placestats

Active labour market spending vs. Health score

Fades after adjusting for income

Across 42 countries, Active labour market spending and Health score 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) leaves r = +0.40, which could easily be chance (q = 0.16, allowing for the many pairs tested, and allowing for countries in the same region being alike).

Comparing countries across the middle half of active labour market spending, 0.178% to 0.696% of GDP, health score is better by 0.243 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.187 typical gaps.

Link before adjusting (r)+0.527p = 0.000 · 42 countries
After adjusting for national income+0.398p = 0.010 · likely range [+0.10, +0.63]
p, allowing for regions0.043standard error 0.136 · 5 regions
Check for luck (q)0.163across 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.

Active labour market spending · % of GDPlink with income +0.54 · moderate
Health score · typical gaps (standard deviations)link with income +0.22 · independent

“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 →Health score · typical gaps (standard deviations) →0.001%1.64%-0.6750.864Australia: 0.368% of GDP, -0.17 typical gaps (standard deviations)Austria: 0.866% of GDP, 0.369 typical gaps (standard deviations)Belgium: 0.866% of GDP, 0.203 typical gaps (standard deviations)Bulgaria: 1.06% of GDP, 0.0868 typical gaps (standard deviations)Canada: 0.214% of GDP, 0.0258 typical gaps (standard deviations)Switzerland: 0.606% of GDP, 0.598 typical gaps (standard deviations)Chile: 0.134% of GDP, -0.675 typical gaps (standard deviations)Colombia: 0.436% of GDP, -0.0599 typical gaps (standard deviations)Costa Rica: 0.129% of GDP, -0.286 typical gaps (standard deviations)Czechia: 0.288% of GDP, -0.0437 typical gaps (standard deviations)Germany: 0.562% of GDP, 0.217 typical gaps (standard deviations)Denmark: 1.64% of GDP, 0.493 typical gaps (standard deviations)Spain: 0.923% of GDP, 0.4 typical gaps (standard deviations)Estonia: 0.549% of GDP, 0.166 typical gaps (standard deviations)Finland: 0.838% of GDP, 0.08 typical gaps (standard deviations)France: 0.835% of GDP, 0.578 typical gaps (standard deviations)United Kingdom: 0.153% of GDP, -0.0207 typical gaps (standard deviations)Greece: 0.306% of GDP, -0.0923 typical gaps (standard deviations)Croatia: 0.622% of GDP, -0.283 typical gaps (standard deviations)Hungary: 0.329% of GDP, -0.299 typical gaps (standard deviations)Ireland: 1.22% of GDP, -0.0742 typical gaps (standard deviations)Iceland: 0.397% of GDP, 0.188 typical gaps (standard deviations)Israel: 0.131% of GDP, 0.167 typical gaps (standard deviations)Italy: 0.442% of GDP, 0.476 typical gaps (standard deviations)Japan: 0.295% of GDP, 0.864 typical gaps (standard deviations)Korea, Rep.: 0.423% of GDP, 0.725 typical gaps (standard deviations)Lithuania: 0.37% of GDP, 0.1 typical gaps (standard deviations)Luxembourg: 0.699% of GDP, 0.291 typical gaps (standard deviations)Latvia: 0.138% of GDP, 0.0645 typical gaps (standard deviations)Mexico: 0.001% of GDP, -0.614 typical gaps (standard deviations)Netherlands: 1.51% of GDP, 0.483 typical gaps (standard deviations)Norway: 0.377% of GDP, 0.263 typical gaps (standard deviations)New Zealand: 0.269% of GDP, -0.326 typical gaps (standard deviations)Peru: 0.087% of GDP, -0.319 typical gaps (standard deviations)Poland: 0.523% of GDP, 0.161 typical gaps (standard deviations)Portugal: 0.687% of GDP, 0.272 typical gaps (standard deviations)Romania: 0.042% of GDP, -0.411 typical gaps (standard deviations)Slovak Republic: 0.166% of GDP, -0.0866 typical gaps (standard deviations)Slovenia: 0.227% of GDP, 0.243 typical gaps (standard deviations)Sweden: 1.18% of GDP, 0.372 typical gaps (standard deviations)Turkiye: 0.014% of GDP, -0.182 typical gaps (standard deviations)United States: 0.078% of GDP, -0.605 typical gaps (standard deviations)CHLDNKIRLITAJPNKORMEXNLDSWEUSA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5270.00042
By rank (Spearman), not adjusted+0.6434.3e-642
Standard (Pearson), adjusted for national income+0.3980.01042
By rank (Spearman), adjusted for national income+0.4960.00142

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: +0.128 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.322 (without USA) to +0.471 (without JPN). 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: USA (-0.077).

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+0.43

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+0.65
Middle third14+0.08
Richest third14+0.58

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+0.51

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 = +0.359 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.

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


% of GDP
typical gaps (standard deviations)		Years
Denmark DNK1.64%0.4932021, 2024
Netherlands NLD1.51%0.4832021, 2024
Ireland IRL1.22%-0.07422021, 2024
Sweden SWE1.18%0.3722021, 2024
Bulgaria BGR1.06%0.08682021, 2024
Spain ESP0.923%0.42021, 2024
Belgium BEL0.866%0.2032021, 2024
Austria AUT0.866%0.3692021, 2024
Finland FIN0.838%0.082021, 2024
France FRA0.835%0.5782022, 2024
Luxembourg LUX0.699%0.2912021, 2024
Portugal PRT0.687%0.2722021, 2024
Croatia HRV0.622%-0.2832021, 2024
Switzerland CHE0.606%0.5982021, 2024
Germany DEU0.562%0.2172021, 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
wdi; who_gho

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.

Health score

Health score

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

The average of 23 measures from 2 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: Anaemia in women, HIV prevalence, Under-5 mortality, Premature NCD mortality, Basic water access, DTP3 immunisation, Physicians, Tobacco use, Basic sanitation, Skilled birth attendance, Maternal mortality, Child stunting, Suicide rate, Road traffic deaths, Tuberculosis incidence, Out-of-pocket health spending, Undernourishment, Food insecurity, Adolescent fertility, Infant mortality, Life expectancy, Adult obesity, Health coverage index.

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 14,952 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 Health score

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

More links with Active labour market spending or Health score