How Income Inequality Is Measured and Why It Keeps Rising

The Top 1% Now Holds More Wealth Than the Bottom 50% Combined

In 2023, the richest 1% of the global population controlled approximately 43% of all financial assets, while the bottom half of humanity shared just 2%. This concentration is not a sudden development — it has been accelerating for decades, and understanding it requires precise measurement tools that economists have refined over more than a century.

Income inequality refers to the uneven distribution of income across a population. Wealth inequality is a related but distinct concept — it measures accumulated assets minus liabilities. Both are real. Both are rising. And both are measurable.

The Gini Coefficient: One Number to Describe Inequality

The most widely used measure is the Gini coefficient, developed by Italian statistician Corrado Gini in 1912. It ranges from 0 (perfect equality, everyone earns the same) to 1 (perfect inequality, one person earns everything). Most countries score between 0.25 and 0.65.

The Gini is derived from the Lorenz curve — a graphical plot of cumulative income share against cumulative population share. The more the Lorenz curve bows away from the 45-degree line of perfect equality, the higher the Gini.

The Gini is powerful but incomplete. It cannot distinguish whether inequality is concentrated at the top or the bottom, and it is sensitive to changes in the middle of the distribution.

Beyond the Gini: Other Measurement Tools

Economists use several complementary metrics to get a fuller picture.

• Palma Ratio: Compares the income share of the richest 10% to that of the poorest 40%. Named after economist Gabriel Palma, who observed that the middle 50% of a population captures a fairly stable share across countries — inequality really happens at the extremes.
• P90/P10 Ratio: Divides the income of the person at the 90th percentile by the income of the person at the 10th percentile. A ratio of 5 means the near-wealthy earn five times more than the near-poor.
• Top Decile Share: The percentage of total national income captured by the top 10% of earners. In the U.S., this figure crossed 50% in the early 2010s for the first time since the 1920s.
• Wealth-to-Income Ratio: Measures total private wealth relative to annual national income. French economist Thomas Piketty showed this ratio surged across Western nations from roughly 2–3x in 1970 to 5–6x by 2010.

Why Inequality Keeps Rising

No single cause explains rising inequality. Multiple structural forces interact.

Technology and Skill-Biased Change

Automation favors high-skill workers. Routine tasks — assembly, data entry, bookkeeping — are cheaply automated. Non-routine cognitive tasks and manual tasks requiring judgment are harder to automate. This creates a wage premium at the top and depresses wages in the middle, hollowing out the income distribution in a pattern called labor market polarization.

Winner-Take-All Market Dynamics

Digital platforms exhibit strong network effects. The top streaming service, ride-hailing app, or search engine captures most of the market. One software platform can serve a billion users with minimal additional cost. The winner earns vastly more than the second-place competitor — a structure alien to pre-digital economies.

The Returns to Capital vs. Labor

Piketty's central insight: when the return on capital (r) consistently exceeds economic growth (g), wealth naturally concentrates. Capital owners see their assets compound. Wage earners do not. Between 1980 and 2020, corporate profits as a share of GDP rose in most developed economies while the labor share of income fell by 5–10 percentage points.

Erosion of Labor Institutions

Union membership in the U.S. fell from 35% of private-sector workers in 1954 to under 6% by 2023. Collective bargaining compresses wage distributions — its decline correlates strongly with rising top-end income shares across OECD nations.

The Data Sources That Make Measurement Possible

Modern inequality research draws on multiple data streams:

• Household surveys: Capture income and consumption but typically undercount the very wealthy, who are either not sampled or under-report income.
• Administrative tax records: Far more accurate for top incomes. The World Inequality Database (WID.world), built by Piketty, Emmanuel Saez, and Gabriel Zucman, links tax microdata across 100+ countries.
• National accounts: Provide macroeconomic totals against which survey data is benchmarked.
• Forbes-style wealth lists: Useful for billionaire trends but not statistically representative.

The combination of survey and tax data, corrected for under-reporting at the top, typically reveals inequality to be significantly higher than household surveys alone suggest. The U.S. Gini based on survey data alone is about 0.39; corrected estimates incorporating capital gains and offshore wealth push closer to 0.50.

What Inequality Does to an Economy

High inequality is not just an ethical concern. Research links it to slower intergenerational mobility — the "Great Gatsby Curve" shows that countries with higher Gini scores also have lower economic mobility across generations. High inequality correlates with reduced political trust, lower educational attainment among low-income groups, and weaker aggregate demand, since lower-income households spend a higher share of income than wealthy households do.

The IMF and OECD have both published findings that excessive inequality constrains long-run growth — a reversal of the older assumption that inequality incentivizes effort and investment. The debate is not settled, but the evidence for costs is growing.

The Policy Responses That Show Evidence of Working

Redistribution tools vary in effectiveness:

• Progressive income taxation and capital gains taxes reduce after-tax inequality directly.
• Earned income tax credits boost incomes at the bottom without the employment disincentives of some welfare programs.
• Early childhood education programs show some of the highest measured returns of any public investment, reducing skill gaps before they widen.
• Minimum wage increases, when modest and well-timed, raise incomes at the bottom with limited employment effect at the macroeconomic level.

No policy eliminates the underlying forces — technology and globalization continue to reshape labor demand. But the Scandinavian model demonstrates that high-income countries can maintain Gini scores below 0.30 through sustained institutional and policy commitment, even in the presence of the same global economic forces affecting more unequal nations.