Across 188 countries, Armed conflict present and Political stability rise and fall together at r = -0.64 (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 = -0.55, q = 0.032, allowing for the many pairs tested).
Comparing countries across the middle half of armed conflict present, 0 to 1 points, political stability is worse by 1.38 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1.06 points.
Link before adjusting (r)-0.642p = 3.4e-23 · 188 countries
After adjusting for national income-0.549p = 4.2e-16 · likely range [-0.64, -0.44]
p, allowing for regions0.002standard error 0.106 · 7 regions
Check for luck (q)0.032across 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.
Armed conflict present · 1 if any conflict, else 0link with income -0.39 · moderate
Political stability · index (approx. -2.5 to 2.5)link with income +0.56 · moderate
“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
-0.642
3.4e-23
188
By rank (Spearman), not adjusted
-0.608
2.3e-20
188
Standard (Pearson), adjusted for national income
-0.549
4.2e-16
188
By rank (Spearman), adjusted for national income
-0.510
9.0e-14
188
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 188 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: +0.093 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from -0.570 (without CRI) to -0.538 (without ISR). 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: CRI (-0.021).
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
29
-0.81
Europe & Central Asia
52
-0.48
Latin America & Caribbean
31
-0.56
Middle East, North Africa, Afghanistan & Pakistan
22
-0.54
Sub-Saharan Africa
46
-0.59
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
63
-0.63
Middle third
62
-0.45
Richest third
63
-0.52
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
108
-0.56
Muslims
50
-0.65
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
25
-0.45
Never a European colony
21
-0.76
Spain
20
-0.39
United Kingdom
63
-0.59
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 = -0.549 after dropping 0 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.
The link also shows up within countries over time (r = -0.288). It holds even when looking only at changes from one year to the next (r = -0.072). This is the strongest kind of evidence available here: it holds when each country is compared only with itself, and it is not just a product of shared trends.
Across countries (adjusted)-0.549for comparison
Within countries-0.285each country vs itself
…and vs the same year elsewhere-0.288q = 0.000 · 197 countries
Year-on-year changes-0.072q = 0.013
Read with care.
The association is much weaker in year-on-year changes than in levels, which points to shared country-specific trends.
5,054 country-years (one country in one year), 197 countries, 1996–2024, about 26 years each on average. Share of the variation that happens within countries over time: 40% for Armed conflict present, 12% for Political stability. 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): -0.288. 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
1 if any conflict, else 0
index (approx. -2.5 to 2.5)
Years
South Africa ZAF
1
-0.617
2025, 2024
Ukraine UKR
1
-0.432
2025, 2024
Uganda UGA
1
-1.02
2025, 2024
Tanzania TZA
1
-0.39
2025, 2024
Turkiye TUR
1
-0.971
2025, 2024
Thailand THA
1
-0.683
2025, 2024
Togo TGO
1
-0.809
2025, 2024
Chad TCD
1
-1.78
2025, 2024
Syrian Arab Republic SYR
1
-2.37
2025, 2024
Somalia, Fed. Rep. SOM
1
-2.26
2025, 2024
Sudan SDN
1
-2.02
2025, 2024
Saudi Arabia SAU
1
-0.0482
2025, 2024
Rwanda RWA
1
-0.0437
2025, 2024
Russian Federation RUS
1
-0.903
2025, 2024
Qatar QAT
1
0.951
2025, 2024
Uppsala Conflict Data Program, Georeferenced Event Dataset; rate per population from Our World in Data Kaufmann, D. and A. Kraay, Worldwide Governance Indicators, World Bank
Whether an armed conflict is taking place in the country
Uppsala Conflict Data Program, Uppsala University · via Our World in Data · CC BY 4.0 · updated annual
One if any armed conflict took place on the country's territory that year, and zero if not. That makes it the site's first true yes-or-no measure. A link with a yes-or-no measure is a fair one: it compares the countries at war with the countries not at war. It answers a different question from the death rate: whether a country has a war at all, not how many people die. The two are treated as measuring the same thing, so their pair reads as two views of one thing, not as a finding. It is kept out of the crime score. A yes-or-no flag averaged into a combined score beside a rate would count the same conflicts twice.
Political Stability and Absence of Violence/Terrorism (estimate)
World Bank · CC BY 4.0 · updated annual
How this was computed
Data used: most recent value in 2010-2025; values come from 2024–2025. 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 Armed conflict present and Political stability
This page shows that two measures go together. It does not show that Armed conflict present changes Political stability, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Armed conflict present or Political stability