placestats

Mean years of schooling vs. Vulnerable employment

Holds up after adjusting for income

Across 174 countries, Mean years of schooling and Vulnerable employment rise and fall together at r = -0.81 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.33 (q = 0.020, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak negative link remains.

Comparing countries across the middle half of mean years of schooling, 6.43 to 11.8 years, vulnerable employment is better by 33.7% of employment at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 13.3% of employment.

Link before adjusting (r)-0.806p = 4.9e-41 · 174 countries
After adjusting for national income-0.331p = 8.9e-6 · likely range [-0.46, -0.19]
p, allowing for regions0.001standard error 0.055 · 7 regions
Check for luck (q)0.020across 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.

Mean years of schooling · yearslink with income +0.82 · proxy
Vulnerable employment · % of employmentlink with income -0.87 · 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

Mean years of schooling · years →Vulnerable employment · % of employment →1.4114.30.456%90.2%Afghanistan: 2.51 years, 81.8% of employmentAngola: 5.96 years, 66.3% of employmentAlbania: 10.2 years, 46% of employmentUnited Arab Emirates: 13 years, 1.5% of employmentArgentina: 11.2 years, 22.3% of employmentArmenia: 11.3 years, 32.8% of employmentAustralia: 12.9 years, 9.12% of employmentAustria: 12.4 years, 7.85% of employmentAzerbaijan: 11.1 years, 53.8% of employmentBurundi: 3.47 years, 83.7% of employmentBelgium: 12.7 years, 11% of employmentBenin: 3.19 years, 78.5% of employmentBurkina Faso: 2.27 years, 80.6% of employmentBangladesh: 6.79 years, 57.3% of employmentBulgaria: 11.5 years, 6.92% of employmentBahrain: 11.1 years, 0.749% of employmentBahamas, The: 12.8 years, 15.9% of employmentBosnia and Herzegovina: 11 years, 18.1% of employmentBelarus: 12.3 years, 6.33% of employmentBelize: 8.76 years, 29.8% of employmentBolivia: 10 years, 62.7% of employmentBrazil: 8.43 years, 26.1% of employmentBarbados: 9.93 years, 18.8% of employmentBrunei Darussalam: 9.28 years, 4.48% of employmentBhutan: 5.84 years, 69% of employmentBotswana: 10.5 years, 25.6% of employmentCentral African Republic: 3.99 years, 79.4% of employmentCanada: 13.9 years, 9.56% of employmentSwitzerland: 13.9 years, 9.6% of employmentChile: 11.3 years, 20.9% of employmentChina: 8.04 years, 33.4% of employmentCote d'Ivoire: 4.87 years, 69.4% of employmentCameroon: 6.57 years, 67.6% of employmentCongo, Dem. Rep.: 7.38 years, 81.5% of employmentCongo, Rep.: 8.32 years, 75.9% of employmentColombia: 9.03 years, 43% of employmentComoros: 6.01 years, 56.8% of employmentCabo Verde: 6.09 years, 34.3% of employmentCosta Rica: 8.84 years, 23.4% of employmentCyprus: 12.6 years, 8.38% of employmentCzechia: 13 years, 13.5% of employmentGermany: 14.3 years, 4.34% of employmentDjibouti: 3.95 years, 30.3% of employmentDenmark: 13 years, 5.4% of employmentDominican Republic: 9.44 years, 38% of employmentAlgeria: 7.42 years, 25.6% of employmentEcuador: 8.97 years, 50.1% of employmentEgypt, Arab Rep.: 10.1 years, 23.9% of employmentSpain: 10.8 years, 10.1% of employmentEstonia: 13.6 years, 7.09% of employmentEthiopia: 2.4 years, 84.1% of employmentFinland: 13 years, 9.46% of employmentFiji: 10.4 years, 32.8% of employmentFrance: 11.8 years, 8.5% of employmentGabon: 9.69 years, 29.8% of employmentUnited Kingdom: 13.5 years, 11.5% of employmentGeorgia: 12.7 years, 42.4% of employmentGhana: 7.11 years, 60% of employmentGuinea: 2.49 years, 79.2% of employmentGambia, The: 4.67 years, 63.5% of employmentGuinea-Bissau: 3.67 years, 74.9% of employmentEquatorial Guinea: 8.28 years, 23.1% of employmentGreece: 11.6 years, 23.1% of employmentGuatemala: 5.85 years, 36.2% of employmentGuyana: 8.7 years, 25.3% of employmentHong Kong SAR, China: 12.3 years, 5.76% of employmentHonduras: 7.51 years, 33.9% of employmentCroatia: 12.1 years, 6.35% of employmentHaiti: 5.38 years, 76% of employmentHungary: 12.3 years, 7.83% of employmentIndonesia: 8.7 years, 50% of employmentIndia: 6.88 years, 71.6% of employmentIreland: 11.7 years, 9.64% of employmentIran, Islamic Rep.: 10.8 years, 39.5% of employmentIraq: 6.78 years, 27.1% of employmentIceland: 13.9 years, 8.4% of employmentIsrael: 13.5 years, 7.7% of employmentItaly: 10.8 years, 14.3% of employmentJamaica: 9.96 years, 31.6% of employmentJordan: 10.2 years, 7.86% of employmentJapan: 12.7 years, 7.49% of employmentKazakhstan: 12.5 years, 24.8% of employmentKenya: 8.62 years, 63.8% of employmentKyrgyz Republic: 12.1 years, 29% of employmentCambodia: 5.2 years, 52.3% of employmentKorea, Rep.: 12.7 years, 17.7% of employmentKuwait: 7.57 years, 2.4% of employmentLao PDR: 6.06 years, 76.4% of employmentLebanon: 10.4 years, 19.4% of employmentLiberia: 6.17 years, 76.9% of employmentLibya: 7.78 years, 21.6% of employmentSt. Lucia: 8.61 years, 22% of employmentSri Lanka: 10.8 years, 39.2% of employmentLesotho: 7.73 years, 32.6% of employmentLithuania: 13.6 years, 10.4% of employmentLuxembourg: 12.6 years, 6.95% of employmentLatvia: 13.4 years, 8.62% of employmentMorocco: 6.2 years, 35.5% of employmentMoldova: 11.8 years, 58.6% of employmentMadagascar: 4.59 years, 84.4% of employmentMaldives: 7.41 years, 16.9% of employmentMexico: 9.35 years, 25.3% of employmentNorth Macedonia: 10.2 years, 12.3% of employmentMali: 1.63 years, 75.8% of employmentMalta: 12.4 years, 10.1% of employmentMyanmar: 6.38 years, 62.9% of employmentMontenegro: 12.8 years, 14.3% of employmentMongolia: 9.42 years, 38.4% of employmentMozambique: 4.59 years, 83.7% of employmentMauritania: 4.85 years, 53.3% of employmentMauritius: 10.1 years, 14.9% of employmentMalawi: 5.24 years, 59.9% of employmentMalaysia: 11.1 years, 21.9% of employmentNamibia: 7.27 years, 29.9% of employmentNiger: 1.41 years, 83.7% of employmentNigeria: 7.59 years, 66.5% of employmentNicaragua: 9.93 years, 38.9% of employmentNetherlands: 12.7 years, 13.4% of employmentNorway: 13.1 years, 4.17% of employmentNepal: 4.5 years, 77% of employmentNew Zealand: 12.9 years, 12.6% of employmentOman: 11.9 years, 3.81% of employmentPakistan: 4.32 years, 55.5% of employmentPanama: 10.8 years, 37.9% of employmentPeru: 10.2 years, 47.5% of employmentPhilippines: 9.98 years, 33.6% of employmentPapua New Guinea: 4.96 years, 71.2% of employmentPoland: 13.2 years, 15% of employmentPortugal: 9.7 years, 9.66% of employmentParaguay: 8.93 years, 36.1% of employmentWest Bank and Gaza: 10.1 years, 18.4% of employmentQatar: 10.8 years, 0.456% of employmentRomania: 11.6 years, 13% of employmentRussian Federation: 12.4 years, 4.93% of employmentRwanda: 4.88 years, 39.4% of employmentSaudi Arabia: 11.6 years, 1.66% of employmentSudan: 3.96 years, 39.7% of employmentSenegal: 2.93 years, 63% of employmentSingapore: 12 years, 9.3% of employmentSolomon Islands: 5.88 years, 68.7% of employmentSierra Leone: 3.54 years, 86% of employmentEl Salvador: 7.3 years, 30.8% of employmentSomalia, Fed. Rep.: 1.9 years, 46% of employmentSerbia: 11.6 years, 23.9% of employmentSao Tome and Principe: 5.99 years, 35% of employmentSuriname: 8.43 years, 18.4% of employmentSlovak Republic: 13.1 years, 11.8% of employmentSlovenia: 13 years, 10.6% of employmentSweden: 12.7 years, 6.87% of employmentEswatini: 8.69 years, 28.4% of employmentSyrian Arab Republic: 5.94 years, 38.9% of employmentChad: 2.33 years, 90.2% of employmentTogo: 5.86 years, 75% of employmentThailand: 9.04 years, 48% of employmentTajikistan: 11.3 years, 28% of employmentTurkmenistan: 11.2 years, 28.3% of employmentTimor-Leste: 6.23 years, 58.6% of employmentTonga: 10.9 years, 33.7% of employmentTrinidad and Tobago: 10.8 years, 21.2% of employmentTunisia: 7.59 years, 17.9% of employmentTurkiye: 8.99 years, 23.9% of employmentTanzania: 6.07 years, 83.7% of employmentUganda: 6.32 years, 74.4% of employmentUkraine: 11.1 years, 19% of employmentUruguay: 10.5 years, 24.4% of employmentUnited States: 13.9 years, 3.81% of employmentUzbekistan: 11.9 years, 33.3% of employmentSt. Vincent and the Grenadines: 11.3 years, 22% of employmentViet Nam: 8.98 years, 51.4% of employmentVanuatu: 7.18 years, 58% of employmentSamoa: 11.3 years, 41.6% of employmentSouth Africa: 11.6 years, 11.7% of employmentZambia: 7.4 years, 70.2% of employmentZimbabwe: 8.93 years, 68.2% of employmentBOLDEUDJIETHGEOISLKWTMDANERSOMTCDUSA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.8064.9e-41174
By rank (Spearman), not adjusted-0.8013.4e-40174
Standard (Pearson), adjusted for national income-0.3318.9e-6174
By rank (Spearman), adjusted for national income-0.2770.000174

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 174 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: +0.475 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.352 (without DJI) to -0.304 (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 (+0.027).

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 & Pacific24-0.64
Europe & Central Asia48-0.19
Latin America & Caribbean27-0.10
Middle East, North Africa, Afghanistan & Pakistan22-0.43
Sub-Saharan Africa45-0.30

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 third58-0.45
Middle third58-0.11
Richest third58-0.24

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
Christians104-0.25
Muslims49-0.40

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
France25-0.24
Never a European colony21-0.61
Spain19+0.24
United Kingdom55-0.29

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 = -0.331 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 33years. 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 = -0.089, 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 mean years of schooling moved did not tend to see their vulnerable employment move with it.

Across countries (adjusted)-0.331for comparison
Within countries-0.483each country vs itself
…and vs the same year elsewhere-0.089q = 0.285 · 178 countries
Year-on-year changes-0.012q = 0.768
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.
  • 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.

5,578 country-years (one country in one year), 178 countries, 1991–2023, about 31 years each on average. Share of the variation that happens within countries over time: 10% for Mean years of schooling, 1% for Vulnerable 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 Vulnerable employment trails Mean years of schooling →lag -10: r = -0.153 (n = 4,050)lag -9: r = -0.158 (n = 4,218)lag -8: r = -0.159 (n = 4,374)lag -7: r = -0.157 (n = 4,527)lag -6: r = -0.155 (n = 4,680)lag -5: r = -0.150 (n = 4,833)lag -4: r = -0.144 (n = 4,986)lag -3: r = -0.137 (n = 5,135)lag -2: r = -0.122 (n = 5,284)lag -1: r = -0.106 (n = 5,432)lag +0: r = -0.089 (n = 5,578)lag +1: r = -0.073 (n = 5,722)lag +2: r = -0.065 (n = 5,717)lag +3: r = -0.058 (n = 5,539)lag +4: r = -0.052 (n = 5,361)lag +5: r = -0.045 (n = 5,183)lag +6: r = -0.036 (n = 5,005)lag +7: r = -0.027 (n = 4,827)lag +8: r = -0.020 (n = 4,649)lag +9: r = -0.012 (n = 4,471)lag +10: r = -0.004 (n = 4,293)

Same year (lag 0): -0.089. 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 largest value on this curve (-0.16 at lag -8) is higher than the same-year one by 0.07. That gap is not a finding. It is the largest of 21 closely related estimates, and picking the biggest of many tests always makes it look bigger. That is exactly why nothing on this site is ranked or chosen by lag.

The data


years
% of employment		Years
Germany DEU14.34.34%2023, 2025
Switzerland CHE13.99.6%2023, 2025
United States USA13.93.81%2023, 2025
Iceland ISL13.98.4%2023, 2025
Canada CAN13.99.56%2023, 2025
Lithuania LTU13.610.4%2023, 2025
Estonia EST13.67.09%2023, 2025
Israel ISR13.57.7%2023, 2025
United Kingdom GBR13.511.5%2023, 2025
Latvia LVA13.48.62%2023, 2025
Poland POL13.215%2023, 2025
Norway NOR13.14.17%2023, 2025
Slovak Republic SVK13.111.8%2023, 2025
Denmark DNK135.4%2023, 2025
United Arab Emirates ARE131.5%2023, 2025

United Nations Development Programme, Human Development Report 2025
World Bank, World Development Indicators

Sources

Mean years of schooling

Mean years of schooling, adults aged 25 and over

United Nations Development Programme, Human Development Report Office · via Our World in Data · CC BY 3.0 IGO · updated annual

The schooling adults actually completed, decades ago for most of them. Expected schooling looks ahead at children; this looks back at adults. It is the one to read for the education of the workforce rather than of children.

Vulnerable employment

Vulnerable employment, total (% of total employment)

International Labour Organization · CC BY 4.0 · updated quarterly

Self-employed workers and unpaid family workers, who have no employer and usually no protection. The ILO estimates it with a model for every country and year, which is why it is complete where surveys are not.

How this was computed

Data used: most recent value in 2010-2025; values come from 2021–2025. 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 7 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 Mean years of schooling and Vulnerable employment

This page shows that two measures go together. It does not show that Mean years of schooling changes Vulnerable employment, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Mean years of schooling or Vulnerable employment