placestats

Homicide rate vs. Women in management

Holds up after adjusting for income

Across 131 countries, Homicide rate and Women in management rise and fall together at r = +0.42 (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 = +0.46, q = 0.017, allowing for the many pairs tested). Caution: direction is not consistent across regions.

Comparing countries across the middle half of homicide rate, 0.985 to 6.94 per 100,000 population, women in management is better by 2.95% of managers at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 3.13% of managers.

Link before adjusting (r)+0.421p = 5.5e-7 · 131 countries
After adjusting for national income+0.455p = 5.3e-8 · likely range [+0.31, +0.58]
p, allowing for regions0.001standard error 0.072 · 7 regions
Check for luck (q)0.017across 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.

Homicide rate · per 100,000 populationlink with income -0.38 · moderate
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

Homicide rate · per 100,000 population →Women in management · % of managers →049.45.89%71%Afghanistan: 4.03 per 100,000 population, 5.89% of managersAngola: 4.1 per 100,000 population, 16.2% of managersAlbania: 1.76 per 100,000 population, 33.4% of managersUnited Arab Emirates: 0.693 per 100,000 population, 23.5% of managersArgentina: 4.49 per 100,000 population, 34.1% of managersArmenia: 2.21 per 100,000 population, 31.9% of managersAustralia: 0.854 per 100,000 population, 39.4% of managersAustria: 0.876 per 100,000 population, 36.3% of managersBurundi: 5.65 per 100,000 population, 25.7% of managersBelgium: 1.08 per 100,000 population, 33.1% of managersBangladesh: 2.34 per 100,000 population, 7.23% of managersBulgaria: 1.09 per 100,000 population, 39.1% of managersBahamas, The: 32.2 per 100,000 population, 59.8% of managersBosnia and Herzegovina: 1.22 per 100,000 population, 30.2% of managersBelarus: 2.38 per 100,000 population, 42% of managersBelize: 28.1 per 100,000 population, 41.7% of managersBolivia: 4.42 per 100,000 population, 22.3% of managersBrazil: 19.3 per 100,000 population, 38.7% of managersBarbados: 7.44 per 100,000 population, 50.4% of managersBrunei Darussalam: 0.486 per 100,000 population, 36.4% of managersBhutan: 2.47 per 100,000 population, 15.5% of managersBotswana: 11.4 per 100,000 population, 48.2% of managersSwitzerland: 0.597 per 100,000 population, 33.3% of managersChile: 6.35 per 100,000 population, 31.6% of managersColombia: 24.9 per 100,000 population, 41.9% of managersCosta Rica: 17.7 per 100,000 population, 46.2% of managersCyprus: 0.957 per 100,000 population, 27.5% of managersCzechia: 0.768 per 100,000 population, 26.9% of managersGermany: 0.911 per 100,000 population, 27.7% of managersDenmark: 0.841 per 100,000 population, 26.9% of managersDominican Republic: 10.9 per 100,000 population, 47.8% of managersEcuador: 45.7 per 100,000 population, 45.3% of managersEgypt, Arab Rep.: 1.31 per 100,000 population, 22.3% of managersSpain: 0.691 per 100,000 population, 37% of managersEstonia: 1.54 per 100,000 population, 36% of managersEthiopia: 8.51 per 100,000 population, 27% of managersFinland: 0.982 per 100,000 population, 39.2% of managersFiji: 2.06 per 100,000 population, 34.9% of managersFrance: 1.35 per 100,000 population, 38.7% of managersMicronesia, Fed. Sts.: 0.907 per 100,000 population, 18.2% of managersUnited Kingdom: 1.12 per 100,000 population, 40.5% of managersGeorgia: 2.03 per 100,000 population, 37.5% of managersGhana: 1.83 per 100,000 population, 26.6% of managersGuinea-Bissau: 1.12 per 100,000 population, 25.6% of managersGreece: 0.84 per 100,000 population, 35% of managersGrenada: 13.7 per 100,000 population, 43.3% of managersGuatemala: 23.4 per 100,000 population, 39.8% of managersGuyana: 19.1 per 100,000 population, 42.1% of managersHonduras: 31.4 per 100,000 population, 46% of managersCroatia: 0.667 per 100,000 population, 25.5% of managersHungary: 0.723 per 100,000 population, 42.1% of managersIndonesia: 0.304 per 100,000 population, 24.8% of managersIndia: 2.82 per 100,000 population, 11.9% of managersIreland: 0.654 per 100,000 population, 37.8% of managersIran, Islamic Rep.: 2.38 per 100,000 population, 21.4% of managersIraq: 9.46 per 100,000 population, 17.5% of managersIceland: 1.29 per 100,000 population, 37.3% of managersIsrael: 1.63 per 100,000 population, 32.8% of managersItaly: 0.568 per 100,000 population, 25.3% of managersJamaica: 49.4 per 100,000 population, 63.9% of managersJordan: 0.988 per 100,000 population, 52.3% of managersJapan: 0.229 per 100,000 population, 14.5% of managersKenya: 4.87 per 100,000 population, 43.6% of managersCambodia: 1.82 per 100,000 population, 23.6% of managersKiribati: 7.12 per 100,000 population, 37.4% of managersLebanon: 2.24 per 100,000 population, 28.9% of managersLiberia: 3.09 per 100,000 population, 26.1% of managersSri Lanka: 3.31 per 100,000 population, 29.2% of managersLithuania: 2.63 per 100,000 population, 37.4% of managersLuxembourg: 1.53 per 100,000 population, 26.9% of managersLatvia: 2.5 per 100,000 population, 44% of managersMaldives: 0.615 per 100,000 population, 22.6% of managersMexico: 24.9 per 100,000 population, 39.3% of managersNorth Macedonia: 1.53 per 100,000 population, 36.4% of managersMalta: 0.563 per 100,000 population, 22.7% of managersMyanmar: 2.58 per 100,000 population, 41% of managersMontenegro: 0.789 per 100,000 population, 48.1% of managersMongolia: 5.64 per 100,000 population, 40.5% of managersMozambique: 3.59 per 100,000 population, 29.1% of managersMauritius: 2.27 per 100,000 population, 35.6% of managersMalawi: 1.78 per 100,000 population, 47.7% of managersNamibia: 11.2 per 100,000 population, 48.2% of managersNiger: 4.42 per 100,000 population, 21.6% of managersNigeria: 15.7 per 100,000 population, 37.9% of managersNicaragua: 11.3 per 100,000 population, 53.7% of managersNetherlands: 0.691 per 100,000 population, 28.5% of managersNorway: 0.725 per 100,000 population, 30.8% of managersNepal: 2.13 per 100,000 population, 13.9% of managersPakistan: 4.33 per 100,000 population, 9.57% of managersPanama: 11.7 per 100,000 population, 50% of managersPeru: 8.6 per 100,000 population, 32.9% of managersPhilippines: 4.35 per 100,000 population, 43.2% of managersPalau: 11.2 per 100,000 population, 45.5% of managersPapua New Guinea: 9.34 per 100,000 population, 17.7% of managersPoland: 0.802 per 100,000 population, 40.6% of managersPortugal: 0.72 per 100,000 population, 39.4% of managersWest Bank and Gaza: 0.622 per 100,000 population, 23.5% of managersRomania: 1.12 per 100,000 population, 34.7% of managersRussian Federation: 7.82 per 100,000 population, 41.7% of managersRwanda: 3.61 per 100,000 population, 30.8% of managersSingapore: 0.0691 per 100,000 population, 39.9% of managersSierra Leone: 2.22 per 100,000 population, 22.6% of managersEl Salvador: 7.9 per 100,000 population, 39% of managersSerbia: 1.31 per 100,000 population, 31.9% of managersSao Tome and Principe: 3.23 per 100,000 population, 71% of managersSuriname: 6.52 per 100,000 population, 42.2% of managersSlovak Republic: 1.12 per 100,000 population, 34.1% of managersSlovenia: 0.566 per 100,000 population, 34.9% of managersSweden: 1.15 per 100,000 population, 44.7% of managersEswatini: 12.5 per 100,000 population, 25.2% of managersSeychelles: 7.97 per 100,000 population, 50.2% of managersThailand: 4.79 per 100,000 population, 34.5% of managersTajikistan: 0.892 per 100,000 population, 24.5% of managersTimor-Leste: 4.07 per 100,000 population, 22.4% of managersTonga: 0.946 per 100,000 population, 36.9% of managersTrinidad and Tobago: 40.4 per 100,000 population, 52.7% of managersTunisia: 4.69 per 100,000 population, 20.8% of managersTurkiye: 3.23 per 100,000 population, 21.5% of managersTuvalu: 0 per 100,000 population, 36.1% of managersTanzania: 3.75 per 100,000 population, 29.7% of managersUganda: 8.97 per 100,000 population, 25.6% of managersUkraine: 3.78 per 100,000 population, 44.1% of managersUruguay: 11.2 per 100,000 population, 33.8% of managersUnited States: 5.76 per 100,000 population, 44.1% of managersViet Nam: 1.54 per 100,000 population, 26.1% of managersVanuatu: 0.335 per 100,000 population, 37.9% of managersSamoa: 6.26 per 100,000 population, 40.7% of managersKosovo: 1.89 per 100,000 population, 26.7% of managersSouth Africa: 43.7 per 100,000 population, 39.3% of managersZambia: 5.2 per 100,000 population, 29.6% of managersZimbabwe: 6.76 per 100,000 population, 34.4% of managersAFGBGDECUJAMJORMNEPAKSTPTTOZAF

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.4215.5e-7131
By rank (Spearman), not adjusted+0.3210.000131
Standard (Pearson), adjusted for national income+0.4555.3e-8131
By rank (Spearman), adjusted for national income+0.4488.9e-8131

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 131 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: -0.034 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.400 (without JAM) to +0.494 (without STP). 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: JAM (-0.055).

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+0.26
Europe & Central Asia43+0.22
Latin America & Caribbean24+0.60
Middle East, North Africa, Afghanistan & Pakistan12-0.38
Sub-Saharan Africa24+0.01

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 third44+0.38
Middle third43+0.57
Richest third44+0.55

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
Christians90+0.46
Muslims23+0.05

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
Never a European colony12+0.45
Spain17+0.48
United Kingdom45+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 = +0.346 after dropping 14 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 25years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Within countries over time, there is no link that is clearly more than chance (r = +0.005, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose homicide rate moved did not tend to see their women in management move with it.

Across countries (adjusted)+0.455for comparison
Within countries-0.075each country vs itself
…and vs the same year elsewhere+0.005q = 0.959 · 74 countries
Year-on-year changes-0.019q = 0.675

1,240 country-years (one country in one year), 74 countries, 2000–2024, about 17 years each on average. Share of the variation that happens within countries over time: 13% for Homicide rate, 20% for Women in management. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

0.10−0.1-100+10years Women in management trails Homicide rate →lag -10: r = 0.048 (n = 649)lag -9: r = -0.021 (n = 701)lag -8: r = -0.039 (n = 765)lag -7: r = -0.018 (n = 810)lag -6: r = 0.018 (n = 865)lag -5: r = 0.026 (n = 919)lag -4: r = 0.054 (n = 977)lag -3: r = 0.074 (n = 1,026)lag -2: r = -0.001 (n = 1,098)lag -1: r = -0.004 (n = 1,160)lag +0: r = 0.005 (n = 1,240)lag +1: r = 0.031 (n = 1,302)lag +2: r = 0.059 (n = 1,348)lag +3: r = 0.078 (n = 1,373)lag +4: r = 0.090 (n = 1,373)lag +5: r = 0.084 (n = 1,387)lag +6: r = 0.073 (n = 1,380)lag +7: r = 0.031 (n = 1,373)lag +8: r = 0.025 (n = 1,358)lag +9: r = 0.003 (n = 1,341)lag +10: r = 0.010 (n = 1,333)

Same year (lag 0): +0.005. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

The largest value on this curve (+0.09 at lag +4) is higher than the same-year one by 0.09. That gap is not a finding. It is the largest of 21 closely related estimates, and picking the biggest of many tests always makes it look bigger. That is exactly why nothing on this site is ranked or chosen by lag.

The data


per 100,000 population
% of managers		Years
Jamaica JAM49.463.9%2023, 2014
Ecuador ECU45.745.3%2023, 2025
South Africa ZAF43.739.3%2022, 2024
Trinidad and Tobago TTO40.452.7%2022, 2024
Bahamas, The BHS32.259.8%2022, 2023
Honduras HND31.446%2023, 2025
Belize BLZ28.141.7%2022, 2016
Colombia COL24.941.9%2023, 2025
Mexico MEX24.939.3%2023, 2025
Guatemala GTM23.439.8%2023, 2024
Brazil BRA19.338.7%2023, 2025
Guyana GUY19.142.1%2023, 2021
Costa Rica CRI17.746.2%2023, 2025
Nigeria NGA15.737.9%2023, 2024
Grenada GRD13.743.3%2023

UN Office on Drugs and Crime, Intentional Homicide Victims
World Bank, World Development Indicators

Sources

Homicide rate

Intentional homicide rate (per 100,000 population)

United Nations Office on Drugs and Crime · via Our World in Data · CC BY 3.0 IGO · updated annual

Counts victims of intentional homicide (murder). Homicide is the crime least often left unreported. So it is the only crime figure similar enough across countries to use here. Rates of assault, theft and rape reflect how often people report crimes and how police record them, at least as much as how much crime there is, so they are left out on purpose. Even homicide figures shift when a country switches between police records and public-health records.

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 Homicide rate and Women in management

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

More links with Homicide rate or Women in management