placestats

Fertility rate vs. Wellbeing score

Fades after adjusting for income

Across 107 countries, Fertility rate and Wellbeing score rise and fall together at r = -0.54 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.13, which could easily be chance (q = 0.59, 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 fertility rate, 1.36 to 2.21 births per woman, wellbeing score is worse by 0.39 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap reverses, to 0.105 typical gaps the other way.

Link before adjusting (r)-0.536p = 2.7e-9 · 107 countries
After adjusting for national income+0.126p = 0.197 · likely range [-0.07, +0.31]
p, allowing for regions0.389standard error 0.136 · 7 regions
Check for luck (q)0.587across 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.

Fertility rate · births per womanlink with income -0.81 · 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

Fertility rate · births per woman →Wellbeing score · typical gaps (standard deviations) →0.5825.51-1.981.89Albania: 1.34 births per woman, -0.617 typical gaps (standard deviations)Andorra: 1.09 births per woman, 0.512 typical gaps (standard deviations)Argentina: 1.5 births per woman, 0.216 typical gaps (standard deviations)Armenia: 1.7 births per woman, -0.118 typical gaps (standard deviations)Australia: 1.48 births per woman, 1.25 typical gaps (standard deviations)Austria: 1.31 births per woman, 1.26 typical gaps (standard deviations)Azerbaijan: 1.43 births per woman, -0.0603 typical gaps (standard deviations)Belgium: 1.44 births per woman, 0.818 typical gaps (standard deviations)Burkina Faso: 4.11 births per woman, -0.476 typical gaps (standard deviations)Bangladesh: 2.14 births per woman, -0.561 typical gaps (standard deviations)Bulgaria: 1.72 births per woman, -0.572 typical gaps (standard deviations)Bosnia and Herzegovina: 1.49 births per woman, -0.087 typical gaps (standard deviations)Belarus: 1.22 births per woman, 0.732 typical gaps (standard deviations)Bolivia: 2.52 births per woman, -0.361 typical gaps (standard deviations)Brazil: 1.61 births per woman, 0.123 typical gaps (standard deviations)Canada: 1.25 births per woman, 1.06 typical gaps (standard deviations)Switzerland: 1.29 births per woman, 1.55 typical gaps (standard deviations)Chile: 1.14 births per woman, 0.19 typical gaps (standard deviations)China: 1.01 births per woman, 0.913 typical gaps (standard deviations)Colombia: 1.63 births per woman, -0.125 typical gaps (standard deviations)Cyprus: 1.38 births per woman, -0.0176 typical gaps (standard deviations)Czechia: 1.36 births per woman, 0.726 typical gaps (standard deviations)Germany: 1.36 births per woman, 0.981 typical gaps (standard deviations)Denmark: 1.47 births per woman, 1.89 typical gaps (standard deviations)Algeria: 2.72 births per woman, -0.205 typical gaps (standard deviations)Ecuador: 1.81 births per woman, -0.164 typical gaps (standard deviations)Egypt, Arab Rep.: 2.73 births per woman, -1.08 typical gaps (standard deviations)Spain: 1.1 births per woman, 0.816 typical gaps (standard deviations)Estonia: 1.18 births per woman, 0.622 typical gaps (standard deviations)Ethiopia: 3.91 births per woman, -0.726 typical gaps (standard deviations)Finland: 1.25 births per woman, 1.87 typical gaps (standard deviations)France: 1.61 births per woman, 0.717 typical gaps (standard deviations)United Kingdom: 1.55 births per woman, 1.07 typical gaps (standard deviations)Georgia: 1.8 births per woman, -0.493 typical gaps (standard deviations)Ghana: 3.34 births per woman, -0.73 typical gaps (standard deviations)Greece: 1.24 births per woman, -0.284 typical gaps (standard deviations)Guatemala: 2.29 births per woman, 0.352 typical gaps (standard deviations)Hong Kong SAR, China: 0.841 births per woman, 0.0778 typical gaps (standard deviations)Croatia: 1.46 births per woman, 0.0883 typical gaps (standard deviations)Haiti: 2.63 births per woman, -0.461 typical gaps (standard deviations)Hungary: 1.41 births per woman, 0.266 typical gaps (standard deviations)Indonesia: 2.12 births per woman, -0.192 typical gaps (standard deviations)India: 1.96 births per woman, -0.736 typical gaps (standard deviations)Ireland: 1.47 births per woman, 0.894 typical gaps (standard deviations)Iran, Islamic Rep.: 1.68 births per woman, -0.684 typical gaps (standard deviations)Iraq: 3.22 births per woman, -0.726 typical gaps (standard deviations)Iceland: 1.56 births per woman, 1.78 typical gaps (standard deviations)Italy: 1.18 births per woman, 0.438 typical gaps (standard deviations)Jordan: 2.6 births per woman, -0.666 typical gaps (standard deviations)Japan: 1.15 births per woman, 0.552 typical gaps (standard deviations)Kazakhstan: 2.98 births per woman, 0.304 typical gaps (standard deviations)Kenya: 3.17 births per woman, -0.678 typical gaps (standard deviations)Kyrgyz Republic: 2.6 births per woman, 0.225 typical gaps (standard deviations)Korea, Rep.: 0.748 births per woman, 0.475 typical gaps (standard deviations)Kuwait: 1.56 births per woman, 0.607 typical gaps (standard deviations)Lebanon: 2.23 births per woman, -1.54 typical gaps (standard deviations)Libya: 2.3 births per woman, -0.158 typical gaps (standard deviations)Lithuania: 1.11 births per woman, 0.51 typical gaps (standard deviations)Luxembourg: 1.25 births per woman, 0.652 typical gaps (standard deviations)Latvia: 1.24 births per woman, 0.212 typical gaps (standard deviations)Macao SAR, China: 0.582 births per woman, 0.875 typical gaps (standard deviations)Morocco: 2.21 births per woman, -0.382 typical gaps (standard deviations)Moldova: 1.73 births per woman, -1.29 typical gaps (standard deviations)Maldives: 1.56 births per woman, 0.0845 typical gaps (standard deviations)Mexico: 1.89 births per woman, 0.335 typical gaps (standard deviations)North Macedonia: 1.4 births per woman, -0.171 typical gaps (standard deviations)Mali: 5.51 births per woman, -0.328 typical gaps (standard deviations)Malta: 1.01 births per woman, 0.15 typical gaps (standard deviations)Myanmar: 2.1 births per woman, -0.547 typical gaps (standard deviations)Montenegro: 1.8 births per woman, 0.239 typical gaps (standard deviations)Mongolia: 2.5 births per woman, 0.000193 typical gaps (standard deviations)Malaysia: 1.54 births per woman, 0.215 typical gaps (standard deviations)Nigeria: 4.38 births per woman, -0.611 typical gaps (standard deviations)Nicaragua: 2.21 births per woman, 0.0736 typical gaps (standard deviations)Netherlands: 1.43 births per woman, 1.54 typical gaps (standard deviations)Norway: 1.45 births per woman, 1.82 typical gaps (standard deviations)New Zealand: 1.57 births per woman, 1.46 typical gaps (standard deviations)Pakistan: 3.55 births per woman, -0.299 typical gaps (standard deviations)Peru: 1.97 births per woman, -0.348 typical gaps (standard deviations)Philippines: 1.89 births per woman, -0.119 typical gaps (standard deviations)Poland: 1.14 births per woman, 0.505 typical gaps (standard deviations)Puerto Rico (US): 0.92 births per woman, 0.077 typical gaps (standard deviations)Portugal: 1.41 births per woman, 0.195 typical gaps (standard deviations)West Bank and Gaza: 3.25 births per woman, -0.644 typical gaps (standard deviations)Qatar: 1.72 births per woman, 0.756 typical gaps (standard deviations)Romania: 1.39 births per woman, 0.197 typical gaps (standard deviations)Russian Federation: 1.42 births per woman, -0.00878 typical gaps (standard deviations)Rwanda: 3.65 births per woman, -0.867 typical gaps (standard deviations)Singapore: 0.97 births per woman, 0.779 typical gaps (standard deviations)Serbia: 1.64 births per woman, 0.105 typical gaps (standard deviations)Slovak Republic: 1.46 births per woman, 0.318 typical gaps (standard deviations)Slovenia: 1.52 births per woman, 0.55 typical gaps (standard deviations)Sweden: 1.43 births per woman, 1.7 typical gaps (standard deviations)Thailand: 1.2 births per woman, 0.256 typical gaps (standard deviations)Tajikistan: 3.04 births per woman, 0.104 typical gaps (standard deviations)Trinidad and Tobago: 1.54 births per woman, 0.0637 typical gaps (standard deviations)Tunisia: 1.82 births per woman, -0.73 typical gaps (standard deviations)Turkiye: 1.48 births per woman, -0.508 typical gaps (standard deviations)Ukraine: 0.988 births per woman, -0.244 typical gaps (standard deviations)Uruguay: 1.4 births per woman, 0.449 typical gaps (standard deviations)United States: 1.63 births per woman, 0.943 typical gaps (standard deviations)Uzbekistan: 3.49 births per woman, 0.617 typical gaps (standard deviations)Viet Nam: 1.9 births per woman, 0.469 typical gaps (standard deviations)Kosovo: 1.54 births per woman, -0.288 typical gaps (standard deviations)South Africa: 2.21 births per woman, -0.515 typical gaps (standard deviations)Zambia: 4.04 births per woman, -1.67 typical gaps (standard deviations)Zimbabwe: 3.67 births per woman, -1.98 typical gaps (standard deviations)ALBDNKFINLBNMDAMLINGANORUZBZMBZWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5362.7e-9107
By rank (Spearman), not adjusted-0.5912.0e-11107
Standard (Pearson), adjusted for national income+0.1260.197107
By rank (Spearman), adjusted for national income+0.0690.479107

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 107 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: +0.409 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.076 (without MLI) to +0.164 (without ZWE). 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 (-0.050).

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 & Pacific15+0.08
Europe & Central Asia49+0.34
Latin America & Caribbean14+0.10
Middle East, North Africa, Afghanistan & Pakistan14+0.24

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 third36-0.05
Middle third35-0.25
Richest third36+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
Christians62+0.03
Muslims29+0.29

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+0.04
Spain12+0.10
United Kingdom25-0.24

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 = +0.073 after dropping 9 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


births per woman
typical gaps (standard deviations)		Years
Mali MLI5.51-0.3282024, 2010
Nigeria NGA4.38-0.6112024, 2022
Burkina Faso BFA4.11-0.4762024, 2010
Zambia ZMB4.04-1.672024, 2010
Ethiopia ETH3.91-0.7262024, 2022
Zimbabwe ZWE3.67-1.982024, 2022
Rwanda RWA3.65-0.8672024, 2014
Pakistan PAK3.55-0.2992024, 2022
Uzbekistan UZB3.490.6172024, 2022
Ghana GHA3.34-0.732024, 2014
West Bank and Gaza PSE3.25-0.6442024, 2014
Iraq IRQ3.22-0.7262024, 2022
Kenya KEN3.17-0.6782024, 2022
Tajikistan TJK3.040.1042024, 2022
Kazakhstan KAZ2.980.3042024, 2022

World Bank, World Development Indicators
ivs; whr

Sources

Fertility rate

Fertility rate, total (births per woman)

World Bank · CC BY 4.0 · updated quarterly

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 2010–2024. 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 Fertility rate and Wellbeing score

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

More links with Fertility rate or Wellbeing score