentina: 406 PISA points, 15.2% of 15 to 24 year oldsAustralia: 507 PISA points, 8.4% of 15 to 24 year oldsAustria: 491 PISA points, 13.4% of 15 to 24 year oldsBelgium: 491 PISA points, 7.35% of 15 to 24 year oldsBulgaria: 421 PISA points, 11.5% of 15 to 24 year oldsBosnia and Herzegovina: 398 PISA points, 14.5% of 15 to 24 year oldsBelarus: 471 PISA points, 65.7% of 15 to 24 year oldsBrazil: 403 PISA points, 18.7% of 15 to 24 year oldsBrunei Darussalam: 446 PISA points, 18.4% of 15 to 24 year oldsCanada: 515 PISA points, 13.3% of 15 to 24 year oldsSwitzerland: 503 PISA points, 6.99% of 15 to 24 year oldsChile: 444 PISA points, 13.4% of 15 to 24 year oldsColombia: 411 PISA points, 22% of 15 to 24 year oldsCosta Rica: 411 PISA points, 19.4% of 15 to 24 year oldsCyprus: 411 PISA points, 9.37% of 15 to 24 year oldsCzechia: 498 PISA points, 4.89% of 15 to 24 year oldsGermany: 492 PISA points, 8.2% of 15 to 24 year oldsDenmark: 494 PISA points, 7.91% of 15 to 24 year oldsDominican Republic: 360 PISA points, 24.7% of 15 to 24 year oldsAlgeria: 376 PISA points, 20.9% of 15 to 24 year oldsSpain: 485 PISA points, 9.42% of 15 to 24 year oldsEstonia: 526 PISA points, 10.9% of 15 to 24 year oldsFinland: 511 PISA points, 9.13% of 15 to 24 year oldsFrance: 487 PISA points, 11% of 15 to 24 year oldsUnited Kingdom: 500 PISA points, 14.4% of 15 to 24 year oldsGeorgia: 384 PISA points, 15.3% of 15 to 24 year oldsGreece: 441 PISA points, 10.4% of 15 to 24 year oldsGuatemala: 373 PISA points, 22.3% of 15 to 24 year oldsHong Kong SAR, China: 520 PISA points, 5.95% of 15 to 24 year oldsCroatia: 483 PISA points, 8.97% of 15 to 24 year oldsHungary: 486 PISA points, 9.55% of 15 to 24 year oldsIndonesia: 383 PISA points, 21.6% of 15 to 24 year oldsIreland: 504 PISA points, 6.37% of 15 to 24 year oldsIceland: 447 PISA points, 4% of 15 to 24 year oldsIsrael: 465 PISA points, 15.3% of 15 to 24 year oldsItaly: 477 PISA points, 9.91% of 15 to 24 year oldsJamaica: 403 PISA points, 19.7% of 15 to 24 year oldsJordan: 375 PISA points, 29.4% of 15 to 24 year oldsJapan: 547 PISA points, 3.14% of 15 to 24 year oldsKazakhstan: 423 PISA points, 9.49% of 15 to 24 year oldsCambodia: 347 PISA points, 9.73% of 15 to 24 year oldsLebanon: 384 PISA points, 23.5% of 15 to 24 year oldsLithuania: 484 PISA points, 12.5% of 15 to 24 year oldsLuxembourg: 477 PISA points, 7.73% of 15 to 24 year oldsLatvia: 494 PISA points, 9.12% of 15 to 24 year oldsMacao SAR, China: 543 PISA points, 4.96% of 15 to 24 year oldsMorocco: 365 PISA points, 35.3% of 15 to 24 year oldsMoldova: 417 PISA points, 9.05% of 15 to 24 year oldsMexico: 410 PISA points, 16.2% of 15 to 24 year oldsNorth Macedonia: 380 PISA points, 19.5% of 15 to 24 year oldsMalta: 466 PISA points, 8.36% of 15 to 24 year oldsMontenegro: 403 PISA points, 14.2% of 15 to 24 year oldsMongolia: 412 PISA points, 9.03% of 15 to 24 year oldsMalaysia: 416 PISA points, 10.2% of 15 to 24 year oldsNetherlands: 488 PISA points, 3.91% of 15 to 24 year oldsNorway: 478 PISA points, 6.15% of 15 to 24 year oldsNew Zealand: 504 PISA points, 12.8% of 15 to 24 year oldsPanama: 388 PISA points, 15.1% of 15 to 24 year oldsPeru: 408 PISA points, 22.8% of 15 to 24 year oldsPhilippines: 356 PISA points, 16.5% of 15 to 24 year oldsPoland: 499 PISA points, 10.1% of 15 to 24 year oldsPortugal: 484 PISA points, 6.91% of 15 to 24 year oldsParaguay: 368 PISA points, 18.6% of 15 to 24 year oldsWest Bank and Gaza: 369 PISA points, 25.8% of 15 to 24 year oldsRomania: 428 PISA points, 16.5% of 15 to 24 year oldsRussian Federation: 478 PISA points, 6.68% of 15 to 24 year oldsSaudi Arabia: 390 PISA points, 16.4% of 15 to 24 year oldsSingapore: 561 PISA points, 6.46% of 15 to 24 year oldsEl Salvador: 373 PISA points, 19.1% of 15 to 24 year oldsSerbia: 447 PISA points, 12.7% of 15 to 24 year oldsSlovak Republic: 462 PISA points, 8.02% of 15 to 24 year oldsSlovenia: 500 PISA points, 6.83% of 15 to 24 year oldsSweden: 494 PISA points, 4.95% of 15 to 24 year oldsThailand: 409 PISA points, 12.4% of 15 to 24 year oldsTrinidad and Tobago: 425 PISA points, 15.8% of 15 to 24 year oldsTunisia: 386 PISA points, 22.6% of 15 to 24 year oldsTurkiye: 476 PISA points, 23.3% of 15 to 24 year oldsUkraine: 450 PISA points, 16.5% of 15 to 24 year oldsUruguay: 435 PISA points, 12.6% of 15 to 24 year oldsUnited States: 499 PISA points, 11.6% of 15 to 24 year oldsViet Nam: 472 PISA points, 10.3% of 15 to 24 year oldsKosovo: 357 PISA points, 30% of 15 to 24 year oldsBLRJPNKHMMACMARMNGPHLSGPTURXKX

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5126.6e-784
By rank (Spearman), not adjusted-0.7104.1e-1484
Standard (Pearson), adjusted for national income-0.1490.18084
By rank (Spearman), adjusted for national income-0.3270.00384

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 84 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: +0.363 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.376 (without BLR) to -0.118 (without VNM). 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: BLR (-0.227).

Fragile: this link may not hold up.
  • leave-one-out range spans 0.26 in r
  • 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
East Asia & Pacific14-0.64
Europe & Central Asia43-0.00
Latin America & Caribbean15-0.48

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 third28-0.43
Middle third28+0.22
Richest third28-0.29

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
Christians55-0.00
Muslims16-0.11

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
Spain14-0.19
United Kingdom13-0.00

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 = -0.394 after dropping 2 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 = -0.033, 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 science moved did not tend to see their youth not in work or study move with it.

Across countries (adjusted)-0.149for comparison
Within countries+0.173each country vs itself
…and vs the same year elsewhere-0.033q = 0.888 · 45 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.

261 country-years (one country in one year), 45 countries, 2006–2022, about 6 years each on average. Share of the variation that happens within countries over time: 5% for PISA science, 13% for Youth not in work or study. 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

0.20−0.2-70+6years Youth not in work or study trails PISA science →lag -7: r = -0.162 (n = 214)lag -6: r = -0.128 (n = 217)lag -5: r = -0.058 (n = 218)lag -4: r = -0.200 (n = 239)lag -3: r = -0.127 (n = 234)lag -2: r = -0.092 (n = 239)lag -1: r = -0.021 (n = 243)lag +0: r = -0.033 (n = 261)lag +1: r = -0.169 (n = 247)lag +2: r = -0.115 (n = 261)lag +3: r = -0.105 (n = 253)lag +4: r = -0.070 (n = 200)lag +5: r = -0.028 (n = 215)lag +6: r = -0.018 (n = 210)

Same year (lag 0): -0.033. 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 (-0.20 at lag -4) is higher than the same-year one by 0.17. That gap is not a finding. It is the largest of 14 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


PISA points
% of 15 to 24 year olds		Years
Singapore SGP5616.46%2022, 2025
Japan JPN5473.14%2022, 2019
Macao SAR, China MAC5434.96%2022, 2016
Estonia EST52610.9%2022, 2025
Hong Kong SAR, China HKG5205.95%2022, 2025
Canada CAN51513.3%2022, 2025
Finland FIN5119.13%2022, 2025
Australia AUS5078.4%2022, 2025
New Zealand NZL50412.8%2022, 2024
Ireland IRL5046.37%2022, 2025
Switzerland CHE5036.99%2022, 2025
Slovenia SVN5006.83%2022, 2025
United Kingdom GBR50014.4%2022, 2025
United States USA49911.6%2022, 2025
Poland POL49910.1%2022, 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 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

Youth not in work or study

Share of youth not in education, employment or training, total (% of youth population)

International Labour Organization · CC BY 4.0 · updated quarterly

From labour force surveys, so yearly for about a hundred countries and occasional elsewhere.

How this was computed

Data used: most recent value in 2010-2025; values come from 2014–2025. 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 14,952 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore PISA science and Youth not in work or study

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

More links with PISA science or Youth not in work or study