placestats

Education score vs. Youth not in work or study

Fades after adjusting for income

Across 172 countries, Education score and Youth not in work or study 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 -0.14, which could easily be chance (q = 0.32, 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: direction is not consistent across regions.

Comparing countries across the middle half of youth not in work or study, 11.5% to 25.8% of 15 to 24 year olds, education score is worse by 0.418 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0736 typical gaps.

Link before adjusting (r)-0.527p = 1.1e-13 · 172 countries
After adjusting for national income-0.137p = 0.075 · likely range [-0.28, +0.01]
p, allowing for regions0.121standard error 0.076 · 7 regions
Check for luck (q)0.319across 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.

Education score · typical gaps (standard deviations)link with income +0.81 · proxy
Youth not in work or study · % of 15 to 24 year oldslink with income -0.63 · 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

Education score · typical gaps (standard deviations) →Youth not in work or study · % of 15 to 24 year olds →-2.11.443.14%65.7%Aruba: 0.697 typical gaps (standard deviations), 16.6% of 15 to 24 year oldsAfghanistan: -0.557 typical gaps (standard deviations), 43.8% of 15 to 24 year oldsAngola: -0.482 typical gaps (standard deviations), 24.9% of 15 to 24 year oldsAlbania: 0.923 typical gaps (standard deviations), 21% of 15 to 24 year oldsUnited Arab Emirates: 0.911 typical gaps (standard deviations), 8.92% of 15 to 24 year oldsArgentina: 1.03 typical gaps (standard deviations), 15.2% of 15 to 24 year oldsArmenia: 0.65 typical gaps (standard deviations), 20.2% of 15 to 24 year oldsAntigua and Barbuda: 0.912 typical gaps (standard deviations), 20.8% of 15 to 24 year oldsAustralia: 1.03 typical gaps (standard deviations), 8.53% of 15 to 24 year oldsAustria: 1 typical gaps (standard deviations), 13.4% of 15 to 24 year oldsAzerbaijan: 0.629 typical gaps (standard deviations), 9.64% of 15 to 24 year oldsBurundi: -0.587 typical gaps (standard deviations), 11.2% of 15 to 24 year oldsBelgium: 1.25 typical gaps (standard deviations), 8.15% of 15 to 24 year oldsBenin: -0.586 typical gaps (standard deviations), 14.2% of 15 to 24 year oldsBurkina Faso: -0.582 typical gaps (standard deviations), 24.5% of 15 to 24 year oldsBangladesh: 0.335 typical gaps (standard deviations), 15.4% of 15 to 24 year oldsBulgaria: 0.794 typical gaps (standard deviations), 10.9% of 15 to 24 year oldsBosnia and Herzegovina: 0.607 typical gaps (standard deviations), 14.3% of 15 to 24 year oldsBelarus: 0.722 typical gaps (standard deviations), 65.7% of 15 to 24 year oldsBelize: 0.166 typical gaps (standard deviations), 24.9% of 15 to 24 year oldsBermuda: 0.693 typical gaps (standard deviations), 6.79% of 15 to 24 year oldsBolivia: 0.634 typical gaps (standard deviations), 8.02% of 15 to 24 year oldsBrazil: 0.731 typical gaps (standard deviations), 18.7% of 15 to 24 year oldsBarbados: 0.581 typical gaps (standard deviations), 29% of 15 to 24 year oldsBrunei Darussalam: 0.499 typical gaps (standard deviations), 19% of 15 to 24 year oldsBhutan: 0.277 typical gaps (standard deviations), 15.3% of 15 to 24 year oldsBotswana: 0.469 typical gaps (standard deviations), 38% of 15 to 24 year oldsCanada: 1.06 typical gaps (standard deviations), 13.3% of 15 to 24 year oldsSwitzerland: 0.92 typical gaps (standard deviations), 6.99% of 15 to 24 year oldsChile: 0.979 typical gaps (standard deviations), 13.4% of 15 to 24 year oldsCote d'Ivoire: -0.0434 typical gaps (standard deviations), 18.8% of 15 to 24 year oldsCameroon: -0.125 typical gaps (standard deviations), 23.2% of 15 to 24 year oldsCongo, Dem. Rep.: -0.251 typical gaps (standard deviations), 31.4% of 15 to 24 year oldsColombia: 0.63 typical gaps (standard deviations), 22% of 15 to 24 year oldsComoros: 0.00771 typical gaps (standard deviations), 21.2% of 15 to 24 year oldsCabo Verde: -0.216 typical gaps (standard deviations), 28% of 15 to 24 year oldsCosta Rica: 0.629 typical gaps (standard deviations), 19.4% of 15 to 24 year oldsCyprus: 1.02 typical gaps (standard deviations), 13.2% of 15 to 24 year oldsCzechia: 1.08 typical gaps (standard deviations), 4.62% of 15 to 24 year oldsGermany: 0.938 typical gaps (standard deviations), 7.58% of 15 to 24 year oldsDjibouti: -0.825 typical gaps (standard deviations), 44% of 15 to 24 year oldsDenmark: 0.941 typical gaps (standard deviations), 6.9% of 15 to 24 year oldsDominican Republic: 0.651 typical gaps (standard deviations), 24.7% of 15 to 24 year oldsAlgeria: 0.663 typical gaps (standard deviations), 20.9% of 15 to 24 year oldsEcuador: 0.722 typical gaps (standard deviations), 17.7% of 15 to 24 year oldsEgypt, Arab Rep.: 0.489 typical gaps (standard deviations), 23.8% of 15 to 24 year oldsSpain: 0.983 typical gaps (standard deviations), 10.5% of 15 to 24 year oldsEstonia: 0.841 typical gaps (standard deviations), 10.2% of 15 to 24 year oldsEthiopia: -0.777 typical gaps (standard deviations), 17.5% of 15 to 24 year oldsFinland: 1.02 typical gaps (standard deviations), 8.28% of 15 to 24 year oldsFiji: 0.887 typical gaps (standard deviations), 20.8% of 15 to 24 year oldsFrance: 0.907 typical gaps (standard deviations), 12.6% of 15 to 24 year oldsMicronesia, Fed. Sts.: -0.00832 typical gaps (standard deviations), 28.7% of 15 to 24 year oldsGabon: -0.00264 typical gaps (standard deviations), 20.2% of 15 to 24 year oldsUnited Kingdom: 1.19 typical gaps (standard deviations), 14.4% of 15 to 24 year oldsGeorgia: 0.697 typical gaps (standard deviations), 14.7% of 15 to 24 year oldsGhana: 0.168 typical gaps (standard deviations), 23.9% of 15 to 24 year oldsGuinea: -0.598 typical gaps (standard deviations), 34.3% of 15 to 24 year oldsGambia, The: -0.345 typical gaps (standard deviations), 36.5% of 15 to 24 year oldsGuinea-Bissau: -1.3 typical gaps (standard deviations), 13.2% of 15 to 24 year oldsGreece: 1.31 typical gaps (standard deviations), 10.4% of 15 to 24 year oldsGrenada: 0.804 typical gaps (standard deviations), 20.1% of 15 to 24 year oldsGuatemala: 0.22 typical gaps (standard deviations), 24% of 15 to 24 year oldsGuyana: 0.39 typical gaps (standard deviations), 44.8% of 15 to 24 year oldsHong Kong SAR, China: 1.34 typical gaps (standard deviations), 5.95% of 15 to 24 year oldsHonduras: 0.0516 typical gaps (standard deviations), 29% of 15 to 24 year oldsCroatia: 0.985 typical gaps (standard deviations), 8.08% of 15 to 24 year oldsHungary: 0.83 typical gaps (standard deviations), 9.98% of 15 to 24 year oldsIndonesia: 0.591 typical gaps (standard deviations), 21.4% of 15 to 24 year oldsIndia: 0.605 typical gaps (standard deviations), 25.6% of 15 to 24 year oldsIreland: 1.18 typical gaps (standard deviations), 5.67% of 15 to 24 year oldsIran, Islamic Rep.: 0.667 typical gaps (standard deviations), 24.3% of 15 to 24 year oldsIraq: -0.133 typical gaps (standard deviations), 36.9% of 15 to 24 year oldsIceland: 1.26 typical gaps (standard deviations), 3.98% of 15 to 24 year oldsIsrael: 0.804 typical gaps (standard deviations), 15.3% of 15 to 24 year oldsItaly: 0.94 typical gaps (standard deviations), 12% of 15 to 24 year oldsJamaica: 0.446 typical gaps (standard deviations), 19.7% of 15 to 24 year oldsJordan: 0.68 typical gaps (standard deviations), 29.4% of 15 to 24 year oldsJapan: 1.04 typical gaps (standard deviations), 3.14% of 15 to 24 year oldsKazakhstan: 0.74 typical gaps (standard deviations), 9.49% of 15 to 24 year oldsKenya: 0.0734 typical gaps (standard deviations), 18.5% of 15 to 24 year oldsKyrgyz Republic: 0.764 typical gaps (standard deviations), 19.3% of 15 to 24 year oldsCambodia: 0.174 typical gaps (standard deviations), 6.32% of 15 to 24 year oldsKiribati: 0.376 typical gaps (standard deviations), 35.4% of 15 to 24 year oldsLao PDR: -0.35 typical gaps (standard deviations), 22.5% of 15 to 24 year oldsLebanon: 0.088 typical gaps (standard deviations), 23.5% of 15 to 24 year oldsLiberia: -1.22 typical gaps (standard deviations), 39.9% of 15 to 24 year oldsSt. Lucia: 0.462 typical gaps (standard deviations), 25.5% of 15 to 24 year oldsSri Lanka: 0.421 typical gaps (standard deviations), 17.2% of 15 to 24 year oldsLesotho: -0.337 typical gaps (standard deviations), 38% of 15 to 24 year oldsLithuania: 0.928 typical gaps (standard deviations), 14.9% of 15 to 24 year oldsLuxembourg: 0.66 typical gaps (standard deviations), 10.2% of 15 to 24 year oldsLatvia: 0.923 typical gaps (standard deviations), 9.89% of 15 to 24 year oldsMacao SAR, China: 0.965 typical gaps (standard deviations), 4.96% of 15 to 24 year oldsMorocco: 0.345 typical gaps (standard deviations), 35.3% of 15 to 24 year oldsMoldova: 0.734 typical gaps (standard deviations), 9.05% of 15 to 24 year oldsMadagascar: -0.569 typical gaps (standard deviations), 24.3% of 15 to 24 year oldsMaldives: 0.427 typical gaps (standard deviations), 26.3% of 15 to 24 year oldsMexico: 0.636 typical gaps (standard deviations), 16.2% of 15 to 24 year oldsMarshall Islands: 0.934 typical gaps (standard deviations), 40% of 15 to 24 year oldsNorth Macedonia: 0.658 typical gaps (standard deviations), 19.5% of 15 to 24 year oldsMali: -1.24 typical gaps (standard deviations), 30.1% of 15 to 24 year oldsMalta: 0.945 typical gaps (standard deviations), 7.84% of 15 to 24 year oldsMyanmar: -0.0676 typical gaps (standard deviations), 15% of 15 to 24 year oldsMontenegro: 0.943 typical gaps (standard deviations), 14.2% of 15 to 24 year oldsMongolia: 0.749 typical gaps (standard deviations), 9.9% of 15 to 24 year oldsMozambique: -0.56 typical gaps (standard deviations), 19.2% of 15 to 24 year oldsMauritania: -0.911 typical gaps (standard deviations), 44.1% of 15 to 24 year oldsMauritius: 0.621 typical gaps (standard deviations), 13.9% of 15 to 24 year oldsMalawi: -0.546 typical gaps (standard deviations), 39.4% of 15 to 24 year oldsMalaysia: 0.529 typical gaps (standard deviations), 10.2% of 15 to 24 year oldsNamibia: 0.228 typical gaps (standard deviations), 31.9% of 15 to 24 year oldsNiger: -1.04 typical gaps (standard deviations), 15.7% of 15 to 24 year oldsNigeria: -0.241 typical gaps (standard deviations), 11.9% of 15 to 24 year oldsNicaragua: 0.168 typical gaps (standard deviations), 24.5% of 15 to 24 year oldsNetherlands: 1.27 typical gaps (standard deviations), 4.14% of 15 to 24 year oldsNorway: 1 typical gaps (standard deviations), 5.82% of 15 to 24 year oldsNepal: 0.452 typical gaps (standard deviations), 34.8% of 15 to 24 year oldsNaoero: 0.496 typical gaps (standard deviations), 50.4% of 15 to 24 year oldsNew Zealand: 1.44 typical gaps (standard deviations), 12.8% of 15 to 24 year oldsOman: 0.293 typical gaps (standard deviations), 25.5% of 15 to 24 year oldsPakistan: -0.556 typical gaps (standard deviations), 28.5% of 15 to 24 year oldsPanama: 0.393 typical gaps (standard deviations), 15.1% of 15 to 24 year oldsPeru: 0.773 typical gaps (standard deviations), 22.8% of 15 to 24 year oldsPhilippines: 0.548 typical gaps (standard deviations), 12.4% of 15 to 24 year oldsPalau: 0.84 typical gaps (standard deviations), 11.3% of 15 to 24 year oldsPapua New Guinea: -0.297 typical gaps (standard deviations), 27.7% of 15 to 24 year oldsPoland: 0.952 typical gaps (standard deviations), 10.1% of 15 to 24 year oldsPuerto Rico (US): 0.956 typical gaps (standard deviations), 19.5% of 15 to 24 year oldsPortugal: 1.02 typical gaps (standard deviations), 7.02% of 15 to 24 year oldsParaguay: 0.452 typical gaps (standard deviations), 18.6% of 15 to 24 year oldsWest Bank and Gaza: 0.564 typical gaps (standard deviations), 25.8% of 15 to 24 year oldsRomania: 0.584 typical gaps (standard deviations), 17% of 15 to 24 year oldsRussian Federation: 0.85 typical gaps (standard deviations), 6.68% of 15 to 24 year oldsRwanda: -0.127 typical gaps (standard deviations), 15.3% of 15 to 24 year oldsSaudi Arabia: 0.8 typical gaps (standard deviations), 16.4% of 15 to 24 year oldsSudan: -0.831 typical gaps (standard deviations), 46.5% of 15 to 24 year oldsSenegal: -0.815 typical gaps (standard deviations), 35.2% of 15 to 24 year oldsSingapore: 1.26 typical gaps (standard deviations), 6.46% of 15 to 24 year oldsSolomon Islands: -0.0603 typical gaps (standard deviations), 7.04% of 15 to 24 year oldsSierra Leone: -0.279 typical gaps (standard deviations), 25.9% of 15 to 24 year oldsEl Salvador: 0.37 typical gaps (standard deviations), 20.5% of 15 to 24 year oldsSomalia, Fed. Rep.: -2.1 typical gaps (standard deviations), 51% of 15 to 24 year oldsSerbia: 0.761 typical gaps (standard deviations), 12.7% of 15 to 24 year oldsSao Tome and Principe: 0.172 typical gaps (standard deviations), 43.8% of 15 to 24 year oldsSuriname: -0.157 typical gaps (standard deviations), 18.2% of 15 to 24 year oldsSlovak Republic: 0.801 typical gaps (standard deviations), 8.75% of 15 to 24 year oldsSlovenia: 1.18 typical gaps (standard deviations), 7.13% of 15 to 24 year oldsSweden: 0.968 typical gaps (standard deviations), 5.58% of 15 to 24 year oldsEswatini: 0.404 typical gaps (standard deviations), 36.5% of 15 to 24 year oldsSeychelles: 0.782 typical gaps (standard deviations), 16.9% of 15 to 24 year oldsChad: -1.2 typical gaps (standard deviations), 42.3% of 15 to 24 year oldsTogo: 0.075 typical gaps (standard deviations), 13% of 15 to 24 year oldsThailand: 0.764 typical gaps (standard deviations), 12.4% of 15 to 24 year oldsTajikistan: 0.525 typical gaps (standard deviations), 41.3% of 15 to 24 year oldsTimor-Leste: 0.12 typical gaps (standard deviations), 29.1% of 15 to 24 year oldsTonga: 0.921 typical gaps (standard deviations), 25.6% of 15 to 24 year oldsTrinidad and Tobago: 0.581 typical gaps (standard deviations), 15.8% of 15 to 24 year oldsTunisia: 0.496 typical gaps (standard deviations), 22.6% of 15 to 24 year oldsTurkiye: 1.03 typical gaps (standard deviations), 22.9% of 15 to 24 year oldsTuvalu: 0.577 typical gaps (standard deviations), 34.3% of 15 to 24 year oldsTanzania: -0.351 typical gaps (standard deviations), 12.8% of 15 to 24 year oldsUganda: -0.832 typical gaps (standard deviations), 13.8% of 15 to 24 year oldsUkraine: 0.784 typical gaps (standard deviations), 16.5% of 15 to 24 year oldsUruguay: 0.9 typical gaps (standard deviations), 14% of 15 to 24 year oldsUnited States: 1.11 typical gaps (standard deviations), 11.6% of 15 to 24 year oldsViet Nam: 0.537 typical gaps (standard deviations), 10.3% of 15 to 24 year oldsVanuatu: 0.198 typical gaps (standard deviations), 29.3% of 15 to 24 year oldsSamoa: 0.515 typical gaps (standard deviations), 30.1% of 15 to 24 year oldsSouth Africa: 0.665 typical gaps (standard deviations), 34.6% of 15 to 24 year oldsZambia: -0.123 typical gaps (standard deviations), 26.7% of 15 to 24 year oldsZimbabwe: 0.181 typical gaps (standard deviations), 36% of 15 to 24 year oldsBLRGNBHKGISLLBRMHLNERNLDNRUSOMTCDUGA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5271.1e-13172
By rank (Spearman), not adjusted-0.6143.1e-19172
Standard (Pearson), adjusted for national income-0.1370.075172
By rank (Spearman), adjusted for national income-0.1840.016172

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 172 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: +0.391 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.169 (without GNB) to -0.095 (without GUY). 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: GUY (+0.042).

Fragile: this link may not hold up.
  • direction is not consistent across regions

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 & Pacific29+0.16
Europe & Central Asia46-0.19
Latin America & Caribbean28-0.49
Middle East, North Africa, Afghanistan & Pakistan17-0.61
Sub-Saharan Africa43-0.20

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 third58-0.12
Middle third57-0.19
Richest third57-0.53

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
Christians104-0.10
Muslims42-0.23

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
France21-0.72
Never a European colony17+0.05
Spain19-0.40
United Kingdom55-0.17

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 = -0.133 after dropping 7 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.

Loading…

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)
% of 15 to 24 year olds		Years
New Zealand NZL1.4412.8%2023, 2024
Hong Kong SAR, China HKG1.345.95%2024, 2025
Greece GRC1.3110.4%2023, 2025
Netherlands NLD1.274.14%2023, 2024
Iceland ISL1.263.98%2023, 2024
Singapore SGP1.266.46%2023, 2025
Belgium BEL1.258.15%2023, 2024
United Kingdom GBR1.1914.4%2023, 2025
Ireland IRL1.185.67%2022, 2024
Slovenia SVN1.187.13%2023, 2024
United States USA1.1111.6%2022, 2025
Czechia CZE1.084.62%2023, 2024
Canada CAN1.0613.3%2023, 2025
Japan JPN1.043.14%2023, 2019
Argentina ARG1.0315.2%2023, 2025

uis; undp_hdr; wdi
World Bank, World Development Indicators

Sources

Education score

Education score

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

The average of 10 measures from 3 publishers. 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: Primary completion, Expected schooling, Mean years of schooling, Adult literacy, Pupil-teacher ratio, Primary enrollment, Out of school, primary, Secondary enrollment, Tertiary enrollment, Researchers.

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 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 7 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 Education score and Youth not in work or study

This page shows that two measures go together. It does not show that Education score 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 Education score or Youth not in work or study