Across 177 countries, Government effectiveness and Unemployment rise and fall together at r = -0.20 (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 = -0.23, q = 0.015, allowing for the many pairs tested). Caution: direction is not consistent across regions.
Comparing countries across the middle half of unemployment, 3.17% to 8.54% of labor force, government effectiveness is worse by 0.178 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.116 points.
Link before adjusting (r)-0.197p = 0.009 · 177 countries
After adjusting for national income-0.230p = 0.002 · likely range [-0.37, -0.08]
p, allowing for regions0.063standard error 0.101 · 7 regions
Check for luck (q)0.015across 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.
Government effectiveness · index (approx. -2.5 to 2.5)link with income +0.85 · proxy
Unemployment · % of labor forcelink with income -0.00 · independent
“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
-0.197
0.009
177
By rank (Spearman), not adjusted
-0.073
0.333
177
Standard (Pearson), adjusted for national income
-0.230
0.002
177
By rank (Spearman), adjusted for national income
-0.136
0.072
177
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 177 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: -0.032 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from -0.247 (without BWA) to -0.205 (without LBY). 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: LBY (+0.025).
Fragile: this link may not hold up.
direction is not consistent across regions
much weaker within regions than across them (largely a between-region difference)
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
25
+0.11
Europe & Central Asia
48
+0.05
Latin America & Caribbean
29
-0.02
Middle East, North Africa, Afghanistan & Pakistan
22
-0.13
Sub-Saharan Africa
45
-0.22
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
59
-0.31
Middle third
59
-0.12
Richest third
59
-0.02
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
106
-0.18
Muslims
49
-0.34
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.
n
r
France
25
-0.51
Never a European colony
21
-0.39
Spain
19
+0.17
United Kingdom
55
-0.28
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 = -0.209 after dropping 11 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 29years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.
The link shows up within countries over time (r = -0.158) but mostly disappears in year-to-year changes (r = -0.038). That points to slow trends particular to each country, not the two measures moving together from year to year.
Across countries (adjusted)-0.230for comparison
Within countries-0.192each country vs itself
…and vs the same year elsewhere-0.158q = 0.000 · 184 countries
Year-on-year changes-0.038q = 0.098
Read with care.
Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.
4,715 country-years (one country in one year), 184 countries, 1996–2024, about 26 years each on average. Share of the variation that happens within countries over time: 14% for Government effectiveness, 7% for Unemployment. 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
Same year (lag 0): -0.158. 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 data
index (approx. -2.5 to 2.5)
% of labor force
Years
Singapore SGP
2.28
2.82%
2024, 2025
Japan JPN
2.09
2.45%
2024, 2025
Luxembourg LUX
2.04
6.34%
2024, 2025
Denmark DNK
1.91
5.53%
2024, 2025
New Zealand NZL
1.85
5.08%
2024, 2025
Norway NOR
1.84
4.64%
2024, 2025
Switzerland CHE
1.84
4.87%
2024, 2025
Finland FIN
1.82
9.46%
2024, 2025
Australia AUS
1.81
4.09%
2024, 2025
Sweden SWE
1.77
8.69%
2024, 2025
Canada CAN
1.76
6.91%
2024, 2025
Netherlands NLD
1.75
3.87%
2024, 2025
Iceland ISL
1.65
3.63%
2024, 2025
Hong Kong SAR, China HKG
1.64
2.8%
2024, 2025
Ireland IRL
1.61
4.63%
2024, 2025
Kaufmann, D. and A. Kraay, Worldwide Governance Indicators, World Bank World Bank, World Development Indicators
Unemployment, total (% of total labor force) (modeled ILO estimate)
International Labour Organization · CC BY 4.0 · updated quarterly
How this was computed
Data used: most recent value in 2010-2025; values come from 2021–2025. 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 Government effectiveness and Unemployment
This page shows that two measures go together. It does not show that Government effectiveness changes Unemployment, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Government effectiveness or Unemployment