placestats

Regime type vs. Wellbeing score

Fades after adjusting for income

Across 103 countries, Regime type 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 +0.16, which could easily be chance (q = 0.34, 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 regime type, 1 to 3 points, wellbeing score is better by 0.775 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.209 typical gaps.

Link before adjusting (r)+0.513p = 3.0e-8 · 103 countries
After adjusting for national income+0.165p = 0.098 · likely range [-0.03, +0.35]
p, allowing for regions0.151standard error 0.100 · 7 regions
Check for luck (q)0.344across 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.

Regime type · regime category (0-3)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

Regime type · regime category (0-3) →Wellbeing score · typical gaps (standard deviations) →03-1.981.89Albania: 1 regime category (0-3), -0.617 typical gaps (standard deviations)Argentina: 2 regime category (0-3), 0.216 typical gaps (standard deviations)Armenia: 2 regime category (0-3), -0.118 typical gaps (standard deviations)Australia: 3 regime category (0-3), 1.25 typical gaps (standard deviations)Austria: 3 regime category (0-3), 1.26 typical gaps (standard deviations)Azerbaijan: 1 regime category (0-3), -0.0603 typical gaps (standard deviations)Belgium: 3 regime category (0-3), 0.818 typical gaps (standard deviations)Burkina Faso: 0 regime category (0-3), -0.476 typical gaps (standard deviations)Bangladesh: 0 regime category (0-3), -0.561 typical gaps (standard deviations)Bulgaria: 2 regime category (0-3), -0.572 typical gaps (standard deviations)Bosnia and Herzegovina: 1 regime category (0-3), -0.087 typical gaps (standard deviations)Belarus: 0 regime category (0-3), 0.732 typical gaps (standard deviations)Bolivia: 2 regime category (0-3), -0.361 typical gaps (standard deviations)Brazil: 2 regime category (0-3), 0.123 typical gaps (standard deviations)Canada: 2 regime category (0-3), 1.06 typical gaps (standard deviations)Switzerland: 3 regime category (0-3), 1.55 typical gaps (standard deviations)Chile: 3 regime category (0-3), 0.19 typical gaps (standard deviations)China: 0 regime category (0-3), 0.913 typical gaps (standard deviations)Colombia: 2 regime category (0-3), -0.125 typical gaps (standard deviations)Cyprus: 3 regime category (0-3), -0.0176 typical gaps (standard deviations)Czechia: 3 regime category (0-3), 0.726 typical gaps (standard deviations)Germany: 3 regime category (0-3), 0.981 typical gaps (standard deviations)Denmark: 3 regime category (0-3), 1.89 typical gaps (standard deviations)Algeria: 1 regime category (0-3), -0.205 typical gaps (standard deviations)Ecuador: 2 regime category (0-3), -0.164 typical gaps (standard deviations)Egypt, Arab Rep.: 1 regime category (0-3), -1.08 typical gaps (standard deviations)Spain: 3 regime category (0-3), 0.816 typical gaps (standard deviations)Estonia: 3 regime category (0-3), 0.622 typical gaps (standard deviations)Ethiopia: 1 regime category (0-3), -0.726 typical gaps (standard deviations)Finland: 3 regime category (0-3), 1.87 typical gaps (standard deviations)France: 3 regime category (0-3), 0.717 typical gaps (standard deviations)United Kingdom: 2 regime category (0-3), 1.07 typical gaps (standard deviations)Georgia: 1 regime category (0-3), -0.493 typical gaps (standard deviations)Ghana: 2 regime category (0-3), -0.73 typical gaps (standard deviations)Greece: 2 regime category (0-3), -0.284 typical gaps (standard deviations)Guatemala: 2 regime category (0-3), 0.352 typical gaps (standard deviations)Hong Kong SAR, China: 0 regime category (0-3), 0.0778 typical gaps (standard deviations)Croatia: 2 regime category (0-3), 0.0883 typical gaps (standard deviations)Haiti: 0 regime category (0-3), -0.461 typical gaps (standard deviations)Hungary: 1 regime category (0-3), 0.266 typical gaps (standard deviations)Indonesia: 1 regime category (0-3), -0.192 typical gaps (standard deviations)India: 1 regime category (0-3), -0.736 typical gaps (standard deviations)Ireland: 3 regime category (0-3), 0.894 typical gaps (standard deviations)Iran, Islamic Rep.: 1 regime category (0-3), -0.684 typical gaps (standard deviations)Iraq: 1 regime category (0-3), -0.726 typical gaps (standard deviations)Iceland: 3 regime category (0-3), 1.78 typical gaps (standard deviations)Italy: 3 regime category (0-3), 0.438 typical gaps (standard deviations)Jordan: 0 regime category (0-3), -0.666 typical gaps (standard deviations)Japan: 3 regime category (0-3), 0.552 typical gaps (standard deviations)Kazakhstan: 1 regime category (0-3), 0.304 typical gaps (standard deviations)Kenya: 2 regime category (0-3), -0.678 typical gaps (standard deviations)Kyrgyz Republic: 1 regime category (0-3), 0.225 typical gaps (standard deviations)Korea, Rep.: 3 regime category (0-3), 0.475 typical gaps (standard deviations)Kuwait: 0 regime category (0-3), 0.607 typical gaps (standard deviations)Lebanon: 1 regime category (0-3), -1.54 typical gaps (standard deviations)Libya: 0 regime category (0-3), -0.158 typical gaps (standard deviations)Lithuania: 3 regime category (0-3), 0.51 typical gaps (standard deviations)Luxembourg: 3 regime category (0-3), 0.652 typical gaps (standard deviations)Latvia: 3 regime category (0-3), 0.212 typical gaps (standard deviations)Morocco: 0 regime category (0-3), -0.382 typical gaps (standard deviations)Moldova: 2 regime category (0-3), -1.29 typical gaps (standard deviations)Maldives: 2 regime category (0-3), 0.0845 typical gaps (standard deviations)Mexico: 1 regime category (0-3), 0.335 typical gaps (standard deviations)North Macedonia: 2 regime category (0-3), -0.171 typical gaps (standard deviations)Mali: 0 regime category (0-3), -0.328 typical gaps (standard deviations)Malta: 2 regime category (0-3), 0.15 typical gaps (standard deviations)Myanmar: 0 regime category (0-3), -0.547 typical gaps (standard deviations)Montenegro: 2 regime category (0-3), 0.239 typical gaps (standard deviations)Mongolia: 2 regime category (0-3), 0.000193 typical gaps (standard deviations)Malaysia: 2 regime category (0-3), 0.215 typical gaps (standard deviations)Nigeria: 2 regime category (0-3), -0.611 typical gaps (standard deviations)Nicaragua: 1 regime category (0-3), 0.0736 typical gaps (standard deviations)Netherlands: 3 regime category (0-3), 1.54 typical gaps (standard deviations)Norway: 3 regime category (0-3), 1.82 typical gaps (standard deviations)New Zealand: 3 regime category (0-3), 1.46 typical gaps (standard deviations)Pakistan: 1 regime category (0-3), -0.299 typical gaps (standard deviations)Peru: 2 regime category (0-3), -0.348 typical gaps (standard deviations)Philippines: 1 regime category (0-3), -0.119 typical gaps (standard deviations)Poland: 2 regime category (0-3), 0.505 typical gaps (standard deviations)Portugal: 2 regime category (0-3), 0.195 typical gaps (standard deviations)Qatar: 0 regime category (0-3), 0.756 typical gaps (standard deviations)Romania: 2 regime category (0-3), 0.197 typical gaps (standard deviations)Russian Federation: 1 regime category (0-3), -0.00878 typical gaps (standard deviations)Rwanda: 1 regime category (0-3), -0.867 typical gaps (standard deviations)Singapore: 1 regime category (0-3), 0.779 typical gaps (standard deviations)Serbia: 1 regime category (0-3), 0.105 typical gaps (standard deviations)Slovak Republic: 2 regime category (0-3), 0.318 typical gaps (standard deviations)Slovenia: 2 regime category (0-3), 0.55 typical gaps (standard deviations)Sweden: 3 regime category (0-3), 1.7 typical gaps (standard deviations)Thailand: 1 regime category (0-3), 0.256 typical gaps (standard deviations)Tajikistan: 1 regime category (0-3), 0.104 typical gaps (standard deviations)Trinidad and Tobago: 3 regime category (0-3), 0.0637 typical gaps (standard deviations)Tunisia: 1 regime category (0-3), -0.73 typical gaps (standard deviations)Turkiye: 1 regime category (0-3), -0.508 typical gaps (standard deviations)Ukraine: 1 regime category (0-3), -0.244 typical gaps (standard deviations)Uruguay: 3 regime category (0-3), 0.449 typical gaps (standard deviations)United States: 2 regime category (0-3), 0.943 typical gaps (standard deviations)Uzbekistan: 1 regime category (0-3), 0.617 typical gaps (standard deviations)Viet Nam: 0 regime category (0-3), 0.469 typical gaps (standard deviations)Kosovo: 2 regime category (0-3), -0.288 typical gaps (standard deviations)South Africa: 2 regime category (0-3), -0.515 typical gaps (standard deviations)Zambia: 1 regime category (0-3), -1.67 typical gaps (standard deviations)Zimbabwe: 1 regime category (0-3), -1.98 typical gaps (standard deviations)BLRCHNDNKFINLBNMDANORQATZMBZWE

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+0.5241.4e-8103
Standard (Pearson), adjusted for national income+0.1650.098103
By rank (Spearman), adjusted for national income+0.0870.387103

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: +0.348 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.134 (without HKG) to +0.200 (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 (+0.036).

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+0.29
Europe & Central Asia48+0.28
Latin America & Caribbean13-0.31
Middle East, North Africa, Afghanistan & Pakistan13-0.43

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 third35-0.15
Middle third34-0.09
Richest third34+0.44

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+0.13
Muslims28-0.12

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 colony15-0.00
Spain12-0.03
United Kingdom25+0.18

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 = +0.177 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


regime category (0-3)

typical gaps (standard deviations)
Years
Uruguay URY30.4492025, 2022
Trinidad and Tobago TTO30.06372025, 2014
Sweden SWE31.72025, 2022
New Zealand NZL31.462025, 2022
Norway NOR31.822025, 2022
Netherlands NLD31.542025, 2022
Latvia LVA30.2122025, 2022
Luxembourg LUX30.6522025, 2010
Lithuania LTU30.512025, 2022
Korea, Rep. KOR30.4752025, 2022
Japan JPN30.5522025, 2022
Italy ITA30.4382025, 2022
Iceland ISL31.782025, 2022
Ireland IRL30.8942025, 2010
France FRA30.7172025, 2022

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

Sources

Regime type

Regime type, Regimes of the World classification

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

Four ranked categories, not a scale. It is the only such measure on this site. A closed autocracy holds no multiparty elections for its leader. An electoral autocracy holds them, but they are neither free nor fair. An electoral democracy clears that bar. A liberal democracy also has independent courts and protected personal freedoms. The four steps are not equal distances apart. So read the rank-based link, which uses only the order, rather than the ordinary one. Both are shown. The categories are set by cut-off points on the V-Dem indices already on this site. That is why its pairs with them are flagged as built from the same numbers. It is also why it is kept out of the governance score: a grouping of those indices averaged back in beside them would count each twice. Our World in Data extends the categories back to territories before independence. This site starts at 1960, and its single-year snapshot at 2010, so that extension reaches nothing shown here.

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 Regime type and Wellbeing score

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

More links with Regime type or Wellbeing score