placestats

Aid given vs. Wellbeing score

Fades after adjusting for income

Across 44 countries, Aid given and Wellbeing score rise and fall together at r = +0.60 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.33, which could easily be chance (q = 0.079, 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: leave-one-out range spans 0.19 in r.

Comparing countries across the middle half of aid given, 0.135% to 0.426% of GNI, wellbeing score is better by 0.456 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.277 typical gaps.

Link before adjusting (r)+0.595p = 2.0e-5 · 44 countries
After adjusting for national income+0.333p = 0.029 · likely range [+0.04, +0.58]
p, allowing for regions0.011standard error 0.060 · 4 regions
Check for luck (q)0.079across 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.

Aid given · % of GNIlink with income +0.68 · high
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

Aid given · % of GNI →Wellbeing score · typical gaps (standard deviations) →0.0118%1.03%-0.5721.89Australia: 0.184% of GNI, 1.25 typical gaps (standard deviations)Austria: 0.329% of GNI, 1.26 typical gaps (standard deviations)Azerbaijan: 0.0633% of GNI, -0.0603 typical gaps (standard deviations)Belgium: 0.37% of GNI, 0.818 typical gaps (standard deviations)Bulgaria: 0.117% of GNI, -0.572 typical gaps (standard deviations)Canada: 0.316% of GNI, 1.06 typical gaps (standard deviations)Switzerland: 0.46% of GNI, 1.55 typical gaps (standard deviations)Cyprus: 0.0384% of GNI, -0.0176 typical gaps (standard deviations)Czechia: 0.116% of GNI, 0.726 typical gaps (standard deviations)Germany: 0.558% of GNI, 0.981 typical gaps (standard deviations)Denmark: 0.723% of GNI, 1.89 typical gaps (standard deviations)Spain: 0.271% of GNI, 0.816 typical gaps (standard deviations)Estonia: 0.193% of GNI, 0.622 typical gaps (standard deviations)Finland: 0.443% of GNI, 1.87 typical gaps (standard deviations)France: 0.423% of GNI, 0.717 typical gaps (standard deviations)United Kingdom: 0.432% of GNI, 1.07 typical gaps (standard deviations)Greece: 0.13% of GNI, -0.284 typical gaps (standard deviations)Croatia: 0.236% of GNI, 0.0883 typical gaps (standard deviations)Hungary: 0.139% of GNI, 0.266 typical gaps (standard deviations)Ireland: 0.425% of GNI, 0.894 typical gaps (standard deviations)Iceland: 0.337% of GNI, 1.78 typical gaps (standard deviations)Italy: 0.296% of GNI, 0.438 typical gaps (standard deviations)Japan: 0.345% of GNI, 0.552 typical gaps (standard deviations)Kazakhstan: 0.0188% of GNI, 0.304 typical gaps (standard deviations)Korea, Rep.: 0.203% of GNI, 0.475 typical gaps (standard deviations)Kuwait: 0.113% of GNI, 0.607 typical gaps (standard deviations)Lithuania: 0.212% of GNI, 0.51 typical gaps (standard deviations)Luxembourg: 0.993% of GNI, 0.652 typical gaps (standard deviations)Latvia: 0.18% of GNI, 0.212 typical gaps (standard deviations)Malta: 0.205% of GNI, 0.15 typical gaps (standard deviations)Netherlands: 0.58% of GNI, 1.54 typical gaps (standard deviations)Norway: 1.03% of GNI, 1.82 typical gaps (standard deviations)New Zealand: 0.273% of GNI, 1.46 typical gaps (standard deviations)Poland: 0.162% of GNI, 0.505 typical gaps (standard deviations)Portugal: 0.178% of GNI, 0.195 typical gaps (standard deviations)Qatar: 0.432% of GNI, 0.756 typical gaps (standard deviations)Romania: 0.135% of GNI, 0.197 typical gaps (standard deviations)Russian Federation: 0.0667% of GNI, -0.00878 typical gaps (standard deviations)Slovak Republic: 0.133% of GNI, 0.318 typical gaps (standard deviations)Slovenia: 0.216% of GNI, 0.55 typical gaps (standard deviations)Sweden: 0.849% of GNI, 1.7 typical gaps (standard deviations)Thailand: 0.0118% of GNI, 0.256 typical gaps (standard deviations)Turkiye: 0.501% of GNI, -0.508 typical gaps (standard deviations)United States: 0.094% of GNI, 0.943 typical gaps (standard deviations)AUSBGRCYPDNKGRCISLLUXNORNZLSWETUR

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5952.0e-544
By rank (Spearman), not adjusted+0.6541.5e-644
Standard (Pearson), adjusted for national income+0.3330.02944
By rank (Spearman), adjusted for national income+0.3180.03844

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 44 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: +0.262 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.262 (without SWE) to +0.456 (without LUX). 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: LUX (+0.122).

Fragile: this link may not hold up.
  • leave-one-out range spans 0.19 in r

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 Asia34+0.31

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 third15-0.45
Middle third14+0.63
Richest third15+0.51

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
Christians33+0.42

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 = +0.447 after dropping 2 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 GNI
typical gaps (standard deviations)		Years
Norway NOR1.03%1.822025, 2022
Luxembourg LUX0.993%0.6522025, 2010
Sweden SWE0.849%1.72025, 2022
Denmark DNK0.723%1.892025, 2022
Netherlands NLD0.58%1.542025, 2022
Germany DEU0.558%0.9812025, 2022
Turkiye TUR0.501%-0.5082025, 2022
Switzerland CHE0.46%1.552025, 2022
Finland FIN0.443%1.872025, 2022
Qatar QAT0.432%0.7562025, 2014
United Kingdom GBR0.432%1.072025, 2022
Ireland IRL0.425%0.8942025, 2010
France FRA0.423%0.7172025, 2022
Belgium BEL0.37%0.8182025, 2010
Japan JPN0.345%0.5522025, 2022

OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics
ivs; whr

Sources

Aid given

Official development assistance given

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator

Donor countries only, about fifty. Countries that receive aid do not appear, so any link with this is a link among rich countries. No "better" direction is set.

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 4 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 Aid given and Wellbeing score

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

More links with Aid given or Wellbeing score