placestats

Free and fair elections vs. Infant mortality

Fades after adjusting for income

Across 167 countries, Free and fair elections and Infant mortality rise and fall together at r = -0.57 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.20, which could easily be chance (q = 0.20, allowing for the many pairs tested, and allowing for countries in the same region being alike). So the first figure mostly shows richer countries differing from poorer ones, not a link between these two things.

Comparing countries across the middle half of free and fair elections, 0.231 to 0.873 points, infant mortality is better by 18.8 per 1,000 live births at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 4.59 per 1,000 live births.

Link before adjusting (r)-0.569p = 1.0e-15 · 167 countries
After adjusting for national income-0.197p = 0.011 · likely range [-0.34, -0.05]
p, allowing for regions0.058standard error 0.084 · 7 regions
Check for luck (q)0.197across 12,497 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
Infant mortality · per 1,000 live birthslink with income -0.86 · proxy

Both of these rise and fall closely with national income, so a strong link between them before adjusting was close to certain. Read the adjusted figure, not the first one.

“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) →Infant mortality · per 1,000 live births →00.9681.569.8Afghanistan: 0 index (0-1), 48.3 per 1,000 live birthsAngola: 0.293 index (0-1), 32.1 per 1,000 live birthsAlbania: 0.467 index (0-1), 8.3 per 1,000 live birthsUnited Arab Emirates: 0.543 index (0-1), 3.8 per 1,000 live birthsArgentina: 0.878 index (0-1), 8 per 1,000 live birthsArmenia: 0.673 index (0-1), 8.5 per 1,000 live birthsAustralia: 0.962 index (0-1), 3.1 per 1,000 live birthsAustria: 0.938 index (0-1), 2.8 per 1,000 live birthsAzerbaijan: 0.111 index (0-1), 12.5 per 1,000 live birthsBurundi: 0.107 index (0-1), 30.5 per 1,000 live birthsBelgium: 0.968 index (0-1), 3.1 per 1,000 live birthsBenin: 0.638 index (0-1), 45.2 per 1,000 live birthsBurkina Faso: 0 index (0-1), 43.6 per 1,000 live birthsBangladesh: 0 index (0-1), 24.4 per 1,000 live birthsBulgaria: 0.64 index (0-1), 4.6 per 1,000 live birthsBahrain: 0.274 index (0-1), 7.3 per 1,000 live birthsBosnia and Herzegovina: 0.511 index (0-1), 5.5 per 1,000 live birthsBelarus: 0.194 index (0-1), 1.8 per 1,000 live birthsBolivia: 0.765 index (0-1), 14.2 per 1,000 live birthsBrazil: 0.838 index (0-1), 12.3 per 1,000 live birthsBarbados: 0.875 index (0-1), 9.1 per 1,000 live birthsBhutan: 0.865 index (0-1), 13.7 per 1,000 live birthsBotswana: 0.803 index (0-1), 32.1 per 1,000 live birthsCentral African Republic: 0.123 index (0-1), 58.8 per 1,000 live birthsCanada: 0.944 index (0-1), 4.7 per 1,000 live birthsSwitzerland: 0.942 index (0-1), 3.4 per 1,000 live birthsChile: 0.956 index (0-1), 5.8 per 1,000 live birthsChina: 0 index (0-1), 4.1 per 1,000 live birthsCote d'Ivoire: 0.333 index (0-1), 44.8 per 1,000 live birthsCameroon: 0.12 index (0-1), 40.2 per 1,000 live birthsCongo, Dem. Rep.: 0.18 index (0-1), 56.4 per 1,000 live birthsCongo, Rep.: 0.076 index (0-1), 27 per 1,000 live birthsColombia: 0.756 index (0-1), 10.5 per 1,000 live birthsComoros: 0.183 index (0-1), 35 per 1,000 live birthsCabo Verde: 0.836 index (0-1), 10.6 per 1,000 live birthsCosta Rica: 0.944 index (0-1), 9.1 per 1,000 live birthsCyprus: 0.909 index (0-1), 4.1 per 1,000 live birthsCzechia: 0.94 index (0-1), 2.1 per 1,000 live birthsGermany: 0.957 index (0-1), 3.1 per 1,000 live birthsDjibouti: 0.167 index (0-1), 43 per 1,000 live birthsDenmark: 0.961 index (0-1), 3.5 per 1,000 live birthsDominican Republic: 0.768 index (0-1), 27.7 per 1,000 live birthsAlgeria: 0.307 index (0-1), 19.5 per 1,000 live birthsEcuador: 0.827 index (0-1), 10.9 per 1,000 live birthsEgypt, Arab Rep.: 0.137 index (0-1), 20.8 per 1,000 live birthsSpain: 0.956 index (0-1), 2.6 per 1,000 live birthsEstonia: 0.952 index (0-1), 1.5 per 1,000 live birthsEthiopia: 0.324 index (0-1), 34.5 per 1,000 live birthsFinland: 0.961 index (0-1), 1.9 per 1,000 live birthsFiji: 0.54 index (0-1), 23.5 per 1,000 live birthsFrance: 0.941 index (0-1), 3.4 per 1,000 live birthsGabon: 0.186 index (0-1), 25.9 per 1,000 live birthsUnited Kingdom: 0.924 index (0-1), 4.1 per 1,000 live birthsGeorgia: 0.32 index (0-1), 7.5 per 1,000 live birthsGhana: 0.709 index (0-1), 27.5 per 1,000 live birthsGuinea: 0.002 index (0-1), 59.8 per 1,000 live birthsGambia, The: 0.777 index (0-1), 32.7 per 1,000 live birthsGuinea-Bissau: 0 index (0-1), 42.1 per 1,000 live birthsEquatorial Guinea: 0.078 index (0-1), 47.6 per 1,000 live birthsGreece: 0.944 index (0-1), 3.2 per 1,000 live birthsGuatemala: 0.666 index (0-1), 17.2 per 1,000 live birthsGuyana: 0.489 index (0-1), 23.2 per 1,000 live birthsHonduras: 0.351 index (0-1), 12.8 per 1,000 live birthsCroatia: 0.875 index (0-1), 4.1 per 1,000 live birthsHaiti: 0 index (0-1), 39 per 1,000 live birthsHungary: 0.597 index (0-1), 3.1 per 1,000 live birthsIndonesia: 0.518 index (0-1), 15.2 per 1,000 live birthsIndia: 0.495 index (0-1), 23.3 per 1,000 live birthsIreland: 0.945 index (0-1), 3.4 per 1,000 live birthsIran, Islamic Rep.: 0.235 index (0-1), 10.3 per 1,000 live birthsIraq: 0.372 index (0-1), 20.1 per 1,000 live birthsIceland: 0.929 index (0-1), 2.1 per 1,000 live birthsIsrael: 0.873 index (0-1), 2.7 per 1,000 live birthsItaly: 0.945 index (0-1), 2.3 per 1,000 live birthsJamaica: 0.884 index (0-1), 16.4 per 1,000 live birthsJordan: 0.592 index (0-1), 12 per 1,000 live birthsJapan: 0.937 index (0-1), 1.8 per 1,000 live birthsKazakhstan: 0.339 index (0-1), 7.4 per 1,000 live birthsKenya: 0.493 index (0-1), 34.2 per 1,000 live birthsKyrgyz Republic: 0.426 index (0-1), 14.8 per 1,000 live birthsCambodia: 0.092 index (0-1), 16.4 per 1,000 live birthsKorea, Rep.: 0.935 index (0-1), 2.3 per 1,000 live birthsKuwait: 0 index (0-1), 7 per 1,000 live birthsLao PDR: 0.236 index (0-1), 27.2 per 1,000 live birthsLebanon: 0.307 index (0-1), 15.3 per 1,000 live birthsLiberia: 0.592 index (0-1), 63.2 per 1,000 live birthsLibya: 0 index (0-1), 7.9 per 1,000 live birthsSri Lanka: 0.914 index (0-1), 5.2 per 1,000 live birthsLesotho: 0.785 index (0-1), 56.3 per 1,000 live birthsLithuania: 0.882 index (0-1), 2.8 per 1,000 live birthsLuxembourg: 0.944 index (0-1), 1.9 per 1,000 live birthsLatvia: 0.92 index (0-1), 2.2 per 1,000 live birthsMorocco: 0.455 index (0-1), 14.7 per 1,000 live birthsMoldova: 0.662 index (0-1), 15.1 per 1,000 live birthsMadagascar: 0.183 index (0-1), 43 per 1,000 live birthsMaldives: 0.643 index (0-1), 4.7 per 1,000 live birthsMexico: 0.545 index (0-1), 12.1 per 1,000 live birthsNorth Macedonia: 0.701 index (0-1), 2.5 per 1,000 live birthsMali: 0 index (0-1), 47.5 per 1,000 live birthsMalta: 0.903 index (0-1), 4.7 per 1,000 live birthsMyanmar: 0 index (0-1), 32.8 per 1,000 live birthsMontenegro: 0.608 index (0-1), 1.9 per 1,000 live birthsMongolia: 0.586 index (0-1), 11.2 per 1,000 live birthsMozambique: 0.089 index (0-1), 43.7 per 1,000 live birthsMauritania: 0.288 index (0-1), 30.2 per 1,000 live birthsMauritius: 0.865 index (0-1), 13.8 per 1,000 live birthsMalawi: 0.596 index (0-1), 38 per 1,000 live birthsMalaysia: 0.598 index (0-1), 7 per 1,000 live birthsNamibia: 0.604 index (0-1), 36.4 per 1,000 live birthsNiger: 0 index (0-1), 65.6 per 1,000 live birthsNigeria: 0.355 index (0-1), 69.8 per 1,000 live birthsNicaragua: 0.137 index (0-1), 9.4 per 1,000 live birthsNetherlands: 0.954 index (0-1), 3.4 per 1,000 live birthsNorway: 0.966 index (0-1), 2 per 1,000 live birthsNepal: 0.693 index (0-1), 22.2 per 1,000 live birthsNew Zealand: 0.954 index (0-1), 4 per 1,000 live birthsOman: 0.689 index (0-1), 8.3 per 1,000 live birthsPakistan: 0.174 index (0-1), 48.2 per 1,000 live birthsPanama: 0.84 index (0-1), 12 per 1,000 live birthsPeru: 0.861 index (0-1), 11 per 1,000 live birthsPhilippines: 0.271 index (0-1), 21.7 per 1,000 live birthsPapua New Guinea: 0.27 index (0-1), 31.3 per 1,000 live birthsPoland: 0.825 index (0-1), 3.6 per 1,000 live birthsPortugal: 0.94 index (0-1), 2.7 per 1,000 live birthsParaguay: 0.633 index (0-1), 14.5 per 1,000 live birthsQatar: 0 index (0-1), 4.8 per 1,000 live birthsRomania: 0.658 index (0-1), 6 per 1,000 live birthsRussian Federation: 0.135 index (0-1), 4.1 per 1,000 live birthsRwanda: 0.227 index (0-1), 29.4 per 1,000 live birthsSaudi Arabia: 0 index (0-1), 4.7 per 1,000 live birthsSudan: 0 index (0-1), 42.9 per 1,000 live birthsSenegal: 0.701 index (0-1), 28.9 per 1,000 live birthsSingapore: 0.782 index (0-1), 2.2 per 1,000 live birthsSolomon Islands: 0.748 index (0-1), 16.4 per 1,000 live birthsSierra Leone: 0.319 index (0-1), 54.6 per 1,000 live birthsEl Salvador: 0.307 index (0-1), 8.8 per 1,000 live birthsSomalia, Fed. Rep.: 0 index (0-1), 65.4 per 1,000 live birthsSerbia: 0.212 index (0-1), 4.6 per 1,000 live birthsSao Tome and Principe: 0.753 index (0-1), 9.2 per 1,000 live birthsSuriname: 0.864 index (0-1), 14.8 per 1,000 live birthsSlovak Republic: 0.938 index (0-1), 5.3 per 1,000 live birthsSlovenia: 0.916 index (0-1), 1.8 per 1,000 live birthsSweden: 0.945 index (0-1), 2 per 1,000 live birthsEswatini: 0.376 index (0-1), 42.2 per 1,000 live birthsSeychelles: 0.884 index (0-1), 12.9 per 1,000 live birthsSyrian Arab Republic: 0 index (0-1), 17.7 per 1,000 live birthsChad: 0.079 index (0-1), 56.3 per 1,000 live birthsTogo: 0.309 index (0-1), 34.8 per 1,000 live birthsThailand: 0.457 index (0-1), 7.7 per 1,000 live birthsTajikistan: 0.094 index (0-1), 23.5 per 1,000 live birthsTurkmenistan: 0.071 index (0-1), 30.4 per 1,000 live birthsTimor-Leste: 0.857 index (0-1), 34.6 per 1,000 live birthsTrinidad and Tobago: 0.872 index (0-1), 17 per 1,000 live birthsTunisia: 0.445 index (0-1), 9.7 per 1,000 live birthsTurkiye: 0.417 index (0-1), 8 per 1,000 live birthsTanzania: 0.364 index (0-1), 28.7 per 1,000 live birthsUganda: 0.129 index (0-1), 35.9 per 1,000 live birthsUkraine: 0.604 index (0-1), 7.6 per 1,000 live birthsUruguay: 0.947 index (0-1), 6.2 per 1,000 live birthsUnited States: 0.902 index (0-1), 5.5 per 1,000 live birthsUzbekistan: 0.304 index (0-1), 12.8 per 1,000 live birthsViet Nam: 0.527 index (0-1), 12 per 1,000 live birthsVanuatu: 0.853 index (0-1), 14.4 per 1,000 live birthsKosovo: 0.699 index (0-1), 8 per 1,000 live birthsSouth Africa: 0.849 index (0-1), 24.2 per 1,000 live birthsZambia: 0.461 index (0-1), 34.6 per 1,000 live birthsZimbabwe: 0.171 index (0-1), 62.4 per 1,000 live birthsCHNESTFINGINLBRLSONERNGANORQATSAUSOM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5691.0e-15167
By rank (Spearman), not adjusted-0.6343.8e-20167
Standard (Pearson), adjusted for national income-0.1970.011167
By rank (Spearman), adjusted for national income-0.2360.002167

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 167 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: +0.372 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.221 (without LSO) to -0.173 (without SLB). 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: LSO (-0.025).

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 & Pacific20-0.27
Europe & Central Asia49-0.33
Latin America & Caribbean23-0.36
Middle East, North Africa, Afghanistan & Pakistan21-0.21
Sub-Saharan Africa46-0.35

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 third56-0.24
Middle third55-0.17
Richest third56-0.25

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
Christians99-0.18
Muslims48-0.30

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
France25-0.15
Never a European colony21-0.06
Spain19-0.56
United Kingdom49-0.26

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 = -0.201 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 35years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Within countries over time, there is no link that is clearly more than chance (r = -0.090, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose free and fair elections moved did not tend to see their infant mortality move with it.

Across countries (adjusted)-0.197for comparison
Within countries-0.244each country vs itself
…and vs the same year elsewhere-0.090q = 0.304 · 173 countries
Year-on-year changes-0.004q = 0.672

6,036 country-years (one country in one year), 173 countries, 1990–2024, about 35 years each on average. Share of the variation that happens within countries over time: 16% for Free and fair elections, 23% for Infant mortality. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

0.10−0.1-100+10years Infant mortality trails Free and fair elections →lag -10: r = -0.045 (n = 4,498)lag -9: r = -0.062 (n = 4,671)lag -8: r = -0.069 (n = 4,843)lag -7: r = -0.076 (n = 5,014)lag -6: r = -0.088 (n = 5,185)lag -5: r = -0.090 (n = 5,356)lag -4: r = -0.092 (n = 5,527)lag -3: r = -0.092 (n = 5,698)lag -2: r = -0.092 (n = 5,869)lag -1: r = -0.087 (n = 6,040)lag +0: r = -0.090 (n = 6,036)lag +1: r = -0.086 (n = 5,863)lag +2: r = -0.077 (n = 5,690)lag +3: r = -0.074 (n = 5,517)lag +4: r = -0.073 (n = 5,344)lag +5: r = -0.076 (n = 5,171)lag +6: r = -0.068 (n = 4,998)lag +7: r = -0.061 (n = 4,825)lag +8: r = -0.053 (n = 4,652)lag +9: r = -0.050 (n = 4,479)lag +10: r = -0.044 (n = 4,306)

Same year (lag 0): -0.090. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

The data


index (0-1)

per 1,000 live births
Years
Belgium BEL0.9683.12025, 2024
Norway NOR0.96622025, 2024
Australia AUS0.9623.12025, 2024
Finland FIN0.9611.92025, 2024
Denmark DNK0.9613.52025, 2024
Germany DEU0.9573.12025, 2024
Spain ESP0.9562.62025, 2024
Chile CHL0.9565.82025, 2024
New Zealand NZL0.95442025, 2024
Netherlands NLD0.9543.42025, 2024
Estonia EST0.9521.52025, 2024
Uruguay URY0.9476.22025, 2024
Sweden SWE0.94522025, 2024
Italy ITA0.9452.32025, 2024
Ireland IRL0.9453.42025, 2024

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

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.

Infant mortality

Mortality rate, infant (per 1,000 live births)

World Bank · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2024–2025. 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 12,497 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 Infant mortality

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

More links with Free and fair elections or Infant mortality