Do Homicide rate and Researchers go together across countries?

Across 121 countries the link before adjusting for anything is r = -0.35, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives -0.63.

Does the link hold within countries over time, not just across countries?

Comparing each country only with itself across 1996-2024, and setting aside what happened worldwide in each year, the link is +0.096 (80 countries, 1,503 country-years). Using year-to-year changes, it is +0.026.

Does Homicide rate cause Researchers?

This analysis cannot answer that. It shows only that the two go together. A link between two country measures, adjusted or not, does not show that either one changes the other. Country figures also say nothing about individual people.

Homicide rate vs. Researchers

Holds up after adjusting for income

Across 121 countries, Homicide rate and Researchers rise and fall together at r = -0.35 (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 = -0.27, q = 0.012, allowing for the many pairs tested). Caution: direction is not consistent across regions.

Comparing countries across the middle half of homicide rate, 0.841 to 4.87 per 100,000 population, researchers is worse by 423 per million people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 244 per million people.

Link before adjusting (r)-0.351p = 8.0e-5 · 121 countries

After adjusting for national income-0.268p = 0.003 · likely range [-0.43, -0.09]

p, allowing for regions0.000standard error 0.038 · 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.

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

Researchers · per million peoplelink with income +0.85 · proxy

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

Every country as a dot

best-fit line line after adjusting

Four ways to measure the link

Method	r	p	Countries
Standard (Pearson), not adjusted	-0.351	8.0e-5	121
By rank (Spearman), not adjusted	-0.629	1.1e-14	121
Standard (Pearson), adjusted for national income	-0.268	0.003	121
By rank (Spearman), adjusted for national income	-0.281	0.002	121

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 121 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: +0.083 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.279 (without HND) to -0.246 (without TTO). 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: TTO (+0.022).

Fragile: this link may not hold up.

direction is not consistent across regions
much weaker within regions than across them (largely a between-region difference)

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.

	n	r
East Asia & Pacific	18	+0.00
Europe & Central Asia	45	-0.21
Latin America & Caribbean	17	-0.02
Middle East, North Africa, Afghanistan & Pakistan	17	-0.07
Sub-Saharan Africa	19	+0.12

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.

	n	r
Poorest third	41	-0.21
Middle third	40	-0.37
Richest third	40	-0.20

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.

	n	r
Christians	75	-0.40
Muslims	27	-0.12

By last european coloniser

	n	r
Never a European colony	15	-0.09
Spain	16	-0.26
United Kingdom	34	-0.16

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 = -0.153 after dropping 19 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 29years. 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 = +0.096, 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 researchers move with it.

Across countries (adjusted)-0.268for comparison

Within countries-0.051each country vs itself

…and vs the same year elsewhere+0.096q = 0.390 · 80 countries

Year-on-year changes+0.026q = 0.457

1,503 country-years (one country in one year), 80 countries, 1996–2024, about 19 years each on average. Share of the variation that happens within countries over time: 15% for Homicide rate, 15% for Researchers. 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

Same year (lag 0): +0.096. 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 data

	per 100,000 population	per million people	Years
Ecuador ECU	45.7	400	2023, 2014
South Africa ZAF	43.7	444	2022
Trinidad and Tobago TTO	40.4	493	2022
Honduras HND	31.4	188	2023, 2019
Colombia COL	24.9	90.2	2023, 2017
Mexico MEX	24.9	438	2023, 2024
Guatemala GTM	23.4	1.45	2023
Brazil BRA	19.3	903	2023, 2014
Costa Rica CRI	17.7	508	2023
Nigeria NGA	15.7	22.1	2023, 2019
Puerto Rico (US) PRI	15.1	332	2024, 2015
Eswatini SWZ	12.5	138	2021, 2015
Panama PAN	11.7	250	2023, 2024
Botswana BWA	11.4	180	2021, 2013
Uruguay URY	11.2	938	2023, 2024

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.

Researchers

Researchers in R&D (per million people)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

Researchers counted as full-time equivalents (two half-time researchers count as one), from national research surveys that many countries run only now and then. So coverage is thin outside the OECD.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2024. 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 Researchers

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