Do Unemployment and Wellbeing score go together across countries?

Across 105 countries the link before adjusting for anything is r = -0.28, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives -0.26.

Does the link hold within countries over time, not just across countries?

There are not enough years of data within countries to check this over time.

Does Unemployment cause Wellbeing score?

This analysis cannot answer that. It shows only that the two go together. A link between two country measures, adjusted or not, does not show that either one changes the other. Country figures also say nothing about individual people.

Unemployment vs. Wellbeing score

Holds up after adjusting for income

Across 105 countries, Unemployment and Wellbeing score rise and fall together at r = -0.28 (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 = -0.15, q = 0.011, allowing for the many pairs tested). Caution: direction is not consistent across regions.

Comparing countries across the middle half of unemployment, 3.33% to 8.3% of labor force, wellbeing score is worse by 0.222 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0825 typical gaps.

Link before adjusting (r)-0.282p = 0.004 · 105 countries

After adjusting for national income-0.148p = 0.134 · likely range [-0.33, +0.05]

p, allowing for regions0.000standard error 0.020 · 7 regions

Check for luck (q)0.011across 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.

Unemployment · % of labor forcelink with income -0.00 · independent

Wellbeing score · typical gaps (standard deviations)link with income +0.80 · high

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

Every country as a dot

best-fit line line after adjusting

Four ways to measure the link

Method	r	p	Countries
Standard (Pearson), not adjusted	-0.282	0.004	105
By rank (Spearman), not adjusted	-0.257	0.008	105
Standard (Pearson), adjusted for national income	-0.148	0.134	105
By rank (Spearman), adjusted for national income	-0.191	0.052	105

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 105 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: +0.134 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.181 (without MDA) to -0.131 (without MLI). 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: MDA (-0.033).

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.

	n	r
East Asia & Pacific	15	+0.36
Europe & Central Asia	47	-0.10
Latin America & Caribbean	14	-0.08
Middle East, North Africa, Afghanistan & Pakistan	14	-0.03

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.

	n	r
Poorest third	35	-0.28
Middle third	35	-0.12
Richest third	35	+0.35

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.

	n	r
Christians	62	-0.01
Muslims	28	-0.44

By last european coloniser

	n	r
Never a European colony	15	-0.55
Spain	12	-0.33
United Kingdom	25	-0.12

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 = -0.157 after dropping 5 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 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 labor force	typical gaps (standard deviations)	Years
South Africa ZAF	32.4%	-0.515	2025, 2014
West Bank and Gaza PSE	24.4%	-0.644	2022, 2014
Libya LBY	18.8%	-0.158	2025, 2022
Jordan JOR	16.5%	-0.666	2025, 2022
Iraq IRQ	15.5%	-0.726	2025, 2022
Tunisia TUN	15.1%	-0.73	2025, 2022
Haiti HTI	14.9%	-0.461	2025, 2014
Montenegro MNE	13.6%	0.239	2025, 2022
Armenia ARM	12.9%	-0.118	2025, 2022
North Macedonia MKD	12.3%	-0.171	2025, 2022
Georgia GEO	12.1%	-0.493	2025, 2022
Algeria DZA	11.6%	-0.205	2025, 2014
Rwanda RWA	11.4%	-0.867	2025, 2014
Bosnia and Herzegovina BIH	11%	-0.087	2025, 2022
Lebanon LBN	11%	-1.54	2023, 2022

World Bank, World Development Indicators
ivs; whr

Sources

Unemployment

Unemployment, total (% of total labor force) (modeled ILO estimate)

International Labour Organization · CC BY 4.0 · updated quarterly

Wellbeing score

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

The average of 3 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: Self-reported happiness, Interpersonal trust, Life satisfaction.

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 Unemployment and Wellbeing score

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