Across 187 countries, Armed conflict present and FDI inflows rise and fall together at r = -0.10 (on a scale from −1 to +1, where 0 means no link). There is almost no link to explain.
Comparing countries across the middle half of armed conflict present, 0 to 1 points, fdi inflows is 1.74% of GDP lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 2.14% of GDP.
Link before adjusting (r)-0.100p = 0.174 · 187 countries
After adjusting for national income-0.112p = 0.128 · likely range [-0.25, +0.03]
p, allowing for regions0.003standard error 0.023 · 7 regions
Check for luck (q)0.035across 14,952 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
FDI inflows · % of GDPlink with income -0.01 · 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
-0.100
0.174
187
By rank (Spearman), not adjusted
-0.164
0.025
187
Standard (Pearson), adjusted for national income
-0.112
0.128
187
By rank (Spearman), adjusted for national income
-0.197
0.007
187
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 187 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: -0.012 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from -0.129 (without MOZ) to -0.096 (without GIN). 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: MOZ (-0.017).
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
-0.13
Europe & Central Asia
51
-0.04
Latin America & Caribbean
31
-0.19
Middle East, North Africa, Afghanistan & Pakistan
22
-0.19
Sub-Saharan Africa
46
-0.22
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
-0.19
Middle third
62
-0.21
Richest third
62
-0.04
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
-0.10
Muslims
50
-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.
n
r
France
25
-0.20
Never a European colony
21
-0.21
Spain
20
-0.33
United Kingdom
63
-0.15
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 = -0.139 after dropping 23 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 36years. 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 = -0.002, 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 armed conflict present moved did not tend to see their fdi inflows move with it.
Across countries (adjusted)-0.112for comparison
Within countries-0.008each country vs itself
…and vs the same year elsewhere-0.002q = 0.762 · 190 countries
Year-on-year changes+0.002q = 0.735
6,495 country-years (one country in one year), 190 countries, 1990–2025, about 34 years each on average. Share of the variation that happens within countries over time: 44% for Armed conflict present, 65% for FDI inflows. 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): -0.002. 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.
This curve peaks at the edge of the window (lag +10), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.
The data
1 if any conflict, else 0
% of GDP
Years
South Africa ZAF
1
-0.506%
2025
Ukraine UKR
1
0.758%
2025
Uganda UGA
1
5.42%
2025
Tanzania TZA
1
1.91%
2025
Turkiye TUR
1
0.812%
2025
Thailand THA
1
3.21%
2025
Togo TGO
1
1.86%
2025
Chad TCD
1
0.02%
2025
Syrian Arab Republic SYR
1
1.19%
2025, 2011
Somalia, Fed. Rep. SOM
1
6.42%
2025
Sudan SDN
1
0.000003%
2025
Saudi Arabia SAU
1
2.56%
2025
Rwanda RWA
1
5.91%
2025
Russian Federation RUS
1
0.435%
2025
Qatar QAT
1
1.41%
2025
Uppsala Conflict Data Program, Georeferenced Event Dataset; rate per population from Our World in Data World Bank, World Development Indicators
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.
Data used: most recent value in 2010-2025; values come from 2011–2025. 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 14,952 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Armed conflict present and FDI inflows
This page shows that two measures go together. It does not show that Armed conflict present changes FDI inflows, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Armed conflict present or FDI inflows