placestats

Birth rate vs. Equality score

Holds up after adjusting for income

Across 163 countries, Birth rate and Equality score rise and fall together at r = -0.69 (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 (q = 0.031, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak negative link remains. Caution: direction is not consistent across regions.

Comparing countries across the middle half of birth rate, 9.81 to 25.9 per 1,000 people, equality score is worse by 0.874 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.632 typical gaps.

Link before adjusting (r)-0.690p = 2.5e-24 · 163 countries
After adjusting for national income-0.328p = 2.0e-5 · likely range [-0.46, -0.18]
p, allowing for regions0.002standard error 0.063 · 7 regions
Check for luck (q)0.031across 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.

Birth rate · per 1,000 peoplelink with income -0.85 · proxy
Equality score · typical gaps (standard deviations)link with income +0.64 · 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

Birth rate · per 1,000 people →Equality score · typical gaps (standard deviations) →4.746.2-2.511.06Angola: 37.2 per 1,000 people, -1.52 typical gaps (standard deviations)Albania: 10.1 per 1,000 people, 0.741 typical gaps (standard deviations)United Arab Emirates: 9.82 per 1,000 people, 0.921 typical gaps (standard deviations)Argentina: 11.1 per 1,000 people, -0.0236 typical gaps (standard deviations)Armenia: 11.1 per 1,000 people, 0.843 typical gaps (standard deviations)Australia: 10.7 per 1,000 people, 0.473 typical gaps (standard deviations)Austria: 8.4 per 1,000 people, 0.632 typical gaps (standard deviations)Burundi: 33.2 per 1,000 people, -1.63 typical gaps (standard deviations)Belgium: 9.2 per 1,000 people, 0.895 typical gaps (standard deviations)Benin: 33.4 per 1,000 people, -0.24 typical gaps (standard deviations)Burkina Faso: 31.3 per 1,000 people, -0.796 typical gaps (standard deviations)Bangladesh: 20 per 1,000 people, 0.51 typical gaps (standard deviations)Bulgaria: 8.3 per 1,000 people, 0.143 typical gaps (standard deviations)Bosnia and Herzegovina: 7.72 per 1,000 people, 0.689 typical gaps (standard deviations)Belarus: 7.03 per 1,000 people, 1.04 typical gaps (standard deviations)Belize: 18.1 per 1,000 people, 0.12 typical gaps (standard deviations)Bolivia: 21 per 1,000 people, 0.0341 typical gaps (standard deviations)Brazil: 12.1 per 1,000 people, -0.529 typical gaps (standard deviations)Barbados: 11.1 per 1,000 people, 0.435 typical gaps (standard deviations)Bhutan: 12.5 per 1,000 people, 0.8 typical gaps (standard deviations)Botswana: 24.4 per 1,000 people, -1.27 typical gaps (standard deviations)Central African Republic: 46.2 per 1,000 people, -1.88 typical gaps (standard deviations)Canada: 8.9 per 1,000 people, 0.62 typical gaps (standard deviations)Switzerland: 8.7 per 1,000 people, 0.491 typical gaps (standard deviations)Chile: 8.72 per 1,000 people, -0.0426 typical gaps (standard deviations)China: 6.77 per 1,000 people, 0.37 typical gaps (standard deviations)Cote d'Ivoire: 31.6 per 1,000 people, -0.126 typical gaps (standard deviations)Cameroon: 33.3 per 1,000 people, -0.674 typical gaps (standard deviations)Congo, Dem. Rep.: 40.9 per 1,000 people, -2.33 typical gaps (standard deviations)Congo, Rep.: 30.4 per 1,000 people, -1.38 typical gaps (standard deviations)Colombia: 13.3 per 1,000 people, -0.906 typical gaps (standard deviations)Comoros: 28.2 per 1,000 people, 0.565 typical gaps (standard deviations)Cabo Verde: 12.2 per 1,000 people, -0.374 typical gaps (standard deviations)Costa Rica: 9.99 per 1,000 people, -0.196 typical gaps (standard deviations)Cyprus: 10.5 per 1,000 people, 0.611 typical gaps (standard deviations)Czechia: 7.7 per 1,000 people, 0.961 typical gaps (standard deviations)Germany: 8.1 per 1,000 people, 0.484 typical gaps (standard deviations)Djibouti: 20.9 per 1,000 people, -0.607 typical gaps (standard deviations)Denmark: 9.5 per 1,000 people, 0.709 typical gaps (standard deviations)Dominican Republic: 17.6 per 1,000 people, 0.177 typical gaps (standard deviations)Algeria: 18.8 per 1,000 people, 0.852 typical gaps (standard deviations)Ecuador: 14.8 per 1,000 people, -0.286 typical gaps (standard deviations)Egypt, Arab Rep.: 20.9 per 1,000 people, 0.764 typical gaps (standard deviations)Spain: 6.5 per 1,000 people, 0.498 typical gaps (standard deviations)Estonia: 7.1 per 1,000 people, 0.666 typical gaps (standard deviations)Ethiopia: 31.5 per 1,000 people, -0.344 typical gaps (standard deviations)Finland: 7.8 per 1,000 people, 0.858 typical gaps (standard deviations)Fiji: 17.9 per 1,000 people, 0.553 typical gaps (standard deviations)France: 9.7 per 1,000 people, 0.608 typical gaps (standard deviations)Micronesia, Fed. Sts.: 22.3 per 1,000 people, -0.538 typical gaps (standard deviations)Gabon: 27.1 per 1,000 people, 0.157 typical gaps (standard deviations)United Kingdom: 9.89 per 1,000 people, 0.566 typical gaps (standard deviations)Georgia: 11.3 per 1,000 people, 0.382 typical gaps (standard deviations)Ghana: 25.9 per 1,000 people, -1.07 typical gaps (standard deviations)Guinea: 33.3 per 1,000 people, 0.435 typical gaps (standard deviations)Gambia, The: 29.9 per 1,000 people, -0.358 typical gaps (standard deviations)Guinea-Bissau: 29.6 per 1,000 people, -0.509 typical gaps (standard deviations)Equatorial Guinea: 30 per 1,000 people, -0.000739 typical gaps (standard deviations)Greece: 6.6 per 1,000 people, 0.503 typical gaps (standard deviations)Grenada: 11.5 per 1,000 people, -0.0989 typical gaps (standard deviations)Guatemala: 20.6 per 1,000 people, -0.409 typical gaps (standard deviations)Honduras: 21.6 per 1,000 people, -0.592 typical gaps (standard deviations)Croatia: 8.3 per 1,000 people, 0.701 typical gaps (standard deviations)Haiti: 21.9 per 1,000 people, -0.964 typical gaps (standard deviations)Hungary: 8.2 per 1,000 people, 0.656 typical gaps (standard deviations)Indonesia: 15.8 per 1,000 people, 0.358 typical gaps (standard deviations)India: 16 per 1,000 people, 0.836 typical gaps (standard deviations)Ireland: 10 per 1,000 people, 0.769 typical gaps (standard deviations)Iran, Islamic Rep.: 12.6 per 1,000 people, 0.311 typical gaps (standard deviations)Iraq: 25.6 per 1,000 people, 0.713 typical gaps (standard deviations)Iceland: 11.2 per 1,000 people, 0.895 typical gaps (standard deviations)Israel: 18.6 per 1,000 people, 0.227 typical gaps (standard deviations)Italy: 6.3 per 1,000 people, 0.444 typical gaps (standard deviations)Jamaica: 11.4 per 1,000 people, 0.11 typical gaps (standard deviations)Jordan: 20.5 per 1,000 people, 0.499 typical gaps (standard deviations)Japan: 5.7 per 1,000 people, 0.551 typical gaps (standard deviations)Kazakhstan: 19.5 per 1,000 people, 0.76 typical gaps (standard deviations)Kenya: 27 per 1,000 people, -0.947 typical gaps (standard deviations)Kyrgyz Republic: 19.4 per 1,000 people, 0.801 typical gaps (standard deviations)Kiribati: 25.3 per 1,000 people, 0.995 typical gaps (standard deviations)Korea, Rep.: 4.7 per 1,000 people, 0.545 typical gaps (standard deviations)Lao PDR: 20.9 per 1,000 people, 0.261 typical gaps (standard deviations)Lebanon: 16 per 1,000 people, 0.249 typical gaps (standard deviations)Liberia: 30.6 per 1,000 people, -0.456 typical gaps (standard deviations)St. Lucia: 11.2 per 1,000 people, -0.0751 typical gaps (standard deviations)Sri Lanka: 10.1 per 1,000 people, 0.202 typical gaps (standard deviations)Lesotho: 23.8 per 1,000 people, -1.22 typical gaps (standard deviations)Lithuania: 6.6 per 1,000 people, 0.341 typical gaps (standard deviations)Luxembourg: 9.5 per 1,000 people, 0.505 typical gaps (standard deviations)Latvia: 6.9 per 1,000 people, 0.474 typical gaps (standard deviations)Morocco: 16.4 per 1,000 people, 0.0733 typical gaps (standard deviations)Moldova: 10.6 per 1,000 people, 0.895 typical gaps (standard deviations)Madagascar: 31.7 per 1,000 people, -1.46 typical gaps (standard deviations)Maldives: 10.6 per 1,000 people, 0.754 typical gaps (standard deviations)Mexico: 15.5 per 1,000 people, -0.0506 typical gaps (standard deviations)Marshall Islands: 20.1 per 1,000 people, 0.344 typical gaps (standard deviations)North Macedonia: 8.8 per 1,000 people, 0.413 typical gaps (standard deviations)Mali: 39.5 per 1,000 people, -0.544 typical gaps (standard deviations)Malta: 7.7 per 1,000 people, 0.6 typical gaps (standard deviations)Myanmar: 16.5 per 1,000 people, 0.408 typical gaps (standard deviations)Montenegro: 11.2 per 1,000 people, 0.403 typical gaps (standard deviations)Mongolia: 16.9 per 1,000 people, 0.623 typical gaps (standard deviations)Mozambique: 37 per 1,000 people, -2.51 typical gaps (standard deviations)Mauritania: 34 per 1,000 people, 0.336 typical gaps (standard deviations)Mauritius: 10.3 per 1,000 people, 0.311 typical gaps (standard deviations)Malawi: 31.1 per 1,000 people, -1.72 typical gaps (standard deviations)Malaysia: 12.4 per 1,000 people, 0.0997 typical gaps (standard deviations)Namibia: 25.9 per 1,000 people, -1.55 typical gaps (standard deviations)Niger: 41.4 per 1,000 people, -1.01 typical gaps (standard deviations)Nigeria: 32.5 per 1,000 people, -0.587 typical gaps (standard deviations)Nicaragua: 19.1 per 1,000 people, -0.386 typical gaps (standard deviations)Netherlands: 9.2 per 1,000 people, 0.958 typical gaps (standard deviations)Norway: 9.7 per 1,000 people, 0.91 typical gaps (standard deviations)Nepal: 19 per 1,000 people, 0.652 typical gaps (standard deviations)Naoero: 24.6 per 1,000 people, 0.326 typical gaps (standard deviations)Pakistan: 27.4 per 1,000 people, -0.0796 typical gaps (standard deviations)Panama: 15.9 per 1,000 people, -0.497 typical gaps (standard deviations)Peru: 15.8 per 1,000 people, 0.00275 typical gaps (standard deviations)Philippines: 15.9 per 1,000 people, 0.0435 typical gaps (standard deviations)Poland: 6.9 per 1,000 people, 0.795 typical gaps (standard deviations)Portugal: 7.9 per 1,000 people, 0.48 typical gaps (standard deviations)Paraguay: 19.7 per 1,000 people, -0.155 typical gaps (standard deviations)West Bank and Gaza: 26.5 per 1,000 people, 0.292 typical gaps (standard deviations)Qatar: 9.52 per 1,000 people, 0.421 typical gaps (standard deviations)Romania: 7.5 per 1,000 people, 0.708 typical gaps (standard deviations)Russian Federation: 8.4 per 1,000 people, 0.539 typical gaps (standard deviations)Rwanda: 28.1 per 1,000 people, -0.82 typical gaps (standard deviations)Sudan: 33 per 1,000 people, 0.213 typical gaps (standard deviations)Senegal: 29.2 per 1,000 people, -0.103 typical gaps (standard deviations)Solomon Islands: 26.7 per 1,000 people, -0.732 typical gaps (standard deviations)Sierra Leone: 30.1 per 1,000 people, -0.683 typical gaps (standard deviations)El Salvador: 15.6 per 1,000 people, 0.0329 typical gaps (standard deviations)Serbia: 9.2 per 1,000 people, 0.525 typical gaps (standard deviations)Sao Tome and Principe: 28.1 per 1,000 people, -0.235 typical gaps (standard deviations)Suriname: 17.2 per 1,000 people, 0.129 typical gaps (standard deviations)Slovak Republic: 8.5 per 1,000 people, 1.06 typical gaps (standard deviations)Slovenia: 7.9 per 1,000 people, 1.02 typical gaps (standard deviations)Sweden: 9.3 per 1,000 people, 0.734 typical gaps (standard deviations)Eswatini: 23.6 per 1,000 people, -1.85 typical gaps (standard deviations)Seychelles: 11 per 1,000 people, 0.575 typical gaps (standard deviations)Syrian Arab Republic: 23.2 per 1,000 people, 0.457 typical gaps (standard deviations)Chad: 43.3 per 1,000 people, -0.729 typical gaps (standard deviations)Togo: 32.1 per 1,000 people, -0.634 typical gaps (standard deviations)Thailand: 8.12 per 1,000 people, 0.525 typical gaps (standard deviations)Tajikistan: 25.3 per 1,000 people, 0.207 typical gaps (standard deviations)Timor-Leste: 21.8 per 1,000 people, -0.345 typical gaps (standard deviations)Tonga: 23 per 1,000 people, 0.87 typical gaps (standard deviations)Tunisia: 13.4 per 1,000 people, 0.484 typical gaps (standard deviations)Turkiye: 11 per 1,000 people, -0.0777 typical gaps (standard deviations)Tuvalu: 22 per 1,000 people, -0.0403 typical gaps (standard deviations)Tanzania: 34.8 per 1,000 people, -1.21 typical gaps (standard deviations)Uganda: 34.4 per 1,000 people, -1.56 typical gaps (standard deviations)Ukraine: 5.47 per 1,000 people, 0.967 typical gaps (standard deviations)Uruguay: 9.8 per 1,000 people, 0.135 typical gaps (standard deviations)United States: 10.6 per 1,000 people, 0.00824 typical gaps (standard deviations)Uzbekistan: 25.6 per 1,000 people, 0.5 typical gaps (standard deviations)Viet Nam: 13.4 per 1,000 people, 0.323 typical gaps (standard deviations)Vanuatu: 27.7 per 1,000 people, 0.0795 typical gaps (standard deviations)Samoa: 25 per 1,000 people, 0.0986 typical gaps (standard deviations)Kosovo: 11.9 per 1,000 people, -0.0202 typical gaps (standard deviations)South Africa: 18.5 per 1,000 people, -1.12 typical gaps (standard deviations)Zambia: 32.7 per 1,000 people, -2.37 typical gaps (standard deviations)Zimbabwe: 29.9 per 1,000 people, -1.72 typical gaps (standard deviations)BLRCAFCODCOLGINKIRMOZMRTSVNSWZUKRZMB

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6902.5e-24163
By rank (Spearman), not adjusted-0.6662.9e-22163
Standard (Pearson), adjusted for national income-0.3282.0e-5163
By rank (Spearman), adjusted for national income-0.2820.000163

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 163 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: +0.361 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.348 (without MRT) to -0.298 (without AGO). 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: AGO (+0.031).

Fragile: this link may not hold up.
  • direction is not consistent across regions
  • much weaker within regions than across them (largely a between-region difference)

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 & Pacific23+0.10
Europe & Central Asia47-0.08
Latin America & Caribbean24-0.05
Middle East, North Africa, Afghanistan & Pakistan16+0.10
Sub-Saharan Africa45-0.11

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 third55-0.31
Middle third54-0.37
Richest third54-0.30

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
Christians103-0.45
Muslims40-0.25

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
France24-0.10
Never a European colony16-0.06
Spain20+0.05
United Kingdom48-0.44

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 = -0.290 after dropping 5 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


per 1,000 people

typical gaps (standard deviations)
Years
Central African Republic CAF46.2-1.882024, 2021
Chad TCD43.3-0.7292024, 2022
Niger NER41.4-1.012024, 2021
Congo, Dem. Rep. COD40.9-2.332024, 2020
Mali MLI39.5-0.5442024, 2021
Angola AGO37.2-1.522024, 2018
Mozambique MOZ37-2.512024, 2022
Tanzania TZA34.8-1.212024, 2018
Uganda UGA34.4-1.562024, 2019
Mauritania MRT340.3362024, 2019
Benin BEN33.4-0.242024, 2021
Cameroon CMR33.3-0.6742024, 2021
Guinea GIN33.30.4352024, 2018
Burundi BDI33.2-1.632024, 2020
Sudan SDN330.2132024, 2014

World Bank, World Development Indicators
wdi

Sources

Birth rate

Birth rate, crude (per 1,000 people)

World Bank · CC BY 4.0 · updated quarterly

Equality score

Equality score

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

The average of 2 measures from 1 publisher. 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: Extreme poverty rate, Gini index.

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 Birth rate and Equality score

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

More links with Birth rate or Equality score