Across 187 countries, Control of corruption and HDI rise and fall together at r = +0.73 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.23, which could easily be chance (q = 0.21, 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 hdi, 0.628 to 0.862 points, control of corruption is better by 1.13 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.829 points.
Link before adjusting (r)+0.726p = 6.9e-32 · 187 countries
After adjusting for national income+0.227p = 0.002 · likely range [+0.09, +0.36]
p, allowing for regions0.055standard error 0.095 · 7 regions
Check for luck (q)0.207across 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.
Control of corruption · index (approx. -2.5 to 2.5)link with income +0.73 · high
HDI · index, 0 to 1link with income +0.96 · proxy
Both of these rise and fall closely with national income, so a strong link between them before adjusting was close to certain. Read the adjusted figure, not the first one.
“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
+0.726
6.9e-32
187
By rank (Spearman), not adjusted
+0.738
2.1e-33
187
Standard (Pearson), adjusted for national income
+0.227
0.002
187
By rank (Spearman), adjusted for national income
+0.256
0.000
187
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 187 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: +0.499 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.195 (without GUY) to +0.245 (without BTN). 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: GUY (-0.032).
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
30
+0.54
Europe & Central Asia
50
+0.69
Latin America & Caribbean
31
+0.39
Middle East, North Africa, Afghanistan & Pakistan
22
+0.23
Sub-Saharan Africa
46
+0.14
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
63
+0.25
Middle third
62
-0.07
Richest third
62
+0.65
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
108
+0.33
Muslims
49
-0.22
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
-0.19
Never a European colony
21
-0.04
Spain
20
+0.40
United Kingdom
63
+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 = +0.227 after dropping 0 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 28years. 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 = +0.214) but mostly disappears in year-to-year changes (r = +0.033). That points to slow trends particular to each country, not the two measures moving together from year to year.
Across countries (adjusted)+0.227for comparison
Within countries+0.072each country vs itself
…and vs the same year elsewhere+0.214q = 0.001 · 192 countries
Year-on-year changes+0.033q = 0.241
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.
4,564 country-years (one country in one year), 192 countries, 1996–2023, about 24 years each on average. Share of the variation that happens within countries over time: 6% for Control of corruption, 5% for HDI. 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): +0.214. 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)
index, 0 to 1
Years
Denmark DNK
2.29
0.962
2024, 2023
Finland FIN
2.19
0.948
2024, 2023
Luxembourg LUX
2.02
0.922
2024, 2023
Switzerland CHE
2.01
0.97
2024, 2023
Singapore SGP
1.97
0.946
2024, 2023
Sweden SWE
1.97
0.959
2024, 2023
Norway NOR
1.96
0.97
2024, 2023
New Zealand NZL
1.93
0.938
2024, 2023
Netherlands NLD
1.91
0.955
2024, 2023
Australia AUS
1.85
0.958
2024, 2023
Iceland ISL
1.83
0.972
2024, 2023
Germany DEU
1.77
0.959
2024, 2023
Estonia EST
1.67
0.905
2024, 2023
Canada CAN
1.63
0.939
2024, 2023
Ireland IRL
1.57
0.949
2024, 2023
Kaufmann, D. and A. Kraay, Worldwide Governance Indicators, World Bank United Nations Development Programme, Human Development Report 2025
Measures how much people believe public power is used for private gain. It is based on perceptions: it does not count corrupt acts. And perceptions themselves shift with press freedom and with prosecutions.
United Nations Development Programme, Human Development Report Office · via Our World in Data · CC BY 3.0 IGO · updated annual
The geometric mean (a kind of average that multiplies the parts together) of three parts: income per person (GNI per capita), life expectancy, and schooling (expected years and average years). All four inputs are on this site, and each is flagged. So a link between the HDI and any of them is shown for what it is: the index matching a part of itself. For the same reason it is kept out of this site's own topic scores. Those already contain its parts, and adding it would count each twice. It is the most-cited development index there is. It is here mostly so its parts can be read separately.
How this was computed
Data used: most recent value in 2010-2025; values come from 2023–2024. 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 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 Control of corruption and HDI
This page shows that two measures go together. It does not show that Control of corruption changes HDI, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.