placestats

Conflict deaths vs. Informal employment

Holds up after adjusting for income

Across 140 countries, Conflict deaths and Informal employment rise and fall together at r = +0.08 (on a scale from −1 to +1, where 0 means no link). There is almost no link to explain.

Comparing countries across the middle half of conflict deaths, 0 to 0.0385 per 100,000 people, informal employment is worse by 0.00417% of employment at the top of that range than the bottom. Comparing only countries with similar national income, the gap reverses, to 0.00442% of employment the other way.

Link before adjusting (r)+0.079p = 0.353 · 140 countries
After adjusting for national income-0.165p = 0.052 · likely range [-0.32, +0.00]
p, allowing for regions0.002standard error 0.027 · 6 regions
Check for luck (q)0.028across 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.

Conflict deaths · per 100,000 peoplelink with income -0.42 · moderate
Informal employment · % of employmentlink with income -0.88 · proxy

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

Conflict deaths · per 100,000 people →Informal employment · % of employment →02590.63%98.5%Afghanistan: 0.753 per 100,000 people, 86.1% of employmentAngola: 0.0615 per 100,000 people, 95.3% of employmentArgentina: 0.0981 per 100,000 people, 51.6% of employmentArmenia: 0 per 100,000 people, 76.1% of employmentAntigua and Barbuda: 0 per 100,000 people, 12.8% of employmentAustria: 0 per 100,000 people, 1.32% of employmentBurundi: 0.431 per 100,000 people, 98% of employmentBelgium: 0 per 100,000 people, 1.37% of employmentBenin: 0.851 per 100,000 people, 96.3% of employmentBurkina Faso: 18.6 per 100,000 people, 93.8% of employmentBangladesh: 0 per 100,000 people, 84% of employmentBulgaria: 0 per 100,000 people, 1.2% of employmentBahamas, The: 0 per 100,000 people, 18.3% of employmentBosnia and Herzegovina: 0 per 100,000 people, 16.6% of employmentBolivia: 0 per 100,000 people, 83.9% of employmentBrazil: 0.278 per 100,000 people, 35.6% of employmentBarbados: 0 per 100,000 people, 61.8% of employmentBrunei Darussalam: 0 per 100,000 people, 21.4% of employmentBotswana: 0 per 100,000 people, 75.6% of employmentSwitzerland: 0 per 100,000 people, 1.48% of employmentChile: 0 per 100,000 people, 26.4% of employmentCote d'Ivoire: 0 per 100,000 people, 92.1% of employmentCameroon: 1.23 per 100,000 people, 87.1% of employmentCongo, Dem. Rep.: 7.85 per 100,000 people, 96.3% of employmentColombia: 1.76 per 100,000 people, 56% of employmentComoros: 0 per 100,000 people, 88.8% of employmentCabo Verde: 0 per 100,000 people, 60.6% of employmentCosta Rica: 2.76 per 100,000 people, 36.1% of employmentCyprus: 0 per 100,000 people, 1.68% of employmentCzechia: 0 per 100,000 people, 2.26% of employmentGermany: 0 per 100,000 people, 2.49% of employmentDjibouti: 0 per 100,000 people, 47.6% of employmentDenmark: 0 per 100,000 people, 2.82% of employmentDominican Republic: 0 per 100,000 people, 54.7% of employmentEcuador: 1.93 per 100,000 people, 68.5% of employmentEgypt, Arab Rep.: 0 per 100,000 people, 68.6% of employmentSpain: 0 per 100,000 people, 2.2% of employmentEstonia: 0 per 100,000 people, 2.4% of employmentEthiopia: 4 per 100,000 people, 77.7% of employmentFinland: 0 per 100,000 people, 2.19% of employmentFiji: 0 per 100,000 people, 45.7% of employmentFrance: 0 per 100,000 people, 3.15% of employmentUnited Kingdom: 0 per 100,000 people, 6.51% of employmentGeorgia: 0 per 100,000 people, 51.5% of employmentGhana: 0.279 per 100,000 people, 78% of employmentGambia, The: 0 per 100,000 people, 83.9% of employmentGuinea-Bissau: 0 per 100,000 people, 94.8% of employmentGreece: 0 per 100,000 people, 3.58% of employmentGrenada: 0 per 100,000 people, 48% of employmentGuatemala: 0.0375 per 100,000 people, 75.9% of employmentGuyana: 0 per 100,000 people, 51% of employmentHonduras: 0 per 100,000 people, 82.6% of employmentCroatia: 0 per 100,000 people, 1.17% of employmentHaiti: 20.4 per 100,000 people, 91.6% of employmentHungary: 0 per 100,000 people, 1.31% of employmentIndonesia: 0.0364 per 100,000 people, 81% of employmentIndia: 0.0416 per 100,000 people, 88.1% of employmentIreland: 0 per 100,000 people, 1.9% of employmentIraq: 0.285 per 100,000 people, 67.6% of employmentIceland: 0 per 100,000 people, 1.97% of employmentItaly: 0 per 100,000 people, 3.42% of employmentJamaica: 0 per 100,000 people, 54.6% of employmentJordan: 0 per 100,000 people, 55.1% of employmentKenya: 0.122 per 100,000 people, 86.5% of employmentKyrgyz Republic: 0 per 100,000 people, 57.5% of employmentCambodia: 0.981 per 100,000 people, 89.4% of employmentKiribati: 0 per 100,000 people, 61.5% of employmentKorea, Rep.: 0 per 100,000 people, 29.1% of employmentLao PDR: 0 per 100,000 people, 90.5% of employmentLebanon: 5.93 per 100,000 people, 55.5% of employmentLiberia: 0 per 100,000 people, 89.3% of employmentSt. Lucia: 0 per 100,000 people, 28.3% of employmentSri Lanka: 0 per 100,000 people, 67.6% of employmentLesotho: 0 per 100,000 people, 89.1% of employmentLithuania: 0 per 100,000 people, 3.2% of employmentLuxembourg: 0 per 100,000 people, 1.93% of employmentLatvia: 0 per 100,000 people, 2.17% of employmentMoldova: 0 per 100,000 people, 52.2% of employmentMadagascar: 0 per 100,000 people, 96.1% of employmentMaldives: 0 per 100,000 people, 47.3% of employmentMexico: 5.94 per 100,000 people, 56.4% of employmentMarshall Islands: 0 per 100,000 people, 32.6% of employmentNorth Macedonia: 0 per 100,000 people, 11.1% of employmentMali: 8.54 per 100,000 people, 94.4% of employmentMalta: 0 per 100,000 people, 0.63% of employmentMyanmar: 4.21 per 100,000 people, 80.7% of employmentMongolia: 0 per 100,000 people, 27.1% of employmentMozambique: 1.71 per 100,000 people, 95.5% of employmentMauritania: 0 per 100,000 people, 89.3% of employmentMauritius: 0 per 100,000 people, 23.4% of employmentMalawi: 0 per 100,000 people, 92.7% of employmentNamibia: 0 per 100,000 people, 55.6% of employmentNiger: 3.98 per 100,000 people, 98.5% of employmentNigeria: 1.69 per 100,000 people, 93.1% of employmentNicaragua: 0 per 100,000 people, 81.8% of employmentNetherlands: 0 per 100,000 people, 2.63% of employmentNorway: 0 per 100,000 people, 1.43% of employmentNepal: 0 per 100,000 people, 81.5% of employmentNaoero: 0 per 100,000 people, 47.9% of employmentPakistan: 1.3 per 100,000 people, 88.7% of employmentPanama: 0 per 100,000 people, 58.7% of employmentPeru: 0 per 100,000 people, 70.5% of employmentPalau: 0 per 100,000 people, 7.27% of employmentPoland: 0 per 100,000 people, 8.62% of employmentPortugal: 0 per 100,000 people, 4.73% of employmentParaguay: 0 per 100,000 people, 64.5% of employmentWest Bank and Gaza: 259 per 100,000 people, 48.8% of employmentRomania: 0 per 100,000 people, 2.21% of employmentRussian Federation: 3.07 per 100,000 people, 19.3% of employmentRwanda: 0.00686 per 100,000 people, 84.3% of employmentSudan: 145 per 100,000 people, 94.2% of employmentSenegal: 0 per 100,000 people, 89.2% of employmentSierra Leone: 0 per 100,000 people, 93.1% of employmentEl Salvador: 0 per 100,000 people, 64% of employmentSomalia, Fed. Rep.: 19.7 per 100,000 people, 81.9% of employmentSerbia: 0 per 100,000 people, 17.8% of employmentSuriname: 0 per 100,000 people, 50.9% of employmentSlovak Republic: 0 per 100,000 people, 4.37% of employmentSlovenia: 0 per 100,000 people, 0.7% of employmentSweden: 0 per 100,000 people, 2.83% of employmentEswatini: 0 per 100,000 people, 53.3% of employmentSeychelles: 0 per 100,000 people, 14.2% of employmentChad: 0.681 per 100,000 people, 96.9% of employmentTogo: 0.803 per 100,000 people, 92.3% of employmentThailand: 0.158 per 100,000 people, 63.2% of employmentTajikistan: 0 per 100,000 people, 63.6% of employmentTimor-Leste: 0 per 100,000 people, 80.6% of employmentTonga: 0 per 100,000 people, 59.2% of employmentTunisia: 0 per 100,000 people, 36.9% of employmentTurkiye: 0.00114 per 100,000 people, 27.7% of employmentTuvalu: 0 per 100,000 people, 20.1% of employmentTanzania: 1.43 per 100,000 people, 90.8% of employmentUganda: 0.00389 per 100,000 people, 94.5% of employmentUruguay: 0 per 100,000 people, 28.5% of employmentViet Nam: 0 per 100,000 people, 67% of employmentVanuatu: 0 per 100,000 people, 72.4% of employmentSamoa: 0 per 100,000 people, 51.5% of employmentSouth Africa: 0.00154 per 100,000 people, 34.8% of employmentZambia: 0 per 100,000 people, 82.7% of employmentZimbabwe: 0 per 100,000 people, 85% of employmentBDIHRVHTIMDGMLTPSESDNSVNTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.0790.353140
By rank (Spearman), not adjusted+0.4917.4e-10140
Standard (Pearson), adjusted for national income-0.1650.052140
By rank (Spearman), adjusted for national income+0.2320.006140

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: -0.086 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.178 (without TUV) to -0.056 (without PSE). 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: PSE (+0.109).

Fragile: this link may not hold up.
  • correlation moves sharply once outliers are trimmed
  • sign flips once outliers are trimmed
  • 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+0.25
Europe & Central Asia40+0.09
Latin America & Caribbean26-0.09
Sub-Saharan Africa40-0.08

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 third47-0.27
Middle third46+0.05
Richest third47+0.15

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+0.01
Muslims31-0.37

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
France19-0.13
Never a European colony12-0.03
Spain16-0.06
United Kingdom43-0.02

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 = +0.333 after dropping 33 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 26years. 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 conflict deaths moved did not tend to see their informal employment move with it.

Across countries (adjusted)-0.165for comparison
Within countries-0.052each country vs itself
…and vs the same year elsewhere-0.029q = 0.005 · 82 countries
Year-on-year changes-0.002q = 0.862
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.

1,190 country-years (one country in one year), 82 countries, 2000–2025, about 15 years each on average. Share of the variation that happens within countries over time: 85% for Conflict deaths, 2% 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

0.10−0.1-100+10years Informal employment trails Conflict deaths →lag -10: r = 0.035 (n = 526)lag -9: r = 0.002 (n = 590)lag -8: r = -0.026 (n = 663)lag -7: r = -0.028 (n = 736)lag -6: r = -0.021 (n = 810)lag -5: r = -0.031 (n = 877)lag -4: r = -0.041 (n = 959)lag -3: r = -0.041 (n = 1,037)lag -2: r = -0.013 (n = 1,118)lag -1: r = -0.004 (n = 1,181)lag +0: r = -0.029 (n = 1,190)lag +1: r = -0.031 (n = 1,190)lag +2: r = -0.017 (n = 1,190)lag +3: r = 0.005 (n = 1,190)lag +4: r = 0.021 (n = 1,190)lag +5: r = 0.009 (n = 1,190)lag +6: r = 0.007 (n = 1,190)lag +7: r = 0.033 (n = 1,190)lag +8: r = 0.051 (n = 1,190)lag +9: r = 0.054 (n = 1,190)lag +10: r = -0.018 (n = 1,190)

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.

The data


per 100,000 people
% of employment		Years
West Bank and Gaza PSE25948.8%2025
Sudan SDN14594.2%2025, 2022
Haiti HTI20.491.6%2025, 2012
Somalia, Fed. Rep. SOM19.781.9%2025, 2019
Burkina Faso BFA18.693.8%2025, 2024
Mali MLI8.5494.4%2025, 2023
Congo, Dem. Rep. COD7.8596.3%2025, 2020
Mexico MEX5.9456.4%2025, 2024
Lebanon LBN5.9355.5%2025, 2019
Myanmar MMR4.2180.7%2025, 2020
Ethiopia ETH477.7%2025, 2021
Niger NER3.9898.5%2025, 2022
Russian Federation RUS3.0719.3%2025, 2024
Costa Rica CRI2.7636.1%2025
Ecuador ECU1.9368.5%2025

Uppsala Conflict Data Program, Georeferenced Event Dataset; rate per population from Our World in Data
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

Conflict deaths

Deaths in armed conflicts, per 100,000 people

Uppsala Conflict Data Program, Uppsala University · via Our World in Data · CC BY 4.0 · updated annual

Deaths from organised violence on a country's territory, per 100,000 of its people. That covers fighting involving a government, fighting between other armed groups, and attacks on civilians. Deaths are counted where the fighting happens, not by who was fighting. So a war fought on one country's soil by another country's army counts here. It is zero for most countries in most years, and in the hundreds per hundred thousand for a few at war. That is why it is put on a log scale (which squeezes very large values together) where it is used for adjusting. It is also why the "leave one out" check matters on every pair involving it: a handful of countries carry the whole link. The site's only other measure of violence is the homicide rate, which counts something different. A peaceful country can have a high homicide rate, and a country at war can have a low one. It is kept out of every topic score. In 2023, 143 of the 197 countries reporting it report exactly zero. A log scale, used here since a few values are huge, cannot handle zero, so every zero becomes a blank. A safety score built on it covered 79 countries instead of 172. It silently dropped the peaceful ones, the opposite of what such a score should say. A score needs parts that vary across nearly every country. This one is a rare event almost everywhere and the biggest fact in a dozen places. That makes it worth its own page, and useless inside an average.

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 Conflict deaths and Informal employment

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

More links with Conflict deaths or Informal employment