Order Code RL33835
Real Earnings and the Distribution
of Earnings, 1995-2005
January 24, 2007
Gerald Mayer
Economic Analyst
Domestic Social Policy Division

Real Earnings and the Distribution of
Earnings, 1995-2005
Summary
Real earnings and the distribution of earnings are indicators of a nation’s
economic well-being. Changes in the level of real earnings (i.e., actual earnings
adjusted for inflation) show how the standard of living has changed over time.
Changes in the distribution of earnings show how the relative standards of living of
different individuals or families have changed over time.
When studying changes in earnings it is useful to compare years when overall
labor market conditions are similar. The civilian unemployment rate was 5.6% in
1995 and 5.5% in 2004. (Although annual data are available for 2005, the
unemployment rate was 5.1%.) A study of earnings can examine the earnings of all
workers
(i.e., full-time and part-time, part-year and full-year) or, to try to control for
changes in annual hours worked, the earnings of full-time, year-round workers.
From 1995 to 2004, real weekly earnings increased for workers across the
earnings distribution. Most of this growth occurred between 1995 and the recession
year of 2001. Although men earned more than women, the earnings gap between
men and women narrowed from 1995 to 2004.
Among all workers, real earnings increased more at the top and bottom of the
distribution than in the middle. Some analysts describe this phenomenon as the
“hollowing out” of the middle of the distribution. The hollowing out occurred among
men, but not women. Two factors may help explain the hollowing out of the
distribution. First, from 1995 to 2004, the average workweek of lower-wage workers
increased relative to the average workweek of workers in the middle of the
distribution. Second, the average hourly wage of lower-wage workers increased
relative to the average hourly wage of workers in the middle of the distribution. In
both cases, these increases occurred mainly between 1995 and 2001.
Among full-time, year-round workers at the bottom and middle of the earnings
distribution, the growth in earnings was more evenly distributed than at the top of the
distribution. Among the highest paid workers, the growth in earnings was
approximately double the growth for other workers.
Between 1995 and 2004, earnings equality appears to have peaked in 1999. The
distribution of weekly earnings among all workers differed from the distribution
among full-time, year-round workers. Among all workers, inequality declined
slightly from 1995 to 2004. But, during the period, inequality declined from 1995
to 1999, before increasing from 1999 to 2004. In contrast, inequality increased
among full-time, year-round workers from 1995 to 2004. Inequality increased
because the top 5% of earners received a larger share of total earnings, while workers
in the middle of the distribution received a smaller share of total earnings.
Some evidence suggests that earnings inequality declined after the 2001
recession until 2004. This report will be updated periodically.

Contents
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Definition of Earnings and Unit of Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 2
Summary of Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Policies to Increase Real Earnings
or Reduce Inequality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Real Earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Productivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Economic Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Inequality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Indirect Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Direct Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Tradeoff with Economic Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Macroeconomic Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
The Trend in Real Weekly Earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
All Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Hollowing Out of the Earnings Distribution . . . . . . . . . . . . . . . . . . . . 10
Full-Time, Year-Round Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
The Distribution of Weekly Earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Gini Coefficient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
All Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Full-Time, Year-Round Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
The Trend in the Share of Total Earnings by Quintile . . . . . . . . . . . . . . . . . 19
All Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Full-Time, Year-Round Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Measures of Inequality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Gini Coefficient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Share of Total Earnings by Quintile . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Data and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
CPI-U-RS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Topcoded Earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Confidence Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
List of Figures
Figure 1. Percentage of Full-Time Workers and Full-Time, Year-Round
Workers, 1995-2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Figure 2. Real Weekly Wages, All Workers, 1995-2005 . . . . . . . . . . . . . . . . . . . 9
Figure 3. Real Weekly Wages, Men, 1995-2005 . . . . . . . . . . . . . . . . . . . . . . . . 10
Figure 4. Real Weekly Wages, Women, 1995-2005 . . . . . . . . . . . . . . . . . . . . . . 11
Figure 5. Real Weekly Wages, Full-Time, Year-Round Workers, 1995-2005 . . 12

Figure 6. Real Weekly Wages, Full-Time, Year-Round Workers, Men,
1995-2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Figure 7. Real Weekly Wages, Full-Time, Year-Round Workers, Women,
1995-2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Figure 8. Gini Coefficient for All Workers, 1995-2005 . . . . . . . . . . . . . . . . . . . 18
Figure 9. Gini Coefficient for Full-Time, Year-Round Workers, 1995-2005 . . 18
Figure 10. Illustration of Lorenz Curves and Gini Coefficients for Two
Groups of Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
List of Tables
Table 1. The Trend in Real Weekly Wages: All Workers, 1995-2005 . . . . . . . . 8
Table 2. The Trend in Real Weekly Wages: Full-Time, Year-Round Workers,
1995-2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Table 3. Gini Coefficients for All Workers and for Full-Time, Year-Round
Workers, 1995-2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Table 4. Share of Total Weekly Earnings, All Workers, 1995-2005 . . . . . . . . . 21
Table 5. Share of Total Weekly Earnings, Full, Time, Year-Round Workers,
1995-2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Real Earnings and the Distribution of
Earnings, 1995-2005
Introduction
Real earnings and the distribution of earnings are indicators of a nation’s
economic well-being. Changes in the level of real earnings (i.e., actual earnings
adjusted for inflation) show how the standard of living has changed over time.
Changes in the distribution of earnings show how the relative standards of living of
different individuals or families have changed over time.
The level of real earnings is related to several policy issues, including saving
and investment, research and development, education, healthcare, and trade. The
distribution of earnings is related to issues such as taxation, income redistribution,
education and training for lower-skilled workers, the cost of higher education,
minimum wage, and immigration.
This report examines the trends in real earnings and the distribution of earnings
in the United States from 1995 to 2005.1 When studying changes in earnings, it is
appropriate to compare years when overall labor market conditions are similar. The
civilian unemployment rate was 5.6% in 1995 and 5.5% in 2004.2 In both years, the
unemployment rate was falling after short recessions (in 1990-1991 and 2001,
respectively). Therefore, in this report, the analysis focuses on changes in real
earnings and the distribution of earnings from 1995 to 2004. But, since data for 2005
are the most recent annual data available, the report also shows earnings for 2005.
The report provides separate analyses for men and women.
This report analyzes individual earnings. A study of individual income or of
family earnings or income may reach different conclusions.3 The report does not
review research on the causes of changes in inequality.4
1 In addition to real earnings and the distribution of earnings, economists also study earnings
mobility, or how the earnings of a given sample of workers change over time. A study of
earnings mobility may provide different results than the findings in this report.
2 In 2005, the civilian unemployment rate was 5.1%, below the levels of 1995 or 2004.
3 Earnings account for the largest share of individual and family income. In 2005, annual
earnings accounted for 82.1% of total income for individuals 16 and over and 81.9% of total
family income.
4 A hearing before the House Committee on Ways and Means included some discussion of
the causes of changes in equality. U.S. Congress, House, Committee on Ways and Means,
Hearing on the Economy, Jan. 23, 2007, available at [http://waysandmeans.house.gov].

CRS-2
Definition of Earnings and Unit of Analysis
The results of an analysis of real earnings and the distribution of earnings may
be affected by the definition of earnings, whose earnings are studied (e.g., all
workers, full-time workers, or prime-age workers), the measure of inequality, and the
time period studied.
Earnings are payments that individuals receive for their labor services.
Individuals may be paid for a period of time worked (e.g., an hourly wage) or the
quantity of goods or services produced (e.g., a piece rate). Individuals may also
receive a salary, which is a given amount paid every week or month, or other time
period. Earnings may be defined as cash wages or as total compensation. The latter
consists of cash wages plus fringe benefits such as employer-provided health
insurance, paid vacations, or employer contributions to a retirement plan.
The results of an analysis of individual earnings may differ from a study of
individual income or family earnings or income.5 Many individuals and families
receive cash or in-kind benefits from sources other than work (e.g., interest,
dividends, rent, cash welfare assistance, refundable tax credits, or in-kind benefits
such as food, housing, or healthcare). Some families have more wage earners than
other families.
This report analyzes individual weekly earnings, where earnings consist of cash
wages before taxes or other deductions. Individual earnings consist of total annual
earnings from all jobs. Weekly earnings are annual earnings divided by the number
of weeks worked. The analysis includes wage and salary workers and self-employed
workers who are ages 16 or older. Because there are differences in the labor market
characteristics of men and women, the earnings of men and women are analyzed
separately.6 The analysis uses data from the March Current Population Survey
(CPS), which is a household survey conducted by the Census Bureau for the Bureau
of Labor Statistics (BLS). An explanation of the data and methodology used in this
report is provided in the Appendix.
Finally, the report analyzes the earnings of two groups of workers: (1) all
workers and (2) persons employed full-time, year-round. Full-time workers are
persons who work 35 or more hours a week. Persons who work year-round are
persons who work 50 or more weeks a year.
5 For analyses of the distribution of household income, see CRS Report RS20811, The
Distribution of Income
, by Brian W. Cashell; CRS Report RL32639, Inequality in the
Distribution of Income: Trends and International Comparisons
, by Brian W. Cashell; and
U.S. Department of Commerce, Bureau of the Census, Income, Poverty, and Health
Insurance Coverage in the United States: 2003
, P 60-226, Aug. 2004, pp. 27-33.
6 In general, women tend to work fewer hours per week than men, spend less time in the
labor force, and enter and leave the labor force more often than men. The distribution of
women by occupation and industry also differs from men. See CRS Report 98-278 E, The
Gender Wage Gap and Pay Equity: Is Comparable Worth the Next Step?
by Linda Levine.

CRS-3
Analyzing the earnings of full-time, year-round workers helps control for
changes in hours worked per week, temporary and seasonal employment, and spells
of unemployment.7 As the economy expanded after the 1990-1991 recession, the
percentage of workers employed full-time increased from 78.8% in 1995 to 81.0%
in 2000. During the same period, the percentage of workers employed full-time,
year-round increased from 63.2% to 67.5%. After the 2001 recession, these
percentages leveled off.8 (See Figure 1.)
Figure 1. Percentage of Full-Time Workers and
Full-Time, Year-Round Workers, 1995-2005
Source: Calculated by CRS from the March Current Population Survey (CPS).
Summary of Findings
! From 1995 to 2004, real earnings increased for workers at all
earnings levels. Most of the growth occurred between 1995 and the
recession year of 2001. Although men earned more than women, the
earnings gap narrowed over the 10-year period.
! Among all workers, real earnings increased more at the top and
bottom of the earnings distribution. Some analysts call this
phenomenon the “hollowing out” of the middle of the earnings
7 In 1995, full-time, year-round workers worked an average of 43.8 hours a week. In 2001
it was 43.4 hours, where it stayed through 2004.
8 For a discussion of the economic recovery following the 2001 recession, see CRS Report
RL32047, The ‘Jobless Recovery’ From the 2001 Recession: A Comparison to Earlier
Recoveries and Possible Explanations
, by Marc Labonte and Linda Levine.

CRS-4
distribution. The hollowing may have been due, in part, to an
increase in the average workweek (i.e., the average number of hours
worked) and in the average hourly wage of lower-wage workers
relative to workers in the middle of the distribution.
! Among full-time, year-round workers in the bottom and middle of
the earnings distribution, the growth in real earnings was more
evenly distributed than at the top of the distribution. Among the
highest paid workers, the growth in earnings was approximately
double the growth for other workers.
! Among all workers, inequality declined slightly from 1995 to 2004.
During the period, however, inequality fell from 1995 to 1999,
before increasing from 1999 to 2004.
! Among full-time, year-round workers, inequality increased from
1995 to 2004. Inequality increased because the top 5% of earners
received a larger share of total earnings, while workers in the middle
of the distribution received a smaller share of total earnings.
! Some evidence suggests that inequality declined after the recession
in 2001 until 2004.
Policies to Increase Real Earnings
or Reduce Inequality
A variety of policy options are available to increase real earnings or reduce
earnings inequality. Policies to increase real earnings may differ from policies to
reduce inequality. In some cases, the policies may conflict.
Real Earnings
Productivity. Real earnings rise with increased productivity. Productivity
may rise with greater saving (private and public), more capital investment per
worker, more investment in human capital (e.g., education, training, and healthcare),
and advances in technology. Technological innovation may include improved
equipment, the introduction of new products, or improved methods of production,
transportation, and communication.
Economic Efficiency. Another way to increase real earnings is to improve
what economists call economic efficiency. According to standard economic theory,
competitive markets generally result in the most efficient allocation of resources,
where resources consist of individuals with different skills, capital goods (e.g.,
computers, machinery, and buildings), and natural resources. A more efficient
allocation of resources generally results in a higher standard of living; that is, greater
total output and consumer satisfaction.

CRS-5
Economic efficiency can be improved with a greater exchange of goods (e.g.,
trade) and a better allocation of labor and capital (e.g., neutral tax policies, migration,
or the deregulation of labor, product, or other markets).
Inequality
Inequality may be reduced using either direct or indirect policies. Direct
policies include income transfer programs. Indirect policies consist of programs that
improve the income-producing human capital (e.g., education, training, or healthcare)
of lower-skilled workers. Policies to reduce inequality may involve a tradeoff,
however, with policies to improve economic efficiency.9
Indirect Policies. Inequality can be reduced with policies that reduce the
relative supply of less-skilled labor, increase the relative supply of skilled labor, or
both. Such policies may include increased investment in early childhood education,
improved education from kindergarten through high school, greater adult education,
and improved access to health care for lower income workers and families.
Inequality may also be reduced by increasing the relative supply of college-educated
workers; for example, policies that lower the cost of higher education or increase
educational assistance to lower income students. Some policies may be more cost
effective than others.

9 The literature on the causes of inequality is extensive. These causes are reviewed in Frank
Levy and Richard J. Murnane, “U.S. Earnings Levels and Earnings Inequality: A Review
of Recent Trends and Proposed Explanations,” Journal of Economic Literature, v. 30, Sept.
1992, pp. 1354-1371; George E. Johnson, “Changes in Earnings Inequality: The Role of
Demand Shifts,” Journal of Economic Perspectives, v. 11, spring 1997, pp. 41-54; Robert
H. Topel,”Factor Proportions and Relative Wages: The Supply-Side Determinants of Wage
Inequality,” Journal of Economic Perspectives, v. 11, spring 1997, pp. 55-74; Nicole M.
Fortin and Thomas Lemieux, “Institutional Changes and Rising Wage Inequality: Is There
a Linkage?” Journal of Economic Perspectives, v. 11, spring 1997, pp. 75-96; Yolanda K.
Kodrzycki, “Labor Markets and Earnings Inequality: A Status Report,” New England
Economic Review
, May/June 1996, pp. 11-24; CRS Report 98-441 E, Is Globalization the
Force Behind Recent Poor U.S. Wage Performance? An Analysis
, by Craig K. Elwell; and
Sheldon Danziger and Peter Gottschalk, America Unequal (Cambridge, MA: Harvard
University Press, 1995), pp. 127-148. For a discussion of the effect of changes in the real
value of the minimum wage on the distribution of earnings, see David S. Lee,”Wage
Inequality in the United States During the 1980s: Rising Dispersion or Falling Minimum
Wage?” The Quarterly Journal of Economics, v. 114, Aug. 1999, pp. 977-1023.

CRS-6
Direct Policies. Income inequality may also be reduced through income
redistribution programs. These programs include policies such as progressive
taxation — including refundable tax credits like the Earned Income Tax Credit
(EITC) or the Child Tax Credit (CTC). They also include in-kind transfers; for
example, of food, housing, and healthcare.
Tradeoff with Economic Efficiency. Competitive markets may allocate
resources efficiently, but they may result in a distribution of earnings that some
policymakers find unacceptable. Thus, policies to reduce inequality may involve a
tradeoff with improved economic efficiency. Some economists argue that a higher
minimum wage, easier union recognition procedures, or different trade policies may
reduce inequality. Other economists argue that these policies may reduce total
economic output and may not have a significant impact on inequality. Similarly,
some economists argue that progressive taxation and income redistribution programs
may harm economic efficiency. For example, progressive taxation may discourage
saving and investment. Transfer payments or other forms of nonlabor income may
reduce the supply of labor (i.e., they may affect decisions to work or how much to
work).
Macroeconomic Policies. The findings in this report indicate that earnings
inequality fell in the mid- to late 1990s as the economy expanded and the
unemployment rate fell. Therefore, fiscal and monetary policies that reduce and
maintain low unemployment may also affect the degree of inequality. Fiscal policy
consists of government choices that affect spending and revenue. Monetary policy
consists of actions by the Federal Reserve Bank that affect money supply and interest
rates.
The Trend in Real Weekly Earnings
The remainder of this report provides a detailed description of the findings.
This section examines the trend in real weekly earnings from 1995 to 2004.
Nominal, or actual, earnings are adjusted for inflation using the Consumer Price
Index for All Urban Consumers, adjusted to take into account the current methods
for measuring price changes (CPI-U-RS). An explanation of this index is provided
in the Appendix.
This section shows the trend in real earnings for workers at the 20th, 40th, 60th,
80th, and 95th percentiles. If weekly earnings are arranged from lowest to highest,
workers at the 20th percentile earn more than 20% of workers, workers at the 40th
percentile earn more than 40% of workers, and so on.
All Workers
The trend in real weekly earnings for all workers from 1995 to 2005 is shown
in Table 1. Separately, the table also shows the trend in real weekly earnings for
men and women. Figures 2, 3, and 4 provide graphical representations of the
findings in Table 1.

CRS-7
From 1995 to 2004, real weekly earnings increased for workers at all
percentiles. (See Table 1.) The increases were greater, however, at the lower and
upper ends of the distribution than in the middle of the distribution. For example,
earnings increased by 14.2% at the 20th percentile and by 12.8% at the 95th percentile,
but by 9.4% at the 60th percentile. Some analysts call this phenomenon the
“hollowing out” of the middle of the earnings distribution.
Table 1 also shows three differences in the real weekly earnings of men and
women. First, at each percentile, the real weekly earnings of men are greater than the
earnings of women. For example, in 2004, men at the 20th percentile had real
earnings of $336 a week, compared to $219 for women. At the 60th percentile men
and women earned $835 and $596, respectively. At the 95th percentile, men earned
$2,475 a week, compared to $1,550 a week for women.

CRS-8
Table 1. The Trend in Real Weekly Wages: All Workers, 1995-2005
Percent
Percentile
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Change,
1995 to 2004
A. All Workers
20th Percentile
$235
$238
$243
$253
$264
$272
$276
$271
$266
$268
$277
14.2%
40th Percentile
$416
$429
$438
$460
$451
$472
$475
$480
$486
$477
$481
14.7%
60th Percentile
$636
$643
$663
$690
$677
$698
$707
$726
$714
$696
$700
9.4%
80th Percentile
$978
$977
$1,003
$1,035
$1,081
$1,090
$1,082
$1,086
$1,102
$1,093
$1,100
11.7%
95th Percentile
$1,761
$1,787
$1,866
$1,886
$1,982
$1,984
$2,098
$2,088
$2,041
$1,987
$2,046
12.8%
B. Men
20th Percentile
$294
$298
$311
$324
$336
$340
$334
$334
$336
$336
$335
14.4%
40th Percentile
$514
$524
$548
$575
$563
$567
$573
$585
$571
$576
$577
12.2%
60th Percentile
$783
$780
$816
$828
$852
$852
$848
$835
$849
$835
$831
6.6%
80th Percentile
$1,174
$1,191
$1,189
$1,242
$1,284
$1,308
$1,272
$1,303
$1,327
$1,292
$1,300
10.0%
95th Percentile
$2,094
$2,144
$2,286
$2,300
$2,343
$2,376
$2,439
$2,505
$2,449
$2,475
$2,500
18.2%
C. Women
20th Percentile
$186
$191
$194
$207
$215
$218
$221
$226
$222
$219
$231
17.8%
40th Percentile
$322
$334
$350
$359
$360
$386
$386
$397
$403
$397
$385
23.3%
60th Percentile
$489
$500
$515
$552
$563
$567
$573
$585
$592
$596
$577
21.9%
80th Percentile
$758
$762
$793
$805
$834
$872
$848
$868
$884
$878
$885
15.8%
95th Percentile
$1,272
$1,310
$1,348
$1,387
$1,464
$1,482
$1,544
$1,538
$1,571
$1,550
$1,538
21.9%
Source: Calculated by CRS from the March Current Population Survey (CPS).
Note: Weekly earnings are in 2005 dollars.

CRS-9
Second, from 1995 to 2004, the earnings gap between men and women
narrowed. For women at the 20th percentile, real weekly earnings increased by
17.8%, compared to a 14.4% increase among men.10 At the 60th percentile, the real
earnings of women increased by 21.9%, compared to 6.6% for men. At the 95th
percentile women’s earnings increased by 21.9%, compared to an increase of 18.2%
for men.
Third, the hollowing out of the earnings distribution observed among all
workers was due to differences between men and women in the growth of earnings.
For women, the growth in earnings was more evenly distributed than among men.
The biggest difference between men and woman was at the 60th percentile, where the
real earnings of women increased by 21.9%, compared to a 6.6% increase for men.
Figure 2. Real Weekly Wages, All Workers, 1995-2005
Finally, much of the wage growth from 1995 to 2004 occurred before the
recession year of 2001. For example, Table 1 shows that, for workers at the 20th
percentile, real weekly earnings increased by 17.4% from 1995 to 2001, and fell by
2.7% from 2001 to 2004. At the 60th percentile, real earnings increased by 11.1%
from 1995 to 2001, but fell by 1.6% from 2001 to 2004. At the 95th percentile, real
wages increased by 19.1% from 1995 to 2001, then fell by 5.3% from 2001 to 2004.
10 In Tables 1 and 2 weekly earnings are rounded to the nearest dollar. The percentage
changes shown were calculated using unrounded weekly earnings. Therefore, calculations
based on rounded earnings may be different from those shown.


CRS-10
Although the peak years differed, the pattern was similar for men and women
— except for women at the 60th percentile, whose real weekly earnings increased
steadily throughout the period from 1995 to 2004 (before falling in 2005). (Compare
Figures 3 and 4.)
Figure 3. Real Weekly Wages, Men, 1995-2005
Hollowing Out of the Earnings Distribution. Table 1 shows that for all
workers, and for men, the earnings at the top and bottom of the distribution increased
more than earnings in the middle of the distribution. Therefore, there may have been
a hollowing out of the middle of the earnings distribution. This hollowing out may
have been due, in part, to two factors. First, from 1995 to 2004, the average
workweek of lower-wage workers increased relative to the average workweek of
workers in the middle of the earnings distribution. Second, the average hourly wage
of lower-wage workers increased relative to the average hourly wage of workers in
the middle of the distribution.
From 1995 to 2000, the average workweek of workers in the first quintile
increased by 1.2 hours — from 26.5 hours to 27.7 hours, before falling to 27.1 hours
in 2004. In the middle three quintiles the average workweek did not change.11 It was
40.8 hours in 1995 and 2000 and 40.7 hours in 2004.
From 1995 to 2004, the average real hourly wage of workers in the first quintile
increased by 18.3% (from $6.21 to $7.35), compared to a 12.1% increase (from
$14.22 to $15.93) for workers in the middle three quintiles. Most of the increase
11 Although there is no official definition of “middle class,” some analysts define the middle
class as the middle three quintiles of earners.

CRS-11
(16.4%) in the average real hourly wage in the first quintile occurred between 1995
and the recession year of 2001.
Figure 4. Real Weekly Wages, Women, 1995-2005
Thus, to some extent, the hollowing out of the earnings distribution from 1995
to 2004 may have been due to improved economic conditions during the 1990s. As
the economy expands and the unemployment rate falls, the average workweek often
rises and the relative earnings of lower-wage workers often increase relative to the
earnings of other workers.12 An increase in the basic federal minimum wage in 1996
and 1997 may also have had an effect on the real hourly wage of lower-wage
workers.13 On the other hand, following welfare reform in 1996, the employment of
single mothers increased significantly.14
Full-Time, Year-Round Workers
Table 2 shows the trend in real weekly earnings for workers who worked full-
time, year-round from 1995 to 2005. Figures 5, 6, and 7 provide graphical
representations of the data in Table 2.
12 To increase output, employers may hire more workers, but they may also ask current
workers to work more hours.
13 The basic federal minimum wage was raised from $4.25 to $4.75 an hour in October 1996
and to $5.15 an hour in September 1997.
14 Among other things, the Personal Responsibility and Work Opportunity Reconciliation
Act of 1996 (P.L. 104-193) set a time limit on cash welfare assistance and imposed greater
work requirements on welfare recipients. CRS Report RL32760, Temporary Assistance for
Needy Families (TANF) Block Grant: Responses to Frequently Asked Questions
, by Gene
Falk.

CRS-12
From 1995 to 2004, the growth in real weekly earnings of full-time, year-round
workers differed from the growth of real earnings for all workers in two ways. First,
for full-time, year-round workers, there was no hollowing out of the earnings
distribution. From 1995 to 2004, real earnings at the lower and middle percentiles
increased by 6.0% to 8.3%. (See Table 2.) Second, at the 95th percentile, the
increase in real earnings (14.6%) was approximately double the growth in earnings
at the other percentiles.
In other ways, the growth in real earnings of full-time, year-round was similar
to the growth in earnings for all workers. At each percentile, men earned more than
women. For example, in 2004, men at the 20th percentile earned $462 a week,
compared to $380 for women. At the 60th percentile men had real weekly earnings
of $962, compared to $703 a week for women. At the 95th percentile, men earned
$2,673 a week, and women earned $1,673 a week.
In addition, from 1995 to 2004, the earnings gap narrowed between men and
women who worked full-time, year-round. For women at the 20th percentile, real
weekly earnings increased by 10.3%, compared to 3.8% for men. At the 60th
percentile, the real earnings of women increased by 10.3%, compared to 8.3% for
men. At the 95th percentile the earnings of women increased by 21.9%, compared to
an increase of 14.8% for men.15
Figure 5. Real Weekly Wages, Full-Time, Year-Round Workers,
1995-2005
15 At the 40th percentile, the real wages of men increased more than the wages of women;
9.4% and 6.2%, respectively.

CRS-13
Table 2. The Trend in Real Weekly Wages: Full-Time, Year-Round Workers, 1995-2005
Percent
Percentile
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Change,
1995 to 2004
A. All Full-Time, Year-Round Workers
20th Percentile
$382
$386
$397
$414
$405
$414
$424
$418
$408
$410
$404
7.3%
40th Percentile
$563
$572
$583
$598
$605
$610
$615
$626
$612
$596
$596
6.0%
60th Percentile
$778
$781
$812
$805
$822
$828
$848
$835
$828
$827
$827
6.3%
80th Percentile
$1,101
$1,141
$1,166
$1,150
$1,194
$1,199
$1,230
$1,253
$1,224
$1,192
$1,231
8.3%
95th Percentile
$1,908
$1,906
$1,983
$2,070
$2,153
$2,180
$2,121
$2,192
$2,245
$2,186
$2,250
14.6%
B. Men
20th Percentile
$440
$450
$466
$460
$459
$458
$467
$459
$469
$457
$462
3.8%
40th Percentile
$636
$643
$676
$690
$676
$680
$679
$689
$694
$696
$673
9.4%
60th Percentile
$881
$903
$933
$920
$946
$968
$954
$939
$959
$954
$962
8.3%
80th Percentile
$1,258
$1,263
$1,283
$1,349
$1,352
$1,417
$1,378
$1,461
$1,429
$1,391
$1,394
10.6%
95th Percentile
$2,251
$2,263
$2,332
$2,300
$2,478
$2,616
$2,545
$2,609
$2,612
$2,584
$2,673
14.8%
C. Women
20th Percentile
$342
$347
$350
$345
$355
$362
$382
$376
$371
$378
$380
10.3%
40th Percentile
$487
$476
$490
$506
$507
$523
$530
$522
$531
$517
$520
6.2%
60th Percentile
$631
$643
$653
$690
$676
$680
$700
$710
$714
$696
$703
10.3%
80th Percentile
$881
$885
$910
$920
$937
$952
$957
$994
$1,020
$994
$1,000
12.8%
95th Percentile
$1,370
$1,429
$1,423
$1,495
$1,557
$1,526
$1,591
$1,628
$1,653
$1,669
$1,673
21.9%
Source: Calculated by CRS from the March Current Population Survey (CPS).
Note: Weekly earnings are in 2005 dollars.


CRS-14
Finally, like the real earnings of all workers, much of the gain in earnings of
full-time, year-round workers occurred between 1995 and the recession in 2001. For
example, for workers at the 20th percentile, real weekly wages increased by 11.1%
from 1995 to 2001, and fell by 3.4% from 2001 to 2004. At the 60th percentile, real
wages increased by 9.0% from 1995 to 2001, but fell by 2.5% from 2001 to 2004.
At the 95th percentile, however, real earnings increased steadily from 1995 to 2004.16
Although the peak years differed, the pattern was similar for men and women. For
men, there was some leveling off in the growth in earnings at the 95th percentile.
(Compare Figures 6 and 7.)
Figure 6. Real Weekly Wages, Full-Time, Year-Round
Workers, Men, 1995-2005
Source: Calculated by CRS from the March Current Population Survey (CPS).
16 Table 2 shows that, at the 95th percentile, real wages increased steadily from 1995 to
2003, before falling in 2004. But this decrease may have been a function of survey
respondents rounding off their earnings. In both 2003 and 2004, nominal annual earnings
(i.e., unadjusted for inflation) at the 95th percentile were $110,000.

CRS-15
Figure 7. Real Weekly Wages, Full-Time, Year-Round
Workers, Women, 1995-2005
Source: Calculated by CRS from the March Current Population Survey (CPS).
The Distribution of Weekly Earnings
This section examines the trend in the distribution of weekly earnings from 1995
to 2004. Different measures of inequality provide different information and can lead
to different conclusions about the trend in the distribution of earnings. Most measures
identify whether inequality differs between groups or has changed over time. But
some measures may not reveal how inequality differs between groups or has changed.
This report uses two measures of inequality: the Gini coefficient and the share of
total weekly earnings received by each quintile (or fifth) of workers. Together, the
two measures indicate whether the distribution of earnings changed and, if so, how
it changed.
Gini Coefficient
The Gini coefficient is a measure of earnings equality that ranges from 0 to 1.
If the earnings of all individuals are the same, the Gini coefficient is equal to 0,
representing complete equality. If one worker receives all the earnings and all other
workers receive zero earnings, the Gini coefficient is equal to 1. Thus, a larger
coefficient indicates a greater degree of inequality. More information on the Gini
coefficient is provided in the Appendix.

CRS-16
Table 3 shows Gini coefficients for all workers and for full-time, year-round
workers for the period 1995 to 2005. The results in Table 3 are shown graphically
in Figures 8 and 9.
All Workers. The top panel of Table 3, and Figure 8, show that, for all
workers, from 1995 to 2004 inequality did not change significantly; that is, the
decline in the Gini coefficient (from 0.474 to 0.467) was not statistically significant.17
However, inequality declined from 1995 to 1999, and then increased from 1999 to
2004. The pattern was the same for men and women, except that for women the
decline in inequality occurred from 1995 to 2000. Inequality among women increased
after 2000, but declined again after the recession in 2001.
Full-Time, Year-Round Workers. Table 3 shows that the distribution of
earnings among full-time, year-round workers was more equal than among all
workers. Unlike the distribution of earnings among all workers, however, the bottom
panel of Table 3, and Figure 9, shows that, for full-time, year-round workers,
inequality increased from 1995 to 2004. For men, inequality declined from 1995 to
1999, and increased from 1999 to 2004. For women, inequality generally increased
throughout the period from 1995 to 2004.
17 Unless stated otherwise, the comparisons discussed in this section of the report are
significant at either the 95% or 90% confidence levels. See Appendix for an explanation
of confidence levels.

CRS-17
Table 3. Gini Coefficients for All Workers and for Full-Time,
Year-Round Workers, 1995-2005
Year
Total
Men
Women
A. All Workers
1995
0.474
0.468
0.444
1996
0.464
0.458
0.435
1997
0.466
0.460
0.436
1998
0.466
0.458
0.444
1999
0.453
0.444
0.428
2000
0.467
0.469
0.425
2001
0.471
0.466
0.447
2002
0.472
0.475
0.433
2003
0.468
0.464
0.446
2004
0.467
0.466
0.437
2005
0.475
0.479
0.439
B. Full-Time, Year-Round Workers
1995
0.387
0.396
0.331
1996
0.393
0.400
0.342
1997
0.391
0.399
0.339
1998
0.390
0.397
0.343
1999
0.380
0.384
0.337
2000
0.402
0.415
0.339
2001
0.406
0.415
0.359
2002
0.402
0.414
0.349
2003
0.398
0.407
0.356
2004
0.402
0.414
0.354
2005
0.407
0.421
0.355
Source: Calculated by CRS from the March Current Population Survey (CPS).

CRS-18
Figure 8. Gini Coefficient for All Workers, 1995-2005
Source: Calculated by CRS from the March Current Population Survey (CPS).
Figure 9. Gini Coefficient for Full-Time, Year-Round
Workers, 1995-2005
Source: Calculated by CRS from the March Current Population Survey (CPS).

CRS-19
The Trend in the Share of Total Earnings by Quintile
The Gini coefficient shows whether the distribution of earnings has become
either more or less equal. But it does not show where the distribution may have
changed. To examine where the earnings distribution may have changed, this section
shows the share of total weekly earnings received by each quintile (or fifth) of
workers.
Tables 4 and 5 show the share of total weekly earnings received by each
quintile of workers from 1995 to 2005. In this report, the top quintile of earners is
separated into two groups: the top 5% of earners and the top 81% to 95% of earners.
The Appendix provides more information on this measure of equality.

All Workers. Among all workers, inequality declined from 1995 to 2004.
(See Table 4.) Inequality declined because the share of total weekly earnings
received by the lowest quintile of workers increased by 5.8%, while the share of
earnings received by the top 5% of earners declined by 2.9%. However, the
improvement in inequality occurred mainly between 1995 and 1999. Inequality
increased from 1999 to 2004.18 Between 1999 and 2004, however, the increase in
inequality may have occurred mainly between 1999 and the recession in 2001. For
example, from 2001 to 2004, the share of earnings received by the top 5% of earners
decreased by 3.6%.19
From 1995 to 2004, there were some differences in the distribution of earnings
of men and women in the middle of the distribution. The share of earnings received
by men in the middle three quintiles increased from 1995 to 1999, then decreased
from 1999 to 2004. Among women there was no change over the 10-year period in
the share of earnings received by the middle three quintiles. For both men and
women, earnings among the top 5% of earnings decreased from 1995 to 1999, then
increased from 1999 to 2004.
Full-Time, Year-Round Workers. Like the Gini coefficient, the
calculations in Table 5 show that, from 1995 to 2004 inequality increased among
full-time, year-round workers. Inequality increased because the top 5% of earners
received a greater share of earnings, while the share of earnings received by the third
and fourth quintiles decreased. The share of earnings received by the lowest and
second quintiles did not change. The increase in inequality occurred mainly from
1999 to 2004. Again, most of the increase may have occurred between 1999 and the
18 For example, the earnings shares received by the two lowest quintiles increased from 1995
to 1999, but were unchanged from 1999 to 2004. The shares of earnings received by the
third and fourth quintiles, as well as by the top 81% to 95% of earners, increased from 1995
to 1999, then declined from 1999 to 2004. The opposite occurred among the top 5% of
earners. Their share of earnings declined from 1995 to 1999, then increased from 1999 to
2004.
19 From 2001 to 2004, the changes in the shares of earnings received by the other earnings
groups were not statistically significant.

CRS-20
recession of 2001. From 2001 to 2004, the share of earnings received by the top 5%
of full-time, year-round earners decreased by 3.9%.20
As was the case with all workers, from 1995 to 2004, there were some
differences in the distribution of earnings of men and women in the middle of the
distribution. The share of earnings received by full-time, year-round men in the
middle three quintiles declined from 1999 to 2004. (The changes from 1995 to 1999
were not statistically significant.) Among women there was no change in the share
of earnings received by the middle three quintiles. For both men and women, there
was no change in the shares of earnings received by the top 5% of earners from 1995
to 1999, but their shares increased from 1999 to 2004.
20 From 2001 to 2004, the changes in the shares of earnings received by the other earnings
groups were not statistically significant.

CRS-21
Table 4. Share of Total Weekly Earnings, All Workers, 1995-2005
Percent
Percent
Percent
Earnings
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Change,
Change,
Change,
Group
1995 to 1999 1999 to 2004 1995 to 2004
A. All Workers
Lowest Quintile
3.59
3.76
3.73
3.79
3.87
3.86
3.83
3.83
3.79
3.80
3.80
7.8%
-1.8%
5.8%
Second Quintile
8.89
9.09
9.09
9.12
9.31
9.17
9.08
9.08
9.12
9.17
9.01
4.7%
-1.5%
3.1%
Third Quintile
14.40
14.64
14.61
14.59
14.89
14.43
14.32
14.28
14.38
14.44
14.12
3.4%
-3.0%
0.3%
Fourth Quintile
21.94
22.11
21.93
21.79
22.45
21.61
21.37
21.37
21.60
21.67
21.25
2.3%
-3.5%
-1.2%
81%-95%
26.22
26.57
26.36
26.27
27.34
26.19
26.27
26.31
26.69
26.71
26.32
4.3%
-2.3%
1.9%
Top 5%
24.95
23.82
24.27
24.45
22.15
24.74
25.13
25.13
24.42
24.22
25.49
-11.2%
9.3%
-2.9%
B. Men
Lowest Quintile
3.82
3.93
3.96
3.98
4.06
4.01
4.00
3.95
4.01
3.98
3.92
6.3%
-2.0%
4.2%
Second Quintile
9.18
9.41
9.42
9.51
9.66
9.24
9.33
9.10
9.26
9.25
9.00
5.2%
-4.2%
0.8%
Third Quintile
14.55
14.80
14.70
14.75
15.12
14.24
14.32
14.07
14.39
14.33
13.89
3.9%
-5.2%
-1.5%
Fourth Quintile
21.60
21.85
21.53
21.59
22.30
21.13
21.13
20.88
21.40
21.27
20.77
3.2%
-4.6%
-1.5%
81%-95%
25.32
25.72
25.68
25.87
26.87
25.35
25.83
25.80
26.35
26.20
25.81
6.1%
-2.5%
3.5%
Top 5%
25.54
24.29
24.71
24.30
21.99
26.02
25.38
26.20
24.60
24.97
26.62
-13.9%
13.6%
-2.2%
C. Women
Lowest Quintile
3.86
4.06
4.00
4.07
4.16
4.21
4.08
4.12
3.97
4.03
4.10
7.8%
-3.1%
4.4%
Second Quintile
9.56
9.74
9.73
9.62
9.89
9.99
9.61
9.89
9.61
9.75
9.74
3.5%
-1.4%
2.0%
Third Quintile
15.32
15.49
15.49
15.23
15.61
15.80
15.10
15.54
15.21
15.47
15.29
1.9%
-0.9%
1.0%
Fourth Quintile
23.01
23.07
23.14
22.61
23.21
23.14
22.26
22.88
22.44
22.82
22.62
0.9%
-1.7%
-0.8%
81%-95%
26.89
26.99
26.87
26.37
27.29
26.96
26.23
26.70
26.52
27.09
26.88
1.5%
-0.7%
0.7%
Top 5%
21.36
20.66
20.78
22.11
19.84
19.90
22.72
20.86
22.25
20.84
21.37
-7.1%
5.0%
-2.4%
Source: Calculated by CRS from the March Current Population Survey (CPS). Details may not add to totals because of rounding.

CRS-22
Table 5. Share of Total Weekly Earnings, Full, Time, Year-Round Workers, 1995-2005
Percent
Percent
Percent
Earnings
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Change,
Change,
Change,
Group
1995 to 1999 1999 to 2004 1995 to 2004
A. All Full-Time, Year-Round Workers
Lowest Quintile
6.27
6.25
6.28
6.27
6.31
6.14
6.15
6.21
6.20
6.11
6.07
0.6%
-3.2%
-2.6%
Second Quintile
11.10
11.09
11.13
11.12
11.20
10.79
10.73
10.76
10.85
10.80
10.62
0.9%
-3.6%
-2.7%
Third Quintile
15.59
15.35
15.41
15.47
15.74
15.07
14.93
15.04
15.12
15.04
14.92
1.0%
-4.4%
-3.5%
Fourth Quintile
21.78
21.42
21.42
21.47
22.00
21.20
20.90
21.07
21.30
21.23
21.14
1.0%
-3.5%
-2.5%
81%-95%
24.61
24.39
24.41
24.60
25.49
24.64
24.62
24.95
25.18
25.03
25.10
3.6%
-1.8%
1.7%
Top 5%
20.65
21.50
21.35
21.06
19.26
22.16
22.67
21.96
21.36
21.79
22.14
-6.7%
13.1%
5.5%
B. Men
Lowest Quintile
6.06
6.02
6.09
6.06
6.17
5.88
5.90
5.89
5.95
5.82
5.76
1.8%
-5.7%
-4.0%
Second Quintile
10.96
10.94
10.97
11.02
11.18
10.48
10.52
10.45
10.57
10.48
10.30
2.0%
-6.3%
-4.4%
Third Quintile
15.50
15.33
15.30
15.38
15.69
14.77
14.73
14.76
15.03
14.86
14.65
1.2%
-5.3%
-4.1%
Fourth Quintile
21.50
21.20
21.09
21.27
21.97
21.00
20.81
21.02
21.26
21.03
20.86
2.2%
-4.3%
-2.2%
81%-95%
24.30
24.17
24.34
24.68
25.37
24.35
24.54
25.00
25.35
25.08
25.05
4.4%
-1.1%
3.2%
Top 5%
21.69
22.34
22.21
21.59
19.61
23.51
23.49
22.87
21.84
22.74
23.38
-9.6%
16.0%
4.8%
C. Women
Lowest Quintile
7.23
7.26
7.27
7.24
7.13
7.14
6.97
7.14
6.91
6.93
6.96
-1.4%
-2.8%
-4.1%
Second Quintile
12.51
12.32
12.33
12.23
12.33
12.38
11.93
12.08
12.00
12.03
11.84
-1.4%
-2.4%
-3.8%
Third Quintile
16.97
16.51
16.66
16.62
16.89
16.72
16.14
16.34
16.24
16.29
16.27
-0.5%
-3.6%
-4.0%
Fourth Quintile
22.83
22.20
22.40
22.20
22.67
22.45
21.75
22.10
21.98
22.11
22.24
-0.7%
-2.5%
-3.2%
81%-95%
24.60
24.17
24.28
24.26
24.83
24.61
24.16
24.41
24.45
24.72
24.94
0.9%
-0.4%
0.5%
Top 5%
15.86
17.55
17.06
17.44
16.15
16.70
19.05
17.92
18.42
17.92
17.75
1.8%
11.0%
13.0%
Source: Calculated by CRS from the March Current Population Survey (CPS). Details may not add to totals because of rounding.


CRS-23
Appendix
This appendix provides a brief explanation of the measures of inequality used
in this report. It also describes the data and methodology used in the report.
Measures of Inequality
This report uses two measures of inequality: the Gini coefficient and the share
of earnings received by each quintile of workers.
Gini Coefficient. The Gini coefficient is calculated using the following
formula:
where f is the proportion of earners in interval i and p is the proportion of total
i
i
earnings received by earners in interval i and all lower intervals.21
Figure 10. Illustration of Lorenz Curves and Gini
Coefficients for Two Groups of Workers
ngs
Percent of Earni
Source: Calculated by CRS from the March Current Population Survey (CPS).
21 U.S. Bureau of the Census, Studies in the Distribution of Income, Series P60-183, 1992,
p. 60.

CRS-24
Graphically, the Gini coefficient is illustrated in Figure 10. The horizontal axis
shows the percent of all earners; the vertical axis shows the percent of earnings
received by all earners. The diagonal line represents total earnings equality. For
example, on the diagonal line, 25% of earners receive 25% of earnings, 50% of
earners receive 50% of earnings, and so on.
In Figure 10 the two dotted lines — called Lorenz curves — illustrate two
possible earnings distributions. The Gini coefficient is the ratio of (a) the area
between the diagonal line and the Lorenz curve and (b) the total area under the
diagonal line. Figure 10 illustrates the distribution of earnings for two groups of
workers (or the same group of workers at different times). The distribution of
earnings for the first group (where the Gini coefficient is .163) is more equal than the
distribution of earnings for the second group (where the Gini coefficient is .289). For
the first group of workers, the bottom 60% of workers receive half of all earnings;
the top 40% receive the other half of earnings. In the second group, the bottom 70%
of earners receive half of all earnings; the top 30% receive the other half.
Share of Total Earnings by Quintile. To calculate the share of earnings
received by each quintile, workers are first ranked from lowest to highest paid.
Workers are then divided into five equal-size groups, or quintiles. The total earnings
received by each quintile is divided by the total earnings of all workers. If everyone’s
earnings were the same, each quintile would receive one-fifth of all earnings. The
greater the share of earnings received by the highest paid workers (i.e., the top
quintile) or the smaller the share of earnings received by the lowest paid workers
(i.e., the bottom quintile) the greater the degree of inequality. In this report, the top
quintile of earners is separated into two groups: the top 5% of earners and the top
81% to 95% of earners.
Data and Methodology
The analysis in this report uses data from the March Current Population Survey
(CPS). The CPS is a household survey conducted by the U.S. Bureau of the Census
for the Bureau of Labor Statistics (BLS) of the U.S. Department of Labor. The
monthly CPS is the main source of labor force data for the nation, including
estimates of the monthly unemployment rate. The CPS collects a wide range of
demographic, social, and labor market information.
The CPS sample is representative of the civilian noninstitutional population; it
does not include persons on active duty in the Armed Forces or persons in institutions
such as nursing homes or correctional facilities. The survey includes civilian
noninstitutional persons living in group quarters. (Group quarters are living quarters
where residents share common facilities; examples include group homes, fraternities,
or sororities.)22
Each March, in what is called the Annual Social and Economic Supplement
(ASEC), the CPS asks questions about earnings for the previous year. Thus, in
22 U.S. Department of Labor, Bureau of Labor Statistics, Current Population Survey:
Design and Methodology
, Technical Paper 63RV, Mar. 2002, pp. 1-1, 3-7 to 3-9, 5-4.

CRS-25
March 2006, the survey collected information on annual earnings for 2005. The
March CPS collects earnings information for both wage and salary workers and self-
employed persons. Some persons may have earnings from both sources. When
reporting their annual earnings some self-employed persons may include losses on
their investments. This report uses positive earnings only. The March 2006
supplement interviewed about 76,700 households.23
In Tables 1 and 2, data for consecutive years should be compared with caution.
When answering the question in the March CPS about annual earnings, some
respondents may round off their earnings. For example, many people may report that
they earn $50,000 a year, when they earn either more or less than $50,000. From one
year to the next, this rounding may affect the observed trend in weekly earnings.
CPI-U-RS. In this report, nominal weekly wages were adjusted for inflation
using the CPI-U-RS (the Consumer Price Index for all Urban Consumers Research
Series).
Over the years, BLS has introduced a number of changes in the way it measures
changes in prices. Each improvement is intended to make the CPI-U more accurate.
But the historical CPI-U is not adjusted to take the improvements into account. The
CPI-U-RS adjusts the historical CPI-U (starting in 1978) to take into account most
of the improvements made in measuring price changes. The CPI-U-RS shows what
the CPI-U would have been if current methods had been used to measure inflation.
Compared to the CPI-U, the CPI-U-RS provides a more consistent measure of
inflation.24 From 1995 to 2005, the CPI-U-RS increased by 27.2%. The CPI-U
increased by 28.1%.
Topcoded Earnings. In the March CPS, if a person’s annual earnings exceed
a certain amount, the individual’s actual earnings are not reported. Instead, BLS
reports the average earnings of those persons whose earnings are above the topcoded
amount. For 2005 (i.e., the March 2006 CPS), annual earnings from a person’s
longest job were topcoded at $200,000, or $3,846.15 a week. BLS averages earnings
for several groups of workers, based on gender, race, Hispanic origin, and work
experience. For example, BLS calculates average earnings for all white, non-
Hispanic men who work full-time, year-round and whose earnings for their longest
held job were over $200,000. To arrive at total annual earnings, this amount is added
to any earnings from other employment (e.g., a person may have held more than one
job during the year).
For the period 1995 to 2005, workers with topcoded annual earnings from their
longest job generally accounted for less than 1% of workers. Therefore, in this
report, topcoded earnings did not affect the estimates of real weekly earnings or the
23 U.S. Census Bureau, Current Population Survey, 2006 Annual Social and Economic
(ASEC) Supplement
, available at [http://www.census.gov/apsd/techdoc/cps/cpsmar06.pdf],
p. 2-1.
24 Stewart, Kenneth J, and Stephen B. Reed, “Consumer Price Index Research Series Using
Current Methods, 1978-98,” Monthly Labor Review, vol. 122, June 1999, p. 29.

CRS-26
share of total weekly earnings by quintile. Because of topcoding, the Gini
coefficients shown in this report may understate the degree of inequality.
Confidence Levels. Estimates based on survey responses from a sample of
households have two kinds of error: nonsampling and sampling. Examples of
nonsampling error include information that is misreported and errors made in
processing collected information. Sampling error occurs because a sample, and not
the entire population, of households is surveyed. The difference between an estimate
based on a sample of households and the actual population value is known as
sampling error. When using sample data, researchers typically construct confidence
intervals around population estimates. Confidence intervals provide information
about the accuracy of estimated values. With a 95% confidence interval and repeated
samples from a population, 95% of intervals will include the average estimate of a
population characteristic.