Learning Objectives

• Explain the distribution of income, and analyze the sources of income inequality in a market economy
• Measure income distribution in quintiles
• Calculate and graph a Lorenz curve
• Show income inequality through demand and supply diagrams

Measuring Income Distribution by Quintiles

One common way of measuring income inequality is to rank all households by income, from lowest to highest, and then to divide all households into five groups with equal numbers of people, known as quintiles. This calculation allows for measuring the distribution of income among the five groups compared to the total. The first quintile is the lowest fifth (or 20 percent), the second quintile is the next lowest, and so on. Income inequality can be measured by comparing what share of the total income is earned by each quintile.

U.S. income distribution by quintile appears in Table 14.5. In 2013, for example, the bottom quintile of the income distribution received 3.2 percent of income; the second quintile received 8.4 percent; the third quintile, 14.4 percent; the fourth quintile, 23.0 percent; and the top quintile, 51.0 percent. The final column of Table 14.5 shows what share of income went to households in the top five percent of the income distribution: 22.3 percent in 2011. Over time, from the late 1960s to the early 1980s, the top fifth of the income distribution typically received between about 43 percent and 45 percent of all income. The share of income that the top fifth received then begins to rise. According to the Census Bureau, much of this increase in the share of income going to the top fifth can be traced to an increase in the share of income going to the top five percent. The quintile measure shows how income inequality has increased in recent decades.

It can also be useful to divide the income distribution in ways other than quintiles; for example, into tenths or even into percentiles (that is, hundredths). A more detailed breakdown can provide additional insights. For example, the last column of Table 14.5 shows the income received by the top five percent of the income distribution. Between 1980 and 2013, the share of income going to the top five percent increased by 5.7 percentage points (from 16.5 percent in 1980 to 22.2 percent in 2013). From 1980 to 2013 the share of income going to the top quintile increased by 7.0 percentage points (from 44.1 percent in 1980 to 51.0 percent in 2013). Thus, the top 20 percent of households (the fifth quintile) received over half (51 percent) of all the income in the United States in 2013.

Lorenz Curve

The data on income inequality can be presented in various ways. For example, you could draw a bar graph that showed the share of income going to each fifth of the income distribution. Figure 14.8 presents an alternative way of showing inequality data in what is called a Lorenz curve. The Lorenz curve shows the cumulative share of population on the horizontal axis and the cumulative percentage of total income received on the vertical axis.

Figure 14.8 The Lorenz Curve A Lorenz curve graphs the cumulative shares of income received by everyone up to a certain quintile. The income distribution in 1980 was closer to the perfect equality line than the income distribution in 2011—that is, the U.S. income distribution became more unequal over time.

Every Lorenz curve diagram begins with a line sloping up at a 45-degree angle, shown as a dashed line in Figure 14.8. The points along this line show what perfect equality of the income distribution looks like. It would mean, for example, that the bottom 20 percent of the income distribution receives 20 percent of the total income, the bottom 40 percent gets 40 percent of total income, and so on. The other lines reflect actual U.S. data on inequality for 1980 and 2011.

The trick in graphing a Lorenz curve is that you must change the shares of income for each specific quintile, which are shown in the first column of numbers in Table 14.6, into cumulative income, shown in the second column of numbers. For example, the bottom 40 percent of the cumulative income distribution will be the sum of the first and second quintiles; the bottom 60 percent of the cumulative income distribution will be the sum of the first, second, and third quintiles, and so on. The final entry in the cumulative income column needs to be 100 percent, because by definition, 100 percent of the population receives 100 percent of the income.

In a Lorenz curve diagram, a more unequal distribution of income will loop farther down and away from the 45-degree line, while a more equal distribution of income will move the line closer to the 45-degree line. The greater inequality of the U.S. income distribution between 1980 and 2013 is illustrated in Figure 14.8 because the Lorenz curve for 2013 is farther from the 45-degree line than the Lorenz curve for 1980. The Lorenz curve is a useful way of presenting the quintile data that provides an image of all the quintile data at once. The next Clear It Up feature shows how income inequality differs in various countries compared to the United States.

Another way to show income inequality is the Gini coefficient. It was developed by the Italian statistician, demographer, and sociologist Corrado Gini. Much like the Lorenz curve, it represents the extent to which total income is distributed (or dispersed) across the population. In a country with perfect income inequality (in other words, where one person receives all the income), the Gini coefficient would equal one. In the other extreme, where each percentage of the population receives the equivalent share of income (the bottom 10 percent receives 10 percent, the bottom 20 percent receives 20 percent, and so on), the Gini coefficient would equal zero. Thus, a higher Gini coefficient represents a more unequal distribution of income. The Gini coefficient relates directly to the Lorenz curve. On a Lorenz curve graph, the area between the dashed line that represents perfect income equality and the actual Lorenz curve is the Gini coefficient. The Gini coefficient is often used to compare income inequality across countries. For example, in 2014, the United States had a Gini coefficient of 0.41, whereas Canada had a Gini coefficient of 0.34, and Mexico had a Gini coefficient of 0.48.

Link It Up

Visit this website to watch a video of wealth inequality across the world.

Causes of Growing Inequality: The Changing Composition of American Households

In 1970, 41 percent of married women were in the labor force, but by 2015, according to the Bureau of Labor Statistics (2013), 56.7 percent of married women were in the labor force. One result of this trend is that more households have two earners. Moreover, it has become more common for one high earner to marry another high earner. A few decades ago, the common pattern featured a man with relatively high earnings, such as an executive or a doctor, marrying a woman who did not earn as much, like a secretary or a nurse. Often, the woman would leave paid employment, at least for a few years, to raise a family. However, now doctors are marrying doctors and executives are marrying executives, and mothers with high-powered careers are often returning to work while their children are quite young. This pattern of households with two high-income earners tends to increase the proportion of high-earning households.

According to data from 2013 in the National Journal (2012), even as two-income-earner couples have increased, so have single-parent households. Of all U.S. families, 13.1 percent were headed by single mothers; the poverty rate among single-parent households tends to be relatively high.

These changes in family structure, including the growth of single-parent families who tend to be at the lower end of the income distribution, and the growth of two-income-career high-earner couples near the top end of the income distribution, account for roughly half of the rise in income inequality across households in recent decades.

Link It Up

Visit this website to watch a video that helps explain wealth inequality in the United States.

Causes of Growing Inequality: A Shift in the Distribution of Wages

Another factor behind the rise in U.S. income inequality is that earnings have become less equal since the late 1970s. In particular, the earnings of high-skilled labor relative to low-skilled labor have increased. The causes of this are varied, complex, and open to plenty of debate. One argument is that these so-called winner-take-all labor markets result from changes in technology, which have increased global demand for workers that labor economists call super-stars—the most skilled, talented, and/or educated CEO, doctor, basketball player, actor, and so on. This labor market theory argues that in order to incentivize the very best performance out of the very best workers, these workers need to be paid more than other workers with the same characteristics. When this is combined with a growing global demand for their skills and talent, their resulting salaries are pushed by market forces above productivity differences versus educational differences.

This global demand pushes salaries far above productivity differences versus educational differences. One way to measure this change is to take the earnings of workers with at least a four-year college bachelor’s degree (including those who went on and completed an advanced degree) and divide them by the earnings of workers with only a high school degree. The result is that those in the 25–34 age bracket with college degrees earned about 1.67 times as much as high school graduates in 2010, up from 1.59 times in 1995, according to U.S. Census data. Winner-take-all labor market theory argues that the salary gap between the median and the top one percent is not due to educational differences.

Economists use the supply and demand model to reason through the most likely causes of this shift. According to the National Center for Education Statistics, in recent decades, the supply of U.S. workers with college degrees has increased substantially; for example, 840,000 four-year bachelor’s degrees were conferred on Americans in 1970; in 2009–2010, 1,602,480 such degrees were conferred—an increase of about 90 percent. In Figure 14.9, this shift in supply to the right, from S₀ to S₁, should result in a lower equilibrium wage for high-skilled labor. Thus, the increase in the price of high-skilled labor must be explained by a greater demand, as in the movement from D₀ to D₁. Evidently, combining both the increase in supply and in demand has resulted in a shift from E₀ to E₁, and a resulting higher wage.

Figure 14.9 Why Would Wages Rise for High-Skilled Labor? The proportion of workers attending college has increased in recent decades, so the supply curve for high-skilled labor has shifted to the right, from S₀ to S₁. If the demand for high-skilled labor had remained at D₀, then this shift in supply would have led to lower wages for high-skilled labor. However, the wages for high-skilled labor, especially if there is a large global demand, have increased, even with the shift in supply to the right. The explanation must lie in a shift to the right in demand for high-skilled labor, from D₀ to D₁. The figure shows how a combination of the shift in supply, from S₀ to S₁, and the shift in demand, from D₀ to D₁, led to both an increase in the quantity of high-skilled labor hired and also to a rise in the wage for such labor, from W₀ to W₁.

What factors would cause the demand for high-skilled labor to rise? The most plausible explanation is that while the explosion in new information and communications technologies over the last several decades has helped many workers to become more productive, the benefits have been especially great for high-skilled workers such as top business managers, consultants, and design professionals. The new technologies have also helped to encourage globalization, the remarkable increase in international trade over the last few decades, by making it more possible to learn about and coordinate economic interactions all around the world. In turn, the rising impact of foreign trade in the U.S. economy has opened up greater opportunities for high-skilled workers to sell their services around the world. And, lower-skilled workers have to compete with a larger supply of similarly skilled workers around the globe.

The market for high-skilled labor can be viewed as a race between forces of supply and demand. Additional education and on-the-job training will tend to increase the supply of high-skilled labor and to hold down its relative wage. Conversely, new technology and other economic trends such as globalization tend to increase the demand for high-skilled labor and push up its relative wage. The greater inequality of wages can be viewed as a sign that demand for skilled labor is increasing faster than supply. On the other hand, if the supply of lower-skilled workers exceeds the demand, then average wages in the lower quintiles of the income distribution will decrease. The combination of forces in the high-skilled and low-skilled labor markets leads to increased income disparity.