placestats

Active labour market spending vs. Secondary enrollment

Holds up after adjusting for income

Across 42 countries, Active labour market spending and Secondary enrollment rise and fall together at r = +0.54 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = +0.47, q = 0.017, allowing for the many pairs tested).

Comparing countries across the middle half of active labour market spending, 0.178% to 0.696% of GDP, secondary enrollment is better by 9.47% gross at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 9.15% gross.

Link before adjusting (r)+0.536p = 0.000 · 42 countries
After adjusting for national income+0.475p = 0.002 · likely range [+0.20, +0.68]
p, allowing for regions0.001standard error 0.050 · 5 regions
Check for luck (q)0.017across 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.

Active labour market spending · % of GDPlink with income +0.54 · moderate
Secondary enrollment · % grosslink with income +0.71 · high

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

Every country as a dot

Active labour market spending · % of GDP →Secondary enrollment · % gross →0.001%1.64%81.6%143%Australia: 0.368% of GDP, 132% grossAustria: 0.866% of GDP, 101% grossBelgium: 0.866% of GDP, 143% grossBulgaria: 1.06% of GDP, 94.8% grossCanada: 0.214% of GDP, 104% grossSwitzerland: 0.606% of GDP, 101% grossChile: 0.134% of GDP, 106% grossColombia: 0.436% of GDP, 102% grossCosta Rica: 0.129% of GDP, 122% grossCzechia: 0.288% of GDP, 97.6% grossGermany: 0.562% of GDP, 100% grossDenmark: 1.64% of GDP, 126% grossSpain: 0.923% of GDP, 119% grossEstonia: 0.549% of GDP, 109% grossFinland: 0.838% of GDP, 142% grossFrance: 0.835% of GDP, 104% grossUnited Kingdom: 0.153% of GDP, 112% grossGreece: 0.306% of GDP, 105% grossCroatia: 0.622% of GDP, 105% grossHungary: 0.329% of GDP, 107% grossIreland: 1.22% of GDP, 131% grossIceland: 0.397% of GDP, 109% grossIsrael: 0.131% of GDP, 98.5% grossItaly: 0.442% of GDP, 101% grossJapan: 0.295% of GDP, 102% grossKorea, Rep.: 0.423% of GDP, 96.3% grossLithuania: 0.37% of GDP, 105% grossLuxembourg: 0.699% of GDP, 109% grossLatvia: 0.138% of GDP, 101% grossMexico: 0.001% of GDP, 103% grossNetherlands: 1.51% of GDP, 138% grossNorway: 0.377% of GDP, 116% grossNew Zealand: 0.269% of GDP, 114% grossPeru: 0.087% of GDP, 108% grossPoland: 0.523% of GDP, 108% grossPortugal: 0.687% of GDP, 120% grossRomania: 0.042% of GDP, 81.6% grossSlovak Republic: 0.166% of GDP, 93.2% grossSlovenia: 0.227% of GDP, 108% grossSweden: 1.18% of GDP, 132% grossTurkiye: 0.014% of GDP, 118% grossUnited States: 0.078% of GDP, 97.5% grossAUSAUTBELBGRCRIDNKNLDROUSVKTURUSA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5360.00042
By rank (Spearman), not adjusted+0.3630.01842
Standard (Pearson), adjusted for national income+0.4750.00242
By rank (Spearman), adjusted for national income+0.2730.08442

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 42 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: +0.061 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.411 (without NLD) to +0.557 (without BGR). 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: BGR (+0.082).

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 Asia30+0.50

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 third14+0.02
Middle third14+0.48
Richest third14+0.62

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
Christians35+0.43

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 = +0.343 after dropping 3 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 34years. 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 = +0.034, 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 active labour market spending moved did not tend to see their secondary enrollment move with it.

Across countries (adjusted)+0.475for comparison
Within countries+0.086each country vs itself
…and vs the same year elsewhere+0.034q = 0.682 · 42 countries
Year-on-year changes+0.122q = 0.073

826 country-years (one country in one year), 42 countries, 1990–2023, about 20 years each on average. Share of the variation that happens within countries over time: 34% for Active labour market spending, 24% for Secondary enrollment. 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

0.20−0.2-100+10years Secondary enrollment trails Active labour market spending →lag -10: r = 0.089 (n = 460)lag -9: r = 0.012 (n = 496)lag -8: r = -0.069 (n = 531)lag -7: r = -0.143 (n = 566)lag -6: r = -0.174 (n = 603)lag -5: r = -0.151 (n = 644)lag -4: r = -0.118 (n = 681)lag -3: r = -0.054 (n = 721)lag -2: r = -0.063 (n = 758)lag -1: r = -0.038 (n = 793)lag +0: r = 0.034 (n = 826)lag +1: r = 0.021 (n = 856)lag +2: r = 0.023 (n = 879)lag +3: r = 0.023 (n = 883)lag +4: r = 0.023 (n = 875)lag +5: r = 0.040 (n = 866)lag +6: r = 0.056 (n = 856)lag +7: r = 0.047 (n = 846)lag +8: r = 0.018 (n = 832)lag +9: r = -0.013 (n = 813)lag +10: r = -0.089 (n = 802)

Same year (lag 0): +0.034. 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 (-0.17 at lag -6) is higher than the same-year one by 0.14. That gap is not a finding. It is the largest of 21 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 GDP
% gross		Years
Denmark DNK1.64%126%2021, 2024
Netherlands NLD1.51%138%2021, 2023
Ireland IRL1.22%131%2021, 2022
Sweden SWE1.18%132%2021, 2024
Bulgaria BGR1.06%94.8%2021, 2024
Spain ESP0.923%119%2021, 2024
Belgium BEL0.866%143%2021, 2023
Austria AUT0.866%101%2021, 2024
Finland FIN0.838%142%2021, 2024
France FRA0.835%104%2022, 2024
Luxembourg LUX0.699%109%2021, 2024
Portugal PRT0.687%120%2021, 2023
Croatia HRV0.622%105%2021, 2023
Switzerland CHE0.606%101%2021, 2024
Germany DEU0.562%100%2021, 2024

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

Active labour market spending

Public spending on active labour market programmes

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

Training, help finding jobs, wage subsidies and jobs created by government: spending on getting people into work rather than supporting them while out of it.

Secondary enrollment

School enrollment, secondary (% gross)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2019–2024. 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 Active labour market spending and Secondary enrollment

This page shows that two measures go together. It does not show that Active labour market spending changes Secondary enrollment, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Active labour market spending or Secondary enrollment