placestats

Fertility rate vs. Secondary enrollment

Fades after adjusting for income

Across 187 countries, Fertility rate and Secondary enrollment rise and fall together at r = -0.75 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.35, which could easily be chance (q = 0.075, 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 fertility rate, 1.44 to 3.09 births per woman, secondary enrollment is worse by 27.3% gross at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 15.5% gross.

Link before adjusting (r)-0.750p = 4.2e-35 · 187 countries
After adjusting for national income-0.350p = 1.0e-6 · likely range [-0.47, -0.22]
p, allowing for regions0.011standard error 0.095 · 7 regions
Check for luck (q)0.075across 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
Secondary enrollment · % grosslink with income +0.71 · 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 →Secondary enrollment · % gross →0.5826.033.35%143%Aruba: 1.61 births per woman, 124% grossAfghanistan: 4.76 births per woman, 59.6% grossAngola: 5.05 births per woman, 51.5% grossAlbania: 1.34 births per woman, 108% grossAndorra: 1.09 births per woman, 102% grossUnited Arab Emirates: 1.21 births per woman, 102% grossArgentina: 1.5 births per woman, 106% grossArmenia: 1.7 births per woman, 90.9% grossAntigua and Barbuda: 1.58 births per woman, 109% grossAustralia: 1.48 births per woman, 132% grossAustria: 1.31 births per woman, 101% grossAzerbaijan: 1.43 births per woman, 91.1% grossBurundi: 4.79 births per woman, 23.1% grossBelgium: 1.44 births per woman, 143% grossBenin: 4.48 births per woman, 43.6% grossBurkina Faso: 4.11 births per woman, 30% grossBangladesh: 2.14 births per woman, 64.3% grossBulgaria: 1.72 births per woman, 94.8% grossBahrain: 1.8 births per woman, 98.8% grossBahamas, The: 1.37 births per woman, 79.5% grossBosnia and Herzegovina: 1.49 births per woman, 87.9% grossBelarus: 1.22 births per woman, 94.8% grossBelize: 2.02 births per woman, 86.5% grossBermuda: 1.41 births per woman, 74.4% grossBolivia: 2.52 births per woman, 90.5% grossBrazil: 1.61 births per woman, 104% grossBarbados: 1.71 births per woman, 104% grossBrunei Darussalam: 1.73 births per woman, 91.8% grossBhutan: 1.45 births per woman, 86.2% grossBotswana: 2.7 births per woman, 70.6% grossCentral African Republic: 5.95 births per woman, 15.8% grossCanada: 1.25 births per woman, 104% grossSwitzerland: 1.29 births per woman, 101% grossChile: 1.14 births per woman, 106% grossChina: 1.01 births per woman, 92.3% grossCote d'Ivoire: 4.23 births per woman, 65.3% grossCameroon: 4.26 births per woman, 44.8% grossCongo, Dem. Rep.: 5.98 births per woman, 55.5% grossCongo, Rep.: 4.11 births per woman, 50.5% grossColombia: 1.63 births per woman, 102% grossComoros: 3.82 births per woman, 54.8% grossCabo Verde: 1.51 births per woman, 96.4% grossCosta Rica: 1.32 births per woman, 122% grossCuracao: 1.4 births per woman, 89.9% grossCayman Islands: 1.52 births per woman, 84.8% grossCyprus: 1.38 births per woman, 107% grossCzechia: 1.36 births per woman, 97.6% grossGermany: 1.36 births per woman, 100% grossDominica: 1.48 births per woman, 103% grossDenmark: 1.47 births per woman, 126% grossDominican Republic: 2.22 births per woman, 76.4% grossAlgeria: 2.72 births per woman, 105% grossEcuador: 1.81 births per woman, 92.8% grossEgypt, Arab Rep.: 2.73 births per woman, 84.8% grossSpain: 1.1 births per woman, 119% grossEstonia: 1.18 births per woman, 109% grossEthiopia: 3.91 births per woman, 33.9% grossFinland: 1.25 births per woman, 142% grossFiji: 2.27 births per woman, 98.1% grossFrance: 1.61 births per woman, 104% grossGabon: 3.59 births per woman, 70.3% grossUnited Kingdom: 1.55 births per woman, 112% grossGeorgia: 1.8 births per woman, 101% grossGhana: 3.34 births per woman, 75.7% grossGuinea: 4.13 births per woman, 38.6% grossGambia, The: 3.91 births per woman, 107% grossGreece: 1.24 births per woman, 105% grossGrenada: 1.47 births per woman, 101% grossGuatemala: 2.29 births per woman, 49.6% grossGuyana: 2.4 births per woman, 91.4% grossHong Kong SAR, China: 0.841 births per woman, 107% grossHonduras: 2.48 births per woman, 51.8% grossCroatia: 1.46 births per woman, 105% grossHungary: 1.41 births per woman, 107% grossIndonesia: 2.12 births per woman, 97.2% grossIndia: 1.96 births per woman, 79.6% grossIreland: 1.47 births per woman, 131% grossIran, Islamic Rep.: 1.68 births per woman, 85.1% grossIceland: 1.56 births per woman, 109% grossIsrael: 2.87 births per woman, 98.5% grossItaly: 1.18 births per woman, 101% grossJamaica: 1.35 births per woman, 84.5% grossJordan: 2.6 births per woman, 91.8% grossJapan: 1.15 births per woman, 102% grossKazakhstan: 2.98 births per woman, 97.6% grossKenya: 3.17 births per woman, 84.3% grossKyrgyz Republic: 2.6 births per woman, 91.7% grossCambodia: 2.55 births per woman, 58.8% grossKiribati: 3.12 births per woman, 90.3% grossSt. Kitts and Nevis: 1.53 births per woman, 138% grossKorea, Rep.: 0.748 births per woman, 96.3% grossKuwait: 1.56 births per woman, 95.4% grossLao PDR: 2.4 births per woman, 50.5% grossLebanon: 2.23 births per woman, 63.8% grossLiberia: 3.86 births per woman, 37.7% grossSt. Lucia: 1.39 births per woman, 87.9% grossSri Lanka: 1.95 births per woman, 88% grossLesotho: 2.66 births per woman, 59.4% grossLithuania: 1.11 births per woman, 105% grossLuxembourg: 1.25 births per woman, 109% grossLatvia: 1.24 births per woman, 101% grossMacao SAR, China: 0.582 births per woman, 94.7% grossMorocco: 2.21 births per woman, 90% grossMoldova: 1.73 births per woman, 99.3% grossMadagascar: 3.91 births per woman, 34.1% grossMaldives: 1.56 births per woman, 79.4% grossMexico: 1.89 births per woman, 103% grossMarshall Islands: 2.86 births per woman, 85.8% grossNorth Macedonia: 1.4 births per woman, 90.1% grossMali: 5.51 births per woman, 38.9% grossMalta: 1.01 births per woman, 103% grossMyanmar: 2.1 births per woman, 77% grossMontenegro: 1.8 births per woman, 93.9% grossMongolia: 2.5 births per woman, 96.8% grossMozambique: 4.69 births per woman, 37.2% grossMauritania: 4.63 births per woman, 36% grossMauritius: 1.44 births per woman, 90.7% grossMalawi: 3.59 births per woman, 36.6% grossMalaysia: 1.54 births per woman, 80.3% grossNamibia: 3.21 births per woman, 82% grossNiger: 5.93 births per woman, 19.9% grossNigeria: 4.38 births per woman, 46.9% grossNicaragua: 2.21 births per woman, 70.2% grossNetherlands: 1.43 births per woman, 138% grossNorway: 1.45 births per woman, 116% grossNepal: 1.96 births per woman, 90.4% grossNaoero: 3.29 births per woman, 94.5% grossNew Zealand: 1.57 births per woman, 114% grossOman: 2.51 births per woman, 95.1% grossPakistan: 3.55 births per woman, 48.3% grossPanama: 2.11 births per woman, 76.6% grossPeru: 1.97 births per woman, 108% grossPhilippines: 1.89 births per woman, 85.3% grossPalau: 1.88 births per woman, 95.7% grossPapua New Guinea: 3.07 births per woman, 52.1% grossPoland: 1.14 births per woman, 108% grossPuerto Rico (US): 0.92 births per woman, 81.5% grossPortugal: 1.41 births per woman, 120% grossParaguay: 2.42 births per woman, 79.1% grossWest Bank and Gaza: 3.25 births per woman, 89.1% grossQatar: 1.72 births per woman, 99.6% grossRomania: 1.39 births per woman, 81.6% grossRussian Federation: 1.42 births per woman, 92.5% grossRwanda: 3.65 births per woman, 48.8% grossSaudi Arabia: 2.31 births per woman, 111% grossSudan: 4.26 births per woman, 43.5% grossSenegal: 3.77 births per woman, 44.1% grossSingapore: 0.97 births per woman, 103% grossSolomon Islands: 3.51 births per woman, 49% grossSierra Leone: 3.7 births per woman, 86.9% grossEl Salvador: 1.77 births per woman, 62.1% grossSan Marino: 1.16 births per woman, 60.4% grossSomalia, Fed. Rep.: 6.01 births per woman, 3.35% grossSerbia: 1.64 births per woman, 89.8% grossSao Tome and Principe: 3.6 births per woman, 90.4% grossSuriname: 2.23 births per woman, 76.1% grossSlovak Republic: 1.46 births per woman, 93.2% grossSlovenia: 1.52 births per woman, 108% grossSweden: 1.43 births per woman, 132% grossEswatini: 2.72 births per woman, 82% grossSint Maarten (Dutch part): 1.44 births per woman, 111% grossSeychelles: 1.85 births per woman, 70.8% grossSyrian Arab Republic: 2.7 births per woman, 38.7% grossTurks and Caicos Islands: 1.45 births per woman, 120% grossChad: 6.03 births per woman, 23.5% grossTogo: 4.12 births per woman, 63.4% grossThailand: 1.2 births per woman, 92.1% grossTajikistan: 3.04 births per woman, 86.9% grossTurkmenistan: 2.66 births per woman, 94.6% grossTimor-Leste: 2.63 births per woman, 84.7% grossTonga: 3.1 births per woman, 92.4% grossTrinidad and Tobago: 1.54 births per woman, 95.7% grossTunisia: 1.82 births per woman, 90.3% grossTurkiye: 1.48 births per woman, 118% grossTuvalu: 3.17 births per woman, 90.7% grossTanzania: 4.54 births per woman, 28.2% grossUkraine: 0.988 births per woman, 86.2% grossUruguay: 1.4 births per woman, 119% grossUnited States: 1.63 births per woman, 97.5% grossUzbekistan: 3.49 births per woman, 98.1% grossSt. Vincent and the Grenadines: 1.76 births per woman, 125% grossViet Nam: 1.9 births per woman, 93.4% grossVanuatu: 3.57 births per woman, 135% grossSamoa: 3.8 births per woman, 87.4% grossSouth Africa: 2.21 births per woman, 104% grossZambia: 4.04 births per woman, 56.8% grossZimbabwe: 3.67 births per woman, 52.4% grossBELCAFCODFINGMBGTMNERNLDSMRSOMSYRVUT

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.7504.2e-35187
By rank (Spearman), not adjusted-0.6552.8e-24187
Standard (Pearson), adjusted for national income-0.3501.0e-6187
By rank (Spearman), adjusted for national income-0.1780.015187

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 187 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: +0.401 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.365 (without VUT) to -0.331 (without SOM). 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: SOM (+0.018).

Fragile: this link may not hold up.
  • direction is not consistent across regions

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 & Pacific30+0.23
Europe & Central Asia50+0.14
Latin America & Caribbean36-0.38
Middle East, North Africa, Afghanistan & Pakistan19+0.05
Sub-Saharan Africa43-0.51

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 third63-0.41
Middle third62-0.11
Richest third62-0.05

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
Christians107-0.29
Muslims45-0.46

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
France23-0.31
Never a European colony21-0.07
Spain18-0.53
United Kingdom60-0.39

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 = -0.294 after dropping 6 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.

The link shows up within countries over time (r = -0.271) but mostly disappears in year-to-year changes (r = -0.026). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)-0.350for comparison
Within countries-0.618each country vs itself
…and vs the same year elsewhere-0.271q = 0.000 · 195 countries
Year-on-year changes-0.026q = 0.593
Read with care.
  • Almost all of this indicator's variation is between countries, not within them, 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.
  • The association is much weaker in year-on-year changes than in levels, which points to shared country-specific trends.

4,361 country-years (one country in one year), 195 countries, 1990–2024, about 22 years each on average. Share of the variation that happens within countries over time: 10% for Fertility rate, 13% for Secondary enrollment. 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

0.30−0.3-100+10years Secondary enrollment trails Fertility rate →lag -10: r = -0.194 (n = 2,940)lag -9: r = -0.210 (n = 3,096)lag -8: r = -0.225 (n = 3,242)lag -7: r = -0.233 (n = 3,392)lag -6: r = -0.246 (n = 3,530)lag -5: r = -0.257 (n = 3,673)lag -4: r = -0.267 (n = 3,820)lag -3: r = -0.281 (n = 3,967)lag -2: r = -0.280 (n = 4,106)lag -1: r = -0.277 (n = 4,255)lag +0: r = -0.271 (n = 4,361)lag +1: r = -0.256 (n = 4,282)lag +2: r = -0.257 (n = 4,191)lag +3: r = -0.256 (n = 4,096)lag +4: r = -0.253 (n = 4,015)lag +5: r = -0.247 (n = 3,924)lag +6: r = -0.247 (n = 3,853)lag +7: r = -0.241 (n = 3,782)lag +8: r = -0.236 (n = 3,725)lag +9: r = -0.213 (n = 3,665)lag +10: r = -0.194 (n = 3,551)

Same year (lag 0): -0.271. 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.

The data


births per woman
% gross		Years
Chad TCD6.0323.5%2024
Somalia, Fed. Rep. SOM6.013.35%2024, 2023
Congo, Dem. Rep. COD5.9855.5%2024, 2023
Central African Republic CAF5.9515.8%2024, 2017
Niger NER5.9319.9%2024
Mali MLI5.5138.9%2024, 2023
Angola AGO5.0551.5%2024, 2023
Burundi BDI4.7923.1%2024, 2025
Afghanistan AFG4.7659.6%2024, 2023
Mozambique MOZ4.6937.2%2024, 2017
Mauritania MRT4.6336%2024, 2020
Tanzania TZA4.5428.2%2024, 2021
Benin BEN4.4843.6%2024, 2022
Nigeria NGA4.3846.9%2024, 2023
Sudan SDN4.2643.5%2024, 2019

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

Sources

Fertility rate

Fertility rate, total (births per woman)

World Bank · CC BY 4.0 · updated quarterly

Secondary enrollment

School enrollment, secondary (% gross)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2012–2025. 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 Fertility rate and Secondary enrollment

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

More links with Fertility rate or Secondary enrollment