placestats

European ancestry vs. Primary completion

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 145 countries, European ancestry and Primary completion rise and fall together at r = +0.55 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.03, which could easily be chance (q = 0.89, 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: sign flips when a single country is removed.

Comparing countries across the middle half of european ancestry, 0% to 99% of population, primary completion is better by 21.7% of children at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1.04% of children.

Link before adjusting (r)+0.546p = 1.2e-12 · 145 countries
After adjusting for national income+0.031p = 0.713 · likely range [-0.13, +0.19]
p, allowing for regions0.808standard error 0.122 · 7 regions
Check for luck (q)0.890across 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
Primary completion · % of childrenlink with income +0.83 · 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 →Primary completion · % of children →0%100%28.8%100%Afghanistan: 12% of population, 55.4% of childrenAngola: 2% of population, 65.2% of childrenAlbania: 100% of population, 97.4% of childrenArgentina: 90% of population, 96.7% of childrenArmenia: 100% of population, 99.5% of childrenAustralia: 89.6% of population, 99.5% of childrenAustria: 100% of population, 100% of childrenAzerbaijan: 99% of population, 98.4% of childrenBurundi: 0% of population, 60.5% of childrenBelgium: 98.4% of population, 98.9% of childrenBenin: 0% of population, 70.1% of childrenBurkina Faso: 0% of population, 72.2% of childrenBangladesh: 0% of population, 90.8% of childrenBulgaria: 100% of population, 99.1% of childrenBosnia and Herzegovina: 100% of population, 99.8% of childrenBelarus: 100% of population, 99.8% of childrenBelize: 40% of population, 90.2% of childrenBolivia: 26.7% of population, 98.5% of childrenBrazil: 74.4% of population, 93% of childrenBhutan: 0% of population, 93.6% of childrenBotswana: 1.5% of population, 99% of childrenCentral African Republic: 0.6% of population, 30.8% of childrenCanada: 85.6% of population, 99.9% of childrenSwitzerland: 99.5% of population, 99.8% of childrenChile: 59.3% of population, 97.4% of childrenChina: 0% of population, 99% of childrenCote d'Ivoire: 0% of population, 78.8% of childrenCameroon: 0% of population, 77.8% of childrenCongo, Dem. Rep.: 0.46% of population, 68.4% of childrenCongo, Rep.: 0% of population, 93.9% of childrenColombia: 45.6% of population, 95.5% of childrenComoros: 0% of population, 86.1% of childrenCosta Rica: 60.4% of population, 98.9% of childrenCyprus: 100% of population, 99% of childrenCzechia: 100% of population, 99.9% of childrenGermany: 100% of population, 100% of childrenDenmark: 100% of population, 99.9% of childrenDominican Republic: 52% of population, 96.1% of childrenAlgeria: 0% of population, 96.5% of childrenEcuador: 32% of population, 99.5% of childrenEgypt, Arab Rep.: 0% of population, 96.3% of childrenSpain: 99.7% of population, 98.6% of childrenEstonia: 100% of population, 99.5% of childrenEthiopia: 0% of population, 64.6% of childrenFinland: 100% of population, 99.7% of childrenFiji: 2.2% of population, 98.9% of childrenFrance: 94.2% of population, 99.6% of childrenGabon: 1% of population, 74.3% of childrenUnited Kingdom: 94.6% of population, 99.9% of childrenGeorgia: 100% of population, 99.8% of childrenGhana: 0% of population, 79.1% of childrenGuinea: 0% of population, 61% of childrenGambia, The: 0.5% of population, 74.8% of childrenGuinea-Bissau: 3% of population, 30.5% of childrenEquatorial Guinea: 5.75% of population, 73.6% of childrenGreece: 100% of population, 99.3% of childrenGuatemala: 22% of population, 87% of childrenGuyana: 1.3% of population, 99.2% of childrenHonduras: 46% of population, 89.6% of childrenCroatia: 100% of population, 99.8% of childrenHaiti: 2.5% of population, 50.5% of childrenHungary: 100% of population, 99.2% of childrenIndonesia: 0% of population, 98.9% of childrenIndia: 0% of population, 96.5% of childrenIreland: 100% of population, 99.8% of childrenIran, Islamic Rep.: 0% of population, 96.7% of childrenIraq: 5.6% of population, 83.3% of childrenIsrael: 35.6% of population, 100% of childrenItaly: 99.8% of population, 99.9% of childrenJamaica: 8% of population, 99.4% of childrenJordan: 2% of population, 98.5% of childrenJapan: 0% of population, 100% of childrenKazakhstan: 97.9% of population, 99.7% of childrenKenya: 0% of population, 88.4% of childrenKyrgyz Republic: 98% of population, 99.4% of childrenCambodia: 0% of population, 82.7% of childrenKorea, Rep.: 0% of population, 100% of childrenLao PDR: 0% of population, 70.1% of childrenLiberia: 0% of population, 29.8% of childrenLesotho: 0% of population, 79.8% of childrenLithuania: 100% of population, 99.7% of childrenLuxembourg: 99.2% of population, 98.6% of childrenLatvia: 100% of population, 99.6% of childrenMorocco: 8% of population, 84.6% of childrenMoldova: 100% of population, 98.8% of childrenMadagascar: 0.6% of population, 54% of childrenMexico: 30% of population, 98.2% of childrenNorth Macedonia: 100% of population, 99.5% of childrenMali: 0% of population, 50% of childrenMalta: 4.2% of population, 98.1% of childrenMyanmar: 0% of population, 89.8% of childrenMongolia: 1.8% of population, 99.7% of childrenMozambique: 0% of population, 53.5% of childrenMauritania: 0% of population, 51.8% of childrenMauritius: 16% of population, 99.9% of childrenMalawi: 0% of population, 57.7% of childrenMalaysia: 0% of population, 99.8% of childrenNamibia: 10.8% of population, 86.3% of childrenNiger: 0% of population, 77.5% of childrenNigeria: 0% of population, 76.8% of childrenNicaragua: 51% of population, 77.7% of childrenNetherlands: 96.6% of population, 99.8% of childrenNorway: 100% of population, 99.8% of childrenNepal: 0% of population, 90.8% of childrenPakistan: 0% of population, 59.5% of childrenPanama: 45.2% of population, 95.1% of childrenPeru: 28% of population, 98.1% of childrenPhilippines: 0% of population, 96.2% of childrenPapua New Guinea: 0% of population, 66% of childrenPoland: 100% of population, 99.7% of childrenPortugal: 98.4% of population, 99.5% of childrenParaguay: 52.9% of population, 94.9% of childrenQatar: 0.9% of population, 100% of childrenRomania: 100% of population, 99.1% of childrenRussian Federation: 100% of population, 99.7% of childrenRwanda: 0% of population, 71.9% of childrenSudan: 0% of population, 75.6% of childrenSenegal: 1.3% of population, 65.7% of childrenSierra Leone: 0% of population, 68.8% of childrenEl Salvador: 50% of population, 93.7% of childrenSomalia, Fed. Rep.: 0% of population, 28.8% of childrenSlovak Republic: 100% of population, 99.8% of childrenSlovenia: 100% of population, 99.5% of childrenSweden: 99.3% of population, 100% of childrenEswatini: 2.8% of population, 82.5% of childrenSyrian Arab Republic: 5.2% of population, 98.1% of childrenChad: 0% of population, 37.8% of childrenTogo: 0% of population, 87.8% of childrenThailand: 0% of population, 99.2% of childrenTajikistan: 100% of population, 98.8% of childrenTurkmenistan: 100% of population, 99.8% of childrenTimor-Leste: 0% of population, 82.1% of childrenTrinidad and Tobago: 7.1% of population, 98% of childrenTunisia: 0% of population, 96.9% of childrenTurkiye: 99.3% of population, 98% of childrenTanzania: 0% of population, 75.7% of childrenUganda: 0% of population, 30.4% of childrenUkraine: 100% of population, 99.6% of childrenUruguay: 92% of population, 97.9% of childrenUnited States: 76.2% of population, 100% of childrenUzbekistan: 99% of population, 99.8% of childrenViet Nam: 0% of population, 98.6% of childrenSouth Africa: 18% of population, 97.1% of childrenZambia: 1% of population, 67.4% of childrenZimbabwe: 1% of population, 86.9% of childrenAUTDEUDNKGNBJPNKORLBRMYSSOMUGA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5461.2e-12145
By rank (Spearman), not adjusted+0.6563.2e-19145
Standard (Pearson), adjusted for national income+0.0310.713145
By rank (Spearman), adjusted for national income+0.1940.020145

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 145 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: +0.515 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.009 (without TJK) to +0.045 (without CAF). 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: TJK (-0.040).

Fragile: this link may not hold up.
  • sign flips when a single country is removed
  • 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 & Pacific16-0.21
Europe & Central Asia45-0.05
Latin America & Caribbean22+0.11
Middle East, North Africa, Afghanistan & Pakistan13-0.12
Sub-Saharan Africa43+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.

nr
Poorest third49+0.22
Middle third48+0.15
Richest third48+0.14

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
Christians90-0.00
Muslims38+0.26

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
France23+0.17
Never a European colony19+0.40
Spain19+0.10
United Kingdom39-0.16

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 = +0.105 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
% of children		Years
Ukraine UKR100%99.6%2000, 2025
Turkmenistan TKM100%99.8%2000, 2025
Tajikistan TJK100%98.8%2000, 2025
Slovenia SVN100%99.5%2000, 2025
Slovak Republic SVK100%99.8%2000, 2025
Russian Federation RUS100%99.7%2000, 2025
Romania ROU100%99.1%2000, 2025
Poland POL100%99.7%2000, 2025
Norway NOR100%99.8%2000, 2025
North Macedonia MKD100%99.5%2000, 2025
Moldova MDA100%98.8%2000, 2025
Latvia LVA100%99.6%2000, 2025
Lithuania LTU100%99.7%2000, 2025
Ireland IRL100%99.8%2000, 2025
Hungary HUN100%99.2%2000, 2025

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).
UNESCO Institute for Statistics, SDG indicator 4.1.2 modelled estimates

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.

Primary completion

Primary completion rate, modelled estimate

UNESCO Institute for Statistics · via Our World in Data · CC BY 3.0 IGO · updated annual

The share of children who finish primary school. UNESCO estimates it from household surveys and uses a statistical model to fill in across years. It is not the World Bank's primary completion rate, which is a ratio built from school enrolment counts of children entering the last grade. This one asks whether the child actually finished.

How this was computed

Data used: most recent value in 2010-2025; values come from 2000–2025. 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 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 Primary completion

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

More links with European ancestry or Primary completion