Across 167 countries, Gender score and Regime type rise and fall together at r = +0.61 (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 = +0.54, q = 0.022, allowing for the many pairs tested).
Comparing countries across the middle half of regime type, 1 to 2 points, gender score is better by 0.451 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.433 typical gaps.
Link before adjusting (r)+0.610p = 2.0e-18 · 167 countries
After adjusting for national income+0.541p = 5.5e-14 · likely range [+0.42, +0.64]
p, allowing for regions0.002standard error 0.102 · 7 regions
Check for luck (q)0.022across 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.
Gender score · typical gaps (standard deviations)link with income +0.37 · moderate
Regime type · regime category (0-3)link with income +0.49 · 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
+0.610
2.0e-18
167
By rank (Spearman), not adjusted
+0.607
3.6e-18
167
Standard (Pearson), adjusted for national income
+0.541
5.5e-14
167
By rank (Spearman), adjusted for national income
+0.522
5.7e-13
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: +0.070 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.518 (without QAT) to +0.555 (without NIC). 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: QAT (-0.022).
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
20
+0.27
Europe & Central Asia
49
+0.55
Latin America & Caribbean
23
+0.19
Middle East, North Africa, Afghanistan & Pakistan
21
+0.31
Sub-Saharan Africa
46
+0.41
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
+0.33
Middle third
55
+0.47
Richest third
56
+0.71
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
+0.39
Muslims
48
+0.24
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
+0.18
Never a European colony
21
+0.52
Spain
19
+0.30
United Kingdom
49
+0.51
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 = +0.541 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 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
typical gaps (standard deviations)
regime category (0-3)
Years
Iceland ISL
2.19
3
2024, 2025
Finland FIN
2.04
3
2024, 2025
Nicaragua NIC
1.98
1
2024, 2025
Sweden SWE
1.79
3
2024, 2025
Chile CHL
1.72
3
2024, 2025
Costa Rica CRI
1.7
3
2025
Estonia EST
1.7
3
2024, 2025
Spain ESP
1.69
3
2024, 2025
New Zealand NZL
1.62
3
2024, 2025
Australia AUS
1.57
3
2024, 2025
Norway NOR
1.53
3
2024, 2025
South Africa ZAF
1.45
2
2024, 2025
Moldova MDA
1.45
2
2024, 2025
Belgium BEL
1.45
3
2024, 2025
Namibia NAM
1.41
2
2024, 2025
vdem; wb_gender; wdi Coppedge, M. et al., V-Dem Dataset, Varieties of Democracy (V-Dem) Project
PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel
The average of 5 measures from 3 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: Women's political empowerment, Women ministers, Women in parliament, Women in management, Married by 18.
V-Dem Institute, University of Gothenburg · via Our World in Data · CC BY 4.0 · updated annual
Four ranked categories, not a scale. It is the only such measure on this site. A closed autocracy holds no multiparty elections for its leader. An electoral autocracy holds them, but they are neither free nor fair. An electoral democracy clears that bar. A liberal democracy also has independent courts and protected personal freedoms. The four steps are not equal distances apart. So read the rank-based link, which uses only the order, rather than the ordinary one. Both are shown. The categories are set by cut-off points on the V-Dem indices already on this site. That is why its pairs with them are flagged as built from the same numbers. It is also why it is kept out of the governance score: a grouping of those indices averaged back in beside them would count each twice. Our World in Data extends the categories back to territories before independence. This site starts at 1960, and its single-year snapshot at 2010, so that extension reaches nothing shown here.
How this was computed
Data used: most recent value in 2010-2025; values come from 2018–2025. 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 Gender score and Regime type
This page shows that two measures go together. It does not show that Gender score changes Regime type, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.