Interpersonal trust vs. Political corruption
Fades after adjusting for income
Across 103 countries, Interpersonal trust and Political corruption rise and fall together at r = -0.59 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.31, which could easily be chance (q = 0.11, 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 interpersonal trust, 12.5% to 31.6% of respondents, political corruption is better by 0.206 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0904 points.
Link before adjusting (r)-0.591p = 4.9e-11 · 103 countries
After adjusting for national income-0.311p = 0.001 · likely range [-0.48, -0.12]
p, allowing for regions0.022standard error 0.101 · 7 regions
Check for luck (q)0.113across 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.
Interpersonal trust · % of respondentslink with income +0.66 · high
Political corruption · index (0-1)link with income -0.68 · high
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 | -0.591 | 4.9e-11 | 103 |
| By rank (Spearman), not adjusted | -0.592 | 4.7e-11 | 103 |
| Standard (Pearson), adjusted for national income | -0.311 | 0.001 | 103 |
| By rank (Spearman), adjusted for national income | -0.163 | 0.103 | 103 |
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 103 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: +0.280 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from -0.346 (without CHN) to -0.296 (without NZL). 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: CHN (-0.035).
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 | 14 | -0.34 | |
| Europe & Central Asia | 48 | -0.26 | |
| Latin America & Caribbean | 13 | -0.38 | |
| Middle East, North Africa, Afghanistan & Pakistan | 13 | -0.45 |
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 | -0.13 | |
| Middle third | 34 | +0.13 | |
| Richest third | 34 | -0.64 |
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 | 61 | -0.36 | |
| Muslims | 28 | -0.07 |
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 | ||
|---|---|---|---|
| Never a European colony | 15 | -0.02 | |
| Spain | 12 | -0.23 | |
| United Kingdom | 25 | -0.35 |
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 = -0.310 after dropping 6 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 respondents | index (0-1) | Years | |
|---|---|---|---|
| Denmark DNK | 73.9% | 0.004 | 2022, 2025 |
| Norway NOR | 72.1% | 0.01 | 2022, 2025 |
| Finland FIN | 68.4% | 0.031 | 2022, 2025 |
| China CHN | 63.5% | 0.554 | 2022, 2025 |
| Sweden SWE | 62.8% | 0.009 | 2022, 2025 |
| Iceland ISL | 62.3% | 0.014 | 2022, 2025 |
| Switzerland CHE | 58.5% | 0.02 | 2022, 2025 |
| Netherlands NLD | 57% | 0.027 | 2022, 2025 |
| New Zealand NZL | 56.6% | 0.014 | 2022, 2025 |
| Austria AUT | 49.8% | 0.095 | 2022, 2025 |
| Australia AUS | 48.5% | 0.029 | 2022, 2025 |
| Canada CAN | 46.7% | 0.026 | 2022, 2025 |
| United Kingdom GBR | 43.3% | 0.042 | 2022, 2025 |
| Germany DEU | 41.6% | 0.024 | 2022, 2025 |
| Spain ESP | 41% | 0.113 | 2022, 2025 |
Haerpfer, C. et al., World Values Survey; EVS, European Values Study
Coppedge, M. et al., V-Dem Dataset, Varieties of Democracy (V-Dem) Project
Sources
Interpersonal trust
Share agreeing that most people can be trusted
World Values Survey Association and European Values Study · via Our World in Data · Free for non-commercial use with attribution · updated irregular (survey waves, roughly every 5 years)
The share who answer "most people can be trusted" rather than "you can't be too careful". Trust in other people is the classic measure of social ties (social capital). It is only loosely linked to national income. That makes it one of the few measures here where adjusting for GDP is a real test, not a foregone result. The survey runs in waves, not every year. So data for each country are sparse and uneven, and two readings for a country may be five or more years apart.
Political corruption
Political corruption index
V-Dem Institute, University of Gothenburg · via Our World in Data · CC BY 4.0 · updated annual
Expert ratings of corruption across the government, parliament, courts and public sector. It runs the opposite way to the Corruption Perceptions Index, where higher means cleaner. So the two should move strongly in opposite directions. V-Dem is also one of the datasets Transparency International combines into that index.
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 Interpersonal trust and Political corruption
This page shows that two measures go together. It does not show that Interpersonal trust changes Political corruption, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Interpersonal trust or Political corruption
- Electoral democracy vs Political corruption before -0.71 → after adjusting -0.60
- Political corruption vs Regime type before -0.64 → after adjusting -0.49
- Political corruption vs Political stability before -0.69 → after adjusting -0.46
- Interpersonal trust vs Religious attendance before -0.65 → after adjusting -0.44
- Interpersonal trust vs Religion very important before -0.64 → after adjusting -0.43
- Interpersonal trust vs Regulatory quality before +0.67 → after adjusting +0.43
- Interpersonal trust vs Religiously unaffiliated before +0.58 → after adjusting +0.42
- Age at childbearing vs Political corruption before -0.57 → after adjusting -0.41