GENDER PAY 

DIFFERENCES 

Progress Made, but 

Women Remain 

Overrepresented 

among Low-Wage 

Workers 

Report to Congressional Requesters

October 2011 

GAO-12-10 

United States Government Accountability Office

GAO 
 United States Government Accountability Office 

Highlights of GAO-12-10, a report to 

congressional requesters 

October 2011 

GENDER PAY DIFFERENCES 

Progress Made, but Women Remain Overrepresented

among Low-Wage Workers 

Why GAO Did This Study 

Women represent an increasingly 

larger share of the total workforce in 

the United States—constituting nearly 

half of the total workforce. In addition, 

an increasing proportion of women in 

the workforce are more educated. 

However, research by GAO and others 

has shown that women’s average pay 

has been and remains lower than that 

of men. Questions have been raised 

about the extent to which lessadvantaged women—that is, those 

who are low wage or less educated—

experience lower wages than lessadvantaged men. 

GAO was asked to examine the 

differences in representation, key 

characteristics, and pay among women 

and men (1) with less education and 

(2) with low wages. GAO defined lesseducated workers as those having a 

high school degree or less and lowwage workers as those earning an 

hourly wage rate in the bottom 

quintile—or 20 percent—of wages 

across the workforce. GAO analyzed 

data from the Department of Labor’s 

Current Population Survey (CPS); 

reviewed other work on similar topics; 

and interviewed agency officials, 

representatives of women’s groups, 

and other researchers. 

What GAO Recommends 

GAO is not making recommendations 

in this report. The Department of Labor 

provided technical comments, which 

were incorporated where appropriate. 

The Department of Commerce had no 

comments on this report. 

What GAO Found 

Women in general have surpassed men in obtaining education over the last three 

decades, but on average, women with a high school degree or less earned lower 

hourly wages than men with the same level of education. Among these lesseducated workers, women tended to work in industries and occupations, such as 

health care and social assistance, that had lower wages than those in which men 

worked. Even when less-educated women and men were in the same broad 

industry or occupation category, these women’s average hourly wage was lower 

than men’s. GAO estimated that in 2010, less-educated women earned 86 

cents—compared with 81 cents in 2000—for every dollar men earned, after 

adjusting for available factors that may affect pay. The annual household income 

of less-educated workers varied based on marital status and the presence of 

children, but in all cases, women, on average, had lower personal earnings than 

men. Less-educated single women households with children had among the 

lowest total annual income of all households, averaging about $37,000. 

Women have made progress in earning higher wages over the last three 

decades, but they remain overrepresented among workers who earn low wages. 

Women made up an estimated 49 percent of the overall workforce in 2010, but 

constituted 59 percent of the low-wage workforce. Low-wage women and men 

earned a similar hourly wage, but women as a group earned less in a typical 

week—in part, because they were more likely to work part-time. While hourly 

wages for low-wage men and women did not vary much, annual household 

income did vary, largely based on marital status and the presence of children in 

the household. Single women with children in the household had the lowest 

annual household income, averaging about $27,000. 

Estimated Pay Differences between Less-Educated Women and Men, 2000-2010 

Source: GAO analysis of CPS data.

Male pay

Female pay

Adjusteda

Unadjusted

Hourly wage (in dollars)

Difference in pay

81¢

77¢

86¢

81¢

0

0.7

0.8

0.9

1.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

a

The adjusted pay difference controls for the following factors—age, race/ethnicity, education, marital 

status, children in the household, full-time/ part-time job status, union membership, citizenship status, 

veteran status, state of residence, industry, and occupation (see app. III for more details). View GAO-12-10 or key components. 

For more information, contact Andrew Sherrill 

at (202) 512-7215 or sherrilla@gao.gov. 
Page i GAO-12-10 

Contents 

Letter 1 

Women with a High School Degree or Less Earn Lower Wages than 

Men 4

Even with Progress, Women Remain Overrepresented in the LowWage Workforce 8

Concluding Observations 10

Agency Comments and Our Evaluation 11

Appendix I Fact Sheets Less-Educated and Low-Wage Workers 12 

Appendix II Objectives, Scope, and Methodology 25 

Appendix III Multivariate Analysis 31 

Appendix IV Description of Industries and Occupations 39 

Appendix V Representation by Industry and Occupation for LessEducated and Low-Wage Workers 41 

Appendix VI Characteristics of Less-Educated and Low-Wage Workers, 

Calendar Year 2010 45 

Appendix VII Characteristics of Less-Educated Workers Employed in 

Retail Trade and Manufacturing Industries, Calendar Year 2010 47 

Appendix VIII Annual Household Income for Less-Educated and Low-Wage 

Workers, Calendar Year 2009 49 

Gender Pay Differences 
Appendix IX GAO Contact and Staff Acknowledgments 50 

Related GAO Products 51

Tables 

Table 1: Estimated Coefficient for Women by Year 33

Table 2: Estimated Coefficient for Women by Selected 

Characteristics and Industries, 2010 35

Table 3: Odds Ratio of Being Low Wage from Logistic Regression 

Analysis 38

Table 4: Examples of Areas Contained within Each Industry 39

Table 5: Examples of Areas Contained within Each Occupation 40

Table 6: Less-Educated Workers by Industry, Calendar Year 2010 41

Table 7: Less-Educated Workers by Occupation, Calendar Year 

201042

Table 8: Low-Wage Workers by Industry, Calendar Year 2010 43

Table 9: Low-Wage Workers by Occupation, Calendar Year 2010 44

Figures 

Figure 1: Amount of Overlap between Less-Educated and LowWage Worker Populations in 2010 3

Figure 2: Annual Household Income of Less-Educated Workers, as 

of 2009 7

Figure 3: Annual Household Income of Low-Wage Workers, as of 

2009 9

Figure 4: Percentage of Workers Who Are Low Wage, by Education 

Level, as of 2010 10

Page ii GAO-12-10 Gender Pay Differences
Abbreviations 

ASEC Annual Social and Economic Supplement 

BLS Bureau of Labor Statistics 

CPS Current Population Survey 

DOL Department of Labor 

NAIC North American Industry Classification System 

SIC Standard Industry Classification 

This is a work of the U.S. government and is not subject to copyright protection in the 

United States. The published product may be reproduced and distributed in its entirety 

without further permission from GAO. However, because this work may contain 

copyrighted images or other material, permission from the copyright holder may be 

necessary if you wish to reproduce this material separately. 

Page iii GAO-12-10 Gender Pay Differences
 

Page 1 GAO-12-10 

United States Government Accountability Office

Washington, DC 20548 

October 12, 2011 

The Honorable Robert P. Casey, Jr. 

Chairman

Joint Economic Committee 

United States Congress 

The Honorable Carolyn B. Maloney 

House of Representatives 

Over the past 30 years, the size of the United States workforce has grown 

from about 75 million to over 115 million workers, with women 

representing an increasingly larger share. By the end of 2010, women 

made up nearly half (47 percent) of the workforce, up from 41 percent in 

1980. During the same period, the percentage of women who worked 

rose 10 percentage points to just over 66 percent, while the percentage of 

men who worked fell 8 percentage points to about 77 percent.1

Women have also attained higher education levels since 1980. Both men 

and women workers are better educated than they were 30 years ago; 

however, women have surpassed men with respect to obtaining high 

school diplomas and college degrees. Younger women—those from age 

25 to 34—now complete high school and college at somewhat higher 

rates than men. For example, in 2010, 90 percent of women within that 

age group held at least a high school diploma or equivalent compared 

with 87 percent for men of that age. Moreover, 37 percent of these 

younger women held a bachelor’s degree or higher, compared with 29 

percent of younger men.2

Gender Pay Differences 

 1

 Data presented in this report are estimates based on GAO analysis of the Current 

Population Survey. Data on workforce participation are based on workers age 25 to 64, 

including those who are self-employed. Subsequent analyses in this report exclude selfemployed workers, because of the difficulty in accurately estimating hourly wages for this 

population. For more information about our analysis, see appendix II. 

2

U.S. Census Bureau, Table 226: Educational Attainment by Race, Hispanic Origin, and 

Sex, http://www.census.gov/compendia/statab/2011/tables/11s0226.xls, and Table 1: 

Educational Attainment of the Population 18 Years and Over, by Age, Sex, Race, and 

Hispanic Origin: 2010, 

http://www.census.gov/hhes/socdemo/education/data/cps/2010/Table1-01.xls

(Washington, D.C.: Aug. 11, 2011). 
 

While gains have been made in some areas, research by GAO and 

others has shown that women’s average pay has been and remains lower 

than that of men.3 For example, in 2003, we reported that across the 

general workforce, gender pay differences had narrowed over time, but 

women in 2000 received 80 cents for every dollar earned by men after 

adjusting for available factors that may affect pay.4 Most recently, in 

2010, in response to a request from the Joint Economic Committee

examined women’s progress in the workplace and reported on 

differences in the representation, characteristics, and pay of women and 

men in management positions.

, we 

 

5 As with our findings for the overall worker 

population, we found a pay difference between male and female 

managers, although it had narrowed somewhat over time. We estimated 

that women managers earned 81 cents for every dollar earned by male 

managers in 2007, compared with 79 cents in 2000, after adjusting for 

selected factors. 

As a follow-up to our earlier work, you asked us to examine gender 

differences among less-advantaged workers—specifically, those with less 

education and those with low wages. We defined less-educated workers 

as those having a high school degree or less. We defined low-wage 

workers as those earning an hourly wage rate in the bottom quintile—or 

20 percent—of wages across the workforce.6 In 2010, those in the bottom 

quintile earned an average hourly wage of $11.00 or less. These two 

populations are somewhat distinct, but they also overlap. We estimated 

that nearly 60 percent of low-wage workers have a high school degree or 

Gender Pay Differences

 

3

GAO, Women’s Earnings: Work Patterns Partially Explain Difference between Men’s and 

Women’s Earnings, GAO-04-35 (Washington, D.C.: Oct. 31, 2003). White House Council 

on Women and Girls, Women in America: Indicators of Social and Economic Well-Being

(March 2011). 

4

For other examples of past GAO work on gender pay differences see GAO, Women’s 

Pay: Gender Pay Gap in the Federal Workforce Narrows as Differences in Occupation, 

Education, and Experience Diminish, GAO-09-279 (Washington, D.C.: Mar. 17, 2009), 

and Retirement Security: Women Face Challenges in Ensuring Financial Security in 

Retirement, GAO-08-105 (Washington, D.C.: Oct.11, 2007). 

5

GAO, Women in Management: Analysis of Female Managers’ Representation, 

Characteristics, and Pay, GAO-10-892R (Washington, D.C.: Sept. 20, 2010). 

6

In the rest of this report, when we refer to “hourly wage” we mean hourly wage rate. Our 

analysis includes workers who are paid in hourly wages as well as those workers who are 

paid on other schedules. 

Page 2 GAO-12-10 
 

less, while just over a third of less-educated workers are also low-wage 

(see fig.1). 

Figure 1: Amount of Overlap between Less-Educated and Low-Wage Worker 

Populations in 2010 

Source: GAO analysis of CPS data.

34.6 million

Less-educated

workers

34% of workers with

a high school diploma

or less earn low wages 

60% of workers who earn

low wages have a high

school diploma or less

19.8 million

Low-wage

workers

11.8 million

Low-wage

and less

educated

workers

To respond to your request, we are answering the following question: 

What are the differences in representation, key characteristics, and pay 

among women and men (1) with less education and (2) with low wages? 

To perform this work, we analyzed data from the Department of Labor 

Bureau of Labor Statistics’ (BLS) Current Population Survey (CPS) to 

obtain information on gender differences in representation, 

characteristics, and pay among workers who have low wages or less 

education. We selected the CPS because it provides a good measure of 

hourly wages, large sample sizes, and data over time. We assessed CPS 

data reliability—by reviewing documentation on CPS design, methods, 

and data elements; interviewing agency officials; and performing 

Page 3 GAO-12-10 Gender Pay Differences
 

electronic data testing—and determined that the data were sufficiently 

reliable for our purposes. We restricted our analysis to individuals ages 

25 to 64 who were not self-employed. As is the case with research that 

uses statistical modeling to study pay differences, our models cannot 

explain any earnings difference between women and men in our 

population that persists after controlling for available factors that may 

affect pay. For example, our work could not measure level of work 

experience. In addition, our analysis cannot determine whether 

differences in pay were due to worker choice or discrimination. Beyond 

our analysis of CPS data, we also reviewed other work on similar topics 

and interviewed representatives of women’s groups and other 

researchers to provide the appropriate context for this report.7

We conducted our work from January to October 2011 in accordance with 

all sections of GAO’s Quality Assurance Framework that are relevant to 

our objectives. The framework requires that we plan and perform the 

engagement to obtain sufficient and appropriate evidence to meet our 

stated objectives and to discuss any limitations in our work. We believe 

that the information and data obtained, and the analysis conducted, 

provide a reasonable basis for any findings and conclusions in this 

product. Appendix I includes separate fact sheets that provide more 

details on representation, characteristics, and pay for each population—

less-educated and low-wage workers. Appendixes II and III provide 

detailed descriptions of our methodology. 

Women in general have surpassed men in obtaining education over the 

last three decades, but on average, less-educated women earn lower 

wages than less-educated men. Within this less-educated group, 81 

percent of women compared with 75 percent of men had a high school 

diploma in 2010, according to BLS data. Less-educated women also 

tended to be older than less-educated men, averaging about age 45 

compared with about age 42 for men.8 Although women were older and 

had greater high school graduation rates than men among the less 

educated, women’s wages lagged behind men’s. The particular industry 

and occupation in which they worked had a considerable effect on the 

Women with a High 

School Degree or Less 

Earn Lower Wages 

than Men 

 7

Estimated differences presented in this report are significant at the 95 percent confidence 

level. 

8

See appendix I for more information on characteristics of less-educated workers. 

Page 4 GAO-12-10 Gender Pay Differences
 

Page 5 GAO-12-10 Gender Pay Differences 

wages of less-educated workers, which averaged from $11.10 to $23.02 

per hour.9

 Women tended to work in industries and occupations that had 

lower wages than the industries and occupations in which men worked. 

For example, in 2010, health care and social assistance drew the largest 

number of less-educated women, where they earned, on average, about 

$14 per hour. At the same time, a sizable number of less-educated men 

worked in construction or in transportation/utilities, where they earned, on 

average, more than $19 per hour. Further, even when less-educated 

women and men worked in the same broad industry or occupation 

category, women’s average hourly wage was lower than men’s. 

As we found in our earlier studies of the general population, among lesseducated workers, differences in pay between women and men have 

narrowed somewhat over time.10 We estimated that, in 2000, lesseducated women earned 81 cents for every dollar men earned, while in 

2010, the pay difference decreased by 5 cents—to 86 cents per dollar, 

after adjusting for available factors that may affect pay.11 The factors 

available for adjusting with the models are limited, however, and could 

account for about 25 percent of the pay differences. 

Beyond the hourly wages of less-educated workers, when considering the 

annual household income of this group, we found that the household 

income of these workers varied depending on marital status and the 

 

9

The broad industry and occupational categories used in this report combine many 

narrowly defined industries and occupations. There may be considerable variation in 

average wages and gender represention between the narrow industries and occupations 

within these broad categories. 

10However, models used to estimate gender pay differences are limited because some 

factors that affect pay are not measured and available in datasets. As a result, our 

estimated differences should not be interpreted to represent actual pay differences 

between women and men that may exist if we could measure all factors that affect pay. 

11The unadjusted pay differences between less-educated women and men from 2000 to 

2010 averaged about 4 cents higher than the adjusted amounts. However, the unadjusted 

pay differences do not take into account any factors that may affect pay, including different 

attributes of women and men, or that women and men may work in different industries or 

occupations. 
 

presence of children.12 However, in all of these household categories, 

women had lower average personal wage and salary earnings than men. 

We estimated that 43 percent of less-educated women were unmarried, 

including those with and without children in the household (compared with 

about 36 percent of men). Less-educated unmarried women were almost 

three times more likely than less-educated unmarried men to have a child 

in the household. These single woman households had among the lowest 

total annual income of all households—averaging about $37,000 in 

households with children and $40,000 in those without children. About onethird of these households’ income came from sources other than the wage 

and salary earnings of the less-educated worker. While married lesseducated women had lower wage and salary earnings than married lesseducated men, they had a slightly higher total household income, and in 

these households, women’s earnings were a smaller proportion of total 

household income (see fig. 2). Less-educated women were more likely 

than less-educated men to work part-time—on average, 29 percent of 

women and 15 percent of men worked part-time in 2010. 

 12Total household income includes (1) annual wage and salary earnings of the worker; (2) 

annual wage and salary earnings of others in the household; and (3) income from outside 

the household, including government benefits (such as Social Security, public assistance, 

veterans’ payments); retirement, investment, and rental income; and other sources of nonwage/salary income. We restricted our analysis to women and men who were defined as 

either the “householder” (for example, the owner or renter) or spouse of householder. 

Page 6 GAO-12-10 Gender Pay Differences
 

Figure 2: Annual Household Income of Less-Educated Workers, as of 2009 

Source: GAO analysis of CPS data.

Household

income

(in dollars)

Unmarried workers

Without children

in household

With at least

one child

Without children

in household

With at least

one child

Married workers

Annual wages and salary of the less-educated worker

Annual wages and salary of others in household

Income from outside the household (including government aid)

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

Men Women Men Women Men Women Men Women

65%

23%

12%

$37,438

69%

23%

7%

$51,452

69%

20%

10%

$39,887

76%

17%

7%

$47,599

37%

49%

14%

$79,384

57%

35%

8%

$77,684

34%

56%

9%

$75,145

61%

33%

6%

$67,574

Note: These are 2009 data collected in 2010. The largest 95 percent margin of error for total 

household income of any group in this figure was plus or minus $3,148, for unmarried men with 

children in household. Some percentages may not add to 100 percent because of rounding. 

Page 7 GAO-12-10 Gender Pay Differences
 

Page 8 GAO-12-10 Gender Pay Differences 

Women have made progress in earning higher wages over the last three 

decades, but they remain overrepresented among workers who earn low 

wages. We estimated that women made up 49 percent of the overall 

workforce in 2010, but constituted 59 percent of the low-wage workforce. 

Women and men in the bottom quintile of wages earned a similar hourly 

wage, averaging from $8.21 to $9.09 depending on industry and 

occupation.13 However, relatively more women than men were in this lowwage group. Moreover, women as a group earned less in a typical week 

because women were more likely than men to work part-time. In 2010, 41 

percent of low-wage women worked part-time compared with 26 percent 

of low-wage men, according to our estimates. 

While low-wage workers earned similar hourly wages, women were more 

likely to work part-time (and therefore fewer hours per year) and as a 

result, earn less annually. The annual household income of low-wage 

workers varied depending on marital status and the presence of children 

in the household. We estimated that just under one-fifth of low-wage 

women were unmarried with at least one child in the household—making 

them almost three times more likely than unmarried low-wage men to 

have a child in the household. These single woman households had the 

lowest total annual income of all households, averaging about $27,000. 

Fifty-seven percent of the household income (or about $15,000) came 

from their personal wage and salary earnings. The remaining $12,000 

came from other sources, such as government benefits and other 

household members’ earnings. Without income from these other sources, 

the low-wage single mother households would be well below the poverty 

level of $22,314 (or $10.73 per hour, full-time) for a family of four.14

 

13We found that the difference between the hourly wage rates for women and men in the 

low-wage group was less than 1 percent, in part because of the limiting effect of the 

minimum wage. 

14GAO analysis of U.S. Census Bureau data. 

Even with Progress, 

Women Remain 

Overrepresented in 

the Low-Wage 

Workforce 

Low-Wage Workers Earn 

Similar Hourly Wages, but 

Women Earn Less 

Annually 
 

Among low-wage workers who were married—both with and without 

children in the household—the earnings of the women were lower than 

those of men. However, the households with low-wage working married 

women had higher total household income—mainly because of the higher 

earnings of others in the household (for example, a spouse)—and relied 

less on the woman’s earnings than the households of low-wage working 

married men (see fig. 3). 

Figure 3: Annual Household Income of Low-Wage Workers, as of 2009 

Source: GAO analysis of CPS data.

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

Men Women Men Women Men Women Men Women

$26,721

$33,465

$29,790 $31,078

$64,954

$54,246

$64,862

$40,889

Household

income

(in dollars)

57%

25%

18%

54%

33%

14%

54%

28%

18%

57%

31%

12%

Unmarried workers

Without children

in household

With at least

one child

Without children

in household

With at least

one child

Married workers

23%

57%

20%

34%

50%

16%

21%

67%

12%

45%

46%

10%

Annual wages and salary of the low-wage worker

Annual wages and salary of others in household

Income from outside the household (including government aid)

Notes: These are 2009 data collected in 2010. The largest 95 percent margin of error for total 

household income of any group in this figure was plus or minus $3,397 for unmarried men with 

children in the household. Some percentages may not add to 100 percent because of rounding. 

Page 9 GAO-12-10 Gender Pay Differences
 

Across the general workforce, workers who are better educated are less 

likely to earn low wages. Workers who have a high school education or 

more are far less likely than those who do not to be in the bottom quintile 

of wages. This trend can be seen in the percentage of low-wage workers 

in each educational category (see fig. 4). For example, 55 percent of 

workers with less than a high school degree in 2010 were low wage; 

however, only 28 percent of those with a high school degree (and without 

further education) were low wage. A separate analysis—which examined 

the effect of education on the likelihood of being a low-wage worker—

confirmed these findings. We found that for both women and men, 

workers who had a high school degree or more were substantially less 

likely to earn low wages than those without a high school degree, after 

adjusting for available factors that may affect pay. See appendix III for a 

detailed description of our methodology for this analysis. 

Additional Education 

Reduces Likelihood of 

Being Low Wage 

Figure 4: Percentage of Workers Who Are Low Wage, by Education Level, as of 2010 

Source: GAO analysis of CPS data.

0

20

40

60

80

100

55

Percentage

Workers with

a high school

diploma

Workers

with less than

a high school

diploma

Workers with

some college

Workers with

college degree

or higher

28

20

7

Unlike our previous work on pay differences that has focused on federal 

workers or managers, this work examines gender pay issues for lowwage and less-educated worker populations. Our findings confirm that 

working women have continued to make progress over time both in their 

wages and in their education levels. Even with gains, however, women 

Concluding 

Observations 

Page 10 GAO-12-10 Gender Pay Differences
 

who had a high school degree or less in 2010 still earned less than men 

with the same education levels. As is true with research examining 

gender pay differences, our analysis was not able to capture all 

potentially salient factors. For example, we could not assess the role that 

work experience might have played in gender pay differences. In addition, 

our study leaves other questions unanswered. In particular, why are 

women employed in industries and occupations where the average 

earnings are lower? Moreover, even when men and women work in the 

same industries or occupations, why do women generally earn lower 

wages than men? It remains unclear what effect the weak economy and 

continued high unemployment will have on the work patterns or pay 

differences we found. Understanding these and other issues that may 

affect gender pay differences would better position policymakers in 

focusing scarce resources to respond to the needs of less-advantaged 

workers. 

We provided a draft of this report to the Secretaries of Commerce and 

Labor for review and comment. The Department of Labor provided 

technical comments, which we incorporated where appropriate. The 

Department of Commerce had no comments. 

Agency Comments 

and Our Evaluation 

As agreed with your offices, unless you publicly announce the contents of 

this report earlier, we plan no further distribution until 30 days from the 

report date. At that time, we will send copies to the appropriate 

congressional committees and to the Secretaries of Commerce and 

Labor. In addition, the report will be available at no charge on the GAO 

website at http://www.gao.gov. 

If you or your staff have any questions concerning this report, please 

contact me at (202) 512-7215 or sherrilla@gao.gov. Contact points for 

our Offices of Congressional Relations and Public Affairs may be found 

on the last page of this report. GAO staff who made major contributions to 

Andrew Sherrill, 

this report are listed in appendix IX. 

Director, Education, Workforce, 

 and Income Security Issues 

Page 11 GAO-12-10 Gender Pay Differences
Page 12 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

Defining the Less-Educated Population 

This section of the report is about the United States’ 34.6 million lesseducated workers—defined as those with a high school degree or less. 

This analysis includes only wage and salary earners age 25-64, who had 

positive usual weekly hours and earnings. 

Less-Educated Workers Compared with Low-Wage Workers, Calendar Year 2010 

Source: GAO analysis of CPS data.

34.6 million

Less-educated

workers

19.8 million

Low-wage

workers

11.8 million

Low-wage

and lesseducated

workers

About This Report 

This report examines gender 

differences among two populations 

of less-advantaged workers— 

(1) those with less education and 

(2) those with low wages. 

While these two populations are 

somewhat distinct, they also 

overlap—11.8 million (or 34 

percent) less-educated workers 

also earn low wages (see fig.). 

Less-Educated Workers

Overview 

Appendix I: Fact Sheets: Less-Educated and Low-Wage Workers 
Page 13 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

Women Tend to Be More Educated than Men 

Over the last three decades, while the U.S. workforce in general has 

become more educated, women have attained higher education levels at 

a faster rate than men. 

• From 1980 to 2010, the proportion of working women with only 

a high school degree or less decreased from about 60 percent 

to about 32 percent. 

• Over the same period, the proportion of working men with only 

a high school degree or less decreased from about 55 percent 

to about 39 percent. 

Representation of Less-Educated Workers by Gender 

Note: In 1992, the CPS changed its measure of education level—before 1992, CPS used the number 

of years of school completed, and beginning in 1992, CPS has used the highest diploma 

or degree received. 

 

1

We define the workforce as wage and salary earners in the civilian labor force 

age 25-64 with positive usual weekly hours and earnings. 

Lesseducated

workers

The Workforce 

In 2010 

Size of U.S. workforce (in millions)1

Total U.S. workers: 96.7 

Male workers: 49.5 

Female workers: 47.2 

Total less-educated workers: 34.6 

Less-educated men: 19.4 

Less-educated women: 15.2 

In 1980 

Size of U.S. workforce (in millions): 

Total U.S. workers: 64.4 

Male workers: 36.5 

Female workers: 28.0 

Total less-educated workers: 36.9 

Less-educated men: 20.0 

Less-educated women: 16.9 

Note: Some numbers may not add 

to total amount because of rounding. 

More on Unemployment 

In 2010 

Unemployment rate 

of total U.S. labor force

Total unemployed: 8.3 percent 

Men: 9.0 percent 

Women: 7.5 percent 

Unemployment rate 

of less-educated workers

Total unemployed: 11.6 percent 

Men: 12.5 percent 

Women: 10.3 percent 

Source: GAO analysis of CPS data. 

Less-Educated Workers

Representation over Time 

Source: GAO analysis of CPS data.

0

10

20

30

40

50

60

70

80

1980 1985 1990 1995 2000 2005 2010

Percentage of

female workforce

with high school

diploma or less

Percentage of

male workforce

with high school

diploma or less

Percentage of workers

60

55

32

39
Page 14 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

A Look by Gender 

Less-educated women tended to work in industries that had a lower 

average hourly wage than that of men in 2010. 

Representation of Less-Educated Women and Men by Industry (in millions)

a

The difference between the number of women and men was not statistically significant 

at the 95 percent confidence level. 

Lesseducated

workers

For More on Industries 

See appendix IV for a description 

of examples of areas contained 

within each industry. 

For More on Wages 

We estimated that when lesseducated women and men worked 

in the same industry, women’s 

hourly wage rate was lower than 

men’s for 12 of the 14 industries. 

See appendix V for the hourly 

wage rate for less-educated 

workers by gender in each 

industry. 

The average hourly wage rate for 

all 34.6 million less-educated 

workers was $15.98. 

Statistical Note 

Except where otherwise indicated, 

all differences between women and 

men were statistically significant at 

the 95 percent confidence level. 

Source: GAO analysis of CPS data. 

Less-Educated Workers

Representation by Industry 

Source: GAO analysis of CPS data.

Average hourly wage for

less-educated workers

43210123

Other servicesa

Agriculture and mining

Leisure and hospitalitya

Educational services

Information and

communication

Health care and

social assistance

Retail trade

Professional and

business services

Public administrationa

Transportation

and utilities

Financial activities

Wholesale trade

Construction

Manufacturing

Men

Workers (in millions)

Women

$20.35

$19.55

$19.47

$19.03

$17.66

$17.23

$16.87

$15.72

$15.15

$14.77

$14.47

$14.15

$14.08

$12.17

0.3

2.0

0.7

3.0

0.5

0.8

3.9

1.6

0.8

0.5

0.9

2.3

0.6

1.7

0.2

0.6

0.7

0.2

1.1

0.3

1.6

1.1

0.1

1.1

0.9

2.4

3.2

1.8

Higher

wages

Lower

wages
Page 15 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

A Look by Gender 

Some occupations employed both less-educated women and men, while 

others employed primarily one gender in 2010. 

Representation of Less-Educated Women and Men by Occupation (in millions)

Source: GAO analysis of CPS data.

32101234

Personal care and service

Protective service

Food preparation

and serving

Production

Installation, maintenance,

and repair

Office and

administrative support

Sales and related

Management

Construction

and extraction

Health care practitioners

and technicians

Health care support

Cleaning and maintenance

Workers (in millions)

$12.31

$12.58

$18.71

$15.25

$18.93

$23.02

$17.10

$15.61

$14.70

$16.06

$19.55

$15.67

$11.10

Business and finance $21.01

$12.18

1.0 0.8

0.2 0.4

1.9 0.1

3.0 0.0

0.1 0.4

0.6 0.2

1.3 4.0

2.9 1.3

3.2 0.6

0.1 0.4

1.4 1.9

0.1 1.0

1.4 1.2

0.2 1.0

1.1 1.4

Men Women

Average hourly wage for

less-educated workers

Higher

wages

Lower

wages Transportation and

material moving

Education, training,

and library

Lesseducated

workers

For More on Occupations 

See appendix IV for a description 

of examples of areas contained 

within each occupation. 

For More on Wages 

We estimated that when lesseducated women and men worked 

in the same occupation, women’s 

hourly wage rate was lower than 

men’s for all 15 occupations. 

See appendix V for the hourly 

wage rate for less-educated 

workers by gender in each 

occupation. 

Statistical Note 

This list of occupations shown 

in the figure at right represents 

about 95 percent of the total 

less-educated workforce; 

occupations held by a small 

number of workers were omitted. 

All differences between the 

number of women and men were 

statistically significant at the 

95 percent confidence level. 

Source: GAO analysis of CPS data. 

Less-Educated Workers

Representation by Occupation 
Page 16 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

A Look by Gender 

In 2010, compared with less-educated men, less-educated women 

tended to be older, more often black and less often Hispanic, slightly 

more likely to have a high school degree, less often married, and more 

often part-time workers. 

Less-educated unmarried women were almost three times more likely to 

have a child in the household compared with less-educated unmarried 

men. 

Characteristics of Less-Educated Workers 

Source: GAO analysis of CPS data.

Education No diploma

Men 25% 75%

Women 19% 81%

High school graduate

Men Women

White

Black

Hispanic

Asian/other

59%

21%

14%

6%

56%

28%

11%

5%

Men Women Men Women Men Women Men Women

Age

31% 28%

5%

15%

29% 33% 35%

25%

Job status

Without children

in household

With at least

one child

Without children

in household

With at least

one child

Unmarried workers Married workers

Men Women

Age

(in years)

29% 27% 29%

15%

22% 25%

32%

21%

Men Part-time Women

71%

15%

Part-time

Full-time Full-time

85%

29%

Marriage/

children

Race/

ethnicity

Average age: 42.4 Average age: 44.6

25-34 35-44 45-54 55-64 25-34 35-44 45-54 55-64

Note: Some percentages may not add to 100 percent because of rounding. 

Lesseducated

workers

For More on Characteristics 

See appendix VI for more detailed 

information on characteristics of 

less-educated workers by gender. 

For More on Two Industries 

See appendix VII for a comparison 

of the characteristics and pay of 

less-educated women and men in 

two industries that employ a large 

number of both women and men—

(1) retail trade and 

(2) manufacturing. 

Full-Time versus Part-Time 

In this analysis, a full-time worker is 

defined as one who works 

35 hours or more per week. 

A part-time worker is one who 

works less than 35 hours per week. 

Statistical Note 

Differences in the distribution 

of women and men within each 

reported characteristic were 

statistically significant at the 

95 percent confidence level. 

Source: GAO analysis of CPS data. 

Less-Educated Workers

Characteristics 
Page 17 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

Among Less-Educated Workers in 20092

Households of unmarried women had lower incomes than those of men, 

while married women’s households had higher incomes. 

Unmarried women had the lowest total household income. Differences 

based on children were not statistically significant. 

Unmarried women’s average wage and salary earnings were about twothirds of total household income compared with one-third for married 

women’s earnings. 

Women were more likely to work part-time (and therefore fewer hours per 

year) and earned less per hour compared with men.3

Annual Household Income of Less-Educated Workers 

Source: GAO analysis of CPS data.

Household

income

(in dollars)

Unmarried workers

Without children

in household

With at least

one child

Without children

in household

With at least

one child

Married workers

Annual wages and salary of the less-educated worker

Annual wages and salary of others in household

Income from outside the household (including government aid)

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

Men Women Men Women Men Women Men Women

65%

23%

12%

$37,438

69%

23%

7%

$51,452

69%

20%

10%

$39,887

76%

17%

7%

$47,599

37%

49%

14%

$79,384

57%

35%

8%

$77,684

34%

56%

9%

$75,145

61%

33%

6%

$67,574

Note: Some percentages may not add to 100 because of rounding. 

 

2

This page shows 2009 data collected in 2010. See appendix VIII for standard 

errors on estimates. 

3

A “full-time” worker was defined as one who worked 50 or more weeks per year, 

and 35 or more hours per week; all other workers were defined as “part-time”. 

Lesseducated

workers

About Our Analysis 

We restricted this analysis to 

workers that were householders 

(or spouses of a householder)—

generally, those who owned, 

bought, or rented the home (this 

excludes children, other relatives, 

and nonrelatives in household). 

This resulted in a population of 

27.9 million less-educated workers 

out of 34.6 million total lesseducated workers in the entire 

workforce. 

See appendixes II and VIII for more 

details. 

Included in Total Household Income 

Annual wages and salary of worker

are defined as those earned solely by the 

less-educated worker. 

Annual wages and salary of others in 

household can include wages/salary of 

others in household who may not be 

less-educated workers. 

Income from outside the household

includes government benefits (such as 

Social Security, public assistance, 

veterans’ payments); retirement, 

investment, and rental income; and other 

sources of non-wage/salary income. 

Wages and Job Status 

For this subpopulation of 27.9 million 

less-educated householders (or spouses 

of a householder) 

Full-time less-educated workers 

Men: 81 percent (12.1 million) 

Women: 70 percent (9.0 million) 

Part-time less-educated workers 

Men: 19 percent (2.9 million) 

Women: 30 percent (3.9 million) 

Source: GAO analysis of CPS data. 

Less-Educated Workers

Annual Household Income 
Page 18 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

Estimated Pay Differences 

Model 1: Over time (from 2000 to 2010), the difference in hourly wages 

between less-educated women and men has gradually narrowed, even 

without adjusting for factors that may affect pay. 

• Unadjusted pay differences do not take into account any factors 

that may affect pay, including different attributes of women and 

men, or that women and men may work in different industries or 

occupations. To show the importance of these factors, we 

conducted analysis in two steps described below. 

Model 2: After adjusting for available factors that may affect pay—except 

for industry and occupation—the difference in hourly wages between 

less-educated women and men has gradually narrowed from 2000 to 

2010, but was similar to the unadjusted difference. 

Model 3: After adjusting for available factors that may affect pay—

including industry and occupation—we found a similar narrowing of pay 

differences over time (see all factors at left). However, including industry 

and occupation in the model caused the pay difference to shrink. Unlike 

in Model 2, the adjusted difference was less than the unadjusted 

difference in each year, demonstrating the ability of industry and 

occupation to explain pay differences among less-educated workers. 

Estimated Pay Differences between Less-Educated Women and Men 

Source: GAO analysis of CPS data.

0

0.7

0.8

0.9

1.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Male pay

Adjusted without

industry/occupation

(model 2)

Female pay

Adjusted (model 3)

Unadjusted

(model 1)

Hourly wage (in dollars)

Difference in pay

81¢

77¢

86¢

81¢

Lesseducated

workers

About Our Analysis 

Our analysis adjusted for the 

following factors—age, 

race/ethnicity, education, marital 

status, number of children in the 

household, full-time versus parttime job status, union membership, 

citizenship status, veteran status, 

state of residence, industry, and 

occupation. 

We did not attempt to provide an 

explanation for any difference in 

earnings between women and men 

that persists after controlling for 

available factors that may affect 

pay. Specifically, our analysis 

cannot determine whether 

differences in pay were due to 

worker choice or discrimination. 

See appendix III for details about 

how we conducted this analysis. 

For More on Pay 

We estimated that the smallest pay 

difference between less-educated 

women and men was for those who 

were unmarried without children in 

the household. 

See appendix III for data on the 

estimated pay differences between 

less-educated women and men by 

marital status and presence of 

children in the household. 

Source: GAO analysis of CPS data. 

Less-Educated Workers

Pay Differences by Gender 
Page 19 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

Defining the Low-Wage Population 

This section of the report is about the United States’ 19.8 million 

low-wage workers—defined as those who earn an hourly wage rate that 

is in the bottom quintile (bottom 20 percent) of wages across the entire 

workforce. This analysis includes wage and salary earners age 

25-64 who had positive usual weekly hours and earnings. 

Low-Wage Workers Compared with Less-Educated Workers, Calendar Year 2010 

Source: GAO analysis of CPS data.

34.6 million

Less-educated

workers

19.8 million

Low-wage

workers

11.8 million

Low-wage

and lesseducated

workers

About This Report 

This report examines gender 

differences among two populations 

of less-advantaged workers— 

(1) those with less education and 

(2) those with low wages. 

While these two populations are 

somewhat distinct, they also 

overlap—11.8 million (or 60 

percent of) low-wage workers are 

also less educated (see fig.). 

Low-Wage Workers

Overview 
Page 20 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

More Women Earn Low Wages than Men 

While there has been some progress over time, women are still 

overrepresented in the low-wage workforce. 

• In 1980, 43 percent of the entire workforce were women, but 

73 percent of the bottom quintile of wage earners were women. 

• In 2010, women’s percentage of the entire workforce had 

increased to 49 percent and women’s representation in the bottom 

quintile of wage earners had decreased to 59 percent. 

Representation of Women in Low-Wage Workforce, 1980-2010 

Women Are More Likely to Be Low-Wage Workers 

In a separate analysis, we examined the likelihood of women being in the 

low-wage workforce as compared with men. In our analysis, we found 

that women were more likely than men to be in the bottom quintile of 

wage earners, and even after using a multivariate analysis to adjust for 

differences between women’s and men’s levels of education, occupation, 

industry, as well as other available factors that may affect pay, we found 

that this difference in likelihood was not reduced. 

See appendix III for more details about this analysis. 

Low-wage

workers

The Workforce 

In 2010 

Size of U.S. workforce (in millions) 

Total U.S. workers: 96.7 

Male workers: 49.5 

Female workers: 47.2 

Total low-wage workers: 19.8 

Low-wage men: 8.2 

Low-wage women: 11.6 

In 1980 

Size of U.S. workforce (in millions): 

Total U.S. workers: 64.4 

Male workers: 36.5 

Female workers: 28.0 

Total low-wage workers: 13.0 

Low-wage men: 3.5 

Low-wage women: 9.5 

Note: Some numbers may not add 

to total amount because of rounding. 

Source: GAO analysis of CPS data. 

Low-Wage Workers

Representation over Time 
Page 21 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

Low-Wage Women and Men Earn Similar Wages 

Some industries employed low-wage women and men in similar numbers 

in 2010, while others employed primarily one gender. 

Among the three industries that employ the largest numbers of low-wage 

workers, two industries—retail trade and leisure and hospitality—

employed large numbers of both women and men. The third industry—

health care and social assistance—employed mostly women. 

The average hourly wage rate for both women and men in the low-wage 

workforce did not vary markedly across industries—it ranged from $8.31 

to $8.96. 

Representation of Low-Wage Women and Men by Industry (in millions) 

a

The difference between the number of women and men was not statistically significant 

at the 95 percent confidence level. 

Low-wage

workers

For More on Industries 

See appendix IV for a description 

of examples of areas contained 

within each industry. 

For More on Wages 

See appendix V for the hourly 

wage rate for low-wage workers 

by gender in each industry. 

The average hourly wage rate for 

all 19.8 million low-wage workers 

was $8.65. 

Statistical Note 

Except where otherwise indicated, 

all differences between women and 

men were statistically significant at 

the 95 percent confidence level. 

Source: GAO analysis of CPS data. 

Low-Wage Workers

Representation by Industry 

Source: GAO analysis of CPS data.

$8.71

1.5 1 0.5 0 0.5 1 1.5 2 2.5

Other services

Agriculture and mining

Leisure and hospitality

Educational services

Information and

communicationa

Health care and

social assistance

Retail trade

Professional and

business servicesa

Public administration

Transportation

and utilities

Financial activities

Wholesale trade

Construction

Manufacturing

Men

Average hourly wage

for low-wage workers

Workers (in millions)

Women

$8.96

$8.92

$8.81

$8.75

$8.74

$8.72

$8.72

$8.71

$8.62

$8.55

$8.38

$8.31

$8.31

1.3

0.4

1.3

1.0

0.8

0.3

0.4

0.7 0.1

0.2 0.6

0.5

0.2

0.3

0.3

0.1

2.1

2.7

1.7

0.8

0.8

1.1

0.8

0.2

0.3

0.1

0.2

0.1
Page 22 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

Low-Wage Women Cluster in Certain Occupations 

More than half of low-wage women were in four occupations that 

employed the largest number of low-wage workers in 2010: 

• office and administrative support, 

• sales and related, 

• food preparation and serving, and 

• cleaning and maintenance. 

In comparison, a large number of low-wage men were employed in the 

transportation/material moving and production occupations, and to a 

lesser extent in the same four occupations noted above. 

The average hourly wage rate for those in the low-wage workforce did 

not vary markedly across occupations—it ranged from $8.28 to $9.03. 

Representation of Low-Wage Women and Men by Occupation (in millions)

Low-wage

workers

For More on Occupations 

See appendix IV for a description 

of examples of areas contained 

within each occupation. 

For More on Wages 

See appendix V for the hourly 

wage rate for low-wage workers by 

gender in each occupation. 

Statistical Note 

The list of occupations shown 

in the figure at right represents 

about 95 percent of the total 

low-wage workforce; occupations 

held by a small number of workers 

were omitted. 

All differences between the 

number of women and men were 

statistically significant at the 

95 percent confidence level. 

Source: GAO analysis of CPS data. 

Low-Wage Workers

Representation by Occupation 
Page 23 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

A Look by Gender 

In 2010, compared with low-wage men, low-wage women tended to be: 

older, more often white and less often Hispanic, better educated, as likely 

to be married, more often had children in the household, and more often 

part-time workers. 

Low-wage unmarried women were almost three times more likely to have 

a child in the household compared with low-wage unmarried men. 

Characteristics of Low-Wage Workers 

Source: GAO analysis of CPS data.

Age

Men Women Men Women Men Women Men Women

Marriage/

children

Race/

ethnicity

Education No diploma

Men Women

Men Women

Men

White

Black

Hispanic

Asian/other

56%

21%

16%

6%

Age

(in years)

41%

24% 21%

14%

31%

25% 27%

17%

46%

27% 39% 23% 11%

Women 17% 39% 31% 13%

33%

41%

28%

6%

18%

23% 27% 30% 28%

14%

7%

High school graduate

Some

college

College

degree

Job status

Without children

in household

With at least

one child

Without children

in household

With at least

one child

Unmarried workers Married workers

Men Women

Part-time

59%

26%

74% Full-time Part-time 41% Full-time

Average age: 40.0 Average age: 42.2

25-34 35-44 45-54 55-64 25-34 35-44 45-54 55-64

Note: Some percentages may not add to 100 percent because of rounding. 

Low-wage

workers

For More on Characteristics 

See appendix VI for more detailed 

information on characteristics of 

low-wage workers by gender. 

Full-Time versus Part-Time 

In this analysis, a full-time worker is 

defined as one who works 

35 hours or more per week. 

A part-time worker is one who 

works less than 35 hours per week. 

Education and Low Wages 

In a separate analysis, we 

examined the effect of education 

on the likelihood of being a lowwage worker. We found that for 

both women and men, workers 

who have a high school degree 

or more are substantially less likely 

to earn low wages than those 

without a high school degree. 

See appendix III for more details 

about this analysis. 

Statistical Note 

Differences in the distribution 

of women and men within each 

reported characteristic were 

statistically significant at the 

95 percent confidence level. 

Source: GAO analysis of CPS data. 

Low-Wage Workers

Characteristics 
Page 24 GAO-12-10 Gender Pay Differences 

Appendix I October 2011

Among Low-Wage Workers in 20094

Married women—both with and without children in the household—had 

higher total household income compared with married men. 

Unmarried women with children in the household had the lowest total 

household income. 

On average, married women’s annual wage and salary earnings were 

less than a quarter of average total household income. In contrast, 

unmarried women’s earnings were over half of total household income. 

While the hourly wage was similar among all low-wage workers, women’s 

annual personal earnings were lower then men’s, regardless of marital 

status or presence of children in the household—in part because more 

women worked part-time (i.e., fewer hours per year) compared with men.5

Annual Household Income of Low-Wage Workers 

Source: GAO analysis of CPS data.

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

Men Women Men Women Men Women Men Women

$26,721

$33,465

$29,790 $31,078

$64,954

$54,246

$64,862

$40,889

Household

income

(in dollars)

57%

25%

18%

54%

33%

14%

54%

28%

18%

57%

31%

12%

Unmarried workers

Without children

in household

With at least

one child

Without children

in household

With at least

one child

Married workers

23%

57%

20%

34%

50%

16%

21%

67%

12%

45%

46%

10%

Annual wages and salary of the low-wage worker

Annual wages and salary of others in household

Income from outside the household (including government aid)

Note: Some percentages may not add to 100 percent because of rounding. 

 

4

This page shows 2009 data collected in 2010. See appendix VIII for the 

standard errors for estimates. 

5

In this analysis, a “full-time” worker was defined as one who worked 50 or more 

weeks per year, and 35 or more hours per week; all other workers were defined 

as “part-time.” 

Low-wage

workers

About Our Analysis 

We restricted this analysis to 

workers that were householders 

(or spouses of a householder)—

generally, those who owned, 

bought, or rented the home (this 

excludes children, other relatives, 

and nonrelatives in the household). 

This resulted in a population of 

16.7 million low-wage workers out 

of a total of 19.8 million low-wage 

workers in the entire workforce. 

See appendixes II and VIII for more 

details. 

Included in Total Household Income 

Annual wages and salary of worker

are defined as those earned solely by the 

low-wage worker. 

Annual wages and salary of others in 

household can include wages/salary of 

others in household who may not be lowwage workers. 

Income from outside the household

includes government benefits (such as 

Social Security, public assistance, 

veterans’ payments); retirement, 

investment, and rental income; and other 

sources of non-wage/salary income 

Wages and Job Status 

For this subpopulation of 16.7 million lowwage householders (or spouses of a 

householder) 

Full-time low-wage workers 

Men: 71 percent (4.2 million) 

Women: 58 percent (6.3 million) 

Part-time low-wage workers 

Men: 29 percent (1.7 million) 

Women: 42 percent (4.6 million) 

Source: GAO analysis of CPS data. 

Low-Wage Workers

Annual Household Income 
Appendix II: Objectives, Scope, and Appendix II: Objectives, Scope, and Methodology 

Methodology 

This appendix discusses in more detail the methodology for our study 

examining gender differences among less-advantaged workers—

pecifically, those with less education and those with low wages. Our 

study was framed around one question: What are the differences in 

representation, key characteristics, and pay among women and men (1) 

with less education and (2) with low wages? 

To perform this work, we analyzed data from the Department of Labor’s 

(DOL) Current Population Survey (CPS) to obtain information on the 

gender differences in representation, characteristics, and pay among 

workers who have less education or low wages. The CPS is administered 

by DOL’s Bureau of Labor Statistics and the Department of Commerce’s 

Census Bureau. 

 For our analyses of the differences in representation, characteristics, 

and pay, we used data from the outgoing rotation groups of the CPS 

(the basic monthly CPS). For representation and pay analyses, we 

used data covering 1980-2010; for characteristics analyses, we used 

2010 data. 

 For our analyses of annual income of the household or individual, we 

used the Annual Social and Economic (ASEC) Supplement, or March 

CPS supplement. We used 2009 ASEC data collected in 2010. 

We selected the CPS mainly because of the precision of the hourly wage 

information. In addition, CPS contains large sample sizes, and allowed us 

to present information over a long time period. 

 Our definition of working included those who were classified as 

employed. We excluded those individuals that were self-employed 

because of the difficulty of obtaining reliable estimates of earnings for 

those workers. 

 For both analyses, we limited our analysis to wage and salary earners 

in the civilian labor force, from age 25 to 64, with positive usual 

weekly hours and earnings (in the case of the monthly CPS), or 

positive annual earnings in the prior calendar year (in the case of the 

ASEC). 

 We defined “less-educated” as those with a high school degree or 

less. 

s

Analysis of Federal 

Datasets 

Definitions 

Page 25 GAO-12-10 Gender Pay Differences
Appendix II: Objectives, Scope, and 

Methodology 

Page 26 GAO-12-10 Gender Pay Differences

 We defined “low-wage” as those with an hourly wage rate in the 

bottom quintile (bottom 20 percent) of wages across the workfo

workers that reported positive earnings. For workers that were not 

paid an hourly wage, we estimated the hourly wage rate using we

earnings and usual hours worked per week. For the workers in our 

sample, we estimated that the bottom quin

rce for 

ekly 

tile of hourly wages was 

$11.00 or less in 2010. 

 more weeks per year. 

To determine workers that were low wage in this analysis, 

 For analysis of characteristics using the basic monthly CPS from 

d 

e household using the number 

00 

 primary family, and our analysis includes wage earners who 

 We limited the occupations reported to those that represented 95 

percent of the less-educated or low-wage population. 

 In the monthly CPS, a person was defined as full-time if he/she 

worked 35 hours or more per week. For the household income 

analyses, which used the ASEC, full-time was defined as 35 hours or 

more per week and 50 or

 For our analyses of annual household income, we restricted our 

analyses to workers that were “householders” (or the spouse of a 

householder)—generally, those who owned, bought, or rented the 

home (this excludes children, other relatives, and nonrelatives in 

household). 

we estimated the hourly wage using the annual wage and salary 

earnings, the usual hours worked per week, and the weeks worked 

during 2009. For the workers in this sample, we estimated that the 

bottom quintile of hourly wages was $11.90 or less. 

 We defined a person as having a child in the household differently 

based on the dataset we were using. 

2010, we defined a person as having a child if the person live

with their “own child” in the household. For analysis of the 

differences in hourly pay between women and men using the 

basic monthly CPS over the period 2000 through 2010, we 

defined the number of children in th

of children under 18 in the household, regardless of whether the 

children were the “own children” of the wage earner. We could not 

identify “own children” for all wage earners over the period 20

through 2010, because prior to 2010 the basic monthly CPS 

identified “own child” only for the head of the household or spouse

in the

were not part of the primary family. 
Appendix II: Objectives, Scope, and 

Methodology 

 For the ASEC, we combined information from person, family, 

household records. For persons to “have a child,” they had to 

meet two criteria. First, they had to be either the head or spouse

of the head of a family. Second, a family in the household had to 

have a child in the household under 18 years. In addition, becau

analyses that used the ASEC involved those individuals’ share o

household income, w

and 

se 

f 

e restricted the sample to householders or 

spouses of householders. We were able to closely approximate 

is 

ts 

ble for our analyses. 

Specifically, we 

e 

in 

ut 

e 

 Completed our own electronic data testing to assess the accuracy and 

against published reports using 

the CPS or other national surveys, like the American Community 

lity 

 the hourly wage. For other 

workers, an hourly wage can be estimated by using their usual weekly 

Data Reliability 

official counts of employed people with or without children by th

method. 

We assessed the reliability of the CPS generally and of data elemen

that were critical to our analyses and determined that, despite the 

limitations outlined below, they were sufficiently relia

 Reviewed documentation on the general design and methods of th

CPS and on the specific elements of the CPS data that were used 

our analyses. 

 Interviewed Census Bureau and BLS officials knowledgeable abo

the CPS data and consulted these officials periodically throughout th

course of our study. 

completeness of the data used in our analyses. To the extent 

possible, we compared our estimates 

Survey. 

Because CPS and ASEC are survey data collected from a probabi

sample, estimates produced from these data are subject to sampling 

error. We followed guidance from the Census Bureau and BLS to 

construct standard errors associated with the estimates presented in this 

report and to conduct statistical testing where appropriate. 

As a result of these efforts, we identified the following limitations with the

data: 

 Hourly wage estimates: In the CPS data, only workers that are paid 

an hourly wage are asked directly about

Page 27 GAO-12-10 Gender Pay Differences
Appendix II: Objectives, Scope, and 

Methodology 

pay and the usual hours worked. However, this introduces possible 

error into the hourly wage estimates.1 We tested the degree of this

error by comparing estimates of hourly wage from two separate CPS 

sources, and found that the data were sufficiently reliable for our 

purposes. 

 Definitions of occupation and industry that have changed over time: 

During the past decades, there have been changes in the definitions

of occupation and industry. In the CPS data, industries were coded 

using the Standard Industry Classification (SIC) system prior to 2000 

and using the North American Industry Classification System (NAICS) 

n on 

efined above. We also estimated the number of 

less-educated workers that were men and women within each industry 

s 

ean 

sample design used in the CPS, we 

used the person weight present in the CPS data file. In addition, for 

ing 

 

after 2000. Although it is possible to cross-walk between the two 

systems, this would also introduce a source of error. Consequently,

our regression estimates of the effect of industry and occupatio

wage begin in 2000, when the new industry classification system was 

in place. 

Gender Pay Differences

To analyze the representation of less-educated and low-wage men and 

women, we used CPS to estimate the number of men and women that 

were less educated, as d

and occupation, and the mean hourly wage. In addition, we estimated the 

number of men and women in the workforce that were low wage, a

defined above. We also estimated the number of low-wage workers that 

were men and women within each industry and occupation, and the m

hourly wage. To take account of the 

estimates of counts and proportions, standard errors were adjusted us

generalized variance functions provided by BLS. See appendix V. 

 

Methods 

Representation of LessEducated and Low-Wage 

Workers 

1

See, for example, Long Liu, 2009, “On Hourly Wages and Weekly Earnings in the 

Current Population Survey,” Economic Letters 105: 113-116. 

Page 28 GAO-12-10 
Appendix II: Objectives, Scope, and 

Methodology 

To analyze the characteristics of less-educated and low-wage men and 

women, we used CPS to generate descriptive statistics for women and 

men by age, race/ethnicity, education level, and job status (full- or parttime). In addition, we reported on the combination of marital status 

(married or unmarried) and the presence of children in the household. 

See appendix VI. 

o 

nd low-wage women and men in the workforce, we examined 

in (1) personal wage and salary earnings and (2) total 

15 

both less-educated and low-wage workers. See appendix VIII. 

We used multivariate analysis in two areas: (1) to examine the differences 

in pay between less-educated male and female workers and (2) to 

estimate the likelihood of being low wage. See appendix III. 

age 

een the hourly wage 

rates for women and men in the low-wage group was less than 1 percent, 

Characteristics of LessEducated and Low-Wage 

Workers 

Characteristics of LessEducated Workers for Tw

Industries 

d Low-Wage 

Workers 

Pay of Less-Educated and 

Low-Wage Workers 

We also did analysis on the characteristics of less-educated workers in tw

industries—retail trade and manufacturing—that employ a large number of 

less-educated women and men. We used CPS to generate descriptive 

statistics for less-educated women and men by age, race/ethnicity, 

education level, and job status (full- or part-time). In addition, we reported 

on the combination of marital status (married or unmarried) and the 

presence of children in the household. See appendix VII. 

o 

Household Income of Less- To analyze the differences in household income between less-educated 

Educated an a

differences 

household income. Because this analysis involved annual income, we 

used data from the March CPS ASEC supplement, which asks 

respondents about personal wage and salary earnings as well as other 

forms of household income over the prior year. 

Given that differences in total household income are affected by the total 

number of individuals in the household, we performed separate analyses

by marital status and the presence of children in the household. To avoid 

double counting of people within the same household (such as parent and 

child), we restricted our analysis to individuals that were householders or 

the spouses of householders—generally those who owned, bought, or 

rented the home, excluding children, other relatives, and nonrelatives in 

the household. This resulted in a reduction in sample size of about 

percent for 

We did not conduct multivariate analysis to examine the pay of low-w

workers, because we found that the difference betw

Page 29 GAO-12-10 Gender Pay Differences
Appendix II: Objectives, Scope, and 

Methodology 

in part because of the limiting effect of the minimum wage. By definition, 

all low-wage workers were below the 20 percent wage threshold and, wi

rare exceptions, at or above the federal minimum wage. 

To provide the app

th 

ropriate context for this report, we (1) reviewed 

selected GAO and other reports and articles on similar topics and 

) interviewed agency officials (BLS and Census Bureau) and 

nce in 

did not 

 explaining the 

differences. Models with different variables can result in differences in the 

stimates (see app. III). In addition, some factors are difficult to measure, 

t 

quires that we plan and 

perform the engagement to obtain sufficient and appropriate evidence to 

Document Reviews 

and Interviews 

Limitations 

(2

representatives of women’s groups and other researchers. 

This report did not attempt to provide an explanation for any differe

earnings between less-educated women and men that persists after 

controlling for available factors that may affect pay. In addition, we 

compare the relative importance of any of the variables in

e

and as a result, our analysis cannot determine whether differences in 

industry, occupation, or pay are due to factors such as years of 

experience, worker choice, or discrimination. 

We conducted our work from January 2011 to October 2011 in 

accordance with all sections of GAO’s Quality Assurance Framework tha

are relevant to our objectives. The framework re

meet our stated objectives and to discuss any limitations in our work. We 

believe that the information and data obtained, and the analysis 

conducted, provide a reasonable basis for any findings and conclusions in

this product. 

Page 30 GAO-12-10 Gender Pay Differences
Appendix III: Multivariate Analysis 

Page 31 GAO-12-10 

Appendix III: Multivariate Analysis 

We used multivariate analysis in two areas: (1) to examine the differences

in pay between less-educated male and female workers and (2) to 

estimate the difference between male and female workers in likelihood of 

being low wage. 

en 

 groups 

analysis to those working and not self-employed, because of limitations 

ith calculating hourly wages for self-employed workers. In this analysis, 

nal 

r 

we 

garithm of hourly wage 

rate. We estimated three models with varying levels of controls. Model 1 

vector of 

mmy 

1980 to 2010). Because of variable coding changes over 

time, we estimated models 2 and 3 for the most recent 11 years, 2000-

2010.1

 

We conducted a regression analysis of the differences in pay betwe

less-educated men and women using the 2010 outgoing rotation

of the Current Population Survey (the basic monthly CPS). We limited the 

Differences in Pay 

w

we used an indicator variable for gender to measure the average 

difference between men’s and women’s salaries. By including additio

variables in the regression, we adjusted for other characteristics of men 

and women, and determined the extent to which the difference was (or 

was not) explained by the addition of those variables. 

To determine the extent to which gender differences persist when othe

characteristics of less-educated workers are taken into account, 

performed regression analysis to predict the lo

included no explanatory factors. Model 2 included the following 

characteristics: age, age squared, and dummy variables for race, 

Hispanic status, state, veteran status, high school degree, citizenship, 

marital status, part-time status, union membership, and the number of 

children in the household. Regression model 3 included the following 

vector of characteristics: all variables in model 2 in addition to du

variables for industry and occupation. We estimated model 1 for 31 years 

of CPS data (

1

We performed the multivariate regression over a shorter time period because of the need 

for consistent occupation and industry designations. We did not examine interaction terms 

for the control variables. 

Gender Pay Differences 
Appendix III: Multivariate Analysis 

Page 32 GAO-12-10 Gender Pay Differences

(1) Model 1: Without controlling for factors 

Ln(hourly wage rate) =  + 1*(female) + 

(2) Model 2: 

Ln(hourly wage rate) =  + 2*(female) + 1*(vector of characteristics of 

the individual) + 

(3) Model 3: 

Ln(hourly wage rate) =  + 3 (female) + 2*(vector of characteristics of the 

individual) + *(vector of industry and occupation dummy variables) 

In these models, 1, 2 ,and 3 are coefficients on the indicator variable 

for female in the different models, 1 and 2 are vectors of coefficients on

individual characteristics,  is a vector of coefficients on

+ 

 occupation and 

industry, and  is the error term. Because we used the logarithm of the 

n 

en 

the 

s 

and men has gradually narrowed and was similar to the 

unadjusted difference. After adjusting for industry and occupation, as well 

s other available factors that may affect pay, the unexplained difference 

in hourly wages between less-educated women and men narrowed even 

ore from 2000 to 2010. 

 

hourly wage rate, the standard interpretation of the ’s (the coefficients o

female), is that they represent the average log point difference betwe

men and women, after adjusting for the other variables in the model. 

Following practice in the economic literature, that coefficient was 

modified, to more closely approximate a percentage difference (by 

exp[coefficient on female]).2

Table 1 shows the estimated coefficient on female by year. Standard 

errors are in parentheses. As the table shows, over time (1980-2010), 

difference in hourly wages between less-educated women and men ha

gradually narrowed, without adjusting for factors that may affect pay. After 

adjusting for available factors that may affect pay—except for industry 

and occupation—the difference in hourly wages between less-educated

women 

a

m

2

Francine Blau and Lawrence Kahn, “Gender Differences in Pay,” The Journal of 

pectives, Vol. 14, No. 4 (2000). This is an issue that is especially important 

80). 

Economic Pers

if the pay differences are large. See Robert Halvorsen and Raymond Palmquist, “The 

Interpretation of Dummy Variables in Semi-logarithmic Equations” American Economic 

Review, Vol. 70, No.3 (19
Appendix III: Multivariate Analysis 

Table 1: Estimated Coefficient for Women by Year 

Model 1 

(unadjusted difference) 

Model 2 

d difference controlling for 

ividual characteristics) 

Model 3 

(adjusted difference controlling for 

individual characteristics, industry, 

and occupation) 

(adjuste

ind

Year Coefficient (1)

Women’s p

percen

of m 2) of men’s Coefficient (3) of men’s

ay as 

tage 

en’s Coefficient (

Women’s pay as 

percentage 

Women’s pay as 

percentage

1980 -0.436 65 

 (0.003) 

1981 -0.423 65 

 (0.003) 

1982 -0.403 67 

 (0.004) 

1983 -0.394 67 

 (0.004) 

1984 -0.386 68 

 (0.004) 

1985 -0.378 68 

 (0.004) 

1986 -0.363 70 

 (0.004) 

1987 -0.349 71 

 (0.004) 

1988 -0.346 71 

 (0.004) 

1989 -0.329 72 

 (0.004) 

1990 -0.308 74 

 (0.004) 

1991 -0.281 76 

 (0.004) 

1992 -0.270 76 

 (0.004) 

1993 -0.261 77 

 (0.004) 

1994 -0.275 76 

 (0.005) 

1995 -0.281 76 

 (0.005) 

1996 -0.270 76 

 (0.005) 

1997 -0.268 77 

 (0.005) 

 

Page 33 GAO-12-10 Gender Pay Differences
Appendix III: Multivariate Analysis 

Model 1 

(unadjusted difference) 

Model 2 

(adjusted difference controlling for 

individua s) 

Model 3 

(adjusted difference controlling for 

individual cha cs, industry, 

l characteristic

racteristi

and occupation) 

Year Coefficien 1

’s pay as 

tage 

t ( ) Coefficien 2 Coefficien 3

Women

percen

of men’s t ( )

Women’s pay as 

percentage

of men’s t ( ) 

Women’s pay as 

percentage 

of men’s

1998 -0.266 77 

(0.005) 

1999 -0.278 76 

(0.005) 

2000 -0.259 77 -0.242 78 -0.208 81

(0.005) (0.005) (0.006) 

2001 -0.246 78 -0.228 80 -0.191 83

(0.005) (0.005) (0.006) 

2002 -0.234 79 -0.217 80 -0.184 83

(0.005) (0.005) (0.006) 

2003 -0.227 80 -0.226 80 -0.186 83

(0.005) (0.005) (0.006) 

2004 -0.223 80 -0.219 80 -0.196 82

(0.005) (0.005) (0.006) 

2005 -0.226 80 -0.216 81 -0.181 83

(0.005) (0.005) (0.006) 

2006 -0.225 80 -0.220 80 -0.172 84

(0.005) (0.005) (0.006) 

2007 -0.227 80 -0.217 80 -0.180 84

(0.005) (0.006) (0.007) 

2008 -0.237 79 -0.228 80 -0.182 83

(0.005) (0.006) (0.006) 

2009 -0.216 81 -0.214 81 -0.172 84

(0.006) (0.006) (0.007) 

2010 -0.205 81 -0.192 83 -0.150 86

(0.006) (0.006) (0.007) 

So analysis of CPS data. 

Note: Standard errors are shown in parentheses below the point estimates. 

urce: GAO

Page 34 GAO-12-10 Gender Pay Differences
Appendix III: Multivariate Analysis 

In addition to the main analysis, we also performed analyses on 

subpopulations. Table 2 shows the results of these regression analyses for 

work s with children, workers without ch ldren, married and unmarried 

workers with and without children, and also for workers in two industries: 

retail trade and manufacturing. This analysis was done only for 2010. 

In general we found that the gender pay difference was larger for workers 

with children than for workers without children; the pay difference was 

also generally larger for married workers than for unmarried workers. 

Among married workers, however, th

workers with children was almost the me as the pay differenc

among workers without children. 

: Estimated C t for Women b cted Chara cs and Industries, Calendar Yea

er i

e gender pay difference among 

 sa gender e 

Table 2 oefficien y Sele cteristi r 2010 

Mode

(unadjusted d nce) 

Model 2 

ted difference

olling for individual 

aracteristics) 

odel 3 

(adju erence controllin

for i l characteristics, 

ind nd occupation) 

l 1

iffere

(adjus

contr

ch

M

sted diff

ndividua

g 

ustry, a

Characteristic Coefficient 

W pay 

as r tage 

n’s ient

Women’s p as 

perc ge 

of men’s C t

Women’s pa 

as percenta

of men’s

o

 pe

men’s

cen

of me Coeffic

ay

enta

oefficien

y

ge 

Marriage/children 

Workers without children -0.167 85 -0.176 84 -0.141 87

(0.007) 08) 9)

rs with children -0.271 76 232 79 9

(0.0 (0.00

Worke -0. -0.17 84

(0.011) 11) 3)

ried, without chi -0.112 89 129 88 6

(0.0 (0.01

Unmar ldren -0. -0.08 92

(0.011) 11) 3)

ried, with childr -0.183 83 181 83 9

(0.0 (0.01

Unmar en -0. -0.14 86

(0.025) 24) 8)

Married, without children -0.233 80 -0.206 81

(0.0 (0.02

79 -0.227

 (0.010) 12)

Married, with children -0.259 77 -0.245 78 -0.189 83

(0.010) (0.0

 (0.013) (0.013) (0.015)

Selected Industriesa 

Manufacturing -0.212 81 -0.185 83 -0.193 82

 (0.013) (0.012) (0.012)

Retail trade -0.197 82 -0.157 86 -0.153 86

 (0.014) (0.015) (0.016)

Source: GAO analysis of CPS data. 

ote: Standard errors are shown in parentheses below the point estimates. 

a

In the regressions for specific industries, Model 3 includes all the factors in Model 2 plus controls for 

occupation, but does not include controls for industry. 

N

Page 35 GAO-12-10 Gender Pay Differences
Appendix III: Multivariate Analysis 

The likelihood of being low wage is associated with gender. Of t

approximately 47.2 million women workers, 11.6 million are low wage 

(about 25 percent). In comparison, of the 49.5 million male workers, ab

8.2 million are low wage (about 17 percent). However, other factors affect 

being low wage as well, such as education. About 55 percent of thos

he 

out 

e 

with less than a high school degree are low wage, as compared with 28 

nique called logistic regression. 

Specifically, logistic regression allowed us to address relative 

orce, and the 

d with 

differences in other facto ing education, industry, occupation, and 

ics of t regre

chniqu cher 

ent occurring ing a low-wage wo

 or more expla For this analysis, 

basi C t—the s S ata n the o

modeling. Unlike in the analysis of pay differences among the 

less educa , in th ysis, we inclu ll workers and did not limit

to those who were ucated. We estimated the following model: 

Logit(probability tha rker is low wage) =  + *( + *(vector of 

other expl tory va s) + 

After estimation, any coefficient can be transformed into what is known 

an odds ratio.3 For example, in the case of gender, it is the odds of a 

woman be a low-wage worker over the corresponding odds for a ma

If 11.6 of 47.2 million women are low wage, then the odds of a woman 

being low ge is 1 .2-11.6), or 0 . n the o nd, if 8.2 of

49.5 million men are low wage, the odds of a man being low wage is 

8.2/(49.5-8.2), or 0.20. In this case, an odds ratio of about 1.6 (.33/.20) 

represents e incre ikelihood of a woman being low wage—a 

 

percent with a high school degree, 20 percent with some college, and 

only 7 percent of those with a bachelor’s degree or higher. 

To investigate the extent to which differences in education and other 

factors explain differences in the likelihoods of men and women being low

wage, we used a multivariate tech

representation of men and women in the low-wage workf

extent to which differences in representation were associate

rs, includ

he individual. Logistic 

e—enables the resear

characterist

statistical te

ssion—a widely used 

to examine how the relative

odds of an ev

related to one

c monthly

(in this case, be

natory factors. 

ame CP

rker) are 

we used the 

PS datase d we used i ther 

regression 

ted is anal ded a it 

less ed

t a wo female)

ana riable

as 

ing n. 

wa 1.6/(47 .33 O ther ha

 th ased l

 dds of being a lowLikelihood of Being Low 

Wage 

3

An odds ratio of 1.0 would indicate that women and men have equal o

wage worker. 

Page 36 GAO-12-10 Gender Pay Differences
Appendix III: Multivariate Analysis 

woman has about 60 percent greater odds than a man of earning lo

wages. 

The logistic method allows the researcher to estimate how the odds ratio 

changes when other characteristics are controlled for, similar to how a 

regression allows a researcher to control for characteristics when 

examining differences in pay. Table 3 shows the relative odds of being

low-wage worker, unadjusted, and then provides the results

w 

 a 

 of the logistic 

analysis with the same statistical controls used in the multivariate 

rs. 

bles for 

did not 

wage 

whether those odds are adjusted or not. The adjusted odds for a high 

t graduate from high school. A worker 

with some college had about a third of the odds (37 percent) as a worker 

ot 

 

regression analysis of differences in pay among less-educated worke

All explanatory factors were defined in the same way as in that analysis 

except for education, which was expanded to include dummy varia

“some college” and “college degree or higher” (categories that 

exist in the less-educated population). As table 3 shows, adding the 

statistical controls did not reduce the odds of a women being a lowworker. In contrast, the odds ratio changed from 1.64 to 1.74, an increase 

of about 7 percent. In this analysis, we did not attempt to provide an 

explanation for any difference in likelihood of earning lower pay between 

women and men that persists after controlling for available factors that 

may affect pay. 

Using the same statistical controls to isolate the effect of gender, we also 

attempted to isolate the effect of education. As table 3 shows, increased 

education substantially reduced the odds of being a low-wage worker,

school graduate being a low-wage worker were about half (49 percent) as 

much as for a worker who did no

that did not graduate from high school. A college graduate had about a 

sixth of the odds of being a low-wage worker than a worker who had n

graduated from high school.4

 

t the traditional ages for completing high school or college. 

4

 Because this analysis, like the others, was restricted to those aged 25-64, it did not 

include those a

Page 37 GAO-12-10 Gender Pay Differences
Appendix III: Multivariate Analysis 

Table 3: Odds Ratios of Being Low Wage from Logistic Regression Analysis 

Odds ratios—

unadjusted 

individual characteristics, 

industry, and occupation

Odds ratios—adjusted for 

Women (versus men) 1.64 1.74

(1.67–1.81)

High school diploma 

(versus no high school 

diploma) 

0.33 0.49

(0.47–0.52)

Some college (versus no 

high school diploma) 

0.21 0.37

(0.35–0.40)

College degree or higher 

(versus no high school 

diploma) 

0.06 0.16

(0.15–0.18)

Source: GAO analysis of CPS data. 

Note: Ninety-five percent confidence intervals are shown in parentheses. 

In order to check that the results of the logistic regression analysis were 

not overly dependent on the particular outcome variable we used, we 

conducted sensitivity analyses in which models were fit using not only the 

20th percentile but also the 15th and 25th percentiles of the hourly wage 

rate distribution as cutoffs for “low wage.” These three models yielded 

substantively similar results. 

Page 38 GAO-12-10 Gender Pay Differences
Appendix IV: Description of Industries and 

Occupations 

Page 39 GAO-12-10 

Appendix IV: Description of Industries and 

Occupations 

Table 4: Examples of Areas Contained within Each Industry 

Industry category Examples 

Agriculture and mining Animal and crop production, fishing, forestr g, 

extraction, trapping 

y, hunting, loggin mining, oil and gas 

Construction C , heavy and civil engineering truction, specialty trade 

contractors 

onstruction of buildings cons

Educational services B ges and universities, compute management training, 

e es, elementary and secondary schools, technical and

s

usiness schools, colle

ducational support servic

chools 

r and 

 trade 

Financial activities B ntal services, funds and , insurance carriers, real es

s urities and commodities 

anking, consumer goods re

avings institutions, sec

 trusts tate, 

Health care and social assistance C munity food and housin dividual and family 

s tial care facilities, offices of health practitioners (p

dentists, chiro etrists, etc), outpatient and home health care cen

hild day care services, com

ervices, nursing and residen

practors, optom

g, hospitals, in

hysicians, 

ters 

Information and communication Broadc ng, motion picture and sound recording industries, publishing 

industries, tele

asting, data processi

communications 

Leisure and hospitality Accommodation services, amusement and gambling, historical sites, independent artists, 

museums, performing arts, restaurants and taverns, spectator sports and recreation 

Manufacturing C

m

p

m

omputer and electronic product manufacturing, food manufacturing, machinery and 

etal product manufacturing, petroleum and chemical manufacturing, plastics and rubber

roducts manufacturing, printing, textile product mills, transportation equipment 

anufacturing, wood and paper product manufacturing 

Other services A

p

m igious organizations 

utomotive repair and maintenance, barber shops and beauty salons, civic and 

rofessional organizations, funeral homes, laundry services, personal goods repair and 

aintenance, private households, rel

Professional and business services Administrative support, management of companies and enterprises, professional services, 

scientific and technical services, waste management services 

Public administration Administration of public programs, community development, executive and legislative 

government bodies, justice and public order, national security and international affairs, 

public finance, urban planning 

Retail trade Automobile dealers, book and music stores, building material and garden equipment 

dealers, clothing stores, electronics and appliance stores, food and beverage stores, 

furniture and home furnishings stores, gasoline stations, general merchandise stores, 

health and personal care stores, nonstore retailers, sporting goods stores 

Transportation and utilities Air transportation, couriers and messengers, electric power, natural gas distribution, postal 

service, sightseeing transportation, transit and ground passenger transportation, 

transportation support activities, truck and rail transportation, warehousing and storage, 

water transportation, water and sewage 

Wholesale trade Durable and nondurable goods wholesalers, wholesale electronic markets 

Source: U.S. Bureau of Labor Statistics, 2007 North American Industry Classification System, last revised February 28, 2011. 

Note: This list contains examples for illustrative purposes only and is not a complete list. 

Gender Pay Differences 
Appendix IV: Description of Industries and 

Occupations 

Page 40 GAO-12-10 Gender Pay Differences

Table 5: Examples of Areas Contained within Each Occupation 

Occupation category Examples 

Business and finance Claim , 

marke

s adjusters, cost estimators, event planners, fundraisers, human resources workers

t researchers 

Cleaning and maintenance Janito

cleaners, pest control workers, tree trimmers 

rs and cleaners, landscaping and groundskeeping workers, maids and housekeeping 

Construction and extraction Brick rators, 

const s, 

highw nce workers, mining machine operators, painters, plumbers, pipe fitters, 

roofe

masons, carpenters, carpet installers, cement masons, construction equipment ope

ruction laborers, earth drillers, explosives workers, hazardous materials removal worker

ay maintena

rs 

Education, training, and library Adult education instructors, graduate teaching assistants, library technicians, teacher assistants 

Farming, fishing, and forestry Agric

relate

ultural equipment operators, animal breeders, farm workers and laborers, fishers and 

d fishing workers, forest and conservation workers, hunters and trappers, logging workers 

Food preparation and serving Barte

worke

nders, chefs, cooks, dishwashers, fast food and counter workers, food preparation 

rs, hosts and hostesses, waiters and waitresses 

Health care practitioners and Athle nicians, medical records technicians, paramedics, 

technicians pharm

tic trainers, clinical laboratory tech

acy technicians 

Health care support Home

prepa

 health aides, laboratory animal caretakers, massage therapists, medical equipment 

rers, nursing assistants, orderlies, therapist assistants, veterinary assistants 

Installation, maintenance, and 

repair 

Autom

heatin

teleco

otive technicians and repairers, electric motor repairers, electrical power line installers, 

g and air conditioning installers, security and fire alarm systems installers, 

mmunications equipment installers 

Management General and operations managers, human resources managers, marketing and sales managers

Office and administrative support Broke , customer service 

repre

reade

secre perators, tellers 

rage clerks, computer operators, couriers and messengers

sentatives, data entry keyers, dispatchers, file clerks, insurance claims clerks, meter 

rs, postal service mail carriers, proofreaders, receptionists, transportation ticket agents, 

taries and administrative assistants, stock clerks, switchboard o

Personal care and service Bagg

servic

age porters, barbers, bellhops, child care workers, funeral service workers, gaming 

es workers, hairdressers, ticket takers, tour guides, ushers 

Production Assem e 

tool o

printin

make

blers and fabricators, bakers, butchers and meat cutters, computer-controlled machin

perators, laundry workers, machinists, metal and plastic workers, pourers and casters,

g workers, sewing machine operators, shoe and leather workers, tailors, tool and die 

rs, upholsterers, welders, woodworkers 

Protective service Anim

inves

worke

scree

al control workers, bailiffs, correctional officers, crossing guards, detectives and criminal 

tigators, firefighters, fish and game wardens, jailers, lifeguards, parking enforcement 

rs, police and sheriff’s patrol officers, security guards, ski patrol, transportation security 

ners 

Sales and related Cashi

sales

ers, door-to-door sales workers, models, real estate brokers and sales agents, retail 

persons, sales representatives, street vendors, telemarketers, travel agents 

Transportation and material moving Bus dr

locomo rial 

collect s, ship and boat captains and operators, subway operators, taxi drivers, transportation 

inspectors 

ivers, chauffeurs, crane operators, flight attendants, heavy and light truck drivers, 

tive engineers and operators, parking lot attendants, refuse and recyclable mate

or

Source: U.S. Bureau of Labor Statistics, 2010 Standard Occupational Classification, January 2009. 

Note: This list contains examples for illustrative purposes only and is not a complete list. It also 

includes occupations that may or may not be associated with low wages or less education. 
Appendix V: Representation by Industry and 

Occupation for Less-Educated and Low-Wage 

Workers 

Page 41 GAO-12-10 

Appendix V: Representation by Industry and 

Occupation for Less-Educated and Low-Wage 

Workers 

Table 6: Less-Educated Workers by Industry, Calendar Year 2010 

Industry 

ber of 

men 

Perc

rage 

women of total

Average 

women number of total

rage 

ourly 

wage

Num entage 

of total 

hourly 

wage for 

men

Number of Percentage 

hourly 

wage for Total Percentage 

Ave

h

Ave

Agriculture and 750,862 4 $15.68 135,524 1 $12.21 886,386 3 $15.15

mining (31,044) (0.58) (34,333) (0.29)

2 

 (0.33) (12,807)

Construction 2,975,90 15 19.11 178,243 1 17.74 3,154,145 9 19.03

 (61,048) )

504,557 3 16.25 1,101,759 7 14.09 1,606,316 5 14.77

(0.22) (14,684) (0.60) (64,363) (0.21

Educational 

services (25,482) (0.33) (36,322) (0.24) (46,128) (0.20)

Financial 485,134 3 18.27 1,125,781 7 17.40 1,610,915 5 17.66

activities (24,989)

14.08

 (0.48) (36,711) (0.26) (46,193) (0.23)

Health care and 620,513 3 16.04 3,157,288 21 13.70 3,777,802 11

social (28,241) assistance 

20.35

 (0.39) (60,784) (0.13) (70,317) (0.13)

Information and 318,804 2 21.11 211,416 1 19.22 530,220 2

communication (20,276) (15,989) (0.84) (26,580) (0.51)

22 

 (0.64)

Leisure and 1,650,3 9 13.15 1,751,550 12 11.24 3,401,872 10 12.17

hospitality (45,797) (0.12)

7

 (0.20) (45,632) (0.13) (66,797) 

Manufacturing 3,856,178 20 17.92 1,594,513 10 14.35 5,450,691 16 16.8

(69,151) 

 886,596 

 (0.14) (43,577) (0.22) (84,070) (0.12)

Other services 5 16.41 886,825 6 12.52 1,773,421 5 14.46

 (33,708) 

1,575,382 

(0.33) (32,626) (0.22) (48,446) (0.20)

Professional 8 16.56 1,136,813 7 14.55 2,712,195 8 15.72

and business 

services (44,764) 9)

21 4 19.47

 (0.27) (36,888) (0.26) (59,757) (0.1

Public 702,9 21.29 660,995 4 17.53 1,363,916 4

administration (30,044) (0.27)

2,250,327 

 (0.41) (28,202) (0.33) (42,533) 

Retail trade 12 15.71 2,404,691 16 12.69 4,655,018 13 14.15

(53,302) 2)

1,975,214 .55

(0.18) (53,273) (0.14) (77,865) (0.1

Transportation 10 20.18 555,490 4 17.29 2,530,704 7 19

and utilities (50,013) (0.38) (57,752) (0.21)

830,095 23

 (0.24) (25,869)

Wholesale trade 4 17.86 287,197 2 15.42 1,117,292 3 17.

 (32,626) (0.28)

Total 19,382,809 98

(0.32) (18,628) (0.56) (38,522) 

100 $17.48 15,188,084 100 $14.06 34,570,893 100 $15.

 (140,810) (0.07) (123,910) (0.07) (193,659) (0.05)

Source: GAO analysis of data from the Current Population Survey. 

Note: Standard errors are shown in parentheses below the point estimates. The wages are annual 

averages of monthly data. 

Gender Pay Differences 
Appendix V: Representation by Industry and 

Occupation for Less-Educated and Low-Wage 

Workers 

Page 42 GAO-12-10 Gender Pay Differences

Table 7: Less-Educated Workers by Occupation, Calendar Year 2010 

Occupation 

Number 

of men 

Percentage 

of total 

Average 

hourly 

wage for 

men

Number of 

women

Percentage 

of total

Average 

hourly 

wage for 

women

Total 

number 

Percentage 

of total

Average 

hourly 

wage

Business and 176,561 1 $23.28 425,086 3 $20.07 601,647 2 $21.01

finance (15,101) (0.92) (22,646) (0.48) (28,308) (0.44)

Cleaning and 1,424,809 7 13.54 1,170,599 8 10.81 2,595,409 8 12.31

maintenance (42,606) (0.19) (37,425) (0.16) (58,475) (0.13)

Construction 2,990,651 15 18.98 46,962 0 15.47 3,037,612 9 18.93

and extraction (61,194) (0.21) (7,543) (1.15) (63,183) (0.21)

Education 68,569 0 20.23 443,042 3 14.48 511,611 1 15.25

training, a

library 

, 

nd 

1,

(9,416) (1.24) (23,117) (0.37) (26,111) (0.37)

Food 130,349 6 11.80 1,413,263 9 10.54 2,543,612 7 11.10

preparation an

serving 

d (38,010) (0.18) (41,067) (0.13) (57,897) (0.11)

Health care 82,657 0 21.02 403,525 3 18.24 486,181 1 18.71

practitioners 

and technicians 

1 1 7 1 3

(10,337) (1.34) (22,066) (0.42) (25,455) (0.42)

Health care 104,308 14.09 ,018,734 12.43 ,123,042 12.58

1 10 0 1 6

support (11,611) (0.78) (34,943) (0.18) (38,621) (0.18)

Installation, ,906,499 19.66 59,214 15.93 ,965,712 19.55

maintenance, 

and repair (49,154) (0.21) (8,469) (0.87) (50,978) (0.20)

Management 986,936 5 25.37 750,644 5 19.93 1,737,580 5 23.02

(35,545) (0.44) (30,039) (0.40) (47,958) (0.31)

Office and 1,282,703 7 16.60 4,029,572 27 15.89 5,312,276 15 16.06

administr

support 

ative (40,457) (0.24) (68,330) (0.13) (83,028) (0.11)

Personal care 218,181 1 13.77 965,021 6 11.82 1,183,202 3 12.18

and service (16,783) (0.44) (34,019) (0.28) (39,635) (0.24)

Production 2,946,861 15 17.07 1,260,306 8 12.38 4,207,167 12 15.67

(60,760) (0.16) (38,814) (0.15) (74,117) (0.12)

Protective 596,364 3 18.05 198,440 1 14.26 794,804 2 17.10

service (27,689) (0.42) (15,492) (0.56) (32,519) (0.35)

Sales a 1,369,766 7 17.31 1,882,320 12 12.80 3,252,085 9 14.70

related

nd 

16 4 11

(41,788) (0.26) (47,271) (0.18) (65,337) (0.16)

Transportation 3,168,669 16.15 608,201 12.76 3,776,870 15.61

and material 

moving (62,927) 

Total 19,382,809 100 100 $14.06 34,570,893 100 $15.98

(0.16) (27,060) (0.32) (70,309) (0.14)

 $17.48 15,188,084

 (140,810) (0.07) (123,910) (0.07) (193,659) (0.05)

Source: GAO analysis of data from the Current Population Survey. 

Note: Standard errors are shown in parentheses below the point estimates. This list represents about 

95 percent of the total less-educated workforce; occupations with a small number of workers were 

omitted. Because of the omissions, columns will sum to less than the totals listed in the table. The 

wages are annual averages of monthly data. 
Appendix V: Representation by Industry and 

Occupation for Less-Educated and Low-Wage 

Workers 

Table 8: Low-Wage Workers by Industry, Calendar Year 2010 

Industry 

Number 

of men 

Percentage 

of total 

Average 

hourly 

wage for 

men

Number of 

women

Percentage 

of total

Average 

hourly 

wage for 

women

Total 

number 

Percentage 

of total

Average 

hourly 

wage

Agriculture and 329,434 4 $8.33 107,225 1 $8.25 436,659 2 $8.31

mining 

9 1 4

(20,683) (0.12) (11,393) (0.18) (24,127) (0.10)

Construction 740,624 8.94 75,271 8.63 815,895 8.92

(30,833) (0.07) (9,548) (0.23) (32,946) (0.06)

Educational 304,957 4 8.62 1,103,943 10 8.53 1,408,901 7 8.55

services (1

243,4 5

9,832) (0.12) (36,358) (0.06) (43,224) (0.05)

Financial 92 3 8.34 550,487 8.93 793,979 4 8.75

activities 

5 2 23 3 16

(17,727) (0.17) (25,753) (0.08) (32,503) (0.08)

Health care and 437,041 8.60 ,665,586 8.73 ,102,627 8.71

social 

assistance (2

1 1 1

3,724) (0.11) (56,006) (0.04) (63,844) (0.03)

Information and 119,124 8.61 147,331 8.62 266,455 8.62

communication (12,407) (0.23) (13,352) (0.17) (18,856) (0.14)

Leisure and 1,269,569 16 8.59 1,674,666 14 8.23 2,944,234 15 8.38

(4

1 13 7 7 1 9

hospitality (40,252) (0.05) 4,639) (0.05) (62,220) (0.03)

Manufacturing ,038,250 8.98 85,701 8.93 ,823,951 8.96

5 7 1 6

(36,447) (0.06) (30,727) (0.06) (49,124) (0.04)

Other services 442,601 8.28 813,248 8.32 ,255,849 8.31

10 7 1 8

(23,874) (0.11) (31,256) (0.07) (40,826) (0.06)

Professional and 840,802 8.77 837,329 8.68 ,678,131 8.72

business 

services (32,834) (0.06) (31,711) (0.06) (47,138) (0.04)

Public 248,916 3 8.59 301,406 3 8.84 550,323 3 8.72

administration 

 1, 1 2, 1 3 1

(17,923) (0.15) (19,082) (0.11) (27,078) (0.09)

Retail trade 349,290 7 8.76 130,408 8 8.67 ,479,699 8 8.71

(41,479) (0.05) (50,220) (0.04) (67,542) (0.03)

Transportat 535,895 7 8.67 247,540 2 8.90 783,436 4 8.74

and utilit

ion 

ies (26,257) (0.09) (17,298) (0.11) (32,287) (0.07)

Wholesale trade 277,162 3 8.82 152,722 1 8.77 429,884 2 8.81

(18,909) (0.13) (13,594) (0.13) (23,940) (0.10)

Total 8,177,158 100 $8.70 11,592,864 100 $8.62 19,770,021 100 $8.65

(98,214) (0.02) (110,776) (0.02) (153,544) (0.01)

Source: GAO analysis of data from the Current Population Survey. 

Note: Standard errors are shown in parentheses below the point estimates. The wages are annual 

averages of monthly data. 

Page 43 GAO-12-10 Gender Pay Differences
Appendix V: Representation by Industry and 

Occupation for Less-Educated and Low-Wage 

Workers 

Table 9: Low-Wage Workers by Occupation, Calendar Year 2010

Occupation 

Number of 

men 

Percentage 

of total 

Average 

hourly 

wage for 

men

Number of 

women

Percentage 

of total

Average 

hourly 

wage for 

women

Total 

number 

Percentage 

of total

Average 

hourly 

wage

Cleaning and 816,201 10 $8.75 964,916 8 $8.39 1,781,116 9 $8.55

maintenance (32,355) (0.06) (34,017) (0.05) (48,550) (0.04)

Construction 728,783 9 9.01 24,240 0 8.55 753,023 4 9.00

and extraction

1 7 6 4

(30,588) (0

8.23

.07) (5,420) (0

8.54

.23) (31,657) (

8.51

0.06)

Education, 95,713 29,860 825,572 

(0 (0 ( training, and 

library (11,123) .26) (29,624) .07) (33,140) 0.07)

Farming, fi 260,426 3 8.24 95,013 1 8.38 355,439 2 8.28

and forestr

shing, 

y 

11 1 12 2 12

(18,331) (0

8.58

.12) (10,726) (0

8.21

.16) (21,773) (

8.36

0.10)

Food 939,792 ,366,822 ,306,614 

(0 (0 (

3 2

preparation and 

serving (34,695) .06) (40,397) .05) (55,169) 0.04)

Health care 65,777 1 8.86 373,913 8.81 439,690 8.82

practitioners 

and technicians (9,222) (0 (0 (

1 8 1 5

.33) (21,245) .10) (24,211) 0.10)

Health care 88,554 8.98 962,486 8.79 ,051,040 8.81

(0 (0 (

5 0 2

support (10,699) .19) (33,975) .05) (37,370) 0.05)

Installation, 398,894 8.79 26,540 8.75 425,434 8.78

(0 (0 (

Management 3 3 3

maintenance, 

and repair (22,670) .10) (5,671) .35) (23,816) 0.09)

227,841 8.24 311,999 8.63 539,839 8.47

(17,149) (0 (0 (

8 2 17 2 14

.18) (19,413) .13) (26,819) 0.11)

Office and 662,800 8.86 ,019,132 9.09 ,681,932 9.03

(0 (0 (

3 1 9 1 6

administrative 

support (29,181) .07) (48,921) .04) (59,427) 0.03)

Personal 210,136 8.71 ,013,136 8.32 ,223,272 8.39

ice 

care 

(0 (0 (

11 6 1 8

and serv

Production 

(16,471) .12) (34,848) .06) (40,296) 0.05)

910,718 8.87 748,646 8.83 ,659,365 8.85

 (34,159) 

346,161 4 

(0.06) (29,999)

153,613

(0.06) (46,877) (0.04)

Protective 8.89 1 8.84 499,774 3 8.87

service 

1 1, 1 2 1

(21,125) (0.11) (13,633) (0.13) (25,808) (0.08)

Sales and 848,967 0 8.61 848,666 6 8.55 ,697,633 4 8.57

related (32,992) (0.07) (46,855) (0.04) (59,598) (0.03)

Transportation 1,280,424 16 8.68 428,623 4 8.52 1,709,047 9 8.64

and material 

moving (40,422) (0.05) (22,739) (0.09) (47,567) (0.04)

Total 8,177,158 100 $8.70 11,592,864 100 $8.62 19,770,021 100 $8.65

(98,214) (0.02) (110,776) (0.02) (153,544) (0.01)

Source: GAO analysis of data from the Current Population Survey. 

Note: Standard errors are shown in parentheses below the point estimates. This list represents about

95 percent of the total low-wage workforce; occupations with a small number of workers were 

omitted. Because of the omissions, columns will sum to less than the totals listed in the table. The 

wages are annual averages of monthly data. 

Page 44 GAO-12-10 Gender Pay Differences 
Appendix VI: Characteristics of Less-Educated 

and Low-Wage Workers, Calendar Year 2010 

Page 45 GAO-12-10 Gender Pay Differences 

Less-educated workers Low-wage workers 

Men Women Total Men Women Total

Total workers 19,382,809 15,188,084 34,570,893 8,177,158 11,592,864 19,770,021

 (140,810) (123,910) (193,659) (98,214) (110,776) (153,544)

Characteristic 

Age (in percent) 

Age 25-34 28.7 21.7 25.6 41.1 30.5 34.9

(0.4) (0.4) (0.3) (0.6) (0.5) (0.4)

Age 35-44 27.4 25.2 26.4 23.9 25.5 24.8

(0.4) (0.4) (0.3) (0.5) (0.4) (0.4)

Age 45-54 28.8 32.1 30.2 21.1 26.9 24.5

(0.4) (0.4) (0.3) (0.5) (0.5) (0.4)

Age 55-64 15.1 21.1 17.7 14.0 17.1 15.8

(0.3) (0.4) (0.2) (0.4) (0.4) (0.3)

Average age (in years) 

 42.4 44.6 43.4 40.0 42.2 41.3

 (0.076) (0.083) (0.057) (0.125) (0.099) (0.079)

Job status (in percent) 

Part-time 14.7 28.9 20.9 26.5 40.8 34.8

(0.3) (0.4) (0.3) (0.6) (0.5) (0.4)

Full-time 85.3 71.1 79.1 73.6 59.2 65.2

(0.3) (0.4) (0.3) (0.6) (0.5) (0.4)

Marital status (in percent) 

Unmarried 36.2 42.6 39.0 47.2 45.9 46.5

(0.4) (0.4) (0.3) (0.6) (0.5) (0.4)

Married 63.9 57.4 61.0 52.8 54.1 53.5

(0.4) (0.4) (0.3) (0.6) (0.5) (0.4)

Own children in household (in percent) 

No 60.0 60.4 60.1 64.5 54.8 58.8

(0.4) (0.4) (0.3) (0.6) (0.5) (0.4)

Yes 40.0 39.7 39.9 35.5 45.2 41.2

(0.4) (0.4) (0.3) (0.6) (0.5) (0.4)

Race/ethnicity (in percent) 

White 56.3 59.5 57.7 45.9 56.4 52.0

(0.4) (0.4) (0.3) (0.6) (0.5) (0.4)

Hispanic 28.3 20.5 24.9 33.2 21.2 26.2

(0.3) (0.4) (0.3) (0.5) (0.4) (0.4)

Black 10.7 14.5 12.4 14.3 16.1 15.3

(0.3) (0.3) (0.2) (0.4) (0.4) (0.3)

Asian 3.0 3.7 3.3 4.5 4.4 4.5

(0.1) (0.2) (0.1) (0.2) (0.2) (0.2)

Other 1.7 1.8 1.7 2.1 1.9 2.0

(0.1) (0.1) (0.1) (0.2) (0.1) (0.1)

 

Appendix VI: Characteristics of LessEducated and Low-Wage Workers, Calendar 

Year 2010 
Appendix VI: Characteristics of Less-Educated 

and Low-Wage Workers, Calendar Year 2010 

Page 46 GAO-12-10 Gender Pay Differences

Less-educated workers Low-wage workers 

Men Women Total Men Women Total

Education (in percent) 

Less than high school 24.7 19.1 22.3 27.3 17.0 21.2

(0.4) 

75.3

(0.4)

80.9

(0.3)

77.8

(0.6) 

38.5 38.8

(0.4) (0.3)

High school 38.7

e

(0.4) (0.4) (0.3) (0.6) (0.5) (0.4)

Some colleg a — — — 22.7 31.2 27.7

(0.5) (0.5) (0.4)

Bachelor’s degree or highera

 — — — 11.5 13.1 12.4

(0.4) (0.3) (0.3)

Marriage/children (in percent) 

Married, with children 34.9 24.7 30.4 29.6 27.6 28.4

arried, no

(0.4) (0.4) (0.3) (0.6) (0.5) (0.4)

M children 28.9 32.7 30.6 23.2 26.5 25.1

nmarried, with children 

(0.4) (0.4) (0.3) (0.5) (0.5) (0.4)

U 5.1 15.0 9.4 5.9 17.6 12.8

(0.2) 

31.0

(0.3)

27.7

(0.2)

29.6

(0.3) 

41.3

(0.4)

28.3

(0.3)

Unmarried, no children 33.7

ourly w

(0.4) (0.4) (0.3) (0.6) (0.5) (0.4)

H age—unadjusted 

$17.481 $14.062 $15.979 $8.699 $8.619 $8.652

(0.072) (0.065) (0.050) (0.022) (0.017) (0.013)

Source: GAO analysis of Current Population Survey data. 

Note: Standard erro hown in par the point estimates. F of the estima

proportions, standar s have been adjusted using ge d variance ns provided 

Bureau of Labor Statistics. All estimates except for average age, hourly wage total workers

proportions. Average age and hourly w e means, an workers is a count. 

a

As defined, the less-educated worker population does not include any individuals who have 

completed some college or obtained a bachelor’s degree o

rs are s

d error

entheses below or all 

functio

ted 

neralize by the

, and , are 

age ar d total 

r higher. 
Appendix VII: Characteristics of LessEducated Workers Employed in Retail Trade 

and Manufacturing Industries, Calendar Year 

2010 

Page 47 GAO-12-10 Gender Pay Differences 

Less-educated workers in retail trade Less-educated workers in manufacturing 

 Men Women Total Men Women Total 

Total workers 2,250,327 2,404,691 4,655,018 3,856,178 1,594,513 5,450,691

 (53,302) (53,273) (77,865) (69,151) (43,577) (84,070)

Characteristic 

Age (in percent) 

Age 25–34 32.8 24.0 28.3 23.7 16.8 21.6

 (1.1) (1.0) (0.8) (0.8) (1.0) (0.6)

Age 35–44 25.7 24.6 25.1 27.2 27.3 27.2

 (1.0) (1.0) (0.7) (0.8) (1.2) (0.7)

Age 45–54 26.1 31.1 28.7 31.5 34.5 32.4

 (1.1) (1.0) (0.8) (0.9) (1.3) (0.7)

Age 55–64 15.4 20.3 18.0 17.6 21.4 18.7

 (0.9) (0.9) (0.7) (0.7) (1.1) (0.6)

Average age (in years) 

 41.6 44.1 42.9 43.7 45.5 44.2

 (0.23) (0.21) (0.16) (0.17) (0.24) (0.14)

Job status (in percent) 

Part-time 16.7 33.8 25.5 10.1 15.8 11.8

 (0.9) (1.1) (0.7) (0.6) (1.0) (0.5)

Full-time 83.3 66.2 74.5 89.9 84.2 88.2

 (0.9) (1.1) (0.7) (0.6) (1.0) (0.5)

Marital status (in percent) 

Unmarried 41.3 43.9 42.7 32.0 41.9 34.9

 (1.2) (1.1) (0.8) (0.9) (1.4) (0.7)

Married 58.7 56.1 57.3 68.0 58.2 65.1

 (1.2) (1.1) (0.8) (0.9) (1.4) (0.7)

Own children in household (in percent) 

No 62.3 61.3 61.8 60.6 62.2 61.1

 (1.2) (1.1) (0.8) (0.9) (1.3) (0.8)

Yes 37.7 38.7 38.2 39.4 37.8 38.9

 (1.2) (1.1) (0.8) (0.9) (1.3) (0.8)

Race/ethnicity (in percent) 

White 64.2 66.8 65.6 61.7 56.9 60.3

 (1.1) (1.1) (0.8) (0.9) (1.4) (0.8)

Hispanic 21.2 16.3 18.6 24.8 25.2 24.9

 (0.9) (0.9) (0.7) (0.7) (1.3) (0.7)

Black 9.8 11.9 10.9 9.2 10.2 9.5

 (0.7) (0.8) (0.6) (0.5) (0.9) (0.5)

Asian 3.4 3.0 3.2 2.9 6.1 3.9

 (0.4) (0.4) (0.3) (0.3) (0.7) (0.3)

Other 1.3 2.0 1.7 1.4 1.5 1.4

 (0.3) (0.3) (0.2) (0.2) (0.3) (0.2)

Appendix VII: Characteristics of Less-Educated 

Workers Employed in Retail Trade and 

Manufacturing Industries, Calendar Year 2010 
Appendix VII: Characteristics of LessEducated Workers Employed in Retail Trade 

and Manufacturing Industries, Calendar Year 

2010 

Page 48 GAO-12-10 Gender Pay Differences 

Less-educated workers in retail trade Less-educated workers in manufacturing 

 Men Women Total Men Women Total 

Education (in percent) 

Less than high school 19.3 18.4 18.9 23.4 24.9 23.9

 (0.9) (0.9) (0.7) (0.8) (1.2) (0.7)

High school 80.7 81.6 81.1 76.6 75.2 76.2

 (0.9) (0.9) (0.7) (0.8) (1.2) (0.7)

Marriage/children (in percent) 

Married, with children 31.63 23.2 27.3 34.9 25.1 32.0

 (1.1) (0.9) (0.8) (0.9) (1.2) (0.7)

Married, no children 27.03 32.9 30.1 33.1 33.1 33.1

 (1.1) (1.1) (0.8) (0.9) (1.3) (0.7)

Unmarried, with children 6.03 15.5 10.9 4.4 12.8 6.9

 (0.6) (0.8) (0.5) (0.4) (0.9) (0.4)

Unmarried, no children 35.31 28.4 31.7 27.6 29.1 28.0

 (1.1) (1.0) (0.8) (0.8) (1.3) (0.7)

Hourly wage—unadjusted 

$15.71 

(0.18) 

$12.69

(0.14)

$14.15

(0.12)

$17.92 

(0.14) 

$14.35

(0.22)

$16.87

(0.12)

Source: GAO analysis of Current Population Survey data. 

Note: Standard errors are shown in parentheses below the point estimates. For all of the estimated 

proportions, standard errors have been adjusted using generalized variance functions provided by the 

Bureau of Labor Statistics. All estimates except for average age, hourly wage, and total workers are 

proportions. Average age and hourly wage are means, and total workers is a count. 
Appendix VIII: Annual Household Income for 

Less-Educated and Low-Wage Workers, 

Calendar Year 2009 

Page 49 GAO-12-10 

Appendix VIII: Annual Household Income for 

Less-Educated and Low-Wage Workers, 

Calendar Year 2009 

Worker population Gender 

Number 

workers in th

categor

at person’s 

rage wage 

and salary 

earnings

Average of 

other 

usehold 

age and 

salary 

gsa

other 

old 

omeb

Avera l 

ho d 

e 

wage and 

salary as a 

percentage of 

av 

hou 

i

Average 

wage and 

s

earning

ful

wo

of

Th

ave

is 

y 

ho

w

earnin

Average of 

househ

inc

ge tota

usehol

incom

Average

erage

sehold

ncome

alary 

s for 

l-year 

rkers

Less-educated workers 

Married with child Women 

present 

3,950,758 

(3,3

$25,814

(649) 

 $42,281

(896) 

 $7,049

(277) 

$75,145 

) 

34.3 $31,906

70) (1,298 (885)

 Men 6,303,5

(5,2

 40,937

(518) 

 22,510

(482) (148) 

4 

) 

35 4

26) 

 4,127 67,57

(841

60.6 4,603

(599)

M

c

arried with no W

hild present 

omen 4,710,

(2,80

 29,073

(621) 

 38,897

(873)

1,414

(425) 

4 

) 

708 3

9) 

 1 79,38

(1,053

36.6 3,992

(742)

 Men 4,872,48

(2,94

 43,908

(573) 

 27,538

(605) (288) ) 

6 4

6) 

 6,238 77,684 

(942

56.5 6

(617)

,893

Not married with Wom

child present 

en 1,888,

(1,47

 24,463

(841) 

 8,540

(555) (281) 

8 

) 

2

(

808 

1) 

 4,434 37,43

(1,100

65.3 8,842

1,011)

 Men 634,935 

(

 35,720

(1,04

 11,896

(920)

 3,835

(508) 

 51,452 

) 

69.4 39,073

526) 8) (1,606 (1,172)

Not married with no 

child present 

Women 2,402,152 

(1,4

 27,649

(545

 8,119

(574) (286) 

7 

86) ) ) 

 4,119 39,88

(789

69.3 31,471

(567)

 Men 3,126,061

(1,859

 3,335 47,599 75.8 40,250

)

 36,091 8,174

) (694) (512) (240) (929) (769

Low-wage workers 

Married with child 

present 

Women 3,653,662

(3,154) (158)

 $13,938

(142) 

 $43,379

(856) 

 $7,546

(384) 

 $64,862 

(958) 

21.5 $18,577

 Men 2,308,694 

(1,839) 

 18,262

(224) 

 18,727

(753) 

 3,900

(244) 

 40,889 

(822) 

44.7 20,979

(216)

Married with no 

child present 

Women 3,304,891 

(2,006) 

 15,189

(177) 

 36,748

(1,278) 

 13,016

(637) 

 64,954 

(1,340) 

23.4 19,156

(173)

 Men 1,542,520 

(972) 

 18,308

(303) 

 27,184

(1,606) 

 8,754

(631) 

 54,246 

(1,657) 

33.7 21,552

(303)

Not married with 

child present 

Women 1,772,016 

(1,406) 

 15,327

(228) 

 6,714

(483) 

 4,678

(283) 

 26,721 

(541) 

57.4 18,771

(225)

 Men 304,267 

(230) 

 17,916

(603) 

 10,899

(1,400)

 4,650

(750) 

 33,465 

(1,733) 

53.5 20,860

(608)

Not married with no 

child present 

Women 2,168,518 

(1,295) 

 16,109

(236) 

 8,440

(604) 

 5,241

(401) 

 29,790 

(772) 

54.1 19,516

(226)

 Men 1,676,396 

(1,014) 

 17,774

(330) 

 9,570

(775) 

 3,734

(371)

 31,078 

(913) 

57.2 21,112

(313)

Source: GAO analysis of Current Population Survey Annual Social and Economic data. 

Note: Parentheses are used to show standard errors below the point estimates, with the exception of 

the number of workers column for which the number of survey observations is shown. 

a

Other household wage and salary earnings can include the wages/salary of others in the household 

who may not be less-educated or low-wage workers. 

b

Other household income includes government benefits (such as Social Security, public assistance, 

veterans’ payments); retirement, investment, and rental income; and other sources of nonwage/salary income. 

Gender Pay Differences 
Appendix IX: GAO Contact and Staff Appendix IX: GAO Contact and Staff Acknowledgments 

Acknowledgments 

Gender Pay Differences

Andrew Sherrill, (202) 512-7215, or sherrilla@gao.gov

In As tor

An harge) a ort, 

en Bo ss us m Ma

ignific ntribu lso co ting to ork wer on Fec

nd Ja ebbe

GAO Contact 

 addition to the contact above, Dianne Blank (

inda Siegel (

nett, Ben 

sistant Direc

and Jam

pton, Anna

) and 

es 

ria 

L

B

alyst-in-C

litzer, Ru

 man

Burnett, S

ged this rep

annah Co

Ortiz, Rhiannon Patterson, David Perkins, and Shana Wallace made 

s ant c

m

o tions

. 

. A ntribu this w e R so 

a es R

Staff 

A d n cknowle gme ts 

Page 50 GAO-12-10 
Related GAO Products Related GAO Products 

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