placestats

Muslim share vs. Women's political empowerment

Fades after adjusting for income

A country is not a person. Countries where more people are counted as belonging to this group also tend to differ on the other measure, and that is all. It does not follow that the people in the group are the people with the different score. Making that leap is called the ecological fallacy: reading a pattern across places as a fact about individual people. It is the most common misuse of this kind of data. Religion also varies strongly with region, history and national income, so much of what looks religious here is really those. That is what the adjusted figures are for. The religion shares are estimates for two years only, and the survey questions are asked in rounds that can be ten years apart.

Across 168 countries, Muslim share and Women's political empowerment rise and fall together at r = -0.55 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) leaves r = -0.51, which could easily be chance (q = 0.12, allowing for the many pairs tested, and allowing for countries in the same region being alike). Caution: direction is not consistent across regions.

Comparing countries across the middle half of muslim share, 0.338% to 64.9% of population, women's political empowerment is worse by 0.164 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.14 points.

Link before adjusting (r)-0.547p = 1.8e-14 · 168 countries
After adjusting for national income-0.506p = 3.1e-12 · likely range [-0.61, -0.38]
p, allowing for regions0.025standard error 0.170 · 7 regions
Check for luck (q)0.121across 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.

Muslim share · % of populationlink with income -0.14 · independent
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

Muslim share · % of population →Women's political empowerment · index (0-1) →0.00186%99.9%0.0280.954Afghanistan: 99.9% of population, 0.028 index (0-1)Angola: 0.256% of population, 0.77 index (0-1)Albania: 74.5% of population, 0.893 index (0-1)United Arab Emirates: 72.9% of population, 0.614 index (0-1)Argentina: 0.929% of population, 0.832 index (0-1)Armenia: 0.267% of population, 0.875 index (0-1)Australia: 3.5% of population, 0.906 index (0-1)Austria: 8.3% of population, 0.905 index (0-1)Azerbaijan: 94.7% of population, 0.649 index (0-1)Burundi: 2.99% of population, 0.653 index (0-1)Belgium: 6.81% of population, 0.952 index (0-1)Benin: 31.4% of population, 0.882 index (0-1)Burkina Faso: 67.4% of population, 0.602 index (0-1)Bangladesh: 91.1% of population, 0.537 index (0-1)Bulgaria: 10.3% of population, 0.907 index (0-1)Bahrain: 74% of population, 0.568 index (0-1)Bosnia and Herzegovina: 53.6% of population, 0.821 index (0-1)Belarus: 0.262% of population, 0.657 index (0-1)Bolivia: 0.0098% of population, 0.84 index (0-1)Brazil: 0.0177% of population, 0.818 index (0-1)Barbados: 0.707% of population, 0.895 index (0-1)Bhutan: 0.222% of population, 0.675 index (0-1)Botswana: 0.33% of population, 0.699 index (0-1)Central African Republic: 6.24% of population, 0.556 index (0-1)Canada: 4.89% of population, 0.872 index (0-1)Switzerland: 6.08% of population, 0.93 index (0-1)Chile: 0.067% of population, 0.913 index (0-1)China: 1.82% of population, 0.587 index (0-1)Cote d'Ivoire: 46.3% of population, 0.696 index (0-1)Cameroon: 25.2% of population, 0.76 index (0-1)Congo, Dem. Rep.: 1.27% of population, 0.55 index (0-1)Congo, Rep.: 1.46% of population, 0.466 index (0-1)Colombia: 0.00393% of population, 0.777 index (0-1)Comoros: 98.3% of population, 0.556 index (0-1)Cabo Verde: 0.313% of population, 0.855 index (0-1)Costa Rica: 0.0252% of population, 0.907 index (0-1)Cyprus: 24.4% of population, 0.856 index (0-1)Czechia: 0.327% of population, 0.93 index (0-1)Germany: 6.55% of population, 0.942 index (0-1)Djibouti: 97.7% of population, 0.584 index (0-1)Denmark: 4.22% of population, 0.954 index (0-1)Dominican Republic: 0.0248% of population, 0.825 index (0-1)Algeria: 98.4% of population, 0.625 index (0-1)Ecuador: 0.0181% of population, 0.79 index (0-1)Egypt, Arab Rep.: 95.2% of population, 0.547 index (0-1)Spain: 3.58% of population, 0.943 index (0-1)Estonia: 0.598% of population, 0.941 index (0-1)Ethiopia: 36.2% of population, 0.691 index (0-1)Finland: 1.61% of population, 0.932 index (0-1)Fiji: 5.78% of population, 0.644 index (0-1)France: 9.1% of population, 0.929 index (0-1)Gabon: 8.64% of population, 0.798 index (0-1)United Kingdom: 6.37% of population, 0.838 index (0-1)Georgia: 10.5% of population, 0.816 index (0-1)Ghana: 19.9% of population, 0.767 index (0-1)Guinea: 86.8% of population, 0.532 index (0-1)Gambia, The: 97% of population, 0.813 index (0-1)Guinea-Bissau: 56% of population, 0.502 index (0-1)Equatorial Guinea: 4.05% of population, 0.449 index (0-1)Greece: 5.12% of population, 0.896 index (0-1)Guatemala: 0.00271% of population, 0.722 index (0-1)Guyana: 6.5% of population, 0.81 index (0-1)Hong Kong SAR, China: 0.268% of population, 0.801 index (0-1)Honduras: 0.00277% of population, 0.789 index (0-1)Croatia: 1.37% of population, 0.913 index (0-1)Haiti: 0.00186% of population, 0.403 index (0-1)Hungary: 0.139% of population, 0.818 index (0-1)Indonesia: 87% of population, 0.726 index (0-1)India: 15.2% of population, 0.658 index (0-1)Ireland: 1.69% of population, 0.927 index (0-1)Iran, Islamic Rep.: 99.8% of population, 0.32 index (0-1)Iraq: 99.5% of population, 0.555 index (0-1)Iceland: 1.21% of population, 0.883 index (0-1)Israel: 14.7% of population, 0.862 index (0-1)Italy: 4.42% of population, 0.929 index (0-1)Jamaica: 0.016% of population, 0.929 index (0-1)Jordan: 97.1% of population, 0.669 index (0-1)Japan: 0.17% of population, 0.844 index (0-1)Kazakhstan: 77.9% of population, 0.682 index (0-1)Kenya: 10.9% of population, 0.804 index (0-1)Kyrgyz Republic: 91.7% of population, 0.733 index (0-1)Cambodia: 2.04% of population, 0.534 index (0-1)Korea, Rep.: 0.31% of population, 0.878 index (0-1)Kuwait: 80.2% of population, 0.357 index (0-1)Lao PDR: 0.0222% of population, 0.508 index (0-1)Lebanon: 67.8% of population, 0.608 index (0-1)Liberia: 12.7% of population, 0.823 index (0-1)Libya: 99% of population, 0.412 index (0-1)Sri Lanka: 10.2% of population, 0.742 index (0-1)Lesotho: 0.218% of population, 0.809 index (0-1)Lithuania: 0.0892% of population, 0.926 index (0-1)Luxembourg: 1.83% of population, 0.896 index (0-1)Latvia: 0.67% of population, 0.95 index (0-1)Morocco: 99.7% of population, 0.712 index (0-1)Moldova: 0.181% of population, 0.898 index (0-1)Madagascar: 1.16% of population, 0.704 index (0-1)Maldives: 94.1% of population, 0.532 index (0-1)Mexico: 0.00629% of population, 0.801 index (0-1)North Macedonia: 34.7% of population, 0.824 index (0-1)Mali: 94.1% of population, 0.706 index (0-1)Malta: 3.64% of population, 0.917 index (0-1)Myanmar: 3.35% of population, 0.33 index (0-1)Montenegro: 21.3% of population, 0.866 index (0-1)Mongolia: 3.53% of population, 0.806 index (0-1)Mozambique: 19.4% of population, 0.725 index (0-1)Mauritania: 99.2% of population, 0.541 index (0-1)Mauritius: 17.5% of population, 0.814 index (0-1)Malawi: 11.6% of population, 0.755 index (0-1)Malaysia: 64.1% of population, 0.772 index (0-1)Namibia: 0.119% of population, 0.855 index (0-1)Niger: 98.1% of population, 0.709 index (0-1)Nigeria: 56.1% of population, 0.732 index (0-1)Nicaragua: 0.00459% of population, 0.531 index (0-1)Netherlands: 5.5% of population, 0.903 index (0-1)Norway: 4.11% of population, 0.926 index (0-1)Nepal: 5.08% of population, 0.792 index (0-1)New Zealand: 1.36% of population, 0.937 index (0-1)Oman: 81.8% of population, 0.357 index (0-1)Pakistan: 96.5% of population, 0.524 index (0-1)Panama: 0.0531% of population, 0.742 index (0-1)Peru: 0.0216% of population, 0.775 index (0-1)Philippines: 6.46% of population, 0.81 index (0-1)Papua New Guinea: 0.0748% of population, 0.48 index (0-1)Poland: 0.00732% of population, 0.878 index (0-1)Portugal: 0.409% of population, 0.811 index (0-1)Paraguay: 0.0113% of population, 0.669 index (0-1)Qatar: 75.9% of population, 0.388 index (0-1)Romania: 0.356% of population, 0.872 index (0-1)Russian Federation: 8.19% of population, 0.546 index (0-1)Rwanda: 1.81% of population, 0.626 index (0-1)Saudi Arabia: 92.7% of population, 0.347 index (0-1)Sudan: 98.9% of population, 0.219 index (0-1)Senegal: 97.6% of population, 0.855 index (0-1)Singapore: 16.1% of population, 0.785 index (0-1)Solomon Islands: 0.34% of population, 0.675 index (0-1)Sierra Leone: 80.1% of population, 0.801 index (0-1)El Salvador: 0.0035% of population, 0.587 index (0-1)Somalia, Fed. Rep.: 99.8% of population, 0.337 index (0-1)Serbia: 4.42% of population, 0.864 index (0-1)Sao Tome and Principe: 0.0915% of population, 0.843 index (0-1)Suriname: 13.1% of population, 0.877 index (0-1)Slovak Republic: 0.0548% of population, 0.878 index (0-1)Slovenia: 1.61% of population, 0.94 index (0-1)Sweden: 8.1% of population, 0.923 index (0-1)Eswatini: 0.136% of population, 0.391 index (0-1)Seychelles: 0.893% of population, 0.908 index (0-1)Syrian Arab Republic: 94.2% of population, 0.29 index (0-1)Chad: 56.4% of population, 0.625 index (0-1)Togo: 16.1% of population, 0.692 index (0-1)Thailand: 4.51% of population, 0.688 index (0-1)Tajikistan: 98.9% of population, 0.431 index (0-1)Turkmenistan: 94.3% of population, 0.437 index (0-1)Timor-Leste: 0.257% of population, 0.768 index (0-1)Trinidad and Tobago: 5.46% of population, 0.874 index (0-1)Tunisia: 99.3% of population, 0.765 index (0-1)Turkiye: 97.1% of population, 0.558 index (0-1)Tanzania: 29.9% of population, 0.834 index (0-1)Uganda: 11.4% of population, 0.636 index (0-1)Ukraine: 0.568% of population, 0.888 index (0-1)Uruguay: 0.0893% of population, 0.875 index (0-1)United States: 1.19% of population, 0.829 index (0-1)Uzbekistan: 95.6% of population, 0.643 index (0-1)Viet Nam: 0.0721% of population, 0.808 index (0-1)Vanuatu: 0.0193% of population, 0.715 index (0-1)Kosovo: 94.3% of population, 0.771 index (0-1)South Africa: 1.6% of population, 0.83 index (0-1)Zambia: 0.511% of population, 0.791 index (0-1)Zimbabwe: 0.529% of population, 0.727 index (0-1)AFGALBDNKESTGMBHTILVAMMRSDNSENSWZSYR

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5471.8e-14168
By rank (Spearman), not adjusted-0.3813.4e-7168
Standard (Pearson), adjusted for national income-0.5063.1e-12168
By rank (Spearman), adjusted for national income-0.3503.4e-6168

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 168 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: +0.041 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.525 (without SEN) to -0.489 (without SAU). 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: SEN (-0.019).

Fragile: this link may not hold up.
  • direction is not consistent across regions

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 & Pacific21-0.01
Europe & Central Asia49-0.57
Latin America & Caribbean23+0.05
Middle East, North Africa, Afghanistan & Pakistan21-0.48
Sub-Saharan Africa46-0.24

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 third56-0.31
Middle third56-0.48
Richest third56-0.86

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+0.19
Muslims48-0.28

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
France25-0.02
Never a European colony21-0.73
Spain19+0.05
United Kingdom49-0.56

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 = -0.486 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


% of population
index (0-1)		Years
Afghanistan AFG99.9%0.0282020, 2025
Somalia, Fed. Rep. SOM99.8%0.3372020, 2025
Iran, Islamic Rep. IRN99.8%0.322020, 2025
Morocco MAR99.7%0.7122020, 2025
Iraq IRQ99.5%0.5552020, 2025
Tunisia TUN99.3%0.7652020, 2025
Mauritania MRT99.2%0.5412020, 2025
Libya LBY99%0.4122020, 2025
Tajikistan TJK98.9%0.4312020, 2025
Sudan SDN98.9%0.2192020, 2025
Algeria DZA98.4%0.6252020, 2025
Comoros COM98.3%0.5562020, 2025
Niger NER98.1%0.7092020, 2025
Djibouti DJI97.7%0.5842020, 2025
Senegal SEN97.6%0.8552020, 2025

Pew Research Center, Religious Composition by Country, 2010-2020. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here.
Coppedge, M. et al., V-Dem Dataset, Varieties of Democracy (V-Dem) Project
One of these measures is published under a licence that forbids changes. Values are shown exactly as published and must not be republished in a changed or rescaled form.

Sources

Muslim share

Share of the population identifying as Muslim

Pew Research Center · via Our World in Data · Pew Research Center terms of use, excerpts with attribution · updated decennial · comparable from 2010 only

The second largest religion. The three religion shares are parts of one total. So for any pair of them, more of one means less of the others. They are built from the same numbers, so they are bound to match, and the site flags this. Hindu, Buddhist, folk and other religions are not included, so that what is taken from Pew's dataset stays a small excerpt of it. No "better" direction is set.

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 2020–2025. 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 Muslim share and Women's political empowerment

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

More links with Muslim share or Women's political empowerment