placestats

Fertility rate vs. Labor share of income

Holds up after adjusting for income

Across 137 countries, Fertility rate and Labor share of income rise and fall together at r = -0.24 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = -0.40, q = 0.044, allowing for the many pairs tested).

Comparing countries across the middle half of labor share of income, 42.6% to 58.6% of GDP, fertility rate is 0.386 births per woman lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.356 births per woman.

Link before adjusting (r)-0.242p = 0.004 · 137 countries
After adjusting for national income-0.398p = 1.6e-6 · likely range [-0.53, -0.25]
p, allowing for regions0.002standard error 0.078 · 7 regions
Check for luck (q)0.044across 18,622 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
Labor share of income · % of GDPlink with income +0.08 · independent

“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 →Labor share of income · % of GDP →0.5826.0316.4%75.1%Aruba: 1.61 births per woman, 64.5% of GDPAngola: 5.05 births per woman, 22.3% of GDPAlbania: 1.34 births per woman, 70.5% of GDPArgentina: 1.5 births per woman, 52.8% of GDPArmenia: 1.7 births per woman, 50.9% of GDPAustralia: 1.48 births per woman, 54.6% of GDPAustria: 1.31 births per woman, 60.8% of GDPAzerbaijan: 1.43 births per woman, 39.2% of GDPBurundi: 4.79 births per woman, 60.6% of GDPBelgium: 1.44 births per woman, 58.6% of GDPBenin: 4.48 births per woman, 61.7% of GDPBurkina Faso: 4.11 births per woman, 42.6% of GDPBulgaria: 1.72 births per woman, 51.7% of GDPBahrain: 1.8 births per woman, 29.4% of GDPBahamas, The: 1.37 births per woman, 39.7% of GDPBosnia and Herzegovina: 1.49 births per woman, 67.1% of GDPBelarus: 1.22 births per woman, 57% of GDPBermuda: 1.41 births per woman, 58.6% of GDPBolivia: 2.52 births per woman, 49.8% of GDPBrazil: 1.61 births per woman, 51.1% of GDPBarbados: 1.71 births per woman, 75.1% of GDPBotswana: 2.7 births per woman, 27.8% of GDPCentral African Republic: 5.95 births per woman, 16.4% of GDPCanada: 1.25 births per woman, 65.9% of GDPSwitzerland: 1.29 births per woman, 65.3% of GDPChile: 1.14 births per woman, 44% of GDPChina: 1.01 births per woman, 56.1% of GDPCote d'Ivoire: 4.23 births per woman, 33.2% of GDPCameroon: 4.26 births per woman, 64.4% of GDPColombia: 1.63 births per woman, 47.8% of GDPCabo Verde: 1.51 births per woman, 62.6% of GDPCosta Rica: 1.32 births per woman, 53.1% of GDPCuracao: 1.4 births per woman, 67.9% of GDPCayman Islands: 1.52 births per woman, 49.1% of GDPCyprus: 1.38 births per woman, 53.7% of GDPCzechia: 1.36 births per woman, 51.2% of GDPGermany: 1.36 births per woman, 63.7% of GDPDjibouti: 2.62 births per woman, 63.4% of GDPDenmark: 1.47 births per woman, 60.1% of GDPDominican Republic: 2.22 births per woman, 42.7% of GDPEcuador: 1.81 births per woman, 53% of GDPEgypt, Arab Rep.: 2.73 births per woman, 36.2% of GDPSpain: 1.1 births per woman, 59.4% of GDPEstonia: 1.18 births per woman, 60.7% of GDPFinland: 1.25 births per woman, 58.3% of GDPFiji: 2.27 births per woman, 48.9% of GDPFrance: 1.61 births per woman, 63.1% of GDPGabon: 3.59 births per woman, 27.5% of GDPUnited Kingdom: 1.55 births per woman, 59.5% of GDPGeorgia: 1.8 births per woman, 46.7% of GDPGuinea: 4.13 births per woman, 42.2% of GDPGreece: 1.24 births per woman, 54% of GDPGuatemala: 2.29 births per woman, 46.9% of GDPHong Kong SAR, China: 0.841 births per woman, 52.7% of GDPHonduras: 2.48 births per woman, 54.7% of GDPCroatia: 1.46 births per woman, 61.3% of GDPHungary: 1.41 births per woman, 53.7% of GDPIndonesia: 2.12 births per woman, 50.9% of GDPIndia: 1.96 births per woman, 53.3% of GDPIreland: 1.47 births per woman, 30.9% of GDPIran, Islamic Rep.: 1.68 births per woman, 39.3% of GDPIraq: 3.22 births per woman, 29.6% of GDPIceland: 1.56 births per woman, 61.7% of GDPIsrael: 2.87 births per woman, 49.9% of GDPItaly: 1.18 births per woman, 51.2% of GDPJamaica: 1.35 births per woman, 60.9% of GDPJordan: 2.6 births per woman, 49.3% of GDPJapan: 1.15 births per woman, 58.7% of GDPKazakhstan: 2.98 births per woman, 37.3% of GDPKenya: 3.17 births per woman, 54% of GDPKyrgyz Republic: 2.6 births per woman, 40% of GDPKorea, Rep.: 0.748 births per woman, 54.6% of GDPKuwait: 1.56 births per woman, 24.9% of GDPLao PDR: 2.4 births per woman, 39.8% of GDPLebanon: 2.23 births per woman, 44.5% of GDPSri Lanka: 1.95 births per woman, 38.1% of GDPLesotho: 2.66 births per woman, 66.1% of GDPLithuania: 1.11 births per woman, 57.1% of GDPLuxembourg: 1.25 births per woman, 49.8% of GDPLatvia: 1.24 births per woman, 62.2% of GDPMacao SAR, China: 0.582 births per woman, 32.2% of GDPMorocco: 2.21 births per woman, 46.5% of GDPMoldova: 1.73 births per woman, 51.3% of GDPMexico: 1.89 births per woman, 38.1% of GDPNorth Macedonia: 1.4 births per woman, 52.5% of GDPMalta: 1.01 births per woman, 45.9% of GDPMongolia: 2.5 births per woman, 40.6% of GDPMozambique: 4.69 births per woman, 54% of GDPMauritania: 4.63 births per woman, 40.4% of GDPMauritius: 1.44 births per woman, 45.6% of GDPMalaysia: 1.54 births per woman, 39.7% of GDPNamibia: 3.21 births per woman, 52.9% of GDPNiger: 5.93 births per woman, 39.1% of GDPNigeria: 4.38 births per woman, 31.2% of GDPNicaragua: 2.21 births per woman, 52% of GDPNetherlands: 1.43 births per woman, 55.9% of GDPNorway: 1.45 births per woman, 38.4% of GDPNew Zealand: 1.57 births per woman, 55.4% of GDPOman: 2.51 births per woman, 30.3% of GDPPanama: 2.11 births per woman, 32.8% of GDPPeru: 1.97 births per woman, 40.1% of GDPPhilippines: 1.89 births per woman, 44.9% of GDPPoland: 1.14 births per woman, 54.8% of GDPPortugal: 1.41 births per woman, 61.7% of GDPParaguay: 2.42 births per woman, 44.5% of GDPQatar: 1.72 births per woman, 17.7% of GDPRomania: 1.39 births per woman, 50% of GDPRussian Federation: 1.42 births per woman, 52.9% of GDPRwanda: 3.65 births per woman, 74.1% of GDPSaudi Arabia: 2.31 births per woman, 28% of GDPSudan: 4.26 births per woman, 63.5% of GDPSenegal: 3.77 births per woman, 52.3% of GDPSingapore: 0.97 births per woman, 43.9% of GDPSierra Leone: 3.7 births per woman, 59.6% of GDPEl Salvador: 1.77 births per woman, 52.1% of GDPSerbia: 1.64 births per woman, 63.7% of GDPSao Tome and Principe: 3.6 births per woman, 73.8% of GDPSuriname: 2.23 births per woman, 45.8% of GDPSlovak Republic: 1.46 births per woman, 53.2% of GDPSlovenia: 1.52 births per woman, 63.3% of GDPSweden: 1.43 births per woman, 61% of GDPEswatini: 2.72 births per woman, 61.2% of GDPChad: 6.03 births per woman, 48.5% of GDPTogo: 4.12 births per woman, 50.1% of GDPThailand: 1.2 births per woman, 43.8% of GDPTajikistan: 3.04 births per woman, 43.6% of GDPTrinidad and Tobago: 1.54 births per woman, 33.8% of GDPTunisia: 1.82 births per woman, 56.1% of GDPTurkiye: 1.48 births per woman, 42.6% of GDPTanzania: 4.54 births per woman, 58.3% of GDPUkraine: 0.988 births per woman, 55.8% of GDPUruguay: 1.4 births per woman, 51.9% of GDPUnited States: 1.63 births per woman, 56.8% of GDPUzbekistan: 3.49 births per woman, 37.9% of GDPSouth Africa: 2.21 births per woman, 54.3% of GDPZambia: 4.04 births per woman, 30% of GDPZimbabwe: 3.67 births per woman, 53.3% of GDPAGOALBBRBCAFCUWKWTMACNERQATRWASTPTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.2420.004137
By rank (Spearman), not adjusted-0.2770.001137
Standard (Pearson), adjusted for national income-0.3981.6e-6137
By rank (Spearman), adjusted for national income-0.3366.4e-5137

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 137 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: -0.156 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.414 (without CMR) to -0.365 (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).

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 & Pacific15-0.19
Europe & Central Asia46-0.50
Latin America & Caribbean25-0.35
Middle East, North Africa, Afghanistan & Pakistan15-0.23
Sub-Saharan Africa31-0.61

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 third46-0.52
Middle third45-0.59
Richest third46-0.26

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
Christians85-0.34
Muslims33-0.64

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
France16-0.33
Never a European colony16-0.70
Spain18-0.55
United Kingdom34-0.38

By official ideology

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
Nationalist18-0.67
No strong official ideology92-0.42

By party system

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
A few parties banned18-0.74
No parties banned100-0.32

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 = -0.346 after dropping 10 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 34years. 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 = -0.008, 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 fertility rate moved did not tend to see their labor share of income move with it.

Across countries (adjusted)-0.398for comparison
Within countries+0.181each country vs itself
…and vs the same year elsewhere-0.008q = 0.943 · 139 countries
Year-on-year changes+0.031q = 0.236
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.

4,703 country-years (one country in one year), 139 countries, 1990–2023, about 34 years each on average. Share of the variation that happens within countries over time: 13% for Fertility rate, 10% for Labor share of income. 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

0.10−0.1-100+10years Labor share of income trails Fertility rate →lag -10: r = -0.054 (n = 3,452)lag -9: r = -0.051 (n = 3,591)lag -8: r = -0.046 (n = 3,730)lag -7: r = -0.044 (n = 3,869)lag -6: r = -0.045 (n = 4,008)lag -5: r = -0.044 (n = 4,147)lag -4: r = -0.036 (n = 4,286)lag -3: r = -0.030 (n = 4,425)lag -2: r = -0.023 (n = 4,564)lag -1: r = -0.017 (n = 4,703)lag +0: r = -0.008 (n = 4,703)lag +1: r = -0.002 (n = 4,568)lag +2: r = 0.003 (n = 4,430)lag +3: r = 0.006 (n = 4,292)lag +4: r = 0.007 (n = 4,154)lag +5: r = 0.000 (n = 4,016)lag +6: r = -0.006 (n = 3,878)lag +7: r = -0.009 (n = 3,740)lag +8: r = -0.010 (n = 3,602)lag +9: r = -0.028 (n = 3,464)lag +10: r = -0.043 (n = 3,326)

Same year (lag 0): -0.008. 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


births per woman
% of GDP		Years
Chad TCD6.0348.5%2024, 2023
Central African Republic CAF5.9516.4%2024, 2023
Niger NER5.9339.1%2024, 2023
Angola AGO5.0522.3%2024, 2023
Burundi BDI4.7960.6%2024, 2023
Mozambique MOZ4.6954%2024, 2023
Mauritania MRT4.6340.4%2024, 2023
Tanzania TZA4.5458.3%2024, 2023
Benin BEN4.4861.7%2024, 2023
Nigeria NGA4.3831.2%2024, 2023
Sudan SDN4.2663.5%2024, 2023
Cameroon CMR4.2664.4%2024, 2023
Cote d'Ivoire CIV4.2333.2%2024, 2023
Guinea GIN4.1342.2%2024, 2023
Togo TGO4.1250.1%2024, 2023

World Bank, World Development Indicators
Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table", American Economic Review, 105(10), 3150-3182, www.ggdc.net/pwt. Data: Penn World Table version 11.0, Groningen Growth and Development Centre, doi:10.34894/FABVLR.

Sources

Fertility rate

Fertility rate, total (births per woman)

World Bank · CC BY 4.0 · updated quarterly

Labor share of income

Labor share of GDP (Penn World Table)

Groningen Growth and Development Centre, University of Groningen · via DataverseNL · CC BY 4.0 · updated irregular (new versions every few years)

The share of a country's income (GDP) that is paid to people for their work: wages, salaries and benefits, plus an estimate of what the self-employed, such as farmers and shopkeepers, earn for their work. The rest goes to the owners of land, buildings and machines as profit, rent and interest. Where there is little data on the self-employed, the Penn World Table fills in a value by a fixed rule, so figures for poorer countries are rougher, and a few countries show the same value every year. No "better" direction is set.

How this was computed

Data used: most recent value in 2010-2025; values come from 2023–2024. 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 18,622 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated V-Dem v16; V-Party v2. How the country data works · explore Fertility rate and Labor share of income

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

More links with Fertility rate or Labor share of income