Across 190 countries, Government effectiveness and Refugees originating rise and fall together at r = -0.31 (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 = -0.19, q = 0.0046, allowing for the many pairs tested). Caution: correlation moves sharply once outliers are trimmed.
Comparing countries across the middle half of refugees originating, 2.16 to 131 per 100,000 people, government effectiveness is worse by 0.0154 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.00534 points.
Link before adjusting (r)-0.311p = 1.2e-5 · 190 countries
After adjusting for national income-0.190p = 0.009 · likely range [-0.32, -0.05]
p, allowing for regions0.131standard error 0.109 · 7 regions
Check for luck (q)0.005across 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.
Government effectiveness · index (approx. -2.5 to 2.5)link with income +0.85 · proxy
Refugees originating · per 100,000 peoplelink with income -0.49 · 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
-0.311
1.2e-5
190
By rank (Spearman), not adjusted
-0.579
2.3e-18
190
Standard (Pearson), adjusted for national income
-0.190
0.009
190
By rank (Spearman), adjusted for national income
-0.354
5.6e-7
190
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 190 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: +0.121 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from -0.210 (without CAF) to -0.143 (without SYR). 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: SYR (+0.047).
Fragile: this link may not hold up.
correlation moves sharply once outliers are trimmed
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
31
-0.42
Europe & Central Asia
48
-0.12
Latin America & Caribbean
34
-0.05
Middle East, North Africa, Afghanistan & Pakistan
22
-0.26
Sub-Saharan Africa
46
-0.21
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
64
-0.40
Middle third
63
-0.13
Richest third
63
-0.13
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
109
-0.11
Muslims
49
-0.34
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
-0.18
Spain
20
-0.11
United Kingdom
63
-0.33
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 = -0.345 after dropping 29 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 = -0.175). It holds even when looking only at changes from one year to the next (r = -0.067). 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)-0.190for comparison
Within countries-0.173each country vs itself
…and vs the same year elsewhere-0.175q = 0.000 · 193 countries
Year-on-year changes-0.067q = 0.000
Read with care.
Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.
4,730 country-years (one country in one year), 193 countries, 1996–2024, about 25 years each on average. Share of the variation that happens within countries over time: 42% for Government effectiveness, 6% for Refugees originating. 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): -0.175. 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
index (approx. -2.5 to 2.5)
per 100,000 people
Years
Singapore SGP
2.28
0.772
2024
Japan JPN
2.09
0.0444
2024
Luxembourg LUX
2.04
0.743
2024
Denmark DNK
1.91
0.268
2024
New Zealand NZL
1.85
0.997
2024
Norway NOR
1.84
0.395
2024
Switzerland CHE
1.84
0.056
2024
Finland FIN
1.82
0.089
2024
Australia AUS
1.81
0.116
2024
Sweden SWE
1.77
0.924
2024
Canada CAN
1.76
0.778
2024
Netherlands NLD
1.75
0.746
2024
Iceland ISL
1.65
0
2024
Hong Kong SAR, China HKG
1.64
3.24
2024
Ireland IRL
1.61
1.29
2024
Kaufmann, D. and A. Kraay, Worldwide Governance Indicators, World Bank UNHCR Refugee Data Finder; rate per population from Our World in Data
Refugees originating from the country, per 100,000 people
United Nations High Commissioner for Refugees · via Our World in Data · CC BY 4.0 · updated annual
People recognised as refugees abroad, compared with the population of the country they left. It is zero for most of the world and in the thousands for a dozen countries at war. So it is put on a log scale (which squeezes very large values together) wherever it is used for adjusting, and its links lean on those few countries. The "leave one out" check shows by how much. It has a "better" direction and sits under governance. But it is an outcome of governance, not a measure of it, so it is kept out of the governance score.
How this was computed
Data used: most recent value in 2010-2025; values come from 2022–2024. 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 Government effectiveness and Refugees originating
This page shows that two measures go together. It does not show that Government effectiveness changes Refugees originating, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Government effectiveness or Refugees originating