Foundationsdevelopment
Inequality: Measuring the Gaps Between Rich and Poor
Overview
Inequality — how unevenly income and wealth are distributed — shapes politics, health, growth, and social stability. It has risen in most rich countries since 1980 while falling between countries (as Asia caught up). This lesson teaches the measurement toolkit (Gini coefficient, top income shares, Palma ratio), the facts about where inequality is highest and lowest, the drivers (technology, globalization, policy, institutions), and the debate over whether and how much it matters for growth and welfare.
Learning objectives
- Define and compute inequality measures: Gini, top shares, Palma
- Distinguish inequality within vs. between countries
- Describe global inequality trends since 1980
- Explain the drivers: skill-biased tech, globalization, policy
- Evaluate the inequality-growth debate
How inequality is measured
The Gini coefficient (0 = perfect equality, 1 = one person has everything) is the standard summary: Nordics ~0.27, the US ~0.41, South Africa ~0.63 (world's highest). But Gini hides shape — so economists add top income shares (the top 1%'s share doubled in the US since 1980 to ~20%), the Palma ratio (top 10% share ÷ bottom 40% share — stable and intuitive), and wealth Ginis (far higher than income: US wealth Gini ~0.85). Percentile ratios (P90/P10) show gaps directly. Each measure answers a different question; serious analysis uses several.
Wealth is always more unequal than income — it accumulates across generations. The top 10% own ~70% of US wealth but earn ~45% of income.
The great facts: within vs. between
Two stories diverge. Between-country inequality fell dramatically as China, India, and others converged toward rich-country incomes — the main driver of falling global inequality since 1990. Within-country inequality rose in most advanced economies (US, UK, Germany) and many emerging ones (China, India), driven by skill premiums, capital's rising share, and policy shifts. Net effect: global inequality (all humans ranked together) declined — Milanovic's 'elephant curve' shows the global middle (Asian workers) gaining hugely while rich-country working classes stagnated. The politics of inequality is mostly about the within-country rise.
Branko Milanovic's chart of 1988–2008 income growth by global percentile: a trunk (top 1% soaring), a body (Asian middle rising), and a trough (rich-country lower-middle stagnating) — the defining image of modern inequality.
What drives inequality
Four forces dominate. Skill-biased technological change: computers complement educated workers and substitute routine ones, widening the college premium. Globalization: trade and offshoring pressure low-skill wages in rich countries (Stolper-Samuelson) while creating new elites in emerging markets. Institutions and policy: union decline, minimum-wage erosion, tax cuts for top earners, and deregulation all pushed US inequality up — the same technology produced far less inequality in Scandinavia. And capital dynamics: Piketty's r > g — when returns on capital exceed growth, wealth concentrates across generations absent shocks or redistribution.
Inequality's drivers interact and vary by country. monocausal stories (just technology, just globalization) fail — the US-Nordic contrast with similar technology proves policy matters.
Does inequality hurt growth?
The evidence is nuanced. Extreme inequality can harm growth: credit constraints block poor children's education (talent wasted), elites capture policy, and instability deters investment — IMF research finds lower inequality robustly correlates with longer growth spells. But the relationship isn't linear: some inequality incentivizes effort and investment, and redistribution can itself distort. The emerging consensus: inequality of opportunity (unequal starting lines) is clearly damaging; inequality of outcomes is debated. What matters most for welfare may be absolute poverty and mobility, not the Gini per se — though high inequality corrodes both.
A society with high outcome inequality but high mobility (rags-to-riches common) differs profoundly from one where birth determines fate. Measure both.
Policies that reduce inequality
The toolkit: progressive taxation (income, wealth, inheritance — with real administrative challenges), transfers (the single biggest equalizer in Nordics — pensions, child benefits, unemployment insurance), education (the long-run leveler, though slow), minimum wages and labor protections (modest, well-evidenced effects), and predistribution (antitrust, corporate governance, union rights — shaping market incomes before taxes). Developing countries add land reform and rural investment. The Nordic model shows high equality coexists with prosperity — but it requires state capacity and trust that can't simply be copied. The lesson: inequality is substantially a policy choice, within institutional constraints.
Key points
- Inequality is measured by Gini, top shares, Palma ratio — and wealth is far more unequal than income.
- Between-country inequality fell (Asian convergence); within-country inequality rose in most rich nations.
- Drivers: skill-biased tech, globalization, weakened labor institutions, tax policy, r > g dynamics.
- Extreme inequality likely harms growth via wasted talent and instability; opportunity inequality is clearly damaging.
- Policy — progressive taxes, transfers, education, labor institutions — substantially shapes outcomes.
Common misconceptions
✓ Truth: The Nordics combine low inequality with high prosperity, and IMF evidence links lower inequality to more durable growth. The trade-off is far weaker than claimed — design matters more than destiny.
✓ Truth: It raised within-country inequality in rich nations but slashed between-country inequality — the net effect on global inequality is a decline. Both facts are true simultaneously.
✓ Truth: Same Gini can hide very different shapes (top-heavy vs. bottom-heavy). Always supplement with top shares, percentile ratios, and wealth data.
Practice questions
Q1. The Gini coefficient of 0.63 (South Africa) versus 0.27 (Norway) indicates:
- South Africa is 63% poorer
- South Africa's income distribution is far more unequal
- Norway has no poor people
- Ginis can't be compared
Gini measures inequality of distribution (0 = perfect equality, 1 = maximum). Higher means more unequal — it says nothing direct about average income levels.
Q2. Milanovic's 'elephant curve' showed 1988–2008 income growth was highest for:
- The global top 1% and the emerging Asian middle classes
- Rich-country working classes
- Sub-Saharan farmers
- European pensioners
The curve's trunk (top 1% soaring) and body (Asian middle rising) contrast with the trough — rich-country lower-middle classes whose incomes stagnated.
Q3. IMF research on inequality and growth notably found that:
- Inequality always boosts growth
- Lower inequality is robustly correlated with longer sustained growth spells
- Redistribution never matters
- Gini is meaningless
Ostry, Berg, and Tsangarides (2014): lower net inequality predicts longer growth episodes, and redistribution is generally not harmful to growth — challenging the equity-efficiency trade-off.
Click a question to reveal the answer and explanation.
Frequently asked questions
Why is South Africa the world's most unequal country?
Apartheid's legacy: racially skewed land, education, and capital ownership persist, overlaid with high unemployment and a skills mismatch. Post-1994 policies reduced poverty but barely dented the Gini (~0.63).
What is Piketty's r > g argument?
When the return on capital (r) persistently exceeds economic growth (g), wealth compounds faster than wages, concentrating fortunes across generations. Piketty argues this is capitalism's normal tendency, checked historically by wars, inflation, and progressive taxation.
How does the US compare on inequality?
Highest among rich democracies: Gini ~0.41 (vs. ~0.30 EU average), top 1% taking ~20% of income, and the lowest intergenerational mobility in the Nordics-comparison set — the 'Great Gatsby curve' link.
Can inequality be too low?
Theoretically, zero inequality would destroy incentives — but no real economy is near that bound. The practical debate is about the range from Nordic (~0.27) to US (~0.41) levels, where evidence favors the lower end for growth durability.