Economics Finance
December 16th, 2013 23 Minute Read Report by Diana Furchtgott-Roth

The Myth of Increasing Income Inequality

INTRODUCTION AND SUMMARY
President Obama has called income inequality the “defining challenge of our time,” reflecting the misguided assumption that income inequality in the U.S. has increased in recent years. Populist cries for redistribution as a means to remedy this purported inequality have gained currency in both the press and in the public imagination. This paper, based on an updated original analysis of U.S. Labor Department data, concludes that inequality as measured by per capita spending is no greater today than in it was in the 1980s.

INTRODUCTION AND SUMMARY

President Obama has called income inequality the “defining challenge of our time,” reflecting the misguided assumption that income inequality in the U.S. has increased in recent years. Populist cries for redistribution as a means to remedy this purported inequality have gained currency in both the press and in the public imagination. This paper, based on an updated original analysis of U.S. Labor Department data, concludes that inequality as measured by per capita spending is no greater today than in it was in the 1980s.

Below, I examine in more detail the following topics:

Problems with current measures of inequality

Accounting for changes in demographic patterns over time

Using spending to measure inequality

I conclude that the increase in income inequality has been exaggerated. Published government spending data by income quintile show that the ratio of spending between the top and bottom 20 percent has essentially not changed between 1987 and 2012. In terms of total spending, inequality is at the same level as 1987.

Why do other measures show increasing inequality? First, many studies use measures of income before taxes are paid and before transfers, such as food stamps, Medicaid, and housing allowances. Including these transfers reduces inequality.

Second, many studies do not take into account demographic changes in the composition of households over the past 25 years. These changes include more two-earner households at the top of the income scale and more one-person households at the bottom. Studies that show increasing inequality are capturing these demographic changes.

Third, some of this increase in measured inequality is due to the Tax Reform Act of 1986, which lowered top individual income-tax rates from 50 percent to 28 percent, leading more small businesses to file taxes under individual, rather than corporate, tax schedules (Joint Committee on Taxation, “General Explanation of the Tax Reform Act of 1986” (H.R. 3838, 99th Congress, Public Law 99-514), May 4, 1987). 

A superior measure of well-being that avoids these pitfalls is real spending per person by income quintile. Spending power shows how individuals are doing over time relative to those in other income groups. These data can be calculated from published consumer expenditure data from the government’s Consumer Expenditure Survey. An examination of these data from 1987 through 2012 shows that inequality has not changed.

 

IS INEQUALITY INCREASING?

Ask almost anyone the most important economic facts about income distribution in America, and you are almost certain to hear that income distribution has worsened dramatically over the past generation and over the past decade in particular, with people at the top getting a bigger fraction of total personal income.

But measuring inequality is not simple. The choice of the measure of income, along with the measure of the household unit, substantially influences the results of the inequality measure. Should income be measured before the government removes taxes, or after? Should income include government transfers such as food stamps, Medicare, Medicaid, unemployment benefits, and housing supplements? Furthermore, should wealth measures be included? 

In order to measure inequality, disposable income is the most accurate measure. This is what Americans can spend to make themselves better off. Hence, income should be measured after taxes are paid because households cannot avail themselves of tax revenue for expenditures. Similarly, income should include transfer payments because those are available for spending.

Economists often divide households into income quintiles (fifths) and measure the differences in their incomes. However, the demographic characteristics of these quintiles have been changing over time, so comparisons of quintiles are misleading (U.S. Census Bureau, “Changing American Households,” Annual Social and Economic Supplements, 1960–2013). Quintiles differ in the number of people per household and the number of earners per household. Table 1 shows that in 2012, households in the lowest fifth had an average of 1.7 people, and in half these households there were no earners. The highest fifth, however, had 3.1 persons per household, with 2 earners (U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, September 2013). 

 

 

To show the unexpected nature of the income distribution tables, a higher percentage of Americans in the bottom quintiles own their homes free of mortgage debt than do Americans in upper quintiles. Some 28 percent of households in the lowest-income group and 31 percent in the next-to-lowest group owned their homes without a mortgage in 2012 (U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, September 2013). This is because more seniors are represented in the lower two quintiles, and many have paid off their homes. In the top quintile, 11 percent of households own their homes debt-free, the smallest share of any quintile—a counterintuitive result. 

The lowest-income group contains at least three significant groups of individuals. Some have low incomes because of lack of employment and are searching for jobs or better-paying jobs. A second group comprises elderly people who may have small amounts of retirement income but substantial assets, such as stocks and a home. These individuals are not in the labor force. A third group consists of students or recent graduates whose education levels ensure that they will have a prosperous future. Clearly, the first group is a social problem in need of a solution, but not the other two.

One reason for income inequality is the differing number of earners per household in upper and lower quintiles. Table 2, based on data from the Census Bureau, shows the median income by number of earners in a household from 1990 to 2012. The biggest change has been the size of the contribution of the second earner, reflecting increasing women’s wages in the job market, as young women have invested in their education in preparation for a full-time career.

 

 

In 1990, median income for a family with one earner was about $41,800. In 2012, that median income for that one-earner family rose to about $43,300, a 4 percent difference. But the increase between a family with two earners in 1990 and 2012 was far greater. That family’s income rose from about $71,000 to about $82,600, a 16.5 percent difference, resulting in a measured increase in inequality.

Table 2 shows that if there were more one-earner households, the distribution of income would be far more even.

Another change is the shrinkage in household size at the bottom of the income scale, adding to a false perception of increased inequality. This is due to the increased longevity of today’s seniors and to the higher numbers of divorced people and single- parent households.

Figure 1 shows the increase in the percentage of one-person households between 1960 and 2012. In 1960, 13 percent of households had just one person. By 2011, 27 percent of households, more than double the previous share, had one person.

 

 

One major demographic change, contributing to increased inequality, has been the movement of women into the workforce, beginning in the 1980s. This has resulted in the increased prevalence of two- earner couples and their higher household incomes at the top of the income scale. 

With the increased number of women in the workforce over the past quarter-century, if two individuals get married, they frequently become one household with higher earnings—and the measured distribution of income and wealth in society widens. The higher the earnings of the two singles, the more the distribution of income appears inequitable if they marry.

Accompanying their movement into the workforce, women are postponing marriage, so the number of young single women has risen over time. Before the 1970s, the median age at first marriage for women was under 21 years of age. Since 1970, the median age at first marriage for women has steadily risen, to age 27 in 2012 (U.S. Census Bureau, “Table MS-2. Estimated Median Age at First Marriage, by Sex: 1890 to the Present.” May 2013). This trend reflects the increasing number of women attending college and pursuing career opportunities upon graduation.

Table 3 shows the distribution of American women who are at least 15 years old, by marital status. In 1970, 22.1 percent of women over 15 years old had never been married, and only 4 percent were divorced. By 2012, the percentage of women who have never been married grew to 28.4 percent, and the percentage of divorced women increased to 11 percent. 

The postponement of marriage and the high incidence of divorce have led to an increase in the relative population of young female-headed households, a substantial percentage of which are also susceptible to poverty.

 

 

It is notable that 30 percent of female households without a husband are living in poverty. In contrast, only 7 percent of married couples and 17 percent of male households without a wife are poor (U.S. Census Bureau, “Income, Poverty, and Health Insurance Coverage in the United States: 2012,” Current Population Reports, P60-236, Washington, D.C.: U.S. Government Printing Office, 2013).  

Many female-headed households have children present from earlier marriages or from relationships outside of marriage. In such situations, women are more likely to be the custodial parent. In 2010, 79 percent of the custodial parents were mothers. Moreover, the illegitimacy rate has increased significantly, from 26 births per 1,000 unmarried women of childbearing age in 1970 to a peak of 52 births per 1,000 unmarried women of childbearing age in 2008 (Child Trends Data Bank, 2010). 

Since women live longer than men, there are female-headed households headed by senior citizens. These might have low income, but they are not necessarily poor, since they might have assets such as retirement accounts and real estate. 

Census data in Table 4 show that men and women living alone are most likely to be in the lowest-income quintiles. Some 46 percent of women living alone were in the bottom quintile in 2012, and 72 percent of women living alone were in the bottom two quintiles. Only 3.4 percent of women living alone were in the top quintile. The trends are similar for men. Some 60 percent of men living alone were in the bottom two quintiles, and only 6.8 percent were in the top quintile.

 

 

In contrast, married couples are more likely to be in the top quintiles. Some 32 percent of married couples were in the top quintile, and 58.4 percent were in the top two quintiles. Only 7 percent of married-couple families were in the lowest quintile in 2012. 

Table 5 shows quintiles by the types of households. In the top quintile, 77.5 percent of households are married couples. In the top 5 percent of income earners, 81.4 percent are married couples.

 

 

Census data also tell us that the majority of house-holds in the bottom quintile, 61 percent, have no earners, and less than 5 percent of these households have two earners. Conversely, over three-quarters of households in the top-income quintile have two earners or more.

In 1960, 40 percent of married women with children over the age of six worked, but by 2010, that figure had climbed to 70 percent, according to Department of Labor data. During the past half-century, married women steadily moved into higher-income jobs and professions previously dominated by men. This demographic change has substantial implications for the reported distribution of income because of the way that income distribution is measured.

An analysis of individual tax returns by the Internal Revenue Service shows the increasing number of joint returns with two earners over time. In 1969, 46 percent of joint tax returns had wage and salary income from two earners. By 1999, 60 percent of joint tax returns had income from two earners.

This combination of more dual-income couples and more single households has exacerbated inequality in the economy. Part of this is the now-familiar path of two young people getting some kind of schooling, getting a first job, and then, after a few years, getting married.

Individuals move around quintiles as they age and their careers progress. High school or college graduates will start out in the bottom quintile, and then move into a higher quintile when they get a job. Marriage to someone with a job will result in the perception of more upward mobility, as two household incomes combine into one.

Another factor that can influence measures of inequality is changes in the tax code. The Tax Reform Act of 1986 lowered the top individual tax rate to 28 percent, and the corporate rate to 35 percent (Joint Committee on Taxation, “General Explanation of the Tax Reform Act of 1986” (H.R. 3838, 99th Congress, Public Law 99-514), May 4, 1987). In 1986, the top individual rate was 50 percent, and the top corporate rate was 46 percent, so small businesses would pay tax at a lower rate if they incorporated and filed taxes as corporations With the implementation of the Tax Reform Act of 1986, the top individual tax rate of 28 percent meant that small businesses were often better off filing under the individual tax code. Revenues shifted from the corporate to the individual tax sector. In the late 1980s and 1990s, that made it appear as though people had suddenly become better off and income inequality had worsened. This had not happened; rather, income that had been declared on a corporate return was being declared on the individual return. This makes any comparisons between pre- and post-1986 returns meaningless.

Finally, inequality appears greater because the cost of living varies substantially in different parts of the country. College graduates tend to move to locations with higher costs of housing, food, and services, such as New York, Boston, Washington, D.C., and San Francisco. College students prefer these cities because they have amenities such as museums, theaters, shopping, and restaurants. As more well-educated people move into these locations, they become more attractive.

What this means for the study of inequality is that high incomes are less valuable in high-cost locations. A $200,000 salary goes further in Mobile than in New York, for instance, and if more $200,000 wage earners move to New York, the distribution of income is more unequal.

Low-income individuals spend a higher proportion of their income on food and clothing, and high-income people spend more on services. The price of food and clothing, nondurables, has been rising more slowly than the price of services, which are disproportionately consumed by higher-income individuals.

 

USING SPENDING TO MEASURE INEQUALITY

A more meaningful measure of inequality that avoids changes in tax laws and changes in demography comes from an examination of spending. Spending is an accurate measure of the welfare of different income groups. The Department of Labor publishes data every year on consumer spending, based on income quintiles, or fifths. The latest data are for 2012. This analysis shows that economic inequality has not increased, contrary to what the levelers contend.

Differences in per-person spending from the lowest-income fifth to the highest are not different from 25 years ago. These measures of spending show less inequality than do measures of income.

The Department of Labor data, which are published every year, track spending by income group. Spending is vital because it determines our current standard of living and our confidence in the future. It shows how much purchasing power individual Americans have.

I calculate spending on a per-person basis in order to produce comparable measures. These data are converted into 2012 dollars using the Bureau of Labor Statistics Consumer Price Index for all urban centers. It is important to compute spending on a per-person basis because the number of persons in a household varies by quintile, as can be seen in Table 6. For a given level of income, a family is better off with fewer people.

Table 6 shows that the average annual spending for a household in the lowest quintile in 2012 was $13,032 per person. In contrast, the average spending for a household in the top quintile was $32,054 per person.

On a per-person basis, the new Department of Labor numbers show that in 2012, households in the top fifth of the income distribution spent 2.5 times the amount spent by the bottom quintile, as can be seen in Figure 6. That was about the same as 25 years ago. There is no increase in inequality. In addition, the overall level of inequality is remarkably small. A person moving from the bottom quintile to the top quintile can expect to increase spending by only 146 percent.

On a per-person basis, all income groups spent less in real terms in 2012 than in 2007 because of the recession. Those in the bottom group spent 2.3 percent less, those in the middle quintile spent 8.5 percent less, and those in the top quintile spent 4.3 percent less. The fact that higher-income groups reined in spending more is not surprising, as a higher portion of their income is discretionary.

But compared with 1987, the big winners are the lowest-income group, whose expenditures increased by 12.1 percent in constant dollars. In contrast, the highest group spending per person increased by only 9.2 percent. This shows that even though the distribution of income might be wider, those at the bottom are doing better than they did 25 years ago because they have greater spending power, after adjusting for inflation.

Moreover, the top-income group has not progressed much at all but has essentially been flat. This is partly a result of the recession of the past few years. From 1987 to 2007, all groups did better. But over the past five years, expenditures per person have declined in all strata. The aggregate spending numbers mask some interesting patterns. The only area of society where higher-income people spend substantially more than lower-income individuals is on insurance and pensions.

 

 

On a per-capita basis, Americans spend less on food today than they did 25 years ago. This is remarkable, given the increase in obesity. Higher-income Americans spend less than twice (177 percent) as much on food as do lower-income Americans. Inequality in food expenditures has stayed the same. The top quintile in 2012 spent 1.8 times as much as the lowest quintile, the same as 25 years ago.

The largest expenditure category for Americans of all incomes is housing. The top-income group spends 30 percent of its expenditures on housing, while the lowest-income group spends 40 percent. Housing inequality has decreased over the past quarter-century, from a ratio of 2 to 1.8. Over the past five years, the top-income quintile is spending 12 percent less on housing, whereas the expenditure of the lowest quintile is down 3.7 percent.

There has been a remarkable decline in all income strata on expenditures on apparel and services. Services in this category comprise laundering, dry cleaning, tailoring, shoe repair, and other apparel-related services. Spending inequality has decreased from a ratio of 2.8 percent to 2.4 percent. Apparently, Americans are spending substantially less on clothing than they spent 25 years ago. The major reasons are the influx of lower-priced clothing from overseas and the increased informality of clothing in society.

Transportation is the second-largest category of spending for Americans. The ratio of spending between the top and bottom quintile is less today, 2.6, than it was 25 years ago, 3.0. The decline has occurred despite higher car and gasoline prices and likely reflects that Americans buy fewer new cars today than they did 25 years ago and that these cars use less gasoline. 

Spending on entertainment has risen over the past 25 years, especially for lower-income Americans. But inequality in entertainment spending has declined substantially, from a ratio of 3.7 to 3.0. Entertainment spending includes theater fees and admissions, cable, video games, iPods and iTunes, pets, playground equipment, photography, recreational vehicles, sporting goods, and other recreational equipment. 

Spending on personal-care products and services, such as shampoo, hairdressers, and barbers, has changed remarkably little over the past 25 years. Inequality has risen slightly, from a ratio of 2.5 to a ratio of 2.6.

In contrast to other categories, spending on health care has become more unequal. It has increased for all classes but especially for upper-income individuals. For the lowest quintile, spending in real terms has increased by 20 percent, and for the upper quintile it has risen by 94 percent. This increase comes in spite of expanded insurance coverage.

Another area of increased inequality is education spending. Average spending of those in the top quintile increased by 143 percent during the past 25 years but grew by less only 36 percent for the lowest quintile. The income inequality measure increased from 1.7 in 1987 to 3.0 in 2012. On the other hand, spending on reading declined dramatically over the past 25 years. People might be spending more on education, but they are spending less on reading. That may be one reason that SAT verbal scores are declining. Twenty-five years ago, Americans in the top quintile spent an average of $166 per year on newspapers, magazines, and books. By 2012, that figure had declined to $68 per person. In the lowest quintile, spending declined from $72 per person to $26 per person. Stated differently, per-capita spending in the highest-income quintile in 2012 was less than per-capita spending in the lowest quintile in 1987.

The area of greatest inequality is spending on insurance and pensions. In the lowest quintile, spending from 1987 to 2012 increased 7.5 percent, from $268 per person to $288 per person. In contrast, in the top 20 percent, spending increased from over $3,882 per person to over $5,011per person over the same period, an increase of 29 percent. The ratio of spending inequality jumped from 14.5 to 17.4. Personal insurance and pensions is the only area of spending where there is a dramatic difference between spending patterns of high-income and low-income Americans.

 

CONCLUSION

Many commentators today bemoan a supposed inequality in the United States. Much of this concern is a problem in search of reality, caused by problems of measurement and changes in demographic patterns over the past quarter-century. Government data on spending patterns show remarkable stability over the past 25 years and, if anything, a narrowing rather than an expansion of inequality.

 

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