placestats

Gender score vs. Governance score

Holds up after adjusting for income

Across 169 countries, Gender score and Governance score rise and fall together at r = +0.60 (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 = +0.53, q = 0.046, allowing for the many pairs tested).

Comparing countries across the middle half of gender score, -0.0146 to 1.04 typical gaps, governance score is better by 0.772 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.624 typical gaps.

Link before adjusting (r)+0.601p = 6.2e-18 · 169 countries
After adjusting for national income+0.530p = 1.5e-13 · likely range [+0.41, +0.63]
p, allowing for regions0.004standard error 0.119 · 7 regions
Check for luck (q)0.046across 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
Governance score · typical gaps (standard deviations)link with income +0.53 · moderate

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

Gender score · typical gaps (standard deviations) →Governance score · typical gaps (standard deviations) →-1.212.19-1.41.47Afghanistan: -0.756 typical gaps (standard deviations), -1.4 typical gaps (standard deviations)Angola: 0.461 typical gaps (standard deviations), -0.522 typical gaps (standard deviations)Albania: 1.27 typical gaps (standard deviations), 0.323 typical gaps (standard deviations)United Arab Emirates: 0.89 typical gaps (standard deviations), -0.981 typical gaps (standard deviations)Argentina: 1.08 typical gaps (standard deviations), 0.815 typical gaps (standard deviations)Armenia: 1.26 typical gaps (standard deviations), 0.22 typical gaps (standard deviations)Australia: 1.57 typical gaps (standard deviations), 1.38 typical gaps (standard deviations)Austria: 1.17 typical gaps (standard deviations), 1.33 typical gaps (standard deviations)Azerbaijan: -0.374 typical gaps (standard deviations), -1.33 typical gaps (standard deviations)Burundi: 0.991 typical gaps (standard deviations), -1.09 typical gaps (standard deviations)Belgium: 1.45 typical gaps (standard deviations), 1.41 typical gaps (standard deviations)Benin: 0.759 typical gaps (standard deviations), 0.285 typical gaps (standard deviations)Burkina Faso: -0.093 typical gaps (standard deviations), -0.784 typical gaps (standard deviations)Bangladesh: -0.782 typical gaps (standard deviations), -0.359 typical gaps (standard deviations)Bulgaria: 0.273 typical gaps (standard deviations), 0.74 typical gaps (standard deviations)Bahrain: 0.0565 typical gaps (standard deviations), -1.05 typical gaps (standard deviations)Bosnia and Herzegovina: 0.116 typical gaps (standard deviations), 0.0899 typical gaps (standard deviations)Belarus: 0.153 typical gaps (standard deviations), -1.26 typical gaps (standard deviations)Belize: -0.821 typical gaps (standard deviations), 0.0883 typical gaps (standard deviations)Bolivia: 0.641 typical gaps (standard deviations), 0.552 typical gaps (standard deviations)Brazil: 0.685 typical gaps (standard deviations), 0.85 typical gaps (standard deviations)Barbados: 1.16 typical gaps (standard deviations), 1.24 typical gaps (standard deviations)Bhutan: -0.491 typical gaps (standard deviations), 0.61 typical gaps (standard deviations)Botswana: 0.25 typical gaps (standard deviations), 0.872 typical gaps (standard deviations)Central African Republic: -0.215 typical gaps (standard deviations), -1.02 typical gaps (standard deviations)Canada: 1.38 typical gaps (standard deviations), 1.36 typical gaps (standard deviations)Switzerland: 1.22 typical gaps (standard deviations), 1.47 typical gaps (standard deviations)Chile: 1.72 typical gaps (standard deviations), 1.32 typical gaps (standard deviations)China: -0.0629 typical gaps (standard deviations), -1.2 typical gaps (standard deviations)Cote d'Ivoire: 0.00107 typical gaps (standard deviations), -0.116 typical gaps (standard deviations)Cameroon: 0.739 typical gaps (standard deviations), -0.834 typical gaps (standard deviations)Congo, Dem. Rep.: -0.00209 typical gaps (standard deviations), -0.824 typical gaps (standard deviations)Congo, Rep.: -0.252 typical gaps (standard deviations), -0.925 typical gaps (standard deviations)Colombia: 0.908 typical gaps (standard deviations), 0.733 typical gaps (standard deviations)Comoros: -0.257 typical gaps (standard deviations), -0.464 typical gaps (standard deviations)Cabo Verde: 1.2 typical gaps (standard deviations), 1.15 typical gaps (standard deviations)Costa Rica: 1.7 typical gaps (standard deviations), 1.34 typical gaps (standard deviations)Cyprus: 0.593 typical gaps (standard deviations), 1.1 typical gaps (standard deviations)Czechia: 0.196 typical gaps (standard deviations), 1.31 typical gaps (standard deviations)Germany: 1.34 typical gaps (standard deviations), 1.36 typical gaps (standard deviations)Djibouti: 0.259 typical gaps (standard deviations), -0.784 typical gaps (standard deviations)Denmark: 1.1 typical gaps (standard deviations), 1.47 typical gaps (standard deviations)Dominican Republic: 1.32 typical gaps (standard deviations), 0.621 typical gaps (standard deviations)Algeria: -0.399 typical gaps (standard deviations), -0.695 typical gaps (standard deviations)Ecuador: 1.34 typical gaps (standard deviations), 0.447 typical gaps (standard deviations)Egypt, Arab Rep.: -0.204 typical gaps (standard deviations), -0.987 typical gaps (standard deviations)Spain: 1.69 typical gaps (standard deviations), 1.32 typical gaps (standard deviations)Estonia: 1.7 typical gaps (standard deviations), 1.41 typical gaps (standard deviations)Ethiopia: 1.4 typical gaps (standard deviations), -0.741 typical gaps (standard deviations)Finland: 2.04 typical gaps (standard deviations), 1.38 typical gaps (standard deviations)Fiji: -0.199 typical gaps (standard deviations), 0.57 typical gaps (standard deviations)France: 1.36 typical gaps (standard deviations), 1.24 typical gaps (standard deviations)Gabon: 0.419 typical gaps (standard deviations), -0.529 typical gaps (standard deviations)United Kingdom: 1.23 typical gaps (standard deviations), 1.27 typical gaps (standard deviations)Georgia: 0.641 typical gaps (standard deviations), 0.0179 typical gaps (standard deviations)Ghana: 0.134 typical gaps (standard deviations), 0.845 typical gaps (standard deviations)Guinea: 0.289 typical gaps (standard deviations), -0.676 typical gaps (standard deviations)Gambia, The: 0.216 typical gaps (standard deviations), 0.362 typical gaps (standard deviations)Guinea-Bissau: -0.221 typical gaps (standard deviations), -0.465 typical gaps (standard deviations)Equatorial Guinea: -0.151 typical gaps (standard deviations), -1.32 typical gaps (standard deviations)Greece: 0.861 typical gaps (standard deviations), 0.914 typical gaps (standard deviations)Guatemala: 0.823 typical gaps (standard deviations), 0.291 typical gaps (standard deviations)Guyana: 1.29 typical gaps (standard deviations), 0.538 typical gaps (standard deviations)Honduras: 1.04 typical gaps (standard deviations), 0.146 typical gaps (standard deviations)Croatia: 0.51 typical gaps (standard deviations), 0.865 typical gaps (standard deviations)Haiti: -0.419 typical gaps (standard deviations), -0.66 typical gaps (standard deviations)Hungary: -0.00646 typical gaps (standard deviations), 0.225 typical gaps (standard deviations)Indonesia: 0.0942 typical gaps (standard deviations), 0.125 typical gaps (standard deviations)India: -0.409 typical gaps (standard deviations), 0.146 typical gaps (standard deviations)Ireland: 0.727 typical gaps (standard deviations), 1.41 typical gaps (standard deviations)Iran, Islamic Rep.: -0.961 typical gaps (standard deviations), -1.26 typical gaps (standard deviations)Iraq: 0.119 typical gaps (standard deviations), -0.488 typical gaps (standard deviations)Iceland: 2.19 typical gaps (standard deviations), 1.32 typical gaps (standard deviations)Israel: 0.453 typical gaps (standard deviations), 0.783 typical gaps (standard deviations)Italy: 0.707 typical gaps (standard deviations), 1 typical gaps (standard deviations)Jamaica: 1.09 typical gaps (standard deviations), 1.01 typical gaps (standard deviations)Jordan: -0.0146 typical gaps (standard deviations), -0.271 typical gaps (standard deviations)Japan: -0.021 typical gaps (standard deviations), 1.28 typical gaps (standard deviations)Kazakhstan: 0.296 typical gaps (standard deviations), -0.796 typical gaps (standard deviations)Kenya: 0.693 typical gaps (standard deviations), 0.217 typical gaps (standard deviations)Kyrgyz Republic: 0.129 typical gaps (standard deviations), -0.725 typical gaps (standard deviations)Cambodia: -0.47 typical gaps (standard deviations), -1.01 typical gaps (standard deviations)Korea, Rep.: 0.412 typical gaps (standard deviations), 1.05 typical gaps (standard deviations)Kuwait: -1.02 typical gaps (standard deviations), -0.696 typical gaps (standard deviations)Lao PDR: -0.093 typical gaps (standard deviations), -1.14 typical gaps (standard deviations)Lebanon: -0.687 typical gaps (standard deviations), -0.112 typical gaps (standard deviations)Liberia: 0.525 typical gaps (standard deviations), 0.416 typical gaps (standard deviations)Libya: -0.0625 typical gaps (standard deviations), -0.885 typical gaps (standard deviations)St. Lucia: -0.14 typical gaps (standard deviations), 0.552 typical gaps (standard deviations)Sri Lanka: -0.262 typical gaps (standard deviations), 0.602 typical gaps (standard deviations)Lesotho: 0.261 typical gaps (standard deviations), 0.671 typical gaps (standard deviations)Lithuania: 0.944 typical gaps (standard deviations), 1.14 typical gaps (standard deviations)Luxembourg: 0.927 typical gaps (standard deviations), 1.38 typical gaps (standard deviations)Latvia: 1.32 typical gaps (standard deviations), 1.22 typical gaps (standard deviations)Morocco: 0.514 typical gaps (standard deviations), -0.351 typical gaps (standard deviations)Moldova: 1.45 typical gaps (standard deviations), 0.5 typical gaps (standard deviations)Madagascar: 0.668 typical gaps (standard deviations), -0.193 typical gaps (standard deviations)Maldives: -0.746 typical gaps (standard deviations), 0.0802 typical gaps (standard deviations)Mexico: 1.33 typical gaps (standard deviations), 0.134 typical gaps (standard deviations)North Macedonia: 1.08 typical gaps (standard deviations), 0.352 typical gaps (standard deviations)Mali: 0.147 typical gaps (standard deviations), -0.753 typical gaps (standard deviations)Malta: 0.55 typical gaps (standard deviations), 1.12 typical gaps (standard deviations)Myanmar: 0.308 typical gaps (standard deviations), -1.39 typical gaps (standard deviations)Montenegro: 0.895 typical gaps (standard deviations), 0.55 typical gaps (standard deviations)Mongolia: 0.547 typical gaps (standard deviations), 0.716 typical gaps (standard deviations)Mozambique: 0.926 typical gaps (standard deviations), -0.298 typical gaps (standard deviations)Mauritania: 0.103 typical gaps (standard deviations), -0.421 typical gaps (standard deviations)Mauritius: 0.0843 typical gaps (standard deviations), 1.07 typical gaps (standard deviations)Malawi: 0.728 typical gaps (standard deviations), 0.576 typical gaps (standard deviations)Malaysia: -0.0868 typical gaps (standard deviations), 0.169 typical gaps (standard deviations)Namibia: 1.41 typical gaps (standard deviations), 0.69 typical gaps (standard deviations)Niger: 0.397 typical gaps (standard deviations), -0.548 typical gaps (standard deviations)Nigeria: -0.213 typical gaps (standard deviations), -0.0132 typical gaps (standard deviations)Nicaragua: 1.98 typical gaps (standard deviations), -1.24 typical gaps (standard deviations)Netherlands: 1.19 typical gaps (standard deviations), 1.32 typical gaps (standard deviations)Norway: 1.53 typical gaps (standard deviations), 1.43 typical gaps (standard deviations)Nepal: 0.416 typical gaps (standard deviations), 0.441 typical gaps (standard deviations)New Zealand: 1.62 typical gaps (standard deviations), 1.32 typical gaps (standard deviations)Oman: -0.95 typical gaps (standard deviations), -0.665 typical gaps (standard deviations)Pakistan: -0.689 typical gaps (standard deviations), -0.437 typical gaps (standard deviations)Panama: 0.873 typical gaps (standard deviations), 0.84 typical gaps (standard deviations)Peru: 0.933 typical gaps (standard deviations), 0.522 typical gaps (standard deviations)Philippines: 0.494 typical gaps (standard deviations), 0.0585 typical gaps (standard deviations)Papua New Guinea: -1.01 typical gaps (standard deviations), 0.227 typical gaps (standard deviations)Poland: 1.13 typical gaps (standard deviations), 0.996 typical gaps (standard deviations)Portugal: 1.05 typical gaps (standard deviations), 1.26 typical gaps (standard deviations)Paraguay: 0.39 typical gaps (standard deviations), 0.349 typical gaps (standard deviations)Qatar: -0.892 typical gaps (standard deviations), -0.908 typical gaps (standard deviations)Romania: 0.285 typical gaps (standard deviations), 0.749 typical gaps (standard deviations)Russian Federation: 0.137 typical gaps (standard deviations), -1.14 typical gaps (standard deviations)Rwanda: 1.02 typical gaps (standard deviations), -0.868 typical gaps (standard deviations)Saudi Arabia: -0.552 typical gaps (standard deviations), -1.14 typical gaps (standard deviations)Sudan: -1.21 typical gaps (standard deviations), -1.22 typical gaps (standard deviations)Senegal: 0.477 typical gaps (standard deviations), 0.683 typical gaps (standard deviations)Singapore: 1.04 typical gaps (standard deviations), 0.0449 typical gaps (standard deviations)Solomon Islands: -0.473 typical gaps (standard deviations), 0.697 typical gaps (standard deviations)Sierra Leone: 0.991 typical gaps (standard deviations), 0.299 typical gaps (standard deviations)El Salvador: 0.618 typical gaps (standard deviations), -0.352 typical gaps (standard deviations)Somalia, Fed. Rep.: -0.615 typical gaps (standard deviations), -1.01 typical gaps (standard deviations)Serbia: 1.01 typical gaps (standard deviations), -0.0738 typical gaps (standard deviations)Sao Tome and Principe: 0.8 typical gaps (standard deviations), 0.8 typical gaps (standard deviations)Suriname: 1.04 typical gaps (standard deviations), 0.996 typical gaps (standard deviations)Slovak Republic: 0.374 typical gaps (standard deviations), 1.02 typical gaps (standard deviations)Slovenia: 1.26 typical gaps (standard deviations), 1.19 typical gaps (standard deviations)Sweden: 1.79 typical gaps (standard deviations), 1.42 typical gaps (standard deviations)Eswatini: -0.0447 typical gaps (standard deviations), -1.05 typical gaps (standard deviations)Seychelles: 1.17 typical gaps (standard deviations), 0.975 typical gaps (standard deviations)Syrian Arab Republic: -0.767 typical gaps (standard deviations), -1.05 typical gaps (standard deviations)Chad: 0.144 typical gaps (standard deviations), -0.999 typical gaps (standard deviations)Togo: 0.48 typical gaps (standard deviations), -0.371 typical gaps (standard deviations)Thailand: 0.332 typical gaps (standard deviations), -0.383 typical gaps (standard deviations)Tajikistan: -0.106 typical gaps (standard deviations), -1.34 typical gaps (standard deviations)Turkmenistan: -0.394 typical gaps (standard deviations), -1.39 typical gaps (standard deviations)Timor-Leste: 0.73 typical gaps (standard deviations), 0.779 typical gaps (standard deviations)Trinidad and Tobago: 1.21 typical gaps (standard deviations), 1.03 typical gaps (standard deviations)Tunisia: 0.319 typical gaps (standard deviations), -0.257 typical gaps (standard deviations)Turkiye: -0.502 typical gaps (standard deviations), -0.691 typical gaps (standard deviations)Tanzania: 0.828 typical gaps (standard deviations), -0.315 typical gaps (standard deviations)Uganda: 0.849 typical gaps (standard deviations), -0.646 typical gaps (standard deviations)Ukraine: 0.643 typical gaps (standard deviations), -0.0525 typical gaps (standard deviations)Uruguay: 0.63 typical gaps (standard deviations), 1.39 typical gaps (standard deviations)United States: 1.06 typical gaps (standard deviations), 0.998 typical gaps (standard deviations)Uzbekistan: 0.228 typical gaps (standard deviations), -1.04 typical gaps (standard deviations)Viet Nam: 0.0903 typical gaps (standard deviations), -0.933 typical gaps (standard deviations)Vanuatu: 0.107 typical gaps (standard deviations), 0.885 typical gaps (standard deviations)Kosovo: 0.375 typical gaps (standard deviations), 0.371 typical gaps (standard deviations)South Africa: 1.45 typical gaps (standard deviations), 0.883 typical gaps (standard deviations)Zambia: 0.211 typical gaps (standard deviations), 0.212 typical gaps (standard deviations)Zimbabwe: 0.576 typical gaps (standard deviations), -0.609 typical gaps (standard deviations)AFGBDIETHFINIRNISLJPNNICPNGSDNSLBSWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6016.2e-18169
By rank (Spearman), not adjusted+0.6192.8e-19169
Standard (Pearson), adjusted for national income+0.5301.5e-13169
By rank (Spearman), adjusted for national income+0.5385.6e-14169

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 169 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 +0.511 (without QAT) to +0.566 (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: NIC (+0.036).

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.

nr
East Asia & Pacific20+0.32
Europe & Central Asia49+0.66
Latin America & Caribbean25-0.02
Middle East, North Africa, Afghanistan & Pakistan21+0.45
Sub-Saharan Africa46+0.40

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.

nr
Poorest third57+0.17
Middle third56+0.58
Richest third56+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.

nr
Christians101+0.27
Muslims48+0.44

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.

nr
France25+0.43
Never a European colony21+0.56
Spain19+0.22
United Kingdom51+0.49

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 = +0.530 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)

typical gaps (standard deviations)
Years
Iceland ISL2.191.322024, 2025
Finland FIN2.041.382024, 2025
Nicaragua NIC1.98-1.242024, 2025
Sweden SWE1.791.422024, 2025
Chile CHL1.721.322024, 2025
Costa Rica CRI1.71.342025
Estonia EST1.71.412024, 2025
Spain ESP1.691.322024, 2025
New Zealand NZL1.621.322024, 2025
Australia AUS1.571.382024, 2025
Norway NOR1.531.432024, 2025
South Africa ZAF1.450.8832024, 2025
Moldova MDA1.450.52024, 2025
Belgium BEL1.451.412024, 2025
Namibia NAM1.410.692024, 2025

vdem; wb_gender; wdi
fh; un_sdg; vdem; wdi; wgi

Sources

Gender score

Gender score

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.

Governance score

Governance score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 19 measures from 5 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: Civil liberties (FH), Political rights (FH), Pre-trial detainee share, Civil society participation, Political corruption, Electoral democracy, Freedom of association, Freedom of expression, Free and fair elections, Liberal democracy, Participatory democracy, Political civil liberties, Birth registration, Control of corruption, Government effectiveness, Political stability, Rule of law, Regulatory quality, Voice and accountability.

How this was computed

Data used: most recent value in 2010-2025; values come from 2011–2025. 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 Governance score

This page shows that two measures go together. It does not show that Gender score changes Governance score, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Gender score or Governance score