placestats

Electoral democracy vs. Wellbeing score

Fades after adjusting for income

Across 103 countries, Electoral democracy and Wellbeing score rise and fall together at r = +0.51 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.15, which could easily be chance (q = 0.30, 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. Caution: direction is not consistent across regions.

Comparing countries across the middle half of electoral democracy, 0.287 to 0.786 points, wellbeing score is better by 0.737 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.181 typical gaps.

Link before adjusting (r)+0.513p = 3.0e-8 · 103 countries
After adjusting for national income+0.148p = 0.137 · likely range [-0.05, +0.33]
p, allowing for regions0.117standard error 0.081 · 7 regions
Check for luck (q)0.295across 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.

Electoral democracy · index (0-1)link with income +0.49 · moderate
Wellbeing score · typical gaps (standard deviations)link with income +0.80 · high

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

Every country as a dot

Electoral democracy · index (0-1) →Wellbeing score · typical gaps (standard deviations) →0.0340.913-1.981.89Albania: 0.484 index (0-1), -0.617 typical gaps (standard deviations)Argentina: 0.69 index (0-1), 0.216 typical gaps (standard deviations)Armenia: 0.614 index (0-1), -0.118 typical gaps (standard deviations)Australia: 0.844 index (0-1), 1.25 typical gaps (standard deviations)Austria: 0.839 index (0-1), 1.26 typical gaps (standard deviations)Azerbaijan: 0.171 index (0-1), -0.0603 typical gaps (standard deviations)Belgium: 0.889 index (0-1), 0.818 typical gaps (standard deviations)Burkina Faso: 0.134 index (0-1), -0.476 typical gaps (standard deviations)Bangladesh: 0.195 index (0-1), -0.561 typical gaps (standard deviations)Bulgaria: 0.599 index (0-1), -0.572 typical gaps (standard deviations)Bosnia and Herzegovina: 0.498 index (0-1), -0.087 typical gaps (standard deviations)Belarus: 0.163 index (0-1), 0.732 typical gaps (standard deviations)Bolivia: 0.605 index (0-1), -0.361 typical gaps (standard deviations)Brazil: 0.784 index (0-1), 0.123 typical gaps (standard deviations)Canada: 0.84 index (0-1), 1.06 typical gaps (standard deviations)Switzerland: 0.882 index (0-1), 1.55 typical gaps (standard deviations)Chile: 0.839 index (0-1), 0.19 typical gaps (standard deviations)China: 0.072 index (0-1), 0.913 typical gaps (standard deviations)Colombia: 0.679 index (0-1), -0.125 typical gaps (standard deviations)Cyprus: 0.773 index (0-1), -0.0176 typical gaps (standard deviations)Czechia: 0.849 index (0-1), 0.726 typical gaps (standard deviations)Germany: 0.828 index (0-1), 0.981 typical gaps (standard deviations)Denmark: 0.913 index (0-1), 1.89 typical gaps (standard deviations)Algeria: 0.265 index (0-1), -0.205 typical gaps (standard deviations)Ecuador: 0.607 index (0-1), -0.164 typical gaps (standard deviations)Egypt, Arab Rep.: 0.187 index (0-1), -1.08 typical gaps (standard deviations)Spain: 0.822 index (0-1), 0.816 typical gaps (standard deviations)Estonia: 0.887 index (0-1), 0.622 typical gaps (standard deviations)Ethiopia: 0.257 index (0-1), -0.726 typical gaps (standard deviations)Finland: 0.852 index (0-1), 1.87 typical gaps (standard deviations)France: 0.865 index (0-1), 0.717 typical gaps (standard deviations)United Kingdom: 0.772 index (0-1), 1.07 typical gaps (standard deviations)Georgia: 0.401 index (0-1), -0.493 typical gaps (standard deviations)Ghana: 0.711 index (0-1), -0.73 typical gaps (standard deviations)Greece: 0.741 index (0-1), -0.284 typical gaps (standard deviations)Guatemala: 0.637 index (0-1), 0.352 typical gaps (standard deviations)Hong Kong SAR, China: 0.151 index (0-1), 0.0778 typical gaps (standard deviations)Croatia: 0.686 index (0-1), 0.0883 typical gaps (standard deviations)Haiti: 0.238 index (0-1), -0.461 typical gaps (standard deviations)Hungary: 0.421 index (0-1), 0.266 typical gaps (standard deviations)Indonesia: 0.462 index (0-1), -0.192 typical gaps (standard deviations)India: 0.377 index (0-1), -0.736 typical gaps (standard deviations)Ireland: 0.887 index (0-1), 0.894 typical gaps (standard deviations)Iran, Islamic Rep.: 0.159 index (0-1), -0.684 typical gaps (standard deviations)Iraq: 0.369 index (0-1), -0.726 typical gaps (standard deviations)Iceland: 0.807 index (0-1), 1.78 typical gaps (standard deviations)Italy: 0.745 index (0-1), 0.438 typical gaps (standard deviations)Jordan: 0.282 index (0-1), -0.666 typical gaps (standard deviations)Japan: 0.819 index (0-1), 0.552 typical gaps (standard deviations)Kazakhstan: 0.259 index (0-1), 0.304 typical gaps (standard deviations)Kenya: 0.563 index (0-1), -0.678 typical gaps (standard deviations)Kyrgyz Republic: 0.313 index (0-1), 0.225 typical gaps (standard deviations)Korea, Rep.: 0.819 index (0-1), 0.475 typical gaps (standard deviations)Kuwait: 0.138 index (0-1), 0.607 typical gaps (standard deviations)Lebanon: 0.419 index (0-1), -1.54 typical gaps (standard deviations)Libya: 0.193 index (0-1), -0.158 typical gaps (standard deviations)Lithuania: 0.786 index (0-1), 0.51 typical gaps (standard deviations)Luxembourg: 0.869 index (0-1), 0.652 typical gaps (standard deviations)Latvia: 0.834 index (0-1), 0.212 typical gaps (standard deviations)Morocco: 0.259 index (0-1), -0.382 typical gaps (standard deviations)Moldova: 0.553 index (0-1), -1.29 typical gaps (standard deviations)Maldives: 0.556 index (0-1), 0.0845 typical gaps (standard deviations)Mexico: 0.469 index (0-1), 0.335 typical gaps (standard deviations)North Macedonia: 0.562 index (0-1), -0.171 typical gaps (standard deviations)Mali: 0.164 index (0-1), -0.328 typical gaps (standard deviations)Malta: 0.783 index (0-1), 0.15 typical gaps (standard deviations)Myanmar: 0.08 index (0-1), -0.547 typical gaps (standard deviations)Montenegro: 0.636 index (0-1), 0.239 typical gaps (standard deviations)Mongolia: 0.535 index (0-1), 0.000193 typical gaps (standard deviations)Malaysia: 0.504 index (0-1), 0.215 typical gaps (standard deviations)Nigeria: 0.505 index (0-1), -0.611 typical gaps (standard deviations)Nicaragua: 0.151 index (0-1), 0.0736 typical gaps (standard deviations)Netherlands: 0.832 index (0-1), 1.54 typical gaps (standard deviations)Norway: 0.89 index (0-1), 1.82 typical gaps (standard deviations)New Zealand: 0.849 index (0-1), 1.46 typical gaps (standard deviations)Pakistan: 0.302 index (0-1), -0.299 typical gaps (standard deviations)Peru: 0.667 index (0-1), -0.348 typical gaps (standard deviations)Philippines: 0.392 index (0-1), -0.119 typical gaps (standard deviations)Poland: 0.768 index (0-1), 0.505 typical gaps (standard deviations)Portugal: 0.822 index (0-1), 0.195 typical gaps (standard deviations)Qatar: 0.034 index (0-1), 0.756 typical gaps (standard deviations)Romania: 0.605 index (0-1), 0.197 typical gaps (standard deviations)Russian Federation: 0.17 index (0-1), -0.00878 typical gaps (standard deviations)Rwanda: 0.193 index (0-1), -0.867 typical gaps (standard deviations)Singapore: 0.434 index (0-1), 0.779 typical gaps (standard deviations)Serbia: 0.3 index (0-1), 0.105 typical gaps (standard deviations)Slovak Republic: 0.733 index (0-1), 0.318 typical gaps (standard deviations)Slovenia: 0.692 index (0-1), 0.55 typical gaps (standard deviations)Sweden: 0.889 index (0-1), 1.7 typical gaps (standard deviations)Thailand: 0.424 index (0-1), 0.256 typical gaps (standard deviations)Tajikistan: 0.158 index (0-1), 0.104 typical gaps (standard deviations)Trinidad and Tobago: 0.786 index (0-1), 0.0637 typical gaps (standard deviations)Tunisia: 0.395 index (0-1), -0.73 typical gaps (standard deviations)Turkiye: 0.293 index (0-1), -0.508 typical gaps (standard deviations)Ukraine: 0.386 index (0-1), -0.244 typical gaps (standard deviations)Uruguay: 0.862 index (0-1), 0.449 typical gaps (standard deviations)United States: 0.735 index (0-1), 0.943 typical gaps (standard deviations)Uzbekistan: 0.218 index (0-1), 0.617 typical gaps (standard deviations)Viet Nam: 0.146 index (0-1), 0.469 typical gaps (standard deviations)Kosovo: 0.631 index (0-1), -0.288 typical gaps (standard deviations)South Africa: 0.743 index (0-1), -0.515 typical gaps (standard deviations)Zambia: 0.497 index (0-1), -1.67 typical gaps (standard deviations)Zimbabwe: 0.268 index (0-1), -1.98 typical gaps (standard deviations)BLRCHNDNKEGYFINGHALBNMDANORQATZMBZWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5133.0e-8103
By rank (Spearman), not adjusted+0.5521.5e-9103
Standard (Pearson), adjusted for national income+0.1480.137103
By rank (Spearman), adjusted for national income+0.1080.282103

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 103 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: +0.365 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.119 (without HKG) to +0.186 (without CHN). 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: CHN (+0.038).

Fragile: this link may not hold up.
  • direction is not consistent across regions

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+0.28
Europe & Central Asia48+0.20
Latin America & Caribbean13-0.38
Middle East, North Africa, Afghanistan & Pakistan13-0.27

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 third35-0.32
Middle third34+0.04
Richest third34+0.43

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
Christians61+0.12
Muslims28-0.28

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
Never a European colony15+0.01
Spain12-0.32
United Kingdom25+0.27

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 = +0.150 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


index (0-1)

typical gaps (standard deviations)
Years
Denmark DNK0.9131.892025, 2022
Norway NOR0.891.822025, 2022
Sweden SWE0.8891.72025, 2022
Belgium BEL0.8890.8182025, 2010
Ireland IRL0.8870.8942025, 2010
Estonia EST0.8870.6222025, 2022
Switzerland CHE0.8821.552025, 2022
Luxembourg LUX0.8690.6522025, 2010
France FRA0.8650.7172025, 2022
Uruguay URY0.8620.4492025, 2022
Finland FIN0.8521.872025, 2022
New Zealand NZL0.8491.462025, 2022
Czechia CZE0.8490.7262025, 2022
Australia AUS0.8441.252025, 2022
Canada CAN0.841.062025, 2022

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

Sources

Electoral democracy

Electoral democracy index (polyarchy)

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

Based on political scientist Robert Dahl's idea of "polyarchy": are leaders chosen in free and fair elections, with freedom of speech, freedom to form groups, and the vote for nearly all adults? It is the base index that most other V-Dem measures are built on.

Wellbeing score

Wellbeing score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 3 measures from 2 publishers. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Self-reported happiness, Interpersonal trust, Life satisfaction.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2025. 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 Electoral democracy and Wellbeing score

This page shows that two measures go together. It does not show that Electoral democracy changes Wellbeing score, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Electoral democracy or Wellbeing score