placestats

African ancestry vs. Out of school, primary

Holds up 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 151 countries, African ancestry and Out of school, primary rise and fall together at r = +0.56 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.33 (q = 0.011, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak positive link remains. Caution: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of african ancestry, 0% to 91.7% of population, out of school, primary is worse by 13.7% of primary-age children at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 9.74% of primary-age children.

Link before adjusting (r)+0.564p = 5.0e-14 · 151 countries
After adjusting for national income+0.330p = 3.8e-5 · likely range [+0.18, +0.47]
p, allowing for regions0.000standard error 0.047 · 7 regions
Check for luck (q)0.011across 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.

African ancestry · % of populationlink with income -0.59 · moderate
Out of school, primary · % of primary-age childrenlink with income -0.45 · moderate

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

Every country as a dot

African ancestry · % of population →Out of school, primary · % of primary-age children →0%100%0.00387%65.6%Angola: 98% of population, 36.8% of primary-age childrenAlbania: 0% of population, 0.488% of primary-age childrenUnited Arab Emirates: 0% of population, 0.00387% of primary-age childrenArgentina: 2% of population, 0.735% of primary-age childrenArmenia: 0% of population, 1.08% of primary-age childrenAustralia: 0% of population, 0.124% of primary-age childrenAustria: 0% of population, 1.43% of primary-age childrenAzerbaijan: 0% of population, 0.0266% of primary-age childrenBurundi: 100% of population, 26.5% of primary-age childrenBelgium: 0% of population, 1.66% of primary-age childrenBenin: 100% of population, 9.61% of primary-age childrenBurkina Faso: 100% of population, 34.3% of primary-age childrenBangladesh: 0% of population, 5.86% of primary-age childrenBulgaria: 0% of population, 5.9% of primary-age childrenBahrain: 0% of population, 4.75% of primary-age childrenBosnia and Herzegovina: 0% of population, 2.1% of primary-age childrenBelarus: 0% of population, 4.49% of primary-age childrenBelize: 17.4% of population, 10.7% of primary-age childrenBolivia: 0.907% of population, 9.25% of primary-age childrenBrazil: 15.7% of population, 2.19% of primary-age childrenBhutan: 0% of population, 10.5% of primary-age childrenBotswana: 98.5% of population, 0.535% of primary-age childrenCentral African Republic: 99.4% of population, 37.9% of primary-age childrenCanada: 1.53% of population, 4.99% of primary-age childrenSwitzerland: 0% of population, 0.143% of primary-age childrenChile: 1.4% of population, 2.12% of primary-age childrenCote d'Ivoire: 99.3% of population, 12.6% of primary-age childrenCameroon: 100% of population, 3.76% of primary-age childrenCongo, Rep.: 100% of population, 17.1% of primary-age childrenColombia: 17.3% of population, 7.32% of primary-age childrenComoros: 100% of population, 20.6% of primary-age childrenCabo Verde: 58.6% of population, 41.8% of primary-age childrenCosta Rica: 8.91% of population, 4.49% of primary-age childrenCyprus: 0% of population, 0.425% of primary-age childrenCzechia: 0% of population, 0.809% of primary-age childrenGermany: 0% of population, 0.274% of primary-age childrenDenmark: 0% of population, 0.893% of primary-age childrenDominican Republic: 44.4% of population, 4.93% of primary-age childrenAlgeria: 0% of population, 1.57% of primary-age childrenEcuador: 6.97% of population, 4.72% of primary-age childrenEgypt, Arab Rep.: 5.5% of population, 3.51% of primary-age childrenSpain: 0% of population, 1.24% of primary-age childrenEstonia: 0% of population, 3.39% of primary-age childrenEthiopia: 100% of population, 22.5% of primary-age childrenFinland: 0% of population, 1.77% of primary-age childrenFiji: 0% of population, 2.39% of primary-age childrenFrance: 0% of population, 0.204% of primary-age childrenGabon: 99% of population, 28.8% of primary-age childrenUnited Kingdom: 1.8% of population, 0.0698% of primary-age childrenGeorgia: 0% of population, 6.17% of primary-age childrenGhana: 100% of population, 4.77% of primary-age childrenGuinea: 100% of population, 14.7% of primary-age childrenGambia, The: 99.5% of population, 16.9% of primary-age childrenGuinea-Bissau: 96.5% of population, 30.5% of primary-age childrenEquatorial Guinea: 94.3% of population, 65.6% of primary-age childrenGreece: 0% of population, 0.11% of primary-age childrenGuatemala: 4.14% of population, 8.43% of primary-age childrenGuyana: 39% of population, 18% of primary-age childrenHong Kong SAR, China: 0% of population, 1.4% of primary-age childrenHonduras: 2% of population, 26.6% of primary-age childrenCroatia: 0% of population, 1.81% of primary-age childrenHungary: 0% of population, 2.81% of primary-age childrenIndonesia: 0% of population, 0.877% of primary-age childrenIndia: 0% of population, 0.119% of primary-age childrenIreland: 0% of population, 1.81% of primary-age childrenIran, Islamic Rep.: 0% of population, 0.103% of primary-age childrenIsrael: 0.982% of population, 2.66% of primary-age childrenItaly: 0% of population, 2.06% of primary-age childrenJamaica: 89% of population, 4.34% of primary-age childrenJordan: 0% of population, 1.89% of primary-age childrenJapan: 0% of population, 0.0684% of primary-age childrenKazakhstan: 0% of population, 7.91% of primary-age childrenKenya: 100% of population, 32.9% of primary-age childrenKyrgyz Republic: 0% of population, 2.96% of primary-age childrenCambodia: 0% of population, 3.69% of primary-age childrenKorea, Rep.: 0% of population, 0.0557% of primary-age childrenKuwait: 0% of population, 7.47% of primary-age childrenLao PDR: 0% of population, 10.4% of primary-age childrenLebanon: 0% of population, 22.5% of primary-age childrenLiberia: 100% of population, 38.3% of primary-age childrenSri Lanka: 0% of population, 9.14% of primary-age childrenLesotho: 100% of population, 32.2% of primary-age childrenLithuania: 0% of population, 0.13% of primary-age childrenLuxembourg: 0% of population, 0.256% of primary-age childrenLatvia: 0% of population, 2.74% of primary-age childrenMorocco: 1% of population, 0.471% of primary-age childrenMoldova: 0% of population, 0.463% of primary-age childrenMadagascar: 99.4% of population, 3.4% of primary-age childrenMexico: 6.7% of population, 0.363% of primary-age childrenNorth Macedonia: 0% of population, 3.79% of primary-age childrenMali: 99.1% of population, 34% of primary-age childrenMalta: 0% of population, 2.64% of primary-age childrenMyanmar: 0% of population, 1.41% of primary-age childrenMongolia: 0% of population, 8.56% of primary-age childrenMozambique: 100% of population, 1% of primary-age childrenMauritania: 100% of population, 11.3% of primary-age childrenMauritius: 13% of population, 0.785% of primary-age childrenMalawi: 100% of population, 2.09% of primary-age childrenMalaysia: 0% of population, 12% of primary-age childrenNamibia: 89.2% of population, 0.865% of primary-age childrenNiger: 98.1% of population, 40.4% of primary-age childrenNigeria: 100% of population, 24.3% of primary-age childrenNicaragua: 9% of population, 6.66% of primary-age childrenNetherlands: 0.75% of population, 0.519% of primary-age childrenNorway: 0% of population, 1.38% of primary-age childrenNepal: 0% of population, 0.762% of primary-age childrenNew Zealand: 0% of population, 2.62% of primary-age childrenOman: 1.25% of population, 5.76% of primary-age childrenPakistan: 0% of population, 17.9% of primary-age childrenPanama: 13% of population, 7.7% of primary-age childrenPeru: 5.72% of population, 0.156% of primary-age childrenPhilippines: 0% of population, 11.6% of primary-age childrenPapua New Guinea: 0% of population, 4% of primary-age childrenPoland: 0% of population, 0.0917% of primary-age childrenPuerto Rico (US): 15.8% of population, 13.3% of primary-age childrenPortugal: 0.61% of population, 0.508% of primary-age childrenParaguay: 1% of population, 13.3% of primary-age childrenQatar: 15.1% of population, 4.62% of primary-age childrenRomania: 0% of population, 15.6% of primary-age childrenRussian Federation: 0% of population, 4.94% of primary-age childrenRwanda: 100% of population, 0.97% of primary-age childrenSaudi Arabia: 1.5% of population, 0.527% of primary-age childrenSudan: 98.8% of population, 43.8% of primary-age childrenSenegal: 98.2% of population, 24.5% of primary-age childrenSingapore: 0% of population, 0.212% of primary-age childrenSierra Leone: 100% of population, 0.888% of primary-age childrenEl Salvador: 0% of population, 8.66% of primary-age childrenSlovak Republic: 0% of population, 1.06% of primary-age childrenSlovenia: 0% of population, 1.45% of primary-age childrenSweden: 0% of population, 0.57% of primary-age childrenEswatini: 96.4% of population, 3.83% of primary-age childrenSyrian Arab Republic: 0% of population, 21.8% of primary-age childrenChad: 100% of population, 24.8% of primary-age childrenTogo: 100% of population, 0.639% of primary-age childrenThailand: 0% of population, 0.817% of primary-age childrenTajikistan: 0% of population, 4.15% of primary-age childrenTurkmenistan: 0% of population, 4.31% of primary-age childrenTimor-Leste: 0% of population, 6.88% of primary-age childrenTrinidad and Tobago: 46% of population, 7.16% of primary-age childrenTunisia: 0% of population, 1.09% of primary-age childrenTurkiye: 0% of population, 0.603% of primary-age childrenTanzania: 100% of population, 16.4% of primary-age childrenUganda: 100% of population, 4.12% of primary-age childrenUkraine: 0% of population, 12.9% of primary-age childrenUruguay: 4% of population, 0.0355% of primary-age childrenUnited States: 9.64% of population, 3.98% of primary-age childrenUzbekistan: 0% of population, 0.655% of primary-age childrenViet Nam: 0% of population, 1.73% of primary-age childrenSouth Africa: 78.7% of population, 6.06% of primary-age childrenZambia: 99% of population, 3.51% of primary-age childrenZimbabwe: 99% of population, 10.5% of primary-age childrenAREAZEBWACPVGNQHNDKORNERSDNSLETGO

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5645.0e-14151
By rank (Spearman), not adjusted+0.4671.6e-9151
Standard (Pearson), adjusted for national income+0.3303.8e-5151
By rank (Spearman), adjusted for national income+0.2300.005151

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 151 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: +0.234 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.290 (without GNQ) to +0.351 (without HND). 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: GNQ (-0.039).

Fragile: this link may not hold up.
  • correlation moves sharply once outliers are trimmed
  • direction is not consistent across regions
  • much weaker within regions than across them (largely a between-region difference)

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
Europe & Central Asia45-0.13
Latin America & Caribbean22+0.01
Middle East, North Africa, Afghanistan & Pakistan17+0.13
Sub-Saharan Africa42+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 third51+0.24
Middle third50+0.40
Richest third50+0.73

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+0.25
Muslims41+0.43

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+0.16
Never a European colony19+0.84
Spain19+0.85
United Kingdom43+0.20

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 = +0.174 after dropping 15 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 primary-age children		Years
Uganda UGA100%4.12%2000, 2013
Tanzania TZA100%16.4%2000, 2024
Togo TGO100%0.639%2000, 2024
Chad TCD100%24.8%2000, 2024
Sierra Leone SLE100%0.888%2000, 2015
Rwanda RWA100%0.97%2000, 2024
Nigeria NGA100%24.3%2000, 2023
Malawi MWI100%2.09%2000, 2022
Mauritania MRT100%11.3%2000, 2024
Mozambique MOZ100%1%2000, 2022
Lesotho LSO100%32.2%2000, 2024
Liberia LBR100%38.3%2000, 2022
Kenya KEN100%32.9%2000, 2022
Guinea GIN100%14.7%2000, 2020
Ghana GHA100%4.77%2000, 2024

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

African ancestry

Sub-Saharan African 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 sub-Saharan Africa. 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.

Out of school, primary

Children out of school (% of primary school age)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

Children of primary-school age not enrolled at any level. Treated as measuring the same thing as gross primary enrolment, which is on the site. They are two ways of asking whether children are in school, so their agreement is not a finding.

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 African ancestry and Out of school, primary

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

More links with African ancestry or Out of school, primary