placestats

Civil society participation 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, Civil society participation and Middle Eastern ancestry rise and fall together at r = -0.27 (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 = -0.31, q = 0.0025, 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, civil society participation is worse by 0.00077 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.00086 points.

Link before adjusting (r)-0.271p = 0.001 · 156 countries
After adjusting for national income-0.305p = 0.000 · likely range [-0.44, -0.16]
p, allowing for regions0.243standard error 0.236 · 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.

Civil society participation · index (0-1)link with income +0.29 · 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

Civil society participation · index (0-1) →Middle Eastern ancestry · % of population →0.0430.9790%100%Afghanistan: 0.043 index (0-1), 1% of populationAngola: 0.433 index (0-1), 0% of populationAlbania: 0.595 index (0-1), 0% of populationUnited Arab Emirates: 0.273 index (0-1), 100% of populationArgentina: 0.707 index (0-1), 3% of populationArmenia: 0.656 index (0-1), 0% of populationAustralia: 0.928 index (0-1), 2.5% of populationAustria: 0.884 index (0-1), 0% of populationAzerbaijan: 0.079 index (0-1), 1% of populationBurundi: 0.314 index (0-1), 0% of populationBelgium: 0.947 index (0-1), 1.6% of populationBenin: 0.632 index (0-1), 0% of populationBurkina Faso: 0.636 index (0-1), 0% of populationBangladesh: 0.696 index (0-1), 0% of populationBulgaria: 0.858 index (0-1), 0% of populationBahrain: 0.245 index (0-1), 100% of populationBosnia and Herzegovina: 0.662 index (0-1), 0% of populationBelarus: 0.112 index (0-1), 0% of populationBolivia: 0.845 index (0-1), 0% of populationBrazil: 0.865 index (0-1), 0% of populationBhutan: 0.694 index (0-1), 0% of populationBotswana: 0.856 index (0-1), 0% of populationCentral African Republic: 0.337 index (0-1), 0% of populationCanada: 0.938 index (0-1), 0.9% of populationSwitzerland: 0.971 index (0-1), 0% of populationChile: 0.775 index (0-1), 2% of populationChina: 0.219 index (0-1), 0% of populationCote d'Ivoire: 0.707 index (0-1), 0.7% of populationCameroon: 0.467 index (0-1), 0% of populationCongo, Dem. Rep.: 0.515 index (0-1), 0% of populationCongo, Rep.: 0.566 index (0-1), 0% of populationColombia: 0.787 index (0-1), 0% of populationComoros: 0.545 index (0-1), 0% of populationCabo Verde: 0.683 index (0-1), 0% of populationCosta Rica: 0.883 index (0-1), 0% of populationCyprus: 0.827 index (0-1), 0% of populationCzechia: 0.777 index (0-1), 0% of populationGermany: 0.979 index (0-1), 0% of populationDenmark: 0.971 index (0-1), 0% of populationDominican Republic: 0.823 index (0-1), 0% of populationAlgeria: 0.302 index (0-1), 100% of populationEcuador: 0.69 index (0-1), 0% of populationEgypt, Arab Rep.: 0.212 index (0-1), 94.5% of populationSpain: 0.891 index (0-1), 0.3% of populationEstonia: 0.89 index (0-1), 0% of populationEthiopia: 0.629 index (0-1), 0% of populationFinland: 0.948 index (0-1), 0% of populationFiji: 0.846 index (0-1), 0% of populationFrance: 0.866 index (0-1), 4.8% of populationGabon: 0.714 index (0-1), 0% of populationUnited Kingdom: 0.889 index (0-1), 0% of populationGeorgia: 0.552 index (0-1), 0% of populationGhana: 0.893 index (0-1), 0% of populationGuinea: 0.531 index (0-1), 0% of populationGambia, The: 0.8 index (0-1), 0% of populationGuinea-Bissau: 0.78 index (0-1), 0.5% of populationEquatorial Guinea: 0.099 index (0-1), 0% of populationGreece: 0.752 index (0-1), 0% of populationGuatemala: 0.761 index (0-1), 0% of populationGuyana: 0.768 index (0-1), 0% of populationHong Kong SAR, China: 0.4 index (0-1), 0% of populationHonduras: 0.754 index (0-1), 0% of populationCroatia: 0.694 index (0-1), 0% of populationHaiti: 0.478 index (0-1), 0% of populationHungary: 0.434 index (0-1), 0% of populationIndonesia: 0.711 index (0-1), 0% of populationIndia: 0.694 index (0-1), 0% of populationIreland: 0.954 index (0-1), 0% of populationIran, Islamic Rep.: 0.154 index (0-1), 98% of populationIraq: 0.697 index (0-1), 94.4% of populationIsrael: 0.803 index (0-1), 62.7% of populationItaly: 0.882 index (0-1), 0.2% of populationJamaica: 0.777 index (0-1), 0% of populationJordan: 0.646 index (0-1), 98% of populationJapan: 0.683 index (0-1), 0% of populationKazakhstan: 0.418 index (0-1), 0% of populationKenya: 0.718 index (0-1), 0% of populationKyrgyz Republic: 0.374 index (0-1), 0% of populationCambodia: 0.268 index (0-1), 0% of populationKorea, Rep.: 0.804 index (0-1), 0% of populationKuwait: 0.473 index (0-1), 100% of populationLao PDR: 0.229 index (0-1), 0% of populationLebanon: 0.811 index (0-1), 93.1% of populationLiberia: 0.899 index (0-1), 0% of populationLibya: 0.631 index (0-1), 96.5% of populationSri Lanka: 0.805 index (0-1), 0% of populationLesotho: 0.742 index (0-1), 0% of populationLithuania: 0.831 index (0-1), 0% of populationLuxembourg: 0.954 index (0-1), 0.8% of populationLatvia: 0.892 index (0-1), 0% of populationMorocco: 0.651 index (0-1), 91% of populationMoldova: 0.787 index (0-1), 0% of populationMadagascar: 0.686 index (0-1), 0% of populationMexico: 0.49 index (0-1), 0.8% of populationNorth Macedonia: 0.541 index (0-1), 0% of populationMali: 0.7 index (0-1), 0.9% of populationMalta: 0.82 index (0-1), 95.8% of populationMyanmar: 0.128 index (0-1), 0% of populationMongolia: 0.677 index (0-1), 0% of populationMozambique: 0.705 index (0-1), 0% of populationMauritania: 0.63 index (0-1), 0% of populationMauritius: 0.854 index (0-1), 0% of populationMalawi: 0.931 index (0-1), 0% of populationMalaysia: 0.755 index (0-1), 0% of populationNamibia: 0.667 index (0-1), 0% of populationNiger: 0.82 index (0-1), 1.9% of populationNigeria: 0.786 index (0-1), 0% of populationNicaragua: 0.114 index (0-1), 0% of populationNetherlands: 0.826 index (0-1), 1% of populationNorway: 0.973 index (0-1), 0% of populationNepal: 0.858 index (0-1), 0% of populationNew Zealand: 0.656 index (0-1), 0% of populationOman: 0.318 index (0-1), 81.4% of populationPakistan: 0.651 index (0-1), 0% of populationPanama: 0.632 index (0-1), 0.6% of populationPeru: 0.706 index (0-1), 0% of populationPhilippines: 0.666 index (0-1), 0% of populationPapua New Guinea: 0.604 index (0-1), 0% of populationPoland: 0.729 index (0-1), 0% of populationPortugal: 0.711 index (0-1), 0% of populationParaguay: 0.484 index (0-1), 0% of populationQatar: 0.181 index (0-1), 61.8% of populationRomania: 0.656 index (0-1), 0% of populationRussian Federation: 0.202 index (0-1), 0% of populationRwanda: 0.402 index (0-1), 0% of populationSaudi Arabia: 0.25 index (0-1), 95.4% of populationSudan: 0.256 index (0-1), 1.2% of populationSenegal: 0.874 index (0-1), 0.5% of populationSingapore: 0.412 index (0-1), 0% of populationSierra Leone: 0.902 index (0-1), 0% of populationEl Salvador: 0.407 index (0-1), 0% of populationSomalia, Fed. Rep.: 0.68 index (0-1), 1.1% of populationSlovak Republic: 0.662 index (0-1), 0% of populationSlovenia: 0.907 index (0-1), 0% of populationSweden: 0.939 index (0-1), 0% of populationEswatini: 0.383 index (0-1), 0% of populationSyrian Arab Republic: 0.347 index (0-1), 94.8% of populationChad: 0.392 index (0-1), 0% of populationTogo: 0.631 index (0-1), 0% of populationThailand: 0.641 index (0-1), 0% of populationTajikistan: 0.153 index (0-1), 0% of populationTurkmenistan: 0.065 index (0-1), 0% of populationTimor-Leste: 0.754 index (0-1), 0% of populationTrinidad and Tobago: 0.907 index (0-1), 0% of populationTunisia: 0.478 index (0-1), 100% of populationTurkiye: 0.355 index (0-1), 0.7% of populationTanzania: 0.793 index (0-1), 0% of populationUganda: 0.698 index (0-1), 0% of populationUkraine: 0.726 index (0-1), 0% of populationUruguay: 0.845 index (0-1), 0% of populationUnited States: 0.963 index (0-1), 0.551% of populationUzbekistan: 0.344 index (0-1), 0% of populationViet Nam: 0.666 index (0-1), 0% of populationSouth Africa: 0.776 index (0-1), 0% of populationZambia: 0.918 index (0-1), 0% of populationZimbabwe: 0.757 index (0-1), 0% of populationAFGAZEBHRDEUDNKEGYIRNIRQLBNMLTNORTKM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.2710.001156
By rank (Spearman), not adjusted-0.1200.134156
Standard (Pearson), adjusted for national income-0.3050.000156
By rank (Spearman), adjusted for national income-0.1770.028156

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: -0.035 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.329 (without LBN) to -0.277 (without IRN). 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: IRN (+0.028).

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
  • 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+0.32
Europe & Central Asia45-0.03
Latin America & Caribbean21-0.13
Middle East, North Africa, Afghanistan & Pakistan20+0.13
Sub-Saharan Africa44+0.07

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 third52-0.24
Richest third52-0.55

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
Christians90+0.01
Muslims45-0.08

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
France24-0.20
Never a European colony21-0.31
Spain19+0.12
United Kingdom45-0.48

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 = +0.040 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
Germany DEU0.9790%2025, 2000
Norway NOR0.9730%2025, 2000
Denmark DNK0.9710%2025, 2000
Switzerland CHE0.9710%2025, 2000
United States USA0.9630.551%2025, 2000
Luxembourg LUX0.9540.8%2025, 2000
Ireland IRL0.9540%2025, 2000
Finland FIN0.9480%2025, 2000
Belgium BEL0.9471.6%2025, 2000
Sweden SWE0.9390%2025, 2000
Canada CAN0.9380.9%2025, 2000
Malawi MWI0.9310%2025, 2000
Australia AUS0.9282.5%2025, 2000
Zambia ZMB0.9180%2025, 2000
Trinidad and Tobago TTO0.9070%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

Civil society participation

Civil society participation index

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

How far governments consult civic groups, and how widely people take part in them. A part of the participatory democracy index.

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 Civil society participation and Middle Eastern ancestry

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

More links with Civil society participation or Middle Eastern ancestry