Across 191 countries, Environment score and Refugees originating rise and fall together at r = -0.08 (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 refugees originating, 2.3 to 129 per 100,000 people, environment score is worse by 0.00233 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.00423 typical gaps.
Link before adjusting (r)-0.082p = 0.262 · 191 countries
After adjusting for national income-0.147p = 0.043 · likely range [-0.28, -0.00]
p, allowing for regions0.145standard error 0.088 · 7 regions
Check for luck (q)0.040across 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.
Environment score · typical gaps (standard deviations)link with income -0.20 · independent
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
-0.082
0.262
191
By rank (Spearman), not adjusted
-0.055
0.448
191
Standard (Pearson), adjusted for national income
-0.147
0.043
191
By rank (Spearman), adjusted for national income
-0.178
0.014
191
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 191 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: -0.066 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from -0.193 (without CAF) to -0.082 (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 (+0.065).
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
30
-0.11
Europe & Central Asia
48
-0.05
Latin America & Caribbean
36
-0.23
Middle East, North Africa, Afghanistan & Pakistan
22
-0.02
Sub-Saharan Africa
46
+0.02
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
-0.28
Middle third
63
-0.04
Richest third
64
+0.10
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
110
-0.04
Muslims
49
-0.25
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
-0.21
Never a European colony
21
-0.24
Spain
20
-0.22
United Kingdom
63
-0.13
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 = -0.124 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 0years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.
Not enough history inside each country to look at this over time. That needs countries measured for several years in a row, and at least one of these measures is measured too rarely.
The data
typical gaps (standard deviations)
per 100,000 people
Years
Micronesia, Fed. Sts. FSM
1.41
0
2024
Seychelles SYC
1.37
7.67
2024
Bhutan BTN
1.31
939
2024
Marshall Islands MHL
1.27
0
2024
Guinea-Bissau GNB
1.13
86.3
2024
Zambia ZMB
1.13
1.58
2024
Tanzania TZA
1.04
1.84
2024
Central African Republic CAF
0.95
13,009
2024
Congo, Rep. COG
0.909
223
2024
Belize BLZ
0.901
24.9
2024
Gabon GAB
0.838
37.3
2024
Congo, Dem. Rep. COD
0.825
970
2024
Sao Tome and Principe STP
0.815
2.12
2024
Montenegro MNE
0.725
120
2024
Slovenia SVN
0.723
0.802
2024
wdi UNHCR Refugee Data Finder; rate per population from Our World in Data
PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel
The average of 3 measures from 1 publisher. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Forest area, CO2 per capita, Protected land.
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 14,952 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Environment score and Refugees originating
This page shows that two measures go together. It does not show that Environment score changes Refugees originating, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Environment score or Refugees originating