Stratification & Inequality: Measuring Who Gets What

Line up every adult on Earth by income, poorest at the left and richest at the right. The World Inequality Report 2022 did exactly that with data for 2021 and found that the poorest half of humanity received about 8.5% of the world's income, while the richest tenth received about 52%. The same line-up for wealth is starker still: the bottom half owned about 2%, the top tenth about 76%.

Those two sentences are the whole subject in miniature. They are a measurement: someone had to decide what counts as income, which people to count, and how to compare a Brazilian real with an Indian rupee. They are also a starting point for argument, because people who agree on every digit still disagree about whether such a line-up is a problem, whose fault it is, and what to do. This piece teaches the measuring, and keeps the arguing clearly labelled as arguing.

Throughout, the figures carry their year and source. Survey-based inequality statistics are not interchangeable across countries, and the biggest mistake a newcomer makes is to read a table of Gini numbers as if every row were measured the same way.

The Lorenz curve and the Gini: one number for a whole shape

Picture the population lined up from poorest to richest. Now plot, for each point along that line, the share of all income held by everyone up to that point. At the left, almost nothing; at the right, 100%. If everyone had the same income the plot would be a straight diagonal. Real societies sag below it. That sagging curve is the Lorenz curve, drawn by the American statistician Max Lorenz in 1905.

The Italian statistician Corrado Gini turned the sag into one number in 1912. The Gini coefficient is the area between the diagonal and the Lorenz curve, divided by the whole triangle under the diagonal. Zero means perfect equality; one means one person holds everything. A Gini of 0.30 is not "30% unequal"; it is a way of saying how far the curve bows.

The tool below builds a Lorenz curve from four real-looking points: what the poorest fifth gets, what the richest fifth gets, and what the richest tenth gets. Pick a country preset or drag the sliders yourself. The page computes the curve's Gini from those points; a real national figure uses the whole survey, so the two differ a little.

Without JavaScript: the US in 2024 (World Bank) had a Gini of 41.8, with the poorest fifth receiving 5.1% of income or consumption and the richest fifth 47.1%. Slovenia in 2023 had 24.7, with 10.0% and 34.8%.

Two warnings travel with every Gini. First, it is blind to where on the curve the inequality sits: very different distributions can share the same value. Second, what is being measured matters as much as the arithmetic. Income before or after taxes and transfers, household or per person, income or consumption: each choice moves the number.

What the Gini hides: tops, bottoms and the shape between

A country can have the same Gini as another and a very different top. This is why researchers also report shares: how much goes to the bottom tenth or fifth, and how much to the top tenth or one per cent. José Gabriel Palma's ratio, the top tenth's share divided by the bottom forty per cent's, was proposed because he found that the middle half of most distributions looks surprisingly alike and the real differences sit in the tails.

Surveys have a second problem: the very rich rarely answer them, and when they do they under-report. Researchers at the World Inequality Database (Thomas Piketty, Emmanuel Saez, Gabriel Zucman and colleagues) therefore combine surveys with tax records and national accounts to estimate the top. Their figures for the top are higher than survey-only figures, and the two approaches are an active methodological dispute, not a settled matter. For India, the World Bank's 2023 survey-based Gini of 23.0 is built on consumption, which is much more equal than income; the WID estimates that the top 10% held about 56% of national income in 2014 (Chancel and Piketty, 2019). Both numbers are "right" about different things.

Explore a dozen countries below. Switch the measure and see how the order changes.

Without JavaScript: Gini 54.1 (South Africa, 2022), 50.3 (Brazil, 2024), 41.8 (US, 2024), 33.7 (Germany, 2022), 24.7 (Slovenia, 2023).

Income is one thing, wealth is another

Income is a flow: wages, profits, benefits arriving over a year. Wealth is a stock: houses, savings, shares, pensions, minus debts. Wealth is always more concentrated than income, because it accumulates, it is inherited, and people with spare income can buy assets that grow. Households with big mortgages can have negative net wealth while earning a decent salary, which is why the bottom half's wealth share is near zero.

Without JavaScript: global income 2021, top 10% about 52%, bottom 50% about 8.5%; global wealth, top 10% about 76%, bottom 50% about 2% (World Inequality Report 2022).

Evidence and argument separate here. The evidence is the distribution. The arguments begin with why: Thomas Piketty's Capital in the Twenty-First Century (2013, English 2014) argued that when the return on capital exceeds economic growth, wealth concentrates. Critics have disputed the data (the Financial Times questioned some of his series in 2014), the law-like claim, and whether returns behave as the theory needs. Defenders replied with revised data and extended series. Economists who study the same figures still disagree on how much comes from technology, trade, taxes, institutions, market power or inheritance.

Mobility: the same ladder seen as a matrix

A snapshot of inequality does not say how people move within it. If a society is very unequal but everyone's children shuffle freely, a lifetime perspective looks fairer than the snapshot. If the same families stay at the same rungs, the snapshot understates the problem. Sociologists measure movement with a mobility matrix: sort families into fifths by income, sort their grown children the same way, and tabulate where children from each parental fifth end up.

Without any movement the matrix would have 100% on the diagonal. If rank were inherited not at all, every cell would show 20%, because each child lands in a random fifth. Real countries sit between. The key parameter is the rank-rank correlation between parents' and children's positions. In Raj Chetty and colleagues' 2014 study of US tax records, it was about 0.34; Chetty et al. also reported that a child born in the bottom fifth had about a 7.5% chance of reaching the top fifth, against 20% under random shuffling. The simple model below, set to 0.34, gives about 8%, close to that observed figure.

Without JavaScript: with a rank correlation of 0.34, a child of the poorest fifth in this model has about an 8% chance of reaching the richest fifth and about 35% of staying in the poorest fifth, against 20% for each under pure shuffling.

What the matrix does not tell you is why. Chetty's team found large differences across US places, and the strongest correlates of upward mobility were less segregation, better schools, more two-parent households, and more social ties across class lines. Those are correlates; sociologists and economists debate how far each is cause. And the matrix measures rank, not welfare: a society where everyone is richer can have the same matrix as a stagnant one.

The Great Gatsby curve, and why it is a clue and not a verdict

Plot countries' inequality against how strongly parental income predicts children's income and you get an upward slope: more unequal countries tend to be less mobile. Alan Krueger named it the Great Gatsby curve in 2012, using Miles Corak's data. Climbing the Ladder (30/04) tells that story and tabulates the numbers; here is what the measurement lens adds.

The curve is built from perhaps a couple of dozen rich countries, with inequality measured years before mobility, and with mobility estimates that depend on how each national study defined income and age. The OECD's 2018 report, A Broken Social Elevator?, reported that families at the bottom tenth needed about two generations to reach average income in Denmark, five in the United Kingdom, seven in China and India, nine in Brazil and eleven in Colombia (as reported by secondary summaries of the OECD figures; the OECD's own average across member countries was about four to five). Those are projections from a simple model, not forecasts.

Caste and class: two ways to lock a ladder

Class is a position you hold; caste is a category you belong to. In the sociological sense, a caste system fixes membership at birth, restricts marriage to within the group (endogamy), links rank to ideas of purity or worth, and in its strict forms limits the occupations open to each group. A class system has none of these formal locks: in principle anyone may move, and the ladder is made of money, schooling and connections. Real societies are mixtures, and every comparison is partial.

Take India, where the evidence is richest. In the 2011 census Scheduled Castes were 16.6% of the population and Scheduled Tribes 8.6%. India has not published a full caste census since 1931; Bihar's state survey (published October 2023) counted about 63% of its people as Other Backward Classes or Extremely Backward Classes and about 19.7% as Scheduled Castes, and in April 2025 the national government announced that caste would be enumerated in the next census. Research on mobility finds both change and persistence. Hnatkovska, Lahiri and Paul (2013) found that gaps in education and wages between Scheduled Castes and Tribes and others narrowed between 1983 and 2005; a correspondence study by Thorat and Attewell (2007) sent matched job applications with names signalling caste or religion and found that employers called back applicants with Dalit or Muslim names less often.

The tool below shows the arithmetic that makes group inequality persist even when within-group variation is huge. It is a pure statistical illustration of how a gap in group averages turns into over- and under-representation at the top and bottom. It does not say what causes any real gap.

Without JavaScript: with a 20% group whose average sits half a standard deviation lower, that group makes up about 32% of the poorest fifth and about 10% of the richest fifth.

Does the quota system answer the problem it addresses? Here the evidence and the positions come apart. Defenders of caste-based reservations argue that exclusion was by group, so remedy must be by group; that representation in universities, government and politics matters in itself; and that Scheduled Caste graduates still face discrimination in hiring. Critics offer several different objections: that class-based criteria would target need better, that a "creamy layer" within backward groups captures the benefits (the Supreme Court's 1992 Indra Sawhney ruling excludes it for OBC quotas and capped reservations at about 50%), or that a merit principle should govern selection. India added a 10% quota for economically weaker sections of the unreserved categories in 2019; the Supreme Court upheld it by a 3 to 2 majority in November 2022. These are arguments about justice, and the data in this section can inform each side without deciding between them.

B. R. Ambedkar's Annihilation of Caste (1936, written for a conference that cancelled his speech) argued that caste could not be treated as a mere economic layer, because it divides labourers from one another and is sustained by belief; many Marxist writers in India held that class struggle was primary and caste a form of it. The disagreement is still live in the field: is caste a status order, a class order, or both?

Measuring is not deciding

The facts above are compatible with several philosophies of what, if anything, to do. A graduate keeps them separate and can state each one fairly:

Each position has serious critics, and each looks at different statistics. A top-share figure speaks most to the egalitarian; a poverty line to the sufficientarian; a mobility matrix to the meritocrat. When a speaker moves from "the gap is X" to "so we must Y" without saying which philosophy carries the step, the second part is not a finding.

What a graduate just sees

• A Gini is one number for a whole curve; two countries can share it and differ at the top or the bottom.
• Before comparing two inequality figures, ask: income or consumption, before or after tax, household or person, which year, which survey.
• Surveys miss the very rich; tax-based estimates of top shares are higher, and that method dispute is real.
• Wealth is much more concentrated than income, worldwide: about 76% of it sits with the top tenth, against about 52% of income (2021).
• Mobility is a matrix, not a slogan: ask where children of the poorest fifth end up, and compare that with 20% under pure shuffling.
• A gap between group averages produces big gaps in the tails, even with huge overlap.
• Caste and class overlap but differ: one is a category fixed at birth and marriage, the other a position.
• "The gap is this" and "so we should do that" are different sentences, and the second always needs a value premise.

Where it shows up next

• Race, Ethnicity & Migration (35/79): the group gaps here are measured with categories that were themselves made, which is the next piece's subject.
• Public Policy (35/16) and Political Economy (35/17): tax and transfer design, minimum wages and affirmative action all come from this evidence plus a value judgement.
• Statistics (34/05): the survey weights, confidence intervals and rank correlation behind every table above.
• In the world: the World Bank's inequality tables, the OECD's Society at a Glance, an economist's wealth-tax proposal, an Indian court case on quotas.

If you want to go deeper

• 📘 Textbook. David Grusky (ed.), Social Stratification: Class, Race, and Gender in Sociological Perspective (Routledge/Westview, several editions), the standard reader; and the free OpenStax Introduction to Sociology (3rd ed.), chapters on global and US stratification.
• 📘 Textbook for the numbers. Anthony Atkinson, Inequality: What Can Be Done? (Harvard University Press, 2015), a careful economist's account with proposals clearly marked as proposals.
• 📘 Gentler. Branko Milanovic, Global Inequality: A New Approach for the Age of Globalization (Harvard University Press, 2016), which explains the elephant chart and the world's income ladder.
• 🌐 Free data. World Inequality Database, Our World in Data on economic inequality, and Opportunity Insights for US mobility atlases.
• 🌐 Free course. MIT OpenCourseWare 14.74 Foundations of Development Policy (Spring 2009) for how poverty and inequality are measured in developing countries.