15.4Income Inequality: Measurement and Causes
those enrolled, almost half are children. Healthcare expenditures, however, are highest for the elderly population, which comprises approximately 25% of participants. As (a) indicates, the largest number of households that enroll in are those with children. Lower- adults are the next largest group enrolled in at 38%. People who are blind or have a disability account for 15% of those enrolled, and seniors are 8% of those enrolled. (b) shows how much actual dollars the government spends for each group. Out of total spending, the government spends more on seniors (20%) and people who are blind or have a disability (44%). Thus, 64% of all spending goes to seniors, those who are blind, and people with disabilities. Children receive 21% of all spending, followed by adults at 15%.
FIGURE 15.7Medicaid Enrollment and SpendingPart (a) shows the enrollment by different populations, with children comprising the largest percentage at 47%, followed by adults at 28%, and those who are blind or have a disability at 16%. Part (b) shows that spending is principally for those who are blind or have a disability, followed by the elderly. Although children are the largest population that covers, expenditures on children are only at 19%.
15.4 Income Inequality: Measurement and Causes
LEARNING OBJECTIVES By the end of this section, you will be able to:
- Explain the distribution of , and analyze the sources of in a
- Measure distribution in quintiles
- Calculate and graph a
- Show through and supply diagrams
levels can be subjective based on the overall levels of a country. Typically a government measures based on a percentage of the median . , however, has to do with the distribution of that , in terms of which group receives the most or the least . involves comparing those with high incomes, middle incomes, and low incomes—not just looking at those below or near the . In turn, measuring means dividing the population into various groups and then comparing the groups, a task that we can be carry out in several ways, as the next Clear It Up feature shows. CLEAR IT UP How do you separate and ? Poverty can change even when inequality does not move at all. Imagine a situation in which income for everyone in the population declines by 10%. Poverty would rise, since a greater share of the population would now fall below the poverty line. However, inequality would be the same, because everyone suffered the same proportional loss. Conversely, a general rise in income levels over time would keep inequality the same, but reduce poverty. It is also possible for income inequality to change without affecting the poverty rate. Imagine a situation in which a large number of people who already have high incomes increase their incomes by even more. Inequality would rise as a result—but the number of people below the poverty line would remain unchanged. Why did inequality of household income increase in the United States in recent decades? A trend toward greater income inequality has occurred in many countries around the world, although the effect has been more powerful in the U.S. economy. Economists have focused their explanations for the increasing inequality on two factors that changed more or less continually from the 1970s into the 2000s. One set of explanations focuses on the changing shape of American households. The other focuses on greater inequality of wages, what some economists call “winner take all” labor markets. We will begin with how we measure inequality, and then consider the explanations for growing inequality in the United States.
Measuring Income Distribution by Quintiles
One common way of measuring is to rank all households by , 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 among the five groups compared to the total. The first is the lowest fifth or 20%, the second is the next lowest, and so on. We can measure by comparing what share of the total each earns. U.S. distribution by appears in . In 2020, for example, the bottom of the distribution received 3.2% of ; the second received 8.1%; the third , 14.0%; the fourth , 22.6%; and the top , 52.2%. The final column of shows what share of went to households in the top 5% of the distribution: 23.0% in 2020. Over time, from the late 1960s to the early 1980s, the top fifth of the distribution typically received between about 43% to 44% of all . The share of that the top fifth received then begins to rise. Census Bureau researchers trace, much of this increase in the share of going to the top fifth to an increase in the share of going to the top 5%. The measure shows how has increased in recent decades. Year Lowest Second Third Fourth Quintile Highest Quintile Top 5% 1967 4.0 10.8 17.3 24.2 43.6 17.2 1970 4.1 10.8 17.4 24.5 43.3 16.6 1975 4.3 10.4 17.0 24.7 43.6 16.5 1980 4.2 10.2 16.8 24.7 44.1 16.5 1985 3.9 9.8 16.2 24.4 45.6 17.6 1990 3.8 9.6 15.9 24.0 46.6 18.5 1995 3.7 9.1 15.2 23.3 48.7 21.0 2000 3.6 8.9 14.8 23.0 49.8 22.1 TABLE 15.5Share of Aggregate Income Received by Each Fifth and Top 5% of Households, 1967–2020 (Source: U.S. Census Bureau, https://www.census.gov/data/tables/time-series/demo/income-poverty/ historical-income-households.html, Table H-1, All Races.) Year Lowest Quintile Second Quintile Third Quintile Fourth Quintile Highest Quintile Top 5% 2005 3.4 8.6 14.6 23.0 50.4 22.2 2010 3.3 8.5 14.6 23.4 50.3 21.3 2015 3.1 8.2 14.3 23.2 51.1 22.1 2020 3.0 8.1 14.0 22.6 52.2 23.0 TABLE 15.5Share of Aggregate Income Received by Each Fifth and Top 5% of Households, 1967–2020 (Source: U.S. Census Bureau, https://www.census.gov/data/tables/time-series/demo/income-poverty/ historical-income-households.html, Table H-1, All Races.) 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 shows the received by the top 5% of the distribution. Between 1980 and 2020, the share of going to the top 5% increased by 6.5 percentage points (from 16.5% in 1980 to 23.0% in 2020). From 1980 to 2020 the share of going to the top increased by 8.1 percentage points (from 44.1% in 1980 to 52.2% in 2013). Thus, the top 20% of householders (the fifth ) received over half (51%) of all the in the United States in 2020.
Lorenz Curve
We can present the data on in various ways. For example, you could draw a bar graph that showed the share of going to each fifth of the distribution. presents an alternative way of showing inequality data in a . This curve shows the cumulative share of population on the horizontal axis and the cumulative percentage of total received on the vertical axis.
FIGURE 15.8The Lorenz CurveA graphs the cumulative shares of received by everyone up to a certain . The distribution in 1980 was closer to the perfect equality line than the distribution in 2020—that is, the U.S. distribution became more unequal over time. Every diagram begins with a line sloping up at a 45-degree angle. We show it as a dashed line in . The points along this line show what perfect equality of the distribution looks like. It would mean, for example, that the bottom 20% of the distribution receives 20% of the total , the bottom 40% gets 40% of total , and so on. The other lines reflect actual U.S. data on inequality for 1980 and 2020. The trick in graphing a is that you must change the shares of for each specific , which we show in the first and third columns of numbers in , into cumulative , which we show in the second and fourth columns of numbers. For example, the bottom 40% of the cumulative distribution will be the sum of the first and second quintiles; the bottom 60% of the cumulative distribution will be the sum of the first, second, and third quintiles, and so on. The final in the cumulative column needs to be 100%, because by definition, 100% of the population receives 100% of the . Category Share of Cumulative Share of Share of Cumulative Share of in 1980 (%) in 1980 (%) in 2020 (%) in 2020 (%) First 4.2 4.2 3.0 3.0 Second quintile 10.2 14.4 8.1 11.1 Third quintile 16.8 31.2 14.0 25.1 Fourth quintile 24.7 55.9 22.6 47.7 Fifth quintile 44.1 100.0 52.2 100.0 TABLE 15.6Calculating the Lorenz Curve 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. illustrates the greater inequality of the U.S. distribution between 1980 and 2020 because the for 2020 is farther from the 45-degree line than the for 1980. The is a useful way of presenting the data that provides an image of all the data at once. The next Clear It Up feature shows how differs in various countries compared to the United States. CLEAR IT UP How does economic inequality vary around the world? The U.S. economy has a relatively high degree of by global standards. As shows, based on a variety of national surveys for a selection of years in the second decade of this century, the U.S. economy has greater inequality than Germany (along with most Western European countries). The region of the world with the highest level of is Latin America, illustrated in the numbers for Brazil and Mexico. The level of inequality in the United States is higher than in some of the low- countries of the world, like India and Nigeria, as well as in some middle- countries, like China and Russia. Country Survey Year First Second Third Fourth Fifth United States 2020 3.0% 8.1% 14.0% 22.6% 52.2% Germany 2016 7.6% 12.8% 17.1% 22.8% 39.6% Brazil 2019 3.1% 7.4% 12.3% 19.4% 57.8% Mexico 2018 5.4% 9.5% 13.5% 20.0% 51.7% China 2016 6.5% 10.7% 15.3% 22.2% 45.3% India 2011 8.1% 11.7% 15.2% 20.5% 44.4% Russia 2018 7.1% 11.2% 15.2% 21.4% 45.1% Nigeria 2018 7.1% 11.6% 16.2% 22.7% 42.4% TABLE 15.7 Distribution in Select Countries (Source: U.S. data from U.S. Census Bureau Table H-1. Other data from The World Bank and Inequality Data Base, https://datatopics.worldbank.org/world-development- indicators/themes/-and-inequality.html) LINK IT UP Visit this website (https://openstax.org/l/inequality/) to watch a video of inequality across the world.
Causes of Growing Inequality: The Changing Composition of American Households
In 1970, 41% of married women were in the labor force, but by 2019, according to the Bureau of Labor Statistics, 58.6% 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 earners tends to increase the proportion of high-earning households. According to data in the National Journal, even as two-earner couples have increased, so have single-parent households. Of all U.S. families, in 2021, about 23% were headed by single mothers. The among single-parent households tends to be relatively high. These changes in family , including the growth of single-parent families who tend to be at the lower end of the distribution, and the growth of two-career high-earner couples near the top end of the distribution, account for roughly half of the rise in across households in recent decades. LINK IT UP Visit this website (https://openstax.org/l/US_wealth) to watch a video that illustrates the distribution of in the United States.
Causes of Growing Inequality: A Shift in the Distribution of Wages
Another factor behind the rise in U.S. 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. Winner- take-all labor markets result from changes in , which have increased global for “stars,”—whether the best CEO, doctor, basketball player, or actor. This global pushes salaries far above productivity differences associated with educational differences. One way to measure this change is to take workers' earnings with at least a four-year college bachelor’s degree (including those who went on and completed an advanced degree) and divide them by workers' earnings with only a high school degree. The result is that those in the 25–34 age bracket with college degrees earned about 1.85 times as much as high school graduates in 2020, up from 1.59 times in 1995, according to U.S. Census data. Winner-take-all argues that the salary gap between the median and the top 1 percent is not due to educational differences. Economists use the and supply 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 2018–2019, 2.0 million such degrees were conferred—an increase of over 138%. In , this to the right, from S0 to S1, by itself should result in a lower wage for high-skilled labor. Thus, we can explain the increase in the of high-skilled labor by a greater , like the movement from D0 to D1. Evidently, combining both the increase in supply and in has resulted in a shift from E0 to E1, and a resulting higher wage.
FIGURE 15.9Why 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 for high-skilled labor had remained at D0, then this would have led to lower wages for high- skilled labor. However, the wages for high-skilled labor, especially if there is a large global , have increased even with the to the right. The explanation must lie in a shift to the right in for high-skilled labor, from D0 to D1. The figure shows how a combination of the , from S0 to S1, and the , 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 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 like top business managers, consultants, and design professionals. The new technologies have also helped to encourage , 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. We can view the for high-skilled labor as a race between forces of supply and . Additional education and on-the-job training will tend to increase the high-skilled labor supply and to hold down its relative wage. Conversely, new and other economic trends like globalization tend to increase the demand for high-skilled labor and push up its relative wage. We can view the greater inequality of wages as a sign that demand for skilled labor is increasing faster than supply. Alternatively, 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.
15.5 Government Policies to Reduce Income Inequality
LEARNING OBJECTIVES By the end of this section, you will be able to:
- Explain the arguments for and against government intervention in a
- Identify beneficial ways to reduce the economic inequality in a society
- Show the tradeoff between incentives and equality
No society should expect or desire complete equality of at a given point in time, for a number of reasons. First, most workers receive relatively low earnings in their first few jobs, higher earnings as they reach middle age, and then lower earnings after retirement. Thus, a society with people of varying ages will have a certain amount of . Second, people’s preferences and desires differ. Some are willing to work long hours to have for large houses, fast cars and computers, luxury vacations, and the ability to support children and grandchildren. These factors all imply that a snapshot of inequality in a given year does not provide an accurate picture of how people’s incomes rise and fall over time. Even if we expect some degree of economic inequality at any point in time, how much inequality should there be? There is also the difference between and , as the following Clear It Up feature explains. CLEAR IT UP How do you measure versus ? is a flow of received, often measured on a monthly or an annual basis. is the sum of the value of all assets, including in bank accounts, financial investments, a pension fund, and the value of a home. In calculating , one must subtract all debts, such as debt owed on a home mortgage and on credit cards. A retired person, for example, may have relatively little income in a given year, other than a pension or Social Security. However, if that person has saved and invested over time, the person’s accumulated wealth can be quite substantial. In the United States, the wealth distribution is more unequal than the income distribution, because differences in income can accumulate over time to make even larger differences in wealth. However, we can measure the degree of inequality in the wealth distribution with the same tools we use to measure the inequality in the income distribution, like quintile measurements. Once every three years the Federal Reserve Bank publishes the Survey of Consumer Finance which reports a collection of data on wealth. Even if they cannot answer the question of how much inequality is too much, economists can still play an important role in spelling out policy options and tradeoffs. If a society decides to reduce the level of economic
Text from Principles of Microeconomics 3e, OpenStax, licensed CC BY-NC-SA 4.0. Access for free at openstax.org.
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