placestats

Equality score vs. Fertility rate

Fades after adjusting for income

Across 163 countries, Equality score and Fertility rate rise and fall together at r = -0.65 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.26, which could easily be chance (q = 0.11, 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: much weaker within regions than across them (largely a between-region difference).

Comparing countries across the middle half of fertility rate, 1.46 to 3.32 births per woman, equality score is worse by 0.761 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.401 typical gaps.

Link before adjusting (r)-0.647p = 1.1e-20 · 163 countries
After adjusting for national income-0.256p = 0.001 · likely range [-0.39, -0.11]
p, allowing for regions0.017standard error 0.078 · 7 regions
Check for luck (q)0.111across 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.

Equality score · typical gaps (standard deviations)link with income +0.64 · high
Fertility rate · births per womanlink with income -0.81 · proxy

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

Equality score · typical gaps (standard deviations) →Fertility rate · births per woman →-2.511.060.7486.03Angola: -1.52 typical gaps (standard deviations), 5.05 births per womanAlbania: 0.741 typical gaps (standard deviations), 1.34 births per womanUnited Arab Emirates: 0.921 typical gaps (standard deviations), 1.21 births per womanArgentina: -0.0236 typical gaps (standard deviations), 1.5 births per womanArmenia: 0.843 typical gaps (standard deviations), 1.7 births per womanAustralia: 0.473 typical gaps (standard deviations), 1.48 births per womanAustria: 0.632 typical gaps (standard deviations), 1.31 births per womanBurundi: -1.63 typical gaps (standard deviations), 4.79 births per womanBelgium: 0.895 typical gaps (standard deviations), 1.44 births per womanBenin: -0.24 typical gaps (standard deviations), 4.48 births per womanBurkina Faso: -0.796 typical gaps (standard deviations), 4.11 births per womanBangladesh: 0.51 typical gaps (standard deviations), 2.14 births per womanBulgaria: 0.143 typical gaps (standard deviations), 1.72 births per womanBosnia and Herzegovina: 0.689 typical gaps (standard deviations), 1.49 births per womanBelarus: 1.04 typical gaps (standard deviations), 1.22 births per womanBelize: 0.12 typical gaps (standard deviations), 2.02 births per womanBolivia: 0.0341 typical gaps (standard deviations), 2.52 births per womanBrazil: -0.529 typical gaps (standard deviations), 1.61 births per womanBarbados: 0.435 typical gaps (standard deviations), 1.71 births per womanBhutan: 0.8 typical gaps (standard deviations), 1.45 births per womanBotswana: -1.27 typical gaps (standard deviations), 2.7 births per womanCentral African Republic: -1.88 typical gaps (standard deviations), 5.95 births per womanCanada: 0.62 typical gaps (standard deviations), 1.25 births per womanSwitzerland: 0.491 typical gaps (standard deviations), 1.29 births per womanChile: -0.0426 typical gaps (standard deviations), 1.14 births per womanChina: 0.37 typical gaps (standard deviations), 1.01 births per womanCote d'Ivoire: -0.126 typical gaps (standard deviations), 4.23 births per womanCameroon: -0.674 typical gaps (standard deviations), 4.26 births per womanCongo, Dem. Rep.: -2.33 typical gaps (standard deviations), 5.98 births per womanCongo, Rep.: -1.38 typical gaps (standard deviations), 4.11 births per womanColombia: -0.906 typical gaps (standard deviations), 1.63 births per womanComoros: 0.565 typical gaps (standard deviations), 3.82 births per womanCabo Verde: -0.374 typical gaps (standard deviations), 1.51 births per womanCosta Rica: -0.196 typical gaps (standard deviations), 1.32 births per womanCyprus: 0.611 typical gaps (standard deviations), 1.38 births per womanCzechia: 0.961 typical gaps (standard deviations), 1.36 births per womanGermany: 0.484 typical gaps (standard deviations), 1.36 births per womanDjibouti: -0.607 typical gaps (standard deviations), 2.62 births per womanDenmark: 0.709 typical gaps (standard deviations), 1.47 births per womanDominican Republic: 0.177 typical gaps (standard deviations), 2.22 births per womanAlgeria: 0.852 typical gaps (standard deviations), 2.72 births per womanEcuador: -0.286 typical gaps (standard deviations), 1.81 births per womanEgypt, Arab Rep.: 0.764 typical gaps (standard deviations), 2.73 births per womanSpain: 0.498 typical gaps (standard deviations), 1.1 births per womanEstonia: 0.666 typical gaps (standard deviations), 1.18 births per womanEthiopia: -0.344 typical gaps (standard deviations), 3.91 births per womanFinland: 0.858 typical gaps (standard deviations), 1.25 births per womanFiji: 0.553 typical gaps (standard deviations), 2.27 births per womanFrance: 0.608 typical gaps (standard deviations), 1.61 births per womanMicronesia, Fed. Sts.: -0.538 typical gaps (standard deviations), 2.74 births per womanGabon: 0.157 typical gaps (standard deviations), 3.59 births per womanUnited Kingdom: 0.566 typical gaps (standard deviations), 1.55 births per womanGeorgia: 0.382 typical gaps (standard deviations), 1.8 births per womanGhana: -1.07 typical gaps (standard deviations), 3.34 births per womanGuinea: 0.435 typical gaps (standard deviations), 4.13 births per womanGambia, The: -0.358 typical gaps (standard deviations), 3.91 births per womanGuinea-Bissau: -0.509 typical gaps (standard deviations), 3.76 births per womanEquatorial Guinea: -0.000739 typical gaps (standard deviations), 4.12 births per womanGreece: 0.503 typical gaps (standard deviations), 1.24 births per womanGrenada: -0.0989 typical gaps (standard deviations), 1.47 births per womanGuatemala: -0.409 typical gaps (standard deviations), 2.29 births per womanHonduras: -0.592 typical gaps (standard deviations), 2.48 births per womanCroatia: 0.701 typical gaps (standard deviations), 1.46 births per womanHaiti: -0.964 typical gaps (standard deviations), 2.63 births per womanHungary: 0.656 typical gaps (standard deviations), 1.41 births per womanIndonesia: 0.358 typical gaps (standard deviations), 2.12 births per womanIndia: 0.836 typical gaps (standard deviations), 1.96 births per womanIreland: 0.769 typical gaps (standard deviations), 1.47 births per womanIran, Islamic Rep.: 0.311 typical gaps (standard deviations), 1.68 births per womanIraq: 0.713 typical gaps (standard deviations), 3.22 births per womanIceland: 0.895 typical gaps (standard deviations), 1.56 births per womanIsrael: 0.227 typical gaps (standard deviations), 2.87 births per womanItaly: 0.444 typical gaps (standard deviations), 1.18 births per womanJamaica: 0.11 typical gaps (standard deviations), 1.35 births per womanJordan: 0.499 typical gaps (standard deviations), 2.6 births per womanJapan: 0.551 typical gaps (standard deviations), 1.15 births per womanKazakhstan: 0.76 typical gaps (standard deviations), 2.98 births per womanKenya: -0.947 typical gaps (standard deviations), 3.17 births per womanKyrgyz Republic: 0.801 typical gaps (standard deviations), 2.6 births per womanKiribati: 0.995 typical gaps (standard deviations), 3.12 births per womanKorea, Rep.: 0.545 typical gaps (standard deviations), 0.748 births per womanLao PDR: 0.261 typical gaps (standard deviations), 2.4 births per womanLebanon: 0.249 typical gaps (standard deviations), 2.23 births per womanLiberia: -0.456 typical gaps (standard deviations), 3.86 births per womanSt. Lucia: -0.0751 typical gaps (standard deviations), 1.39 births per womanSri Lanka: 0.202 typical gaps (standard deviations), 1.95 births per womanLesotho: -1.22 typical gaps (standard deviations), 2.66 births per womanLithuania: 0.341 typical gaps (standard deviations), 1.11 births per womanLuxembourg: 0.505 typical gaps (standard deviations), 1.25 births per womanLatvia: 0.474 typical gaps (standard deviations), 1.24 births per womanMorocco: 0.0733 typical gaps (standard deviations), 2.21 births per womanMoldova: 0.895 typical gaps (standard deviations), 1.73 births per womanMadagascar: -1.46 typical gaps (standard deviations), 3.91 births per womanMaldives: 0.754 typical gaps (standard deviations), 1.56 births per womanMexico: -0.0506 typical gaps (standard deviations), 1.89 births per womanMarshall Islands: 0.344 typical gaps (standard deviations), 2.86 births per womanNorth Macedonia: 0.413 typical gaps (standard deviations), 1.4 births per womanMali: -0.544 typical gaps (standard deviations), 5.51 births per womanMalta: 0.6 typical gaps (standard deviations), 1.01 births per womanMyanmar: 0.408 typical gaps (standard deviations), 2.1 births per womanMontenegro: 0.403 typical gaps (standard deviations), 1.8 births per womanMongolia: 0.623 typical gaps (standard deviations), 2.5 births per womanMozambique: -2.51 typical gaps (standard deviations), 4.69 births per womanMauritania: 0.336 typical gaps (standard deviations), 4.63 births per womanMauritius: 0.311 typical gaps (standard deviations), 1.44 births per womanMalawi: -1.72 typical gaps (standard deviations), 3.59 births per womanMalaysia: 0.0997 typical gaps (standard deviations), 1.54 births per womanNamibia: -1.55 typical gaps (standard deviations), 3.21 births per womanNiger: -1.01 typical gaps (standard deviations), 5.93 births per womanNigeria: -0.587 typical gaps (standard deviations), 4.38 births per womanNicaragua: -0.386 typical gaps (standard deviations), 2.21 births per womanNetherlands: 0.958 typical gaps (standard deviations), 1.43 births per womanNorway: 0.91 typical gaps (standard deviations), 1.45 births per womanNepal: 0.652 typical gaps (standard deviations), 1.96 births per womanNaoero: 0.326 typical gaps (standard deviations), 3.29 births per womanPakistan: -0.0796 typical gaps (standard deviations), 3.55 births per womanPanama: -0.497 typical gaps (standard deviations), 2.11 births per womanPeru: 0.00275 typical gaps (standard deviations), 1.97 births per womanPhilippines: 0.0435 typical gaps (standard deviations), 1.89 births per womanPoland: 0.795 typical gaps (standard deviations), 1.14 births per womanPortugal: 0.48 typical gaps (standard deviations), 1.41 births per womanParaguay: -0.155 typical gaps (standard deviations), 2.42 births per womanWest Bank and Gaza: 0.292 typical gaps (standard deviations), 3.25 births per womanQatar: 0.421 typical gaps (standard deviations), 1.72 births per womanRomania: 0.708 typical gaps (standard deviations), 1.39 births per womanRussian Federation: 0.539 typical gaps (standard deviations), 1.42 births per womanRwanda: -0.82 typical gaps (standard deviations), 3.65 births per womanSudan: 0.213 typical gaps (standard deviations), 4.26 births per womanSenegal: -0.103 typical gaps (standard deviations), 3.77 births per womanSolomon Islands: -0.732 typical gaps (standard deviations), 3.51 births per womanSierra Leone: -0.683 typical gaps (standard deviations), 3.7 births per womanEl Salvador: 0.0329 typical gaps (standard deviations), 1.77 births per womanSerbia: 0.525 typical gaps (standard deviations), 1.64 births per womanSao Tome and Principe: -0.235 typical gaps (standard deviations), 3.6 births per womanSuriname: 0.129 typical gaps (standard deviations), 2.23 births per womanSlovak Republic: 1.06 typical gaps (standard deviations), 1.46 births per womanSlovenia: 1.02 typical gaps (standard deviations), 1.52 births per womanSweden: 0.734 typical gaps (standard deviations), 1.43 births per womanEswatini: -1.85 typical gaps (standard deviations), 2.72 births per womanSeychelles: 0.575 typical gaps (standard deviations), 1.85 births per womanSyrian Arab Republic: 0.457 typical gaps (standard deviations), 2.7 births per womanChad: -0.729 typical gaps (standard deviations), 6.03 births per womanTogo: -0.634 typical gaps (standard deviations), 4.12 births per womanThailand: 0.525 typical gaps (standard deviations), 1.2 births per womanTajikistan: 0.207 typical gaps (standard deviations), 3.04 births per womanTimor-Leste: -0.345 typical gaps (standard deviations), 2.63 births per womanTonga: 0.87 typical gaps (standard deviations), 3.1 births per womanTunisia: 0.484 typical gaps (standard deviations), 1.82 births per womanTurkiye: -0.0777 typical gaps (standard deviations), 1.48 births per womanTuvalu: -0.0403 typical gaps (standard deviations), 3.17 births per womanTanzania: -1.21 typical gaps (standard deviations), 4.54 births per womanUganda: -1.56 typical gaps (standard deviations), 4.17 births per womanUkraine: 0.967 typical gaps (standard deviations), 0.988 births per womanUruguay: 0.135 typical gaps (standard deviations), 1.4 births per womanUnited States: 0.00824 typical gaps (standard deviations), 1.63 births per womanUzbekistan: 0.5 typical gaps (standard deviations), 3.49 births per womanViet Nam: 0.323 typical gaps (standard deviations), 1.9 births per womanVanuatu: 0.0795 typical gaps (standard deviations), 3.57 births per womanSamoa: 0.0986 typical gaps (standard deviations), 3.8 births per womanKosovo: -0.0202 typical gaps (standard deviations), 1.54 births per womanSouth Africa: -1.12 typical gaps (standard deviations), 2.21 births per womanZambia: -2.37 typical gaps (standard deviations), 4.04 births per womanZimbabwe: -1.72 typical gaps (standard deviations), 3.67 births per womanAREBLRCAFCODCOLGINMOZMRTSWZTCDUKRZMB

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6471.1e-20163
By rank (Spearman), not adjusted-0.6087.7e-18163
Standard (Pearson), adjusted for national income-0.2560.001163
By rank (Spearman), adjusted for national income-0.1650.036163

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: +0.391 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.276 (without MRT) to -0.222 (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 (+0.034).

Fragile: this link may not hold up.
  • 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 Asia47-0.02
Latin America & Caribbean24-0.03
Middle East, North Africa, Afghanistan & Pakistan16-0.00
Sub-Saharan Africa45-0.01

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 third55-0.25
Middle third54-0.26
Richest third54-0.13

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
Christians103-0.34
Muslims40-0.29

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
France24-0.09
Never a European colony16-0.04
Spain20+0.11
United Kingdom48-0.30

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 = -0.211 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


typical gaps (standard deviations)

births per woman
Years
Slovak Republic SVK1.061.462023, 2024
Belarus BLR1.041.222020, 2024
Slovenia SVN1.021.522023, 2024
Kiribati KIR0.9953.122023, 2024
Ukraine UKR0.9670.9882020, 2024
Czechia CZE0.9611.362023, 2024
Netherlands NLD0.9581.432021, 2024
United Arab Emirates ARE0.9211.212018, 2024
Norway NOR0.911.452023, 2024
Moldova MDA0.8951.732023, 2024
Iceland ISL0.8951.562019, 2024
Belgium BEL0.8951.442023, 2024
Tonga TON0.873.12021, 2024
Finland FIN0.8581.252023, 2024
Algeria DZA0.8522.722011, 2024

wdi
World Bank, World Development Indicators

Sources

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.

Fertility rate

Fertility rate, total (births per woman)

World Bank · CC BY 4.0 · updated quarterly

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 Equality score and Fertility rate

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

More links with Equality score or Fertility rate