placestats

East Asian ancestry vs. Mobile subscriptions

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 158 countries, East Asian ancestry and Mobile subscriptions rise and fall together at r = +0.23 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = +0.23, q = 0.0088, allowing for the many pairs tested). Caution: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of east asian ancestry, 0% to 0.487% of population, mobile subscriptions is better by 0.201 per 100 people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.182 per 100 people.

Link before adjusting (r)+0.232p = 0.003 · 158 countries
After adjusting for national income+0.230p = 0.004 · likely range [+0.08, +0.37]
p, allowing for regions0.000standard error 0.030 · 7 regions
Check for luck (q)0.009across 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.

East Asian ancestry · % of populationlink with income +0.24 · independent
Mobile subscriptions · per 100 peoplelink with income +0.58 · moderate

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

Every country as a dot

East Asian ancestry · % of population →Mobile subscriptions · per 100 people →0%100%32.1574Afghanistan: 0% of population, 60.1 per 100 peopleAngola: 0% of population, 69.7 per 100 peopleAlbania: 0% of population, 89.1 per 100 peopleUnited Arab Emirates: 0% of population, 203 per 100 peopleArgentina: 0% of population, 140 per 100 peopleArmenia: 0% of population, 135 per 100 peopleAustralia: 7.1% of population, 113 per 100 peopleAustria: 0% of population, 124 per 100 peopleAzerbaijan: 0% of population, 110 per 100 peopleBurundi: 0% of population, 63.2 per 100 peopleBelgium: 0% of population, 104 per 100 peopleBenin: 0% of population, 126 per 100 peopleBurkina Faso: 0% of population, 117 per 100 peopleBangladesh: 0% of population, 108 per 100 peopleBulgaria: 0% of population, 118 per 100 peopleBahrain: 0% of population, 160 per 100 peopleBosnia and Herzegovina: 0% of population, 121 per 100 peopleBelarus: 0% of population, 131 per 100 peopleBelize: 0.5% of population, 67.2 per 100 peopleBolivia: 0% of population, 98 per 100 peopleBrazil: 0.8% of population, 102 per 100 peopleBhutan: 0% of population, 99.8 per 100 peopleBotswana: 0% of population, 164 per 100 peopleCentral African Republic: 0% of population, 38.8 per 100 peopleCanada: 5.59% of population, 94.1 per 100 peopleSwitzerland: 0% of population, 129 per 100 peopleChile: 0% of population, 133 per 100 peopleChina: 100% of population, 132 per 100 peopleCote d'Ivoire: 0% of population, 184 per 100 peopleCameroon: 0% of population, 108 per 100 peopleCongo, Dem. Rep.: 0% of population, 58.5 per 100 peopleCongo, Rep.: 0% of population, 95.5 per 100 peopleColombia: 0% of population, 174 per 100 peopleComoros: 0% of population, 110 per 100 peopleCabo Verde: 0% of population, 112 per 100 peopleCosta Rica: 1% of population, 136 per 100 peopleCyprus: 0% of population, 156 per 100 peopleCzechia: 0% of population, 127 per 100 peopleGermany: 0% of population, 129 per 100 peopleDenmark: 0% of population, 127 per 100 peopleDominican Republic: 0% of population, 93.7 per 100 peopleAlgeria: 0% of population, 115 per 100 peopleEcuador: 0% of population, 102 per 100 peopleEgypt, Arab Rep.: 0% of population, 97.1 per 100 peopleSpain: 0% of population, 130 per 100 peopleEstonia: 0% of population, 151 per 100 peopleEthiopia: 0% of population, 65.1 per 100 peopleFinland: 0% of population, 126 per 100 peopleFiji: 52.8% of population, 574 per 100 peopleFrance: 1% of population, 117 per 100 peopleGabon: 0% of population, 125 per 100 peopleUnited Kingdom: 0% of population, 122 per 100 peopleGeorgia: 0% of population, 161 per 100 peopleGhana: 0% of population, 114 per 100 peopleGuinea: 0% of population, 97.9 per 100 peopleGambia, The: 0% of population, 126 per 100 peopleGuinea-Bissau: 0% of population, 147 per 100 peopleEquatorial Guinea: 0% of population, 49.5 per 100 peopleGreece: 0% of population, 114 per 100 peopleGuatemala: 0% of population, 113 per 100 peopleGuyana: 0.7% of population, 113 per 100 peopleHong Kong SAR, China: 100% of population, 365 per 100 peopleHonduras: 0% of population, 70.9 per 100 peopleCroatia: 0% of population, 122 per 100 peopleHaiti: 0% of population, 65.2 per 100 peopleHungary: 0% of population, 105 per 100 peopleIndonesia: 100% of population, 123 per 100 peopleIndia: 0% of population, 79.4 per 100 peopleIreland: 0% of population, 113 per 100 peopleIran, Islamic Rep.: 0% of population, 174 per 100 peopleIraq: 0% of population, 100 per 100 peopleIsrael: 0% of population, 177 per 100 peopleItaly: 0% of population, 133 per 100 peopleJamaica: 0.5% of population, 118 per 100 peopleJordan: 0% of population, 69.6 per 100 peopleJapan: 100% of population, 178 per 100 peopleKazakhstan: 2.1% of population, 127 per 100 peopleKenya: 0% of population, 126 per 100 peopleKyrgyz Republic: 2% of population, 107 per 100 peopleCambodia: 100% of population, 116 per 100 peopleKorea, Rep.: 100% of population, 173 per 100 peopleKuwait: 0% of population, 168 per 100 peopleLao PDR: 100% of population, 64.8 per 100 peopleLebanon: 0% of population, 74 per 100 peopleLiberia: 0% of population, 32.1 per 100 peopleLibya: 0% of population, 193 per 100 peopleSri Lanka: 0% of population, 133 per 100 peopleLesotho: 0% of population, 70.3 per 100 peopleLithuania: 0% of population, 139 per 100 peopleLuxembourg: 0% of population, 144 per 100 peopleLatvia: 0% of population, 121 per 100 peopleMorocco: 0% of population, 153 per 100 peopleMoldova: 0% of population, 120 per 100 peopleMadagascar: 0% of population, 75.5 per 100 peopleMexico: 0% of population, 116 per 100 peopleNorth Macedonia: 0% of population, 108 per 100 peopleMali: 0% of population, 112 per 100 peopleMalta: 0% of population, 142 per 100 peopleMyanmar: 97.5% of population, 114 per 100 peopleMongolia: 98.2% of population, 141 per 100 peopleMozambique: 0% of population, 49.5 per 100 peopleMauritania: 0% of population, 92.1 per 100 peopleMauritius: 3% of population, 173 per 100 peopleMalawi: 0% of population, 69.3 per 100 peopleMalaysia: 92.5% of population, 140 per 100 peopleNamibia: 0% of population, 85.2 per 100 peopleNiger: 0% of population, 60.6 per 100 peopleNigeria: 0% of population, 70.8 per 100 peopleNicaragua: 0% of population, 106 per 100 peopleNetherlands: 0.95% of population, 129 per 100 peopleNorway: 0% of population, 109 per 100 peopleNepal: 0% of population, 99.8 per 100 peopleNew Zealand: 18.5% of population, 130 per 100 peopleOman: 1.08% of population, 121 per 100 peoplePakistan: 0% of population, 76.9 per 100 peoplePanama: 1.5% of population, 157 per 100 peoplePeru: 2% of population, 125 per 100 peoplePhilippines: 100% of population, 115 per 100 peoplePapua New Guinea: 100% of population, 38.8 per 100 peoplePoland: 0% of population, 138 per 100 peoplePuerto Rico (US): 0% of population, 126 per 100 peoplePortugal: 0.9% of population, 124 per 100 peopleParaguay: 0% of population, 127 per 100 peopleQatar: 2.2% of population, 154 per 100 peopleRomania: 0% of population, 120 per 100 peopleRussian Federation: 0% of population, 186 per 100 peopleRwanda: 0% of population, 93.2 per 100 peopleSaudi Arabia: 1.2% of population, 160 per 100 peopleSudan: 0% of population, 70.2 per 100 peopleSenegal: 0% of population, 124 per 100 peopleSingapore: 92% of population, 171 per 100 peopleSierra Leone: 0% of population, 108 per 100 peopleEl Salvador: 0% of population, 177 per 100 peopleSomalia, Fed. Rep.: 0% of population, 54 per 100 peopleSlovak Republic: 0% of population, 140 per 100 peopleSlovenia: 0% of population, 131 per 100 peopleSweden: 0.7% of population, 141 per 100 peopleEswatini: 0% of population, 140 per 100 peopleSyrian Arab Republic: 0% of population, 71.2 per 100 peopleChad: 0% of population, 72.9 per 100 peopleTogo: 0% of population, 80.8 per 100 peopleThailand: 100% of population, 161 per 100 peopleTajikistan: 0% of population, 76.2 per 100 peopleTurkmenistan: 0% of population, 88.2 per 100 peopleTimor-Leste: 100% of population, 116 per 100 peopleTrinidad and Tobago: 1.5% of population, 119 per 100 peopleTunisia: 0% of population, 118 per 100 peopleTurkiye: 0% of population, 108 per 100 peopleTanzania: 0% of population, 127 per 100 peopleUganda: 0% of population, 83.2 per 100 peopleUkraine: 0% of population, 133 per 100 peopleUruguay: 0% of population, 146 per 100 peopleUnited States: 3.35% of population, 113 per 100 peopleUzbekistan: 1% of population, 110 per 100 peopleViet Nam: 100% of population, 128 per 100 peopleSouth Africa: 0.45% of population, 179 per 100 peopleZambia: 0% of population, 109 per 100 peopleZimbabwe: 0% of population, 94.2 per 100 peopleARECAFFJIHKGJPNLAOLBRLBYMOZPHLPNG

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.2320.003158
By rank (Spearman), not adjusted+0.2250.004158
Standard (Pearson), adjusted for national income+0.2300.004158
By rank (Spearman), adjusted for national income+0.1080.178158

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: +0.002 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.161 (without HKG) to +0.263 (without PNG). 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: HKG (-0.069).

Fragile: this link may not hold up.
  • correlation moves sharply once outliers are trimmed
  • sign flips once outliers are trimmed
  • 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 & Pacific19-0.12
Europe & Central Asia45-0.00
Latin America & Caribbean23-0.03
Middle East, North Africa, Afghanistan & Pakistan20-0.32
Sub-Saharan Africa44+0.15

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 third53-0.13
Middle third52+0.21
Richest third53+0.55

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+0.22
Muslims45+0.01

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
France24-0.17
Never a European colony21+0.41
Spain19+0.03
United Kingdom46+0.17

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 = -0.024 after dropping 32 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
Viet Nam VNM100%1282000, 2024
Timor-Leste TLS100%1162000, 2024
Thailand THA100%1612000, 2024
Papua New Guinea PNG100%38.82000, 2024
Philippines PHL100%1152000, 2024
Lao PDR LAO100%64.82000, 2023
Korea, Rep. KOR100%1732000, 2024
Cambodia KHM100%1162000, 2024
Japan JPN100%1782000, 2023
Indonesia IDN100%1232000, 2024
Hong Kong SAR, China HKG100%3652000, 2024
China CHN100%1322000, 2024
Mongolia MNG98.2%1412000, 2024
Myanmar MMR97.5%1142000, 2024
Malaysia MYS92.5%1402000, 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

East Asian ancestry

East Asian and Pacific 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 East Asia, Southeast Asia or the Pacific. 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.

Mobile subscriptions

Mobile cellular subscriptions (per 100 people)

International Telecommunication Union · CC BY 4.0 · updated quarterly

Counts SIM card subscriptions, not people. People with more than one SIM card push several countries well above 100 per 100 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 East Asian ancestry and Mobile subscriptions

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

More links with East Asian ancestry or Mobile subscriptions