placestats

Informal employment vs. Maternal mortality

Fades after adjusting for income

Across 140 countries, Informal employment and Maternal mortality rise and fall together at r = +0.66 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.14, which could easily be chance (q = 0.52, 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.

Comparing countries across the middle half of informal employment, 16% to 83.9% of employment, maternal mortality is worse by 218 per 100,000 live births at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 64.9 per 100,000 live births.

Link before adjusting (r)+0.658p = 1.1e-18 · 140 countries
After adjusting for national income+0.137p = 0.108 · likely range [-0.03, +0.30]
p, allowing for regions0.316standard error 0.123 · 6 regions
Check for luck (q)0.521across 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.

Informal employment · % of employmentlink with income -0.88 · proxy
Maternal mortality · per 100,000 live birthslink with income -0.85 · 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

Informal employment · % of employment →Maternal mortality · per 100,000 live births →0.63%98.5%1993Afghanistan: 86.1% of employment, 521 per 100,000 live birthsAngola: 95.3% of employment, 183 per 100,000 live birthsArgentina: 51.6% of employment, 33 per 100,000 live birthsArmenia: 76.1% of employment, 19 per 100,000 live birthsAntigua and Barbuda: 12.8% of employment, 35 per 100,000 live birthsAustria: 1.32% of employment, 6 per 100,000 live birthsBurundi: 98% of employment, 392 per 100,000 live birthsBelgium: 1.37% of employment, 4 per 100,000 live birthsBenin: 96.3% of employment, 518 per 100,000 live birthsBurkina Faso: 93.8% of employment, 242 per 100,000 live birthsBangladesh: 84% of employment, 115 per 100,000 live birthsBulgaria: 1.2% of employment, 6 per 100,000 live birthsBahamas, The: 18.3% of employment, 76 per 100,000 live birthsBosnia and Herzegovina: 16.6% of employment, 6 per 100,000 live birthsBolivia: 83.9% of employment, 146 per 100,000 live birthsBrazil: 35.6% of employment, 67 per 100,000 live birthsBarbados: 61.8% of employment, 35 per 100,000 live birthsBrunei Darussalam: 21.4% of employment, 36 per 100,000 live birthsBotswana: 75.6% of employment, 155 per 100,000 live birthsSwitzerland: 1.48% of employment, 5 per 100,000 live birthsChile: 26.4% of employment, 10 per 100,000 live birthsCote d'Ivoire: 92.1% of employment, 359 per 100,000 live birthsCameroon: 87.1% of employment, 258 per 100,000 live birthsCongo, Dem. Rep.: 96.3% of employment, 427 per 100,000 live birthsColombia: 56% of employment, 59 per 100,000 live birthsComoros: 88.8% of employment, 179 per 100,000 live birthsCabo Verde: 60.6% of employment, 40 per 100,000 live birthsCosta Rica: 36.1% of employment, 24 per 100,000 live birthsCyprus: 1.68% of employment, 14 per 100,000 live birthsCzechia: 2.26% of employment, 3 per 100,000 live birthsGermany: 2.49% of employment, 4 per 100,000 live birthsDjibouti: 47.6% of employment, 162 per 100,000 live birthsDenmark: 2.82% of employment, 4 per 100,000 live birthsDominican Republic: 54.7% of employment, 124 per 100,000 live birthsEcuador: 68.5% of employment, 55 per 100,000 live birthsEgypt, Arab Rep.: 68.6% of employment, 17 per 100,000 live birthsSpain: 2.2% of employment, 3 per 100,000 live birthsEstonia: 2.4% of employment, 5 per 100,000 live birthsEthiopia: 77.7% of employment, 195 per 100,000 live birthsFinland: 2.19% of employment, 8 per 100,000 live birthsFiji: 45.7% of employment, 30 per 100,000 live birthsFrance: 3.15% of employment, 7 per 100,000 live birthsUnited Kingdom: 6.51% of employment, 8 per 100,000 live birthsGeorgia: 51.5% of employment, 20 per 100,000 live birthsGhana: 78% of employment, 234 per 100,000 live birthsGambia, The: 83.9% of employment, 354 per 100,000 live birthsGuinea-Bissau: 94.8% of employment, 505 per 100,000 live birthsGreece: 3.58% of employment, 5 per 100,000 live birthsGrenada: 48% of employment, 48 per 100,000 live birthsGuatemala: 75.9% of employment, 94 per 100,000 live birthsGuyana: 51% of employment, 75 per 100,000 live birthsHonduras: 82.6% of employment, 47 per 100,000 live birthsCroatia: 1.17% of employment, 3 per 100,000 live birthsHaiti: 91.6% of employment, 328 per 100,000 live birthsHungary: 1.31% of employment, 12 per 100,000 live birthsIndonesia: 81% of employment, 140 per 100,000 live birthsIndia: 88.1% of employment, 80 per 100,000 live birthsIreland: 1.9% of employment, 4 per 100,000 live birthsIraq: 67.6% of employment, 66 per 100,000 live birthsIceland: 1.97% of employment, 3 per 100,000 live birthsItaly: 3.42% of employment, 6 per 100,000 live birthsJamaica: 54.6% of employment, 130 per 100,000 live birthsJordan: 55.1% of employment, 31 per 100,000 live birthsKenya: 86.5% of employment, 149 per 100,000 live birthsKyrgyz Republic: 57.5% of employment, 42 per 100,000 live birthsCambodia: 89.4% of employment, 137 per 100,000 live birthsKiribati: 61.5% of employment, 80 per 100,000 live birthsKorea, Rep.: 29.1% of employment, 4 per 100,000 live birthsLao PDR: 90.5% of employment, 112 per 100,000 live birthsLebanon: 55.5% of employment, 15 per 100,000 live birthsLiberia: 89.3% of employment, 628 per 100,000 live birthsSt. Lucia: 28.3% of employment, 44 per 100,000 live birthsSri Lanka: 67.6% of employment, 18 per 100,000 live birthsLesotho: 89.1% of employment, 478 per 100,000 live birthsLithuania: 3.2% of employment, 8 per 100,000 live birthsLuxembourg: 1.93% of employment, 11 per 100,000 live birthsLatvia: 2.17% of employment, 19 per 100,000 live birthsMoldova: 52.2% of employment, 19 per 100,000 live birthsMadagascar: 96.1% of employment, 445 per 100,000 live birthsMaldives: 47.3% of employment, 32 per 100,000 live birthsMexico: 56.4% of employment, 42 per 100,000 live birthsMarshall Islands: 32.6% of employment, 155 per 100,000 live birthsNorth Macedonia: 11.1% of employment, 3 per 100,000 live birthsMali: 94.4% of employment, 367 per 100,000 live birthsMalta: 0.63% of employment, 8 per 100,000 live birthsMyanmar: 80.7% of employment, 185 per 100,000 live birthsMongolia: 27.1% of employment, 41 per 100,000 live birthsMozambique: 95.5% of employment, 99 per 100,000 live birthsMauritania: 89.3% of employment, 381 per 100,000 live birthsMauritius: 23.4% of employment, 66 per 100,000 live birthsMalawi: 92.7% of employment, 225 per 100,000 live birthsNamibia: 55.6% of employment, 139 per 100,000 live birthsNiger: 98.5% of employment, 350 per 100,000 live birthsNigeria: 93.1% of employment, 993 per 100,000 live birthsNicaragua: 81.8% of employment, 60 per 100,000 live birthsNetherlands: 2.63% of employment, 4 per 100,000 live birthsNorway: 1.43% of employment, 1 per 100,000 live birthsNepal: 81.5% of employment, 142 per 100,000 live birthsNaoero: 47.9% of employment, 273 per 100,000 live birthsPakistan: 88.7% of employment, 155 per 100,000 live birthsPanama: 58.7% of employment, 37 per 100,000 live birthsPeru: 70.5% of employment, 51 per 100,000 live birthsPalau: 7.27% of employment, 89 per 100,000 live birthsPoland: 8.62% of employment, 2 per 100,000 live birthsPortugal: 4.73% of employment, 15 per 100,000 live birthsParaguay: 64.5% of employment, 58 per 100,000 live birthsWest Bank and Gaza: 48.8% of employment, 16 per 100,000 live birthsRomania: 2.21% of employment, 12 per 100,000 live birthsRussian Federation: 19.3% of employment, 9 per 100,000 live birthsRwanda: 84.3% of employment, 229 per 100,000 live birthsSudan: 94.2% of employment, 256 per 100,000 live birthsSenegal: 89.2% of employment, 237 per 100,000 live birthsSierra Leone: 93.1% of employment, 354 per 100,000 live birthsEl Salvador: 64% of employment, 39 per 100,000 live birthsSomalia, Fed. Rep.: 81.9% of employment, 563 per 100,000 live birthsSerbia: 17.8% of employment, 11 per 100,000 live birthsSuriname: 50.9% of employment, 84 per 100,000 live birthsSlovak Republic: 4.37% of employment, 4 per 100,000 live birthsSlovenia: 0.7% of employment, 3 per 100,000 live birthsSweden: 2.83% of employment, 4 per 100,000 live birthsEswatini: 53.3% of employment, 118 per 100,000 live birthsSeychelles: 14.2% of employment, 42 per 100,000 live birthsChad: 96.9% of employment, 748 per 100,000 live birthsTogo: 92.3% of employment, 349 per 100,000 live birthsThailand: 63.2% of employment, 34 per 100,000 live birthsTajikistan: 63.6% of employment, 14 per 100,000 live birthsTimor-Leste: 80.6% of employment, 192 per 100,000 live birthsTonga: 59.2% of employment, 67 per 100,000 live birthsTunisia: 36.9% of employment, 36 per 100,000 live birthsTurkiye: 27.7% of employment, 15 per 100,000 live birthsTuvalu: 20.1% of employment, 170 per 100,000 live birthsTanzania: 90.8% of employment, 276 per 100,000 live birthsUganda: 94.5% of employment, 170 per 100,000 live birthsUruguay: 28.5% of employment, 15 per 100,000 live birthsViet Nam: 67% of employment, 48 per 100,000 live birthsVanuatu: 72.4% of employment, 100 per 100,000 live birthsSamoa: 51.5% of employment, 101 per 100,000 live birthsSouth Africa: 34.8% of employment, 118 per 100,000 live birthsZambia: 82.7% of employment, 85 per 100,000 live birthsZimbabwe: 85% of employment, 358 per 100,000 live birthsARMHNDHRVLBRMOZNGANORSVNTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6581.1e-18140
By rank (Spearman), not adjusted+0.8553.6e-41140
Standard (Pearson), adjusted for national income+0.1370.108140
By rank (Spearman), adjusted for national income+0.3951.5e-6140

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: +0.521 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.066 (without NGA) to +0.161 (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: NGA (-0.071).

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 & Pacific19-0.01
Europe & Central Asia40+0.42
Latin America & Caribbean26+0.08
Sub-Saharan Africa40+0.33

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+0.32
Middle third46+0.19
Richest third47+0.54

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+0.08
Muslims31+0.44

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+0.32
Never a European colony12+0.05
Spain16+0.55
United Kingdom43+0.22

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 = +0.192 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 24years. 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 = -0.171, 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 informal employment moved did not tend to see their maternal mortality move with it.

Across countries (adjusted)+0.137for comparison
Within countries+0.010each country vs itself
…and vs the same year elsewhere-0.171q = 0.226 · 82 countries
Year-on-year changes-0.048q = 0.489
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.

1,118 country-years (one country in one year), 82 countries, 2000–2023, about 14 years each on average. Share of the variation that happens within countries over time: 2% for Informal employment, 6% for Maternal mortality. 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 Maternal mortality trails Informal employment →lag -10: r = -0.160 (n = 1,190)lag -9: r = -0.155 (n = 1,190)lag -8: r = -0.159 (n = 1,190)lag -7: r = -0.170 (n = 1,190)lag -6: r = -0.181 (n = 1,190)lag -5: r = -0.188 (n = 1,190)lag -4: r = -0.189 (n = 1,190)lag -3: r = -0.193 (n = 1,190)lag -2: r = -0.186 (n = 1,190)lag -1: r = -0.175 (n = 1,181)lag +0: r = -0.171 (n = 1,118)lag +1: r = -0.152 (n = 1,037)lag +2: r = -0.146 (n = 959)lag +3: r = -0.099 (n = 877)lag +4: r = -0.115 (n = 810)lag +5: r = -0.097 (n = 736)lag +6: r = -0.081 (n = 663)lag +7: r = -0.108 (n = 590)lag +8: r = -0.102 (n = 526)lag +9: r = -0.096 (n = 463)lag +10: r = -0.110 (n = 381)

Same year (lag 0): -0.171. 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


% of employment

per 100,000 live births
Years
Niger NER98.5%3502022, 2023
Burundi BDI98%3922014, 2023
Chad TCD96.9%7482018, 2023
Benin BEN96.3%5182022, 2023
Congo, Dem. Rep. COD96.3%4272020, 2023
Madagascar MDG96.1%4452022, 2023
Mozambique MOZ95.5%992015, 2023
Angola AGO95.3%1832024, 2023
Guinea-Bissau GNB94.8%5052022, 2023
Uganda UGA94.5%1702021, 2023
Mali MLI94.4%3672023
Sudan SDN94.2%2562022, 2023
Burkina Faso BFA93.8%2422024, 2023
Nigeria NGA93.1%9932024, 2023
Sierra Leone SLE93.1%3542018, 2023

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)
World Bank, World Development Indicators

Sources

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.

Maternal mortality

Maternal mortality ratio, modelled estimate (per 100,000 live births)

WHO and the UN Maternal Mortality Estimation Inter-Agency Group · CC BY 4.0 · updated quarterly

Estimated with a model, like stunting, and for the same reason. Deaths in childbirth are rare in small countries with weak death records, so the agencies estimate rather than count.

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 Informal employment and Maternal mortality

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

More links with Informal employment or Maternal mortality