The U.S. Income Distribution and Mobility:
Trends and International Comparisons
Linda Levine
Specialist in Labor Economics
March 7, 2012
Congressional Research Service
7-5700
www.crs.gov
R42400
CRS Report for Congress
Pr
epared for Members and Committees of Congress
The U.S. Income Distribution and Mobility: Trends and International Comparisons
Summary
Approaching three years into the recovery from the 2007-2009 recession, the unemployment rate
remains over 8%. The persistent difficulty of many of the workers who lost jobs to find
reemployment has meant reduced incomes for them and their families. A historically slow
rebound in the labor market appears to be partly responsible for some groups’ focus on the
distribution of the benefits of economic growth and for some policymakers’ interest in
redistributing income through the tax code, for example. Varying perceptions about a trade-off
between economic growth and income equality appear to underlie longstanding congressional
deliberations about such policy issues as the progressivity of income tax rates, the tax treatment
of capital gains, and the adjustment of the federal minimum wage.
If income were equally divided across households, each quintile (fifth) would account for 20% of
total income. The Congressional Budget Office and others have documented that the bottom fifth
has long accounted for much less than 20% of total income. The bottom quintile’s share of
income has remained little changed for the past few decades at less than 4%, according to U.S.
Census Bureau data. In contrast, the income shares of the top fifth and the top 5% of households
appear to have trended upward. The top fifth’s share of total household income rose from 42.6%
in 1968 to 50.2% in 2010; the top 5%’s share, from 16.3% to 21.3%. (Estimates derived from
federal income tax data suggest that those at the very top of the income distribution have
experienced greater gains.) The middle class, defined as the middle 60%, received a
disproportionately smaller share of the total economic pie in 2010 (46.5%) than in 1968 (53.2%).
Two explanations are most often offered for the changes in recent decades in the U.S. distribution
of income. They are skill-biased technological change (SBTC) and globalization. Additional
support for education and training is a frequently cited policy measure to both improve U.S.
competitiveness in the international marketplace and raise the relative incomes of low- and
middle-skill workers as well as the incomes of their children when they enter the labor force.
Based on the limited data that are comparable across nations, the U.S. income distribution
appears to be among the most uneven of all major industrialized countries and the United States
appears to be among the nations experiencing the greatest increases in measures of inequality.
Three leading explanations are put forth for these cross-country differences: (1) other advanced
economies devote a larger share of national output to transfers, which tends to equalize income
across households; (2) the progressivity of tax rates varies by country and thus has different
effects on the distribution of after-tax income; and (3) equality in the distribution of earnings,
which account for most household income, varies substantially across countries.
The extent to which countries undertake policies that affect their income distributions may reflect
national differences in perceptions about the degree of income mobility. In the United States, a
longstanding argument against redistributionary measures has been that each person has an equal
opportunity to move up the income ladder. Research raises questions about whether Americans’
reported perceptions about their likelihood of changing position in the income distribution are
exaggerated.
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Contents
Introduction...................................................................................................................................... 1
Measures of Income......................................................................................................................... 2
Measures of the Distribution of Income .......................................................................................... 3
Explaining Recent Trends in the Distribution of U.S. Household Income ...................................... 7
International Comparisons of Income Distributions........................................................................ 9
Explaining Cross-Country Differences in the Distribution of Income .......................................... 12
Income Mobility in the United States ............................................................................................ 14
Intergenerational Mobility....................................................................................................... 14
The Trend in Intergenerational Mobility in the United States........................................... 14
Cross-Country Comparisons of Intergenerational Mobility.............................................. 16
Intragenerational Mobility....................................................................................................... 16
Concluding Remarks ..................................................................................................................... 18
Figures
Figure 1. Gini Coefficients for U.S. Households, 1968-2010.......................................................... 5
Tables
Table 1. Distribution of U.S. Household Income by Quintile, Selected Years ................................ 4
Table 2. Summary Measures of Disposable Household Income Distributions for Selected
Countries in the Mid-2000s ........................................................................................................ 10
Table 3. Summary Measure of Disposable Household Income Distributions for Selected
Countries in the Late 2000s and Change from Mid-1980s to Late 2000s .................................. 11
Contacts
Author Contact Information........................................................................................................... 18
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Introduction
The unemployment rate averaged 8.9% in 2011 and remains above 8.0% thus far in 2012, over
three percentage points higher than its level at the outset of the December 2007-June 2009
recession. The inability of many of the workers who lost jobs during the recession to find new
ones during the recovery has meant reduced income for them and their families.1 The slow pace
of recovery in the labor market has renewed interest in the long-term trend of growing inequality
in the distribution of income.2 In other words, the benefits of economic growth (e.g., higher
incomes) began accruing unequally across U.S. households long before the late 2000s.
Economic theory provides little basis for preferring any particular degree of equality in the
distribution of income. In theory, what matters with respect to labor income is that the distribution
results from markets that operate efficiently; that is, markets in which the final demand for goods
and services and the relative productivity of the firms producing those goods and services
determine the demand for labor and the earnings of jobs in each sector of the economy.
Theoretical arguments for a more equal distribution of income than that which results from
market forces are based on a number of propositions, including the diminishing marginal utility
of income. This refers to the idea that each additional dollar of income yields less and less
satisfaction (utility) than the first. For example, one additional dollar of income adds less to the
utility of someone earning $100,000 than to the satisfaction of someone earning $20,000. If this
proposition is correct, it should be possible to increase the overall well-being of society by
transferring money from those with high incomes to those with low incomes because the loss in
utility will be less for high-income individuals than the gain for low-income individuals.
However, the costs commonly associated with income redistribution (e.g., slower economic
growth) may offset some and possibly all of any net gain in well-being.3
With varying perceptions about a trade-off between economic growth and income equality,
members of the U.S. public policy community have long debated how best to improve the well-
being of the population. This disagreement appears to underlie longstanding congressional
deliberations about several policy issues, such as the progressivity of income tax rates, tax
treatment of capital gains and inheritance, provision of social insurance (e.g., Social Security) as
well as social welfare benefits (e.g., food stamps), and raising the federal minimum wage.4 It also
has extended to consideration of initiatives (e.g., grants for early childhood education and college
tuition tax expenditures) that arguably promote equality in the opportunity to move up the income
ladder,5 which an increasingly unequal distribution of income may suggest a lack of and which
may itself curb the potential productive capacity of the economy.6
1 The December 2007-June 2009 recession was the eleventh recession of the postwar period. The labor market
following the latest recession has been recovering more slowly than it did after most of the ten prior recessions. For
more information see CRS Report R41434, Job Growth During the Recovery, by Linda Levine.
2 D.B. Grusky and C. Wimer, “Is There Too Much Inequality?,” in The Inequality Puzzle: European and US Leaders
Discuss Rising Income Inequality, ed. Roland Berger, David Grusky, Tobias Raffel, Geoffrey Samuels, and Christopher
Wimer (Germany: Springer, 2010), pp. 4-5.
3 For additional information see “Reducing Income Inequality While Boosting Economic Growth: Can It Be Done?”
(part II, chapter 5 of Economic Policy Reforms, Going for Growth 2012, February 2012, 200 pp.), in which the OECD
identifies the impact of various policies on both growth and equality.
4 During the 112th Congress, see for example H.R. 283 (the Living Wage Act of 2011), H.R. 382 (the Income Equity
Act of 2011), S. 1960 (the Job Creation Act), and S. 2059 (Paying a Fair Share Act of 2012).
5 During the 112th Congress, see for example H.R. 953 (Making College Affordable Act of 2011), H.R. 4038 (the
(continued...)
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This report presents recent analysis of the distribution of income and the extent of income
mobility in the United States over time and in comparison with other advanced economies. It
begins with a discussion of data issues related to measuring income and its distribution. The
empirical literature on the development of and explanations for income inequality in the United
States are next addressed. The report then compares the U.S. income distribution with the
distributions of other industrialized countries and presents explanations for cross-country
differences in equality measures. To the degree that a more equal distribution of income arises
from policy decisions rather than market forces, the willingness of a country to incur any
economic costs related to attaining greater equality may reflect varying national beliefs about the
opportunity to ascend the income ladder. For that reason, the report closes with an examination of
income mobility in the United States and other developed nations.
Measures of Income
Two common sources of income data are the Annual Social and Economic supplement to the
Current Population Survey (CPS) and federal income tax returns submitted to the Internal
Revenue Service (IRS). The U.S. Census Bureau, which conducts the CPS, calculates “money
income.” It is the nation’s official measure of income. Money income includes wages and
salaries, interest, dividends, rent, payments from pensions and retirement savings accounts, and
nonmeans-tested cash income (e.g., Social Security, unemployment compensation, and veterans’
payments). Calculated on a pre-tax basis, money income does not include the value of noncash
government benefits (e.g., food stamps and housing subsidies) and capital gains.7
“Market income” is the measure of income derived from federal tax data made available by the
IRS. Perhaps most prominent among the researchers who use tax data to study the distribution of
income are Saez and Piketty. They define pre-tax market income to include all income reported
on individual tax returns including wages and salaries, business and farm income, and capital
income (e.g., dividends, interest, and rents).8 The primary differences between money and market
income thus defined is that market income excludes cash government benefits and includes
realized capital gains.
With respect to the distribution of overall economic well-being, measures based on the concepts
of money and market income fall short and may be misleading. Consider the case of two families
who in every way are equal in terms of wealth and income. Neither owns their home, and they
both have substantial savings in interest-earning assets. Suppose one family uses a portion of its
savings to buy a home. No one would argue that the family is now worse off, but income
measures indicate that to be the case because the family’s interest income would have fallen. In
(...continued)
American College Tuition Tax Relief Act of 2012), S. 1495 (the Early Intervention for Graduation Success Act of
2011), and S. 1978 (the Community College Innovation Act).
6 See for example Florence Jaumotte, Subir Lall, and Chris Papageorgiou, Rising Income Inequality: Technology, or
Trade and Financial Globalization, International Monetary Fund, Working Paper 08/185, July 1, 2008.
7 The Census Bureau also periodically calculates alternative measures of income that include such income sources as
government noncash benefits and capital gains. The latest alternative measures of income are available at
http://www.census.gov/hhes/www/cpstables/032009/rdcall/1_001.htm.
8 Thomas Piketty and Emmanuel Saez, “Income Inequality in the United States, 1913-1998,” Quarterly Journal of
Economics, vol. 118, no. 1 (2003), pp. 1-39. (Hereinafter referred to as Piketty and Saez, Income Inequality in the
United States, 1913-1998.)
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fact, the family that buys its home is earning an implicit income in the use of the house just as it
would earn rental income if the house were leased to others. Not counting this implicit income
may have a significant effect on the distribution of income.
Another weakness in existing income measures as a reflection of overall economic well-being is
that they do not account for the implicit income of homemakers. Consider two married-couple
households with the same income and both spouses receive wages from their employers. If in one
of the households a spouse quits to stay at home and care for their children that household will
experience a drop in measured income. Because the unpaid work done at home is not without
value, the measured difference in the incomes of the two households will overstate the difference
in their living standards.
The time period in which income is measured may also affect comparisons in well-being across
households. Over the course of the business cycle unemployment rises and falls, affecting labor
income. Some households tend to be more adversely affected than others by recessions, so the
stage of the business cycle has an influence on relative income. Similarly, income generally varies
substantially over the course of an individual’s lifetime. New entrants to the labor force typically
have lower incomes than those who have been working for some time, and income tends to
decrease upon retirement. Because of these life-cycle changes in income, the age mix of the
population also influences the relative incomes of households.
Another difficulty in comparing income across households is deciding on the relevant population.
In the case of labor income, the distribution of income among working-age individuals (e.g., 25-
64 year olds) may be of most interest. When it comes to overall well-being, it may be more
appropriate to consider the distribution of income across households. Because most households
can be presumed to pool resources and because some costs of living are fixed, a four-person
household may not need twice as much income as a married-couple household for each person to
enjoy roughly the same living standard.9 The ability to achieve economies of scale thus further
complicates using the distribution of income across households or tax filing units as a basis for
judging economic well-being.10
Measures of the Distribution of Income
The Census Bureau annually publishes a variety of measures that describe the distribution of
money income. One measure divides total money income into quintiles (fifths), with households
ordered from lowest to highest income and then divided into five groups of equal size. The
income within each group is summed, and its share (percentage) of total household income is
calculated. If aggregate income was equally divided across households with income, each quintile
would account for 20% of total money income. To the extent that each quintile falls short of or
exceeds its proportionate (20%) share, it indicates the degree of inequality in the income
distribution.
9 In the Current Population Survey (CPS), a household is defined as all of the individuals who occupy a housing unit as
their usual place of residence. A family is defined as a group of two or more individuals who reside together and who
are related by birth, marriage, or adoption. A household may be composed of one or more families or no families at all;
that is, a person living alone in a housing unit is counted as a household in the CPS.
10 A tax unit is anyone who files a federal income tax return.
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As shown in the last row of Table 1, the bottom fifth of households in 2010 accounted for much
less than the one-fifth of total income it would have gotten if the distribution were perfectly
equal. The top 20%, in contrast, accounted for more than twice what it would have gotten in an
equal distribution. The top 5%, which is within the top fifth, accounted for more than four times
the share it would have had in a perfectly equal distribution. The data thus indicate that income
was quite unequally distributed across U.S. households in 2010.
Table 1. Distribution of U.S. Household Income by Quintile, Selected Years
(1968-2010)
Percentage of Total Household Income
Year
Bottom
Second
Third
Fourth
Fifth
Top 5%
1968 4.2 11.1 17.6 24.5 42.6 16.3
1980 4.2 10.2 16.8 24.7 44.1 16.5
1990 3.8
9.6 15.9 24.0 46.6 18.5
2000 3.6
8.9 14.8 23.0 49.8 22.1
2001 3.5
8.7 14.6 23.0 50.1 22.4
2002 3.5
8.8 14.8 23.3 49.7 21.7
2003 3.4
8.7 14.8 23.4 49.8 21.4
2004 3.4
8.7 14.7 23.2 50.1 21.8
2005 3.4
8.6 14.6 23.0 50.4 22.2
2006 3.4
8.6 14.5 22.9 50.5 22.3
2007 3.4
8.7 14.8 23.4 49.7 21.2
2008 3.4
8.6 14.7 23.3 50.0 21.5
2009 3.4
8.6 14.6 23.2 50.3 21.7
2010 3.3
8.5 14.6 23.4 50.2 21.3
Source: U.S. Census Bureau, Annual Social and Economic Supplements to the Current Population Survey.
Households at various points in the distribution also have fared differently from each other over
time. Between 1968 and 2010, the income share of the three middle quintiles fell from 53.2% to
46.5% (see Table 1). Although there is no official definition of the middle class, the middle 60%
of households is sometimes regarded as such.11 As for the bottom 20% of households, its income
share has stagnated at less than 4.0% for the last few decades. In contrast, the income shares of
the top fifth and the top 5% of households generally have risen from year to year. The top 20%’s
share grew from 42.6% in 1968 to 50.2% in 2010, and the top 5%’s share grew from 16.3% to
21.3%.
Another indicator of the degree of inequality is the Gini coefficient. It is a single number that can
range between zero (a perfectly equal distribution) and one (a perfectly unequal distribution).12
11 CRS Report RS20811, The Distribution of Household Income and the Middle Class, by Linda Levine.
12 For additional information on the Gini coefficient see Malte Luebker, Inequality, Income Shares and Poverty: the
Practical Meaning of Gini Coefficients, International Labour Office, Travail Policy Brief No. 3, Geneva, Switzerland,
June 2010, 8 pp.
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The historical trend in the United States is one of almost steadily increasing income inequality
(from 0.386 in 1968 to 0.469 in 2010), as depicted in Figure 1. During the 2007-2009 recession,
the Gini coefficient fell slightly from its 2006 peak. Nonetheless, its level in 2010 indicates an
income distribution that is much more unequal than in most years since 1968.
Figure 1. Gini Coefficients for U.S. Households, 1968-2010
Source: Created by CRS from data from the U.S. Census Bureau’s Annual Social and Economic Supplements to
the Current Population Survey (CPS).
Note: The increase in the Gini coefficient in the early 1990s was due to the redesign of the CPS.
Researchers who work with the CPS data often calculate an alternative measure of overall
inequality (the ratio of income at the 90th percentile in the distribution to income at the 10th
percentile) because the Gini coefficient does not allow them to ascertain which parts of the
income distribution are driving changes in inequality. An increase in the ratio of the median
income level (50th percentile) to the 10th percentile income level (the 50-10 ratio) suggests that
growth in overall inequality (the 90-10 ratio) is due to those near the bottom of the distribution
falling further behind the typical household. An increase in the ratio of the 90th percentile to the
median income level (the 90-50 ratio) suggests that growth in overall inequality is due to those
near the top of the distribution pulling further ahead of the typical household. Based on these
measures, increased inequality in the upper half of the distribution may have accounted for most
of the overall increase in inequality between 1961 and 2002.13 Looking at just the 1990-2002
period, almost all of the increase in overall inequality appears to be due to an increase in top-half
13 Kevin A. Bryan and Leonardo Martinez, “On the Evolution of Income Inequality in the United States,” Economic
Quarterly, Federal Reserve Bank of Richmond, spring 2008.
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inequality. This pattern of the benefits of economic growth accruing largely to those near the top
of the income distribution was estimated to have continued through 2007.14
The 90-10 ratio may be a poor substitute for estimating overall inequality at a point in time and
over time because it is affected by top-coding in the CPS. Top-coding refers to the Census
Bureau’s long-standing practice of replacing the income reported above a specific level with that
income level to ensure confidentiality. For example, if the total money income of a household
was $780,000 in 2010, the household’s income would have been coded as $250,000 because
$250,000 was the threshold income level in that year. Top-coding therefore presents a problem
when estimating the extent of inequality in a given year because it constrains the actual
distribution of income. The practice also creates a problem when estimating changes in inequality
over time because the top-code thresholds were raised at various times over the years and as a
result, the share of households with suppressed incomes has differed over time.15
These drawbacks to using CPS data, in combination with anecdotal evidence that since the 1990s
those in the top 10% have pulled further away from other households, prompted economists to
turn to other data sources that better capture those with high incomes. Piketty and Saez developed
a time series from the early years of the 20th century forward based primarily on federal income
tax returns to study changes in market income among tax units at the very top of the income
distribution.16 They estimated that between 40% and 45% of total income accrued to the top 10%
of the distribution between the two World Wars before falling to about 30% during World War II.
The top decile’s share remained at 31%-32% until the 1970s when it began trending upward. The
top decile’s share again exceeded 40% by the mid-1990s and has been at all-time highs in recent
years. In 2010, the latest year for which an estimate is available, the top 10% accounted for over
46% of aggregate market income.17
Piketty and Saez attribute most of the changes in the top decile’s share over time to fluctuations in
the top 1% of the distribution. They estimated that before World War I the top 1% accounted for
about 18% of total market income. Its share peaked at almost 24% in the late 1920s, fell to about
8% from the late 1950s to the 1970s, and then turned upward.18 The top 1% was estimated to
have accounted for over 17% of total market income in 2010, about equal to its pre-World War I
share.19
Like the CPS, tax returns have limitations for analyzing income inequality (e.g., time-shifting
income through use of deferred compensation, such as stock options, and reporting income as
14 Javier Diaz-Gimenez, Jose-Victor Rios-Rull, and Andy Glover, “Facts on the Distributions of Earnings, Income, and
Wealth in the United States: 2007 Update,” Federal Reserve Bank of Minneapolis Quarterly Review, vol. 34, no. 1
(February 2011), pp. 2-31. (Hereinafter referred to as Diaz-Gimenez et al., Facts on the Distribution of Earnings,
Income, and Wealth.)
15 Richard V. Burkhauser, Shuaizhang Feng, and Stephen P. Jenkins, “Using the P90/P10 Ratio to Measure US
Inequality Trends with Current Population Survey Data: A View from Inside the Census Bureau Vaults,” Review of
Income and Wealth, vol. 55, no. 1 (2009), pp. 166-185.
16 They define tax units to be married-couples living together or single adults with or without dependents in Piketty and
Saez, Income Inequality in the United States, 1913-1998.
17 Facundo Alvaredo, Anthony B. Atkinson, Thomas Piketty, and Emmanuel Saez, The World Top Income Database,
http://g-mond.parisschoolofeconomics.eu/topincomes/. (Hereinafter referred to as Alvaredo, Atkinson, Piketty, and
Saez, http://g-mond.parisschoolofeconomics.eu/topincomes/.)
18 Piketty and Saez, Income Inequality in the United States, 1913-1998.
19 Alvaredo, Atkinson, Piketty, and Saez, http://g-mond.parisschoolofeconomics.eu/topincomes/.
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earnings or business profits depending on their tax treatment in a given year). Burkhauser, Feng,
Jenkins et al. attempted to reconcile the smaller increases in money income inequality starting in
the 1990s that are estimated by studies based on public-use CPS data with the larger increases in
market income inequality of studies based on tax data. Using internal Census Bureau data (which
is less subject to top-coding than is public-use data) to estimate income shares of those in the 90th-
95th percentile, the 95th-99th percentile, and the top 1%, they found that inequality trends during
most of the 1967-2006 period were quite similar to those of studies that used tax data once
comparable definitions of income and income-receiving units were employed.20
Burkhauser, Larrimore, and Simon more recently estimated that if after-tax, after-transfer income
adjusted for household size is analyzed rather than before-tax, before-transfer income of tax units
income inequality in the United States increased [between 1979 and 2007] not because the
rich got richer, the poor got poorer and the middle class stagnated, but because the rich got
richer at a faster rate than the middle and poorer quintiles and this mainly occurred in the
1980s. [Income] growth was substantial in all quintiles once the influence of government tax
and transfer policy as well as the shift in compensation from wages to health insurance
provided by employers and the shift to increased in-kind health insurance by government is
more fully recognized.21
A Congressional Budget Office report also examined after-tax, after-transfer size-adjusted
household income over the 1979-2007 period. It too estimated that absolute levels of inflation-
adjusted average household income increased across the distribution, but because the rate of
increase was much greater among the highest income households, inequality increased after 1979.
For example, the top 1% of households saw their average real income rise by 275% from 1979 to
2007; the middle three quintiles experienced a 37% increase; and the bottom fifth recorded an
18% gain. Consequently, in 2007, the share of income after taxes and transfers of the top 20% of
size-adjusted households was greater than the combined share of the other 80% of households
(58% and 47%, respectively).22
Explaining Recent Trends in the Distribution of
U.S. Household Income
Two explanations are most commonly offered for the trend toward greater inequality in the
distribution of labor income in the United States.23 One has to do with globalization, that is, the
increased integration of countries’ economies. The second relates to the nature of recent
technological advances.
20 Richard V. Burkhauser, Shuaizhang Feng, and Stephen P. Jenkins et al., Recent Trends in Top Income Shares in the
USA: Reconciling Estimates from the March CPS and IRS Tax Return Data, National Bureau of Economic Research,
Working Paper 15320, Cambridge, MA, September 2009.
21 Richard V. Burkhauser, Jeff Larrimore, and Kosali I. Simon, A “Second Opinion” on the Economic Health of the
American Middle Class, National Bureau of Economic Research, Working Paper 17164, Cambridge, MA, June 2011,
p. 21.
22 Congressional Budget Office, Trends in the Distribution of Household Income Between 1979 and 2007, Washington,
DC, October 2011.
23 Labor income is the leading contributor to household income. In 2007, according to the latest Survey of Consumer
Finances sponsored by the Federal Reserve Board, earnings accounted for 64% of household income.
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Reduced trade restrictions and increased worldwide flows of goods and services have arguably
made less skilled U.S. workers in particular more vulnerable to direct competition from less
skilled workers abroad. In theory, the shift overseas in production of goods and services that
predominantly use less-skilled workers has reduced demand in the United States for these
workers, thereby putting downward pressure on their wages and further widening the existing
wage gap between lower and higher skilled U.S. workers.
Economists generally have not agreed about globalization being a major contributor to increasing
income inequality because little compelling empirical evidence supports the theory. Analyses of
globalization’s employment effect to date have tended to find it too small to explain the
magnitude of the earnings gap.24 Other studies have estimated that a large number of jobs possess
characteristics which make them susceptible to being offshored.25 As it is technological advances
(e.g., high-speed telecommunication) that have made these jobs (e.g., call center workers)
vulnerable to offshore outsourcing, some have suggested that globalization cannot be separated
from the technological change argument (discussed below).26
Economists generally have found technological change to be the most persuasive explanation for
increased inequality at the top of the earnings distribution.27 Frequently cited evidence underlying
this explanation is the comparatively rapid growth in the wage premium paid to more highly
skilled (productive) workers since 1979. For example, the wage gap between workers with a
bachelor’s degrees and workers with a high school education almost doubled between the 1980s
and the 2000s.28 The increase in the skill premium coincided with substantial growth in the
percentage of the labor force with a college education. This suggests that the growth in their
supply did not keep pace with the increase in employer demand for highly skilled workers.29
The increased premium paid to high-skilled workers is commonly ascribed to the nature of
technological change in recent decades. Put another way, the kinds of technological advances that
have occurred since the late 1970s have been biased in favor of those jobs that require higher
levels of education and training. Technological progress seemingly has affected the earnings
distribution in two ways. First, information technology (IT) serves as a substitute for low-skilled
workers, which has reduced demand for and the relative wages of these workers. Second, IT
serves as a complement to high-skilled workers, which has raised demand for and the relative
wages of these workers.30 Autor, Katz, and Kearney have refined this explanation. They
hypothesize that computerization of tasks has polarized the labor market by
• increasing employer demand for those high-skilled workers who perform non-
routine cognitive tasks (e.g., engineers and lawyers);
24 A summary of these studies appears in CRS Report RL32292, Offshoring (or Offshore Outsourcing) and Job Loss
Among U.S. Workers, by Linda Levine.
25 Ibid.
26 Richard B. Freeman, “Globalization and Inequality,” in The Oxford Handbook of Economic Inequality, ed. Wiemer
Salverda, Brian Nolan, and Timothy M. Smeeding (NY: Oxford University Press, 2009), pp. 575-598.
27 See for example Ben S. Bernanke, Speech at Harvard University, June 4, 2008.
28 U.S. Census Bureau, Annual Social and Economic Supplements to the Current Population Survey.
29 Claudia Goldin and Lawrence F. Katz, The Race Between Education and Technology: the Evolution of U.S.
Educational Wage Differentials, 1890 to 2005, National Bureau of Economic Research, Working Paper 12984,
Cambridge, MA, March 2007.
30 David Autor, Frank Levy, and Richard Murnane, “The Skill Content of Recent Technological Change: An Empirical
Exploration,” Quarterly Journal of Economics, vol. 118, no. 5, November 2003, pp. 1279-1333.
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• keeping demand stable for those low-skilled workers who perform non-routine
manual tasks (e.g., truck drivers and home health care aides); and
• decreasing demand for the many medium-skilled workers who perform routine
tasks (e.g., administrative support and factory workers).
They estimated that this pattern of job growth has produced substantial earnings gains among
workers in the top quartile (25%) of the distribution. Workers in the bottom quartile were found to
have experienced slower gains than workers in the top quartile. Nonetheless, wage growth of the
bottom quartile appears to have exceeded that of workers in the middle of the earnings
distribution.31
Two less often mentioned explanations for the increase in U.S. income inequality are the
declining role of labor unions and labor standards in wage-setting and the changing demographics
of the population. Some analysts have offered evidence of inconsistencies in the data that do not
support the skill-biased technological change (SBTC) explanation32 and have argued that changes
over time in economic institutions and social norms have played a part as well (e.g., the value of
the federal minimum wage, the progressivity of income tax rates, and the bargaining power of
labor unions).33 Others have examined changes over time in the U.S. age structure, racial and
ethnic composition, and household living arrangements (e.g., away from married-couple families
and toward single adult households).34
International Comparisons of Income Distributions
Cross-country comparisons of income distributions provide another perspective on the extent of
inequality in the United States. Measures of income differ from one country to the next. For this
reason, researchers typically use data made more comparable by the Luxembourg Income Study
(LIS) project or by the Organisation for Economic Cooperation and Development (OECD).35
Researchers who analyzed LIS data from the mid-1970s to 2000 agree that the comparatively
high level of inequality in the United States has been in place for quite some time and that the
United States was among those countries that experienced the largest increases in inequality over
the 25-year period.36 They found the most equal distributions of disposable household income
31 David H. Autor, Lawrence F. Katz, and Melissa S. Kearney, “Trends in Wage Inequality: Revising the Revisionists,”
Review of Economics and Statistics, vol. 90, no. 2 (May 2008), pp. 300-323.
32 David Card and John E. DiNardo, “Skill-Biased Technological Change and Rising Wage Inequality: Some Problems
and Puzzles,” Journal of Labor Economics, vol. 20 (October 2002), pp. 733-783.
33 Frank Levy and Peter Temin, Inequality and Institutions in 20th Century America, National Bureau of Economic
Research, Working Paper 13106, Cambridge, MA, May 2007.
34 Gary Burtless, “Demographic Transformation and Economic Inequaltiy,” in The Oxford Handbook of Economic
Inequality, ed. Wiemer Salverda, Brian Nolan, and Timothy M. Smeeding (NY: Oxford University Press, 2009), pp.
435-454.
35 The LIS and OECD use as their common measure disposable household money income. Disposable household
income starts with market income, which includes earned income from wages, salaries, and self-employment as well as
other cash income from private sources (e.g., property, private pensions, and child support). Public transfer payments
(e.g., for old-age, sickness and disability, maternity and family support, unemployment, housing, and food) are added to
market income. From this estimate of gross income, personal income tax and workers’ social security contributions are
subtracted to arrive at disposable cash income. This after-tax after-transfer income is then adjusted for household size.
36 Anthony B. Atkinson, Lee Rainwater, and Timothy M. Smeeding, Income Distribution in OECD Countries:
(continued...)
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over the lengthy period were in Scandinavia, Central Europe and Southern Europe, while most
English-speaking countries consistently had the highest levels of inequality. Between the mid-
1970s and 2000, Sweden, Finland and Norway appear to have experienced the smallest increases
in inequality while the United States, the United Kingdom and Italy seemingly experienced the
largest increases. The United States also was estimated to have had the most persistent increase in
inequality from the mid-1970s to 2000. In contrast, the researchers found that the rate at which
inequality increased in other industrialized nations generally slowed in the later years of the
period.
LIS income distribution measures for the mid-2000s for several industrialized nations are
presented in Table 2.The countries are listed in order from lowest Gini coefficient (most equal
distribution) to highest (most unequal distribution). According to this measure, the United States
ranked among the industrialized countries with the most unequal distributions of disposable
(after-tax after cash transfers) household income in the mid-2000s. The comparatively high
degree of income inequality in the United States is evident from the 90-10 and 90-50 ratios as
well. As indicated by the 90-10 ratio, those at the top of the U.S. income distribution had more
than five times the income of those near the bottom. Those at the top of the U.S. distribution also
had about twice the income of the typical household, as indicated by the 90-50 ratio.
Table 2. Summary Measures of Disposable Household Income Distributions for
Selected Countries in the Mid-2000s
Country Year
Gini
Coefficient
P90 /P10
P90 /P50
Denmark
2004 0.228 2.778 1.562
Slovenia
2004 0.231 2.920 1.650
Sweden
2005 0.237 2.821 1.625
Finland
2004 0.256 3.071 1.708
Norway
2004 0.256 2.865 1.604
Netherlands 2004 0.266 3.018 1.737
Austria
2004 0.269 3.232 1.787
Germany
2004 0.278 3.445 1.823
France
2005 0.280 3.528 1.842
Australia
2003 0.312 4.241 1.983
Poland
2004 0.315 4.022 1.959
Canada
2004 0.318 4.379 1.957
Greece
2004 0.327 4.374 2.027
Italy
2004 0.340 4.440 2.029
(...continued)
Evidence From the Luxembourg Income Study, Organisation for Economic Co-operation and Development, 1995;
Timothy Smeeding, Changing Income Inequality in OECD Countries: Updated Results from the Luxembourg Income
Study, Luxembourg Income Study, Working Paper 252, March 2000; Timothy M. Smeeding, Public Policy and
Economic Inequality: The United States in Comparative Perspective, Luxembourg Income Study, Working Paper 367,
February 2004; and Andrea Brandolini and Timothy M. Smeeding, “Patterns of Economic Inequality in Western
Democracies: Some Facts on Levels and Trends,” Political Science and Politics, vol. 39, no. 1 (2006), pp. 21-26.
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Country Year
Gini
Coefficient
P90 /P10
P90 /P50
United
Kingdom
2004 0.344 4.411 2.137
United
States 2004 0.370 5.506 2.126
Mexico
2004 0.457 8.468 2.945
Colombia
2004 0.506 11.254 3.334
Source: Luxembourg Income Study, Inequality Key Figures, downloaded on 12/23/2011 from
http://www.lisdatacenter.org.
Note: Disposable household income is market income (e.g., earnings, self-employment income, pensions, rent,
and dividends) plus public transfer payments (e.g., old-age and unemployment insurance, maternity and family
support) less personal income tax payments and workers’ social security contributions, adjusted for size of
household.
With virtually no change between the mid and late 2000s in the ranking of countries by extent of
inequality in disposable household income, the United States was again among the nations with
the most unequal distributions (see Gini coefficients in Table 2 and Table 3).37 U.S. income
inequality in the late 2000s surpassed the average for the 20 founding member countries of the
OECD (see Table 3).
Disposable household income inequality in the developed countries of the OECD, including those
listed in Table 3, has generally trended upward since the mid-1980s.38 While inequality in the
United States increased by slightly more than the OECD20 average during the mid-1980s to mid-
1990s period, the increase in U.S. inequality was considerably greater relative to the OECD
average from the mid-1990s to late 2000s (see the last columns of Table 3). Changes in U.S. tax
policy initiated in the early 2000s, which have reduced the taxes paid by higher income tax filers
to a greater extent than lower income tax filers, may help to explain the above-average increase in
income inequality in the United States in recent years.39
Table 3. Summary Measure of Disposable Household Income Distributions for
Selected Countries in the Late 2000s and Change from Mid-1980s to Late 2000s
Percentile Point Change
Country Gini
Coefficienta
Mid-1980s to Mid-1990s
Mid-1990s to Late 2000s
Slovenia 0.236 n.a.
n.a.
Denmark 0.248 -0.6
3.3
Norway 0.25 2.1
0.7
Finland 0.259 2.1
3.2
Sweden 0.259 1.4
4.8
Austria 0.261 n.a.
2.7
37 As much as data availability allow, the countries presented in Table 3 are the same as those in Table 2. Differences
tend to be very small between Gini coefficients by country for comparable time periods estimated from either the
OECD or LIS databases.
38 OECD, Divided We Stand: Why Inequality Keeps Rising, December 2011, 388 pp.
39 CRS Report R42131, Changes in the Distribution of Income Among Tax Filers Between 1996 and 2006: The Role of
Labor Income, Capital Income, and Tax Policy, by Thomas L. Hungerford.
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Percentile Point Change
Country Gini
Coefficienta
Mid-1980s to Mid-1990s
Mid-1990s to Late 2000s
France 0.293 -2.3
1.6
Netherlands 0.294
2.5
-0.3
Germany 0.295 1.5
3.0
Poland 0.305 n.a.
n.a.
Greece 0.307 0.0
-2.8
Canada 0.324 -0.4
3.5
Australia 0.336 n.a.
2.7
Italy 0.337
3.9 -1.1
United Kingdom
0.345
2.7
0.9
United States
0.378
2.3
1.8
Mexico 0.476 6.6
-4.3
Chile 0.494
n.a. -3.3
OECD20b 0.316
2.1
0.5
Source: OECD, Divided We Stand: Why Inequality Keeps Rising, December 5, 2011, p. 45.
Notes: Disposable household income is market income (e.g., earnings, self-employment income, pensions, rent,
and dividends) plus public transfer payments (e.g., old-age and unemployment insurance, maternity and family
support) less personal income tax payments and workers’ social security contributions, adjusted for size of
household. n.a. = not available.
a. The Gini coefficients are for 2008, except for Chile (2009) and Denmark (2007).
b. The OECD20 are the founding countries: Austria, Belgium, Canada, Denmark, France, Germany, Greece,
Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, Turkey, the
United Kingdom, and the United States.
Explaining Cross-Country Differences in the
Distribution of Income
Commonly offered reasons for international differences in income inequality fall into three
categories. First, many other countries devote a much larger share of their national output (gross
domestic product, GDP) to income transfers, which have an equalizing effect on the distribution
of income. Second, tax rates in these countries vary with respect to progressivity, and thus have
different effects on the distribution of after-tax income. Third, equality in the distribution of
earnings, which make up the majority of household income, varies substantially from one country
to another.
Smeeding estimated a strong correlation between the income share of those at the low end of the
distribution and the share of GDP accounted for by transfer payments. His analysis suggests that
given the amount of money transferred to households in the United States and the United
Kingdom, those at the low end of their respective income distributions do not benefit as much
from transfers as low-income households in other countries. From this Smeeding concluded that
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transfer payments are not as well targeted at low-income households in the United States as they
are in many other nations.40
The OECD estimated that public cash transfers and household taxes (i.e., income tax payments
and social security contributions) substantially reduce inequality between market income and
disposable income. These government policies were found to have lowered income inequality by
one-fourth on average in the mid-2000s. The redistributive effect of public cash transfers and
household taxes was smaller than average in the United States. While transfer payments were
found to have reduced inequality by twice as much as taxes on average in OECD countries, the
opposite was true in the United States; that is, income tax payments and social security
contributions were more responsible than government cash transfers for reducing inequality in the
United States.41
When in-kind benefits (e.g., health insurance, education, child and elder care) and indirect taxes
(e.g., sales, value-added and property) are taken into account, cross-country differences in
inequality at the low end of the distribution are reduced. This again points to the importance of
the definition of income when estimating inequality. Garfinkel, Rainwater, and Smeeding
estimated that in the United States cash transfers to those at the bottom of the income distribution
are comparatively small while in-kind benefits are substantial.42
Differences between countries’ labor market institutions and policies appear to affect the shape of
the earnings distribution, particularly for those in the bottom half. It has been suggested that the
more centralized or coordinated process of wage-setting in several countries (e.g., Germany)
helps to explain the wage compression toward the bottom of their earnings distributions
compared with that of the United States.43 This may be due, in part, to higher private sector
unionization rates in some other industrialized countries and a larger share of their workers being
affected by union agreements whether or not they are union members. The decrease in union
density in the United States and United Kingdom between 1973 and 1998 may have accounted
for 3% of the increase in male wage inequality in the United States and 5% in the United
Kingdom, for example.44 Comparatively greater union bargaining power (or higher minimum
wages) also may have caused firms in other countries to pay low skilled workers wage rates
above their contribution to output.45 This, in turn, may have prompted these foreign companies to
adopt technologies that raised the productivity of their less skilled employees rather than adopt
technologies biased in favor of high skilled workers as has occurred in the United States.
40 Timothy M. Smeeding, “U.S. Income Inequality in a Cross-National Perspective: Why Are We So Different?,” in
James A. Auerbach and Richard S. Belous (ed), The Inequality Paradox: Growth of Income Disparity, National Policy
Association, Washington, D.C., 2008.
41 OECD, Growing Unequal? Income Distribution and Poverty in OECD Countries, October 2008, 310 pp.
42 Irwin Garfinkel, Lee Rainwater, and Timothy Smeeding, “A Re-examination of Welfare States and Inequality in
Rich Nations: How In-kind Transfers and Indirect Taxes Change the Story,” Journal of Policy Analysis and
Management, vol. 25, no. 4 (2006), pp. 897-919.
43 Gottschalk and Smeeding, “Cross-National Comparisons of Earnings and Income Inequality,” Journal of Economic
Literature, vol. 31, no. 2 (June 1997) pp. 633-687.
44 Winfried Koeniger, Marco Leonardi, and Luca Nunziata, “Labor Market Institutions and Wage Inequality,”
Industrial and Labor Relations Review, vol. 60, no. 3 (April 2007), pp. 340-356.
45 Daron Acemoglu, “Cross-Country Inequality Trends,” The Economic Journal, vol. 113, no. 485 (February 2003), pp.
F121-149.
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Income Mobility in the United States
To the extent that greater equality in the distribution of income results from policy decisions
about taxes and transfers, for example, and not from market forces, that equality may have been
achieved at some cost (e.g., slower economic growth). Assuming the costs are recognized, the
willingness to incur them may reflect varying degrees of concern across countries about income
inequality. The results of a study that compared the relationship between individuals’ perceptions
of their well-being and the extent of inequality in the United States and Europe suggest that
inequality in the distribution of income is less important to people in the United States due to
Americans believing that they live in a comparatively mobile society.46 That is to say, Americans
may be less concerned about inequality in the distribution of income at any given point in time
partly because of a belief that everyone has an equal opportunity to move up the income ladder. A
review of the literature suggests that Americans’ perceptions about their likelihood of changing
position in the income distribution may be exaggerated.
Intergenerational Mobility
Intergenerational elasticity (IGE) measures how persistent position in the income distribution is
from one generation to the next. IGE is a single number that indicates the extent to which parents’
position in the income distribution explains their adult children’s relative income. The lower the
elasticity, the less likely inequality is to be perpetuated from one generation to the next; that is,
the more mobile the society.
Empirical analyses have estimated a strong positive relationship—about 0.5—between parent and
adult child income in the United States.47 An IGE of 0.5 suggests that if the income of a child’s
parents was 30% higher than the average income of families in the parents’ generation, then the
child’s income will be 15% above the average for his/her generation. In other words, in the
United States, about 50% of the (dis)advantage of growing up in a (low) high income family may
be inherited.
The Trend in Intergenerational Mobility in the United States
It is difficult to precisely answer the question of whether the importance of parents’ relative
income to adult children’s relative income changed over the period that inequality has been
increasing in the United States. This is partly the case because few sources cover multiple
generations of adults for which data are available on family income at the time they were
children. As described more fully below, empirical analyses suggest that children born into low-
income families have not become more likely and may have become less likely to surpass their
parents’ position at the bottom of the income distribution. Put differently, mobility in the United
States does not appear to have offset the increase in cross-sectional inequality in recent decades.
46 Alberto Alesina, Rafael Di Tella, and Robert MacCulloch, “Inequality and Happiness: Are Europeans and Americans
Different?,” Journal of Public Economics, vol. 88 (2004), pp. 2009-2042.
47 Isabel V. Sawhill, “Trends in Intergenerational Mobility,” in Getting Ahead or Losing Ground: Economic Mobility in
America, ed. Julia B. Isaacs, Isabel V. Sawhill, and Ron Haskins (Washington, DC: The Brookings Institution, 2008),
112 pp.
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Lee and Solon used data from the Panel Study of Income Dynamics (PSID) for children born
between 1952 and 1975 who reached age 25 between 1977 and 2000 to estimate IGEs. They
found no major change during the two decades in the influence of parent income on adult sons’
incomes. The IGE in each year was estimated to be within 0.1 percentage point of the 0.44
average over the 1980s and 1990s.48 Hertz, who also relied on the PSID but used a variety of
estimation methods, similarly found no substantial change in mobility among cohorts of male and
female children born between 1952 and 1975 when observed as adults starting in the late 1970s.49
Levine and Mazumder used an entirely different methodology than the aforementioned
economists whose research also was based on longitudinal data. Levine and Mazumder examined
the incomes of brothers from two cohorts in the National Longitudinal Surveys (NLS). The older
group was composed of brothers who entered the labor market during the 1970s; the younger
group, brothers who entered the labor market between the early 1980s and mid-1990s. They
estimated that family background, as represented by correlations between sibling incomes, was
more important to the economic outcomes of the younger cohort (which entered the workforce
after 1980).50 Specifically, the correlation between brothers’ incomes doubled from 0.21 for the
older group to 0.42 for the younger group. From this marked increase in the correlation, Levine
and Mazumder infer that intergenerational mobility decreased substantially at some point
between 1983 and 1995.51
Aaronson and Mazumder took yet another approach because they used decennial census data
which, although it allowed them to cover a longer period, does not follow the same individuals
over time as do the PSID and NLS.52 They estimated that movement between generations from
one part of the income distribution to another increased over the 1940-1980 period.
Intergenerational mobility then decreased substantially during the 1980s and appears to have
remained unchanged during the 1990s. This pattern suggests that the opportunity for children in
the United States to attain incomes that exceed their parents’ relative incomes was lower after
1980 compared to the preceding four decades.53 In a more recent article, Mazumder concluded
that his research with Aaronson “and the studies using the PSID are in broad agreement that
intergenerational mobility has been roughly flat since 1990.”54
48 Chul-In Lee and Gary Solon, “Trends in Intergenerational Income Mobility,” Review of Economics and Statistics,
vol. 91 (2009), pp. 766-772.
49 Tom Hertz, “Trends in the Intergenerational Elasticity of Family Income in the United States,” Industrial Relations,
vol. 46, no. 1 (January 2007), pp. 22-50.
50 Levine and Mazumder acknowledge that the correlation captures more than family background (e.g., neighborhood
influence), but estimate that a large majority of the correlation may result from parent income.
51 David I. Levine and Bhashkar Mazumder, “The Growing Importance of Family: Evidence from Brothers’ Earnings,”
Industrial Relations, vol. 46, no. 1 (January 2007), p. 7-21.
52 They created “synthetic families” by linking children’s birth year and residence to the average income of parents in
the same state in an earlier decennial census.
53 Daniel Aaronson and Bhashkar Mazumder, “Intergenerational Economic Mobility in the United States, 1940 to
2000,” Journal of Human Resources, vol. 43, no. 1 (2008), pp. 139-172.
54 Bhashkar Mazumder, Is Intergenerational Economic Mobility Lower Now than in the Past?, The Federal Reserve
Bank of Chicago, Essays on Issues, Number 297, April 2012, p. 3.
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Cross-Country Comparisons of Intergenerational Mobility
Analysts have developed estimates of intergenerational mobility that use differing statistical
approaches and are based on the longitudinal surveys and administrative records available in each
country. The cross-country estimates usually are derived from earnings of fathers and their adult
sons because data on daughters and other sources of income are more limited in countries other
than the United States. Although the rank of the United States differs somewhat from one study to
the next, as discussed below, the United States typically is found to be among the least mobile of
the advanced economies.
Corak reviewed numerous studies that offered differing estimates of intergenerational income
persistence for each of several advanced economies. Based on his assessment of the preferred
IGE for the nations in the meta-analysis, Corak concluded that the United States, the United
Kingdom, and France are the least mobile. In these countries, about 40% to 50% of the economic
advantage high-earning young men have over lower earners may be due to their coming from
more affluent families. In the cases of Canada, Finland, Norway, and Denmark, the effect of
fathers’ on adult sons’ relative earnings was found to be lower at about 20% or less. With IGEs of
about 30%, mobility in Germany and Sweden falls between these two groups.55
Jantti et al. developed comparable intergenerational samples for six countries from which they
derived estimates of intergenerational mobility at different points in the joint distribution of father
and son earnings. The estimation of transition matrices allowed them to compare mobility rates
from one quintile to another in the distribution. The researchers found that the United States has
less upward mobility from the bottom quintile and more low-income persistence than the United
Kingdom and Nordic countries (Denmark, Finland, Norway, and Sweden) included in their
analysis. The authors suggest that, despite these results, Americans have been able to maintain the
perception of living in a mobile society because transition rates of the middle three quintiles are
similar in the United States and other advanced economies. “In the U.S., such middle class moves
are associated with fairly substantial changes in real living standards (i.e., measured in actual
dollars earned) ... [that] are experienced or witnessed by a substantial fraction of the U.S.
population.”56
Intragenerational Mobility
Much the same results are evident when it comes to intragenerational mobility in the United
States. The likelihood of adults moving from their initial positions in the income distribution has
decreased or been unchanged in recent decades, according to available empirical analyses.
Bradbury used data from the PSID to analyze family income mobility for working-age married
couples over the 1969-2006 period. The various measures of mobility she developed indicate that
family income mobility declined between 1969 and 2006, and particularly since the 1980s.
Families, whether they started at the bottom or top of the income distribution, became
increasingly less likely to move up or down the income ladder during their working lives.
55 Miles Corak, Do Poor Children Become Poor Adults? Lessons from a Cross Country Comparison of Generational
Earnings Mobility, Institute for the Study of Labor (IZA), IZA Discussion Paper 1993, Bonn, Germany, March 2006.
56 Markus Jantti, Knut Roed, and Robin Naylor et al., American Exceptionalism in a New Light: A Comparison of
Intergenerational Earnings Mobility in the Nordic Countries, the United Kingdom and the United States, Institute for
the Study of Labor (IZA), IZA Discussion Paper 1938, Bonn, Germany, January 2006, p. 28.
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Bradbury concluded that “family income mobility has been insufficient to stem increases in
inequality of long-term income.”57
Acs and Zimmerman used PSID data to determine the trend in income mobility among 25-44
year olds between 1989 and 2004. They estimated that intragenerational mobility among young
adults has been stable since the 1980s. For example, slightly over one-half of 25-44 year olds
were in the lowest quintile of the income distribution in both the 1984-1994 and 1994-2004
periods. About one-fourth of those in the bottom quintile moved up to the second quintile in the
1984-1994 period, the same share also moved up in the following 10-year period. Similarly, in
both 1984-1994 and 1994-2004, about 10% of those in the bottom quintile were able to move into
the middle quintile of the income distribution; 7%, to the fourth quintile; and 4%, to the top
quintile. Mobility rates from the higher quintiles into the bottom quintile also were little changed
over time: 20%-22% of those in the second quintile were downwardly mobile in the 1984-1994
and 1994-2004 periods, while 11%-15% of those in the middle quintile fell to the bottom quintile;
6%-7% from the fourth quintile dropped to the bottom as did 3%-4% from the top quintile. These
patterns led Acs and Zimmerman to conclude that “in the context of rising income inequality,
stable mobility rates suggest that the distribution of lifetime income must be growing unequal.
That is, lifetime or long-term economic inequality is rising.”58
Auten and Gee used panel data from income tax returns to examine mobility over the past two
decades among tax units aged 25 and older. They similarly found that mobility was about the
same in most income quintiles between the 1987-1996 and 1996-2005 periods. Auten and Gee
also estimated a slight decrease in overall mobility, with 58.3% of individuals changing quintiles
in 1987-1996 compared to 57.5% in 1996-2005. They found that the entire difference resulted
from less downward mobility out of the top 20%.59
Diaz-Gimenez et al. used PSID data to analyze household income mobility between the 1989-
1994 (five-year) and 2001-2007 (six-year) periods. They estimated that income mobility was little
changed, but the six-year span of the more recent period suggested a decrease in mobility.60 Diaz-
Gimenez et al. also found less income mobility among households at the bottom and top of the
income distribution compared to households in the middle three quintiles. As suggested above by
Jantti with regard to cross-country intergenerational mobility, the comparatively high
intragenerational mobility of a majority of U.S. households (the middle 60%) may partly account
for the seeming misperception among Americans that the United States is a very mobile society.
Burkhauser and Couch reviewed the limited literature on intragenerational mobility in the United
States and several other countries (e.g., the United Kingdom, Germany, France, Denmark, and
Sweden). Their meta-analysis led them to conclude that there does not appear to be a clear
relationship between the extent of income inequality and intragenerational income mobility. In
57 Katharine Bradbury, Trends in U.S. Family Income Mobility, 1969-2006, Federal Reserve Bank of Boston, Working
Paper 11-10, October 20, 2011, p. 27.
58 Gregory Acs and Seth Zimmerman, U.S. Intragenerational Economic Mobility From 1984 to 2004: Trends and
Implications, The Pew Charitable Trusts, Economic Mobility Project, October 2008, p. 12.
59 Gerald Auten and Geoffrey Gee, “Income Mobility in the United States: New Evidence from Income Tax Data,”
National Tax Journal, vol. LXII, no. 2 (June 2009), p. 313.
60 Diaz-Gimenez et al., Distributions of Earnings, Income, and Wealth.
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addition, most of the studies found that the majority of cross-sectional (short-term) inequality
appears to persist over time.61
Concluding Remarks
Measures of the distribution of income across U.S. households show a distribution that is
relatively unequal compared to other developed countries and a distribution that has become more
so in recent decades as high-income households benefitted disproportionately from economic
growth. It also appears that going from rags to riches is relatively rare; that is, where one starts in
the income distribution greatly influences where one ends up. Whether due to skill-biased
technological change, globalization or other factors, it commonly is thought that the dampened
income prospects of low- and middle-skill workers and their children relative to those in high-
skilled households are a cause for concern. Some policy measures that may impact the
distribution of income include those that involve education and training, the tax code, and a
variety of transfer and spending programs.
Author Contact Information
Linda Levine
Specialist in Labor Economics
llevine@crs.loc.gov, 7-7756
61 Richard V. Burkhauser and Kenneth A. Couch, “Intragenerational Inequality and Intertemporal Mobility,” in The
Oxford Handbook of Economic Inequality, ed. Wiemer Salverda, Brian Nolan and Timothy M. Smeeding (New York:
Oxford University Press, 2009), pp. 522-545.
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