Distribution of Income

by Frank Levy
About the Author
The distribution of income lies at the heart of an enduring issue in political economy—the extent to which government should redistribute income from those with more income to those with less.

Whether government should redistribute income is a normative question, and each person’s answer will depend on his or her values. But for many people, answering the normative question requires understanding the facts about the current income distribution. The term “income distribution” is a statistical concept. No one person is distributing income. Rather, the income distribution arises from people’s decisions about work, saving, and investment as they interact through markets and are affected by the tax system. The 1990s and early 2000s witnessed the establishment of a growing body of work, increasingly precise, describing how the income distribution has changed. This work can be summarized in three points:

The distribution of pretax income in the United States today is highly unequal. The most careful studies suggest that the top 10 percent of households, with average income of about $200,000, received 42 percent of all pretax money income in the late 1990s. The top 1 percent of households, averaging $800,000 of income, received 15 percent of all pretax money income.

In the longer view, the path of income inequality over the twentieth century is marked by two main events: a sharp fall in inequality around the outbreak of World War II and an extended rise in inequality that began in the mid-1970s and accelerated in the 1980s. Income inequality today is about as large as it was in the 1920s.

Over multiple years, family income fluctuates, and so the distribution of multiyear income is moderately more equal than the distribution of single-year income.

Trends in Inequality

The most frequently cited statistics come from the U.S. Census Bureau’s Current Population Survey (CPS), the monthly household survey best known as the source of the official unemployment rate. Since 1948, the March edition of the CPS has collected household income information for the previous year, as well as the personal characteristics of household members—their age, education, occupation, and industry (if they work), and other data that help give insight into changing income patterns. Although this makes the CPS an indispensable statistical source, it has disadvantages as well. The CPS uses a restricted income definition: pretax money receipts excluding capital gains. This definition is further restricted by a “cap,” currently $999,999, imposed on reported annual earnings for reasons of confidentiality.1 Together, these problems mean that CPS estimates of inequality omit the effects of taxes, nonmoney income such as government and private health insurance, and the portion of individual earnings that exceeds the cap.

A second source of inequality statistics is the U.S. Treasury’s Statistics of Income (SOI), which summarizes income reported on federal income tax returns. SOI data contain no personal data on taxpayers such as age or education, and they cannot describe the precise shape of the lower part of the income distribution.2 The strengths of SOI data are their ability to accurately describe the upper part of the distribution—SOI income data are not “capped”—and to extend this description back to 1917, thirty years before CPS statistics begin.

Table 1 contains selected information on CPS measures of family and household income inequality since World War II.3 The upper panel describes income patterns across families: living units occupied by two or more related persons. The lower panel describes income patterns across households: all occupied living units including families, persons who live alone, unrelated roommates, and so on. To form each distribution, the sample of families (or households) is listed in order of increasing income. The Census then calculates the fraction of all family income going to the quintile (one-fifth) of families with the lowest incomes, the quintile of families with the second-lowest incomes, and so on, as well as the share going to the highest 5 percent of families (who also are included in the top quintile).

The CPS data in Table 1 trace a J-shaped evolution of post–World War II inequality. In 1947, the top quintile of families received $8.60 for every dollar of income received by the bottom quintile. This ratio fell gradually through the 1950s and 1960s until 1969, when it reached $7.25 to $1.00—the low point of inequality. Beginning in the late 1970s, the ratio began to rise again until, by 2002, it had increased to $11.36 to $1.00, significantly greater than in 1947. Household data tell a similar story.

To make these trends more concrete, Table 1 includes the 1947, 1979, and 2001 income levels that divide each quintile from the next. Similar data are presented for households, and all income levels are expressed in 2003 dollars. Between 1947 and the mid-1970s, income grew rapidly at all points in the distribution, resulting in both rising living standards and moderating inequality. After the mid-1970s, average income grew much more slowly, and the growth that did occur was concentrated in the distributions’ upper half. Between 1979 and 2001, the income dividing the first and second family quintiles grew slightly, from $22,280 to $24,000 (7.7 percent), while the income dividing the fourth and fifth quintiles grew from $74,470 to $94,150 (26.4 percent). Now, as in the 1970s, a majority of families would describe themselves as middle class, but the “middle class” is now a larger, more diverse concept than it once was.4

Inequality estimates based on the U.S. Treasury’s SOI data expand on this picture. At the outset, SOI data do not “cap” high incomes, so household income inequality as reported in the SOI is significantly larger.5 Using “capped” statistics, the CPS reports that the top one-fifth of households receives 49 percent of all pretax money income. The SOI estimates, more accurately, that the top one-tenth of households, with average annual income of about $200,000, receives 42 percent of total pretax money income. The top 1 percent of households with average annual incomes of about $800,000 receives 15 percent of all pretax income. With their longer historical perspective, SOI statistics also show that inequality in the 1920s and 1930s was as high as it is today. Beginning in 1938, the income share of the top one-tenth of households fell from 43 percent to about 32 percent, where it remained until the deep blue-collar recession of the early 1980s. At that point, inequality began its return to the levels of the 1920s and early 1930s.6


Table 1 Family and Household Income Distributions (Census Definitions)
*. Original table rearranged and bracketed headings added here for clarity.
†. Data available only since 1967.

A. Shape of the Family Income Distribution (share of all family income going to each one-fifth [quintile] of families)
First Quintile (Lowest Income) Second Quintile Third Quintile Fourth Quintile Fifth Quintile (Highest Income) Top 5 percent (Contained in Fifth Quintile) Upper bound of Quintile (2003 dollars) Lower bound of top 5%
[1st] [2nd] [3rd] [4th] [5th]*
1947 5.0 11.9 17.0 23.1 43.0 17.5 $11,088 $17,893 $24,263 $34,427 na. $56,506
1959 4.9 12.3 17.9 23.8 41.1 15.9
1969 5.6 12.4 17.7 23.7 40.6 15.6
1979 5.4 11.6 17.5 24.1 41.4 15.3 $23,171 $38,102 $53,979 $74,329 na. $119,243
1989 4.6 10.6 16.5 23.7 44.6 17.9
2001 4.2 9.7 15.4 22.9 47.7 21.0 $24,960 $42,772 $65,000 $97,916 na. $170,668

B. Shape of the Household Income Distribution (share of all households’ income going to each one-fifth [quintile] of households)
First Quintile (Lowest Income) Second Quintile Third Quintile Fourth Quintile Fifth Quintile (Highest Income) Top 5 percent (Contained in Fifth Quintile) Upper bound of Quintile (2003 dollars) Lower bound of top 5%
[1st] [2nd] [3rd] [4th] [5th]*
1967 4.0 10.8 17.3 24.2 43.8 17.5 $14,002 $27,303 $38,766 $55,265 na. $88,678
1979 4.2 10.3 16.9 24.7 44.0 16.4 $16,457 $30,605 $47,018 $68,318 na. $111,445
1989 3.8 9.5 15.8 24.0 46.8 18.9
2001 3.5 8.7 14.6 23.0 50.1 22.4 $17,970 $33,314 $53,000 $83,500 na. $150,499


The Causes of Inequality

In one sense, the growth of inequality in the last part of the twentieth century comes as a surprise. In the 1950s, the bottom part of the income distribution contained large concentrations of two kinds of families: farm families whose in-kind income was not counted in Census data, and elderly families, many of whom were ineligible for the new Social Security program. Over subsequent decades, farm families declined as a proportion of the population while increased Social Security benefits and an expanding private pension system lifted elderly incomes. Both trends favored greater income equality but were outweighed by four main factors.

Family structure. Over time, the two-parent, one-earner family was increasingly replaced by low-income single-parent families and higher-income two-parent, two-earner families. A part of the top quintile’s increased share of income reflects the fact that the average family or household in the top quintile contains almost three times as many workers as the average family or household in the bottom quintile.

Trade and technology. Trade and technology increasingly shifted demand away from less-educated and less-skilled workers toward workers with higher education or particular skills. The result was a growing earnings gap between more- and less-educated/skilled workers.

Expanded markets. With improved communications and transportation, people increasingly functioned in national, rather than local, markets. In these broader markets, persons with unique talents could command particularly high salaries.

Immigration. In 2002, immigrants who had entered the country since 1980 constituted nearly 11 percent of the labor force (see immigration). A relatively high proportion of these immigrants had low levels of education and increased the number of workers competing for low-paid work.7

These factors, however, can explain only part of the increase in inequality. One other factor that explains the particularly high incomes of the highest-paid people is that between 1982 and 2004, the ratio of pay of chief executive officers to pay of the average worker rose from 42:1 to 301:1, and pay of other high-level managers, lawyers, and people in other fields rose substantially also.

Does Measurement Matter?

As noted above, both CPS and SOI statistics measure pretax money income. These measurements are deficient for three reasons. First, increases in governmental aid to the poor have been concentrated in nonmoney benefits such as Medicaid and food stamps and through tax credits under the Earned Income Tax Credit (EITC). Nonmoney benefits are excluded from standard statistics, and EITC tax credits are typically underreported. Second, an increasing proportion of wage-earners’ total compensation goes to health insurance and pension benefits—which are not counted in standard statistics. Third, taxes themselves modify the income distribution.

The U.S. Census has attempted to correct these definition problems for recent years by estimating the household income distribution under alternative income definitions. Table 2 shows the effect in 2001 of moving from the standard Census definition (pretax money excluding capital gains) to an adjusted definition that includes the estimated effects of capital gains, taxes, the EITC, and the monetary value of private and governmental nonmoney benefits. The result is a substantial reduction in inequality, with the ratio between incomes in the top and bottom quintiles falling from $14.31:$1.00 to $10.40:$1.00. Similar adjustments for selected earlier years indicate that better income measurement reduces inequality in any single year. Even under the adjusted definition, though, the trend toward increasing inequality in the 1980s and 1990s remains, but at a slower pace.


Table 2 Shape of the Household Income Distribution Under Alternative Income Definitions for 2001 (share of income going to each quintile of households)
*. Original table rearranged and bracketed headings added here for clarity.
†. Standard Census Income is defined as pretax money income excluding capital gains.

First Quintile (Lowest Income) Second Quintile Third Quintile Fourth Quintile Fifth Quintile (Highest Income) Upper bound of quintile (2003 dollars)
[1st] [2nd] [3rd] [4th]*
Standard Census income 3.5 8.7 14.6 23 50.1 $18,618 $34,780 $55,105 $86,914
Adjusted Census income 4.5 10.3 15.6 22.6 47 $21,334 $35,485 $51,747 $75,195

Note: Adjusted Census Income is based on pretax money income including estimated capital gains, less all taxes paid plus the estimated receipt of the Earned Income Tax Credit plus the imputed value of in-kind income from employer-provided health insurance and government nonmoney benefits like food stamps, Medicare and Medicaid, and free school lunches.


Table 3 Mobility Within the Family Income Distribution

Quintile in 1998
First Quintile (Lowest Income) Second Quintile Third Quintile Fourth Quintile Fifth Quintile (Highest Income)
First Quintile in 1988 53.30% 23.60% 12.40% 6.40% 4.30%
Fifth Quintile in 1988 3.00% 5.70% 14.90% 23.20% 53.20%

Source: Katherine Bradbury and Jane Katz, “Are Lifetime Incomes Growing More Unequal? New Evidence on Family Income Mobility,” Federal Reserve Bank of Boston Regional Review 12, no. 4 (2002).

Inequality and Mobility

A second offset to estimated inequality is economic mobility. Because most family incomes increase as people’s careers develop, long-run incomes are more equal than standard single-year statistics suggest. Table 3 summarizes the results of one study of recent family income mobility.8 Among families in the bottom quintile in 1988, half were in the bottom quintile ten years later, a quarter had moved up to the second quintile, and a quarter had moved to the third or higher quintiles. Families in the fifth quintile (highest incomes) show a similar mobility over time.

The Economic Case for Inequality of Wages and Incomes

David R. Henderson

Is inequality of wages and incomes bad? The question seems ludicrous. Of course inequality is bad, isn’t it? Actually, no. What matters crucially is how the inequality came about.

Inequality of wages and incomes is clearly bad if it results from government privileges. Many people would find such an outcome unjust, but even more important to many economists is that such inequality sets up perverse incentives. Instead of producing valuable products and services for their fellow citizens, as people tend to do in free economies, people in societies based on government-granted privileges devote much of their effort to pleasing, or outright bribing, government officials. In many African countries, for example, such as Côte d’Ivoire, Ghana, and Zaire, there are stark inequalities because the government has the power to take a high percentage of the wealth of the already poor and give a large amount of it to government officials or their cronies. And in many Latin American countries, for many decades a few families have had most of the wealth and have used government power to cement their privileges.

But inequality in wages and incomes in relatively free economies serves two important social functions. First, it gives people strong incentives to produce so as to make higher incomes and wages. Second, it gives people, and not just young people, strong incentives to get training or education that will allow them to perform well in higher-wage jobs. In his January 1999 Richard T. Ely lecture, economist Finis Welch put the point as follows:

Wages play many roles in our economy; along with time worked, they determine labor income, but they also signal relative scarcity and abundance, and with malleable skills, wages provide incentives to render the services that are most highly valued. (Welch 1999, p. 1)

Further Reading

Mbaku, John Mukum. “Bureaucratic Corruption in Africa: The Futility of Cleanups.” Cato Journal 16, no. 1 (1996): 99–118.
Rothbard, Murray. “Egalitarianism as a Revolt against Nature.” Available online at: http://www.lewrockwell.com/rothbard/rothbard31.html.
Welch, Finis. “In Defense of Inequality.” American Economic Review 89, no. 2 (1999): 1–17.

About the Author

Frank Levy is the Daniel Rose Professor of Urban Economics in MIT’s Department of Urban Studies and Planning.


Further Reading

Charles, Kerwin Kofi, and Erik Hurst. “Correlation of Wealth Across Generations.” Journal of Political Economy, 111, no. 6 (2003): 1155–1182.
Fortin, Nicole M., and Thomas Lemeiux. “Institutional Changes and Rising Wage Inequality: Is There a Linkage?” Journal of Economic Perspectives 11, no. 2 (1997): 75–96.
Gottschalk, Peter. “Inequality, Income Growth and Mobility: The Basic Facts.” Journal of Economic Perspectives 11, no. 2 (1997): 21–40.
Johnson, George E. “Changes in Earnings Inequality: The Role of Demand Shifts.” Journal of Economic Perspectives, 11, no. 2 (1997): 41–54.
Saez, Emmanuel. “Income and Wealth Concentration in a Historical and International Perspective.” In Alan J. Auerbach, David E. Card, and John M. Quigley, ed., Public Policy and the Income Distribution. New York: Russell Sage Foundation, 2006. Also available at http://emlab.berkeley.edu/users/saez/berkeleysympo2.pdf.
Topel, Robert. “Factor Proportions and Relative Wages: The Supply Side Determinants of Wage Inequality.” Journal of Economic Perspectives 11, no. 2 (1997): 55–74.

Footnotes

That is, earnings greater than $999,999 are reported as $999,999.

SOI data are combined with national income accounts estimates of total personal income received in the economy to calculate the share of all personal income received by the top 1 percent of households, the top 10 percent of households, and so on. Because many lower-income households do not pay federal income taxes, the SOI cannot provide similar detail on, say, the share of income received by the 10 percent of households with the lowest incomes.

Household and family income data are available online at http://www.census.gov/hhes/income/histinc/histinctb.html.

The connection between “class” and the income distribution is complicated by the fact that the distribution includes families of all ages, ranging from married students to retirees, while our stereotype of a middle-class income is based on families in their prime earning years.

The SOI data are based on tax filing units, a concept that is reasonably close to the Census’s definition of household.

See Thomas Piketty and Emanuel Saez, “Income Inequality in the United States, 1913–1998,” Quarterly Journal of Economics 118, no. 1 (2003): 1–39.

See Robert Lerman, “U.S. Income Inequality Trends and Recent Immigration,” American Economic Review 89, no. 2 (1999): 23–38.

Katherine Bradbury and Jane Katz, “Are Lifetime Incomes Growing More Unequal? New Evidence on Family Income Mobility,” Federal Reserve Bank of Boston Regional Review 12, no. 4 (2002) 3–5.


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