placestats

Extreme poverty rate vs. Fertility rate

Fades after adjusting for income

Across 163 countries, Extreme poverty rate and Fertility rate rise and fall together at r = +0.76 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.37, which could easily be chance (q = 0.067, 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 extreme poverty rate, 0.4% to 17.9% of population, fertility rate is 0.813 births per woman higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.347 births per woman.

Link before adjusting (r)+0.760p = 6.0e-32 · 163 countries
After adjusting for national income+0.373p = 1.0e-6 · likely range [+0.23, +0.50]
p, allowing for regions0.009standard error 0.098 · 7 regions
Check for luck (q)0.067across 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.

Extreme poverty rate · % of populationlink with income -0.83 · proxy
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

Extreme poverty rate · % of population →Fertility rate · births per woman →0%85.3%0.7486.03Angola: 39.3% of population, 5.05 births per womanAlbania: 0.3% of population, 1.34 births per womanUnited Arab Emirates: 0% of population, 1.21 births per womanArgentina: 1% of population, 1.5 births per womanArmenia: 0.8% of population, 1.7 births per womanAustralia: 0.9% of population, 1.48 births per womanAustria: 0.5% of population, 1.31 births per womanBurundi: 74.2% of population, 4.79 births per womanBelgium: 0.1% of population, 1.44 births per womanBenin: 27.2% of population, 4.48 births per womanBurkina Faso: 42.1% of population, 4.11 births per womanBangladesh: 5.9% of population, 2.14 births per womanBulgaria: 1% of population, 1.72 births per womanBosnia and Herzegovina: 0.3% of population, 1.49 births per womanBelarus: 0% of population, 1.22 births per womanBelize: 1% of population, 2.02 births per womanBolivia: 2.1% of population, 2.52 births per womanBrazil: 3% of population, 1.61 births per womanBarbados: 1.7% of population, 1.71 births per womanBhutan: 0% of population, 1.45 births per womanBotswana: 21.4% of population, 2.7 births per womanCentral African Republic: 71.6% of population, 5.95 births per womanCanada: 0.3% of population, 1.25 births per womanSwitzerland: 0.2% of population, 1.29 births per womanChile: 0.4% of population, 1.14 births per womanChina: 0% of population, 1.01 births per womanCote d'Ivoire: 20.8% of population, 4.23 births per womanCameroon: 26.7% of population, 4.26 births per womanCongo, Dem. Rep.: 85.3% of population, 5.98 births per womanCongo, Rep.: 39.2% of population, 4.11 births per womanColombia: 8.5% of population, 1.63 births per womanComoros: 5.1% of population, 3.82 births per womanCabo Verde: 14.6% of population, 1.51 births per womanCosta Rica: 0.8% of population, 1.32 births per womanCyprus: 0% of population, 1.38 births per womanCzechia: 0% of population, 1.36 births per womanGermany: 0.7% of population, 1.36 births per womanDjibouti: 25.4% of population, 2.62 births per womanDenmark: 0.4% of population, 1.47 births per womanDominican Republic: 0.8% of population, 2.22 births per womanAlgeria: 0% of population, 2.72 births per womanEcuador: 3.4% of population, 1.81 births per womanEgypt, Arab Rep.: 1.4% of population, 2.73 births per womanSpain: 0.8% of population, 1.1 births per womanEstonia: 0.3% of population, 1.18 births per womanEthiopia: 38.6% of population, 3.91 births per womanFinland: 0.2% of population, 1.25 births per womanFiji: 4.7% of population, 2.27 births per womanFrance: 0.1% of population, 1.61 births per womanMicronesia, Fed. Sts.: 26.1% of population, 2.74 births per womanGabon: 3.8% of population, 3.59 births per womanUnited Kingdom: 0.4% of population, 1.55 births per womanGeorgia: 4.2% of population, 1.8 births per womanGhana: 39% of population, 3.34 births per womanGuinea: 11.7% of population, 4.13 births per womanGambia, The: 22% of population, 3.91 births per womanGuinea-Bissau: 39.9% of population, 3.76 births per womanEquatorial Guinea: 8.8% of population, 4.12 births per womanGreece: 0.6% of population, 1.24 births per womanGrenada: 0.8% of population, 1.47 births per womanGuatemala: 9.7% of population, 2.29 births per womanHonduras: 15.7% of population, 2.48 births per womanCroatia: 0.3% of population, 1.46 births per womanHaiti: 40.4% of population, 2.63 births per womanHungary: 0.9% of population, 1.41 births per womanIndonesia: 4% of population, 2.12 births per womanIndia: 5.3% of population, 1.96 births per womanIreland: 0.1% of population, 1.47 births per womanIran, Islamic Rep.: 2.5% of population, 1.68 births per womanIraq: 0.5% of population, 3.22 births per womanIceland: 0.1% of population, 1.56 births per womanIsrael: 0.4% of population, 2.87 births per womanItaly: 0.9% of population, 1.18 births per womanJamaica: 1.4% of population, 1.35 births per womanJordan: 0.1% of population, 2.6 births per womanJapan: 1.2% of population, 1.15 births per womanKazakhstan: 0% of population, 2.98 births per womanKenya: 45.5% of population, 3.17 births per womanKyrgyz Republic: 2.2% of population, 2.6 births per womanKiribati: 0.9% of population, 3.12 births per womanKorea, Rep.: 0.1% of population, 0.748 births per womanLao PDR: 7.1% of population, 2.4 births per womanLebanon: 5.8% of population, 2.23 births per womanLiberia: 33.6% of population, 3.86 births per womanSt. Lucia: 0.1% of population, 1.39 births per womanSri Lanka: 2.7% of population, 1.95 births per womanLesotho: 41.9% of population, 2.66 births per womanLithuania: 1.1% of population, 1.11 births per womanLuxembourg: 0.1% of population, 1.25 births per womanLatvia: 0.4% of population, 1.24 births per womanMorocco: 3.7% of population, 2.21 births per womanMoldova: 0.1% of population, 1.73 births per womanMadagascar: 69.2% of population, 3.91 births per womanMaldives: 0% of population, 1.56 births per womanMexico: 1.6% of population, 1.89 births per womanMarshall Islands: 2.1% of population, 2.86 births per womanNorth Macedonia: 3.9% of population, 1.4 births per womanMali: 36.1% of population, 5.51 births per womanMalta: 0.4% of population, 1.01 births per womanMyanmar: 10.3% of population, 2.1 births per womanMontenegro: 2.5% of population, 1.8 births per womanMongolia: 0.4% of population, 2.5 births per womanMozambique: 81.4% of population, 4.69 births per womanMauritania: 10.2% of population, 4.63 births per womanMauritius: 0.5% of population, 1.44 births per womanMalawi: 75.4% of population, 3.59 births per womanMalaysia: 0% of population, 1.54 births per womanNamibia: 22.9% of population, 3.21 births per womanNiger: 60.5% of population, 5.93 births per womanNigeria: 41.8% of population, 4.38 births per womanNicaragua: 6.6% of population, 2.21 births per womanNetherlands: 0.1% of population, 1.43 births per womanNorway: 0.2% of population, 1.45 births per womanNepal: 2.4% of population, 1.96 births per womanNaoero: 9.7% of population, 3.29 births per womanPakistan: 23% of population, 3.55 births per womanPanama: 3.1% of population, 2.11 births per womanPeru: 5.1% of population, 1.97 births per womanPhilippines: 5.3% of population, 1.89 births per womanPoland: 0.2% of population, 1.14 births per womanPortugal: 0.4% of population, 1.41 births per womanParaguay: 2.1% of population, 2.42 births per womanWest Bank and Gaza: 2.1% of population, 3.25 births per womanQatar: 0% of population, 1.72 births per womanRomania: 0.7% of population, 1.39 births per womanRussian Federation: 0.1% of population, 1.42 births per womanRwanda: 38.6% of population, 3.65 births per womanSudan: 10.1% of population, 4.26 births per womanSenegal: 17.9% of population, 3.77 births per womanSolomon Islands: 40.3% of population, 3.51 births per womanSierra Leone: 41.5% of population, 3.7 births per womanEl Salvador: 4.6% of population, 1.77 births per womanSerbia: 1.1% of population, 1.64 births per womanSao Tome and Principe: 13% of population, 3.6 births per womanSuriname: 2.2% of population, 2.23 births per womanSlovak Republic: 0.5% of population, 1.46 births per womanSlovenia: 0% of population, 1.52 births per womanSweden: 0.8% of population, 1.43 births per womanEswatini: 44.5% of population, 2.72 births per womanSeychelles: 0.7% of population, 1.85 births per womanSyrian Arab Republic: 18% of population, 2.7 births per womanChad: 39.5% of population, 6.03 births per womanTogo: 34.7% of population, 4.12 births per womanThailand: 0% of population, 1.2 births per womanTajikistan: 6.1% of population, 3.04 births per womanTimor-Leste: 44% of population, 2.63 births per womanTonga: 0.4% of population, 3.1 births per womanTunisia: 0.7% of population, 1.82 births per womanTurkiye: 0.2% of population, 1.48 births per womanTuvalu: 9% of population, 3.17 births per womanTanzania: 51.3% of population, 4.54 births per womanUganda: 59.8% of population, 4.17 births per womanUkraine: 0% of population, 0.988 births per womanUruguay: 0.2% of population, 1.4 births per womanUnited States: 1.1% of population, 1.63 births per womanUzbekistan: 2.3% of population, 3.49 births per womanViet Nam: 1.6% of population, 1.9 births per womanVanuatu: 19.5% of population, 3.57 births per womanSamoa: 4.5% of population, 3.8 births per womanKosovo: 10% of population, 1.54 births per womanSouth Africa: 17.4% of population, 2.21 births per womanZambia: 71.7% of population, 4.04 births per womanZimbabwe: 49.2% of population, 3.67 births per womanCAFCHNCODKORMDGMOZMRTMWISDNTCDUKRZMB

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.7606.0e-32163
By rank (Spearman), not adjusted+0.7834.9e-35163
Standard (Pearson), adjusted for national income+0.3731.0e-6163
By rank (Spearman), adjusted for national income+0.2870.000163

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: +0.387 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.342 (without COD) to +0.402 (without MWI). 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: COD (-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 & Pacific23-0.19
Europe & Central Asia47+0.04
Latin America & Caribbean24+0.09
Middle East, North Africa, Afghanistan & Pakistan16+0.02
Sub-Saharan Africa45+0.08

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+0.29
Middle third54+0.38
Richest third54+0.17

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+0.44
Muslims40+0.46

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+0.11
Never a European colony16+0.25
Spain20+0.16
United Kingdom48+0.37

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 = +0.359 after dropping 13 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 35years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Within countries over time, there is no link that is clearly more than chance (r = +0.170, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose extreme poverty rate moved did not tend to see their fertility rate move with it.

Across countries (adjusted)+0.373for comparison
Within countries+0.387each country vs itself
…and vs the same year elsewhere+0.170q = 0.205 · 120 countries
Year-on-year changes-0.058q = 0.287
Read with care.
  • Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.
  • Much of the within-country association disappears once shared global year effects are removed, which points to a common worldwide trend rather than a country-level relationship.

2,107 country-years (one country in one year), 120 countries, 1990–2024, about 18 years each on average. Share of the variation that happens within countries over time: 21% for Extreme poverty rate, 9% for Fertility rate. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

0.40−0.4-100+10years Fertility rate trails Extreme poverty rate →lag -10: r = 0.368 (n = 1,686)lag -9: r = 0.343 (n = 1,736)lag -8: r = 0.302 (n = 1,795)lag -7: r = 0.273 (n = 1,838)lag -6: r = 0.241 (n = 1,892)lag -5: r = 0.218 (n = 1,936)lag -4: r = 0.190 (n = 1,969)lag -3: r = 0.174 (n = 2,011)lag -2: r = 0.162 (n = 2,053)lag -1: r = 0.168 (n = 2,084)lag +0: r = 0.170 (n = 2,107)lag +1: r = 0.164 (n = 2,083)lag +2: r = 0.170 (n = 2,024)lag +3: r = 0.199 (n = 1,944)lag +4: r = 0.210 (n = 1,849)lag +5: r = 0.209 (n = 1,773)lag +6: r = 0.219 (n = 1,693)lag +7: r = 0.184 (n = 1,596)lag +8: r = 0.189 (n = 1,527)lag +9: r = 0.189 (n = 1,442)lag +10: r = 0.189 (n = 1,352)

Same year (lag 0): +0.170. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

This curve peaks at the edge of the window (lag -10), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.

The data


% of population
births per woman		Years
Congo, Dem. Rep. COD85.3%5.982020, 2024
Mozambique MOZ81.4%4.692022, 2024
Malawi MWI75.4%3.592019, 2024
Burundi BDI74.2%4.792020, 2024
Zambia ZMB71.7%4.042022, 2024
Central African Republic CAF71.6%5.952021, 2024
Madagascar MDG69.2%3.912021, 2024
Niger NER60.5%5.932021, 2024
Uganda UGA59.8%4.172019, 2024
Tanzania TZA51.3%4.542018, 2024
Zimbabwe ZWE49.2%3.672019, 2024
Kenya KEN45.5%3.172022, 2024
Eswatini SWZ44.5%2.722016, 2024
Timor-Leste TLS44%2.632014, 2024
Burkina Faso BFA42.1%4.112021, 2024

World Bank, World Development Indicators
World Bank, World Development Indicators

Sources

Extreme poverty rate

Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population)

World Bank · CC BY 4.0 · updated quarterly

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 Extreme poverty rate and Fertility rate

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

More links with Extreme poverty rate or Fertility rate