placestats

Labor share of income vs. Middle Eastern ancestry

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 125 countries, Labor share of income and Middle Eastern ancestry rise and fall together at r = -0.35 (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 = -0.35, q = 0.0094, allowing for the many pairs tested). Caution: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of middle Eastern ancestry, 0% to 0.3% of population, labor share of income is 0.041% of GDP lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0418% of GDP.

Link before adjusting (r)-0.345p = 8.1e-5 · 125 countries
After adjusting for national income-0.351p = 6.4e-5 · likely range [-0.50, -0.19]
p, allowing for regions0.276standard error 0.293 · 7 regions
Check for luck (q)0.009across 18,622 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.

Labor share of income · % of GDPlink with income +0.08 · independent
Middle Eastern ancestry · % of populationlink with income +0.16 · independent

Neither of these is closely tied to national income, so adjusting for income is a real test here, not a formality.

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

Every country as a dot

Labor share of income · % of GDP →Middle Eastern ancestry · % of population →16.4%74.1%0%100%Angola: 22.3% of GDP, 0% of populationAlbania: 70.5% of GDP, 0% of populationArgentina: 52.8% of GDP, 3% of populationArmenia: 50.9% of GDP, 0% of populationAustralia: 54.6% of GDP, 2.5% of populationAustria: 60.8% of GDP, 0% of populationAzerbaijan: 39.2% of GDP, 1% of populationBurundi: 60.6% of GDP, 0% of populationBelgium: 58.6% of GDP, 1.6% of populationBenin: 61.7% of GDP, 0% of populationBurkina Faso: 42.6% of GDP, 0% of populationBulgaria: 51.7% of GDP, 0% of populationBahrain: 29.4% of GDP, 100% of populationBosnia and Herzegovina: 67.1% of GDP, 0% of populationBelarus: 57% of GDP, 0% of populationBolivia: 49.8% of GDP, 0% of populationBrazil: 51.1% of GDP, 0% of populationBotswana: 27.8% of GDP, 0% of populationCentral African Republic: 16.4% of GDP, 0% of populationCanada: 65.9% of GDP, 0.9% of populationSwitzerland: 65.3% of GDP, 0% of populationChile: 44% of GDP, 2% of populationChina: 56.1% of GDP, 0% of populationCote d'Ivoire: 33.2% of GDP, 0.7% of populationCameroon: 64.4% of GDP, 0% of populationColombia: 47.8% of GDP, 0% of populationCabo Verde: 62.6% of GDP, 0% of populationCosta Rica: 53.1% of GDP, 0% of populationCyprus: 53.7% of GDP, 0% of populationCzechia: 51.2% of GDP, 0% of populationGermany: 63.7% of GDP, 0% of populationDenmark: 60.1% of GDP, 0% of populationDominican Republic: 42.7% of GDP, 0% of populationEcuador: 53% of GDP, 0% of populationEgypt, Arab Rep.: 36.2% of GDP, 94.5% of populationSpain: 59.4% of GDP, 0.3% of populationEstonia: 60.7% of GDP, 0% of populationFinland: 58.3% of GDP, 0% of populationFiji: 48.9% of GDP, 0% of populationFrance: 63.1% of GDP, 4.8% of populationGabon: 27.5% of GDP, 0% of populationUnited Kingdom: 59.5% of GDP, 0% of populationGeorgia: 46.7% of GDP, 0% of populationGuinea: 42.2% of GDP, 0% of populationGreece: 54% of GDP, 0% of populationGuatemala: 46.9% of GDP, 0% of populationHong Kong SAR, China: 52.7% of GDP, 0% of populationHonduras: 54.7% of GDP, 0% of populationCroatia: 61.3% of GDP, 0% of populationHungary: 53.7% of GDP, 0% of populationIndonesia: 50.9% of GDP, 0% of populationIndia: 53.3% of GDP, 0% of populationIreland: 30.9% of GDP, 0% of populationIran, Islamic Rep.: 39.3% of GDP, 98% of populationIraq: 29.6% of GDP, 94.4% of populationIsrael: 49.9% of GDP, 62.7% of populationItaly: 51.2% of GDP, 0.2% of populationJamaica: 60.9% of GDP, 0% of populationJordan: 49.3% of GDP, 98% of populationJapan: 58.7% of GDP, 0% of populationKazakhstan: 37.3% of GDP, 0% of populationKenya: 54% of GDP, 0% of populationKyrgyz Republic: 40% of GDP, 0% of populationKorea, Rep.: 54.6% of GDP, 0% of populationKuwait: 24.9% of GDP, 100% of populationLao PDR: 39.8% of GDP, 0% of populationLebanon: 44.5% of GDP, 93.1% of populationSri Lanka: 38.1% of GDP, 0% of populationLesotho: 66.1% of GDP, 0% of populationLithuania: 57.1% of GDP, 0% of populationLuxembourg: 49.8% of GDP, 0.8% of populationLatvia: 62.2% of GDP, 0% of populationMorocco: 46.5% of GDP, 91% of populationMoldova: 51.3% of GDP, 0% of populationMexico: 38.1% of GDP, 0.8% of populationNorth Macedonia: 52.5% of GDP, 0% of populationMalta: 45.9% of GDP, 95.8% of populationMongolia: 40.6% of GDP, 0% of populationMozambique: 54% of GDP, 0% of populationMauritania: 40.4% of GDP, 0% of populationMauritius: 45.6% of GDP, 0% of populationMalaysia: 39.7% of GDP, 0% of populationNamibia: 52.9% of GDP, 0% of populationNiger: 39.1% of GDP, 1.9% of populationNigeria: 31.2% of GDP, 0% of populationNicaragua: 52% of GDP, 0% of populationNetherlands: 55.9% of GDP, 1% of populationNorway: 38.4% of GDP, 0% of populationNew Zealand: 55.4% of GDP, 0% of populationOman: 30.3% of GDP, 81.4% of populationPanama: 32.8% of GDP, 0.6% of populationPeru: 40.1% of GDP, 0% of populationPhilippines: 44.9% of GDP, 0% of populationPoland: 54.8% of GDP, 0% of populationPortugal: 61.7% of GDP, 0% of populationParaguay: 44.5% of GDP, 0% of populationQatar: 17.7% of GDP, 61.8% of populationRomania: 50% of GDP, 0% of populationRussian Federation: 52.9% of GDP, 0% of populationRwanda: 74.1% of GDP, 0% of populationSaudi Arabia: 28% of GDP, 95.4% of populationSudan: 63.5% of GDP, 1.2% of populationSenegal: 52.3% of GDP, 0.5% of populationSingapore: 43.9% of GDP, 0% of populationSierra Leone: 59.6% of GDP, 0% of populationEl Salvador: 52.1% of GDP, 0% of populationSlovak Republic: 53.2% of GDP, 0% of populationSlovenia: 63.3% of GDP, 0% of populationSweden: 61% of GDP, 0% of populationEswatini: 61.2% of GDP, 0% of populationChad: 48.5% of GDP, 0% of populationTogo: 50.1% of GDP, 0% of populationThailand: 43.8% of GDP, 0% of populationTajikistan: 43.6% of GDP, 0% of populationTrinidad and Tobago: 33.8% of GDP, 0% of populationTunisia: 56.1% of GDP, 100% of populationTurkiye: 42.6% of GDP, 0.7% of populationTanzania: 58.3% of GDP, 0% of populationUkraine: 55.8% of GDP, 0% of populationUruguay: 51.9% of GDP, 0% of populationUnited States: 56.8% of GDP, 0.551% of populationUzbekistan: 37.9% of GDP, 0% of populationSouth Africa: 54.3% of GDP, 0% of populationZambia: 30% of GDP, 0% of populationZimbabwe: 53.3% of GDP, 0% of populationAGOALBBHRBIHCAFGABJORKWTMLTRWASAUTUN

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.3458.1e-5125
By rank (Spearman), not adjusted-0.2450.006125
Standard (Pearson), adjusted for national income-0.3516.4e-5125
By rank (Spearman), adjusted for national income-0.2740.002125

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 125 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: -0.006 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.383 (without TUN) to -0.315 (without KWT). 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: KWT (+0.036).

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
East Asia & Pacific14+0.17
Europe & Central Asia44+0.07
Latin America & Caribbean19+0.20
Middle East, North Africa, Afghanistan & Pakistan14-0.09
Sub-Saharan Africa30-0.10

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 third42-0.14
Middle third41-0.21
Richest third42-0.75

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
Christians77-0.07
Muslims32-0.20

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
France15+0.16
Never a European colony16-0.64
Spain18-0.15
United Kingdom32-0.47

By official ideology

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
Nationalist18-0.66
No strong official ideology88-0.19

By party system

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
A few parties banned17-0.50
No parties banned95-0.03

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 = -0.164 after dropping 27 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 GDP
% of population		Years
Rwanda RWA74.1%0%2023, 2000
Albania ALB70.5%0%2023, 2000
Bosnia and Herzegovina BIH67.1%0%2023, 2000
Lesotho LSO66.1%0%2023, 2000
Canada CAN65.9%0.9%2023, 2000
Switzerland CHE65.3%0%2023, 2000
Cameroon CMR64.4%0%2023, 2000
Germany DEU63.7%0%2023, 2000
Sudan SDN63.5%1.2%2023, 2000
Slovenia SVN63.3%0%2023, 2000
France FRA63.1%4.8%2023, 2000
Cabo Verde CPV62.6%0%2023, 2000
Latvia LVA62.2%0%2023, 2000
Portugal PRT61.7%0%2023, 2000
Benin BEN61.7%0%2023, 2000

Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table", American Economic Review, 105(10), 3150-3182, www.ggdc.net/pwt. Data: Penn World Table version 11.0, Groningen Growth and Development Centre, doi:10.34894/FABVLR.
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).

Sources

Labor share of income

Labor share of GDP (Penn World Table)

Groningen Growth and Development Centre, University of Groningen · via DataverseNL · CC BY 4.0 · updated irregular (new versions every few years)

The share of a country's income (GDP) that is paid to people for their work: wages, salaries and benefits, plus an estimate of what the self-employed, such as farmers and shopkeepers, earn for their work. The rest goes to the owners of land, buildings and machines as profit, rent and interest. Where there is little data on the self-employed, the Penn World Table fills in a value by a fixed rule, so figures for poorer countries are rougher, and a few countries show the same value every year. No "better" direction is set.

Middle Eastern ancestry

Middle Eastern and North 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 the Middle East or North 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.

How this was computed

Data used: most recent value in 2010-2025; values come from 2000–2023. 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 18,622 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated V-Dem v16; V-Party v2. How the country data works · explore Labor share of income and Middle Eastern ancestry

This page shows that two measures go together. It does not show that Labor share of income changes Middle Eastern ancestry, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Labor share of income or Middle Eastern ancestry