placestats

Environment score vs. Women's political empowerment

Holds up after adjusting for income

Across 167 countries, Environment score and Women's political empowerment rise and fall together at r = +0.18 (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 = +0.43, q = 0.012, allowing for the many pairs tested).

Comparing countries across the middle half of women's political empowerment, 0.625 to 0.873 points, environment score is better by 0.132 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.328 typical gaps.

Link before adjusting (r)+0.178p = 0.021 · 167 countries
After adjusting for national income+0.430p = 7.6e-9 · likely range [+0.30, +0.55]
p, allowing for regions0.024standard error 0.144 · 7 regions
Check for luck (q)0.012across 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.

Environment score · typical gaps (standard deviations)link with income -0.33 · moderate
Women's political empowerment · index (0-1)link with income +0.54 · moderate

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

Every country as a dot

Environment score · typical gaps (standard deviations) →Women's political empowerment · index (0-1) →-1.131.560.0280.954Afghanistan: -0.155 typical gaps (standard deviations), 0.028 index (0-1)Angola: -0.111 typical gaps (standard deviations), 0.77 index (0-1)Albania: 0.171 typical gaps (standard deviations), 0.893 index (0-1)United Arab Emirates: -0.57 typical gaps (standard deviations), 0.614 index (0-1)Argentina: -0.603 typical gaps (standard deviations), 0.832 index (0-1)Armenia: 0.686 typical gaps (standard deviations), 0.875 index (0-1)Australia: -0.398 typical gaps (standard deviations), 0.906 index (0-1)Austria: 0.0941 typical gaps (standard deviations), 0.905 index (0-1)Azerbaijan: -0.0733 typical gaps (standard deviations), 0.649 index (0-1)Burundi: 0.347 typical gaps (standard deviations), 0.653 index (0-1)Belgium: -0.459 typical gaps (standard deviations), 0.952 index (0-1)Benin: 0.727 typical gaps (standard deviations), 0.882 index (0-1)Burkina Faso: 0.354 typical gaps (standard deviations), 0.602 index (0-1)Bangladesh: -0.359 typical gaps (standard deviations), 0.537 index (0-1)Bulgaria: 0.709 typical gaps (standard deviations), 0.907 index (0-1)Bahrain: -0.928 typical gaps (standard deviations), 0.568 index (0-1)Bosnia and Herzegovina: -0.692 typical gaps (standard deviations), 0.821 index (0-1)Belarus: -0.676 typical gaps (standard deviations), 0.657 index (0-1)Bolivia: 0.394 typical gaps (standard deviations), 0.84 index (0-1)Brazil: 0.379 typical gaps (standard deviations), 0.818 index (0-1)Barbados: -0.789 typical gaps (standard deviations), 0.895 index (0-1)Bhutan: 1.23 typical gaps (standard deviations), 0.675 index (0-1)Botswana: 0.28 typical gaps (standard deviations), 0.699 index (0-1)Central African Republic: 0.648 typical gaps (standard deviations), 0.556 index (0-1)Canada: -0.75 typical gaps (standard deviations), 0.872 index (0-1)Switzerland: -0.442 typical gaps (standard deviations), 0.93 index (0-1)Chile: -0.101 typical gaps (standard deviations), 0.913 index (0-1)China: -0.545 typical gaps (standard deviations), 0.587 index (0-1)Cote d'Ivoire: 0.412 typical gaps (standard deviations), 0.696 index (0-1)Cameroon: 0.0784 typical gaps (standard deviations), 0.76 index (0-1)Congo, Dem. Rep.: 0.678 typical gaps (standard deviations), 0.55 index (0-1)Congo, Rep.: 0.756 typical gaps (standard deviations), 0.466 index (0-1)Colombia: -0.0873 typical gaps (standard deviations), 0.777 index (0-1)Comoros: 0.869 typical gaps (standard deviations), 0.556 index (0-1)Cabo Verde: 0.0177 typical gaps (standard deviations), 0.855 index (0-1)Costa Rica: 0.306 typical gaps (standard deviations), 0.907 index (0-1)Cyprus: 0.483 typical gaps (standard deviations), 0.856 index (0-1)Czechia: -0.235 typical gaps (standard deviations), 0.93 index (0-1)Germany: 0.448 typical gaps (standard deviations), 0.942 index (0-1)Djibouti: -0.477 typical gaps (standard deviations), 0.584 index (0-1)Denmark: -0.347 typical gaps (standard deviations), 0.954 index (0-1)Dominican Republic: 0.145 typical gaps (standard deviations), 0.825 index (0-1)Algeria: -0.761 typical gaps (standard deviations), 0.625 index (0-1)Ecuador: 0.0746 typical gaps (standard deviations), 0.79 index (0-1)Egypt, Arab Rep.: -0.316 typical gaps (standard deviations), 0.547 index (0-1)Spain: 0.119 typical gaps (standard deviations), 0.943 index (0-1)Estonia: -0.252 typical gaps (standard deviations), 0.941 index (0-1)Ethiopia: 0.527 typical gaps (standard deviations), 0.691 index (0-1)Finland: -0.495 typical gaps (standard deviations), 0.932 index (0-1)Fiji: -0.572 typical gaps (standard deviations), 0.644 index (0-1)France: 0.167 typical gaps (standard deviations), 0.929 index (0-1)Gabon: 0.102 typical gaps (standard deviations), 0.798 index (0-1)United Kingdom: 0.147 typical gaps (standard deviations), 0.838 index (0-1)Georgia: -0.0275 typical gaps (standard deviations), 0.816 index (0-1)Ghana: 0.0578 typical gaps (standard deviations), 0.767 index (0-1)Guinea: 1.11 typical gaps (standard deviations), 0.532 index (0-1)Gambia, The: 0.114 typical gaps (standard deviations), 0.813 index (0-1)Guinea-Bissau: 0.871 typical gaps (standard deviations), 0.502 index (0-1)Equatorial Guinea: -0.0954 typical gaps (standard deviations), 0.449 index (0-1)Greece: 0.359 typical gaps (standard deviations), 0.896 index (0-1)Guatemala: 0.152 typical gaps (standard deviations), 0.722 index (0-1)Guyana: -0.65 typical gaps (standard deviations), 0.81 index (0-1)Hong Kong SAR, China: 0.654 typical gaps (standard deviations), 0.801 index (0-1)Honduras: 0.274 typical gaps (standard deviations), 0.789 index (0-1)Croatia: 0.502 typical gaps (standard deviations), 0.913 index (0-1)Haiti: 0.0265 typical gaps (standard deviations), 0.403 index (0-1)Hungary: -0.0923 typical gaps (standard deviations), 0.818 index (0-1)Indonesia: -0.396 typical gaps (standard deviations), 0.726 index (0-1)India: -0.496 typical gaps (standard deviations), 0.658 index (0-1)Ireland: -0.486 typical gaps (standard deviations), 0.927 index (0-1)Iran, Islamic Rep.: -0.811 typical gaps (standard deviations), 0.32 index (0-1)Iraq: -0.95 typical gaps (standard deviations), 0.555 index (0-1)Iceland: -0.317 typical gaps (standard deviations), 0.883 index (0-1)Israel: 0.039 typical gaps (standard deviations), 0.862 index (0-1)Italy: -0.163 typical gaps (standard deviations), 0.929 index (0-1)Jamaica: -0.0871 typical gaps (standard deviations), 0.929 index (0-1)Jordan: -0.575 typical gaps (standard deviations), 0.669 index (0-1)Japan: 0.0374 typical gaps (standard deviations), 0.844 index (0-1)Kazakhstan: -0.833 typical gaps (standard deviations), 0.682 index (0-1)Kenya: 0.175 typical gaps (standard deviations), 0.804 index (0-1)Kyrgyz Republic: -0.438 typical gaps (standard deviations), 0.733 index (0-1)Cambodia: 0.919 typical gaps (standard deviations), 0.534 index (0-1)Korea, Rep.: -0.524 typical gaps (standard deviations), 0.878 index (0-1)Kuwait: -0.716 typical gaps (standard deviations), 0.357 index (0-1)Lao PDR: -0.17 typical gaps (standard deviations), 0.508 index (0-1)Lebanon: -0.454 typical gaps (standard deviations), 0.608 index (0-1)Liberia: 0.00915 typical gaps (standard deviations), 0.823 index (0-1)Libya: -1.13 typical gaps (standard deviations), 0.412 index (0-1)Sri Lanka: 0.547 typical gaps (standard deviations), 0.742 index (0-1)Lesotho: 0.514 typical gaps (standard deviations), 0.809 index (0-1)Lithuania: -0.281 typical gaps (standard deviations), 0.926 index (0-1)Luxembourg: 0.322 typical gaps (standard deviations), 0.896 index (0-1)Latvia: -0.203 typical gaps (standard deviations), 0.95 index (0-1)Morocco: -0.672 typical gaps (standard deviations), 0.712 index (0-1)Moldova: -0.459 typical gaps (standard deviations), 0.898 index (0-1)Madagascar: 0.36 typical gaps (standard deviations), 0.704 index (0-1)Maldives: -0.8 typical gaps (standard deviations), 0.532 index (0-1)Mexico: -0.326 typical gaps (standard deviations), 0.801 index (0-1)North Macedonia: 0.152 typical gaps (standard deviations), 0.824 index (0-1)Mali: -0.0198 typical gaps (standard deviations), 0.706 index (0-1)Malta: 0.236 typical gaps (standard deviations), 0.917 index (0-1)Myanmar: -0.212 typical gaps (standard deviations), 0.33 index (0-1)Montenegro: 0.445 typical gaps (standard deviations), 0.866 index (0-1)Mongolia: -0.34 typical gaps (standard deviations), 0.806 index (0-1)Mozambique: 0.845 typical gaps (standard deviations), 0.725 index (0-1)Mauritania: -0.574 typical gaps (standard deviations), 0.541 index (0-1)Mauritius: -0.72 typical gaps (standard deviations), 0.814 index (0-1)Malawi: 0.664 typical gaps (standard deviations), 0.755 index (0-1)Malaysia: -0.607 typical gaps (standard deviations), 0.772 index (0-1)Namibia: 0.901 typical gaps (standard deviations), 0.855 index (0-1)Niger: 0.626 typical gaps (standard deviations), 0.709 index (0-1)Nigeria: 0.0752 typical gaps (standard deviations), 0.732 index (0-1)Nicaragua: 0.266 typical gaps (standard deviations), 0.531 index (0-1)Netherlands: -0.177 typical gaps (standard deviations), 0.903 index (0-1)Norway: -0.396 typical gaps (standard deviations), 0.926 index (0-1)Nepal: 0.466 typical gaps (standard deviations), 0.792 index (0-1)New Zealand: 0.254 typical gaps (standard deviations), 0.937 index (0-1)Oman: -0.467 typical gaps (standard deviations), 0.357 index (0-1)Pakistan: 0.193 typical gaps (standard deviations), 0.524 index (0-1)Panama: 0.369 typical gaps (standard deviations), 0.742 index (0-1)Peru: 0.0974 typical gaps (standard deviations), 0.775 index (0-1)Philippines: -0.0823 typical gaps (standard deviations), 0.81 index (0-1)Papua New Guinea: -0.299 typical gaps (standard deviations), 0.48 index (0-1)Poland: 0.439 typical gaps (standard deviations), 0.878 index (0-1)Portugal: -0.0126 typical gaps (standard deviations), 0.811 index (0-1)Paraguay: -0.0611 typical gaps (standard deviations), 0.669 index (0-1)Qatar: -0.944 typical gaps (standard deviations), 0.388 index (0-1)Romania: 0.0298 typical gaps (standard deviations), 0.872 index (0-1)Russian Federation: -0.804 typical gaps (standard deviations), 0.546 index (0-1)Rwanda: 0.196 typical gaps (standard deviations), 0.626 index (0-1)Saudi Arabia: -0.601 typical gaps (standard deviations), 0.347 index (0-1)Sudan: -0.31 typical gaps (standard deviations), 0.219 index (0-1)Senegal: 0.483 typical gaps (standard deviations), 0.855 index (0-1)Singapore: -0.984 typical gaps (standard deviations), 0.785 index (0-1)Solomon Islands: -0.276 typical gaps (standard deviations), 0.675 index (0-1)Sierra Leone: 0.321 typical gaps (standard deviations), 0.801 index (0-1)El Salvador: -0.382 typical gaps (standard deviations), 0.587 index (0-1)Somalia, Fed. Rep.: 0.153 typical gaps (standard deviations), 0.337 index (0-1)Serbia: -0.367 typical gaps (standard deviations), 0.864 index (0-1)Sao Tome and Principe: 0.743 typical gaps (standard deviations), 0.843 index (0-1)Suriname: -0.373 typical gaps (standard deviations), 0.877 index (0-1)Slovak Republic: 0.435 typical gaps (standard deviations), 0.878 index (0-1)Slovenia: 0.52 typical gaps (standard deviations), 0.94 index (0-1)Sweden: -0.314 typical gaps (standard deviations), 0.923 index (0-1)Eswatini: -0.41 typical gaps (standard deviations), 0.391 index (0-1)Seychelles: 1.56 typical gaps (standard deviations), 0.908 index (0-1)Syrian Arab Republic: -0.637 typical gaps (standard deviations), 0.29 index (0-1)Chad: 0.69 typical gaps (standard deviations), 0.625 index (0-1)Togo: 0.773 typical gaps (standard deviations), 0.692 index (0-1)Thailand: -0.227 typical gaps (standard deviations), 0.688 index (0-1)Tajikistan: 0.294 typical gaps (standard deviations), 0.431 index (0-1)Turkmenistan: -1.02 typical gaps (standard deviations), 0.437 index (0-1)Timor-Leste: 0.192 typical gaps (standard deviations), 0.768 index (0-1)Trinidad and Tobago: -0.144 typical gaps (standard deviations), 0.874 index (0-1)Tunisia: -0.534 typical gaps (standard deviations), 0.765 index (0-1)Turkiye: -0.745 typical gaps (standard deviations), 0.558 index (0-1)Tanzania: 1.24 typical gaps (standard deviations), 0.834 index (0-1)Uganda: 0.463 typical gaps (standard deviations), 0.636 index (0-1)Ukraine: -0.231 typical gaps (standard deviations), 0.888 index (0-1)Uruguay: -0.715 typical gaps (standard deviations), 0.875 index (0-1)United States: -0.744 typical gaps (standard deviations), 0.829 index (0-1)Uzbekistan: -0.58 typical gaps (standard deviations), 0.643 index (0-1)Viet Nam: -0.665 typical gaps (standard deviations), 0.808 index (0-1)Vanuatu: -0.407 typical gaps (standard deviations), 0.715 index (0-1)South Africa: -0.708 typical gaps (standard deviations), 0.83 index (0-1)Zambia: 1.15 typical gaps (standard deviations), 0.791 index (0-1)Zimbabwe: 0.559 typical gaps (standard deviations), 0.727 index (0-1)AFGBRBCANGINGNBIRNLBYSYCTZAURYZMB

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.1780.021167
By rank (Spearman), not adjusted+0.1420.067167
Standard (Pearson), adjusted for national income+0.4307.6e-9167
By rank (Spearman), adjusted for national income+0.4442.1e-9167

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: -0.252 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.414 (without LBY) to +0.445 (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: BTN (+0.015).

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 & Pacific21+0.04
Europe & Central Asia48+0.45
Latin America & Caribbean23+0.05
Middle East, North Africa, Afghanistan & Pakistan21+0.37
Sub-Saharan Africa46+0.27

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 third56+0.36
Middle third55+0.44
Richest third56+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.

nr
Christians99+0.28
Muslims47+0.31

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+0.20
Never a European colony21+0.50
Spain19+0.09
United Kingdom49+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 = +0.416 after dropping 2 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)

index (0-1)
Years
Seychelles SYC1.560.9082024, 2025
Tanzania TZA1.240.8342024, 2025
Bhutan BTN1.230.6752024, 2025
Zambia ZMB1.150.7912024, 2025
Guinea GIN1.110.5322024, 2025
Cambodia KHM0.9190.5342024, 2025
Namibia NAM0.9010.8552024, 2025
Guinea-Bissau GNB0.8710.5022024, 2025
Comoros COM0.8690.5562024, 2025
Mozambique MOZ0.8450.7252024, 2025
Togo TGO0.7730.6922024, 2025
Congo, Rep. COG0.7560.4662024, 2025
Sao Tome and Principe STP0.7430.8432024, 2025
Benin BEN0.7270.8822024, 2025
Bulgaria BGR0.7090.9072024, 2025

wdi
Coppedge, M. et al., V-Dem Dataset, Varieties of Democracy (V-Dem) Project

Sources

Environment score

Environment score

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

The average of 3 measures from 1 publisher. 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: Forest area, CO2 per capita, Protected land.

Women's political empowerment

Women's political empowerment index

V-Dem Institute, University of Gothenburg · via Our World in Data · CC BY 4.0 · updated annual

Women's civil liberties, their part in civic groups, and their political representation. It is built from its own set of questions, not from the parts of the democracy indices, so it is not tagged as measuring the same thing. Still, read its links with them carefully. Whether women take part in politics is partly built into whether real political participation exists at all. So a strong link with general democracy measures is closer to definitional (true by how the terms are defined) than to a finding about the world.

How this was computed

Data used: most recent value in 2010-2025; values come from 2023–2025. 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 Environment score and Women's political empowerment

This page shows that two measures go together. It does not show that Environment score changes Women's political empowerment, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Environment score or Women's political empowerment