Conflict deaths vs. Military spending
Fades after adjusting for income
Across 156 countries, Conflict deaths and Military spending rise and fall together at r = +0.70 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) leaves r = +0.72, which could easily be chance (q = 0.19, allowing for the many pairs tested, and allowing for countries in the same region being alike). Caution: leave-one-out range spans 0.85 in r.
Comparing countries across the middle half of conflict deaths, 0 to 0.104 per 100,000 people, military spending is 0.0102% of GDP higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0105% of GDP.
Link before adjusting (r)+0.704p = 1.2e-24 · 156 countries
After adjusting for national income+0.725p = 1.5e-26 · likely range [+0.64, +0.79]
p, allowing for regions0.056standard error 0.306 · 7 regions
Check for luck (q)0.193across 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.
Conflict deaths · per 100,000 peoplelink with income -0.42 · moderate
Military spending · % of GDPlink with income +0.19 · independent
“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 | +0.704 | 1.2e-24 | 156 |
| By rank (Spearman), not adjusted | +0.053 | 0.512 | 156 |
| Standard (Pearson), adjusted for national income | +0.725 | 1.5e-26 | 156 |
| By rank (Spearman), adjusted for national income | +0.165 | 0.040 | 156 |
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 156 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: -0.021 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.008 (without UKR) to +0.858 (without SDN). 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: UKR (-0.717).
Fragile: this link may not hold up.
- leave-one-out range spans 0.85 in r
- correlation moves sharply once outliers are trimmed
- sign flips 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.
| n | r | ||
|---|---|---|---|
| East Asia & Pacific | 19 | +0.85 | |
| Europe & Central Asia | 47 | +0.97 | |
| Latin America & Caribbean | 20 | -0.20 | |
| Middle East, North Africa, Afghanistan & Pakistan | 20 | +0.08 | |
| Sub-Saharan Africa | 44 | -0.06 |
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 | 52 | -0.04 | |
| Middle third | 52 | +0.95 | |
| Richest third | 52 | +0.42 |
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 | 92 | +0.95 | |
| Muslims | 45 | +0.00 |
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.
| n | r | ||
|---|---|---|---|
| France | 23 | +0.24 | |
| Never a European colony | 20 | -0.10 | |
| Spain | 17 | +0.07 | |
| United Kingdom | 47 | +0.02 |
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 = -0.136 after dropping 43 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 35years. 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 = +0.053, 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 conflict deaths moved did not tend to see their military spending move with it.
Across countries (adjusted)+0.725for comparison
Within countries+0.055each country vs itself
…and vs the same year elsewhere+0.053q = 0.541 · 164 countries
Year-on-year changes+0.027q = 0.501
5,087 country-years (one country in one year), 164 countries, 1990–2024, about 31 years each on average. Share of the variation that happens within countries over time: 96% for Conflict deaths, 55% for Military spending. 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): +0.053. 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 people | % of GDP | Years | |
|---|---|---|---|
| Ukraine UKR | 232 | 34.5% | 2025, 2024 |
| Sudan SDN | 145 | 0.925% | 2025, 2021 |
| Haiti HTI | 20.4 | 0.0684% | 2025, 2024 |
| Somalia, Fed. Rep. SOM | 19.7 | 1.59% | 2025, 2024 |
| Burkina Faso BFA | 18.6 | 4.68% | 2025, 2024 |
| Syrian Arab Republic SYR | 13.4 | 4.06% | 2025, 2010 |
| Mali MLI | 8.54 | 4.2% | 2025, 2024 |
| Congo, Dem. Rep. COD | 7.85 | 1.23% | 2025, 2024 |
| Central African Republic CAF | 6.28 | 2.52% | 2025, 2024 |
| Mexico MEX | 5.94 | 0.893% | 2025, 2024 |
| Lebanon LBN | 5.93 | 2.59% | 2025, 2024 |
| Congo, Rep. COG | 4.64 | 1.19% | 2025, 2024 |
| Myanmar MMR | 4.21 | 6.79% | 2025, 2024 |
| Ethiopia ETH | 4 | 0.651% | 2025, 2024 |
| Niger NER | 3.98 | 2.24% | 2025, 2024 |
Uppsala Conflict Data Program, Georeferenced Event Dataset; rate per population from Our World in Data
World Bank, World Development Indicators
Sources
Conflict deaths
Deaths in armed conflicts, per 100,000 people
Uppsala Conflict Data Program, Uppsala University · via Our World in Data · CC BY 4.0 · updated annual
Deaths from organised violence on a country's territory, per 100,000 of its people. That covers fighting involving a government, fighting between other armed groups, and attacks on civilians. Deaths are counted where the fighting happens, not by who was fighting. So a war fought on one country's soil by another country's army counts here. It is zero for most countries in most years, and in the hundreds per hundred thousand for a few at war. That is why it is put on a log scale (which squeezes very large values together) where it is used for adjusting. It is also why the "leave one out" check matters on every pair involving it: a handful of countries carry the whole link. The site's only other measure of violence is the homicide rate, which counts something different. A peaceful country can have a high homicide rate, and a country at war can have a low one. It is kept out of every topic score. In 2023, 143 of the 197 countries reporting it report exactly zero. A log scale, used here since a few values are huge, cannot handle zero, so every zero becomes a blank. A safety score built on it covered 79 countries instead of 172. It silently dropped the peaceful ones, the opposite of what such a score should say. A score needs parts that vary across nearly every country. This one is a rare event almost everywhere and the biggest fact in a dozen places. That makes it worth its own page, and useless inside an average.
Military spending
Military expenditure (% of GDP)
Stockholm International Peace Research Institute (SIPRI) · CC BY 4.0 · updated quarterly
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 Conflict deaths and Military spending
This page shows that two measures go together. It does not show that Conflict deaths changes Military spending, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Conflict deaths or Military spending
- Military spending vs Trust in government before -0.27 → after adjusting -0.31
- Freedom of association vs Military spending before -0.20 → after adjusting -0.24
- Equality score vs Military spending before +0.17 → after adjusting +0.18
- Conflict deaths vs Tertiary enrollment before +0.01 → after adjusting +0.18
- Conflict deaths vs Physicians before -0.01 → after adjusting +0.17
- Conflict deaths vs Informal employment before +0.08 → after adjusting -0.17
- Conflict deaths vs Health coverage index before -0.05 → after adjusting +0.14
- Conflict deaths vs Pupil-teacher ratio before -0.02 → after adjusting -0.14