placestats

African ancestry vs. Birth registration

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, African ancestry and Birth registration rise and fall together at r = -0.64 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.28, which could easily be chance (q = 0.17, 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 african ancestry, 0% to 98% of population, birth registration is worse by 32.5% of children under 5 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 14.4% of children under 5.

Link before adjusting (r)-0.636p = 8.1e-18 · 145 countries
After adjusting for national income-0.276p = 0.001 · likely range [-0.42, -0.12]
p, allowing for regions0.047standard error 0.111 · 7 regions
Check for luck (q)0.170across 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
Birth registration · % of children under 5link with income +0.87 · proxy

“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 →Birth registration · % of children under 5 →0%100%2.7%100%Afghanistan: 0% of population, 42.3% of children under 5Angola: 98% of population, 25% of children under 5Albania: 0% of population, 98.4% of children under 5United Arab Emirates: 0% of population, 100% of children under 5Argentina: 2% of population, 99.7% of children under 5Armenia: 0% of population, 99.3% of children under 5Australia: 0% of population, 100% of children under 5Austria: 0% of population, 100% of children under 5Burundi: 100% of population, 83.5% of children under 5Belgium: 0% of population, 100% of children under 5Benin: 100% of population, 85.6% of children under 5Burkina Faso: 100% of population, 76.9% of children under 5Bangladesh: 0% of population, 56% of children under 5Bulgaria: 0% of population, 100% of children under 5Bahrain: 0% of population, 100% of children under 5Belarus: 0% of population, 100% of children under 5Belize: 17.4% of population, 95.7% of children under 5Bolivia: 0.907% of population, 91.9% of children under 5Brazil: 15.7% of population, 96.4% of children under 5Bhutan: 0% of population, 99.9% of children under 5Botswana: 98.5% of population, 87.5% of children under 5Central African Republic: 99.4% of population, 44.8% of children under 5Canada: 1.53% of population, 100% of children under 5Switzerland: 0% of population, 100% of children under 5Chile: 1.4% of population, 99.4% of children under 5Cote d'Ivoire: 99.3% of population, 71.7% of children under 5Cameroon: 100% of population, 61.9% of children under 5Congo, Dem. Rep.: 99.5% of population, 40.1% of children under 5Congo, Rep.: 100% of population, 95.9% of children under 5Colombia: 17.3% of population, 96.8% of children under 5Comoros: 100% of population, 87.3% of children under 5Cabo Verde: 58.6% of population, 91.4% of children under 5Costa Rica: 8.91% of population, 99.6% of children under 5Cyprus: 0% of population, 100% of children under 5Czechia: 0% of population, 100% of children under 5Germany: 0% of population, 100% of children under 5Denmark: 0% of population, 100% of children under 5Dominican Republic: 44.4% of population, 92.2% of children under 5Algeria: 0% of population, 99.6% of children under 5Ecuador: 6.97% of population, 87.2% of children under 5Egypt, Arab Rep.: 5.5% of population, 99.4% of children under 5Spain: 0% of population, 100% of children under 5Estonia: 0% of population, 100% of children under 5Ethiopia: 100% of population, 2.7% of children under 5Finland: 0% of population, 100% of children under 5Fiji: 0% of population, 86.6% of children under 5France: 0% of population, 100% of children under 5Gabon: 99% of population, 89.6% of children under 5United Kingdom: 1.8% of population, 100% of children under 5Georgia: 0% of population, 98.5% of children under 5Ghana: 100% of population, 70.6% of children under 5Guinea: 100% of population, 62% of children under 5Gambia, The: 99.5% of population, 59% of children under 5Guinea-Bissau: 96.5% of population, 46% of children under 5Equatorial Guinea: 94.3% of population, 53.5% of children under 5Greece: 0% of population, 100% of children under 5Guatemala: 4.14% of population, 96.4% of children under 5Guyana: 39% of population, 98.1% of children under 5Honduras: 2% of population, 97% of children under 5Croatia: 0% of population, 100% of children under 5Haiti: 97.5% of population, 84.8% of children under 5Hungary: 0% of population, 100% of children under 5Indonesia: 0% of population, 77% of children under 5India: 0% of population, 89.1% of children under 5Ireland: 0% of population, 100% of children under 5Iran, Islamic Rep.: 0% of population, 98.6% of children under 5Iraq: 0% of population, 98.8% of children under 5Israel: 0.982% of population, 100% of children under 5Italy: 0% of population, 100% of children under 5Jamaica: 89% of population, 98% of children under 5Jordan: 0% of population, 98% of children under 5Japan: 0% of population, 100% of children under 5Kazakhstan: 0% of population, 99.7% of children under 5Kenya: 100% of population, 66.9% of children under 5Kyrgyz Republic: 0% of population, 98.9% of children under 5Cambodia: 0% of population, 73.3% of children under 5Lao PDR: 0% of population, 73% of children under 5Lebanon: 0% of population, 98.9% of children under 5Liberia: 100% of population, 66.3% of children under 5Lesotho: 100% of population, 44.5% of children under 5Lithuania: 0% of population, 100% of children under 5Luxembourg: 0% of population, 100% of children under 5Latvia: 0% of population, 100% of children under 5Morocco: 1% of population, 96.9% of children under 5Moldova: 0% of population, 99.6% of children under 5Madagascar: 99.4% of population, 73.8% of children under 5Mexico: 6.7% of population, 97% of children under 5North Macedonia: 0% of population, 99.8% of children under 5Mali: 99.1% of population, 86.7% of children under 5Malta: 0% of population, 100% of children under 5Myanmar: 0% of population, 81.3% of children under 5Mongolia: 0% of population, 99.6% of children under 5Mozambique: 100% of population, 55% of children under 5Mauritania: 100% of population, 44.8% of children under 5Malawi: 100% of population, 67.2% of children under 5Namibia: 89.2% of population, 78.1% of children under 5Niger: 98.1% of population, 63.9% of children under 5Nigeria: 100% of population, 42.6% of children under 5Nicaragua: 9% of population, 84.7% of children under 5Netherlands: 0.75% of population, 100% of children under 5Norway: 0% of population, 100% of children under 5Nepal: 0% of population, 77.2% of children under 5New Zealand: 0% of population, 100% of children under 5Oman: 1.25% of population, 100% of children under 5Pakistan: 0% of population, 42.2% of children under 5Panama: 13% of population, 96.7% of children under 5Peru: 5.72% of population, 96.4% of children under 5Philippines: 0% of population, 91.8% of children under 5Papua New Guinea: 0% of population, 13.4% of children under 5Poland: 0% of population, 100% of children under 5Portugal: 0.61% of population, 100% of children under 5Paraguay: 1% of population, 71% of children under 5Qatar: 15.1% of population, 100% of children under 5Romania: 0% of population, 100% of children under 5Russian Federation: 0% of population, 100% of children under 5Rwanda: 100% of population, 85.6% of children under 5Saudi Arabia: 1.5% of population, 99.2% of children under 5Sudan: 98.8% of population, 67.3% of children under 5Senegal: 98.2% of population, 78.7% of children under 5Singapore: 0% of population, 99.9% of children under 5Sierra Leone: 100% of population, 90.4% of children under 5El Salvador: 0% of population, 91.2% of children under 5Somalia, Fed. Rep.: 98.9% of population, 5.9% of children under 5Slovak Republic: 0% of population, 100% of children under 5Slovenia: 0% of population, 100% of children under 5Sweden: 0% of population, 100% of children under 5Eswatini: 96.4% of population, 53.5% of children under 5Chad: 100% of population, 25.7% of children under 5Togo: 100% of population, 82.9% of children under 5Thailand: 0% of population, 99.8% of children under 5Tajikistan: 0% of population, 95.8% of children under 5Turkmenistan: 0% of population, 99.9% of children under 5Timor-Leste: 0% of population, 60.4% of children under 5Trinidad and Tobago: 46% of population, 96.5% of children under 5Tunisia: 0% of population, 99.9% of children under 5Turkiye: 0% of population, 98.4% of children under 5Tanzania: 100% of population, 26.4% of children under 5Uganda: 100% of population, 32.2% of children under 5Ukraine: 0% of population, 99.8% of children under 5Uruguay: 4% of population, 99.8% of children under 5United States: 9.64% of population, 100% of children under 5Viet Nam: 0% of population, 96.1% of children under 5South Africa: 78.7% of population, 88.6% of children under 5Zambia: 99% of population, 14% of children under 5Zimbabwe: 99% of population, 48.7% of children under 5AFGAREAUSAUTCOGETHJAMPAKPNGSLESOMZMB

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6368.1e-18145
By rank (Spearman), not adjusted-0.6491.1e-18145
Standard (Pearson), adjusted for national income-0.2760.001145
By rank (Spearman), adjusted for national income-0.2860.001145

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: +0.360 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.341 (without PNG) to -0.251 (without AGO). 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: PNG (-0.065).

Fragile: this link may not hold up.
  • 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 Asia42+0.02
Latin America & Caribbean22+0.09
Middle East, North Africa, Afghanistan & Pakistan17-0.17
Sub-Saharan Africa43-0.17

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 third49-0.10
Middle third48-0.51
Richest third48-0.63

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
Christians91-0.26
Muslims38-0.23

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
France23-0.12
Never a European colony17-0.55
Spain19-0.75
United Kingdom41-0.13

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 = -0.341 after dropping 10 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 under 5		Years
Uganda UGA100%32.2%2000, 2016
Tanzania TZA100%26.4%2000, 2016
Togo TGO100%82.9%2000, 2017
Chad TCD100%25.7%2000, 2019
Sierra Leone SLE100%90.4%2000, 2019
Rwanda RWA100%85.6%2000, 2020
Nigeria NGA100%42.6%2000, 2018
Malawi MWI100%67.2%2000, 2016
Mauritania MRT100%44.8%2000, 2021
Mozambique MOZ100%55%2000, 2015
Lesotho LSO100%44.5%2000, 2018
Liberia LBR100%66.3%2000, 2020
Kenya KEN100%66.9%2000, 2014
Guinea GIN100%62%2000, 2018
Ghana GHA100%70.6%2000, 2018

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.

Birth registration

Completeness of birth registration (%)

UNICEF · CC BY 4.0 · updated quarterly

A measure of how far the state reaches: whether it knows a child exists. Based on surveys and sparse. It is near 100 across the rich world, so all the variation is at the other end.

How this was computed

Data used: most recent value in 2010-2025; values come from 2000–2022. 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 Birth registration

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

More links with African ancestry or Birth registration