Across 167 countries, Control of corruption and Independent opposition rise and fall together at r = +0.51 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) leaves r = +0.43, which could easily be chance (q = 0.085, allowing for the many pairs tested, and allowing for countries in the same region being alike).
Comparing countries across the middle half of independent opposition, 0.383 to 2.06 points, control of corruption is better by 0.609 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.371 points.
Link before adjusting (r)+0.513p = 1.4e-12 · 167 countries
After adjusting for national income+0.434p = 5.4e-9 · likely range [+0.30, +0.55]
p, allowing for regions0.005standard error 0.100 · 7 regions
Check for luck (q)0.085across 17,292 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
Independent opposition · score (higher = more independent)link with income +0.45 · moderate
“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
+0.513
1.4e-12
167
By rank (Spearman), not adjusted
+0.617
6.5e-19
167
Standard (Pearson), adjusted for national income
+0.434
5.4e-9
167
By rank (Spearman), adjusted for national income
+0.470
1.7e-10
167
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 167 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: +0.079 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.417 (without TKM) to +0.465 (without RWA). 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: RWA (+0.031).
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
21
+0.52
Europe & Central Asia
49
+0.57
Latin America & Caribbean
23
+0.56
Middle East, North Africa, Afghanistan & Pakistan
20
-0.03
Sub-Saharan Africa
46
+0.31
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
56
+0.32
Middle third
55
+0.38
Richest third
56
+0.49
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
99
+0.46
Muslims
47
+0.18
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
+0.20
Never a European colony
20
+0.42
Spain
19
+0.47
United Kingdom
48
+0.47
By official ideology
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
Nationalist
24
+0.56
No strong official ideology
117
+0.47
By party system
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
A few parties banned
26
+0.47
No parties banned
122
+0.50
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 = +0.491 after dropping 7 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 = +0.126) but mostly disappears in year-to-year changes (r = +0.060). That points to slow trends particular to each country, not the two measures moving together from year to year.
Across countries (adjusted)+0.434for comparison
Within countries+0.108each country vs itself
…and vs the same year elsewhere+0.126q = 0.020 · 172 countries
Year-on-year changes+0.060q = 0.080
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.
4,437 country-years (one country in one year), 172 countries, 1996–2024, about 26 years each on average. Share of the variation that happens within countries over time: 8% for Control of corruption, 5% for Independent opposition. 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): +0.126. 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)
score (higher = more independent)
Years
Denmark DNK
2.29
2.83
2024, 2025
Finland FIN
2.19
2.65
2024, 2025
Luxembourg LUX
2.02
2.33
2024, 2025
Switzerland CHE
2.01
2.72
2024, 2025
Singapore SGP
1.97
1.89
2024, 2025
Sweden SWE
1.97
2.77
2024, 2025
Norway NOR
1.96
2.19
2024, 2025
New Zealand NZL
1.93
2.77
2024, 2025
Netherlands NLD
1.91
2.86
2024, 2025
Australia AUS
1.85
2.62
2024, 2025
Iceland ISL
1.83
2.43
2024, 2025
Germany DEU
1.77
2.66
2024, 2025
Estonia EST
1.67
2.71
2024, 2025
Canada CAN
1.63
2.51
2024, 2025
Ireland IRL
1.57
3.01
2024, 2025
Kaufmann, D. and A. Kraay, Worldwide Governance Indicators, World Bank Coppedge, M. et al., V-Dem Dataset v16, Varieties of Democracy (V-Dem) Project; Lindberg, S. I. et al., Varieties of Party Identity and Organization (V-Party) Dataset. Read from the V-Dem Institute's vdemdata package.
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.
Opposition parties' independence from the ruling regime
V-Dem Institute, University of Gothenburg · CC BY-SA 4.0 · updated annual (V-Dem); V-Party per election, to 2019
Are opposition parties really independent, or picked or bought by the people in power? Experts answer from 0 ("opposition parties are not allowed") to 4 ("all opposition parties are independent"). V-Dem turns the answers into a score of about -4 to +4. A part of V-Dem's freedom of association index.
How this was computed
Data used: most recent value in 2010-2025; values come from 2019–2025. 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 17,292 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated V-Dem v16; V-Party v2. How the country data works · explore Control of corruption and Independent opposition
This page shows that two measures go together. It does not show that Control of corruption changes Independent opposition, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Control of corruption or Independent opposition