placestats

Birth rate vs. Informal employment

Fades after adjusting for income

Across 140 countries, Birth rate and Informal employment rise and fall together at r = +0.83 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.29, which could easily be chance (q = 0.27, 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 informal employment, 16% to 83.9% of employment, birth rate is 16.3 per 1,000 people higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 5.49 per 1,000 people.

Link before adjusting (r)+0.832p = 3.3e-37 · 140 countries
After adjusting for national income+0.293p = 0.000 · likely range [+0.13, +0.44]
p, allowing for regions0.013standard error 0.078 · 6 regions
Check for luck (q)0.273across 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
Informal employment · % of employmentlink with income -0.88 · 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

Birth rate · per 1,000 people →Informal employment · % of employment →4.743.30.63%98.5%Afghanistan: 35 per 1,000 people, 86.1% of employmentAngola: 37.2 per 1,000 people, 95.3% of employmentArgentina: 11.1 per 1,000 people, 51.6% of employmentArmenia: 11.1 per 1,000 people, 76.1% of employmentAntigua and Barbuda: 11.7 per 1,000 people, 12.8% of employmentAustria: 8.4 per 1,000 people, 1.32% of employmentBurundi: 33.2 per 1,000 people, 98% of employmentBelgium: 9.2 per 1,000 people, 1.37% of employmentBenin: 33.4 per 1,000 people, 96.3% of employmentBurkina Faso: 31.3 per 1,000 people, 93.8% of employmentBangladesh: 20 per 1,000 people, 84% of employmentBulgaria: 8.3 per 1,000 people, 1.2% of employmentBahamas, The: 10.8 per 1,000 people, 18.3% of employmentBosnia and Herzegovina: 7.72 per 1,000 people, 16.6% of employmentBolivia: 21 per 1,000 people, 83.9% of employmentBrazil: 12.1 per 1,000 people, 35.6% of employmentBarbados: 11.1 per 1,000 people, 61.8% of employmentBrunei Darussalam: 13.3 per 1,000 people, 21.4% of employmentBotswana: 24.4 per 1,000 people, 75.6% of employmentSwitzerland: 8.7 per 1,000 people, 1.48% of employmentChile: 8.72 per 1,000 people, 26.4% of employmentCote d'Ivoire: 31.6 per 1,000 people, 92.1% of employmentCameroon: 33.3 per 1,000 people, 87.1% of employmentCongo, Dem. Rep.: 40.9 per 1,000 people, 96.3% of employmentColombia: 13.3 per 1,000 people, 56% of employmentComoros: 28.2 per 1,000 people, 88.8% of employmentCabo Verde: 12.2 per 1,000 people, 60.6% of employmentCosta Rica: 9.99 per 1,000 people, 36.1% of employmentCyprus: 10.5 per 1,000 people, 1.68% of employmentCzechia: 7.7 per 1,000 people, 2.26% of employmentGermany: 8.1 per 1,000 people, 2.49% of employmentDjibouti: 20.9 per 1,000 people, 47.6% of employmentDenmark: 9.5 per 1,000 people, 2.82% of employmentDominican Republic: 17.6 per 1,000 people, 54.7% of employmentEcuador: 14.8 per 1,000 people, 68.5% of employmentEgypt, Arab Rep.: 20.9 per 1,000 people, 68.6% of employmentSpain: 6.5 per 1,000 people, 2.2% of employmentEstonia: 7.1 per 1,000 people, 2.4% of employmentEthiopia: 31.5 per 1,000 people, 77.7% of employmentFinland: 7.8 per 1,000 people, 2.19% of employmentFiji: 17.9 per 1,000 people, 45.7% of employmentFrance: 9.7 per 1,000 people, 3.15% of employmentUnited Kingdom: 9.89 per 1,000 people, 6.51% of employmentGeorgia: 11.3 per 1,000 people, 51.5% of employmentGhana: 25.9 per 1,000 people, 78% of employmentGambia, The: 29.9 per 1,000 people, 83.9% of employmentGuinea-Bissau: 29.6 per 1,000 people, 94.8% of employmentGreece: 6.6 per 1,000 people, 3.58% of employmentGrenada: 11.5 per 1,000 people, 48% of employmentGuatemala: 20.6 per 1,000 people, 75.9% of employmentGuyana: 19.9 per 1,000 people, 51% of employmentHonduras: 21.6 per 1,000 people, 82.6% of employmentCroatia: 8.3 per 1,000 people, 1.17% of employmentHaiti: 21.9 per 1,000 people, 91.6% of employmentHungary: 8.2 per 1,000 people, 1.31% of employmentIndonesia: 15.8 per 1,000 people, 81% of employmentIndia: 16 per 1,000 people, 88.1% of employmentIreland: 10 per 1,000 people, 1.9% of employmentIraq: 25.6 per 1,000 people, 67.6% of employmentIceland: 11.2 per 1,000 people, 1.97% of employmentItaly: 6.3 per 1,000 people, 3.42% of employmentJamaica: 11.4 per 1,000 people, 54.6% of employmentJordan: 20.5 per 1,000 people, 55.1% of employmentKenya: 27 per 1,000 people, 86.5% of employmentKyrgyz Republic: 19.4 per 1,000 people, 57.5% of employmentCambodia: 20.3 per 1,000 people, 89.4% of employmentKiribati: 25.3 per 1,000 people, 61.5% of employmentKorea, Rep.: 4.7 per 1,000 people, 29.1% of employmentLao PDR: 20.9 per 1,000 people, 90.5% of employmentLebanon: 16 per 1,000 people, 55.5% of employmentLiberia: 30.6 per 1,000 people, 89.3% of employmentSt. Lucia: 11.2 per 1,000 people, 28.3% of employmentSri Lanka: 10.1 per 1,000 people, 67.6% of employmentLesotho: 23.8 per 1,000 people, 89.1% of employmentLithuania: 6.6 per 1,000 people, 3.2% of employmentLuxembourg: 9.5 per 1,000 people, 1.93% of employmentLatvia: 6.9 per 1,000 people, 2.17% of employmentMoldova: 10.6 per 1,000 people, 52.2% of employmentMadagascar: 31.7 per 1,000 people, 96.1% of employmentMaldives: 10.6 per 1,000 people, 47.3% of employmentMexico: 15.5 per 1,000 people, 56.4% of employmentMarshall Islands: 20.1 per 1,000 people, 32.6% of employmentNorth Macedonia: 8.8 per 1,000 people, 11.1% of employmentMali: 39.5 per 1,000 people, 94.4% of employmentMalta: 7.7 per 1,000 people, 0.63% of employmentMyanmar: 16.5 per 1,000 people, 80.7% of employmentMongolia: 16.9 per 1,000 people, 27.1% of employmentMozambique: 37 per 1,000 people, 95.5% of employmentMauritania: 34 per 1,000 people, 89.3% of employmentMauritius: 10.3 per 1,000 people, 23.4% of employmentMalawi: 31.1 per 1,000 people, 92.7% of employmentNamibia: 25.9 per 1,000 people, 55.6% of employmentNiger: 41.4 per 1,000 people, 98.5% of employmentNigeria: 32.5 per 1,000 people, 93.1% of employmentNicaragua: 19.1 per 1,000 people, 81.8% of employmentNetherlands: 9.2 per 1,000 people, 2.63% of employmentNorway: 9.7 per 1,000 people, 1.43% of employmentNepal: 19 per 1,000 people, 81.5% of employmentNaoero: 24.6 per 1,000 people, 47.9% of employmentPakistan: 27.4 per 1,000 people, 88.7% of employmentPanama: 15.9 per 1,000 people, 58.7% of employmentPeru: 15.8 per 1,000 people, 70.5% of employmentPalau: 10.7 per 1,000 people, 7.27% of employmentPoland: 6.9 per 1,000 people, 8.62% of employmentPortugal: 7.9 per 1,000 people, 4.73% of employmentParaguay: 19.7 per 1,000 people, 64.5% of employmentWest Bank and Gaza: 26.5 per 1,000 people, 48.8% of employmentRomania: 7.5 per 1,000 people, 2.21% of employmentRussian Federation: 8.4 per 1,000 people, 19.3% of employmentRwanda: 28.1 per 1,000 people, 84.3% of employmentSudan: 33 per 1,000 people, 94.2% of employmentSenegal: 29.2 per 1,000 people, 89.2% of employmentSierra Leone: 30.1 per 1,000 people, 93.1% of employmentEl Salvador: 15.6 per 1,000 people, 64% of employmentSomalia, Fed. Rep.: 42.3 per 1,000 people, 81.9% of employmentSerbia: 9.2 per 1,000 people, 17.8% of employmentSuriname: 17.2 per 1,000 people, 50.9% of employmentSlovak Republic: 8.5 per 1,000 people, 4.37% of employmentSlovenia: 7.9 per 1,000 people, 0.7% of employmentSweden: 9.3 per 1,000 people, 2.83% of employmentEswatini: 23.6 per 1,000 people, 53.3% of employmentSeychelles: 11 per 1,000 people, 14.2% of employmentChad: 43.3 per 1,000 people, 96.9% of employmentTogo: 32.1 per 1,000 people, 92.3% of employmentThailand: 8.12 per 1,000 people, 63.2% of employmentTajikistan: 25.3 per 1,000 people, 63.6% of employmentTimor-Leste: 21.8 per 1,000 people, 80.6% of employmentTonga: 23 per 1,000 people, 59.2% of employmentTunisia: 13.4 per 1,000 people, 36.9% of employmentTurkiye: 11 per 1,000 people, 27.7% of employmentTuvalu: 22 per 1,000 people, 20.1% of employmentTanzania: 34.8 per 1,000 people, 90.8% of employmentUganda: 34.4 per 1,000 people, 94.5% of employmentUruguay: 9.8 per 1,000 people, 28.5% of employmentViet Nam: 13.4 per 1,000 people, 67% of employmentVanuatu: 27.7 per 1,000 people, 72.4% of employmentSamoa: 25 per 1,000 people, 51.5% of employmentSouth Africa: 18.5 per 1,000 people, 34.8% of employmentZambia: 32.7 per 1,000 people, 82.7% of employmentZimbabwe: 29.9 per 1,000 people, 85% of employmentARMCODESPINDITALTUNERSOMTCDTHATUV

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.8323.3e-37140
By rank (Spearman), not adjusted+0.8737.0e-45140
Standard (Pearson), adjusted for national income+0.2930.000140
By rank (Spearman), adjusted for national income+0.4076.5e-7140

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 140 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: +0.539 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.245 (without GUY) to +0.315 (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: GUY (-0.048).

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 & Pacific19-0.15
Europe & Central Asia40+0.39
Latin America & Caribbean26+0.72
Sub-Saharan Africa40+0.58

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 third47+0.34
Middle third46+0.27
Richest third47+0.72

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
Christians90+0.40
Muslims31+0.51

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
France19+0.44
Never a European colony12-0.64
Spain16+0.76
United Kingdom43+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 = +0.293 after dropping 0 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 25years. 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 = +0.001, 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 birth rate moved did not tend to see their informal employment move with it.

Across countries (adjusted)+0.293for comparison
Within countries+0.333each country vs itself
…and vs the same year elsewhere+0.001q = 0.998 · 82 countries
Year-on-year changes+0.006q = 0.942
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.

1,181 country-years (one country in one year), 82 countries, 2000–2024, about 14 years each on average. Share of the variation that happens within countries over time: 2% for Birth rate, 5% for Informal employment. 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

0.20−0.2-100+10years Informal employment trails Birth rate →lag -10: r = -0.094 (n = 463)lag -9: r = -0.007 (n = 526)lag -8: r = 0.045 (n = 590)lag -7: r = 0.042 (n = 663)lag -6: r = 0.017 (n = 736)lag -5: r = 0.016 (n = 810)lag -4: r = 0.037 (n = 877)lag -3: r = 0.024 (n = 959)lag -2: r = 0.005 (n = 1,037)lag -1: r = -0.005 (n = 1,118)lag +0: r = 0.001 (n = 1,181)lag +1: r = -0.002 (n = 1,190)lag +2: r = 0.015 (n = 1,190)lag +3: r = 0.026 (n = 1,190)lag +4: r = 0.035 (n = 1,190)lag +5: r = 0.043 (n = 1,190)lag +6: r = 0.063 (n = 1,190)lag +7: r = 0.080 (n = 1,190)lag +8: r = 0.092 (n = 1,190)lag +9: r = 0.101 (n = 1,190)lag +10: r = 0.116 (n = 1,190)

Same year (lag 0): +0.001. 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


per 1,000 people
% of employment		Years
Chad TCD43.396.9%2024, 2018
Somalia, Fed. Rep. SOM42.381.9%2024, 2019
Niger NER41.498.5%2024, 2022
Congo, Dem. Rep. COD40.996.3%2024, 2020
Mali MLI39.594.4%2024, 2023
Angola AGO37.295.3%2024
Mozambique MOZ3795.5%2024, 2015
Afghanistan AFG3586.1%2024, 2021
Tanzania TZA34.890.8%2024
Uganda UGA34.494.5%2024, 2021
Mauritania MRT3489.3%2024, 2019
Benin BEN33.496.3%2024, 2022
Cameroon CMR33.387.1%2024, 2014
Burundi BDI33.298%2024, 2014
Sudan SDN3394.2%2024, 2022

World Bank, World Development Indicators
United Nations Global SDG Indicators Database; series compiled by the International Labour Organization (8.3.1) and the UN Office on Drugs and Crime (16.3.2)

Sources

Birth rate

Birth rate, crude (per 1,000 people)

World Bank · CC BY 4.0 · updated quarterly

Informal employment

Share of employment that is informal

International Labour Organization · via Our World in Data · CC BY 3.0 IGO · updated annual

Workers with no contract, no social protection or no registered employer, as the ILO (the UN's labour agency) makes them comparable across national labour force surveys. The World Bank's copy of this series was retired, so it comes from the UN's database for the Sustainable Development Goals.

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 6 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 Informal employment

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

More links with Birth rate or Informal employment