placestats

Free and fair elections 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 156 countries, Free and fair elections and Middle Eastern ancestry rise and fall together at r = -0.20 (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 = 0.0018, 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 0.35% of population, free and fair elections is worse by 0.0008 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.00113 points.

Link before adjusting (r)-0.201p = 0.012 · 156 countries
After adjusting for national income-0.352p = 7.0e-6 · likely range [-0.48, -0.21]
p, allowing for regions0.215standard error 0.254 · 7 regions
Check for luck (q)0.002across 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.

Free and fair elections · index (0-1)link with income +0.61 · high
Middle Eastern ancestry · % of populationlink with income +0.16 · independent

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

Every country as a dot

Free and fair elections · index (0-1) →Middle Eastern ancestry · % of population →00.9680%100%Afghanistan: 0 index (0-1), 1% of populationAngola: 0.293 index (0-1), 0% of populationAlbania: 0.467 index (0-1), 0% of populationUnited Arab Emirates: 0.543 index (0-1), 100% of populationArgentina: 0.878 index (0-1), 3% of populationArmenia: 0.673 index (0-1), 0% of populationAustralia: 0.962 index (0-1), 2.5% of populationAustria: 0.938 index (0-1), 0% of populationAzerbaijan: 0.111 index (0-1), 1% of populationBurundi: 0.107 index (0-1), 0% of populationBelgium: 0.968 index (0-1), 1.6% of populationBenin: 0.638 index (0-1), 0% of populationBurkina Faso: 0 index (0-1), 0% of populationBangladesh: 0 index (0-1), 0% of populationBulgaria: 0.64 index (0-1), 0% of populationBahrain: 0.274 index (0-1), 100% of populationBosnia and Herzegovina: 0.511 index (0-1), 0% of populationBelarus: 0.194 index (0-1), 0% of populationBolivia: 0.765 index (0-1), 0% of populationBrazil: 0.838 index (0-1), 0% of populationBhutan: 0.865 index (0-1), 0% of populationBotswana: 0.803 index (0-1), 0% of populationCentral African Republic: 0.123 index (0-1), 0% of populationCanada: 0.944 index (0-1), 0.9% of populationSwitzerland: 0.942 index (0-1), 0% of populationChile: 0.956 index (0-1), 2% of populationChina: 0 index (0-1), 0% of populationCote d'Ivoire: 0.333 index (0-1), 0.7% of populationCameroon: 0.12 index (0-1), 0% of populationCongo, Dem. Rep.: 0.18 index (0-1), 0% of populationCongo, Rep.: 0.076 index (0-1), 0% of populationColombia: 0.756 index (0-1), 0% of populationComoros: 0.183 index (0-1), 0% of populationCabo Verde: 0.836 index (0-1), 0% of populationCosta Rica: 0.944 index (0-1), 0% of populationCyprus: 0.909 index (0-1), 0% of populationCzechia: 0.94 index (0-1), 0% of populationGermany: 0.957 index (0-1), 0% of populationDenmark: 0.961 index (0-1), 0% of populationDominican Republic: 0.768 index (0-1), 0% of populationAlgeria: 0.307 index (0-1), 100% of populationEcuador: 0.827 index (0-1), 0% of populationEgypt, Arab Rep.: 0.137 index (0-1), 94.5% of populationSpain: 0.956 index (0-1), 0.3% of populationEstonia: 0.952 index (0-1), 0% of populationEthiopia: 0.324 index (0-1), 0% of populationFinland: 0.961 index (0-1), 0% of populationFiji: 0.54 index (0-1), 0% of populationFrance: 0.941 index (0-1), 4.8% of populationGabon: 0.186 index (0-1), 0% of populationUnited Kingdom: 0.924 index (0-1), 0% of populationGeorgia: 0.32 index (0-1), 0% of populationGhana: 0.709 index (0-1), 0% of populationGuinea: 0.002 index (0-1), 0% of populationGambia, The: 0.777 index (0-1), 0% of populationGuinea-Bissau: 0 index (0-1), 0.5% of populationEquatorial Guinea: 0.078 index (0-1), 0% of populationGreece: 0.944 index (0-1), 0% of populationGuatemala: 0.666 index (0-1), 0% of populationGuyana: 0.489 index (0-1), 0% of populationHong Kong SAR, China: 0.286 index (0-1), 0% of populationHonduras: 0.351 index (0-1), 0% of populationCroatia: 0.875 index (0-1), 0% of populationHaiti: 0 index (0-1), 0% of populationHungary: 0.597 index (0-1), 0% of populationIndonesia: 0.518 index (0-1), 0% of populationIndia: 0.495 index (0-1), 0% of populationIreland: 0.945 index (0-1), 0% of populationIran, Islamic Rep.: 0.235 index (0-1), 98% of populationIraq: 0.372 index (0-1), 94.4% of populationIsrael: 0.873 index (0-1), 62.7% of populationItaly: 0.945 index (0-1), 0.2% of populationJamaica: 0.884 index (0-1), 0% of populationJordan: 0.592 index (0-1), 98% of populationJapan: 0.937 index (0-1), 0% of populationKazakhstan: 0.339 index (0-1), 0% of populationKenya: 0.493 index (0-1), 0% of populationKyrgyz Republic: 0.426 index (0-1), 0% of populationCambodia: 0.092 index (0-1), 0% of populationKorea, Rep.: 0.935 index (0-1), 0% of populationKuwait: 0 index (0-1), 100% of populationLao PDR: 0.236 index (0-1), 0% of populationLebanon: 0.307 index (0-1), 93.1% of populationLiberia: 0.592 index (0-1), 0% of populationLibya: 0 index (0-1), 96.5% of populationSri Lanka: 0.914 index (0-1), 0% of populationLesotho: 0.785 index (0-1), 0% of populationLithuania: 0.882 index (0-1), 0% of populationLuxembourg: 0.944 index (0-1), 0.8% of populationLatvia: 0.92 index (0-1), 0% of populationMorocco: 0.455 index (0-1), 91% of populationMoldova: 0.662 index (0-1), 0% of populationMadagascar: 0.183 index (0-1), 0% of populationMexico: 0.545 index (0-1), 0.8% of populationNorth Macedonia: 0.701 index (0-1), 0% of populationMali: 0 index (0-1), 0.9% of populationMalta: 0.903 index (0-1), 95.8% of populationMyanmar: 0 index (0-1), 0% of populationMongolia: 0.586 index (0-1), 0% of populationMozambique: 0.089 index (0-1), 0% of populationMauritania: 0.288 index (0-1), 0% of populationMauritius: 0.865 index (0-1), 0% of populationMalawi: 0.596 index (0-1), 0% of populationMalaysia: 0.598 index (0-1), 0% of populationNamibia: 0.604 index (0-1), 0% of populationNiger: 0 index (0-1), 1.9% of populationNigeria: 0.355 index (0-1), 0% of populationNicaragua: 0.137 index (0-1), 0% of populationNetherlands: 0.954 index (0-1), 1% of populationNorway: 0.966 index (0-1), 0% of populationNepal: 0.693 index (0-1), 0% of populationNew Zealand: 0.954 index (0-1), 0% of populationOman: 0.689 index (0-1), 81.4% of populationPakistan: 0.174 index (0-1), 0% of populationPanama: 0.84 index (0-1), 0.6% of populationPeru: 0.861 index (0-1), 0% of populationPhilippines: 0.271 index (0-1), 0% of populationPapua New Guinea: 0.27 index (0-1), 0% of populationPoland: 0.825 index (0-1), 0% of populationPortugal: 0.94 index (0-1), 0% of populationParaguay: 0.633 index (0-1), 0% of populationQatar: 0 index (0-1), 61.8% of populationRomania: 0.658 index (0-1), 0% of populationRussian Federation: 0.135 index (0-1), 0% of populationRwanda: 0.227 index (0-1), 0% of populationSaudi Arabia: 0 index (0-1), 95.4% of populationSudan: 0 index (0-1), 1.2% of populationSenegal: 0.701 index (0-1), 0.5% of populationSingapore: 0.782 index (0-1), 0% of populationSierra Leone: 0.319 index (0-1), 0% of populationEl Salvador: 0.307 index (0-1), 0% of populationSomalia, Fed. Rep.: 0 index (0-1), 1.1% of populationSlovak Republic: 0.938 index (0-1), 0% of populationSlovenia: 0.916 index (0-1), 0% of populationSweden: 0.945 index (0-1), 0% of populationEswatini: 0.376 index (0-1), 0% of populationSyrian Arab Republic: 0 index (0-1), 94.8% of populationChad: 0.079 index (0-1), 0% of populationTogo: 0.309 index (0-1), 0% of populationThailand: 0.457 index (0-1), 0% of populationTajikistan: 0.094 index (0-1), 0% of populationTurkmenistan: 0.071 index (0-1), 0% of populationTimor-Leste: 0.857 index (0-1), 0% of populationTrinidad and Tobago: 0.872 index (0-1), 0% of populationTunisia: 0.445 index (0-1), 100% of populationTurkiye: 0.417 index (0-1), 0.7% of populationTanzania: 0.364 index (0-1), 0% of populationUganda: 0.129 index (0-1), 0% of populationUkraine: 0.604 index (0-1), 0% of populationUruguay: 0.947 index (0-1), 0% of populationUnited States: 0.902 index (0-1), 0.551% of populationUzbekistan: 0.304 index (0-1), 0% of populationViet Nam: 0.527 index (0-1), 0% of populationSouth Africa: 0.849 index (0-1), 0% of populationZambia: 0.461 index (0-1), 0% of populationZimbabwe: 0.171 index (0-1), 0% of populationAREBFABGDCHNDNKFINJORKWTLBYMLTNORSAU

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.2010.012156
By rank (Spearman), not adjusted-0.1030.200156
Standard (Pearson), adjusted for national income-0.3527.0e-6156
By rank (Spearman), adjusted for national income-0.2660.001156

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 156 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: -0.151 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.372 (without JOR) to -0.318 (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 (+0.034).

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 & Pacific19+0.23
Europe & Central Asia45+0.00
Latin America & Caribbean21+0.13
Middle East, North Africa, Afghanistan & Pakistan20+0.07
Sub-Saharan Africa44-0.25

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 third52-0.08
Middle third52-0.36
Richest third52-0.54

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
Christians90+0.02
Muslims45-0.09

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
France24-0.08
Never a European colony21-0.22
Spain19+0.08
United Kingdom45-0.50

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 = -0.023 after dropping 31 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


index (0-1)

% of population
Years
Belgium BEL0.9681.6%2025, 2000
Norway NOR0.9660%2025, 2000
Australia AUS0.9622.5%2025, 2000
Finland FIN0.9610%2025, 2000
Denmark DNK0.9610%2025, 2000
Germany DEU0.9570%2025, 2000
Spain ESP0.9560.3%2025, 2000
Chile CHL0.9562%2025, 2000
New Zealand NZL0.9540%2025, 2000
Netherlands NLD0.9541%2025, 2000
Estonia EST0.9520%2025, 2000
Uruguay URY0.9470%2025, 2000
Sweden SWE0.9450%2025, 2000
Italy ITA0.9450.2%2025, 2000
Ireland IRL0.9450%2025, 2000

Coppedge, M. et al., V-Dem Dataset, Varieties of Democracy (V-Dem) Project
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

Free and fair elections

Free and fair elections index

V-Dem Institute, University of Gothenburg · via Our World in Data · CC BY 4.0 · updated annual

Whether elections are run without voter-registration fraud, widespread irregularities, government threats against the opposition, vote buying or election violence. This asks a narrower question than whether a country is a democracy, and one that is easier to answer. A state can run clean elections while barring the opposition from standing. It can also run dirty elections and still change government. It is the clean-elections part of the electoral democracy index. So its pair with that index, and with liberal and participatory democracy, is built from the same numbers and flagged as such.

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 2000–2025. 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 Free and fair elections and Middle Eastern ancestry

This page shows that two measures go together. It does not show that Free and fair elections changes Middle Eastern ancestry, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Free and fair elections or Middle Eastern ancestry