placestats

Muslim share vs. Women in management

Holds up 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 145 countries, Muslim share and Women in management rise and fall together at r = -0.46 (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 = -0.41, q = 0.046, allowing for the many pairs tested). Caution: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of muslim share, 0.256% to 21.3% of population, women in management is worse by 3.06% of managers at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 2.72% of managers.

Link before adjusting (r)-0.458p = 6.9e-9 · 145 countries
After adjusting for national income-0.408p = 3.9e-7 · likely range [-0.54, -0.26]
p, allowing for regions0.004standard error 0.092 · 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.

Muslim share · % of populationlink with income -0.14 · independent
Women in management · % of managerslink with income +0.30 · 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 in management · % of managers →0.00196%99.9%5.89%71%Afghanistan: 99.9% of population, 5.89% of managersAngola: 0.256% of population, 16.2% of managersAlbania: 74.5% of population, 33.4% of managersUnited Arab Emirates: 72.9% of population, 23.5% of managersArgentina: 0.929% of population, 34.1% of managersArmenia: 0.267% of population, 31.9% of managersAustralia: 3.5% of population, 39.4% of managersAustria: 8.3% of population, 36.3% of managersBurundi: 2.99% of population, 25.7% of managersBelgium: 6.81% of population, 33.1% of managersBenin: 31.4% of population, 23.5% of managersBurkina Faso: 67.4% of population, 25.9% of managersBangladesh: 91.1% of population, 7.23% of managersBulgaria: 10.3% of population, 39.1% of managersBahamas, The: 0.0858% of population, 59.8% of managersBosnia and Herzegovina: 53.6% of population, 30.2% of managersBelarus: 0.262% of population, 42% of managersBelize: 0.18% of population, 41.7% of managersBolivia: 0.0098% of population, 22.3% of managersBrazil: 0.0177% of population, 38.7% of managersBarbados: 0.707% of population, 50.4% of managersBrunei Darussalam: 82.2% of population, 36.4% of managersBhutan: 0.222% of population, 15.5% of managersBotswana: 0.33% of population, 48.2% of managersSwitzerland: 6.08% of population, 33.3% of managersChile: 0.067% of population, 31.6% of managersCote d'Ivoire: 46.3% of population, 22.2% of managersCongo, Dem. Rep.: 1.27% of population, 29.6% of managersColombia: 0.00393% of population, 41.9% of managersCosta Rica: 0.0252% of population, 46.2% of managersCyprus: 24.4% of population, 27.5% of managersCzechia: 0.327% of population, 26.9% of managersGermany: 6.55% of population, 27.7% of managersDenmark: 4.22% of population, 26.9% of managersDominican Republic: 0.0248% of population, 47.8% of managersEcuador: 0.0181% of population, 45.3% of managersEgypt, Arab Rep.: 95.2% of population, 22.3% of managersSpain: 3.58% of population, 37% of managersEstonia: 0.598% of population, 36% of managersEthiopia: 36.2% of population, 27% of managersFinland: 1.61% of population, 39.2% of managersFiji: 5.78% of population, 34.9% of managersFrance: 9.1% of population, 38.7% of managersMicronesia, Fed. Sts.: 0.00196% of population, 18.2% of managersGabon: 8.64% of population, 19.2% of managersUnited Kingdom: 6.37% of population, 40.5% of managersGeorgia: 10.5% of population, 37.5% of managersGhana: 19.9% of population, 26.6% of managersGambia, The: 97% of population, 28.1% of managersGuinea-Bissau: 56% of population, 25.6% of managersGreece: 5.12% of population, 35% of managersGrenada: 0.395% of population, 43.3% of managersGuatemala: 0.00271% of population, 39.8% of managersGuyana: 6.5% of population, 42.1% of managersHonduras: 0.00277% of population, 46% of managersCroatia: 1.37% of population, 25.5% of managersHungary: 0.139% of population, 42.1% of managersIndonesia: 87% of population, 24.8% of managersIndia: 15.2% of population, 11.9% of managersIreland: 1.69% of population, 37.8% of managersIran, Islamic Rep.: 99.8% of population, 21.4% of managersIraq: 99.5% of population, 17.5% of managersIceland: 1.21% of population, 37.3% of managersIsrael: 14.7% of population, 32.8% of managersItaly: 4.42% of population, 25.3% of managersJamaica: 0.016% of population, 63.9% of managersJordan: 97.1% of population, 52.3% of managersJapan: 0.17% of population, 14.5% of managersKenya: 10.9% of population, 43.6% of managersKyrgyz Republic: 91.7% of population, 32.8% of managersCambodia: 2.04% of population, 23.6% of managersKiribati: 0.0854% of population, 37.4% of managersLao PDR: 0.0222% of population, 25.7% of managersLebanon: 67.8% of population, 28.9% of managersLiberia: 12.7% of population, 26.1% of managersSri Lanka: 10.2% of population, 29.2% of managersLesotho: 0.218% of population, 32.9% of managersLithuania: 0.0892% of population, 37.4% of managersLuxembourg: 1.83% of population, 26.9% of managersLatvia: 0.67% of population, 44% of managersMadagascar: 1.16% of population, 28.6% of managersMaldives: 94.1% of population, 22.6% of managersMexico: 0.00629% of population, 39.3% of managersNorth Macedonia: 34.7% of population, 36.4% of managersMali: 94.1% of population, 9.01% of managersMalta: 3.64% of population, 22.7% of managersMyanmar: 3.35% of population, 41% of managersMontenegro: 21.3% of population, 48.1% of managersMongolia: 3.53% of population, 40.5% of managersMozambique: 19.4% of population, 29.1% of managersMauritius: 17.5% of population, 35.6% of managersMalawi: 11.6% of population, 47.7% of managersNamibia: 0.119% of population, 48.2% of managersNiger: 98.1% of population, 21.6% of managersNigeria: 56.1% of population, 37.9% of managersNicaragua: 0.00459% of population, 53.7% of managersNetherlands: 5.5% of population, 28.5% of managersNorway: 4.11% of population, 30.8% of managersNepal: 5.08% of population, 13.9% of managersPakistan: 96.5% of population, 9.57% of managersPanama: 0.0531% of population, 50% of managersPeru: 0.0216% of population, 32.9% of managersPhilippines: 6.46% of population, 43.2% of managersPapua New Guinea: 0.0748% of population, 17.7% of managersPoland: 0.00732% of population, 40.6% of managersPortugal: 0.409% of population, 39.4% of managersWest Bank and Gaza: 99% of population, 23.5% of managersRomania: 0.356% of population, 34.7% of managersRussian Federation: 8.19% of population, 41.7% of managersRwanda: 1.81% of population, 30.8% of managersSudan: 98.9% of population, 13.1% of managersSenegal: 97.6% of population, 23% of managersSingapore: 16.1% of population, 39.9% of managersSolomon Islands: 0.34% of population, 25.1% of managersSierra Leone: 80.1% of population, 22.6% of managersEl Salvador: 0.0035% of population, 39% of managersSomalia, Fed. Rep.: 99.8% of population, 27.7% of managersSerbia: 4.42% of population, 31.9% of managersSao Tome and Principe: 0.0915% of population, 71% of managersSuriname: 13.1% of population, 42.2% of managersSlovak Republic: 0.0548% of population, 34.1% of managersSlovenia: 1.61% of population, 34.9% of managersSweden: 8.1% of population, 44.7% of managersEswatini: 0.136% of population, 25.2% of managersSeychelles: 0.893% of population, 50.2% of managersTogo: 16.1% of population, 29.5% of managersThailand: 4.51% of population, 34.5% of managersTajikistan: 98.9% of population, 24.5% of managersTimor-Leste: 0.257% of population, 22.4% of managersTonga: 0.0605% of population, 36.9% of managersTrinidad and Tobago: 5.46% of population, 52.7% of managersTunisia: 99.3% of population, 20.8% of managersTurkiye: 97.1% of population, 21.5% of managersTanzania: 29.9% of population, 29.7% of managersUganda: 11.4% of population, 25.6% of managersUkraine: 0.568% of population, 44.1% of managersUruguay: 0.0893% of population, 33.8% of managersUnited States: 1.19% of population, 44.1% of managersViet Nam: 0.0721% of population, 26.1% of managersVanuatu: 0.0193% of population, 37.9% of managersSamoa: 0.0253% of population, 40.7% of managersKosovo: 94.3% of population, 26.7% of managersSouth Africa: 1.6% of population, 39.3% of managersZambia: 0.511% of population, 29.6% of managersZimbabwe: 0.529% of population, 34.4% of managersAFGBGDBHSBTNJAMJORJPNNPLPAKSTP

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.4586.9e-9145
By rank (Spearman), not adjusted-0.4306.7e-8145
Standard (Pearson), adjusted for national income-0.4083.9e-7145
By rank (Spearman), adjusted for national income-0.4123.0e-7145

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 145 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: +0.050 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.450 (without JOR) to -0.390 (without BGD). 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: JOR (-0.042).

Fragile: this link may not hold up.
  • correlation moves sharply once outliers are trimmed
  • 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 & Pacific21-0.07
Europe & Central Asia44-0.52
Latin America & Caribbean24+0.04
Middle East, North Africa, Afghanistan & Pakistan12+0.05
Sub-Saharan Africa37-0.42

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 third49-0.47
Middle third48-0.40
Richest third48-0.27

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
Christians97-0.19
Muslims31-0.27

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
France14-0.47
Never a European colony13-0.31
Spain17+0.12
United Kingdom49-0.47

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 = -0.159 after dropping 32 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
% of managers		Years
Afghanistan AFG99.9%5.89%2020
Somalia, Fed. Rep. SOM99.8%27.7%2020, 2019
Iran, Islamic Rep. IRN99.8%21.4%2020, 2024
Iraq IRQ99.5%17.5%2020, 2021
Tunisia TUN99.3%20.8%2020, 2021
West Bank and Gaza PSE99%23.5%2020, 2025
Tajikistan TJK98.9%24.5%2020, 2016
Sudan SDN98.9%13.1%2020, 2022
Niger NER98.1%21.6%2020, 2017
Senegal SEN97.6%23%2020, 2024
Turkiye TUR97.1%21.5%2020, 2024
Jordan JOR97.1%52.3%2020, 2023
Gambia, The GMB97%28.1%2020, 2025
Pakistan PAK96.5%9.57%2020, 2025
Egypt, Arab Rep. EGY95.2%22.3%2020, 2024

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.
World Bank, World Development Indicators
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 in management

Female share of employment in senior and middle management (%)

International Labour Organization · CC BY 4.0 · updated quarterly

Based on surveys and reported irregularly.

How this was computed

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

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

More links with Muslim share or Women in management