placestats

Indigenous American ancestry vs. Marriage rate (UN)

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 81 countries, Indigenous American ancestry and Marriage rate (UN) rise and fall together at r = -0.28 (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 = -0.39, q = 0.0080, allowing for the many pairs tested).

Link before adjusting (r)-0.277p = 0.012 · 81 countries
After adjusting for national income-0.388p = 0.000 · likely range [-0.56, -0.18]
p, allowing for regions0.000standard error 0.049 · 7 regions
Check for luck (q)0.008across 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.

Indigenous American ancestry · % of populationlink with income +0.11 · independent
Marriage rate (UN) · marriages per 1,000 peoplelink with income -0.21 · 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

Indigenous American ancestry · % of population →Marriage rate (UN) · marriages per 1,000 people →0%73.9%1.298.97Albania: 0% of population, 6.74 marriages per 1,000 peopleArgentina: 5% of population, 2.84 marriages per 1,000 peopleArmenia: 0% of population, 5.12 marriages per 1,000 peopleAustralia: 0% of population, 4.44 marriages per 1,000 peopleAustria: 0% of population, 5 marriages per 1,000 peopleAzerbaijan: 0% of population, 4.86 marriages per 1,000 peopleBelgium: 0% of population, 3.96 marriages per 1,000 peopleBulgaria: 0% of population, 3.2 marriages per 1,000 peopleBosnia and Herzegovina: 0% of population, 5.43 marriages per 1,000 peopleBelarus: 0% of population, 5.05 marriages per 1,000 peopleCanada: 3.27% of population, 2.59 marriages per 1,000 peopleSwitzerland: 0% of population, 4.21 marriages per 1,000 peopleChile: 37.3% of population, 3.04 marriages per 1,000 peopleCabo Verde: 0% of population, 4.78 marriages per 1,000 peopleCosta Rica: 29.7% of population, 4.17 marriages per 1,000 peopleCyprus: 0% of population, 7.34 marriages per 1,000 peopleCzechia: 0% of population, 4.09 marriages per 1,000 peopleGermany: 0% of population, 4.18 marriages per 1,000 peopleDenmark: 0% of population, 5.51 marriages per 1,000 peopleDominican Republic: 3.6% of population, 4.11 marriages per 1,000 peopleEgypt, Arab Rep.: 0% of population, 8.97 marriages per 1,000 peopleSpain: 0% of population, 3.57 marriages per 1,000 peopleEstonia: 0% of population, 4.63 marriages per 1,000 peopleFinland: 0% of population, 3.81 marriages per 1,000 peopleFiji: 0% of population, 8.26 marriages per 1,000 peopleFrance: 0% of population, 3.64 marriages per 1,000 peopleUnited Kingdom: 0% of population, 1.29 marriages per 1,000 peopleGeorgia: 0% of population, 5.86 marriages per 1,000 peopleGreece: 0% of population, 3.52 marriages per 1,000 peopleGuatemala: 73.9% of population, 4.21 marriages per 1,000 peopleGuyana: 5% of population, 5.38 marriages per 1,000 peopleHong Kong SAR, China: 0% of population, 6.33 marriages per 1,000 peopleCroatia: 0% of population, 4.46 marriages per 1,000 peopleHungary: 0% of population, 4.86 marriages per 1,000 peopleIreland: 0% of population, 3.8 marriages per 1,000 peopleIran, Islamic Rep.: 0% of population, 6.77 marriages per 1,000 peopleIsrael: 0% of population, 4.9 marriages per 1,000 peopleItaly: 0% of population, 3.12 marriages per 1,000 peopleJamaica: 0% of population, 6.13 marriages per 1,000 peopleJordan: 0% of population, 5.65 marriages per 1,000 peopleJapan: 0% of population, 3.81 marriages per 1,000 peopleKazakhstan: 0% of population, 6.13 marriages per 1,000 peopleKyrgyz Republic: 0% of population, 6.24 marriages per 1,000 peopleKorea, Rep.: 0% of population, 4.36 marriages per 1,000 peopleKuwait: 0% of population, 2.78 marriages per 1,000 peopleSri Lanka: 0% of population, 6.87 marriages per 1,000 peopleLithuania: 0% of population, 4.47 marriages per 1,000 peopleLuxembourg: 0% of population, 3.82 marriages per 1,000 peopleLatvia: 0% of population, 5.45 marriages per 1,000 peopleMoldova: 0% of population, 6.1 marriages per 1,000 peopleMexico: 62.5% of population, 3.81 marriages per 1,000 peopleNorth Macedonia: 0% of population, 6.03 marriages per 1,000 peopleMalta: 0% of population, 4.33 marriages per 1,000 peopleMongolia: 0% of population, 4.04 marriages per 1,000 peopleMauritius: 0% of population, 6.6 marriages per 1,000 peopleMalaysia: 0% of population, 5.63 marriages per 1,000 peopleNicaragua: 40% of population, 4.33 marriages per 1,000 peopleNetherlands: 0% of population, 3.83 marriages per 1,000 peopleNorway: 0% of population, 3.81 marriages per 1,000 peopleNew Zealand: 0% of population, 3.41 marriages per 1,000 peoplePanama: 35.7% of population, 1.74 marriages per 1,000 peoplePeru: 64.2% of population, 1.97 marriages per 1,000 peoplePoland: 0% of population, 3.7 marriages per 1,000 peoplePuerto Rico (US): 17.9% of population, 3.7 marriages per 1,000 peoplePortugal: 0.06% of population, 3.53 marriages per 1,000 peopleQatar: 0% of population, 1.34 marriages per 1,000 peopleRomania: 0% of population, 5.32 marriages per 1,000 peopleRussian Federation: 0% of population, 8.54 marriages per 1,000 peopleSudan: 0% of population, 4.6 marriages per 1,000 peopleSingapore: 0% of population, 6.3 marriages per 1,000 peopleSlovak Republic: 0% of population, 4.88 marriages per 1,000 peopleSlovenia: 0% of population, 2.99 marriages per 1,000 peopleSweden: 0% of population, 4.25 marriages per 1,000 peopleTajikistan: 0% of population, 8.8 marriages per 1,000 peopleTrinidad and Tobago: 0% of population, 5.3 marriages per 1,000 peopleTurkiye: 0% of population, 6.65 marriages per 1,000 peopleUkraine: 0% of population, 5.17 marriages per 1,000 peopleUruguay: 4% of population, 2.78 marriages per 1,000 peopleUnited States: 9.53% of population, 6.1 marriages per 1,000 peopleUzbekistan: 0% of population, 7.31 marriages per 1,000 peopleViet Nam: 0% of population, 6.17 marriages per 1,000 peopleEGYGBRGTMKWTMEXPERQATRUSTJK

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.2770.01281
By rank (Spearman), not adjusted-0.3680.00181
Standard (Pearson), adjusted for national income-0.3880.00081
By rank (Spearman), adjusted for national income-0.4493.0e-581

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 81 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: -0.111 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.430 (without SDN) to -0.318 (without PER). 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: PER (+0.071).

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 Asia44-0.16
Latin America & Caribbean14-0.48

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 third27-0.54
Middle third27-0.53
Richest third27+0.24

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
Christians53-0.42

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
United Kingdom19+0.08

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 = -0.387 after dropping 1 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
marriages per 1,000 people		Years
Guatemala GTM73.9%4.212000, 2023
Peru PER64.2%1.972000, 2023
Mexico MEX62.5%3.812000, 2023
Nicaragua NIC40%4.332000, 2023
Chile CHL37.3%3.042000, 2024
Panama PAN35.7%1.742000, 2024
Costa Rica CRI29.7%4.172000, 2024
Puerto Rico (US) PRI17.9%3.72000, 2024
United States USA9.53%6.12000, 2023
Guyana GUY5%5.382000, 2017
Argentina ARG5%2.842000, 2023
Uruguay URY4%2.782000, 2022
Dominican Republic DOM3.6%4.112000, 2024
Canada CAN3.27%2.592000, 2020
Portugal PRT0.06%3.532000, 2023

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).
United Nations Statistics Division, Demographic Yearbook, 2017 to 2024 editions: tables of marriages and crude marriage rates, and of divorces and crude divorce rates, by urban/rural residence.

Sources

Indigenous American ancestry

Indigenous American 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 Americas, whose people in 1500 were all Indigenous. 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.

Marriage rate (UN)

Crude marriage rate, countries with complete registration

United Nations Statistics Division · UNdata terms of use · updated annual (each edition covers the latest five years)

Marriages registered in the year per 1,000 people, from each country's civil register, as published in the UN Demographic Yearbook. Only countries whose register the UN rates as at least 90% complete are included. That leaves out most of Africa and much of South Asia, where many marriages are religious or customary and never registered, so the countries here lean toward places with strong record-keeping. Countries whose figures include visitors' weddings (Seychelles, about 30 per 1,000, and the Bahamas) are left out, since they show a wedding industry rather than how often residents marry. So is Equatorial Guinea, whose register is far too thin to be complete. Each yearly edition covers five years; where they overlap, the newest is used, since countries revise. Where both exist it matches the OECD series almost exactly (r = 0.998), so the two are treated as one measure, not two findings. The low points in 2020 are the pandemic. A few small island territories, such as the Turks and Caicos Islands (11 to 16 per 1,000), probably count visitors' weddings without saying so. No "better" direction is set: it describes how people live.

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 Indigenous American ancestry and Marriage rate (UN)

This page shows that two measures go together. It does not show that Indigenous American ancestry changes Marriage rate (UN), or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Indigenous American ancestry or Marriage rate (UN)