placestats

Secondary enrollment vs. Vulnerable employment

Fades after adjusting for income

Across 169 countries, Secondary enrollment and Vulnerable employment rise and fall together at r = -0.72 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.16, which could easily be chance (q = 0.21, 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 secondary enrollment, 70.2% to 103% gross, vulnerable employment is better by 21.9% of employment at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 4.08% of employment.

Link before adjusting (r)-0.717p = 5.5e-28 · 169 countries
After adjusting for national income-0.157p = 0.042 · likely range [-0.30, -0.01]
p, allowing for regions0.065standard error 0.070 · 7 regions
Check for luck (q)0.212across 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.

Secondary enrollment · % grosslink with income +0.71 · high
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

Secondary enrollment · % gross →Vulnerable employment · % of employment →3.35%143%0.456%90.2%Afghanistan: 59.6% gross, 81.8% of employmentAngola: 51.5% gross, 66.3% of employmentAlbania: 108% gross, 46% of employmentUnited Arab Emirates: 102% gross, 1.5% of employmentArgentina: 106% gross, 22.3% of employmentArmenia: 90.9% gross, 32.8% of employmentAustralia: 132% gross, 9.12% of employmentAustria: 101% gross, 7.85% of employmentAzerbaijan: 91.1% gross, 53.8% of employmentBurundi: 23.1% gross, 83.7% of employmentBelgium: 143% gross, 11% of employmentBenin: 43.6% gross, 78.5% of employmentBurkina Faso: 30% gross, 80.6% of employmentBangladesh: 64.3% gross, 57.3% of employmentBulgaria: 94.8% gross, 6.92% of employmentBahrain: 98.8% gross, 0.749% of employmentBahamas, The: 79.5% gross, 15.9% of employmentBosnia and Herzegovina: 87.9% gross, 18.1% of employmentBelarus: 94.8% gross, 6.33% of employmentBelize: 86.5% gross, 29.8% of employmentBolivia: 90.5% gross, 62.7% of employmentBrazil: 104% gross, 26.1% of employmentBarbados: 104% gross, 18.8% of employmentBrunei Darussalam: 91.8% gross, 4.48% of employmentBhutan: 86.2% gross, 69% of employmentBotswana: 70.6% gross, 25.6% of employmentCentral African Republic: 15.8% gross, 79.4% of employmentCanada: 104% gross, 9.56% of employmentSwitzerland: 101% gross, 9.6% of employmentChile: 106% gross, 20.9% of employmentChina: 92.3% gross, 33.4% of employmentCote d'Ivoire: 65.3% gross, 69.4% of employmentCameroon: 44.8% gross, 67.6% of employmentCongo, Dem. Rep.: 55.5% gross, 81.5% of employmentCongo, Rep.: 50.5% gross, 75.9% of employmentColombia: 102% gross, 43% of employmentComoros: 54.8% gross, 56.8% of employmentCabo Verde: 96.4% gross, 34.3% of employmentCosta Rica: 122% gross, 23.4% of employmentCyprus: 107% gross, 8.38% of employmentCzechia: 97.6% gross, 13.5% of employmentGermany: 100% gross, 4.34% of employmentDenmark: 126% gross, 5.4% of employmentDominican Republic: 76.4% gross, 38% of employmentAlgeria: 105% gross, 25.6% of employmentEcuador: 92.8% gross, 50.1% of employmentEgypt, Arab Rep.: 84.8% gross, 23.9% of employmentSpain: 119% gross, 10.1% of employmentEstonia: 109% gross, 7.09% of employmentEthiopia: 33.9% gross, 84.1% of employmentFinland: 142% gross, 9.46% of employmentFiji: 98.1% gross, 32.8% of employmentFrance: 104% gross, 8.5% of employmentGabon: 70.3% gross, 29.8% of employmentUnited Kingdom: 112% gross, 11.5% of employmentGeorgia: 101% gross, 42.4% of employmentGhana: 75.7% gross, 60% of employmentGuinea: 38.6% gross, 79.2% of employmentGambia, The: 107% gross, 63.5% of employmentGreece: 105% gross, 23.1% of employmentGuatemala: 49.6% gross, 36.2% of employmentGuyana: 91.4% gross, 25.3% of employmentHong Kong SAR, China: 107% gross, 5.76% of employmentHonduras: 51.8% gross, 33.9% of employmentCroatia: 105% gross, 6.35% of employmentHungary: 107% gross, 7.83% of employmentIndonesia: 97.2% gross, 50% of employmentIndia: 79.6% gross, 71.6% of employmentIreland: 131% gross, 9.64% of employmentIran, Islamic Rep.: 85.1% gross, 39.5% of employmentIceland: 109% gross, 8.4% of employmentIsrael: 98.5% gross, 7.7% of employmentItaly: 101% gross, 14.3% of employmentJamaica: 84.5% gross, 31.6% of employmentJordan: 91.8% gross, 7.86% of employmentJapan: 102% gross, 7.49% of employmentKazakhstan: 97.6% gross, 24.8% of employmentKenya: 84.3% gross, 63.8% of employmentKyrgyz Republic: 91.7% gross, 29% of employmentCambodia: 58.8% gross, 52.3% of employmentKorea, Rep.: 96.3% gross, 17.7% of employmentKuwait: 95.4% gross, 2.4% of employmentLao PDR: 50.5% gross, 76.4% of employmentLebanon: 63.8% gross, 19.4% of employmentLiberia: 37.7% gross, 76.9% of employmentSt. Lucia: 87.9% gross, 22% of employmentSri Lanka: 88% gross, 39.2% of employmentLesotho: 59.4% gross, 32.6% of employmentLithuania: 105% gross, 10.4% of employmentLuxembourg: 109% gross, 6.95% of employmentLatvia: 101% gross, 8.62% of employmentMacao SAR, China: 94.7% gross, 3.33% of employmentMorocco: 90% gross, 35.5% of employmentMoldova: 99.3% gross, 58.6% of employmentMadagascar: 34.1% gross, 84.4% of employmentMaldives: 79.4% gross, 16.9% of employmentMexico: 103% gross, 25.3% of employmentNorth Macedonia: 90.1% gross, 12.3% of employmentMali: 38.9% gross, 75.8% of employmentMalta: 103% gross, 10.1% of employmentMyanmar: 77% gross, 62.9% of employmentMontenegro: 93.9% gross, 14.3% of employmentMongolia: 96.8% gross, 38.4% of employmentMozambique: 37.2% gross, 83.7% of employmentMauritania: 36% gross, 53.3% of employmentMauritius: 90.7% gross, 14.9% of employmentMalawi: 36.6% gross, 59.9% of employmentMalaysia: 80.3% gross, 21.9% of employmentNamibia: 82% gross, 29.9% of employmentNiger: 19.9% gross, 83.7% of employmentNigeria: 46.9% gross, 66.5% of employmentNicaragua: 70.2% gross, 38.9% of employmentNetherlands: 138% gross, 13.4% of employmentNorway: 116% gross, 4.17% of employmentNepal: 90.4% gross, 77% of employmentNew Zealand: 114% gross, 12.6% of employmentOman: 95.1% gross, 3.81% of employmentPakistan: 48.3% gross, 55.5% of employmentPanama: 76.6% gross, 37.9% of employmentPeru: 108% gross, 47.5% of employmentPhilippines: 85.3% gross, 33.6% of employmentPapua New Guinea: 52.1% gross, 71.2% of employmentPoland: 108% gross, 15% of employmentPuerto Rico (US): 81.5% gross, 10.3% of employmentPortugal: 120% gross, 9.66% of employmentParaguay: 79.1% gross, 36.1% of employmentWest Bank and Gaza: 89.1% gross, 18.4% of employmentQatar: 99.6% gross, 0.456% of employmentRomania: 81.6% gross, 13% of employmentRussian Federation: 92.5% gross, 4.93% of employmentRwanda: 48.8% gross, 39.4% of employmentSaudi Arabia: 111% gross, 1.66% of employmentSudan: 43.5% gross, 39.7% of employmentSenegal: 44.1% gross, 63% of employmentSingapore: 103% gross, 9.3% of employmentSolomon Islands: 49% gross, 68.7% of employmentSierra Leone: 86.9% gross, 86% of employmentEl Salvador: 62.1% gross, 30.8% of employmentSomalia, Fed. Rep.: 3.35% gross, 46% of employmentSerbia: 89.8% gross, 23.9% of employmentSao Tome and Principe: 90.4% gross, 35% of employmentSuriname: 76.1% gross, 18.4% of employmentSlovak Republic: 93.2% gross, 11.8% of employmentSlovenia: 108% gross, 10.6% of employmentSweden: 132% gross, 6.87% of employmentEswatini: 82% gross, 28.4% of employmentSyrian Arab Republic: 38.7% gross, 38.9% of employmentChad: 23.5% gross, 90.2% of employmentTogo: 63.4% gross, 75% of employmentThailand: 92.1% gross, 48% of employmentTajikistan: 86.9% gross, 28% of employmentTurkmenistan: 94.6% gross, 28.3% of employmentTimor-Leste: 84.7% gross, 58.6% of employmentTonga: 92.4% gross, 33.7% of employmentTrinidad and Tobago: 95.7% gross, 21.2% of employmentTunisia: 90.3% gross, 17.9% of employmentTurkiye: 118% gross, 23.9% of employmentTanzania: 28.2% gross, 83.7% of employmentUkraine: 86.2% gross, 19% of employmentUruguay: 119% gross, 24.4% of employmentUnited States: 97.5% gross, 3.81% of employmentUzbekistan: 98.1% gross, 33.3% of employmentSt. Vincent and the Grenadines: 125% gross, 22% of employmentViet Nam: 93.4% gross, 51.4% of employmentVanuatu: 135% gross, 58% of employmentSamoa: 87.4% gross, 41.6% of employmentSouth Africa: 104% gross, 11.7% of employmentZambia: 56.8% gross, 70.2% of employmentZimbabwe: 52.4% gross, 68.2% of employmentBELCAFFINGMBLBNNERSLESOMSWESYRTCDVUT

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.7175.5e-28169
By rank (Spearman), not adjusted-0.6951.2e-25169
Standard (Pearson), adjusted for national income-0.1570.042169
By rank (Spearman), adjusted for national income-0.0890.251169

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 169 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: +0.560 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.197 (without SOM) to -0.132 (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: SOM (-0.039).

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 & Pacific25-0.42
Europe & Central Asia48+0.12
Latin America & Caribbean27+0.04
Middle East, North Africa, Afghanistan & Pakistan19-0.30
Sub-Saharan Africa42-0.27

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 third57-0.28
Middle third56+0.09
Richest third56-0.11

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
Christians102-0.21
Muslims45-0.17

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
France23-0.20
Never a European colony21-0.29
Spain18+0.05
United Kingdom52-0.11

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 = -0.197 after dropping 3 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 35years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

The link shows up within countries over time (r = -0.200) but mostly disappears in year-to-year changes (r = -0.031). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)-0.157for comparison
Within countries-0.507each country vs itself
…and vs the same year elsewhere-0.200q = 0.005 · 175 countries
Year-on-year changes-0.031q = 0.453
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.

3,900 country-years (one country in one year), 175 countries, 1991–2025, about 22 years each on average. Share of the variation that happens within countries over time: 12% for Secondary enrollment, 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

0.30−0.3-100+10years Vulnerable employment trails Secondary enrollment →lag -10: r = -0.138 (n = 3,120)lag -9: r = -0.145 (n = 3,225)lag -8: r = -0.153 (n = 3,324)lag -7: r = -0.161 (n = 3,380)lag -6: r = -0.163 (n = 3,435)lag -5: r = -0.162 (n = 3,502)lag -4: r = -0.169 (n = 3,570)lag -3: r = -0.176 (n = 3,655)lag -2: r = -0.186 (n = 3,731)lag -1: r = -0.194 (n = 3,817)lag +0: r = -0.200 (n = 3,900)lag +1: r = -0.208 (n = 3,971)lag +2: r = -0.202 (n = 3,879)lag +3: r = -0.198 (n = 3,746)lag +4: r = -0.200 (n = 3,621)lag +5: r = -0.191 (n = 3,489)lag +6: r = -0.194 (n = 3,357)lag +7: r = -0.200 (n = 3,228)lag +8: r = -0.202 (n = 3,102)lag +9: r = -0.192 (n = 2,961)lag +10: r = -0.184 (n = 2,827)

Same year (lag 0): -0.200. 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


% gross
% of employment		Years
Belgium BEL143%11%2023, 2025
Finland FIN142%9.46%2024, 2025
Netherlands NLD138%13.4%2023, 2025
Vanuatu VUT135%58%2023, 2025
Sweden SWE132%6.87%2024, 2025
Australia AUS132%9.12%2024, 2025
Ireland IRL131%9.64%2022, 2025
Denmark DNK126%5.4%2024, 2025
St. Vincent and the Grenadines VCT125%22%2024, 2025
Costa Rica CRI122%23.4%2024, 2025
Portugal PRT120%9.66%2023, 2025
Uruguay URY119%24.4%2023, 2025
Spain ESP119%10.1%2024, 2025
Turkiye TUR118%23.9%2023, 2025
Norway NOR116%4.17%2024, 2025

World Bank, World Development Indicators
World Bank, World Development Indicators

Sources

Secondary enrollment

School enrollment, secondary (% gross)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

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 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 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 Secondary enrollment and Vulnerable employment

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

More links with Secondary enrollment or Vulnerable employment