Class warfare has always been a mainstay
of liberal politics. Politicians frequently depict the United
States as a nation starkly divided between the rich and poor. For
example, vice presidential candidate John Edwards decries "two
Americas...one privileged, the other burdened...one America that
does the work, another that reaps the reward. One America that pays
the taxes, another America that gets the tax breaks."
How
accurate is this characterization? How unequal is the distribution
of economic resources in our society? This paper will attempt to
answer these questions. Specifically, it will seek to provide:
- A clearer understanding of the existing
level of income equality in U.S. society, and
- An appreciation of the social and economic
forces contributing to existing inequality.
Census Figures on Income Distribution
This
paper analyzes the existing distribution of income in the United
States. The term "income" refers to new revenues and economic
resources received by individuals and families during the course of
a year. The
distribution of annual income is thus distinct from the
distribution of wealth, which refers to economic assets saved from
prior years.
Discussions of income distribution usually
begin with annual data provided by the Census Bureau. To measure
income distribution, the Census Bureau first ranks households from
highest to lowest income. It then divides society into five groups,
called quintiles, and determines the share of total income received
by each quintile.
On
the surface, the Census figures appear lucid and easily
understandable. However, the conventional Census data are marred by
four problems that lead to an overstatement of the level of
economic inequality:
- Conventional Census income figures are
incomplete and omit many types of cash and non-cash income.
- The conventional Census figures do not
take into account the equalizing effects of taxation.
- The Census quintiles actually contain
unequal number of persons, a fact that greatly magnifies the
apparent level of economic inequality.
- Differences in income are substantially
affected by large differences in the amount of work performed
within each quintile, yet these differences in work effort are
rarely acknowledged.
An Accurate Picture of the Distribution of
Economic Resources
This
paper analyzes the distribution of income in the United States
based on data taken from the Census Bureau's Current Population
Survey (CPS) from March 2003 (covering incomes for 2002). Income distribution
data change very little from one year to the next; therefore, the
conclusion reached in this paper would apply with little change for
incomes in 2003.
The
paper presents data on income distribution in four separate
stages:
- Stage
1: Conventional money income distribution.
- Stage
2: Incorporation of the effect of taxes and social welfare
benefits.
- Stage
3: Adjustment of quintiles to contain equal numbers of
persons.
- Stage
4: Hypothetical equalization of work and employment
between the quintiles.
Stage 1: Conventional Income Distribution
Data
As
noted, the Census presents income distribution by dividing U.S.
households into five groups or quintiles. The share of total income
going to each quintile is then determined. The conventional
quintile distribution of income for 2002 is shown in Chart 1. In
that year, the Census reported that the top or most affluent
quintile had 49.7 percent of income, while the bottom quintile had
only 3.5 percent. Thus, the top fifth of households is shown to
have 14.3 times more income than the bottom fifth.
Stage 2: Impact of taxes and Non-Cash
Benefits on Economic Equality
The
conventional Census income distribution data are based on the
concepts of "money income." Money income includes earnings,
interest, dividends, rents, Social Security retirement benefits,
pension or retirement income, survivors' benefits, disability
benefits, veterans' benefits, workers' compensation, alimony, and
some cash welfare benefits.
Despite this list, it is now widely
acknowledged that the Census money income figures grossly
underreport the economic resources available to the American
people. For example,
the aggregate "money income" figures reported by the Census in 1996
equaled only 70 percent of the comparable personal income figures
reported in the Commerce Department's National Income and
Production Accounts (NIPA), which serve as the basis for measuring
gross national product.
Increasingly, Americans receive "non-cash"
incomes that are not included in the Census income distribution
figures based on "money income." For example, many Americans
receive health insurance from their employers. Such insurance is an
important augmentation to salaries. Families who have health
coverage are clearly better off, ceteris paribus, than those who
must pay health costs out of pocket.
Similarly, the poor and the elderly
receive extensive and costly non-cash benefits from the government.
In 2002, the government spent $522 billion on means-tested aid to
the poor and the near poor. This aid included cash, food, housing,
medical care, and social services such as subsidized day care.
Virtually none of this assistance was included in the Census income
distribution figures. In the same year, the government spent $257
billion subsidizing medical care for the elderly through the
Medicare program; this assistance was also ignored in the Census
income distribution figures.
The
social safety net represents a massive transfer of economic
resources away from affluent families and toward the less affluent.
Each year, the government taxes higher-income families and
transfers economic resources to the poor and elderly through
means-tested welfare and Medicare. Overall, the resources
transferred in this manner are over $750 billion per year, or more
than 8 percent of total personal income. Yet almost none of this
massive redistribution of economic resources is recorded in the
conventional Census income distribution figures shown in stage
1.
Fortunately, the Census Bureau's annual
Current Population Survey (CPS) collects data on taxes and on the
receipt of many additional types of income beyond those included
under "money income." While these additional income data are
excluded from the Census' conventional (stage 1) income
distribution figures, which are based on "money income" only, they
are available to researchers in electronic form. We have used these
excluded data as the basis for the analyses provided in this
paper.
Table 1 shows the effects of incorporating
a more complete count of income and taxes on the distribution of
income. Adjustments to income are presented in sub-stages. First,
capital gains and losses are added (stage 2A). This adjustment
raises total annual income by some $320 billion and increases
income inequality. Next, employee health benefits and government
non-cash transfers are added (stage 2B). Government transfers
include the earned income tax credit, food stamps, school lunch
programs, public housing, Medicaid, and Medicare. Medicaid and
Medicare benefits are counted at their insurance or market value,
which equals the average government expenditures on benefits to
individuals in specific age and risk categories. These adjustments
add nearly $700 billion to the total annual income and decrease
income inequality. Finally, the effects of federal income tax,
state income tax, and Social Security taxes are shown in stage 2C.
This adjustment reduces annual total income by some $1.4 trillion
and markedly decreases inequality. We term the income figures in
stage 2C "comprehensive post-tax income."
Inclusion of taxes and non-cash aid
substantially reduces economic inequality. In stage 1, the bottom
quintile was shown to have 3.5 percent of total income; by stage
2C, this number had risen to 5.35 percent. The income share of the
top quintile falls from 49.6 percent in stage 1 to 46.16 percent in
stage 2C.
Stage 3: Adjustment of Quintiles to
Contain Equal Numbers of Persons
When
decision-makers, journalists, and the public view the government's
official income distribution figures, there is a common and
implicit assumption that the quintiles contain equal shares of the
population. After all, the notion that we should measure
"inequality" by comparing the aggregate income of groups that are
themselves unequal in size is at best confusing. However, as noted,
the official Census income "quintiles" do not contain equal shares
of the population, and this fact skews the Census' measure of
income distribution.
No
one would think it valid to measure inequality between New York
State and Delaware by simply comparing the aggregate incomes in the
two states. In such a comparison, income differences would mainly
reflect vast differences in state populations. But the Census makes
precisely this sort of unbalanced comparison whenever it compares
quintiles of unequal size.
Chart 3 shows the percent of the
population contained within each Census "quintile." While the
middle quintile does contain roughly one-fifth of the population,
the others do not. The high disparity in population between the
highest and lowest income quintiles is of particular interest. The
top quintile contains 24.6 percent of the population, but the
bottom quintile contains only 14.3 percent. In raw numbers, there
are 69.4 million persons in the top quintile compared to 40.3
million in the bottom. Thus, for every person in the lowest
quintile there are 1.7 persons in the top quintile. This imbalance
in population is a major factor contributing to the apparent levels
of inequality in Census Bureau figures.
The
Census Bureau quintiles are unequal in size because they are based
on a count of households rather than persons. A household is
defined as a person or group of persons living in a single housing
unit. In the United States, high-income households tend to be
married couples with many members and earners. Low-income
households tend to be single persons with little or no earnings.
Thus, it should be of no surprise that the average household in the
Census' top quintile contains 3.2 persons, while the average
household in the bottom quintile contains 1.8 persons.
The
typical Census practice of measuring inequality by comparing
aggregate incomes between "quintiles" that contain widely differing
numbers of persons can be extremely misleading. To a considerable
degree, the relative poverty of the Census' official bottom
quintile shown in Chart 1 results from the simple lack of people
within the quintile rather than from economic factors.
A
far clearer picture of income inequality can be obtained by
adjusting the quintiles so that each actually contains 20 percent
of the population. In Chart 4, incomes have been corrected to
include taxes and non-cash benefits, and the quintiles are adjusted
to contain equal numbers of persons. As a result, the income share
of the bottom quintile rises to 9.4 percent of total income and the
share of the top quintile falls to 39.6 percent.
Stage 4: Inequality of Income and
Inequality of Work
Counting taxes and safety net benefits
while balancing the quintiles to contain equal shares of the
population dramatically transforms the picture of inequality in the
United States. However, it is possible to probe the issue even
further.
In many respects, economic inequalities between the
quintiles are a direct reflection of disparities in work performed.
Chart 5 reverts to the conventional Census quintiles with unequal
numbers of persons. The chart shows the total annual hours of paid
labor in each quintile. In 2002, individuals in the bottom quintile
performed 4.3 percent of all the work in the U.S. economy, while
those in the top quintile performed 33.9 percent. Thus, the top
quintile performed almost eight times as much labor as did the
bottom quintile.
In
part, the low levels of paid employment in the bottom quintile
reflect the low numbers of working-age adults (ages 18 to 64)
within the group. In the conventional Census figures (with unequal
quintiles), the bottom quintile contains only 11.2 percent of all
working-age adults, while the top quintile contains 27.6 percent.
Not only does the bottom quintile contain fewer adults of working
age, but each adult, on average, works fewer hours during the year
than does his counterpart in the higher-income quintiles. On
average, working-age adults in the bottom quintile worked about
half as many hours during the year as did adults in the top
quintile. The combination of relatively few working-age adults and
low levels of work per adult contributes significantly to the low
income levels in the bottom quintile.
The
stage 4 analysis shows what the distribution of income would be if
working-age adults in the bottom quintile worked as many hours as
those in higher-income families. In contrast to the adjustments in
stages 2 and 3, stage 4 represents a hypothetical rather than an
actual condition, since the non-elderly adults in the bottom
quintile clearly do not work as much as higher-income adults.
The
stage 4 figures incorporate the adjustments made in stages 2 and 3
before making the hypothetical adjustments in hours of work. The
results are presented in Chart 6. The working-age adults in each
quintile are assumed, on average, to perform equal hours of paid
labor during the year. The outcome would be a substantial
equalization of incomes. The income share of the bottom quintile
would rise to 12.3 percent, while that of the top quintile would
fall to 35.8 percent.
Ratio of Incomes Between the Top
and Bottom Quintiles
Chart 7 summarizes the ratios of income of
the top quintile compared to the bottom quintile in various
scenarios. In the conventional figures from stage 1, households in
the top quintile appear to have, on average, $14.30 of income for
each $1.00 of income in the bottom quintile. When the impact of
taxes and non-cash benefits is included in stage 2, the ratio falls
to $8.60 in the top for each $1.00 in the bottom. If the quintiles
are then corrected to contain equal numbers of persons, the ratio
falls to $4.21 to $1.00. Finally, if the annual work levels of
working-age adults in each quintile were hypothetically made equal,
the income ratio of the top to the bottom would fall to $2.91 to
$1.00.
Increasing Inequality?
A
frequent complaint is that the distribution of income is becoming
less equal over time. There is some merit to this charge: According
to conventional Census numbers, the income share of the top fifth
of households rose from 43.7 percent of total income in 1980 to
49.7 percent in 2002. But nearly all of that increase occurred in
the 1980s and mid-1990s. For the past five years, the distribution
of income has remained static, as charts 8 and 9 show. A tiny
increase in the income share of the top quintile corresponds to a
small increase in the share of population and total work occurring
within the quintile. After adjusting quintiles to contain equal
numbers of persons, the top quintile in 1997 had $4.22 in post-tax,
post-benefit income for every $1.00 of similar income at the
bottom. In 2002,
the ratio was $4.21 to $1.00.
The
conventional Census figures also suggest that the incomes of the
two poorest quintiles have fallen over the past 30 years. The
Census reports that in 1970, the two poorest quintiles had 14.9
percent of all money income. By 2002, the figure had fallen to 12.3
percent. However, this apparent decline is a result of the
exclusion of non-cash benefits from the count of income.
Means-tested welfare and Medicare has risen greatly over time, from
1.5 percent of total personal income in 1950 to over 8 percent in
2002. If these benefits were properly included in the income count,
the income share of the two poorest quintiles would be shown to
have risen considerably in the 1960s and to have remained
relatively unchanged over the past 30 years.
Conclusion
The
Census income distribution figures are the foundation of most
class-warfare rhetoric. On the surface, these figures show a high
level of inequality: The top fifth of households have $14.30 of
income for every $1.00 at the bottom.
However, these figures are flawed by the
exclusion of taxes and social safety net spending and by the fact
that the "fifths" do not contain equal numbers of people.
Adjustment for these factors radically alters the picture of income
distribution: The top fifth of the population has $4.21 of income
for every $1.00 at the bottom.
The
remaining inequality in society is heavily influenced by the lack
of work at the bottom. If working-age adults in the lower quintiles
worked as much as their higher-income counterparts, the income
disparity of the top to the bottom quintiles would fall to $2.91 to
$1.00.
Still, the top fifth of U.S. households
(with incomes above $84,000) remain perennial targets of
class-warfare enmity. These families, however, perform a third of
all labor in the economy. They contain the best educated and most
productive workers, and they provide a disproportionate share of
the investment needed to create jobs and spur economic growth.
Nearly all are married-couple families, many with two or more
earners. Far from shirking the tax burden, these families pay 82.5
percent of total federal income taxes and two-thirds of federal
taxes overall. By contrast, the bottom quintile pays 1.1 percent of
total federal taxes.
In
one sense, John Edwards is correct: There is one America that works
a lot and pays a lot in taxes, and there is another America that
works less and pays little. However, the reality is the opposite of
what Edwards suggests. It is the higher-income families who work a
lot and pay nearly all the taxes. Raising taxes even higher on
hard-working families would be unfair and, by reducing future
investments, would reduce economic growth, harming all Americans in
the long run.
Robert
Rector is Senior Research Fellow in Domestic Policy
Studies, and Rea S. Hederman,
Jr., is a Senior Policy Analyst in the Center for Data
Analysis, at The Heritage Foundation.
Methodological
Appendix
This
paper examines the distribution of income and income inequality
with data extracted from the Current Population Survey for the year
2002, conducted in March 2003. Like the Census Bureau, this paper
studies income at the household level. Group quarters are not
included in this survey. The authors also used data extracted from
the Heritage Income Tax Model, which contains a sample of actual
tax returns designed to replicate the total tax returns received by
the Internal Revenue Service. In general, this study does not
account for the underreporting of income to the Census Bureau.
Post-Tax Income
Comprehensive post-tax income includes
money income plus realized capital gains, the earned income credit,
employer-provided health insurance, school lunch benefits, food
stamp benefits, government rent subsidies, Medicaid, and Medicare
benefits. Federal and state income taxes, payroll taxes, and
property taxes are subtracted. Income variables that were given
only at the family or person level were aggregated to the household
level. Thus, all FICA taxes paid by a household were added together
by person and then subtracted from the household's final income.
Food stamps and other family-level income data were treated in the
same manner.
Comprehensive post-tax income is very
similar to the Census income "definition 14" as detailed in the
Census Bureau's Current Population Reports, Income, poverty and
Valuation on Noncash Benefits, except that it employs the basic
market or insurance value for Medicaid and Medicare without the
"fungible" adjustment. The insurance value of Medicaid and
Medicare (also called the market value) equals the average net
government outlay for persons of a specific risk class within a
given state. The risk classes used are elderly, disabled persons,
non-disabled adult, and non-disabled child. Under this approach,
the value of Medicaid or Medicare equals the average cost to the
government of medical services provided to a given class of
persons; it does not report specific medical expenditures for
particular individuals.
The
fungible method of valuing Medicare and Medicaid begins with the
insurance value of benefits but then alters the values based on the
family's income class. The full insurance value is assigned to
benefits received by the middle class, but a lower value or zero
value is assigned when the same benefits are received by a
low-income household. The fungible adjustment was devised for the
measurement of poverty, not income distribution. In measuring
poverty, it is used to determine whether a household's income
should be considered above the poverty threshold. However, the
fungible adjustment, which deliberately reduces the value of
benefits received by low-income groups, is not appropriate for the
measure of income equality that seeks to compare the economic
resources of one household relative to others. The fungible
adjustment results in a substantial undercounting of government
transfers to low income groups.
Top Coding
An
adjustment was made to compensate for the Census' top coding
restriction. Top coding limits the maximum value of capital gains
reported in the CPS to $99,999. With normal CPS data, capital gains
values that exceed this limit are simply reported as $99,999. In
order to obtain a more thorough estimate of high levels of capital
gains income, we have replaced those capital gains values subject
to the top coding restriction with higher values taken from
Internal Revenue Service data. This adjustment was made in the
following manner: The Heritage Tax Model was used to determine the
mean amount of capital gains income for those returns that reported
capital gains income above $99,999. The new mean amount of capital
gains was substituted to replace each CPS top-coded value of
capital gains. As a result, the amount of capital gains income in
the study was increased substantially. These adjustments mainly
increase reported incomes in the top quintile.
Ranking
Adjustments to income in stages 2 and 3
were performed at the level of individual households. After each
adjustment, the households were re-ranked based on their new income
figures. Households then were weighted according to the CPS
household weight variable. The stage 4 adjustments are more
general; earnings were adjusted at the quintile level based the
aggregate earnings and average labor data within the quintile.