placestats

African ancestry vs. Pupil-teacher ratio

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 147 countries, African ancestry and Pupil-teacher ratio rise and fall together at r = +0.71 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.34 (q = 0.034, 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: much weaker within regions than across them (largely a between-region difference).

Comparing countries across the middle half of african ancestry, 0% to 95.3% of population, pupil-teacher ratio is worse by 20.7 pupils per teacher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 7.99 pupils per teacher.

Link before adjusting (r)+0.713p = 4.3e-24 · 147 countries
After adjusting for national income+0.342p = 2.5e-5 · likely range [+0.19, +0.48]
p, allowing for regions0.003standard error 0.070 · 7 regions
Check for luck (q)0.034across 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
Pupil-teacher ratio · pupils per teacherlink 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

African ancestry · % of population →Pupil-teacher ratio · pupils per teacher →0%100%8.383.4Afghanistan: 0% of population, 48.8 pupils per teacherAngola: 98% of population, 50 pupils per teacherAlbania: 0% of population, 17.6 pupils per teacherUnited Arab Emirates: 0% of population, 24.5 pupils per teacherArmenia: 0% of population, 15.4 pupils per teacherAustria: 0% of population, 10 pupils per teacherAzerbaijan: 0% of population, 15.4 pupils per teacherBurundi: 100% of population, 42.5 pupils per teacherBelgium: 0% of population, 11.3 pupils per teacherBenin: 100% of population, 39.2 pupils per teacherBurkina Faso: 100% of population, 39.7 pupils per teacherBangladesh: 0% of population, 30.1 pupils per teacherBulgaria: 0% of population, 15.2 pupils per teacherBahrain: 0% of population, 11.9 pupils per teacherBosnia and Herzegovina: 0% of population, 16.9 pupils per teacherBelarus: 0% of population, 19.2 pupils per teacherBelize: 17.4% of population, 19.8 pupils per teacherBolivia: 0.907% of population, 17.8 pupils per teacherBrazil: 15.7% of population, 20.2 pupils per teacherBhutan: 0% of population, 34.7 pupils per teacherBotswana: 98.5% of population, 23.7 pupils per teacherCentral African Republic: 99.4% of population, 83.4 pupils per teacherSwitzerland: 0% of population, 9.93 pupils per teacherChile: 1.4% of population, 17.8 pupils per teacherChina: 0% of population, 16.4 pupils per teacherCote d'Ivoire: 99.3% of population, 41.8 pupils per teacherCameroon: 100% of population, 44.8 pupils per teacherCongo, Dem. Rep.: 99.5% of population, 33.2 pupils per teacherCongo, Rep.: 100% of population, 44.4 pupils per teacherColombia: 17.3% of population, 23.3 pupils per teacherComoros: 100% of population, 28.1 pupils per teacherCabo Verde: 58.6% of population, 21.1 pupils per teacherCosta Rica: 8.91% of population, 12.2 pupils per teacherCyprus: 0% of population, 12 pupils per teacherCzechia: 0% of population, 18.9 pupils per teacherGermany: 0% of population, 12.3 pupils per teacherDenmark: 0% of population, 10.7 pupils per teacherDominican Republic: 44.4% of population, 18.9 pupils per teacherAlgeria: 0% of population, 24.3 pupils per teacherEcuador: 6.97% of population, 24.3 pupils per teacherEgypt, Arab Rep.: 5.5% of population, 23.7 pupils per teacherSpain: 0% of population, 13.1 pupils per teacherEstonia: 0% of population, 11.3 pupils per teacherEthiopia: 100% of population, 55.1 pupils per teacherFinland: 0% of population, 13.7 pupils per teacherFiji: 0% of population, 28 pupils per teacherFrance: 0% of population, 18.2 pupils per teacherGabon: 99% of population, 24.5 pupils per teacherUnited Kingdom: 1.8% of population, 15.1 pupils per teacherGeorgia: 0% of population, 8.98 pupils per teacherGhana: 100% of population, 27 pupils per teacherGuinea: 100% of population, 47.1 pupils per teacherGambia, The: 99.5% of population, 36.1 pupils per teacherGuinea-Bissau: 96.5% of population, 51.9 pupils per teacherEquatorial Guinea: 94.3% of population, 23.2 pupils per teacherGreece: 0% of population, 9.38 pupils per teacherGuatemala: 4.14% of population, 20.3 pupils per teacherGuyana: 39% of population, 23.2 pupils per teacherHong Kong SAR, China: 0% of population, 13.3 pupils per teacherHonduras: 2% of population, 25.6 pupils per teacherCroatia: 0% of population, 13.5 pupils per teacherHungary: 0% of population, 10.8 pupils per teacherIndonesia: 0% of population, 17 pupils per teacherIndia: 0% of population, 32.7 pupils per teacherIreland: 0% of population, 16.1 pupils per teacherIran, Islamic Rep.: 0% of population, 28.5 pupils per teacherIsrael: 0.982% of population, 12.1 pupils per teacherItaly: 0% of population, 11.5 pupils per teacherJamaica: 89% of population, 24.8 pupils per teacherJordan: 0% of population, 18.5 pupils per teacherJapan: 0% of population, 15.7 pupils per teacherKazakhstan: 0% of population, 17.2 pupils per teacherKenya: 100% of population, 30.7 pupils per teacherKyrgyz Republic: 0% of population, 25 pupils per teacherCambodia: 0% of population, 41.7 pupils per teacherKorea, Rep.: 0% of population, 16.3 pupils per teacherKuwait: 0% of population, 8.88 pupils per teacherLao PDR: 0% of population, 22.3 pupils per teacherLebanon: 0% of population, 12.5 pupils per teacherLiberia: 100% of population, 22.3 pupils per teacherSri Lanka: 0% of population, 21.7 pupils per teacherLesotho: 100% of population, 32.9 pupils per teacherLithuania: 0% of population, 13.5 pupils per teacherLuxembourg: 0% of population, 8.3 pupils per teacherLatvia: 0% of population, 11.5 pupils per teacherMorocco: 1% of population, 26.8 pupils per teacherMoldova: 0% of population, 17.9 pupils per teacherMadagascar: 99.4% of population, 39.8 pupils per teacherMexico: 6.7% of population, 26.6 pupils per teacherNorth Macedonia: 0% of population, 14.9 pupils per teacherMali: 99.1% of population, 37.8 pupils per teacherMalta: 0% of population, 12.9 pupils per teacherMyanmar: 0% of population, 24.4 pupils per teacherMongolia: 0% of population, 30.4 pupils per teacherMozambique: 100% of population, 55.3 pupils per teacherMauritania: 100% of population, 34.3 pupils per teacherMauritius: 13% of population, 16.2 pupils per teacherMalawi: 100% of population, 58.7 pupils per teacherMalaysia: 0% of population, 11.7 pupils per teacherNamibia: 89.2% of population, 25.1 pupils per teacherNiger: 98.1% of population, 36.3 pupils per teacherNigeria: 100% of population, 37.6 pupils per teacherNicaragua: 9% of population, 30.2 pupils per teacherNetherlands: 0.75% of population, 11.8 pupils per teacherNorway: 0% of population, 8.59 pupils per teacherNepal: 0% of population, 19.7 pupils per teacherNew Zealand: 0% of population, 14.9 pupils per teacherOman: 1.25% of population, 9.67 pupils per teacherPakistan: 0% of population, 44.1 pupils per teacherPanama: 13% of population, 22 pupils per teacherPeru: 5.72% of population, 17.4 pupils per teacherPhilippines: 0% of population, 29.1 pupils per teacherPapua New Guinea: 0% of population, 35.5 pupils per teacherPoland: 0% of population, 10.2 pupils per teacherPuerto Rico (US): 15.8% of population, 13.5 pupils per teacherPortugal: 0.61% of population, 12.4 pupils per teacherParaguay: 1% of population, 24.2 pupils per teacherQatar: 15.1% of population, 12.2 pupils per teacherRomania: 0% of population, 19.3 pupils per teacherRussian Federation: 0% of population, 21.3 pupils per teacherRwanda: 100% of population, 59.5 pupils per teacherSaudi Arabia: 1.5% of population, 13.8 pupils per teacherSenegal: 98.2% of population, 36.3 pupils per teacherSingapore: 0% of population, 14.7 pupils per teacherSierra Leone: 100% of population, 27.5 pupils per teacherEl Salvador: 0% of population, 26.9 pupils per teacherSlovak Republic: 0% of population, 15.5 pupils per teacherSlovenia: 0% of population, 13.8 pupils per teacherSweden: 0% of population, 12.2 pupils per teacherEswatini: 96.4% of population, 26.6 pupils per teacherChad: 100% of population, 56.9 pupils per teacherTogo: 100% of population, 40.1 pupils per teacherThailand: 0% of population, 16.6 pupils per teacherTajikistan: 0% of population, 22.3 pupils per teacherTimor-Leste: 0% of population, 26.9 pupils per teacherTunisia: 0% of population, 16.9 pupils per teacherTurkiye: 0% of population, 17 pupils per teacherTanzania: 100% of population, 50.6 pupils per teacherUganda: 100% of population, 42.7 pupils per teacherUkraine: 0% of population, 13 pupils per teacherUruguay: 4% of population, 11 pupils per teacherUnited States: 9.64% of population, 14.2 pupils per teacherUzbekistan: 0% of population, 21.5 pupils per teacherViet Nam: 0% of population, 20.3 pupils per teacherSouth Africa: 78.7% of population, 30.3 pupils per teacherZambia: 99% of population, 42.1 pupils per teacherZimbabwe: 99% of population, 36.4 pupils per teacherAFGBWACAFGABKWTLBRLUXMWINORPAKRWA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.7134.3e-24147
By rank (Spearman), not adjusted+0.6178.6e-17147
Standard (Pearson), adjusted for national income+0.3422.5e-5147
By rank (Spearman), adjusted for national income+0.2600.002147

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 147 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: +0.371 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.321 (without AGO) to +0.368 (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: CAF (+0.027).

Fragile: this link may not hold up.
  • 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 Asia44+0.06
Latin America & Caribbean20+0.20
Middle East, North Africa, Afghanistan & Pakistan17+0.16
Sub-Saharan Africa42+0.13

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+0.29
Middle third49+0.23
Richest third49+0.40

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
Christians87+0.34
Muslims39+0.33

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
France22+0.20
Never a European colony20+0.14
Spain18+0.04
United Kingdom39+0.14

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 = +0.347 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
pupils per teacher		Years
Uganda UGA100%42.72000, 2017
Tanzania TZA100%50.62000, 2018
Togo TGO100%40.12000, 2018
Chad TCD100%56.92000, 2016
Sierra Leone SLE100%27.52000, 2018
Rwanda RWA100%59.52000, 2018
Nigeria NGA100%37.62000, 2010
Malawi MWI100%58.72000, 2018
Mauritania MRT100%34.32000, 2018
Mozambique MOZ100%55.32000, 2018
Lesotho LSO100%32.92000, 2017
Liberia LBR100%22.32000, 2017
Kenya KEN100%30.72000, 2015
Guinea GIN100%47.12000, 2016
Ghana GHA100%272000, 2019

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.

Pupil-teacher ratio

Pupil-teacher ratio, primary

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

The World Bank's copy stops at 2019.

How this was computed

Data used: most recent value in 2010-2025; values come from 2000–2019. 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 Pupil-teacher ratio

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

More links with African ancestry or Pupil-teacher ratio