placestats

HDI vs. Wellbeing score

Fades after adjusting for income

Across 104 countries, HDI and Wellbeing score rise and fall together at r = +0.72 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.10, which could easily be chance (q = 0.75, 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 hdi, 0.741 to 0.915 points, wellbeing score is better by 0.761 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.235 typical gaps.

Link before adjusting (r)+0.716p = 1.3e-17 · 104 countries
After adjusting for national income+0.099p = 0.321 · likely range [-0.10, +0.29]
p, allowing for regions0.594standard error 0.175 · 7 regions
Check for luck (q)0.751across 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.

HDI · index, 0 to 1link with income +0.96 · proxy
Wellbeing score · typical gaps (standard deviations)link with income +0.80 · high

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

HDI · index, 0 to 1 →Wellbeing score · typical gaps (standard deviations) →0.4190.972-1.981.89Albania: 0.81 index, 0 to 1, -0.617 typical gaps (standard deviations)Andorra: 0.913 index, 0 to 1, 0.512 typical gaps (standard deviations)Argentina: 0.865 index, 0 to 1, 0.216 typical gaps (standard deviations)Armenia: 0.811 index, 0 to 1, -0.118 typical gaps (standard deviations)Australia: 0.958 index, 0 to 1, 1.25 typical gaps (standard deviations)Austria: 0.93 index, 0 to 1, 1.26 typical gaps (standard deviations)Azerbaijan: 0.789 index, 0 to 1, -0.0603 typical gaps (standard deviations)Belgium: 0.951 index, 0 to 1, 0.818 typical gaps (standard deviations)Burkina Faso: 0.459 index, 0 to 1, -0.476 typical gaps (standard deviations)Bangladesh: 0.685 index, 0 to 1, -0.561 typical gaps (standard deviations)Bulgaria: 0.845 index, 0 to 1, -0.572 typical gaps (standard deviations)Bosnia and Herzegovina: 0.804 index, 0 to 1, -0.087 typical gaps (standard deviations)Belarus: 0.824 index, 0 to 1, 0.732 typical gaps (standard deviations)Bolivia: 0.733 index, 0 to 1, -0.361 typical gaps (standard deviations)Brazil: 0.786 index, 0 to 1, 0.123 typical gaps (standard deviations)Canada: 0.939 index, 0 to 1, 1.06 typical gaps (standard deviations)Switzerland: 0.97 index, 0 to 1, 1.55 typical gaps (standard deviations)Chile: 0.878 index, 0 to 1, 0.19 typical gaps (standard deviations)China: 0.797 index, 0 to 1, 0.913 typical gaps (standard deviations)Colombia: 0.788 index, 0 to 1, -0.125 typical gaps (standard deviations)Cyprus: 0.913 index, 0 to 1, -0.0176 typical gaps (standard deviations)Czechia: 0.915 index, 0 to 1, 0.726 typical gaps (standard deviations)Germany: 0.959 index, 0 to 1, 0.981 typical gaps (standard deviations)Denmark: 0.962 index, 0 to 1, 1.89 typical gaps (standard deviations)Algeria: 0.763 index, 0 to 1, -0.205 typical gaps (standard deviations)Ecuador: 0.777 index, 0 to 1, -0.164 typical gaps (standard deviations)Egypt, Arab Rep.: 0.754 index, 0 to 1, -1.08 typical gaps (standard deviations)Spain: 0.918 index, 0 to 1, 0.816 typical gaps (standard deviations)Estonia: 0.905 index, 0 to 1, 0.622 typical gaps (standard deviations)Ethiopia: 0.497 index, 0 to 1, -0.726 typical gaps (standard deviations)Finland: 0.948 index, 0 to 1, 1.87 typical gaps (standard deviations)France: 0.92 index, 0 to 1, 0.717 typical gaps (standard deviations)United Kingdom: 0.946 index, 0 to 1, 1.07 typical gaps (standard deviations)Georgia: 0.844 index, 0 to 1, -0.493 typical gaps (standard deviations)Ghana: 0.628 index, 0 to 1, -0.73 typical gaps (standard deviations)Greece: 0.908 index, 0 to 1, -0.284 typical gaps (standard deviations)Guatemala: 0.662 index, 0 to 1, 0.352 typical gaps (standard deviations)Hong Kong SAR, China: 0.955 index, 0 to 1, 0.0778 typical gaps (standard deviations)Croatia: 0.889 index, 0 to 1, 0.0883 typical gaps (standard deviations)Haiti: 0.554 index, 0 to 1, -0.461 typical gaps (standard deviations)Hungary: 0.87 index, 0 to 1, 0.266 typical gaps (standard deviations)Indonesia: 0.728 index, 0 to 1, -0.192 typical gaps (standard deviations)India: 0.685 index, 0 to 1, -0.736 typical gaps (standard deviations)Ireland: 0.949 index, 0 to 1, 0.894 typical gaps (standard deviations)Iran, Islamic Rep.: 0.799 index, 0 to 1, -0.684 typical gaps (standard deviations)Iraq: 0.695 index, 0 to 1, -0.726 typical gaps (standard deviations)Iceland: 0.972 index, 0 to 1, 1.78 typical gaps (standard deviations)Italy: 0.915 index, 0 to 1, 0.438 typical gaps (standard deviations)Jordan: 0.754 index, 0 to 1, -0.666 typical gaps (standard deviations)Japan: 0.925 index, 0 to 1, 0.552 typical gaps (standard deviations)Kazakhstan: 0.837 index, 0 to 1, 0.304 typical gaps (standard deviations)Kenya: 0.628 index, 0 to 1, -0.678 typical gaps (standard deviations)Kyrgyz Republic: 0.72 index, 0 to 1, 0.225 typical gaps (standard deviations)Korea, Rep.: 0.937 index, 0 to 1, 0.475 typical gaps (standard deviations)Kuwait: 0.852 index, 0 to 1, 0.607 typical gaps (standard deviations)Lebanon: 0.752 index, 0 to 1, -1.54 typical gaps (standard deviations)Libya: 0.721 index, 0 to 1, -0.158 typical gaps (standard deviations)Lithuania: 0.895 index, 0 to 1, 0.51 typical gaps (standard deviations)Luxembourg: 0.922 index, 0 to 1, 0.652 typical gaps (standard deviations)Latvia: 0.889 index, 0 to 1, 0.212 typical gaps (standard deviations)Morocco: 0.71 index, 0 to 1, -0.382 typical gaps (standard deviations)Moldova: 0.785 index, 0 to 1, -1.29 typical gaps (standard deviations)Maldives: 0.766 index, 0 to 1, 0.0845 typical gaps (standard deviations)Mexico: 0.789 index, 0 to 1, 0.335 typical gaps (standard deviations)North Macedonia: 0.815 index, 0 to 1, -0.171 typical gaps (standard deviations)Mali: 0.419 index, 0 to 1, -0.328 typical gaps (standard deviations)Malta: 0.924 index, 0 to 1, 0.15 typical gaps (standard deviations)Myanmar: 0.609 index, 0 to 1, -0.547 typical gaps (standard deviations)Montenegro: 0.862 index, 0 to 1, 0.239 typical gaps (standard deviations)Mongolia: 0.747 index, 0 to 1, 0.000193 typical gaps (standard deviations)Malaysia: 0.819 index, 0 to 1, 0.215 typical gaps (standard deviations)Nigeria: 0.56 index, 0 to 1, -0.611 typical gaps (standard deviations)Nicaragua: 0.706 index, 0 to 1, 0.0736 typical gaps (standard deviations)Netherlands: 0.955 index, 0 to 1, 1.54 typical gaps (standard deviations)Norway: 0.97 index, 0 to 1, 1.82 typical gaps (standard deviations)New Zealand: 0.938 index, 0 to 1, 1.46 typical gaps (standard deviations)Pakistan: 0.544 index, 0 to 1, -0.299 typical gaps (standard deviations)Peru: 0.794 index, 0 to 1, -0.348 typical gaps (standard deviations)Philippines: 0.72 index, 0 to 1, -0.119 typical gaps (standard deviations)Poland: 0.906 index, 0 to 1, 0.505 typical gaps (standard deviations)Portugal: 0.89 index, 0 to 1, 0.195 typical gaps (standard deviations)West Bank and Gaza: 0.674 index, 0 to 1, -0.644 typical gaps (standard deviations)Qatar: 0.886 index, 0 to 1, 0.756 typical gaps (standard deviations)Romania: 0.845 index, 0 to 1, 0.197 typical gaps (standard deviations)Russian Federation: 0.832 index, 0 to 1, -0.00878 typical gaps (standard deviations)Rwanda: 0.578 index, 0 to 1, -0.867 typical gaps (standard deviations)Singapore: 0.946 index, 0 to 1, 0.779 typical gaps (standard deviations)Serbia: 0.833 index, 0 to 1, 0.105 typical gaps (standard deviations)Slovak Republic: 0.88 index, 0 to 1, 0.318 typical gaps (standard deviations)Slovenia: 0.931 index, 0 to 1, 0.55 typical gaps (standard deviations)Sweden: 0.959 index, 0 to 1, 1.7 typical gaps (standard deviations)Thailand: 0.798 index, 0 to 1, 0.256 typical gaps (standard deviations)Tajikistan: 0.691 index, 0 to 1, 0.104 typical gaps (standard deviations)Trinidad and Tobago: 0.807 index, 0 to 1, 0.0637 typical gaps (standard deviations)Tunisia: 0.746 index, 0 to 1, -0.73 typical gaps (standard deviations)Turkiye: 0.853 index, 0 to 1, -0.508 typical gaps (standard deviations)Ukraine: 0.779 index, 0 to 1, -0.244 typical gaps (standard deviations)Uruguay: 0.862 index, 0 to 1, 0.449 typical gaps (standard deviations)United States: 0.938 index, 0 to 1, 0.943 typical gaps (standard deviations)Uzbekistan: 0.74 index, 0 to 1, 0.617 typical gaps (standard deviations)Viet Nam: 0.766 index, 0 to 1, 0.469 typical gaps (standard deviations)South Africa: 0.741 index, 0 to 1, -0.515 typical gaps (standard deviations)Zambia: 0.595 index, 0 to 1, -1.67 typical gaps (standard deviations)Zimbabwe: 0.598 index, 0 to 1, -1.98 typical gaps (standard deviations)BFADNKGRCISLLBNMDAMLINORPAKZMBZWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.7161.3e-17104
By rank (Spearman), not adjusted+0.7948.4e-24104
Standard (Pearson), adjusted for national income+0.0990.321104
By rank (Spearman), adjusted for national income+0.1650.096104

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 104 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: +0.618 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.067 (without TJK) to +0.160 (without MLI). 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: MLI (+0.061).

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+0.43
Europe & Central Asia48+0.48
Latin America & Caribbean13-0.42
Middle East, North Africa, Afghanistan & Pakistan14-0.45

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 third35-0.03
Middle third34-0.10
Richest third35+0.62

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+0.20
Muslims28-0.20

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+0.17
Spain12-0.58
United Kingdom25+0.19

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 = +0.181 after dropping 3 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 to 1

typical gaps (standard deviations)
Years
Iceland ISL0.9721.782023, 2022
Norway NOR0.971.822023, 2022
Switzerland CHE0.971.552023, 2022
Denmark DNK0.9621.892023, 2022
Sweden SWE0.9591.72023, 2022
Germany DEU0.9590.9812023, 2022
Australia AUS0.9581.252023, 2022
Netherlands NLD0.9551.542023, 2022
Hong Kong SAR, China HKG0.9550.07782023, 2022
Belgium BEL0.9510.8182023, 2010
Ireland IRL0.9490.8942023, 2010
Finland FIN0.9481.872023, 2022
Singapore SGP0.9460.7792023, 2022
United Kingdom GBR0.9461.072023, 2022
Canada CAN0.9391.062023, 2022

United Nations Development Programme, Human Development Report 2025
ivs; whr

Sources

HDI

Human Development Index

United Nations Development Programme, Human Development Report Office · via Our World in Data · CC BY 3.0 IGO · updated annual

The geometric mean (a kind of average that multiplies the parts together) of three parts: income per person (GNI per capita), life expectancy, and schooling (expected years and average years). All four inputs are on this site, and each is flagged. So a link between the HDI and any of them is shown for what it is: the index matching a part of itself. For the same reason it is kept out of this site's own topic scores. Those already contain its parts, and adding it would count each twice. It is the most-cited development index there is. It is here mostly so its parts can be read separately.

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 2010–2023. 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 HDI and Wellbeing score

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

More links with HDI or Wellbeing score