15.4 Income Inequality: Measurement and Causes

Income Inequality: Measurement and Causes

Income inequality describes how unevenly total income is distributed across households in an economy. Understanding how to measure this gap and what drives it is central to evaluating poverty, policy trade-offs, and economic well-being.

Income Distribution

Income distribution refers to how a nation's total income is divided among its households. In the U.S., the top 20% of earners consistently receive roughly half of all income, while the bottom 20% receive only about 3-4%.

Several forces shape this distribution:

• Differences in education and skills. Higher-skilled workers (doctors, software engineers) command higher wages because their labor is scarcer and more productive. Workers in low-skill roles (retail, food service) face more competition and earn less.
• Technological change. Automation and AI increase demand for workers who can design, manage, or work alongside new technology. At the same time, these advances can eliminate low-skill jobs entirely, widening the wage gap.
• Family structure. Single-parent households rely on one income source, which often places them in lower income brackets. Meanwhile, assortative mating (the tendency of high earners to marry other high earners) concentrates wealth at the top. A household with two professionals earning $80,000 each looks very different from a single-parent household earning $30,000.
• Globalization. Outsourcing of manufacturing and service jobs to countries with lower labor costs (China, India) increases competition for low-skill workers in developed economies and pushes their wages down.
• Decline in unionization. Unions historically used collective bargaining to negotiate higher wages and benefits for workers, especially in manufacturing and service industries. As union membership has fallen, low-skill workers have lost bargaining power, contributing to slower wage growth at the bottom of the distribution.

Measuring Inequality

Economists use three main tools to measure how unequal a distribution of income is.

Quintile Data

Quintile analysis divides the population into five equal groups (each 20%) ranked from lowest to highest income. You then compare what share of total income each group receives. If income were perfectly equal, each quintile would earn exactly 20%. In reality, the top quintile in the U.S. earns around 50% of total income, while the bottom quintile earns roughly 3-4%. The bigger the gap between quintiles, the greater the inequality.

The Lorenz Curve

The Lorenz curve is a graph that plots cumulative percentage of the population (x-axis) against cumulative percentage of income earned (y-axis).

• The Line of Equality is a 45-degree diagonal line representing perfect equality: 10% of the population earns 10% of income, 50% earns 50%, and so on.
• The Lorenz curve bows below this line. The further it bows away, the more unequal the distribution. For example, if the bottom 10% of the population earns only 2% of total income, the curve starts well below the diagonal.

The Gini Coefficient

The Gini coefficient converts the Lorenz curve into a single number between 0 and 1.

$Gini = \frac{\text{Area between the Lorenz curve and the Line of Equality}}{\text{Total area under the Line of Equality}}$

• A Gini of 0 means perfect equality (everyone earns the same).
• A Gini of 1 means perfect inequality (one person earns everything).
• The U.S. Gini coefficient is roughly 0.39-0.49 depending on the measure used, which is relatively high among developed nations.

The larger the gap between the Lorenz curve and the Line of Equality, the higher the Gini coefficient.

Contributing Factors to Rising Inequality

Two broad trends have driven income inequality higher in recent decades: changes in household composition and shifts in wage distribution.

Changes in Household Composition

1. The rise in single-parent households has pushed more families into lower income quintiles, since these households depend on a single earner.
2. Smaller average household sizes mean fewer potential earners per household and less ability to share fixed costs like housing and utilities.
3. Assortative mating amplifies inequality at the top, as dual-income professional couples pull further ahead.

Shifts in Wage Distribution

1. Skill-biased technological change increases demand (and pay) for high-skill workers like programmers and data analysts, while wages for low-skill workers stagnate or decline.
2. Labor market polarization describes the growth of both high-wage, high-skill jobs (tech, finance) and low-wage, low-skill jobs (food service, home health aides), with a simultaneous decline in middle-skill, middle-wage jobs (manufacturing, clerical work). This "hollowing out" of the middle class pushes households toward the upper or lower ends of the distribution.
3. Globalization intensifies competition for low-skill workers in developed economies. When firms can hire workers abroad at lower wages, domestic workers in those roles face downward pressure on pay.

These factors reinforce each other. Technology and globalization both reduce demand for middle-skill labor, while changes in family structure make it harder for lower-income households to climb into higher quintiles.