placestats

Employment in agriculture vs. Redistribution

Fades after adjusting for income

Across 45 countries, Employment in agriculture and Redistribution rise and fall together at r = -0.59 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.26, 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.

Comparing countries across the middle half of redistribution, 23.2% to 38.1% reduction in the Gini, employment in agriculture is 5.09% of employment lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 2.12% of employment.

Link before adjusting (r)-0.592p = 1.8e-5 · 45 countries
After adjusting for national income-0.260p = 0.089 · likely range [-0.52, +0.04]
p, allowing for regions0.185standard error 0.174 · 7 regions
Check for luck (q)0.208across 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
Redistribution · % reduction in the Ginilink with income +0.50 · moderate

“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 →Redistribution · % reduction in the Gini →0.76%41.6%2.67%48.3%Australia: 2.18% of employment, 27.7% reduction in the GiniAustria: 2.77% of employment, 41.4% reduction in the GiniBelgium: 0.985% of employment, 47.7% reduction in the GiniBulgaria: 4.69% of employment, 26% reduction in the GiniBrazil: 7.63% of employment, 13.8% reduction in the GiniCanada: 1.1% of employment, 29.3% reduction in the GiniSwitzerland: 2.24% of employment, 21.2% reduction in the GiniChile: 6.07% of employment, 8.68% reduction in the GiniChina: 21.7% of employment, 6.22% reduction in the GiniCosta Rica: 11.5% of employment, 12.6% reduction in the GiniCzechia: 2.71% of employment, 43.5% reduction in the GiniGermany: 1.07% of employment, 38.7% reduction in the GiniDenmark: 1.62% of employment, 37.5% reduction in the GiniSpain: 3.37% of employment, 34.4% reduction in the GiniEstonia: 2.96% of employment, 33.5% reduction in the GiniFinland: 3.49% of employment, 47.2% reduction in the GiniFrance: 2.33% of employment, 42.2% reduction in the GiniUnited Kingdom: 0.851% of employment, 29.7% reduction in the GiniGreece: 10.7% of employment, 36.9% reduction in the GiniCroatia: 4.33% of employment, 33.1% reduction in the GiniHungary: 4.11% of employment, 29.4% reduction in the GiniIndia: 41.6% of employment, 2.67% reduction in the GiniIreland: 3.85% of employment, 41.2% reduction in the GiniIceland: 3.61% of employment, 35.7% reduction in the GiniIsrael: 0.76% of employment, 23.2% reduction in the GiniItaly: 3.35% of employment, 36.2% reduction in the GiniJapan: 2.81% of employment, 34.1% reduction in the GiniKorea, Rep.: 5.1% of employment, 18.2% reduction in the GiniLithuania: 4.66% of employment, 29.7% reduction in the GiniLuxembourg: 0.878% of employment, 35.7% reduction in the GiniLatvia: 6.66% of employment, 28.1% reduction in the GiniMexico: 11.4% of employment, 3.77% reduction in the GiniNetherlands: 1.7% of employment, 34.2% reduction in the GiniNorway: 2.5% of employment, 39.5% reduction in the GiniNew Zealand: 5.42% of employment, 28.7% reduction in the GiniPoland: 6.22% of employment, 41.9% reduction in the GiniPortugal: 2.78% of employment, 36.5% reduction in the GiniRomania: 10.9% of employment, 38.1% reduction in the GiniRussian Federation: 5.11% of employment, 27% reduction in the GiniSlovak Republic: 2.16% of employment, 48.3% reduction in the GiniSlovenia: 3.66% of employment, 42.4% reduction in the GiniSweden: 1.77% of employment, 33.1% reduction in the GiniTurkiye: 14.2% of employment, 18.6% reduction in the GiniUnited States: 1.52% of employment, 22.1% reduction in the GiniSouth Africa: 5.41% of employment, 12.8% reduction in the GiniBELCHLCHNFINGRCINDMEXROUSVKZAF

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5921.8e-545
By rank (Spearman), not adjusted-0.4380.00345
Standard (Pearson), adjusted for national income-0.2600.08945
By rank (Spearman), adjusted for national income-0.1200.43745

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 45 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: +0.332 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.321 (without IND) to -0.199 (without CHN). 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: IND (-0.061).

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
Europe & Central Asia31-0.30

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 third15-0.14
Middle third15-0.06
Richest third15+0.25

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
Christians36-0.16

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 = -0.188 after dropping 7 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.

Loading…

Over time, within countries

Everything above compares countries with each other at one moment. This section compares each country only with itself over 14years. 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 = -0.087, 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 redistribution move with it.

Across countries (adjusted)-0.260for comparison
Within countries-0.112each country vs itself
…and vs the same year elsewhere-0.087q = 0.701 · 39 countries
Year-on-year changes+0.002q = 0.989
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.

442 country-years (one country in one year), 39 countries, 2011–2024, about 11 years each on average. Share of the variation that happens within countries over time: 4% for Employment in agriculture, 5% for Redistribution. 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

0.30−0.3-80+10years Redistribution trails Employment in agriculture →lag -8: r = -0.185 (n = 217)lag -7: r = -0.187 (n = 249)lag -6: r = -0.203 (n = 286)lag -5: r = -0.208 (n = 338)lag -4: r = -0.166 (n = 371)lag -3: r = -0.162 (n = 416)lag -2: r = -0.150 (n = 441)lag -1: r = -0.116 (n = 442)lag +0: r = -0.087 (n = 442)lag +1: r = -0.084 (n = 442)lag +2: r = -0.076 (n = 442)lag +3: r = -0.077 (n = 442)lag +4: r = -0.058 (n = 442)lag +5: r = -0.014 (n = 442)lag +6: r = -0.009 (n = 442)lag +7: r = -0.028 (n = 442)lag +8: r = -0.073 (n = 442)lag +9: r = -0.129 (n = 442)lag +10: r = -0.206 (n = 442)

Same year (lag 0): -0.087. 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 (-0.21 at lag -5) is higher than the same-year one by 0.12. That gap is not a finding. It is the largest of 19 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
% reduction in the Gini		Years
India IND41.6%2.67%2025, 2011
China CHN21.7%6.22%2025, 2011
Turkiye TUR14.2%18.6%2025, 2022
Costa Rica CRI11.5%12.6%2025, 2024
Mexico MEX11.4%3.77%2025, 2022
Romania ROU10.9%38.1%2025, 2023
Greece GRC10.7%36.9%2025, 2023
Brazil BRA7.63%13.8%2025, 2022
Latvia LVA6.66%28.1%2025, 2023
Poland POL6.22%41.9%2025, 2023
Chile CHL6.07%8.68%2025, 2022
New Zealand NZL5.42%28.7%2025, 2022
South Africa ZAF5.41%12.8%2025, 2017
Russian Federation RUS5.11%27%2025, 2017
Korea, Rep. KOR5.1%18.2%2025, 2022

World Bank, World Development Indicators
OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics

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.

Redistribution

Reduction in the Gini coefficient from taxes and transfers

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator · comparable from 2011 only

The Gini before taxes and payments minus the Gini after them, as a share of the first. It shows how much of the inequality produced by the market the government removes. It is built from the before-tax Gini above, so their pair is built from the same numbers and flagged. No "better" direction is set: a country may redistribute little because its market incomes are already equal.

How this was computed

Data used: most recent value in 2010-2025; values come from 2011–2025. 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 Redistribution

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

More links with Employment in agriculture or Redistribution