placestats

European ancestry vs. Researchers

Fades after adjusting for income

A country is not a person, and ancestry is not destiny. Countries where more people have ancestors from one part of the world also tend to differ on the other measure, and that is all. It does notfollow that people with that ancestry are the people with the different score. Making that leap is called the ecological fallacy: reading a pattern across places as a fact about individual people. Ancestry also goes very closely with region and with history, including colonisation and the Atlantic slave trade, and with national income. So much of what looks like ancestry here is really those. That is what the adjusted figures and the region-by-region view are for. The shares are one estimate, for around the year 2000, of where people’s ancestors lived in 1500, not how anyone identifies.

Across 125 countries, European ancestry and Researchers rise and fall together at r = +0.52 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.18, which could easily be chance (q = 0.57, allowing for the many pairs tested, and allowing for countries in the same region being alike). So the first figure mostly shows richer countries differing from poorer ones, not a link between these two things. Caution: direction is not consistent across regions.

Comparing countries across the middle half of european ancestry, 0% to 99.3% of population, researchers is better by 2,806 per million people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 899 per million people.

Link before adjusting (r)+0.520p = 5.1e-10 · 125 countries
After adjusting for national income+0.185p = 0.040 · likely range [+0.01, +0.35]
p, allowing for regions0.373standard error 0.192 · 7 regions
Check for luck (q)0.569across 13,797 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.

European ancestry · % of populationlink with income +0.57 · moderate
Researchers · per million peoplelink with income +0.85 · proxy

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

European ancestry · % of population →Researchers · per million people →0%100%1.459,472Angola: 2% of population, 18.9 per million peopleAlbania: 100% of population, 429 per million peopleUnited Arab Emirates: 0% of population, 2,607 per million peopleArgentina: 90% of population, 1,313 per million peopleArmenia: 100% of population, 942 per million peopleAustralia: 89.6% of population, 4,569 per million peopleAustria: 100% of population, 6,634 per million peopleAzerbaijan: 99% of population, 1,663 per million peopleBurundi: 0% of population, 22.5 per million peopleBelgium: 98.4% of population, 5,990 per million peopleBurkina Faso: 0% of population, 46.6 per million peopleBulgaria: 100% of population, 2,401 per million peopleBahrain: 0% of population, 849 per million peopleBosnia and Herzegovina: 100% of population, 705 per million peopleBelarus: 100% of population, 1,568 per million peopleBolivia: 26.7% of population, 63.1 per million peopleBrazil: 74.4% of population, 903 per million peopleBhutan: 0% of population, 236 per million peopleBotswana: 1.5% of population, 180 per million peopleCanada: 85.6% of population, 5,624 per million peopleSwitzerland: 99.5% of population, 6,108 per million peopleChile: 59.3% of population, 707 per million peopleChina: 0% of population, 2,107 per million peopleCongo, Dem. Rep.: 0.46% of population, 10.1 per million peopleCongo, Rep.: 0% of population, 127 per million peopleColombia: 45.6% of population, 90.2 per million peopleCabo Verde: 41.4% of population, 125 per million peopleCosta Rica: 60.4% of population, 508 per million peopleCyprus: 100% of population, 1,686 per million peopleCzechia: 100% of population, 4,505 per million peopleGermany: 100% of population, 5,926 per million peopleDenmark: 100% of population, 8,838 per million peopleDominican Republic: 52% of population, 20 per million peopleAlgeria: 0% of population, 1,764 per million peopleEcuador: 32% of population, 400 per million peopleEgypt, Arab Rep.: 0% of population, 1,120 per million peopleSpain: 99.7% of population, 3,654 per million peopleEstonia: 100% of population, 4,800 per million peopleEthiopia: 0% of population, 89 per million peopleFinland: 100% of population, 8,315 per million peopleFrance: 94.2% of population, 5,369 per million peopleUnited Kingdom: 94.6% of population, 4,473 per million peopleGeorgia: 100% of population, 1,896 per million peopleGhana: 0% of population, 87.5 per million peopleGambia, The: 0.5% of population, 50.9 per million peopleGreece: 100% of population, 5,283 per million peopleGuatemala: 22% of population, 1.45 per million peopleHong Kong SAR, China: 0% of population, 5,874 per million peopleHonduras: 46% of population, 188 per million peopleCroatia: 100% of population, 2,440 per million peopleHungary: 100% of population, 4,567 per million peopleIndonesia: 0% of population, 395 per million peopleIndia: 0% of population, 259 per million peopleIreland: 100% of population, 5,753 per million peopleIran, Islamic Rep.: 0% of population, 2,240 per million peopleIraq: 5.6% of population, 164 per million peopleItaly: 99.8% of population, 2,855 per million peopleJordan: 2% of population, 576 per million peopleJapan: 0% of population, 5,609 per million peopleKazakhstan: 97.9% of population, 758 per million peopleKenya: 0% of population, 384 per million peopleCambodia: 0% of population, 30.4 per million peopleKorea, Rep.: 0% of population, 9,472 per million peopleKuwait: 0% of population, 145 per million peopleSri Lanka: 0% of population, 94.5 per million peopleLesotho: 0% of population, 32.2 per million peopleLithuania: 100% of population, 3,704 per million peopleLuxembourg: 99.2% of population, 5,359 per million peopleLatvia: 100% of population, 2,191 per million peopleMorocco: 8% of population, 1,083 per million peopleMoldova: 100% of population, 650 per million peopleMadagascar: 0.6% of population, 32.9 per million peopleMexico: 30% of population, 438 per million peopleNorth Macedonia: 100% of population, 888 per million peopleMali: 0% of population, 26 per million peopleMalta: 4.2% of population, 2,355 per million peopleMyanmar: 0% of population, 28 per million peopleMongolia: 1.8% of population, 535 per million peopleMozambique: 0% of population, 44.4 per million peopleMauritius: 16% of population, 689 per million peopleMalawi: 0% of population, 25.2 per million peopleMalaysia: 0% of population, 1,218 per million peopleNamibia: 10.8% of population, 225 per million peopleNiger: 0% of population, 26.9 per million peopleNigeria: 0% of population, 22.1 per million peopleNetherlands: 96.6% of population, 6,563 per million peopleNorway: 100% of population, 7,451 per million peopleNew Zealand: 80.6% of population, 5,435 per million peopleOman: 0% of population, 739 per million peoplePakistan: 0% of population, 474 per million peoplePanama: 45.2% of population, 250 per million peoplePhilippines: 0% of population, 320 per million peoplePapua New Guinea: 0% of population, 33.2 per million peoplePoland: 100% of population, 3,675 per million peoplePuerto Rico (US): 66.3% of population, 332 per million peoplePortugal: 98.4% of population, 5,983 per million peopleParaguay: 52.9% of population, 139 per million peopleQatar: 0.9% of population, 948 per million peopleRomania: 100% of population, 1,082 per million peopleRussian Federation: 100% of population, 2,639 per million peopleRwanda: 0% of population, 133 per million peopleSaudi Arabia: 0% of population, 1,235 per million peopleSenegal: 1.3% of population, 572 per million peopleSingapore: 0.5% of population, 8,782 per million peopleEl Salvador: 50% of population, 55.5 per million peopleSlovak Republic: 100% of population, 3,507 per million peopleSlovenia: 100% of population, 5,616 per million peopleSweden: 99.3% of population, 8,911 per million peopleEswatini: 2.8% of population, 138 per million peopleSyrian Arab Republic: 5.2% of population, 140 per million peopleChad: 0% of population, 56.7 per million peopleTogo: 0% of population, 57.8 per million peopleThailand: 0% of population, 1,592 per million peopleTrinidad and Tobago: 7.1% of population, 493 per million peopleTunisia: 0% of population, 1,668 per million peopleTurkiye: 99.3% of population, 2,645 per million peopleTanzania: 0% of population, 19.3 per million peopleUganda: 0% of population, 81.3 per million peopleUkraine: 100% of population, 586 per million peopleUruguay: 92% of population, 938 per million peopleUnited States: 76.2% of population, 4,937 per million peopleUzbekistan: 99% of population, 640 per million peopleViet Nam: 0% of population, 836 per million peopleSouth Africa: 18% of population, 444 per million peopleZimbabwe: 1% of population, 95.1 per million peopleALBBDIDNKFINHKGKORMDANGASGPSWETZAUKR

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5205.1e-10125
By rank (Spearman), not adjusted+0.5551.9e-11125
Standard (Pearson), adjusted for national income+0.1850.040125
By rank (Spearman), adjusted for national income+0.1880.036125

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 125 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: +0.335 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.151 (without QAT) to +0.251 (without KOR). 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: KOR (+0.067).

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 & Pacific16-0.07
Europe & Central Asia42-0.08
Latin America & Caribbean17+0.59
Middle East, North Africa, Afghanistan & Pakistan16-0.10
Sub-Saharan Africa29+0.08

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 third42-0.05
Middle third41+0.15
Richest third42+0.33

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
Christians77+0.27
Muslims30+0.09

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
France13-0.14
Never a European colony15-0.29
Spain16+0.25
United Kingdom35+0.44

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 = +0.304 after dropping 6 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


% of population
per million people		Years
Ukraine UKR100%5862000, 2022
Slovenia SVN100%5,6162000, 2023
Slovak Republic SVK100%3,5072000, 2023
Russian Federation RUS100%2,6392000, 2024
Romania ROU100%1,0822000, 2023
Poland POL100%3,6752000, 2023
Norway NOR100%7,4512000, 2023
North Macedonia MKD100%8882000, 2024
Moldova MDA100%6502000, 2024
Latvia LVA100%2,1912000, 2023
Lithuania LTU100%3,7042000, 2023
Ireland IRL100%5,7532000, 2023
Hungary HUN100%4,5672000, 2023
Croatia HRV100%2,4402000, 2023
Greece GRC100%5,2832000, 2023

Putterman, L. and Weil, D. N. (2010), 'Post-1500 Population Flows and the Long-Run Determinants of Economic Growth and Inequality', Quarterly Journal of Economics 125(4); World Migration Matrix version 1.1 (2009).
World Bank, World Development Indicators

Sources

European ancestry

European and Central Asian ancestry (share of the population)

Louis Putterman and David N. Weil, Brown University · No licence stated; used with citation · updated one edition (version 1.1, 2009)

The estimated share of today's population whose ancestors in the year 1500 lived in Europe or Central Asia (the World Bank's Europe & Central Asia region, which includes Turkey, the Caucasus and Central Asia). This is the closest thing to race shares that can be compared across countries: national censuses each use their own race and ethnic categories, and most countries record none. It is about where people's ancestors lived, not how anyone identifies, and it is one estimate for around the year 2000, built from history, migration records and genetic studies. Every country's six ancestry shares add up to 100%, so they are linked to each other by arithmetic. No "better" direction is set.

Researchers

Researchers in R&D (per million people)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

Researchers counted as full-time equivalents (two half-time researchers count as one), from national research surveys that many countries run only now and then. So coverage is thin outside the OECD.

How this was computed

Data used: most recent value in 2010-2025; values come from 2000–2024. 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 13,797 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore European ancestry and Researchers

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

More links with European ancestry or Researchers