placestats

Informal employment vs. Road traffic deaths

Holds up after adjusting for income

Across 138 countries, Informal employment and Road traffic deaths rise and fall together at r = +0.73 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.38 (q = 0.036, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak positive link remains.

Comparing countries across the middle half of informal employment, 14.8% to 84% of employment, road traffic deaths is worse by 15.9 per 100,000 population at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 12.7 per 100,000 population.

Link before adjusting (r)+0.728p = 5.0e-24 · 138 countries
After adjusting for national income+0.380p = 4.7e-6 · likely range [+0.23, +0.51]
p, allowing for regions0.003standard error 0.069 · 6 regions
Check for luck (q)0.036across 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
Road traffic deaths · per 100,000 populationlink 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

Informal employment · % of employment →Road traffic deaths · per 100,000 population →0.63%98.5%064.6Afghanistan: 86.1% of employment, 15.9 per 100,000 populationAngola: 95.3% of employment, 26.1 per 100,000 populationArgentina: 51.6% of employment, 14.1 per 100,000 populationArmenia: 76.1% of employment, 20 per 100,000 populationAntigua and Barbuda: 12.8% of employment, 0 per 100,000 populationAustria: 1.32% of employment, 4.9 per 100,000 populationBurundi: 98% of employment, 35.5 per 100,000 populationBelgium: 1.37% of employment, 5.8 per 100,000 populationBenin: 96.3% of employment, 26.8 per 100,000 populationBurkina Faso: 93.8% of employment, 31 per 100,000 populationBangladesh: 84% of employment, 15.3 per 100,000 populationBulgaria: 1.2% of employment, 9.2 per 100,000 populationBahamas, The: 18.3% of employment, 7.7 per 100,000 populationBosnia and Herzegovina: 16.6% of employment, 13.5 per 100,000 populationBolivia: 83.9% of employment, 21.1 per 100,000 populationBrazil: 35.6% of employment, 16 per 100,000 populationBarbados: 61.8% of employment, 8.2 per 100,000 populationBrunei Darussalam: 21.4% of employment, 7.5 per 100,000 populationBotswana: 75.6% of employment, 26.4 per 100,000 populationSwitzerland: 1.48% of employment, 2.2 per 100,000 populationChile: 26.4% of employment, 14.9 per 100,000 populationCote d'Ivoire: 92.1% of employment, 24.1 per 100,000 populationCameroon: 87.1% of employment, 30.2 per 100,000 populationCongo, Dem. Rep.: 96.3% of employment, 34.9 per 100,000 populationColombia: 56% of employment, 15.4 per 100,000 populationComoros: 88.8% of employment, 26.6 per 100,000 populationCabo Verde: 60.6% of employment, 26.8 per 100,000 populationCosta Rica: 36.1% of employment, 14.8 per 100,000 populationCyprus: 1.68% of employment, 5.8 per 100,000 populationCzechia: 2.26% of employment, 5.9 per 100,000 populationGermany: 2.49% of employment, 3.8 per 100,000 populationDjibouti: 47.6% of employment, 23.5 per 100,000 populationDenmark: 2.82% of employment, 3.7 per 100,000 populationDominican Republic: 54.7% of employment, 64.6 per 100,000 populationEcuador: 68.5% of employment, 20.1 per 100,000 populationEgypt, Arab Rep.: 68.6% of employment, 10.1 per 100,000 populationSpain: 2.2% of employment, 3.9 per 100,000 populationEstonia: 2.4% of employment, 4.5 per 100,000 populationEthiopia: 77.7% of employment, 28.2 per 100,000 populationFinland: 2.19% of employment, 3.9 per 100,000 populationFiji: 45.7% of employment, 13.5 per 100,000 populationFrance: 3.15% of employment, 5.1 per 100,000 populationUnited Kingdom: 6.51% of employment, 3.2 per 100,000 populationGeorgia: 51.5% of employment, 12.4 per 100,000 populationGhana: 78% of employment, 25.7 per 100,000 populationGambia, The: 83.9% of employment, 29.6 per 100,000 populationGuinea-Bissau: 94.8% of employment, 32.2 per 100,000 populationGreece: 3.58% of employment, 8.3 per 100,000 populationGrenada: 48% of employment, 8 per 100,000 populationGuatemala: 75.9% of employment, 22.9 per 100,000 populationGuyana: 51% of employment, 22.3 per 100,000 populationHonduras: 82.6% of employment, 16.1 per 100,000 populationCroatia: 1.17% of employment, 7.9 per 100,000 populationHaiti: 91.6% of employment, 18.8 per 100,000 populationHungary: 1.31% of employment, 7.7 per 100,000 populationIndonesia: 81% of employment, 11.3 per 100,000 populationIndia: 88.1% of employment, 15.6 per 100,000 populationIreland: 1.9% of employment, 3.1 per 100,000 populationIraq: 67.6% of employment, 27.3 per 100,000 populationIceland: 1.97% of employment, 2 per 100,000 populationItaly: 3.42% of employment, 5.3 per 100,000 populationJamaica: 54.6% of employment, 15.1 per 100,000 populationJordan: 55.1% of employment, 17 per 100,000 populationKenya: 86.5% of employment, 28.3 per 100,000 populationKyrgyz Republic: 57.5% of employment, 12.7 per 100,000 populationCambodia: 89.4% of employment, 19.6 per 100,000 populationKiribati: 61.5% of employment, 1.9 per 100,000 populationKorea, Rep.: 29.1% of employment, 8.6 per 100,000 populationLao PDR: 90.5% of employment, 17.9 per 100,000 populationLebanon: 55.5% of employment, 16.4 per 100,000 populationLiberia: 89.3% of employment, 38.9 per 100,000 populationSt. Lucia: 28.3% of employment, 29.8 per 100,000 populationSri Lanka: 67.6% of employment, 19.7 per 100,000 populationLesotho: 89.1% of employment, 31.9 per 100,000 populationLithuania: 3.2% of employment, 8.1 per 100,000 populationLuxembourg: 1.93% of employment, 4.1 per 100,000 populationLatvia: 2.17% of employment, 8.1 per 100,000 populationMoldova: 52.2% of employment, 7.3 per 100,000 populationMadagascar: 96.1% of employment, 29.2 per 100,000 populationMaldives: 47.3% of employment, 1.6 per 100,000 populationMexico: 56.4% of employment, 12.8 per 100,000 populationMarshall Islands: 32.6% of employment, 5.7 per 100,000 populationNorth Macedonia: 11.1% of employment, 5.1 per 100,000 populationMali: 94.4% of employment, 22.7 per 100,000 populationMalta: 0.63% of employment, 4.1 per 100,000 populationMyanmar: 80.7% of employment, 20.4 per 100,000 populationMongolia: 27.1% of employment, 21 per 100,000 populationMozambique: 95.5% of employment, 30 per 100,000 populationMauritania: 89.3% of employment, 25.6 per 100,000 populationMauritius: 23.4% of employment, 12.2 per 100,000 populationMalawi: 92.7% of employment, 33.4 per 100,000 populationNamibia: 55.6% of employment, 34.8 per 100,000 populationNiger: 98.5% of employment, 25.5 per 100,000 populationNigeria: 93.1% of employment, 20.7 per 100,000 populationNicaragua: 81.8% of employment, 16.9 per 100,000 populationNetherlands: 2.63% of employment, 4 per 100,000 populationNorway: 1.43% of employment, 2.1 per 100,000 populationNepal: 81.5% of employment, 16.3 per 100,000 populationPakistan: 88.7% of employment, 13 per 100,000 populationPanama: 58.7% of employment, 13.9 per 100,000 populationPeru: 70.5% of employment, 13.6 per 100,000 populationPalau: 7.27% of employment, 4.78 per 100,000 populationPoland: 8.62% of employment, 9.4 per 100,000 populationPortugal: 4.73% of employment, 8.2 per 100,000 populationParaguay: 64.5% of employment, 22 per 100,000 populationWest Bank and Gaza: 48.8% of employment, 5.3 per 100,000 populationRomania: 2.21% of employment, 10.3 per 100,000 populationRussian Federation: 19.3% of employment, 12 per 100,000 populationRwanda: 84.3% of employment, 29.4 per 100,000 populationSudan: 94.2% of employment, 26.8 per 100,000 populationSenegal: 89.2% of employment, 23.5 per 100,000 populationSierra Leone: 93.1% of employment, 33 per 100,000 populationEl Salvador: 64% of employment, 20.9 per 100,000 populationSomalia, Fed. Rep.: 81.9% of employment, 27.4 per 100,000 populationSerbia: 17.8% of employment, 7.5 per 100,000 populationSuriname: 50.9% of employment, 15.3 per 100,000 populationSlovak Republic: 4.37% of employment, 6.1 per 100,000 populationSlovenia: 0.7% of employment, 5.1 per 100,000 populationSweden: 2.83% of employment, 3.1 per 100,000 populationEswatini: 53.3% of employment, 33.5 per 100,000 populationSeychelles: 14.2% of employment, 11.3 per 100,000 populationChad: 96.9% of employment, 32.4 per 100,000 populationTogo: 92.3% of employment, 28.7 per 100,000 populationThailand: 63.2% of employment, 32.2 per 100,000 populationTajikistan: 63.6% of employment, 15.7 per 100,000 populationTimor-Leste: 80.6% of employment, 11.9 per 100,000 populationTonga: 59.2% of employment, 33 per 100,000 populationTunisia: 36.9% of employment, 16.5 per 100,000 populationTurkiye: 27.7% of employment, 6.7 per 100,000 populationTanzania: 90.8% of employment, 31.1 per 100,000 populationUganda: 94.5% of employment, 29.4 per 100,000 populationUruguay: 28.5% of employment, 14.8 per 100,000 populationViet Nam: 67% of employment, 30.6 per 100,000 populationVanuatu: 72.4% of employment, 14.9 per 100,000 populationSamoa: 51.5% of employment, 13 per 100,000 populationSouth Africa: 34.8% of employment, 22.2 per 100,000 populationZambia: 82.7% of employment, 20.5 per 100,000 populationZimbabwe: 85% of employment, 41.2 per 100,000 populationCHEDOMIDNISLKIRLBRLCANAMNORPAKZWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.7285.0e-24138
By rank (Spearman), not adjusted+0.7882.0e-30138
Standard (Pearson), adjusted for national income+0.3804.7e-6138
By rank (Spearman), adjusted for national income+0.4087.7e-7138

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 138 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: +0.348 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.352 (without GUY) to +0.395 (without IDN). 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 (-0.028).

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 & Pacific17+0.46
Europe & Central Asia40+0.40
Latin America & Caribbean26+0.26
Sub-Saharan Africa40+0.15

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+0.50
Middle third46+0.19
Richest third46+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+0.39
Muslims31+0.31

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+0.20
Never a European colony12+0.31
Spain16+0.14
United Kingdom41+0.26

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 = +0.393 after dropping 1 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 20years. 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 = +0.029, 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 road traffic deaths move with it.

Across countries (adjusted)+0.380for comparison
Within countries+0.064each country vs itself
…and vs the same year elsewhere+0.029q = 0.862 · 67 countries
Year-on-year changes+0.035q = 0.766
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.

800 country-years (one country in one year), 67 countries, 2000–2019, about 12 years each on average. Share of the variation that happens within countries over time: 2% for Informal employment, 12% for Road traffic deaths. 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+8years Road traffic deaths trails Informal employment →lag -10: r = -0.112 (n = 972)lag -9: r = -0.104 (n = 1,021)lag -8: r = -0.155 (n = 1,072)lag -7: r = -0.148 (n = 1,114)lag -6: r = -0.132 (n = 1,130)lag -5: r = -0.113 (n = 1,131)lag -4: r = -0.075 (n = 1,080)lag -3: r = -0.076 (n = 1,008)lag -2: r = -0.044 (n = 938)lag -1: r = -0.006 (n = 862)lag +0: r = 0.029 (n = 800)lag +1: r = 0.045 (n = 727)lag +2: r = 0.013 (n = 655)lag +3: r = -0.040 (n = 583)lag +4: r = -0.117 (n = 520)lag +5: r = -0.180 (n = 458)lag +6: r = -0.221 (n = 381)lag +7: r = -0.270 (n = 330)lag +8: r = -0.343 (n = 276)

Same year (lag 0): +0.029. 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 +8), 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 employment
per 100,000 population		Years
Niger NER98.5%25.52022, 2019
Burundi BDI98%35.52014, 2019
Chad TCD96.9%32.42018, 2019
Benin BEN96.3%26.82022, 2019
Congo, Dem. Rep. COD96.3%34.92020, 2019
Madagascar MDG96.1%29.22022, 2019
Mozambique MOZ95.5%302015, 2019
Angola AGO95.3%26.12024, 2019
Guinea-Bissau GNB94.8%32.22022, 2019
Uganda UGA94.5%29.42021, 2019
Mali MLI94.4%22.72023, 2019
Sudan SDN94.2%26.82022, 2019
Burkina Faso BFA93.8%312024, 2019
Nigeria NGA93.1%20.72024, 2019
Sierra Leone SLE93.1%332018, 2019

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.

Road traffic deaths

Mortality from road traffic injury (per 100,000 population)

World Health Organization · CC BY 4.0 · updated quarterly

The World Bank's copy stops at 2019.

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 Road traffic deaths

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

More links with Informal employment or Road traffic deaths