placestats

Employment in agriculture vs. Mean years of schooling

Fades after adjusting for income

Across 174 countries, Employment in agriculture and Mean years of schooling rise and fall together at r = -0.74 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.15, which could easily be chance (q = 0.14, 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 mean years of schooling, 6.43 to 11.8 years, employment in agriculture is 24.7% of employment lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 5.08% of employment.

Link before adjusting (r)-0.739p = 2.4e-31 · 174 countries
After adjusting for national income-0.149p = 0.051 · likely range [-0.29, +0.00]
p, allowing for regions0.030standard error 0.053 · 7 regions
Check for luck (q)0.143across 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.

Employment in agriculture · % of employmentlink with income -0.86 · proxy
Mean years of schooling · yearslink with income +0.82 · 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

Employment in agriculture · % of employment →Mean years of schooling · years →0.0954%85.3%1.4114.3Afghanistan: 51.6% of employment, 2.51 yearsAngola: 51.9% of employment, 5.96 yearsAlbania: 30.8% of employment, 10.2 yearsUnited Arab Emirates: 1.44% of employment, 13 yearsArgentina: 7% of employment, 11.2 yearsArmenia: 27% of employment, 11.3 yearsAustralia: 2.18% of employment, 12.9 yearsAustria: 2.77% of employment, 12.4 yearsAzerbaijan: 34.2% of employment, 11.1 yearsBurundi: 85.3% of employment, 3.47 yearsBelgium: 0.985% of employment, 12.7 yearsBenin: 40.2% of employment, 3.19 yearsBurkina Faso: 51.8% of employment, 2.27 yearsBangladesh: 44.3% of employment, 6.79 yearsBulgaria: 4.69% of employment, 11.5 yearsBahrain: 0.834% of employment, 11.1 yearsBahamas, The: 0.775% of employment, 12.8 yearsBosnia and Herzegovina: 16.7% of employment, 11 yearsBelarus: 9.48% of employment, 12.3 yearsBelize: 16.1% of employment, 8.76 yearsBolivia: 24.7% of employment, 10 yearsBrazil: 7.63% of employment, 8.43 yearsBarbados: 1.25% of employment, 9.93 yearsBrunei Darussalam: 1.2% of employment, 9.28 yearsBhutan: 42.4% of employment, 5.84 yearsBotswana: 18% of employment, 10.5 yearsCentral African Republic: 66.1% of employment, 3.99 yearsCanada: 1.1% of employment, 13.9 yearsSwitzerland: 2.24% of employment, 13.9 yearsChile: 6.07% of employment, 11.3 yearsChina: 21.7% of employment, 8.04 yearsCote d'Ivoire: 45.4% of employment, 4.87 yearsCameroon: 41.9% of employment, 6.57 yearsCongo, Dem. Rep.: 58.5% of employment, 7.38 yearsCongo, Rep.: 36.4% of employment, 8.32 yearsColombia: 14.2% of employment, 9.03 yearsComoros: 33.6% of employment, 6.01 yearsCabo Verde: 9.25% of employment, 6.09 yearsCosta Rica: 11.5% of employment, 8.84 yearsCyprus: 2.15% of employment, 12.6 yearsCzechia: 2.71% of employment, 13 yearsGermany: 1.07% of employment, 14.3 yearsDjibouti: 1.15% of employment, 3.95 yearsDenmark: 1.62% of employment, 13 yearsDominican Republic: 7.01% of employment, 9.44 yearsAlgeria: 9.48% of employment, 7.42 yearsEcuador: 32.5% of employment, 8.97 yearsEgypt, Arab Rep.: 17.5% of employment, 10.1 yearsSpain: 3.37% of employment, 10.8 yearsEstonia: 2.96% of employment, 13.6 yearsEthiopia: 60.1% of employment, 2.4 yearsFinland: 3.49% of employment, 13 yearsFiji: 35.6% of employment, 10.4 yearsFrance: 2.33% of employment, 11.8 yearsGabon: 28.9% of employment, 9.69 yearsUnited Kingdom: 0.851% of employment, 13.5 yearsGeorgia: 34% of employment, 12.7 yearsGhana: 34.6% of employment, 7.11 yearsGuinea: 47.4% of employment, 2.49 yearsGambia, The: 27.6% of employment, 4.67 yearsGuinea-Bissau: 61.1% of employment, 3.67 yearsEquatorial Guinea: 55.3% of employment, 8.28 yearsGreece: 10.7% of employment, 11.6 yearsGuatemala: 29.1% of employment, 5.85 yearsGuyana: 12.2% of employment, 8.7 yearsHong Kong SAR, China: 0.182% of employment, 12.3 yearsHonduras: 22.4% of employment, 7.51 yearsCroatia: 4.33% of employment, 12.1 yearsHaiti: 46.6% of employment, 5.38 yearsHungary: 4.11% of employment, 12.3 yearsIndonesia: 27.3% of employment, 8.7 yearsIndia: 41.6% of employment, 6.88 yearsIreland: 3.85% of employment, 11.7 yearsIran, Islamic Rep.: 13.6% of employment, 10.8 yearsIraq: 8.17% of employment, 6.78 yearsIceland: 3.61% of employment, 13.9 yearsIsrael: 0.76% of employment, 13.5 yearsItaly: 3.35% of employment, 10.8 yearsJamaica: 13.9% of employment, 9.96 yearsJordan: 3.12% of employment, 10.2 yearsJapan: 2.81% of employment, 12.7 yearsKazakhstan: 11.3% of employment, 12.5 yearsKenya: 45.8% of employment, 8.62 yearsKyrgyz Republic: 15.4% of employment, 12.1 yearsCambodia: 33.4% of employment, 5.2 yearsKorea, Rep.: 5.1% of employment, 12.7 yearsKuwait: 1.89% of employment, 7.57 yearsLao PDR: 68.6% of employment, 6.06 yearsLebanon: 3.51% of employment, 10.4 yearsLiberia: 41.1% of employment, 6.17 yearsLibya: 10% of employment, 7.78 yearsSt. Lucia: 7.47% of employment, 8.61 yearsSri Lanka: 25.9% of employment, 10.8 yearsLesotho: 30.9% of employment, 7.73 yearsLithuania: 4.66% of employment, 13.6 yearsLuxembourg: 0.878% of employment, 12.6 yearsLatvia: 6.66% of employment, 13.4 yearsMorocco: 27.9% of employment, 6.2 yearsMoldova: 50.5% of employment, 11.8 yearsMadagascar: 69.2% of employment, 4.59 yearsMaldives: 11.3% of employment, 7.41 yearsMexico: 11.4% of employment, 9.35 yearsNorth Macedonia: 8.5% of employment, 10.2 yearsMali: 63% of employment, 1.63 yearsMalta: 0.877% of employment, 12.4 yearsMyanmar: 45% of employment, 6.38 yearsMontenegro: 4.19% of employment, 12.8 yearsMongolia: 27% of employment, 9.42 yearsMozambique: 73% of employment, 4.59 yearsMauritania: 32.1% of employment, 4.85 yearsMauritius: 4.71% of employment, 10.1 yearsMalawi: 65% of employment, 5.24 yearsMalaysia: 9.18% of employment, 11.1 yearsNamibia: 22.3% of employment, 7.27 yearsNiger: 73% of employment, 1.41 yearsNigeria: 33.5% of employment, 7.59 yearsNicaragua: 30.5% of employment, 9.93 yearsNetherlands: 1.7% of employment, 12.7 yearsNorway: 2.5% of employment, 13.1 yearsNepal: 22.9% of employment, 4.5 yearsNew Zealand: 5.42% of employment, 12.9 yearsOman: 5.95% of employment, 11.9 yearsPakistan: 36.2% of employment, 4.32 yearsPanama: 16% of employment, 10.8 yearsPeru: 23.1% of employment, 10.2 yearsPhilippines: 20.5% of employment, 9.98 yearsPapua New Guinea: 36.9% of employment, 4.96 yearsPoland: 6.22% of employment, 13.2 yearsPortugal: 2.78% of employment, 9.7 yearsParaguay: 16% of employment, 8.93 yearsWest Bank and Gaza: 6.34% of employment, 10.1 yearsQatar: 1.62% of employment, 10.8 yearsRomania: 10.9% of employment, 11.6 yearsRussian Federation: 5.11% of employment, 12.4 yearsRwanda: 35.1% of employment, 4.88 yearsSaudi Arabia: 2.5% of employment, 11.6 yearsSudan: 39.8% of employment, 3.96 yearsSenegal: 29.6% of employment, 2.93 yearsSingapore: 0.0954% of employment, 12 yearsSolomon Islands: 42.5% of employment, 5.88 yearsSierra Leone: 44.5% of employment, 3.54 yearsEl Salvador: 13.9% of employment, 7.3 yearsSomalia, Fed. Rep.: 30% of employment, 1.9 yearsSerbia: 18% of employment, 11.6 yearsSao Tome and Principe: 12.1% of employment, 5.99 yearsSuriname: 6.98% of employment, 8.43 yearsSlovak Republic: 2.16% of employment, 13.1 yearsSlovenia: 3.66% of employment, 13 yearsSweden: 1.77% of employment, 12.7 yearsEswatini: 14.5% of employment, 8.69 yearsSyrian Arab Republic: 16.3% of employment, 5.94 yearsChad: 71.7% of employment, 2.33 yearsTogo: 37.6% of employment, 5.86 yearsThailand: 28.6% of employment, 9.04 yearsTajikistan: 43.3% of employment, 11.3 yearsTurkmenistan: 21.9% of employment, 11.2 yearsTimor-Leste: 46% of employment, 6.23 yearsTonga: 23.6% of employment, 10.9 yearsTrinidad and Tobago: 4.49% of employment, 10.8 yearsTunisia: 12.5% of employment, 7.59 yearsTurkiye: 14.2% of employment, 8.99 yearsTanzania: 64.6% of employment, 6.07 yearsUganda: 64.9% of employment, 6.32 yearsUkraine: 14.1% of employment, 11.1 yearsUruguay: 8.07% of employment, 10.5 yearsUnited States: 1.52% of employment, 13.9 yearsUzbekistan: 25.2% of employment, 11.9 yearsSt. Vincent and the Grenadines: 9.07% of employment, 11.3 yearsViet Nam: 25% of employment, 8.98 yearsVanuatu: 44.5% of employment, 7.18 yearsSamoa: 26.9% of employment, 11.3 yearsSouth Africa: 5.41% of employment, 11.6 yearsZambia: 54.5% of employment, 7.4 yearsZimbabwe: 54.3% of employment, 8.93 yearsBDICANCPVDEUDJIGEOMDANERSOMTCDTJKUSA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.7392.4e-31174
By rank (Spearman), not adjusted-0.7501.2e-32174
Standard (Pearson), adjusted for national income-0.1490.051174
By rank (Spearman), adjusted for national income-0.1210.112174

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: +0.591 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.186 (without DJI) to -0.114 (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: DJI (-0.037).

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 & Pacific24-0.48
Europe & Central Asia48-0.15
Latin America & Caribbean27-0.31
Middle East, North Africa, Afghanistan & Pakistan22-0.37
Sub-Saharan Africa45-0.09

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 third58-0.16
Middle third58+0.01
Richest third58-0.36

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
Christians104-0.07
Muslims49-0.27

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
France25-0.18
Never a European colony21-0.21
Spain19-0.13
United Kingdom55-0.15

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 = -0.155 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 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 = -0.033, 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 employment in agriculture moved did not tend to see their mean years of schooling move with it.

Across countries (adjusted)-0.149for comparison
Within countries-0.587each country vs itself
…and vs the same year elsewhere-0.033q = 0.705 · 178 countries
Year-on-year changes-0.017q = 0.675
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 Employment in agriculture, 5% for Mean years of schooling. 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 Mean years of schooling trails Employment in agriculture →lag -10: r = 0.045 (n = 4,293)lag -9: r = 0.042 (n = 4,471)lag -8: r = 0.036 (n = 4,649)lag -7: r = 0.028 (n = 4,827)lag -6: r = 0.021 (n = 5,005)lag -5: r = 0.013 (n = 5,183)lag -4: r = 0.004 (n = 5,361)lag -3: r = -0.005 (n = 5,539)lag -2: r = -0.015 (n = 5,717)lag -1: r = -0.023 (n = 5,722)lag +0: r = -0.033 (n = 5,578)lag +1: r = -0.042 (n = 5,432)lag +2: r = -0.052 (n = 5,284)lag +3: r = -0.061 (n = 5,135)lag +4: r = -0.072 (n = 4,986)lag +5: r = -0.085 (n = 4,833)lag +6: r = -0.094 (n = 4,680)lag +7: r = -0.101 (n = 4,527)lag +8: r = -0.103 (n = 4,374)lag +9: r = -0.102 (n = 4,218)lag +10: r = -0.099 (n = 4,050)

Same year (lag 0): -0.033. 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 (-0.10 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


% of employment
years		Years
Burundi BDI85.3%3.472025, 2023
Mozambique MOZ73%4.592025, 2023
Niger NER73%1.412025, 2023
Chad TCD71.7%2.332025, 2023
Madagascar MDG69.2%4.592025, 2023
Lao PDR LAO68.6%6.062025, 2023
Central African Republic CAF66.1%3.992025, 2023
Malawi MWI65%5.242025, 2023
Uganda UGA64.9%6.322025, 2023
Tanzania TZA64.6%6.072025, 2023
Mali MLI63%1.632025, 2023
Guinea-Bissau GNB61.1%3.672025, 2023
Ethiopia ETH60.1%2.42025, 2023
Congo, Dem. Rep. COD58.5%7.382025, 2023
Equatorial Guinea GNQ55.3%8.282025, 2023

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

Sources

Employment in agriculture

Employment in agriculture (% of total employment)

International Labour Organization · CC BY 4.0 · updated quarterly

Estimated with a model by the ILO. The classic measure of a country moving from farming to industry and services. It is one of the measures most closely linked to income on the site. No "better" direction is set, because a farming country is not doing badly by farming.

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.

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 Employment in agriculture and Mean years of schooling

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

More links with Employment in agriculture or Mean years of schooling