placestats

Gini index vs. Refugees originating

Holds up after adjusting for income

Across 161 countries, Gini index and Refugees originating rise and fall together at r = -0.11 (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 = -0.17, q = 0.036, allowing for the many pairs tested). Caution: direction is not consistent across regions.

Comparing countries across the middle half of refugees originating, 2.12 to 147 per 100,000 people, gini index is better by 0.045 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0718 points.

Link before adjusting (r)-0.106p = 0.181 · 161 countries
After adjusting for national income-0.173p = 0.029 · likely range [-0.32, -0.02]
p, allowing for regions0.204standard error 0.121 · 7 regions
Check for luck (q)0.036across 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.

Gini index · index (0-100)link with income -0.34 · moderate
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

Gini index · index (0-100) →Refugees originating · per 100,000 people →23.859.1024,124Angola: 51.3 index (0-100), 33.1 per 100,000 peopleAlbania: 29.4 index (0-100), 784 per 100,000 peopleUnited Arab Emirates: 26.4 index (0-100), 2.37 per 100,000 peopleArgentina: 42.4 index (0-100), 1.02 per 100,000 peopleArmenia: 27.4 index (0-100), 536 per 100,000 peopleAustralia: 33.8 index (0-100), 0.116 per 100,000 peopleAustria: 31.2 index (0-100), 0.362 per 100,000 peopleBurundi: 37.5 index (0-100), 2,295 per 100,000 peopleBelgium: 26.8 index (0-100), 0.792 per 100,000 peopleBenin: 34.4 index (0-100), 7.36 per 100,000 peopleBurkina Faso: 37.4 index (0-100), 637 per 100,000 peopleBangladesh: 30.9 index (0-100), 16.4 per 100,000 peopleBulgaria: 39.5 index (0-100), 7.37 per 100,000 peopleBosnia and Herzegovina: 30.3 index (0-100), 848 per 100,000 peopleBelarus: 24.4 index (0-100), 195 per 100,000 peopleBelize: 39.9 index (0-100), 24.9 per 100,000 peopleBolivia: 40.9 index (0-100), 4.93 per 100,000 peopleBrazil: 50.3 index (0-100), 2.39 per 100,000 peopleBarbados: 34.1 index (0-100), 147 per 100,000 peopleBhutan: 28.5 index (0-100), 939 per 100,000 peopleBotswana: 54.9 index (0-100), 9.88 per 100,000 peopleCentral African Republic: 43 index (0-100), 13,009 per 100,000 peopleCanada: 31.5 index (0-100), 0.778 per 100,000 peopleSwitzerland: 33.8 index (0-100), 0.056 per 100,000 peopleChile: 43 index (0-100), 24.3 per 100,000 peopleChina: 36 index (0-100), 10.8 per 100,000 peopleCote d'Ivoire: 35.3 index (0-100), 92.2 per 100,000 peopleCameroon: 42.2 index (0-100), 377 per 100,000 peopleCongo, Dem. Rep.: 44.7 index (0-100), 970 per 100,000 peopleCongo, Rep.: 48.9 index (0-100), 223 per 100,000 peopleColombia: 54.4 index (0-100), 147 per 100,000 peopleComoros: 30.3 index (0-100), 268 per 100,000 peopleCabo Verde: 42.4 index (0-100), 2.67 per 100,000 peopleCosta Rica: 45.5 index (0-100), 6.16 per 100,000 peopleCyprus: 31.8 index (0-100), 0.736 per 100,000 peopleCzechia: 25.7 index (0-100), 9.85 per 100,000 peopleGermany: 33.7 index (0-100), 0.412 per 100,000 peopleDjibouti: 41.6 index (0-100), 176 per 100,000 peopleDenmark: 29.9 index (0-100), 0.268 per 100,000 peopleDominican Republic: 39 index (0-100), 9.45 per 100,000 peopleAlgeria: 27.6 index (0-100), 18.8 per 100,000 peopleEcuador: 45.9 index (0-100), 27.7 per 100,000 peopleEgypt, Arab Rep.: 28.5 index (0-100), 20.4 per 100,000 peopleSpain: 33.4 index (0-100), 0.363 per 100,000 peopleEstonia: 30.7 index (0-100), 9.26 per 100,000 peopleEthiopia: 31.1 index (0-100), 125 per 100,000 peopleFinland: 27.4 index (0-100), 0.089 per 100,000 peopleFiji: 30.7 index (0-100), 26.7 per 100,000 peopleFrance: 31.8 index (0-100), 0.209 per 100,000 peopleMicronesia, Fed. Sts.: 40.1 index (0-100), 0 per 100,000 peopleGabon: 38 index (0-100), 37.3 per 100,000 peopleUnited Kingdom: 32.4 index (0-100), 0.603 per 100,000 peopleGeorgia: 33.9 index (0-100), 435 per 100,000 peopleGhana: 43.5 index (0-100), 43.8 per 100,000 peopleGuinea: 29.6 index (0-100), 285 per 100,000 peopleGambia, The: 38.8 index (0-100), 295 per 100,000 peopleGuinea-Bissau: 33.4 index (0-100), 86.3 per 100,000 peopleEquatorial Guinea: 38.5 index (0-100), 22.5 per 100,000 peopleGreece: 33.4 index (0-100), 0.965 per 100,000 peopleGrenada: 43.8 index (0-100), 85.3 per 100,000 peopleGuatemala: 45.2 index (0-100), 197 per 100,000 peopleHonduras: 45.7 index (0-100), 933 per 100,000 peopleCroatia: 30.1 index (0-100), 462 per 100,000 peopleHaiti: 41.1 index (0-100), 1,259 per 100,000 peopleHungary: 30.6 index (0-100), 20.5 per 100,000 peopleIndonesia: 34.4 index (0-100), 3.24 per 100,000 peopleIndia: 25.5 index (0-100), 2.71 per 100,000 peopleIreland: 29 index (0-100), 1.29 per 100,000 peopleIran, Islamic Rep.: 35.9 index (0-100), 173 per 100,000 peopleIraq: 29.8 index (0-100), 664 per 100,000 peopleIceland: 26.8 index (0-100), 0 per 100,000 peopleIsrael: 38.3 index (0-100), 13.9 per 100,000 peopleItaly: 34.3 index (0-100), 0.443 per 100,000 peopleJamaica: 39.9 index (0-100), 89.9 per 100,000 peopleJordan: 33.7 index (0-100), 43.2 per 100,000 peopleJapan: 32.3 index (0-100), 0.0444 per 100,000 peopleKazakhstan: 29.2 index (0-100), 20 per 100,000 peopleKenya: 38.5 index (0-100), 20.7 per 100,000 peopleKyrgyz Republic: 27.5 index (0-100), 47.3 per 100,000 peopleKiribati: 24.7 index (0-100), 3.72 per 100,000 peopleKorea, Rep.: 32.9 index (0-100), 0.275 per 100,000 peopleLao PDR: 34.7 index (0-100), 84.4 per 100,000 peopleLebanon: 35.5 index (0-100), 164 per 100,000 peopleLiberia: 35.3 index (0-100), 90.6 per 100,000 peopleSt. Lucia: 43.7 index (0-100), 89 per 100,000 peopleSri Lanka: 37.7 index (0-100), 636 per 100,000 peopleLesotho: 44.9 index (0-100), 1.07 per 100,000 peopleLithuania: 36 index (0-100), 3.88 per 100,000 peopleLuxembourg: 33.6 index (0-100), 0.743 per 100,000 peopleLatvia: 34 index (0-100), 9.56 per 100,000 peopleMorocco: 39.5 index (0-100), 27.9 per 100,000 peopleMoldova: 26.8 index (0-100), 205 per 100,000 peopleMadagascar: 36.8 index (0-100), 1.89 per 100,000 peopleMaldives: 29.3 index (0-100), 14.4 per 100,000 peopleMexico: 42.6 index (0-100), 30 per 100,000 peopleMarshall Islands: 35.5 index (0-100), 0 per 100,000 peopleNorth Macedonia: 33.5 index (0-100), 110 per 100,000 peopleMali: 35.7 index (0-100), 1,446 per 100,000 peopleMalta: 31.8 index (0-100), 1.85 per 100,000 peopleMyanmar: 30.7 index (0-100), 2,427 per 100,000 peopleMontenegro: 34.3 index (0-100), 120 per 100,000 peopleMongolia: 31.4 index (0-100), 72 per 100,000 peopleMozambique: 49.6 index (0-100), 0.329 per 100,000 peopleMauritania: 32 index (0-100), 737 per 100,000 peopleMauritius: 36.8 index (0-100), 20.7 per 100,000 peopleMalawi: 38.5 index (0-100), 2.63 per 100,000 peopleMalaysia: 40.7 index (0-100), 3.4 per 100,000 peopleNamibia: 59.1 index (0-100), 21.3 per 100,000 peopleNiger: 32.9 index (0-100), 163 per 100,000 peopleNigeria: 33.9 index (0-100), 201 per 100,000 peopleNicaragua: 46.2 index (0-100), 434 per 100,000 peopleNetherlands: 25.7 index (0-100), 0.746 per 100,000 peopleNorway: 26.5 index (0-100), 0.395 per 100,000 peopleNepal: 30 index (0-100), 26.4 per 100,000 peopleNaoero: 32.4 index (0-100), 41.8 per 100,000 peoplePakistan: 33.5 index (0-100), 34.3 per 100,000 peoplePanama: 49.7 index (0-100), 7.37 per 100,000 peoplePeru: 40.1 index (0-100), 18.9 per 100,000 peoplePhilippines: 39.3 index (0-100), 0.678 per 100,000 peoplePoland: 28.5 index (0-100), 3.96 per 100,000 peoplePortugal: 33.9 index (0-100), 1.06 per 100,000 peopleParaguay: 44.2 index (0-100), 2.45 per 100,000 peopleWest Bank and Gaza: 36.4 index (0-100), 795 per 100,000 peopleQatar: 35.1 index (0-100), 2.13 per 100,000 peopleRomania: 29.8 index (0-100), 15.4 per 100,000 peopleRussian Federation: 33 index (0-100), 66.9 per 100,000 peopleRwanda: 39.4 index (0-100), 1,747 per 100,000 peopleSudan: 34.2 index (0-100), 4,151 per 100,000 peopleSenegal: 36.2 index (0-100), 70 per 100,000 peopleSolomon Islands: 37.1 index (0-100), 5.37 per 100,000 peopleSierra Leone: 35.7 index (0-100), 93.1 per 100,000 peopleEl Salvador: 39.8 index (0-100), 1,132 per 100,000 peopleSao Tome and Principe: 40.7 index (0-100), 2.12 per 100,000 peopleSuriname: 39.2 index (0-100), 7.88 per 100,000 peopleSlovak Republic: 23.8 index (0-100), 12.1 per 100,000 peopleSlovenia: 24.7 index (0-100), 0.802 per 100,000 peopleSweden: 29.3 index (0-100), 0.924 per 100,000 peopleEswatini: 54.6 index (0-100), 12.1 per 100,000 peopleSeychelles: 32.1 index (0-100), 7.67 per 100,000 peopleSyrian Arab Republic: 26.4 index (0-100), 24,124 per 100,000 peopleChad: 37.4 index (0-100), 72 per 100,000 peopleTogo: 37.9 index (0-100), 151 per 100,000 peopleThailand: 33.3 index (0-100), 0.419 per 100,000 peopleTajikistan: 36.1 index (0-100), 38.2 per 100,000 peopleTimor-Leste: 28.7 index (0-100), 0.357 per 100,000 peopleTonga: 27.1 index (0-100), 40.3 per 100,000 peopleTunisia: 33.7 index (0-100), 29.3 per 100,000 peopleTurkiye: 43.7 index (0-100), 160 per 100,000 peopleTuvalu: 39.1 index (0-100), 0 per 100,000 peopleTanzania: 40.5 index (0-100), 1.84 per 100,000 peopleUganda: 42.7 index (0-100), 20.7 per 100,000 peopleUkraine: 25.6 index (0-100), 13,524 per 100,000 peopleUruguay: 40 index (0-100), 3.87 per 100,000 peopleUnited States: 41.8 index (0-100), 1.16 per 100,000 peopleUzbekistan: 32.7 index (0-100), 14.2 per 100,000 peopleViet Nam: 36.1 index (0-100), 19.8 per 100,000 peopleVanuatu: 32.3 index (0-100), 1.53 per 100,000 peopleSamoa: 38.7 index (0-100), 3.67 per 100,000 peopleSouth Africa: 54.1 index (0-100), 1.83 per 100,000 peopleZambia: 51.5 index (0-100), 1.58 per 100,000 peopleZimbabwe: 50.3 index (0-100), 48 per 100,000 peopleBWACAFKIRNAMSVKSVNSWZSYRUKR

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.1060.181161
By rank (Spearman), not adjusted+0.0900.257161
Standard (Pearson), adjusted for national income-0.1730.029161
By rank (Spearman), adjusted for national income-0.0840.291161

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 161 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: -0.067 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.200 (without CAF) to -0.107 (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).

Fragile: this link may not hold up.
  • 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.

nr
East Asia & Pacific23-0.17
Europe & Central Asia45-0.22
Latin America & Caribbean24-0.01
Middle East, North Africa, Afghanistan & Pakistan16-0.48
Sub-Saharan Africa45+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.

nr
Poorest third54-0.18
Middle third53-0.24
Richest third54-0.16

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.

nr
Christians102-0.15
Muslims39-0.31

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.

nr
France24-0.27
Never a European colony16-0.10
Spain20+0.17
United Kingdom48-0.21

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 = -0.071 after dropping 30 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 = -0.049, 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 gini index moved did not tend to see their refugees originating move with it.

Across countries (adjusted)-0.173for comparison
Within countries-0.020each country vs itself
…and vs the same year elsewhere-0.049q = 0.422 · 118 countries
Year-on-year changes+0.018q = 0.759

1,989 country-years (one country in one year), 118 countries, 1990–2024, about 17 years each on average. Share of the variation that happens within countries over time: 56% for Gini index, 13% 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

0.10−0.1-100+10years Refugees originating trails Gini index →lag -10: r = 0.060 (n = 1,492)lag -9: r = 0.055 (n = 1,555)lag -8: r = 0.047 (n = 1,614)lag -7: r = 0.032 (n = 1,663)lag -6: r = -0.016 (n = 1,735)lag -5: r = -0.026 (n = 1,767)lag -4: r = -0.043 (n = 1,818)lag -3: r = -0.043 (n = 1,856)lag -2: r = -0.047 (n = 1,906)lag -1: r = -0.045 (n = 1,949)lag +0: r = -0.049 (n = 1,989)lag +1: r = -0.063 (n = 1,980)lag +2: r = -0.045 (n = 1,933)lag +3: r = -0.009 (n = 1,861)lag +4: r = -0.021 (n = 1,775)lag +5: r = -0.027 (n = 1,705)lag +6: r = -0.042 (n = 1,631)lag +7: r = -0.046 (n = 1,540)lag +8: r = -0.057 (n = 1,473)lag +9: r = -0.066 (n = 1,395)lag +10: r = -0.075 (n = 1,308)

Same year (lag 0): -0.049. 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


index (0-100)

per 100,000 people
Years
Namibia NAM59.121.32015, 2024
Botswana BWA54.99.882015, 2024
Eswatini SWZ54.612.12016, 2024
Colombia COL54.41472024
South Africa ZAF54.11.832022, 2024
Zambia ZMB51.51.582022, 2024
Angola AGO51.333.12018, 2024
Zimbabwe ZWE50.3482019, 2024
Brazil BRA50.32.392024
Panama PAN49.77.372024
Mozambique MOZ49.60.3292022, 2024
Congo, Rep. COG48.92232011, 2024
Nicaragua NIC46.24342014, 2024
Ecuador ECU45.927.72025, 2024
Honduras HND45.79332024

World Bank, World Development Indicators
UNHCR Refugee Data Finder; rate per population from Our World in Data

Sources

Gini index

Gini index

World Bank · CC BY 4.0 · updated quarterly

Sparse and uneven: most countries report only every few years, and coverage is thinnest where inequality is highest. Be wary of comparisons that match Gini with other measures year by year.

Refugees originating

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 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 Gini index and Refugees originating

This page shows that two measures go together. It does not show that Gini index changes Refugees originating, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Gini index or Refugees originating