placestats

African ancestry vs. Fixed broadband

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 158 countries, African ancestry and Fixed broadband rise and fall together at r = -0.63 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.11, which could easily be chance (q = 0.62, 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 95.9% of population, fixed broadband is worse by 21.9 per 100 people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 3.15 per 100 people.

Link before adjusting (r)-0.628p = 9.5e-19 · 158 countries
After adjusting for national income-0.114p = 0.154 · likely range [-0.27, +0.04]
p, allowing for regions0.431standard error 0.136 · 7 regions
Check for luck (q)0.621across 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
Fixed broadband · per 100 peoplelink with income +0.88 · 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 →Fixed broadband · per 100 people →0%100%048.9Afghanistan: 0% of population, 0.0801 per 100 peopleAngola: 98% of population, 0.363 per 100 peopleAlbania: 0% of population, 24.9 per 100 peopleUnited Arab Emirates: 0% of population, 40.8 per 100 peopleArgentina: 2% of population, 26.1 per 100 peopleArmenia: 0% of population, 20.3 per 100 peopleAustralia: 0% of population, 36.5 per 100 peopleAustria: 0% of population, 30.1 per 100 peopleAzerbaijan: 0% of population, 21.8 per 100 peopleBurundi: 100% of population, 0.0203 per 100 peopleBelgium: 0% of population, 44.2 per 100 peopleBenin: 100% of population, 0.277 per 100 peopleBurkina Faso: 100% of population, 0.851 per 100 peopleBangladesh: 0% of population, 8.09 per 100 peopleBulgaria: 0% of population, 37 per 100 peopleBahrain: 0% of population, 17 per 100 peopleBosnia and Herzegovina: 0% of population, 29.4 per 100 peopleBelarus: 0% of population, 36.3 per 100 peopleBelize: 17.4% of population, 9.75 per 100 peopleBolivia: 0.907% of population, 12.1 per 100 peopleBrazil: 15.7% of population, 24.1 per 100 peopleBhutan: 0% of population, 2.92 per 100 peopleBotswana: 98.5% of population, 7.44 per 100 peopleCentral African Republic: 99.4% of population, 0.0161 per 100 peopleCanada: 1.53% of population, 42.5 per 100 peopleSwitzerland: 0% of population, 47 per 100 peopleChile: 1.4% of population, 23.7 per 100 peopleChina: 0% of population, 47.2 per 100 peopleCote d'Ivoire: 99.3% of population, 1.6 per 100 peopleCameroon: 100% of population, 2.13 per 100 peopleCongo, Dem. Rep.: 99.5% of population, 0.032 per 100 peopleCongo, Rep.: 100% of population, 1.27 per 100 peopleColombia: 17.3% of population, 17.2 per 100 peopleComoros: 100% of population, 0.388 per 100 peopleCabo Verde: 58.6% of population, 8.31 per 100 peopleCosta Rica: 8.91% of population, 23.3 per 100 peopleCyprus: 0% of population, 37.6 per 100 peopleCzechia: 0% of population, 38.9 per 100 peopleGermany: 0% of population, 45.6 per 100 peopleDenmark: 0% of population, 43.4 per 100 peopleDominican Republic: 44.4% of population, 11.2 per 100 peopleAlgeria: 0% of population, 13.3 per 100 peopleEcuador: 6.97% of population, 17.2 per 100 peopleEgypt, Arab Rep.: 5.5% of population, 11.7 per 100 peopleSpain: 0% of population, 39.2 per 100 peopleEstonia: 0% of population, 35.4 per 100 peopleEthiopia: 100% of population, 0.594 per 100 peopleFinland: 0% of population, 36.5 per 100 peopleFiji: 0% of population, 1.8 per 100 peopleFrance: 0% of population, 48.9 per 100 peopleGabon: 99% of population, 4.69 per 100 peopleUnited Kingdom: 1.8% of population, 42.2 per 100 peopleGeorgia: 0% of population, 30.4 per 100 peopleGhana: 100% of population, 0.665 per 100 peopleGuinea: 100% of population, 0.00628 per 100 peopleGambia, The: 99.5% of population, 0.519 per 100 peopleGuinea-Bissau: 96.5% of population, 0.386 per 100 peopleEquatorial Guinea: 94.3% of population, 0.101 per 100 peopleGreece: 0% of population, 44.7 per 100 peopleGuatemala: 4.14% of population, 5.34 per 100 peopleGuyana: 39% of population, 12.9 per 100 peopleHong Kong SAR, China: 0% of population, 40.3 per 100 peopleHonduras: 2% of population, 4.58 per 100 peopleCroatia: 0% of population, 29.6 per 100 peopleHaiti: 97.5% of population, 0.307 per 100 peopleHungary: 0% of population, 37.5 per 100 peopleIndonesia: 0% of population, 4.92 per 100 peopleIndia: 0% of population, 3.15 per 100 peopleIreland: 0% of population, 32.3 per 100 peopleIran, Islamic Rep.: 0% of population, 12.1 per 100 peopleIraq: 0% of population, 17.6 per 100 peopleIsrael: 0.982% of population, 29.2 per 100 peopleItaly: 0% of population, 31.8 per 100 peopleJamaica: 89% of population, 16 per 100 peopleJordan: 0% of population, 7.02 per 100 peopleJapan: 0% of population, 38.6 per 100 peopleKazakhstan: 0% of population, 15.3 per 100 peopleKenya: 100% of population, 3.04 per 100 peopleKyrgyz Republic: 0% of population, 7.8 per 100 peopleCambodia: 0% of population, 4.15 per 100 peopleKorea, Rep.: 0% of population, 47.8 per 100 peopleKuwait: 0% of population, 1.01 per 100 peopleLao PDR: 0% of population, 2.72 per 100 peopleLebanon: 0% of population, 7.29 per 100 peopleLiberia: 100% of population, 0.275 per 100 peopleLibya: 3.5% of population, 4.52 per 100 peopleSri Lanka: 0% of population, 8.47 per 100 peopleLesotho: 100% of population, 0.379 per 100 peopleLithuania: 0% of population, 27.8 per 100 peopleLuxembourg: 0% of population, 40.3 per 100 peopleLatvia: 0% of population, 25.8 per 100 peopleMorocco: 1% of population, 7.3 per 100 peopleMoldova: 0% of population, 29.6 per 100 peopleMadagascar: 99.4% of population, 0.124 per 100 peopleMexico: 6.7% of population, 21.7 per 100 peopleNorth Macedonia: 0% of population, 29.9 per 100 peopleMali: 99.1% of population, 0.774 per 100 peopleMalta: 0% of population, 44.5 per 100 peopleMyanmar: 0% of population, 2.87 per 100 peopleMongolia: 0% of population, 15.8 per 100 peopleMozambique: 100% of population, 0.142 per 100 peopleMauritania: 100% of population, 0.947 per 100 peopleMauritius: 13% of population, 28 per 100 peopleMalawi: 100% of population, 0.0864 per 100 peopleMalaysia: 0% of population, 13.5 per 100 peopleNamibia: 89.2% of population, 2.83 per 100 peopleNiger: 98.1% of population, 0.111 per 100 peopleNigeria: 100% of population, 0.0787 per 100 peopleNicaragua: 9% of population, 5.78 per 100 peopleNetherlands: 0.75% of population, 43 per 100 peopleNorway: 0% of population, 45.2 per 100 peopleNepal: 0% of population, 10.1 per 100 peopleNew Zealand: 0% of population, 38 per 100 peopleOman: 1.25% of population, 11.1 per 100 peoplePakistan: 0% of population, 1.47 per 100 peoplePanama: 13% of population, 18.1 per 100 peoplePeru: 5.72% of population, 11.7 per 100 peoplePhilippines: 0% of population, 7.14 per 100 peoplePapua New Guinea: 0% of population, 0.233 per 100 peoplePoland: 0% of population, 25.4 per 100 peoplePuerto Rico (US): 15.8% of population, 28 per 100 peoplePortugal: 0.61% of population, 45.2 per 100 peopleParaguay: 1% of population, 12.9 per 100 peopleQatar: 15.1% of population, 11.8 per 100 peopleRomania: 0% of population, 35.8 per 100 peopleRussian Federation: 0% of population, 27.1 per 100 peopleRwanda: 100% of population, 0.596 per 100 peopleSaudi Arabia: 1.5% of population, 44.1 per 100 peopleSudan: 98.8% of population, 0.0604 per 100 peopleSenegal: 98.2% of population, 4.04 per 100 peopleSingapore: 0% of population, 27.8 per 100 peopleSierra Leone: 100% of population, 0.00227 per 100 peopleEl Salvador: 0% of population, 12.5 per 100 peopleSomalia, Fed. Rep.: 98.9% of population, 0.723 per 100 peopleSlovak Republic: 0% of population, 33.8 per 100 peopleSlovenia: 0% of population, 34.2 per 100 peopleSweden: 0% of population, 40.6 per 100 peopleEswatini: 96.4% of population, 2.51 per 100 peopleSyrian Arab Republic: 0% of population, 6.86 per 100 peopleChad: 100% of population, 0 per 100 peopleTogo: 100% of population, 1.42 per 100 peopleThailand: 0% of population, 14.9 per 100 peopleTajikistan: 0% of population, 0.984 per 100 peopleTurkmenistan: 0% of population, 5.22 per 100 peopleTimor-Leste: 0% of population, 0.006 per 100 peopleTrinidad and Tobago: 46% of population, 27 per 100 peopleTunisia: 0% of population, 15 per 100 peopleTurkiye: 0% of population, 23.4 per 100 peopleTanzania: 100% of population, 0.246 per 100 peopleUganda: 100% of population, 0.208 per 100 peopleUkraine: 0% of population, 21.7 per 100 peopleUruguay: 4% of population, 33 per 100 peopleUnited States: 9.64% of population, 38.9 per 100 peopleUzbekistan: 0% of population, 34.7 per 100 peopleViet Nam: 0% of population, 23.7 per 100 peopleSouth Africa: 78.7% of population, 5.35 per 100 peopleZambia: 99% of population, 0.79 per 100 peopleZimbabwe: 99% of population, 1.94 per 100 peopleAFGCHNFRAGINJAMKORPNGSLETCDTLS

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6289.5e-19158
By rank (Spearman), not adjusted-0.6289.5e-19158
Standard (Pearson), adjusted for national income-0.1140.154158
By rank (Spearman), adjusted for national income-0.2830.000158

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 158 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: +0.514 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.127 (without FJI) to -0.088 (without GUY). 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: GUY (+0.026).

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
Europe & Central Asia45+0.20
Latin America & Caribbean23-0.07
Middle East, North Africa, Afghanistan & Pakistan20-0.43
Sub-Saharan Africa44-0.91

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 third53-0.51
Middle third52-0.33
Richest third53-0.42

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
Christians92-0.28
Muslims45-0.17

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
France24-0.55
Never a European colony21+0.07
Spain19-0.68
United Kingdom46-0.05

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 = -0.114 after dropping 0 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 100 people		Years
Uganda UGA100%0.2082000, 2024
Tanzania TZA100%0.2462000, 2024
Togo TGO100%1.422000, 2024
Chad TCD100%02000, 2024
Sierra Leone SLE100%0.002272000, 2021
Rwanda RWA100%0.5962000, 2024
Nigeria NGA100%0.07872000, 2024
Malawi MWI100%0.08642000, 2024
Mauritania MRT100%0.9472000, 2024
Mozambique MOZ100%0.1422000, 2024
Lesotho LSO100%0.3792000, 2024
Liberia LBR100%0.2752000, 2022
Kenya KEN100%3.042000, 2024
Guinea GIN100%0.006282000, 2022
Ghana GHA100%0.6652000, 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.

Fixed broadband

Fixed broadband subscriptions (per 100 people)

International Telecommunication Union · CC BY 4.0 · updated quarterly

Subscriptions, not people. A household line counts once, however many people use it. A country that went straight to mobile data can be well connected with few of these lines. Internet users, already on the site, is the measure of people.

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 African ancestry and Fixed broadband

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

More links with African ancestry or Fixed broadband