placestats

Redistribution vs. Youth not in work or study

Fades after adjusting for income

Across 43 countries, Redistribution and Youth not in work or study 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 -0.35, which could easily be chance (q = 0.10, 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.

Comparing countries across the middle half of redistribution, 26.5% to 38.4% reduction in the Gini, youth not in work or study is better by 4.17% 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 2.03% of 15 to 24 year olds.

Link before adjusting (r)-0.649p = 2.5e-6 · 43 countries
After adjusting for national income-0.346p = 0.025 · likely range [-0.59, -0.05]
p, allowing for regions0.019standard error 0.108 · 7 regions
Check for luck (q)0.103across 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.

Redistribution · % reduction in the Ginilink with income +0.50 · moderate
Youth not in work or study · % of 15 to 24 year oldslink with income -0.63 · high

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

Redistribution · % reduction in the Gini →Youth not in work or study · % of 15 to 24 year olds →2.67%48.3%3.14%34.6%Australia: 27.7% reduction in the Gini, 8.53% of 15 to 24 year oldsAustria: 41.4% reduction in the Gini, 13.4% of 15 to 24 year oldsBelgium: 47.7% reduction in the Gini, 8.15% of 15 to 24 year oldsBulgaria: 26% reduction in the Gini, 10.9% of 15 to 24 year oldsBrazil: 13.8% reduction in the Gini, 18.7% of 15 to 24 year oldsCanada: 29.3% reduction in the Gini, 13.3% of 15 to 24 year oldsSwitzerland: 21.2% reduction in the Gini, 6.99% of 15 to 24 year oldsChile: 8.68% reduction in the Gini, 13.4% of 15 to 24 year oldsCosta Rica: 12.6% reduction in the Gini, 19.4% of 15 to 24 year oldsCzechia: 43.5% reduction in the Gini, 4.62% of 15 to 24 year oldsGermany: 38.7% reduction in the Gini, 7.58% of 15 to 24 year oldsDenmark: 37.5% reduction in the Gini, 6.9% of 15 to 24 year oldsSpain: 34.4% reduction in the Gini, 10.5% of 15 to 24 year oldsEstonia: 33.5% reduction in the Gini, 10.2% of 15 to 24 year oldsFinland: 47.2% reduction in the Gini, 8.28% of 15 to 24 year oldsFrance: 42.2% reduction in the Gini, 12.6% of 15 to 24 year oldsUnited Kingdom: 29.7% reduction in the Gini, 14.4% of 15 to 24 year oldsGreece: 36.9% reduction in the Gini, 10.4% of 15 to 24 year oldsCroatia: 33.1% reduction in the Gini, 8.08% of 15 to 24 year oldsHungary: 29.4% reduction in the Gini, 9.98% of 15 to 24 year oldsIndia: 2.67% reduction in the Gini, 25.6% of 15 to 24 year oldsIreland: 41.2% reduction in the Gini, 5.67% of 15 to 24 year oldsIceland: 35.7% reduction in the Gini, 3.98% of 15 to 24 year oldsIsrael: 23.2% reduction in the Gini, 15.3% of 15 to 24 year oldsItaly: 36.2% reduction in the Gini, 12% of 15 to 24 year oldsJapan: 34.1% reduction in the Gini, 3.14% of 15 to 24 year oldsLithuania: 29.7% reduction in the Gini, 14.9% of 15 to 24 year oldsLuxembourg: 35.7% reduction in the Gini, 10.2% of 15 to 24 year oldsLatvia: 28.1% reduction in the Gini, 9.89% of 15 to 24 year oldsMexico: 3.77% reduction in the Gini, 16.2% of 15 to 24 year oldsNetherlands: 34.2% reduction in the Gini, 4.14% of 15 to 24 year oldsNorway: 39.5% reduction in the Gini, 5.82% of 15 to 24 year oldsNew Zealand: 28.7% reduction in the Gini, 12.8% of 15 to 24 year oldsPoland: 41.9% reduction in the Gini, 10.1% of 15 to 24 year oldsPortugal: 36.5% reduction in the Gini, 7.02% of 15 to 24 year oldsRomania: 38.1% reduction in the Gini, 17% of 15 to 24 year oldsRussian Federation: 27% reduction in the Gini, 6.68% of 15 to 24 year oldsSlovak Republic: 48.3% reduction in the Gini, 8.75% of 15 to 24 year oldsSlovenia: 42.4% reduction in the Gini, 7.13% of 15 to 24 year oldsSweden: 33.1% reduction in the Gini, 5.58% of 15 to 24 year oldsTurkiye: 18.6% reduction in the Gini, 22.9% of 15 to 24 year oldsUnited States: 22.1% reduction in the Gini, 11.6% of 15 to 24 year oldsSouth Africa: 12.8% reduction in the Gini, 34.6% of 15 to 24 year oldsAUTBELCHECHLCZEINDMEXROUSVKZAF

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6492.5e-643
By rank (Spearman), not adjusted-0.5160.00043
Standard (Pearson), adjusted for national income-0.3460.02543
By rank (Spearman), adjusted for national income-0.3290.03343

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 43 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: +0.304 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.402 (without ZAF) to -0.309 (without LUX). 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: ZAF (-0.057).

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 Asia31-0.29

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 third15-0.02
Middle third14-0.72
Richest third14-0.16

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
Christians36-0.26

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 = -0.362 after dropping 4 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 14years. 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 = +0.136, 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 redistribution moved did not tend to see their youth not in work or study move with it.

Across countries (adjusted)-0.346for comparison
Within countries+0.125each country vs itself
…and vs the same year elsewhere+0.136q = 0.384 · 38 countries
Year-on-year changes+0.200q = 0.121
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.

429 country-years (one country in one year), 38 countries, 2011–2024, about 11 years each on average. Share of the variation that happens within countries over time: 4% for Redistribution, 14% 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

0.40−0.4-100+7years Youth not in work or study trails Redistribution →lag -10: r = -0.111 (n = 394)lag -9: r = -0.265 (n = 404)lag -8: r = -0.317 (n = 405)lag -7: r = -0.346 (n = 406)lag -6: r = -0.331 (n = 411)lag -5: r = -0.315 (n = 418)lag -4: r = -0.263 (n = 414)lag -3: r = -0.185 (n = 420)lag -2: r = 0.003 (n = 426)lag -1: r = 0.088 (n = 427)lag +0: r = 0.136 (n = 429)lag +1: r = 0.074 (n = 429)lag +2: r = 0.040 (n = 412)lag +3: r = 0.022 (n = 372)lag +4: r = -0.052 (n = 334)lag +5: r = -0.049 (n = 297)lag +6: r = -0.125 (n = 251)lag +7: r = -0.204 (n = 220)

Same year (lag 0): +0.136. 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 (-0.35 at lag -7) is higher than the same-year one by 0.21. That gap is not a finding. It is the largest of 18 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


% reduction in the Gini
% of 15 to 24 year olds		Years
Slovak Republic SVK48.3%8.75%2023, 2024
Belgium BEL47.7%8.15%2023, 2024
Finland FIN47.2%8.28%2023, 2024
Czechia CZE43.5%4.62%2023, 2024
Slovenia SVN42.4%7.13%2023, 2024
France FRA42.2%12.6%2023, 2024
Poland POL41.9%10.1%2023, 2025
Austria AUT41.4%13.4%2023, 2025
Ireland IRL41.2%5.67%2023, 2024
Norway NOR39.5%5.82%2022, 2024
Germany DEU38.7%7.58%2022, 2024
Romania ROU38.1%17%2023, 2024
Denmark DNK37.5%6.9%2022, 2024
Greece GRC36.9%10.4%2023, 2025
Portugal PRT36.5%7.02%2023, 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

Redistribution

Reduction in the Gini coefficient from taxes and transfers

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator · comparable from 2011 only

The Gini before taxes and payments minus the Gini after them, as a share of the first. It shows how much of the inequality produced by the market the government removes. It is built from the before-tax Gini above, so their pair is built from the same numbers and flagged. No "better" direction is set: a country may redistribute little because its market incomes are already equal.

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 2011–2025. 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 Redistribution and Youth not in work or study

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