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111TH Congress
2d Session
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COMMITTEE PRINT
S. PRT.
111–62
INVEST IN WOMEN, INVEST IN AMERICA:
A COMPREHENSIVE REVIEW OF WOMEN
IN THE U.S. ECONOMY
Prepared by the Majority Staff of the
JOINT ECONOMIC COMMITTEE
CONGRESS OF THE UNITED STATES
DECEMBER 2010
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congress.#13
Printed for the use of the Joint Economic Committee
INVEST IN WOMEN, INVEST IN AMERICA:
A COMPREHENSIVE REVIEW OF WOMEN
IN THE U.S. ECONOMY
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111th Congress
2d Session
"
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COMMITTEE PRINT
S. PRT.
111–62
INVEST IN WOMEN, INVEST IN AMERICA:
A COMPREHENSIVE REVIEW OF WOMEN
IN THE U.S. ECONOMY
Prepared by the Majority Staff of the
JOINT ECONOMIC COMMITTEE
CONGRESS OF THE UNITED STATES
DECEMBER 2010
Printed for the use of the Joint Economic Committee
U.S. GOVERNMENT PRINTING OFFICE
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congress.#13
WASHINGTON
63–036
JOINT ECONOMIC COMMITTEE
[Created pursuant to Sec. 5(a) of Public Law 304, 79th Congress]
HOUSE OF REPRESENTATIVES
CAROLYN B. MALONEY, New York, Chair
MAURICE D. HINCHEY, New York
BARON P. HILL, Indiana
LORETTA SANCHEZ, California
ELIJAH E. CUMMINGS, Maryland
VIC SNYDER, Arkansas
KEVIN BRADY, Texas
RON PAUL, Texas
MICHAEL C. BURGESS, M.D., Texas
JOHN CAMPBELL, California
SENATE
CHARLES E. SCHUMER, New York, Vice
Chairman
JEFF BINGAMAN, New Mexico
AMY KLOBUCHAR, Minnesota
ROBERT P. CASEY, JR., Pennsylvania
JIM WEBB, Virginia
MARK R. WARNER, Virginia
SAM BROWNBACK, Kansas, Ranking Minority
JIM DEMINT, South Carolina
JAMES E. RISCH, Idaho
ROBERT F. BENNETT, Utah
ANDREA CAMP, Executive Director
JEFF SCHLAGENHAUF, Minority Staff Director
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Letter of Transmittal
December 2010
To the Members of the Joint Economic Committee:
I asked the Majority Staff of the Joint Economic Committee to
prepare a comprehensive review of women in the U.S. economy so
that policymakers could have a better understanding of women’s
essential contributions to our economy and of their potential to
play a stronger role in our economic recovery. Transmitted hereby
is that review, Invest in Women, Invest in America, which also
serves as the final majority report to be issued under my leadership as Chair of the Joint Economic Committee.
Sincerely,
Carolyn B. Maloney
Chair
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
Part I: Invest in Women, Invest in America
A. Decades of Progress for Women in the Workforce............................................................... 5
B. Women’s Potential Power...................................................................................................... 7
C. What’s Holding Women Back?............................................................................................. 8
D. Potential Solutions................................................................................................................15
aL
Part II: Compendium of JEC Reports and Hearings from the 111 Congress
A. Women in the Economy Today......................................................................................... 31
1. Report: “Women in the Economy 2010: 25 Years of Progress but Challenges
Remain” (August 2010).............................................................................................. 33
2. Report: “Easing the Squeeze on Women and Their Families”
(May 2009)....................................................................................................................43
3. Report: “Women in the Recession: Mothers and Families Hit Hard” (May
2009)..............................................................................................................................47
4. Report: “Working Mothers in the Great Recession” (May 2010).............................56
B. Equal Pay............................................................................................................................. 61
1. Hearing: “Equal Pay for Equal Work? New Evidence on the Persistence of
the Gender Pay Gap” (April 2009)
a. Testimony: Lisa M. Maatz, Director of Public Policy and Government Relations,
American Association of University Women.........................................................63
b. Testimony: Randy Albelda, Professor of Economics, University of
Massachusetts-Boston.............................................................................................. 73
c. Testimony: Andrew Sherrill, Director, Education, Workforce, and Income
Security Issues, Government Accountability Office............................................. 82
2. Hearing: “New Evidence on the Gender Pay Gap for Women and
Mothers in Management” (September 2010)
a. Testimony: Andrew Sherrill, Director, Education, Workforce, and Income
Security Issues, Government Accountability Office............................................. 92
b. Testimony: Ilene H. Lang, President and Chief Executive Officer,
Catalyst, Inc............................................................................................................101
c. Testimony: Michelle J. Budig, Associate Professor of Sociology,
University of Massachusetts-Amherst.................................................................. 125
3. Report: “Earnings Penalty for Part-Time Work: An Obstacle to Equal Pay”
(April 2010).................................................................................................................139
4. Report: “Large Gender Pay Gap for Older Workers Threatens Economic
Security of Older Women” (December 2010)..........................................................143
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Prepared by the Majority Staff of the Joint Economic Committee
Invest in Women, Invest in America:
I December 2010
A Comprehensive Review of Women in the U.S. Economy
I Joint Economic Committee
C. Access to Benefits..............................................................................................................147
1. Report: “Comprehensive Health Care Reform:
An Essential Prescription for Women” (October 2009)........................................... 149
2. Report: “Expanding Access to Paid Sick Leave: The Impact of the
Healthy Families Act on America’s Workers” (March 2010).................................. 172
3. Hearing: “Balancing Work and Family in the Recession: How
Employees and Employers Are Coping” (July 2009)
a. Testimony: Ellen Galinksy, President,
Families and Work Institute...................................................................................184
b. Testimony: Karen Nussbaum, Executive Director,
Working America................................................................................................... 217
c. Testimony: Cynthia Thomas Calvert, Deputy Director,
The Center for WorkLife Law.............................................................................. 224
D. Retirement Security..........................................................................................................231
1. Report: “Social Security Provides Economic Security to Women”
(October 2010)........................................................................................................... 233
E. Appendix............................................................................................................................ 237
1. Report: Government Accountability Office. 2009. Gender Pay Gap in
the Federal Workforce Narrows as Differences in Occupation,
Education, and Experience Diminish.
2. Report: Government Accountability Office. 2010. Women in
Management: Female Managers’ Representation, Characteristics, and
Pay.
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Introduction
As the nation charts a course out of the Great Recession and towards a brighter tomorrow,
women’s participation in the labor market and power over household purchases will be critical
for economic growth. Women comprise half the workforce, and receive the majority of
bachelor’s degrees granted today. Women’s earnings are crucial for family well-being, women’s
purchasing power drives the economy, and women’s leadership in the boardroom is a proven
boon for businesses’ bottom line. Because of all this and more, investing in women means
investing in the nation as a whole.
This report provides a comprehensive overview on women’s position in the economy today.
Decades of progress mean women are poised to lead the nation’s next chapter of economic
growth. Yet roadblocks remain, and these blockades are hampering women’s ability to reach
their full economic potential. The cost of this log-jam is paid not only by women and their
families, but by the economy as a whole. Jump-starting economic growth and putting the nation
on a path to prosperity requires investing in women in order to allow them to meet their full
economic potential. The result will be greater prosperity and progress for all.
Decades of Progress for Women in the Workforce
For the first time in our nation’s history, women comprise half of the U.S. workforce (49.8
percent). In 1970, women accounted for just over one-third (35.6 percent).1 These figures alone
highlight the stunning transformation of the U.S. economy over the last several decades, and
women’s profound role in that transformation.
Women today work in key industries throughout the economy. Women comprise 77.4 percent of
workers in education and health services, the fastest growing sector of the U.S. economy. 59.3
percent of employees in the financial activities industry are women.2 And at least half of the jobs
in government, leisure and hospitality services, and other services are held by women. Female
workers currently comprise the majority share of all but three of the fifteen occupations with the
largest projected employment growth between 2006 and 2016.3 In short, women play a critical
role in many of the economy’s key growth sectors.
Women have pulled ahead of men in educational attainment. While the fraction of men with
four-year college degrees has stagnated, the share of women with four-year college degrees has
grown exponentially. Today, women receive almost 60 percent of the bachelor’s degrees granted
in the United States, compared to just 40 percent in 1970.4 Women’s rise in educational
attainment has accompanied a shift in the American economy, from an industrial economy
dominated by manufacturing and construction to a post-industrial, “knowledge economy”
dominated by service jobs. That same shift has meant a transition away from lower-skilled,
manual work to more sophisticated work requiring a deeper skill set. Jobs requiring some form
of post-secondary award or degree account for nearly half of all the new jobs projected to be
created between 2008 and 2018.5 In short, women are well-positioned to meet the demands of an
increasingly sophisticated economy set to compete in the global marketplace.
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Once upon a time, a working mother was an anomaly in most American communities. Today,
only one in five married couples with children fit the “traditional” model of a breadwinner father
and a stay-at-home mother.6 In 1975, 44.7 percent of families with children fit that model.
Likewise, in 1975, only 4 in 10 mothers (39.6 percent) with a child under age 6 worked outside
the home. By 2008, that figure had risen to over 6 in 10 (64.3 percent). America’s economy
depends on women’s work, as do America’s families.
Women are co-breadwinners in many American families today. In the typical married household,
the wife’s paycheck accounts for over a third (36.0 percent) of the family’s income.7 In contrast,
in 1970, wives’ earnings comprised just over a quarter (26.6 percent) of family income.8
Amongst all working wives in 2008, 38.1 percent earned as much or more than their husbands,
compared to just 18.7 percent in 1967.9 Amongst working wives ages 30 to 44, the share of
wives earning as much or more than their husbands nearly tripled, from 11.9 percent in 1967 to
32.7 percent in 2008.
Women’s earnings are critical for families’ economic well-being. Between 1983 and 2008,
families with wives in the paid labor force saw their income grow by 1.1 percent annually, on
average, compared to a 0.2 percent annual decline in income for families where the wife did not
work.10 Families in which wives work are more likely to move up the income ladder or maintain
their position over time when compared to those without working wives.11 In 2009, women were
the sole job-holders in one in three families with children (34.2 percent). In other words, 7.4
million mothers were their families’ sole source of earnings.12
Many women with children who are their family’s sole earner are single mothers. Over a quarter
(26.0 percent) of working mothers are single moms, a group of women who have long been
active labor market participants.13 Over three-quarters (75.8 percent) of single mothers either
worked or were actively seeking employment in 2009.
However, single mothers are not the only women whose earnings are a critical lifeline for their
families. Married women’s earnings play a particularly crucial role in light of the nature of the
job losses that have characterized the Great Recession. Men experienced greater job losses than
women over the course of the recession, because the hardest-hit industries were more likely to
employ men. The share of married families where the husband was unemployed but the wife
remains employed jumped sharply over the course of the recession.14 Over the first five months
of 2009, when job losses were heaviest, an average of 5.4 percent of working wives had an
unemployed husband at home, compared to an average o f 2.4 percent over the first five months
of 2007. In other words, the share of married couples with an unemployed husband more than
doubled over the course of the recession. In contrast, the share of working husbands with an
unemployed wife remained much lower - just 3.3 percent in the first five months of 2009
compared to 1.6 percent in the first five months of 2007. Families with children were no
exception: 5.7 percent of families with children under the age of 18 had an unemployed husband
and an employed wife. This means that, in 2009, there were 1 million working wives with
children at home, but an unemployed husband. For these families, women’s earnings are a
critical lifeline.
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Invest in Women, Invest in America:
I December 2010
A Comprehensive Review of Women in the U.S. Economy_____________ | Joint Economic Committee______
In no uncertain terms, women have made phenomenal progress over the course of the last several
decades. Women are a vital force in the United States’ economy, providing skills and labor in a
diverse array of sectors. Women’s paychecks have driven their families’ standards of living
upwards, and provide a key safety net during tough economic times.
Women’s Potential Power
Women hold phenomenal potential to drive economic growth. Advertisers realized this basic fact
ages ago, and products marketed specifically to women are recognizable to anyone with a
passing familiarity with popular culture. Indeed, women control 73 percent of household
spending.15 This translates into over $4 trillion in annual discretionary spending. In an economy
driven by consumption, this is a powerful role. In over half of middle- and upper-income
families, women are more likely than men to handle daily money management tasks.16 Yet
women’s power as an engine of economic growth extends beyond their role as consumers.
Women have proven their potential as economic producers as well.
Take, for instance, women’s role in business. Firm performance correlates directly with women’s
representation in corporate leadership. Companies with the most women on their boards of
directors outperform those with the fewest women on their boards on myriad key performance
measures - return on invested capital is 66 percent higher in firms with strong female
representation, return on equity is 53 percent higher, and return on sales is 42 percent higher.17
The link between women’s representation on corporate boards and firm performance holds
across industries. Fortune 500 firms with the best record of promoting women to senior
positions, including their boards of directors, are more profitable than their peers.18 The 25 firms
with the best promotion records post returns on assets 18 percent higher, and returns on
investments 69 percent higher, than the Fortune 500 median for their industry.
The link between gender diversity in corporate leadership and firm performance may stem from
the talents that women are more likely than men to bring to the boardroom. Firms with female
representation on their boards of directors are more likely to be highly attentive to corporate
governance issues, which correlate with improved firm performance.19 Women leaders are more
likely than their male peers to demonstrate types of leadership behavior that positively affect
corporate organizational performance, including participative decision-making, role modeling,
inspiration, expectations and rewards, and mentoring.20
Female business owners are also a major driving force in the United States’ economy. Womenowned businesses account for almost 30 percent of all non-farm, privately-held U.S. firms.21
Growth in women-owned businesses outpaces that of male-owned business. Between 1997 and
2007, the number of women-owned businesses grew by 44 percent, twice the pace of maleowned businesses. These women-owned businesses added roughly 500,000 jobs between 1997
and 2007, when the rest of privately-held firms lost jobs.
Traditionally “female” occupations have expanded in economic importance over the last several
decades, and are poised to grow exponentially in coming years. For instance, as of 2008, health
care sector employment had grown by 25 percent over the last 9 years, compared to just 5
percent in all non-health care sectors combined.22 Women comprise three-quarters (74.5 percent)
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Prepared by the Majority Staff of the Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
of all health care practitioners, and 88.8 percent of all health care support occupations.23 Within
the health care sector, employment growth has been more rapid in the home health and hospice
care sub-sectors than in the health care sector more generally. These are areas that are
particularly saturated with female workers, who comprise the vast majority (88.7 percent) of
home health aides. Projections into the future predict continued strong growth in the health care
sector, particularly because of the aging baby boom population and the continued need for the
“caring” professions that women predominate. For instance, forecasters predict that the economy
will add 581,500 jobs for registered nurses between 2008 and 2018 - over one-third of the total
growth in healthcare practitioner jobs.24 As of 2008, 91.7 percent of registered nurses were
female.
In addition to demographic changes favoring traditionally-female occupations, women’s
educational attainment means that millions of women are in a position to contribute
meaningfully to the economy of the future. Women’s impressive college graduation rate means
that the up-and-coming cohort of young women are poised and ready with the skills and
education necessary for creating economic value in the labor force of tomorrow.
Women are also in a position to influence the shape of the future labor movement in the United
States. While total union membership has declined over the last quarter century, women’s union
membership has been on the rise.25 In 1984, women made up just over one-third (34.0 percent)
of all union members. In 2008, women comprised 45.0 percent of all union members. The
growing importance of women in the labor movement is likely due to the expansion of female
concentrated sectors such as health care, education, and the service sector, combined with the
contraction of male-concentrated sectors such as manufacturing.
What’s Holding Women Back?
Women’s prospective economic power is substantial - as both consumers and producers, women
hold the keys to revving up the economy’s engine and driving the nation towards a future of
prosperity. Yet women face serious constraints to achieving their full potential. A persistent
wage gap not only cheats women and their families out of the earnings they deserve, but
artificially constrains the purchasing power of women, and therefore hampers the American
economy as a whole. Women’s continued underrepresentation in corporate leadership means that
America’s companies are missing out on the proven economic value to having women in the
boardroom and the C-suite. A patchwork social support system - particularly in the work-family
arena, where the United States offers virtually no institutionalized support for working families means that America’s economy suffers as women struggle to balance demands from work and
demands from home. And a retirement system that disadvantages women means that too many
hard-working women spend their elder years on the precipice of economic disaster.
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
A Persistent Gender Wage Gap
The gender wage gap remains substantial today. Women working full-time, year-round earn only
77 cents for every dollar earned by men, and virtually no progress has been made in closing the
gap since 2001.26 In 2009, the most recent year for which data is available, median annual
earnings of women ages 15 and older working full-time, year-round were just $36,278 compared
to $47,127 for their male counterparts. New calculations from the JEC show that the gender
wage gap is even greater for older women. In 2009, median weekly wages for women over 50
were just 75 percent of their male colleagues’ earnings.27
The gender wage gap persists across a wide spectrum of occupations.28 Female attorneys earn
just 80.5 cents for every dollar earned by their male counterparts, and female physicians and
surgeons earn 64.4 cents on the dollar. Women in retail sales earn 70.6 cents for every dollar
earned by men in retail sales, and female truck drivers earn just 76.4 cents on the dollar. A recent
Government Accountability Office (GAO) study requested by Chair Maloney and Representative
John Dingell examined the pay gap amongst women and men employed in management
occupations, and found that full-time female managers earn 81 cents for every dollar earned by
their male manager peers.29 This figure accounts for many observable differences between male
and female managers, so the remaining 19 cent gap between men and women may be attributable
to discriminatory practices. The gender pay gap amongst managers remained persistent between
2000 and 2007, the most recent year of available data.
The pay gap is not limited to the private sector. Even within the federal government, which ought
to be a model employer, a substantial unexplained pay gap persists. In response to a request by
Chair Maloney and Representative Dingell, the GAO examined the gender pay gap in the federal
government and found that women federal employees earn 89 cents for every dollar earned by
their male peers.30 After accounting for observable differences between men and women
(including education, experience, and occupation), that gap narrows to 93 cents on the dollar.
The remaining 7 cent pay gap may be attributable to discriminatory practices.
Women earn less than men across all educational levels.31 In 2009, female high school graduates
earned 69.6 cents for every dollar earned by their male counterparts; median earnings amongst
female high school graduates is $22,468 compared to $32,272 for male high school graduates.
Amongst college graduates, the gender wage gap is similarly substantial, with female college
graduates earnings 70.9 cents for every dollar earned by their male counterparts; median earnings
for female college graduates is $40,098 compared to $56,566 for men. The gender pay gap for
workers with a professional degree is the largest across the education spectrum: professional
women earn 57.9 cents for every dollar earned by professional men, or $67,245 as compared to
men’s $116,136.
The pay gap amongst college graduates grows substantially over the course o f a woman’s
career.3 Just one year out of college, women earn about 80 percent of what their male classmates
earn. Ten years after graduation, women have fallen further behind, earning just 69 cents for
every dollar earned by their male classmates. Similarly, recent research suggests that the pay gap
between male and female professional degree-holders grows steeper over time. For instance, a
study tracking the earnings of graduates of the University of Chicago’s MBA program finds that
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
| Joint Economic Committee______
the gap between male and female MBA’s earnings grows from 11 percent at graduation (i.e. 89
cents on the dollar) to 31 percent at five years out (i.e. 69 cents on the dollar) to a whopping 60
percent at ten years or more (i.e. 40 cents on the dollar).33 A second study tracking male and
female MBA recipients found that women averaged $4,600 less in their first job, even after
controlling for job level.34 Women started at lower levels than men and were outpaced in salary
growth, even after controlling for career aspirations and parenthood status. The salary growth
gap intensified over time. While women and men step off the corporate track at equal rates,
women pay a greater penalty in terms of compensation and position than do men when they
return to corporate life.
Mothers face an additional wage penalty, on top of the basic penalty paid simply by virtue of
being a woman in the labor force. Much research has shown that working mothers earn less than
non-mothers.35 Even after accounting for differences in work experience, job characteristics,
human capital such as education, and other individual attributes, mothers pay a 7 percent wage
penalty per child, relative to non-mothers.36 A GAO report requested by Chair Maloney and
Representative Dingell found that while mothers incurred at 2.5 percent earnings penalty for
each child, fathers enjoyed a 2.1 percent earnings boost for each child.37
Other studies provide detail on the depth of the motherhood wage penalty. A GAO report
requested by Chair Maloney and Representative Dingell found that mothers who are managers
earn 79 cents for every dollar earned by fathers who are managers, and that pay gap has not
budged since 2000.38 The pay gap for mothers is larger than the pay gap for childless female
managers, who earn 83 cents for every dollar earned by childless male managers. While the pay
gap for childless women narrowed slightly between 2000 and 2007, the pay gap for “manager
moms” remains stuck at 79 cents on the dollar. These figures compare full-time workers, and
account for many factors that might explain the discrepancy between men and women, including
age, education and other variables. Another study sent out over 1,200 fictitious resumes to
employers in a large Northeastern city, and found that female applicants with children were
significantly less likely to be hired (and, if hired, were offered a lower salary) than identical male
applicants with children.39 In no uncertain terms, a preponderance of evidence suggests that
women are penalized in the workforce when they have children, despite no evidence that their
productivity suffers.
As detailed above, full-time, full-year female workers earn less, on average, than full-time, fiillyear male workers. This problem persists across occupations and industries, and is particularly
pernicious for mothers. Yet the problem does not stop there. The wage gap for part-time workers
exacerbates the existing problem.40 The “part-time penalty” means that part-time workers are
paid an average of 58 cents on the dollar compared to the hourly wages of their full-time peers.
In other words, while the part-time employee and the full-time employee are likely doing the
same work, the part-time worker faces a wage penalty simply for being a part-timer. Women are
far more likely than men to be employed part-time - nearly two-thirds (64 percent) of part-time
workers are women, and one in four (26 percent) of all employed women work part-time.
Therefore, the part-time wage penalty is an additional factor exacerbating the gender pay gap.
The cost of the pay gap to women and their families is enormous, particularly when measured
over the course of a career.41 In the first five years of her career, between ages 25-29, the average
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I December 2010
I Joint Economic Committee
woman loses $8,510 to the pay gap. Because the pay gap widens as women progress through
their careers, her losses grow progressively larger. By the time she retires at 64, she’s lost over
$430,000 to the pay gap.42 When individual women’s losses due to the pay gap are aggregated
across all working women for a generation, the results are staggering - for instance, as a group,
young college-educated women who entered the workforce between 1984 and 2004 have lost
$1.7 trillion.
The gender wage gap comes at a cost to the economy as a whole. Women’s phenomenal
purchasing power and critical role as financial decision-makers for their households means that
when a woman is cheated out of a portion of her paycheck, the whole economy suffers. Fewer
take-home dollars means fewer purchases, which in turn means a more sluggish economy and
slower economic growth. Closing the gender pay gap therefore has the potential to have salutary
effects not only for women and their families, but for the nation’s future economic health as well.
Underrepresentation in Corporate Leadership
Despite the clearly demonstrated economic rewards that accrue to companies with women in
corporate leadership, women remain dramatically underrepresented in corporate boardrooms and
executive suites43 While women comprise 46.4 percent of all employees in Fortune 500
companies, they make up just 15.7 percent of board seats, 14.4 percent of executive officers, 7.6
percent of top earning executive officers, and 2.4 percent of chief executive officers (CEOs).
Women lag men in Fortune 500 leadership across all industries, including female-prevalent
industries. The percentage of women-held board seats and corporate officer positions are quite
similar across industries, even in fields such as retail and finance, where women represent a
greater share of total employees. The only fields where women’s leadership is markedly lower
than average are utilities, mining, and quarry extraction and oil and gas extraction, where
women’s overall representation is much lower.
Women’s representation in Fortune 500 leadership has remained stagnant over time. Women
have made little progress in representation as CEOs, corporate officers, or board members over
the last several decades 44 The last five years have been particularly flat periods for progress. For
instance, between 1996 and 2003, women’s representation on corporate boards increased from
10.2 percent to 15.2 percent, but it has remained stalled at 15.2 percent for the last six years.
The underrepresentation of women in corporate leadership - in the boardroom and the executive
suite - may mean that U.S. companies are not reaching their full potential. Corporate
performance correlates directly with women’s representation in corporate leadership. Companies
with the most women on their boards of directors outperform those with the least women on their
boards on myriad key economic performance measures, and the link between women’s
representation on corporate boards and firm performance holds across industries 45 Fortune 500
firms with the best record of promoting women to senior positions, including their boards of
directors, are more profitable than their peers.46 A lack of gender diversity in corporate
leadership may be hindering corporate profits, and holding back future economic growth.
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An Out-of-Date Frameworkfo r Social Support
Our nation’s public policies are still rooted in the antiquated assumption that families rely on a
single male breadwinner, and therefore have a wife at home to care for the young, the sick, and
the elderly. The reality is that most families depend on two breadwinners, and many struggle to
patch together care for their loved ones in order to continue to make ends meet. The absence of
social supports for working families spans a wide range of policy areas impacting families from
birth until death.
No Paid Leave
Perhaps the most important advance in social support for working families was the Family and
Medical Leave Act of 1993, but even this major legislative accomplishment only allows 12
weeks of unpaid job-protected family or medical leave to about half of all workers in the United
States. The United States’ approach stands in stark contrast to our peers. The OECD average
length of job-projected leave for new parents is 18 weeks, compared to the U.S.’s 12 weeks.
Beginning in January 2011, the United States will be the only OECD nation with no paid
parental leave.47 As a result of the lack of paid parental leave, many families incur serious
financial hardship upon the birth of a child.
The lack of paid parental leave means the economy pays, too. Paid parental leave can serve as a
powerful retention tool: new mothers who are able to take a paid leave are more likely to return
to the same employer than are those without paid leave. The cost of turnover is substantial, with
turnover costs estimated at between 25 and 200 percent of employee compensation 48 Those
costs stem from direct expenses such as recruiting, interviewing, hiring, training, and supervising
new employees, but also from indirect costs such as lost sales due to consumer dissatisfaction,
new employee errors, and reduced morale of employees charged with training new hires.
The absence of a federal paid sick leave policy also places a special burden on women.
Currently, more than one-third (37 percent) of working women in establishments with 15 or
more workers lack access to paid sick leave.49 The actual share of working women with no
access to paid sick leave may be substantially larger, since smaller establishments are less likely
to provide workplace benefits and women may be more likely to be work in smaller
establishments as compared to men. The absence of paid sick leave means that millions of
women are vulnerable to income and job loss when an illness requires that they stay home from
work. Despite women’s mass movement into the labor force, mothers still bear the primary
responsibility for their children’s health, regardless of whether or not that mother works. Half of
all working mothers must miss work if their child is sick, compared to 30 percent of working
fathers, and half of these mothers who stay home with their sick child report that they do not get
paid when they stay home to provide care. The lack of access to paid sick leave is of particular
harm to working women because of the double burden they face - both self-care and care for an
ailing child.
The absence of a federal paid leave policy takes a toll on the economy, too. Employers pay
substantial wages to workers who go to work ill, known as “presenteeism.” Workers who report
to work sick are typically about half as productive as usual, and that productivity slowdown
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comes at a substantial cost.50 In addition, sick workers may spread their illness to co-workers,
exacerbating productivity problems. The cost of presenteeism averages between $217 and $1,567
per employee per year.51
Inflexible Work Arrangements
The absence of access to flexible work arrangements is another factor holding women back from
achieving their full economic potential. Busy working women face responsibilities at home and
at work, and flexible work arrangements can offer a win-win solution that allows for an easier
balancing act. For the millions of women who are working longer hours in the aftermath of the
Great Recession in order to help their families make ends meet, added flexibility would be of
particular use.
Only 50 percent of American workers agree they have the flexibility they need in order to
successfully manage their work and family life, despite the fact that the vast majority of
Americans rate flexibility as a very important job quality.52 Research shows that workers with a
high-quality work-life “fit,” a summary metric of job quality that includes several important
measures of flexibility, are better employees - they are more likely to remain in their current job,
more highly engaged, in better health, and less stressed than workers with a poor work-life fit.
Flexible work arrangements promoting better work-life fit could boost economic performance by
promoting lower levels of job turnover, higher employee satisfaction, and lower levels of
absenteeism.
Studies provide evidence of precisely this effect. Employees respond to flexibility with enhanced
loyalty and commitment, which increases productivity and makes businesses more competitive.
In the tight labor markets of the 1990s and early 2000s, a major advantage of flexibility was
reduced turnover. Access to flexible work arrangements motivated productive performers to stick
with the current employer, which meant that the employer saved money searching for and
training new employees.53 For example, 96 percent of AstraZeneca employees claimed that
flexibility influenced their decision to remain with the company. Deloitte estimated that the firm
saved $41.5 million in 2003 due to reduced turnover attributable to their flexibility policies.
Moreover, in the absence of broadly available flexible work arrangements, women may work in
positions that are more flexible but less well-suited for their skills and talents. This skills
mismatch may drag down productivity and waste valuable human capital, thereby slowing
economic growth.
Undervalued Early Care and Education Sector
The workplace is not the only arena where federal policies have failed to keep up with the
changing reality of American family life. Prior to the mass movement of women into the labor
force, mothers were more likely to provide early care and education for their own children. The
movement of women into the labor force means that child care arrangements are a necessity for
most American families. Yet the early care and education system in the United States remains
under-developed and underfunded.
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A Comprehensive Review of Women In the U.S. Economy
I December 2010
I Joint Economic Committee
This failure not only hurts working women, who bear the primary responsibility for caring for
children. It also hurts the workers employed in the care sector - child care workers and early
educators, who are primarily women and remain under-valued and under-paid. Moreover, it hurts
the economy as a whole, because under-funded early care and education has meaningful
consequences for children’s health, well-being, and human capital. The failure to invest in early
care and education is a strategic error that is holding back the American economy from achieving
its full potential not only today, but in the future as well.
Quality, affordable early care and education - child care centers and pre-kindergarten programs remain in short supply across the United States. As a result, access to quality, affordable care for
young children presents a major source of financial and emotional stress for working parents.
The cost of full-time, center-based child care for an infant is nearly half (49 percent) of the
annual income for two-parent family living at the federal poverty threshold ($18,310/year in
2009), and nearly one quarter (24 percent) of the annual income for a two-parent family living at
200 percent of the federal poverty threshold ($36,620/year in 2009).54 In all but one state, the
average cost of pre-school is more than the average annual cost of public college tuition. In many
cities, preschool costs twice as much as college tuition.55
This burden is particularly high for low-income families, especially single mothers who simply
do not have the option of staying home to provide care for their own children. While the Head
Start and Early Head Start programs are meant to provide subsidized child care for low-income
families, demand far outstrips the supply of slots in these programs, and many families are
simply not able to access these resources. Moreover, many working families’ incomes are too
high to allow them to qualify for federal programs but too low to comfortably afford safe, secure,
and high-quality child care arrangements.
The lack of access to quality early care and education for children comes at substantial cost.
Working families - particularly the women who bear the primary responsibility for child care
and well-being - are under extraordinary financial and emotional pressure as they struggle to
make sure that their children are safe and nurtured. Yet the problem extends beyond the private
stresses of families scrambling to provide for their children. Government investments in early
childhood education provide a proven bang-for-the-buck. On the flip side, therefore, a failure to
invest in children yields an economy that is failing to reach its full potential. Early interventions
- early child care, pre-kindergarten, and other similar programs - can promote educational
attainment, raise the quality of the workforce, and enhance the productivity of schools, in
addition to reducing crime, teenage pregnancy, and welfare receipt. In terms of earnings alone,
investing in early care and education provides a return on dollars invested as high as 17
percent.56
Despite a large body of research suggesting strong returns on the investment in children, federal
policy has consistently under-funded children’s programs in comparison to other spending
priorities. Spending on children as a share of domestic federal spending has been decreasing for
nearly 50 years.57 In 1960, spending on children comprised 20.2 percent of all domestic
spending. By 2000, that figure was just 16.2 percent, and spending on children as a share of all
domestic spending is projected to dip to just 13.8 percent by 2018.58 This continued under
investment in early care and education is a drag on our nation’s future economic well-being.
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Tenuous Retirement Support
Elderly women are far more likely than elderly men to struggle financially. 11.7 percent of
women over the age of 75 are poor, compared to just 7.4 percent of men.59 Older women are
struggling to get by with today’s retirement system.
Despite the substantial increase in women’s education, employment, and earnings over time,
women still tend to experience shorter and more interrupted career trajectories than do men. The
demands of child birth, child rearing, elder care, and other factors mean that women’s
employment patterns are not as even as men’s. Because our nation’s retirement system is built on
the assumption of consistent, stable work, women’s retirement security remains precarious.
Women’s role as the main caregivers in American society extends across their lifespans. Even
childless women are likely to take some time out of the labor force to care for aging parents or
other infirm relatives. Over 82 percent of all care for the frail elderly is unpaid, and women
account for two-thirds of these unpaid caregivers.60 Daughters account for about seven in ten of
adult children who help their frail parents, and five of every six who assume primary
responsibility for their personal care. The aging of the Baby Boom cohort translates into a
growing elderly population that will require care in the coming years, and much of that care will
be provided by women. As a result, more women are likely to curtail work to provide care.61
Moreover, while women spend more time out of the labor force than men, they also have more
substantial retirement income needs, because women live longer than men.
This time spent out of the labor force combines with the gender pay gap to make saving for
retirement and accruing Social Security benefits a challenge for many women. Women reach
retirement with smaller balances in their individual retirement accounts than their male
colleagues, in part because of the gender pay gap and in part because of career interruptions. The
median female worker neared retirement with a 401k or IRA plan valued at $34,000, compared
to her male counterpart’s $70,000 in 2004.62
Social Security plays a uniquely important role for women because it provides a guaranteed
source of retirement income. Without it, over half of all women over the age of 65 would be
poor.63 Yet lower earnings and time out of the labor force mean that women’s Social Security
contributions are consistently lower than those of men. Because the Social Security system does
not recognize unpaid care as “work,” women’s contributions to the well-being of their children
and parents remains unremunerated. When workers reduce their employment due to transitions
from full- to part-time employment, or from withdrawal from the labor force, their future
retirement streams suffer. Yet women’s care contributions have sizeable economic value. For
instance, family unpaid elder care constitutes an economic value of between $45 billion to $200
billion annually.64 The failure of the current system to recognize this fact means that older
women face a constant challenge to their economic security.
Potential Solutions - 21st Century Economic Equity
The economic status of women has progressed tremendously over the last half-century. Yet, as
the above section explains, women’s full economic potential has yet to be realized. Investments
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
in women, and in policies that advance women’s economic status, are more than investments in
individual and family well-being. They are also investments in the economy as a whole, because
women’s potential for contributing to economic growth and prosperity is enormous. A wide
variety of policy solutions aimed at fostering economic equity in the 21st century could harness
that potential and push America forward into a new era o f economic prosperity.
Stronger Protections Against Wage Discrimination
The Lilly Ledbetter Fair Pay Act reversed the recent Supreme Court decision in Ledbetter v.
Goodyear Tire & Rubber Co., ensuring that workers - all workers who are discriminated against,
not just women - have 180 days from the most recent instance of discrimination to file a
complaint. The Ledbetter Act was an important victory for workers’ rights, but it simply restores
anti-discrimination legislation to where it stood prior to the Supreme Court’s creation of the
Ledbetter standard. Additional protections against discrimination are necessary for closing the
gender pay gap, and the Paycheck Fairness Act would do just that.
The Paycheck Fairness Act would update and strengthen the original Equal Pay Act. The
Paycheck Fairness Act (PFA) prohibits employers from punishing employees for sharing salary
information with their co-workers. It toughens the remedies provisions of the Equal Pay Act by
allowing prevailing plaintiffs in gender discrimination cases to receive compensatory and
punitive damages, just as prevailing plaintiffs in race and ethnicity discrimination cases currently
do. By making discrimination costly, the Paycheck Fairness Act would add teeth to the Equal
Pay Act and dissuade employers from discriminatory behavior. The Paycheck Fairness Act
closes a number of additional loopholes in the Equal Pay Act, includes a number of new datagathering requirements for the federal government, aimed at assisting the Equal Employment
Opportunity Commission (EEOC) to identify and respond to wage discrimination claims and
assisting the Department of Labor in detecting wage discrimination, and creates a competitive
grant program to develop training programs for women and girls on how to negotiate
compensation packages, as well as an award to recognize and promote the achievements of
employers who have made strides in eliminating pay disparities.
Repeated studies have shown persistent unexplained gender pay gaps, suggesting that
discriminatory practices remain a problem in today’s workforce. Robbing women of the wages
they are owed not only cheats those women and their families, but also cheats the economy as a
whole, because those stolen dollars might otherwise have gone back into the economy in the
form of women’s consumer spending. Updating and strengthening legislation aimed at protecting
against gender wage discrimination is a key policy for advancing economic equity and prosperity
in the future.
Health Reform
The Affordable Care Act of 2010, the health care reform legislation passed by Congress and
signed into law by President Obama in March 2010, has the potential to pave the way toward a
more equitable, prosperous future for both women and families and for the economy as a whole.
Under the status-quo health insurance system, women are particularly vulnerable to being un- or
under-insured.65 Women are more vulnerable to high health care costs than men, both because
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women’s health care needs differ from men’s and because women are more economically
vulnerable than men. The inability o f the status-quo system to serve women’s health care needs
has come at great expense. Over half of all medical bankruptcies impact a woman. And the
economy as a whole suffers, too - women’s chronic disease costs hundreds of billions of dollars
each year.
Poor health care has left millions of women in poor health, and unhealthy workers are less
productive than healthy workers. The job-lock created by a health insurance system tied to
employers means that many women remain in sub-optimal jobs in order to maintain health
insurance for themselves and their families, despite the fact that their economic value would be
far greater elsewhere. These inefficiencies are part of why the health care reforms passed into
law last spring are so critical, and why they must not be rolled back in future legislative sessions.
Myriad elements of the reform will be of particular help to boosting women’s economic well
being. A ban on gender rating will put an end to discriminatory practices that charge women
substantially more than similarly-situated men for the same health benefits policies. The creation
of health insurance “exchanges” will expand access to health insurance coverage for the millions
of women who do not have employer-based insurance, including the millions of women who
work part-time and are therefore less likely to have access to an employer-based health insurance
plan. The ban on cost-sharing for well-visits and preventative medicine for all insurers
participating in the exchanges will expand access to cost-effective and necessary preventative
and screening services and treatments for all women. Combined, the health reform legislation
provides both the economic security that comes with access to quality, affordable health
insurance as well as the potential for an economic productivity boost that comes from a healthy
workforce.
In order to achieve the full promise of the law’s reforms, continued vigilance is necessary in
order to insure that implementation goes smoothly. Policymakers would do well to monitor
progress.
Work-Family Policies
The United States is a global laggard in providing adequate social supports for working families.
Our nation’s policies are rooted in a set of antiquated assumptions about the structure of the
typical family where the father brings home the bacon and the mother cares for the home and the
children. These days are long past, and it is high time that our policies catch up. The failure to do
so is holding back the United States economy from fully reaching its potential, because women
remain overburdened with both unremunerated care work and their critical participation in the
labor market. A wide variety o f policies could remedy this situation and unlock our nation’s
economic potential.
In a time of fragile economic recovery, and given the need for fiscal responsibility, is it
appropriate to consider work-life balance policies? The answer is a resounding yes, because such
policies are a proven boon to business, and therefore have the potential to grow the economy.
During recessions and recoveries, the provision of flexible work arrangements provides a winwin solution for employers, as companies can cut back on labor costs, and workers looking for
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reduced hours are able to transition into new, more flexible work arrangements. Flexible work
arrangements also boost employer productivity by improving morale, and potentially by
increasing employee efficiency on the job as well.66 Similarly, the business case for paid sick
leave and paid parental leave is strong because both reduce costly turnover costs and
“presenteeism.” Moreover, most proposals for work-life policies are budget neutral, as they
require either regulatory reforms or employer-employee contributory systems that require little
from the government checkbook.
The Right to Request a Flexible Schedule
The Working Families Flexibility Act would provide employees with the right to request a
modification of work hours, schedule, or work location. It would make it illegal for employers to
interfere or retaliate against employees who utilize the process. The bill is modeled on the verysuccessful “Work-Life Balance Campaign” begun by Tony Blair’s government in the United
Kingdom in 2000. The campaign provides parents with the right to request a flexible schedule,
and, after just one year, about one-quarter of eligible employees - about 800,000 parents - had
successfully reduced or rearranged their work hours, with the majority of employers reporting no
significant problems in complying with the legislation.67
The Working Families Flexibility Act would promote flexibility at a minimal cost. It simply
requires that employers be open to exploring flexible work arrangements, without requiring that
the employer accept the arrangements if the business will suffer. The bill would expand
flexibility across a broad range of practices, including flexible work schedules, compressed
workweeks, reduced-hours arrangements, and telecommuting. Enacting the legislation would be
particularly useful during this period of high unemployment because it motivates both employers
and employees to identify and implement win-win work arrangements that can help to save
American jobs.
Paid Sick Days
The Healthy Families Act, which applies to businesses with 15 or more employees, would allow
workers to earn up to 56 hours (7 days) of paid sick time - one hour for every 30 hours worked to use to stay home and get well when they are ill, to care for a sick family member, to obtain
preventative or diagnostic treatment, or to seek help if they are victims of domestic violence.
The bill would expand paid sick days to an estimated 46 million employees who currently do not
earn paid sick days from their employer.68 The ability of American employees to take time off
without pay has been severely compromised by the recession because more families are now
relying on a single income-eamer due to rising unemployment. Most employers already provide
paid sick days, so the cost of the legislation would be minimal, and it would serve to level the
economic playing field across employers who currently do and do not provide paid sick days. It
would be particularly valuable in the event of a pandemic, since it would reduce the spread of
contagious diseases.
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Stronger Parental Level Policies
The Federal Employees Paid Parental Leave Act would provide four weeks of paid leave for the
birth or adoption of a child by a federal employee. Currently, the federal government provides no
paid parental leave beyond the accrual of sick or vacation days. The act was recently passed by
the House of Representatives. Like other flexibility initiatives, this act would be low-cost, with
the Congressional Budget Office finding that it is budget-neutral, and would not affect direct
spending or receipts. It also would improve morale and employee commitment to provide high
levels of service at a juncture when increasing numbers o f Americans need services that only the
federal government provides. It will serve as an investment in our future, since parents who are
provided with paid leave are more likely to make sure their children receive regular health
check-ups and immunizations, and will have more time to bond with their children during a
crucial stage of early childhood development. The act would make the federal government a
model employer, helping to prod other employers to introduce paid leave.
The Family and Medical Leave Enhancement Act expands the Family and Medical Leave Act of
1993 (FMLA) to cover employees at establishments that employ fewer than 50 but not less than
25 employees. The bill also would extend unpaid employee leave for workers to go to parentteacher conferences or to take their children, grandchildren or other family members to the
doctor for regular medical appointments. This bill would provide FMLA coverage to 13 million
employees who cannot currently take time off for their own illness or that of a family member
without worrying about losing their jobs.69 It would do so at minimal expense to either the
federal government or to employers, and the absence of pay requirements would help employers
to better weather the aftermath of the recession because slack demand is likely to reduce the need
to hire temporary replacement labor. It would provide employees with the opportunity to better
meet the needs of family members for routine or intermittent medical care - a critical need given
the growing population of elderly Americans - and would promote parental involvement in their
children’s education, one of the surest methods for improving educational outcomes.
While the Federal Employees Paid Parental Leave Act and the FMLA Enhancement Act are
important moderate steps toward providing greater access to paid leave for American families,
the United States is badly in need of a comprehensive federal paid parental leave system. As the
only OECD country without a national paid parental leave policy, the United States is in danger
of losing its competitive edge, as other nations’ working mothers are provided with far greater
support and therefore are potentially in a position to pull ahead as global economic producers
and consumers. The design o f such a paid parental leave system could take any number for forms
- for instance, creating a right to access Social Security benefits upon the birth or adoption of a
child, or creating a new system modeled on the employer/worker contribution system of
unemployment insurance.70 The time has come for a serious conversation about how to move the
United States forward on paid leave policies, and doing so is a necessity in order to keep pace
with our global peers.
Financial Regulatory Reform
While women have made progress in joining the ranks o f corporate leadership, the pace has been
slow and women remain too few and far between in corporate board rooms and C-suites. The
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
| December 2010
I Joint Economic Committee
Dodd-Frank Wall Street Reform and Consumer Protection Act, signed into law earlier this year,
will make a difference for women in business leadership, and it will boost women’s power as
consumers as well.
The establishment of Offices of Minority and Women Inclusion at each federal financial services
agency has the potential to boost women’s clout in the corporate world. These Offices will allow
qualified minority- and women-owned securities, accounting, and legal businesses to more
effectively access contracting opportunities. The promotion of diversity in financial services,
including gender diversity, is powerful protection against the “too big to fail” policies that
dragged the economy to the brink of collapse in 2008. Federal agencies’ current contracting
policies promote “too big to fail” by allowing government agencies to continue contracting with
the same large firms who, in many cases, played a role in the recent financial crisis.
Diversification among contractors is crucial if the government is to ensure that no one company
continues to benefit from its largesse. The Dodd-Frank Act empowers these Offices to increase
the participation of minority- and women-owned businesses by ensuring that they are included at
all business levels. By doing so, these Offices have the potential to enhance women’s power as
business leaders.
The creation of the Consumer Financial Protection Bureau promises to provide a boost to women
as consumers. An unregulated consumer credit industry preyed on customers by burying costly
traps in the fine print, concealing true costs. These practices dragged down the economy as a
whole,71 but women have incurred particular injury. Women were 32 percent more likely than
men to receive sub-prime loans, and 41 percent more likely to receive higher-cost sub-prime
loans, regardless of income.72 The Dodd-Frank Act’s creation of the Consumer Financial
Protection Bureau, spearheaded by Elizabeth Warren, promises to be a watchdog on behalf of all
consumers. Because of women’s heightened vulnerability to predatory lending practices, this
watchdog agency will be of particular utility to women. The increased transparency in lending
practices has the potential to enhance women’s financial savvy, thereby increasing women’s
potential as consumers and investors.73
While the Dodd-Frank Act provides the starting point for bolstering women’s positions as both
business leaders and smart consumers, continued vigilance is necessary in order to ensure that
the full potential of these provisions is achieved. Policymakers should monitor the
implementation of these provisions carefully, and insure public reporting on their progress and
results.
Value the Care Economy
The undervalued care economy means that families struggle to find quality, affordable early
education and child care, and this social failure places an enormous burden on the shoulders of
working women. Similarly, women’s unique role in providing elder care - both as paid
caregivers and as unpaid family caretakers - creates economic stresses that impact both families
and the nation as a whole. Investing in early education and child care programs - boosting
funding for Early Head Start and Head Start, for instance, and funding universal pre-kindergarten
programs - is one step toward creating a more secure set of caregiving institutions that will allow
women to meet their full potential in the labor market.
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Investing in the care sector of the economy is also a critical step toward women’s economic
empowerment. Child and elder care workers are a high-tumover, poorly paid group, and they are
predominantly women.74 High turnover means lower quality care. For children in particular,
high-quality care yields phenomenal long-term economic rewards - and lower-quality care
means that the United States’ economy is missing out on those rewards. Boosting wages and
improving job quality could serve to reduce turnover in the paid care economy, which would
both improve the quality of care received and boost the economic fortunes of those employed in
care professions.
The federal role in fostering improvements to the care economy could take various forms. For
instance, the Department of Education (DOE) and the Department of Health and Human Services
(HHS) could convene a national expert panel to address disparities in salaries between the birthto-five and the K-3 workforces with equivalent educational backgrounds, and these agencies
could also use federal dollars to encourage states to address better compensation in their quality
rating and improvement systems. DOE and HHS could invest federal dollars in professional
development, and could incentivize states to include work environment practices that lead to
effective performance and employee well-being as part of their quality rating and improvement
systems.
The federal government could play a role in improving the prospects of the elder care workforce,
as well. For instance, home care workers are exempted from federal overtime and minimum
wage rules under the Fair Labor Standards Act (FLSA). In the recent Coke v. Long Island Home
Care decision, the Supreme Court upheld this exemption, leaving 1.7 million home health aides
without recourse.75 Legislative action could amend the FLSA to better protect home health care
workers, who provide a critical service to our nations’ elderly and play a large and growing role
in the American workforce, particularly in light of the aging Baby Boom cohort and projected
elder care needs in the coming decades.
Consider the Impact o f Tax and Entitlement Reforms on Women
The flurry of reports from deficit-reduction commissions and chatter over reforms to the tax code
have largely ignored the distributional impact of their recommendations. For instance, the
President’s Bi-Partisan Fiscal Commission has paid no attention to the gendered impact of cuts
or changes to the Social Security program. Debates over extensions to the Bush tax cuts have not
focused on this perspective, either. Yet, because of women’s unique work histories and the
continued double-duty they play as workers and caregivers in our economy, such a gendered
perspective is imperative if we are to chart a course toward a prosperous and just future
economy. Any efforts to reform Social Security or revise the tax code ought to take a careful and
conscientious look at the impact on women, and should work to right the continued injustices
that plague women and their families.
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Conclusion
The Great Recession left a great deal o f damage in its wake. Yet, as our nation works to rebuild
and restore the promise of prosperity and growth, we have a tremendous opportunity to become a
better version of our former selves. Doing so will require recognizing our greatest assets,
understanding what’s holding us back from capitalizing on those strengths, and putting in place
the policies necessary to unlock our potential as a great economic power. Women’s role in the
economy is central to that economic renaissance, so the time has come for a focus on economic
gender equity in the 21st century. Doing so means investing in women, and investing in women
means an investment in the economy as a whole. The nation, and America’s 156 million women
and girls, deserve nothing less.
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Endnotes
1Joint Economic Committee Majority Staff analysis of the Current Establishment Survey from the
Bureau of Labor Statistics.
Ibid.
3Boushey, Heather. 2009. “The New Breadwinners.” In Boushey, Heather and Ann O’Leary, eds. The
Shriver Report: A Women’s Nation Changes Everything. Washington, DC: Center for American Progress.
(http://www.shriverreport.com/awn/economv.php).
4Becker, Gary. 2010. “The Revolution in the Economic Empowerment of Women.” (http://www.beckerposner-blog.coni/2010/01/the-revolution-in-the-economic-empowerment-of-women-becker.html). See also
Becker, Gary, et. al. 2010. “The Market for College Graduates and the Worldwide Boom in the Higher
Education of Women.” American Economic Review 100(2): 229-233.
5Lacey, T. Alan and Benjamin Wright. 2009. “Occupational Employment Projections for 2018.” Monthly
Labor Review, November: 82-123 (http://www.bls.gov/opub/mlr/2009/11A.
6Boushey, Heather. 2009. “The New Breadwinners.” In Boushey, Heather and Ann O’Leary, eds. The
Shriver Report: A Women’s Nation Changes Everything, Washington, DC: Center for American Progress.
7Joint Economic Committee Majority Staff analysis of the Current Population Survey from the Bureau of
Labor Statistics, originally published in Joint Economic Committee Majority Staff. 2010. “Women in the
Economy 2010: 25 Years of Progress But Challenges Remain.”
(http://iec.senate.gov/public/index.cfm?p=Reportsl&ContentRecord id=f5b62c08-227f-42b2-89d5886a60f22131 &ContentType id=efc78dac-24bl-4196-a730-d48568b9aSd7&Group id=cl20e658-3d60-470b-a8al6d2d8fc30132).
8Bureau of Labor Statistics. 2009. Women in the Labor Force: A Databook. Table 24.
(http://www.bls.gov/cps/wlf-databook2009.htm').
9Boushey, Heather. 2009. “The New Breadwinners.” In Boushey, Heather and Ann O’Leary, eds. The
Shriver Report: A Women’s Nation Changes Everything. Washington, DC: Center for American Progress.
10Joint Economic Committee Majority Staff analysis of the Current Population Survey from the Bureau
of Labor Statistics, originally published in Joint Economic Committee Majority Staff. 2010. “Women in
the Economy 2010: 25 Years of Progress But Challenges Remain.”
(http://iec.senate.gov/public/index.cfm?p=Reportsl&ContentRecord id=f5b62c08-227f-42b2-89d5886a60f22131 &ContentType id=efc78dac-24b 1-4196-a730-d48568b9a5d7&Group id=c 120e658-3d60-470b-a8al 6d2d8fc30132).
11Bradbury, Katherine and Jane Katz. 2005. “Wives’ Work and Family Income Mobility.” Public Policy
Discussion Papers Number 04-3. Boston, MA: Federal Reserve Bank of Boston.
(http://www.bos.frb.org/economic/ppdp/2004/ppdp0403.pdf).
12Joint Economic Committee Majority Staff analysis of unpublished Current Population Survey data from
the Bureau of Labor Statistics, originally published in Joint Economic Committee Majority Staff. 2010.
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“Working Mothers in the Great Recession.” (http://iec.senate.gov/public/?a=Files.Serve&File
id=c8242af9-
a97b-4a97-9a9d-f7f799991 l a b l
13Ibid.
14Boushey, Heather. 2009. “Women Breadwinners, Men Unemployed.” Washington, DC: Center for
American Progress, (http://www.americanprogress.org/issues/2009/07/breadwin women.html).
15 Silverstein, Micheal. 2008. The Female Economy: What Women Want. PowerPoint presentation on the
United States shared with the Joint Economic Committee.
16Hira, Tahira and Cazilia Lobel. 2006. “Gender Differences in Investment Behavior.” NASD Investor
Education Foundation.
(http://www.finrafoundation.org/web/groups/foundation/@;foundation/documents/fcundation/p 118417.pdf).
17Joy, Lois et. al. 2007. “The Bottom Line: Corporate Performance and Women’s Representation on
Boards.” New York, NY: Catalyst. 0ittp://'www.catalyst.org/pubtication/200/the-bottom-line-corporateperformance-and-womens-representation-on-boards).
18“Women and Profits: Companies That Smash the Glass Ceiling Also Enjoy Higher Profits, a New
Study Indicates.” Harvard Business Review (November 2001): 20. The article cites research by Roy. D.
Adler, Executive Director of the Glass Ceiling Research Center at Pepperdine University.
19Brown, David A. H. et. al. 2002. Women on Boards: Not Just the Right Thing ... But the “Bright”
Thing. Conference Board of Canada. (http://www.europeanpwn.net/files/women on boards canadapdf*)20McKinsey & Company. 2009. Women Matter 3: Women Leaders, a Competitive Edge In and After the
Crisis. (http://www.mckinsev.com/locations/swiss/news Publications/pdf/Women Matter 3 English.pdf).
2iU.S. Department of Commerce Economics and Statistics Administration for the White House Council
on Women and Girls. 2010. Women-Owned Businesses in the 21st Century, (http://www.esa.doc.gov/WOB/Y
22Gaumer, Zachary and David Glass. 2008. “Health Care Sector Growth.” For MedPAC.
(http://www.medpac.gov/transcripts/health%20care%20sector%20growth%20fmal.pdf).
23Bureau of Labor Statistics. 2009. Women in the Labor Force: A Databook. U.S. Department of Labor.
(http://www.bls.gov/cps/wlf-databook2009.htm).
24Lacey, T. Alan and Benjamin Wright. 2009. “Occupational Employment Projections for 2018.”
Monthly Labor Review, November: 82-123 (http://www.bls.gov/opub/mlr/2009/11/).
25Joint Economic Committee Majority Staff analysis of the Current Population Survey from the Bureau
of Labor Statistics, originally published in Joint Economic Committee Majority Staff. 2010. “Women in
the Economy 2010: 25 Years of Progress But Challenges Remain.”
(http://iec.senate.gov/public/index.cfm?p=Reportsl&ContentRecord id=f5b62c08-227f-42b2-89d5886a60f22131 &ContentType id=efc78dac-24bl-4196-a730-d48568b9a5d7&Group id=cl20e658-3d60-470b-a8al6d2d8fc30132L
26U.S. Census Bureau, Current Population Survey, Annual Social and Economic Surveys.
(http.7ywww.census.gov/hhes/www/income/data/liistorical/people/index.htfflD.
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27Joint Economic Committee Majority Staff analysis of the Current Population Survey from the Bureau
of Labor Statistics, originally published in Joint Economic Committee Majority Staff. 2010. “Large
Gender Pay Gap for Older Workers Threatens Economic Security of Older Women.”
(http://iec.senate.«ov/public//index.cihi?a=F'iles.Serve&File id=6dc3f726-69e4-46e6-bd8e684f9a2772d5&SK=86C7D841AE4DA8D0A87EBD4CF8BADB4B).
28Bureau of Labor Statistics. 2009. Women in the Labor Force: A Databook. U.S. Department of Labor.
(http://www.bls.gov/cps/wlf-databook2009.htm).
29Government Accountability Office (GAO). September, 2010. Women in Management: Analysis of
Female Managers’Representation, Characteristics, and Pay. Washington, D.C.: Government
Accountability Office, (http://www.gao.gov/new.items/dl0892r.pdf) .
30Government Accountability Office (GAO). April, 2009. Women’s Pay: Gender Pay Gap in the Federal
Workforce Narrows as Differences in Occupation, Education, and Experience Diminish. Washington,
D.C.: Government Accountability Office. (http://www.gao.gov/products/GAO-Q9-279) .
31U.S. Census Bureau, Current Population Survey, Annual Social and Economic Surveys.
(http://www.census.gov/hhes/www/cpstables/032010/perinc/new03 000.htm). Note, however, that all of these
figures compare all male and female workers over the age of 25, rather than comparing full-time, full-year
workers. As a result, the magnitude of these pay gap figures may be influenced by differences in men’s
and women’s work schedules, amongst other things.
32Dey, Judy Goldberg and Catherine Hill. 2007. Behind the Pay Gap. Washington, D.C.: AAUW
Educational Foundation.
33Bertrand, Marianne, Claudia Goldin, and Lawrence Katz. 2008. “Dynamics of the Gender Gap for
Young Professionals in the Corporate and Financial Sectors.” NBER Working Paper 14681. Cambridge,
MA: National Bureau of Economic Research.
34Carter, Nancy M. and Christine Silva. 2010. “Pipeline’s Broken Promise.” New York: Catalyst, Inc.
35 See for instance Waldfogel, Jane. 1997. “The Effect of Children on Women’s Wages.” American
Sociological Review 62(2): 209-217; Budig, Michelle and Paula England. 2001. “The Wage Penalty for
Motherhood.” American Sociological Review 66(2): 204-225; Anderson, Deborah J. et. al. 2003. “The
Motherhood Wage Penalty Revisited: Experience, Heterogeneity, Work Effort, and Work-Schedule
Flexibility.” Industrial and Labor Relations Review 56(2).
36 Budig, Michelle and Paula England. 2001. “The Wage Penalty for Motherhood.” American
Sociological Review 66(2).
37General Accounting Office (GAO). October, 2003. Women’s Earnings: Work Patterns Partially
Explain Difference Between Men’s and Women’s Earnings. Washington, D.C.: General Accounting
Office. (http://www.gao.gov/new.items/d043 5 .pdf).
38General Accounting Office (GAO). October, 2003. Women’s Earnings: Work Patterns Partially
Explain Difference Between Men’s and Women's Earnings. Washington, D.C.: General Accounting
Office, (http://www.gao.gov/new.items/d0435.pdf) .
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39Correll, Shelly et al. “Getting a Job: Is There a Motherhood Penalty?” American Journal of Sociology
112(15): 1297-1338.
40 Joint Economic Committee Majority Staff analysis of the Current Population Survey and U.S. Census
Bureau data, originally published in Joint Economic Committee Majority Staff. 2010. “The Earnings
Penalty for Part-Time Work: An Obstacle to Equal Pay.”
(http://iec.senate.gov/public/index.cfm?a=Files.Serve&File id=00e50917-a323-49d6-8214d961bt2f732d).
41 Institute for Women’s Policy Research. 2005. “Memo to John Roberts: The Gender Wage Gap is Real.”
Washington, DC: IWPR. (http://www.americanprogressaction.org/issues/2008/pdf/equal pav.pdf).
42Arons, Jessica. December, 2008. “Lifetime Losses: The Career Wage Gap.” Washington, DC: Center
for American Progress, (http://www.americanprogressaction.org/issues/2008/pdf/equal pav.pdf).
43 Lang, Ilene. President, Catalyst, Inc. Testimony to the Joint Economic Committee.
(http://www.catalvst.org/etc/Catalvst Written Testimony.pdf): Catalyst, Inc. November 2010. “Women
CEOs of the Fortune 500.” (http://www.catalvst.org/publication/322/women-ceos-of-the-fortune-1000);
Soares, Rachel, et. al. December 2010. “Catalyst 2010 Census: Fortune 500 Women Executive Officers
and Top Earners.” New York, NY: Catalyst, Inc. (http://www.catalyst.org/publication/459/23/201Qcatalvst-census-fortune-500-women-executive-officers-and-tOD-eamers): Soares, Rachel, et. al. December
2010. “Catalyst 2010 Census: Fortune 500 Women Board Directors. New York, NY: Catalyst, Inc.
(http://www.catalyst.org/publication/460/23/2010-catalvst-census-fortune-500-women-board-directors).
44Ibid.
45Joy, Lois et. al. 2007. “The Bottom Line: Corporate Performance and Women’s Representation on
Boards.” New York, NY: Catalyst. (http ://www.catalyst.org/publication/200/the-bottom-line-corporateperformance-and-womens-representation-on-boards).
46“Women and Profits: Companies That Smash the Glass Ceiling Also Enjoy Higher Profits, a New
Study Indicates.” Harvard Business Review (November 2001): 20. The article cites research by Roy. D.
Adler, Executive Director of the Glass Ceiling Research Center at Pepperdine University.
47OECD. 2007. “Babies and Bosses —Reconciling Work and Family Life: A Synthesis of Findings for
OECD Countries.”See Chart 5.1.
(http://www.oecd.org/document/45/0.3343.en 2649 34819 39651501 1 1 1 1.00.html#Selection). Following
the publication of the OECD study, in June 2010, the Australian government passed legislation enacting a
paid parental leave program scheduled to go into effect on January 1, 2011.
(http://www.fahcsia.gov.au/sa/families/progserv/paid parental/Pages/default.aspx).
48 Sasha Corporation. “Compilation of the Cost of Turnover Studies.”
(http://www.sashacorp.com/tumframe.html).
49Joint Economic Committee Majority Staff analysis of unpublished Current Population Survey data,
originally published in Joint Economic Committee Majority Staff. 2010. “Expanding Access to Paid Sick
Leave: The Impact of the Healthy Families Act on America’s Workers.”
(http://jec.senate.gov/public/index.cfm?a=Files.Serve&File id=abf8aca7-6b94-4152-b720-2d8d04b81ed6).
50Nichol, Kristin L. 2001. “Cost-Benefit Analysis of a Strategy to Vaccinate Healthy Working
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Adults Against Influenza.” Archives of Internal Medicine 161 (March 12): 749 - 759.
51 Goetzel, Ron Z., Stacey R. Long, Ronald J. Ozminkowski, Kevin Hawkins, Shaohung Wang,
and Wendy Lynch. 2004. “Health, Absence, Disability, and Presenteeism Cost Estimates of Certain
Physical and Mental Health Conditions Affecting U.S. Employers.” Journal of Occupational and
Environmental Medicine 46 (April): 398-412. See also Lovell, Vicky. 2005. “Valuing Good Health: An
Estimate of Costs and Savings for the Healthy Families Act.” Washington, DC: Institute for Women’s
Policy Research, (http ://www. iwpr. org/pdf/B248 .pdf).
52Families and Work Institute. 2009. “When Work Works: 2009 Guide to Bold Ideas for Making Work
Work.” New York: Families and Work Institute.
(http://familiesandwork.org/site/research/reports/2009boldideas.pdf).
53 See Corporate Voices for Working Families. 2005. Business Impacts of Flexibility: An Imperative for
Expansion. Washington, D.C.
54 Data from the National Association of Child Care Resource and Referral Agencies, published in Joint
Economic Committee Majority Staff. 2010. “Women in the Economy 2010: 25 Years of Progress But
Challenges Remain.” (http://iec.senate.gov/public/index.cfm?p=Reportsl&ContentRecord id=f5b62c08-227f42b2-89d5-886a60fZ2131&ContentType id=efc78dac-24bl-4196-a730-d48568b9a5d7&Group id=cl20e6583d60-470b-a8al-6d2d8fc30132~).
55Heymann, Jody. “Can Working Families Ever Win?” Boston Review. Orginally published in
February/March 2002. (http://www.bostonreview.net/BR27.1/hevmann.html# 12).
56Heckman, James. January 10, 2006. “Catch ‘Em Young.” Wall Street Journal, page A14.
57The American Recovery and Reinvestment Act injected extra funding into children’s programs for
2010, but the trajectory of decreased spending on children as a share of the federal budget is expected to
resume course when that funding expires at the close of the year. See First Focus. 2010. Children’s
Budget 2010. Washington, DC: First Focus. (http://www.firstfocus.net/library/reports/childrens-budget-2Q 10).
58Isaacs, Julia. 2009. “Supporting Young Families and Children: A Strategy That Pays.” Washington,
DC: Brookings Institution and First Focus.
(http://www.brookings.edu/~/media/Files/rc/articles/2008/winter children families isaacs/winter children families
isaacs.pdf).
59U. S. Census Bureau, Current Population Survey. 2009. Table POVOl: Age and Sex of All People,
Family Members and Unrelated Individuals Iterated by Income-to-Poverty Ratio and Race.
(http://www.census.gov/hhes/www/cpstables/032010/pov/newQl 100 Ol.htni).
60Johnson, Richard W. and Joshua M. Wiener. 2006. “A Profile of Frail Older Americans and Their
Caregivers.” Washington, DC: Urban Institute.
(http://www.urban.org/UploadedPDF/311284 older americans.pdf).
61 Johnson, Richard W. and Anthony T. Lo Sasso. 2006. The Impact of Elder Care on Women’s Labor
Supply. Inquiry 43(3): 195-210.
62Papke, Leslie E. et al. 2008. “Retirement Security for Women: Progress to Date and Policies for
Tomorrow.” Washington, DC: Retirement Security Project.
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('http://www.pewtrusts.org/uploadedFiles/wwwpewtrustsorg/Reports/Retirement securitv/RSPPB Women FINAL 4.2.2008.pdf).
63 Joint Economic Committee Majority Staff analysis of the Current Population Survey, originally
published in Joint Economic Committee Majority Staff. 2010. “Social Security Provides Economic
Security to Women.” (http://iec.senate.gov/public/?a=Files.Serve&File id=d0036901-2da3-4387-b77fd33afffe6f7f).
64Wolff, Jennifer I. and Judith D. Kasper. 2006. Caregivers of Frail Elders: Updating a National Profile.
The Gerontologist 46(3): 344-356. See also White-Means, Shelly and Rose M. Rubin. 2008. “Retirement
Security for Family Elder Caregivers with Labor Force Employment.” Washington, DC: National
Academy for Social Insurance. (http:// www. nasi .ore/sites/default/files/research/WhiteMeans and Rubin January 2009 Rockefeller.pdf).
65Joint Economic Committee Majority Staff. 2009. “Comprehensive Health Reform: An Essential
Prescription for Women.” (http://iec.senate.gov/public/index.cfm?a=Files.Serve&File id=lbll097b-90cb-48068da8 - 16be5fdafe7 a) .
66Galinsky, Ellen. President, Families and Work Institute. July 23, 2009. Testimony to the Joint
Economic Committee. “Balancing Work and Family in the Recession: How Employees and Employers
Are Coping.”
67Kombluh, Karen. 2005. “The Joy of Flex.” Washington Monthly, ('http://www.newamerica.net/node/7355~).
58Lovell, Vicky. 2005. “Valuing Good Health: An Estimate of Costs and Savings for the Healthy
Families Act,” Washington DC: Institute for Women’s Policy Research.
(http://www.iwpr.org/pdf/B248.pdf).
69 Senator Christopher Dodd. 2003. “Dodd Introduces Bill to Expand Historic Family and Medical Leave
Act.” (http://dodd.senate.gov/?q=node/3270/print&pr=press/Releases/03/0205.htmV
70See Boushey, Heather. 2009. “Helping Breadwinners When It Can’t Wait: A Progressive Program for
Family Leave Insurance.” Washington, DC: Center for American Progress.
(http://www.americanprogress.org/issues/2009/06/fmla.html'): See also the Family Leave Insurance Act of
2009, introduced by Representatives Pete Stark (D-CA), Lynn Woolsey (D-CA), George Miller (D-CA),
and Carolyn Maloney (D-NY), modeled on California’s paid family leave program. For a comprehensive
Family Security Insurance policy proposal encompassing paid family leave, see Workplace Flexibility
2010 and the Berkeley Center on Health, Economic, and Family Security. 2010. Family Security
Insurance: A New Foundation for Economic Security.
(http://www.law.berkelev.edu/files/chefs/family security insurance 2010 Final web.pdf).
71 Joint Economic Committee Majority Staff. 2009. “Vicious Cycle: How Unfair Credit Card Practices are
Squeezing Consumers and Undermining the Recovery.”
(http://iec.senate.gov/public/index.cfm?p=Reportsl&ContentRecord id=355f9acl-5056-8059-76d98b95b3c0a95b&ContentType id=efc78dac-24bl-4196-a730-d48568b9a5d7&Group id=cl20e658-3d60470b-a8al-6d2d8fc30132&MonthDisplav=5&YearDisplay=2009')
72 Warren, Elizabeth. 2009. “Feminomics: Women and Bankruptcy.”
(http://www.huffingtonpost.com/elizabeth-warren/feminomics-women-and-bank b 395667.html).
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73 Surveys suggest that women are currently less financially-sawy than men, a fact that may be remedied
with the clear presentation of the details of financial transactions as mandated by the Dodd-Frank Act.
See, for instance, FINRA. 2009. “Financial Capability in the United States.”
(http://www.finrafoundation.Org/web/groups/foundation/@.foundation/documents/foundation/pl20535.pd
I).
74Dill, Janette S., and John Cagle. 2010. Caregiving in a Patient’s Place of Residence: Turnover of Direct
Care Workers in Home Care and Hospice Agencies. Journal of Health and Aging 22:713-733; Whitebook,
Marcy et al. 2004. Then and Now: Changes in Child Care Staffing. Berkeley, CA: Center for the Child
Care Workforce.
(http://www.eric.ed.gov/ERICWebPortal/search/detailmini.isp? nfpb-true& &ERICExtSearch SearchValue 0=E
D452984&ERICExtSearch SearchTvpe 0=no&accno=ED452984).
75Long Island Care at Home & Osborne vs. Evelyn Coke; Bureau of Labor Statistics. 2010. “Home
Health Aides and Personal and Home Care Aides.” Occupational Outlook Handbook, 2010-2011 Edition.
(http://www.bls.gov/oco/ocos326.htm).
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I December 2010
I Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
Women and the Economy 2010: 25 Years of Progress But Challenges Remain
A Report by the Joint Economic Committee
Representative Carolyn B. Maloney, Chair
Senator Charles E. Sehumer, Vice Chair
August 2010
Introduction
On August 26,2010, Americans will celebrate the 90th anniversary of the ratification of the 19th
amendment, which granted women the right to vote and led to their increased participation in our
political system. In 1984, Geraldine Ferraro shattered the political glass ceiling by becoming the
first woman nominated to a national ticket and ushered in a new era of political leadership for
women. Over the last quarter century, women have become a powerful political force, both as
voters and as elected leaders. Did that political benchmark have implications for women’s
economic well-being? Data compiled by the Joint Economic Committee suggest that the answer
is yes.
Twenty-five years ago, America was recovering from the double-dip recession of the 1980s, and
women’s role in the labor force was beginning a multi-decade-long period of expansion. Today,
as our nation’s economy continues down the road to recovery from the Great Recession, women
are poised to be the engine o f future economic growth. Women comprise half of all U.S.
workers, and well over half of all American women are in the labor force. Women’s educational
attainment outstrips that of men, and women’s share of union membership is growing rapidly.
Families are increasingly dependent on working wives’ incomes in order to make ends meet.
Despite a quarter-century of progress, however, challenges remain. While the pay gap has
narrowed over the last 25 years, the average full-time working woman earns only 80 cents for
every dollar earned by the average full-time working man. Certain industries remain heavily
gender-segregated. In addition, millions of women are struggling to juggle work outside the
home with family care-giving responsibilities.
This report, which includes annual data from 1984 through 2009, provides a comprehensive
overview of women’s economic progress over the last twenty-five years and highlights the
additional work left to be done. The role of women in the American economy is of indisputable
importance. The future of the American economy depends on women’s work, both inside and
outside the home.
Women are a critically important part o f the labor force.
In the last 25 years, women’s labor force participation has grown sharply. In 1984, 53.6
percent of women were in the labor market. By 2009, that number had grown to 59.2
percent. All of the growth in women’s labor force participation occurred prior to 2000. In
contrast, over that same period, men’s labor force participation rates were falling. Since the
late 1990s, women’s labor force participation rates have remained roughly flat while men’s
labor force participation has continued to decline. (See Figure 1.)
Prepared, by the Majority Staff of the Joint Economic Committee
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70%
1984
19S9
1994
19S9
2004
Source: Bureau sf Labor Statistics, Current Pcetastior, Surwey.
♦♦♦
While total union membership has declined over the last twenty-five years, women’s union
membership has been on the rise. In 1984, women made up just over one-third (34 percent)
of all union members. In 2008, women comprised 45 percent of all union members. The
growing importance of women in the labor movement is likely due to the expansion of
female-concentrated sectors such as health care, education, and the service sector combined
with the contraction of male-concentrated sectors such as manufacturing. (See Figure 7.)
1984
19E9
1594
1939
2004
2009
S-ourcs: Bureau of Lsfcsr Statistics. Current Peculation Survey,
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VerDate Nov 24 2008
December 2010
Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
Easing the Squeeze on Women and Their Families
A Report by the Joint Economic Committee
Representative Carolyn B. Maloney, Chair
Senator Charles E. Schumer, Vice Chair
May 21, 2009
Democrats inherited one of the worst economic crises in our nation’s history, a crisis that is
putting put extraordinary stress on millions of American families struggling to pay the bills and
invest in their children’s futures. The strain on women and their families is compounded by a
continuing gender pay gap. The road to recovery will be long, but Congress has worked quickly
with the Obama Administration to ease the pressure on working families by advancing an
economic policy agenda aimed at restoring broad-based growth, reducing the high costs of health
care, improving retirement security, and increasing prosperity for all Americans.
The Bush Legacy: The Squeeze on Women and Their Families
1. Falling Incomes, Rising Expenses.
•
•
•
•
Median annual income for female-headed families fell $1,492 to $25,897 between 2000
and 2007, the most recent year for which data is available. For all families, median
annual income in 2007 was $52,153.
The average family health insurance premium increased by nearly 58 percent between
2000 and 2008, to $12,527.
The average cost of college tuition at a four-year public university increased by 47
percent between 2000 and 2007.
The average cost of full-time childcare for one child in 2008 was $6,094.
2. Disappearing Jobs.
•
•
•
1.5 million jobs held by women have vanished since the recession began in December
2007.
Nearly 5 million women are unemployed, an increase of 70 percent since December
2007.
The unemployment rate for women 20 years and older has increased to 7.1 percent, and
to 10.0 percent for women maintaining families, which is 1.1 percentage points higher
than the national average of 8.9 percent in April 2009.
3. One-Third of Single Mothers Living in Poverty.
•
Nationwide, 3.6 million families headed by single mothers (33 percent of all female
headed households with children) lived below the poverty line in 2007.
43 percent of children living in female-headed households lived below the poverty line,
compared to the national child poverty rate of 18 percent. 7.6 million children in female
headed households were poor in 2007, an increase of 20 percent since 2000.
Prepared by the Majority Staff of the Joint Economic Committee
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•
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
4. Nearly 3 Million More Uninsured Women Since 2000.
•
•
21 million women (14 percent) had no health insurance in 2007, the most recent year of
available data. 22 percent of single mothers had no health insurance.
14 percent of children under the age of 18 living in female-headed households had no
health insurance in 2007.
5. Skyrocketing Debt.
•
•
•
•
Women were forced to rely heavily on debt financing in order to pay their bills in the
face of grim earnings and employment prospects since 2000. Average total debt amongst
female headed-households shot up by 59 percent (from $28,000 to $44,300) between
2001 and 2007, the most recent year of available data.
During the sub-prime boom - despite having higher credit scores on average - female
home-buyers were 32 percent more likely than males to receive a high cost subprime
mortgage loan. The Joint Economic Committee estimates that the number of subprime
foreclosures for 2009 will be 830,000, with female homeowners bearing a
disproportionate burden.
Average credit card debt for female-headed households grew by 35 percent, from $1,523
to $2,058 between 2001 and 2007. Variable interest rates and other credit card practices
mean that female-headed households are diverting an increasing share of their incomes
toward servicing their credit card debt, which puts a further strain on family finances.
Average education-related debt for female-headed households doubled between 2001 and
2007, from $1,631 to $2,532, as families struggled to keep up with rising college tuition
costs.
Easing the Squeeze on Women and Their Families
While the problems are enormous, the 111th Congress and the Obama Administration have
worked swiftly to chart a course toward a stronger economic future. The American Recovery and
Reinvestment Act is designed to turn our economy around, and it includes many provisions that
will put money in women’s pockets today and help them invest in their futures. In addition, the
FY2010 budget provides a blueprint for a policy agenda that invests in the economic well-being
of women and their families.
1. Closing the wage gap.
•
With the passage of the Lilly Ledbetter Fair Pay Act, Democrats restored the rights of
women and other workers to challenge unfair pay—to help close the wage gap where
women earn 78 cents for every $1 a man earns in America.
2. Putting money in the pockets of those who need it most.
The Making Work Pay Tax Credit, an extended Child Tax Credit and an expanded
Earned Income Tax Credit are already putting money in the wallets of working mothers
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•
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
and their families. A refundable Child Tax Credit and expanded saver’s credit will
provide a boost to millions saving for their families’ futures.
3. Protecting the most vulnerable.
•
The Recovery Act will help protect the health of low income families by helping states
avoid cuts in Medicaid enrollment and services, and boosting funding for food stamps,
WIC, and food bank programs that serve as critical sources of healthy food for struggling
families across the country.
4. Investing in America’s future through job training and education.
•
Congress and the Administration have committed substantial funding towards job
training in high-growth sectors, including “green jobs,” expanded Trade Adjustment
Assistance expansion to cover training programs for workers displaced from the service
sector, and created a State Fiscal Stabilization Fund to help prevent teacher layoffs and
cuts in other key service.
5. Making college affordable.
•
The American Opportunity Tax Credit and increased Pell Grants are making college
more affordable for millions more women, and the FY2010 Budget proposes an
expansion of the Federal Perkins loan program and a new College Access and
Completion Fund.
6. Helping families stay in their homes.
•
Stabilizing the housing market is central to restoring the American economy, and
Democrats have worked quickly to put in place policies that will ease the burden on
working families. The Helping Families Save Their Homes Act of 2009 will provide
lenders and homeowners with key tools and incentives to modify unfair loans and to
avoid foreclosures. Coupled with the Administration’s actions to help families refinance
into lower interest rate loans if they have mortgages issued or guaranteed by Fannie Mae
and Freddie Mac and owe more on their houses than their current value, this critical piece
of legislation will halt the steep decline in home prices and keep the dream of
homeownership alive for millions of American families.
7. Making child care affordable.
The Recovery Act funded Child Care and Development Block Grants that support quality
child care services for low-income families, additional funding for Head Start and Early
Head Start over the next two years.
Prepared by the Majority Staff of the Joint Economic Committee
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•
Invest in Women, Invest in America:
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December 2010
Joint Economic Committee
8. Making quality health care coverage affordable.
•
With the reauthorization of the Children’s Health Insurance Program, the Democrats
expanded children’s access to health insurance, and the FY2010 Budget includes a
budget-neutral reserve fund that will facilitate the passage of health insurance reform that
achieves America’s shared goals of constraining costs, expanding access, and improving
quality.
Sources: U.S. Census Bureau; Kaiser Family Foundation; National Association of Child Care Resource &
Referral Agencies; College Board; Bureau of Labor Statistics; Consumer Federation of America; JEC
calculations from the Survey of Consumer Finances, the Mortgage Bankers Association’s National
Delinquency Survey, the Bureau of Labor Statistics, and Global Insight.
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
Women in the Recession: Mothers and Families Hit Hard
A Report by the Joint Economic Committee
Representative Carolyn B. Maloney, Chair
Senator Charles E. Schumer, Vice Chair
May 28, 2009
Executive Summary
Working women have received pink slips in growing numbers over the course of the current
recession, which began in December 2007. For the first 3 months of the recession, when job
losses were relatively light, women actually gained rather than lost jobs. This uptick in women’s
employment is similar to what has happened in previous recessions. However, in August 2008,
this recession began to look quite different from past downturns. Women’s job losses picked up
pace to become a significant fraction of the total monthly job losses.
As women’s job losses have accelerated, so have the job losses for working mothers. A Joint
Economic Committee analysis of published and unpublished data collected by the Bureau of
Labor Statistics (BLS) finds that increases in unemployment during this recession have been
especially steep for female heads of household - mothers who are solely responsible for
maintaining their families’ economic security. Key findings of the analysis include the
following:
•
•
•
•
In 2008, seven out of ten mothers with children under 18 years old were in the labor
force. Over half of all mothers usually worked full time last year.
As of April 2009, nearly one million working-age female heads of household wanted a
job but could not find one.
One out of every ten women maintaining a family is unemployed, which exceeds the
highest rate (9.0 percent) experienced during the 2001 recession and the “jobless
recovery” that followed.
The ranks of female heads of household who are unemployed or “marginally attached” to
the labor force has grown across all demographic groups, with women of color faring the
worst. Black and Hispanic women in this group are currently experiencing
unemployment at rates of 13.3 per-cent and 11.0 percent, respectively.
The American Recovery and Reinvestment Act (ARRA) will temper the effects of the current
recession for these families right now and over time. Extended unemployment benefits, nutrition
assistance programs, preserving Medicaid benefits and tax cuts will bring immediate relief for
these families. In addition, ARRA invests in job creation in education, healthcare, and child care
that tend to disproportionately employ women. This will help to ensure that female-headed
households will not be left behind in the recovery.
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Invest in Women, Invest in America;
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Unlike those counted as unemployed, marginally attached workers have not searched for work in
the preceding 4 weeks, (See Figure 3.) The increase in the number of marginally attached female
heads of household has occurred across all demographic groups. Given that a female head of
household is the sole breadwinner for her family, the growing rate of marginal labor force
attachment among this group is particularly troublesome.
Figures. Nearly 1 Million Women Maintaining Families Want a Job
Female Heads of Household, 25-54 fears Old, Unemployed or Marginally Attached,
By Start and End of Last and Current Recession
1200
.... — ................................................- ......................................- .....- ....— .... - ---------------------------- -------------------- - ...................—
......... -................ ... - ....- .................. — .........
1000
March 2001
December 200?
November 2001
April 2009
Source: JEC calculations based on data from unpublished tables from the Bureau of Labor Statistics, Current Population Survey.
Nearly one million working age female heads of household wanted a job but could not find one
as of April 2009,16 months into the .recession,5 These included 761,000 unemployed workingage heads of household, 304,000 more than at the start o f the recession, and an additional
154,000 “marginally attached,” 92,000 more than at the start of the recession.6
The unemployment rate today for all female heads of households is 10.0 percent, which exceeds
the highest rate (9,0 percent) experienced during the 2001 recession and the “jobless recovery”
that followed. Because employment for female heads of household never regained strength
during the jobless recovery of the 2000s, this group entered the current recession with a
relatively high unemployment rate as compared to the rest of the population.7 (See Figure 4.) In
December 2007, the overall civilian unemployment rate was 4.9 percent8 while the rate for
female heads of household was 6,9 percent.9
Comparing the current recession to the 2001 recession shows how much more severe this
recession is for female heads of household. While the unemployment rates were similar at the
start of the recession, the duration of the current recession is taking a heavy toll. Over the past 12
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VerDate Nov 24 2008
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Women o f Color Are Faring the Worst in this Recession
White women, including white female heads of household, have fared somewhat better than
women of color. In both recessions these households experienced a fairly steady, although high,
rate of unemployment. (See Figure 5.) But the current recession now has this group facing an
unemployment rate of 8.7 percent, 3.1 percentages points higher than one year ago and
considerably higher than at any point during the 2001 recession.11
Figure 5. Unemployment Rate Among White Female Heads of Household
By Month for Last and Current Recession
12.0
Current Recession
10.0
y\
/
~
o
~
<T\
Percen
8.0
’
N /
Jobless Recovery
2001 Recession
4.0
2.0
0.0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Months Since Start of Recession
Source: JEC calculations b ased on non-seasonaily adjusted d ata from unpublished tab les from the
Bureau of Labor Statistics, C urrent Population Survey.
Black female heads of household started both recessions with an unemployment rate just under
10 percent, well above the average for all female heads of household.12 (See Figure 6.) At first,
their experience in the labor market during this recession was comparable to their experience in
the 2001 recession. However, as the current recession intensified, the gap widened between the
unemployment rates in the current recession and in the jobless recovery following the 2001
recession. The unemployment rate for black female heads of household is currently 3.7
percentage points higher than it was one year ago, suggesting that the employment situation for
these women is quite difficult.
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Figure 6. Unemployment Rate Among Black Female Heads of Household
By M onth for Last and Current Recession
i e .0
C u rre n t Recession
1 4.0
.... . „„
f/Tf
12.0
10.0
c
g
^
/
\
^ s
Jobless R ecovery
2001 Recession
8.0
a
q.
6.0
4 .0
2.0
0.0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Months Since Start of Recession
Source: JEC calculations based on ncn-seasonally adjusted data from unpublished tables from the
Bureau of Labor Statistics, Current Population Survey.
Hispanic female heads of household started this recession with a lower unemployment rate than
in 2001. (See Figure 7.) Over the past 12 months, the unemployment rate for Hispanic female
heads of household has increased 4.0 percentage points.13
Figure 7. Unemployment Rate Among Hispanic Female Heads of Household
By M onth for Last and C urrent Recession
C u rre n t Recession
1 2 .0
1 0.0
| 8 .0
<y
Q.
2001 Recession
Jobless Recovery
6 .0
4 .0
2 .0
0 .0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Months Since Start of Recession
Source: JEC calculations based on non-seasonally adjusted data from unpublished tables from the
Bureau of .abor Statistics, Current Population Survey.
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Prepared by the Majority Staff of the Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
Summary
The American Recovery and Reinvestment Act (ARRA) will temper the effects of the current
recession for these families right now and over time. Extended unemployment benefits, nutrition
assistance programs, preserving Medicaid benefits and tax cuts will bring immediate relief for
these families. In addition, ARRA invests in job creation in education, healthcare, and child care
that tend to disproportionately employ women. This will help to ensure that female-headed
households will not be left behind in the recovery.
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Endnotes
1Joint Economic Committee, “Equality in Job Loss: Women Are Increasingly Vulnerable to Layoffs
During Recessions” July 22, 2008.
2 Bureau of Labor Statistics (BLS), Current Population Survey (CPS), Table 4. Number of families by
presence and age of own children under 18 years old, type of family, employment status of parents, race
and Hispanic or Latino ethnicity, 2008 annual averages. The Current Population Survey is a monthly
survey of about 50,000 households conducted by the Bureau of the Census for the Bureau of Labor
Statistics. The sample is scientifically selected to represent the civilian non-institutional population. See
w w w .census.gov/cps/ for more information on this survey.
3BLS, Current Employment Statistics. The last seven months available data are for August 2008 through
February 2009.
4 BLS, Current Population Survey, unpublished tables. These data are not seasonally adjusted. According
to the CPS, a “family” is a group of two persons or more (one of whom is the head of the household)
residing together and related by birth, marriage, or adoption. Thus, female heads of households may
include households where the dependents are the aging parents rather than children of the head of
household. We note that the CPS discontinued the use of the word “head of household” in March 1980
and replaced it with “householder.”
5 This is the sum of the unemployed and the marginally attached. Ibid.
6Ibid.
I Ibid.
8BLS, Current Population Survey, Table A-l. Employment status of the civilian population by sex and
age, various months. These data are seasonally adjusted.
9BLS, Current Population Survey, unpublished tables.
10Ibid. We note that the April 2009 data show a reduction in the unemployment rate. However, this is a
highly volatile series and it is not possible to extrapolate a change in trend from a single observation. This
hold for figures 4-7.
II Ibid.
12Ibid.
13Although none of the data used for Figures 4 -7 are seasonally adjusted, a seasonal trend is only visible
for His-panic female heads of households, shown in Figure 7. The peak in the unemployment rate during
the last recession and the spike in unemployment during month 12 of the current recession are for
December. This strong seasonality may indicate that Hispanic women who maintain families are more
likely to be employed in occupations that have strong seasonal trends. Ibid.
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Prepared by the Majority Staff of the Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Understanding the Economy: Working Mothers In the Great Recession
A Report by the Joint Economic Committee
Representative Carolyn B. Maloney, Chair
May 2010
An Update on Working Moms
The Great Recession has taken a huge toll on working families. The vast majority of jobs lost
were lost by men, but a substantial number of jobs were lost by women during this recession.
From December 2007 to April 2010, women lost 46 jobs for every 100 jobs lost by men.1 By
comparison, during the 2001 recession, women lost 17 jobs for every 100 lost by men and
women lost less than 2 jobs for every 100 jobs lost by men during the 1990s recession. Indeed,
in recent months, women lost jobs while men gained jobs.2 From October 2009 to March 2010,
women lost 22,000 jobs while men gained 260,000.3 Women’s increased vulnerability to the
business cycle has important repercussions for families’ economic security. This report provides
an updated look at the employment situation of working mothers4 with children under 18 years
old, and examines the impact of the recession on their participation in the labor market using
unpublished data from the Bureau of Labor Statistics.5
Families Depend on Mothers’ Employment.
Over the past several decades, women have played a role of growing importance in the labor
force. It is clear that in the wake of the Great Recession, families continue to rely upon mothers’
employment. Rather than opting out of the labor force, mothers increased their labor force
participation over the recession. The share of mothers working or actively searching for work
increased from 71.0 percent to 71.4 percent between 2007 and 2009.6
During that time, mothers’ participation shifted away from full-time work to unemployment and
part-time work, with the share of all mothers working full-time dropping to 48.3 percent in 2009
from 51.3 percent in 2007. (See Figure 1.) The share of all mothers working part-time rose
almost a full percentage point to 17.2 percent, while the share of unemployed mothers increased
2.6 percentage points to 5.9 percent.
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Invest in Women, Invest in America;
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Figure 1. Nearly Half of All Mothers Worked FullTime Last Year
Source: Joint Economic Committee Majority Staff calculations based on unpublished dstafrom the Bureau of Labor Statistics, Current
Population Survey.
i
>
O f the 21.7 million mothers who were usually employed in 2009, two-thirds were in a dualeamer family. But the remaining one-third— 7.5 million mothers—were the sole job-holders in
their family, either because their spouse was unemployed or out of the labor force, or because
they were heads o f household. (See Figure 2.)
Figure 2. One-in-Three Working Mothers Was the Only Jobholder in Her Family
tie d w om en,
tse o u t o f th e
ib o r fo rc e
o
M J P 1 o* D ' S
.o '
Lomraittee Va 0'i;> irffcalculations b ased o n tr.u is isre j J a w ' o u t i-Bi.
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Cjrrerrt
•* g
Prepared by the Majority Staff of the Joint Economic Committee
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'* j
Invest in Women, Invest in America:
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I December 2010
I Joint Economic Committee
Married Mothers Search for Work to Improve Their Families’ Economic Security.
Until recently, job losses were concentrated in male-dominated industries like construction and
manufacturing, so fathers were more likely to lose a job and mothers were more likely to hold
onto their employment or quickly find a new job. As job losses slowed in the final months of
2009, women continued to lose jobs as men found employment.
In order to cope with the widespread job losses during the recession, many parents who were
previously out of the labor force entered the workforce, presumably to compensate for a spouse’s
lost wages. In general, mothers are far more likely than fathers to be out of the labor force, thus
the movement of parents into the labor market largely reflects that of mothers. In 2007, 35.2
percent of two-parent families had only one employed parent, compared to 36.8 percent in 2009.
That 1.6 percentage point net difference masks more dramatic changes in the share of families
solely dependent on a mother’s earnings. In fact, families where the mother was the only job
holder rose 2.5 percentage points from 4.9 percent of married-couple families to 7.4 percent.
More than ever, families depend on mothers’ work.
Many married mothers who looked for employment in order to bolster their families’ economic
security found it difficult to find work because of the severe shortage of jobs. The labor force
participation rate rose for married mothers between 2007 and 2009, meaning that more married
mothers were searching for a job. However, the employment-to-population ratio—the so called
‘employment rate’—fell over the recession from 66.7 percent to 65.5 percent, indicating that
fewer married mothers actually had a job. The unemployment rate nearly doubled to 5.8 percent
during that time—a clear sign that mothers wanting work struggled to find a job.
Single Mothers Continue to Struggle with High Unemployment.
Families headed by single mothers had no second parent to fall back on in the face of job loss or
reduced hours and earnings. Labor force participation was already higher among these women,
with over three-quarters (76.5 percent) of women maintaining families working or actively
searching for work in 2007. Consequently, the recession did not boost their participation rate.
Instead, the participation rate of mothers maintaining families dropped to 75.8 percent indicating
that many single mothers dropped out of the labor force probably because they were unable to
find work.
For single mothers in the labor force, unemployment increased dramatically during the recession.
Between 2007 and 2009, the unemployment rate of single mothers increased from 8.0 percent to
13.6 percent. Single mothers of children under the age of 6 who are not yet in school had an
unemployment rate of 17.5 percent in 2009. For these mothers, even searching for work can be a
challenge because they may have to find child care in order to go on an interview, and high costs
of child care eat away a substantial chunk of their earnings once they do find a job.
The Part-Time Penalty Can Be Even Greater for Mothers.
Many women have been unable to find full-time employment because of the weak labor market.
In 2009, 3.3 million women worked part-time for economic reasons, meaning that either their
hours had been cut back or that they searched for full-time work but could only a part-time job.
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I December 2010
I Joint Economic Committee
Some of those part-time workers usually worked part-time but would have preferred to move to
Ml-time work, likely because of economic hardship such as a spouse’s job loss.
Part-time workers face a severe earnings penalty, with a wage equal to as little as 60 percent of
the wage for full-time workers in the same occupation. (See Figure 3.) Part-time work also
means lower earnings over time, and part-time jobs usually do not come with the same health
benefits, paid time-off for vacation and sick leave, or pension benefits that full-time workers
receive.'
Figure 3. Part-Time Workers Are Subject to a Wage Penalty
Part-Time W a g e
as a
Percent of Full-Time Wage B y O c c u p a tio n
B ro k e n D o w n
Parity with
Full-Time — »
Workers
0
20
40
60
80
100
Source: Joint Economic Committee Majority Staff calculations based on data from the United States Census Bureau.
Over one-third (35 percent, or 6.2 million) of all women working part-time in 2009 were
mothers. For many of those, including 2.7 million mothers with children less than 6 years old
and not yet in school, working a part-time job also means finding part-time child care. The part
time earnings penalty is even more devastating for those mothers because part-time child care
can be just as costly as full-time care.8
Conclusion
Families depend on women’s earnings. Mothers’ work is vital not only for their families’
economic security, but also for the strength of the American economy as a whole. Understanding
and addressing the impact of the Great Recession on mothers is a crucial piece of the economic
recovery.
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Endnotes
1 Bureau of Labor Statistics, Current Employment Survey.
2 Ibid.
3 April’s strong employment growth showed women gained 86,000 jobs last month, far fewer than the
204,000 jobs gained by men in April. Bureau of Labor Statistics, Current Employment Survey, April
2010.
4 The Joint Economic Committee released a report on working mothers last year. See Women in the
Recession: Working Mothers Face High Rates of Unemployment, May 28, 2009.
5 Data is from Tables 4, 4a, and 6 using data from the Current Population Survey.
6 Unless otherwise specified, mother refers to a woman with her own children under the age of 18.
Married mothers are those with a spouse who is present. Single mothers include married mothers with
an absent spouse; divorced, separated, and widowed mothers; and mothers who have never been
married.
7 See Joint Economic Committee report: The Earnings Penalty for Part-Time Work, April 20, 2010.
8 Many child care centers do not offer prorated part-time child care meaning that the per-hour cost for
part-time care is higher than for full-time care.
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A Comprehensive Review of Women in the U.S. Economy
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I December 2010
I Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Testimony of Lisa M. Maatz
Director Public Policy and Government Relations
American Association of University Women
before the
United States Joint Economic Committee
Hearing on
“Equal Pay for Equal Work?
New Evidence on the Persistence of the Gender Pay Gap”
April 28, 2009
“Chairwoman Maloney and members of the Committee, thank you for the opportunity to testify
today on the critical issue of pay equity.
I am the Director of Public Policy and Government Relations at the American Association of
University Women. Founded in 1881, AAUW has approximately 100,000 members and 1300
branches nationwide. AAUW has a proud 127-year history of breaking through barriers for
women and girls, releasing its first report on pay equity in 1913. Today, AAUW continues its
mission through education, research, and advocacy.
I am particularly pleased to be here to talk about pay equity, not simply because today is Equal
Pay Day, but also because AAUW believes it’s critical these tough economic times aren’t used
as an excuse to roll back the hard fought gains women have made. Instead, policy makers need to
ensure that women workers - all workers - don’t just survive the downturn but continue the
march toward fair pay and workplace opportunity. Empowering women is one investment that
always pays long-term dividends, not only for the women themselves but their families and the
entire nation as well.
As the recession continues, women are increasingly becoming the sole breadwinners of their
families - making pay equity not just a matter of fairness but the key to families making ends
meet. The American Recovery and Reinvestment Act, signed into law in February, is intended to
save or create 3.5 million jobs over the next two years. According to a White House report, an
estimated 42 percent of the jobs created - nearly 1.5 million - are likely to go to women.1 The
recovery package clearly is counting on women to play a leading role in the nation’s economic
recovery, and their ability to do so is strengthened considerably when women’s paychecks are a
fair reflection of their work. In fact, this is just one of the reasons why new legislation
strengthening pay equity laws is not only necessary but timely, amounting to an “equity”
economic stimulus.
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Prepared by the Majority Staff of the Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
I am also pleased to share findings from AAUW’s research report, Behind the Pay Gap. Our
report provides reliable evidence that sex discrimination in the workplace continues to be a
problem for women, including young college-educated women. I will also discuss pending
legislation that we believe could make real progress in closing the pay gap between men and
women, as well as how the wage gap generally affects women - especially mothers.
The Wage Gap Persists
According to the U.S. Census Bureau and Bureau of Labor Statistics, women who work full time
earn about 78 cents for every dollar men earn.2 Because o f the wage gap, since 1960, the real
median earnings of women have fallen short by more than half a million dollars compared to
men.3 Minority women face a larger wage gap. Compared to white men, African American
women make 67 cents on the dollar (African American men make 78 cents); Hispanic women
make about 58 cents (Hispanic men make almost 66 cents).4
In addition, wage discrimination lowers total lifetime earnings, thereby reducing women’s
benefits from Social Security and pension plans and inhibiting their ability to save not only for
retirement but for other lifetime goals such as buying a home and paying for a college education.
New research calculates that the pay inequity shortfall in women’s earnings is about $210,000
over a 35-year working life.5
Origins of the Wage Gap
One partial explanation for the wage gap is occupational segregation. According to AAUW
research, women are still pigeonholed in “pink-collar” jobs that tend to depress their wages.
AAUW’s 2003 report, Women at Work, found that women are still concentrated in traditionally
female-dominated professions, especially the health and education industries. The highest
proportion of women with a college education work in traditionally female occupations: primary
and secondary school teachers (8.7 percent) and registered nurses (6.9 percent).
A 12-state analysis based on data from the Department of Education found that women tend to
be overwhelmingly clustered in low-wage, low-skill fields. For example, women constitute 98
percent of students in the cosmetology industry, 87 percent in the child care industry, and 86
percent in the health aide industry. In high-wage, high-skill fields, women fall well below the 25
percent threshold to qualify as a “nontraditional field.” For example, women account for 10
percent in the construction and repair industry, 9 percent o f students in the automotive industry,
6 percent in the electrician industry, and 6 percent in the plumbing industry.7
Women’s achievements in higher education during the past three decades are considered to be
partly responsible for narrowing the wage gap.8 But at every education level, women continue to
earn less than similarly educated men. Educational gains have not yet translated into full equity
for women in the workplace.
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A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
The AAUW Report: Behind the Pay Gap
In our report, Behind the Pay Gap, AAUW found that just one year after college graduation,
women earn only 80 percent of what their male counterparts earn. Even women who make the
same choices as men in terms of major and occupation earn less than their male counterparts.
Ten years after graduation, women fall further behind, earning only 69 percent of what men earn.
After controlling for factors known to affect earnings, a portion of these pay gaps remains
unexplained and is likely due to discrimination.
The study is based on nationally representative surveys conducted by the Department of
Education. AAUW’s research uses the Baccalaureate and Beyond Longitudinal Study, a
nationally representative data set of college graduates produced by the Department of Education.
This data set is unique because it is designed to follow bachelor’s degree recipients as they
navigate the workplace, graduate school and other life changes such as having a family. The
research examines two sets of college graduates: men and women who graduated in 1999-2000,
and men and women who graduated in 1992-93; we also limited our analysis to those who
earned their first bachelor’s degree at age 35 or younger.
The 1999-2000 graduates were chosen because they were the most recent graduates interviewed
in the year after graduation. By looking at earnings just one year out of college, we believe you
have as level a playing field as possible. These employees don’t have a lot of work experience
and, for the most part, don’t have caregiving obligations, so you’d expect there to be very little
difference in the wages of men and women. The 1992-1993 graduates were chosen so that we
could analyze earnings ten years after graduation.
The pay gap can only be partially explained by differences in personal choices. Despite
some gains, many majors remain strongly dominated by one gender. Female students are
concentrated in majors that are associated with lower earnings, such as education, health, and
psychology. Male students dominate the higher-paying majors: engineering, mathematics,
physical sciences, and business. Both women and men who majored in “male-dominated” majors
earn more than those who majored in “female-dominated” or “mixed-gender” majors.
The choice of major is not the full story, however, as a pay gap between recently graduated
women and men is found in nearly every field and in every occupation. Women full-time
workers earn less than men full-time workers in nearly every major, although the size of the gap
varies. In education, a female-dominated major and occupation, women earn 95 percent as much
as their male colleagues earn. In biology, a mixed-gender field, women earn only 75 percent as
much as men earn, just one year after graduation.
The kinds of jobs that women and men accept also account for a portion of the pay gap. While
the choice of major is related to occupation, the relationship is not strict. For example, some
mathematics majors teach, while others work in business or computer science. It is important to
bear in mind that such choices themselves can be constrained in part by biased assumptions
regarding appropriate career paths for men and women. Other differences in type of jobs also
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
affect earnings. For example, women are more likely than men to work in the nonprofit and
public sectors, where wages are typically lower than in the for-profit sector.
AAUW’s analysis showed that men and women’s different choices can explain only some of the
pay gap. After controlling for factors like major, occupation, industry, sector, hours worked,
workplace flexibility, experience, educational attainment, enrollment status, GPA, institution
selectivity, age, race/ethnicity, region, marital status and children, a five percent difference in the
earnings of male and female college graduates is unexplained. It is reasonable to assume that this
difference is the product of discrimination.
Discrimination is difficult to measure directly. It is illegal, and furthermore, most people don’t
recognize discriminatory behavior in themselves or others. This research asked a basic but
important question: If a woman made the same choices as a man, would she earn the same pay?
The answer is no.
Ten years after graduation, the pay gap widens. AAUW’s analysis found that, ten years after
graduation, the pay gap widened - so much so that female full-time workers earned only 69
percent of what their male peers earned.
Ten years out, the pay gap within occupations also increased. For example, in engineering and
architecture, where wages were at parity one year out of college, we now see that women earn
only 93 percent of what their male counterparts earn. In business and management, the pay gap
widens, with women earning 69 percent of men’s wages, compared to 81 percent one year out.
Strikingly, women did not make gains in any fields compared to their male counterparts.
Similar to what we saw one year out of college, this pay gap can only partially be explained as a
result of women’s characteristics and choices. In terms of occupation, women and men remained
segregated in the workforce over time, and the difference in earnings among occupations grew
over this time period. Women also continued to be much more likely to work in the lower-paying
non-profit sector. Among full-time workers, women reported working fewer hours than men, and
their employment and experience continuity also differed from men. These choices were
associated with wage penalties.
It is important to note that what we are calling women’s “choices” are often constrained and need
to be looked at in context. When women earn less most couples are likely to prioritize the higherearning husband’s well-being and career path in relation to child care, choice of residence, and
other household decisions. When women are married, this trade-off may be worthwhile;
however, nearly one half of women did not live with a husband in 2005.9 While most women
marry at some point, most also spend a large part of their lives on their own. Women are also
much more likely than men to be single parents.10 Therefore the presumption of the presence of a
higher earning mate is often a false one. It is important for us to remember that lower pay for
women means fewer resources for their children today and women’s retirement tomorrow.
Women are investing in higher education, but not receiving the same salaries as men.
Choices made in college affect earnings ten years later. College selectivity matters for men and
women, but gender differences were more pronounced. Strikingly, a woman who earned a degree
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from a highly selective institution had lower earnings than men with degrees from highly
selective institutions or moderately selective schools, and about the same pay as a man who
attended a minimally selective college. Both women and men invest a great deal of financial
resources in their college educations, and often graduate with substantial student loans. AAUW’s
research suggests that a woman’s investment in attending a highly selective school - which is
typically more expensive - does not pay off for her in the same way it does for her male
counterparts.11 Further, because of the pay gap, women often have a harder time paying off their
student loans.
Ten years out, the unexplained portion of the pay gap widens. AAUW’s analysis showed that
while choices mattered, they explained even less of the pay gap ten years after graduation.
Controlling for a similar set of factors, we found that ten years after graduation, a 12 percent
difference in the earnings of male and female college graduates is unexplained and attributable
only to gender.
The pay gap among full-time workers understates the lifetime difference in the earnings of
women and men. The impact of personal choices such as parenting has profoundly different
effects on men and women. Ten years after graduation, 23 percent of mothers in this sample
were out of the work force, and 17 percent worked part-time. Among fathers, only 1 percent
were out of the work force, and only 2 percent worked part-time. Stay-at home dads in this study
appear to be a rare breed. We know that most mothers return to the workforce, and hence it is
reasonable to assume that the pay gap between men and women will widen as mothers return to
full-time employment, driving down average earnings for women.
Interestingly, motherhood is not the driving factor behind the wage gap among women working
full-time ten years after graduation.12 That is, mothers who were in the workforce full-time did
not earn less than other women also working full-time, controlling for other factors such as
occupation and major.
The Search for Solutions to the Pay Gap
First, it must be publicly recognized as a serious problem. Too often, both women and men
dismiss the pay gap as simply a matter of differing personal choices. While choices about college
major and jobs can make a difference, individuals cannot simply avoid the pay gap by making
different choices. Even women who make the same occupational choices as men will not end up
with the same earnings. If “too many” women make the same occupational choice, resulting in
job segregation, earnings can be expected to decline.
Women’s progress throughout the past 30 years attests to the possibility of change. Before the
Equal Pay Act of 1963, Title IX of the Education Amendments of 1972, Title VII of the Civil
Rights Act of 1964, and the Pregnancy Discrimination Act of 1978, employers could - and did refuse to hire women for occupations deemed “unsuitable,” fire women when they became
pregnant, openly pay differently based on sex, or limit women’s work schedules simply because
they were female. Schools could - and did - set quotas for the number of women admitted or
refuse women admission altogether. In the decades since these civil rights laws were enacted,
women have made remarkable progress in fields such as law, medicine, and business. Thirty
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I December 2010
I Joint Economic Committee
years ago the pay gap was attributed to the notion that women’s education and skills just didn’t
“measure up.” If that was ever the case, it certainly isn’t true now.
Unfortunately, women’s educational gains - ironically likely motivated in part by women’s
desire for economic security13 - have not translated into equal pay for women in the workforce.
In fact, while a college degree does absolutely increase women’s earnings, the pay gap remains
larger for college graduates than the population as a whole.14
AAUW’s research report provides strong evidence that sex discrimination still exists in the
workplace and that this discrimination is not disappearing on its own. It’s clear that existing laws
have failed to end the inequities that women face in the workplace. AAUW believes we must
take stronger steps to address this critical issue. While enactment of the Lilly Ledbetter Fair Pay
Act was a critical first step, restoring the ability of working women to have their day in court to
combat wage discrimination, additional legislation is needed to truly make real progress on pay
equity.
The Paycheck Fairness Act
AAUW applauds Congress and the Obama Administration for moving quickly to pass the
Ledbetter Fair Pay Act. However, the Ledbetter bill is only a down payment on the real change
needed to close the pay gap. The next critical step is for the Senate to pass the Paycheck Fairness
Act (S. 182/H.R. 12); the House already passed the measure in January 2009 by an even stronger
vote (256-163) than the Ledbetter bill (247-171).
Passing both bills is critical to the overall goal of achieving pay equity for all. The Lilly
Ledbetter Fair Pay Act amended Title VII of the Civil Rights Act of 1964 and righted the wrongs
done by the Supreme Court, regaining ground we’d lost. Ledbetter was a narrow fix that simply
returned legal practices and EEOC policies to what they were the day before the Ledbetter
decision was issued in 2007 - nothing more, nothing less. The Paycheck Fairness Act is a much
needed update of the 45-year-old Equal Pay Act, closing longstanding loopholes and
strengthening incentives to prevent pay discrimination. Together, these bills can help to create a
climate where wage discrimination is not tolerated, and give the administration the enforcement
tools it needs to make real progress on pay equity.
Background on the Equal Pay Act of 1963
This law requires that men and women be given equal pay for equal work in the same place of
business or establishment. The jobs do not have to be identical, but they must be substantially
equal. It is job content - not job titles - that determines whether jobs are substantially equal. Pay
differentials are permitted only when they are based on seniority, merit, quantity or quality of
production, or a factor other than sex. It is important to note that when correcting a pay
differential, no employee's pay may be reduced. Instead, the pay of the lower paid employee(s)
must be increased. While laudable in its goals, the Equal Pay Act of 1963 has never lived up to
its promise to provide “equal pay for equal work.”
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What will the Paycheck Fairness Act do?
The Paycheck Fairness Act is a comprehensive bill that strengthens the Equal Pay Act by taking
meaningful steps to create incentives for employers to follow the law, empower women to
negotiate for equal pay, and strengthen federal outreach and enforcement efforts. The bill would
also deter wage discrimination by strengthening penalties for equal pay violations, and by
prohibiting retaliation against workers who inquire about employers’ wage practices or disclose
their own wages. The Paycheck Fairness Act would:
•
Close a loophole in affirmative defenses for employers: The legislation clarifies
acceptable reasons for differences in pay by requiring employers to demonstrate that
wage gaps between men and women doing the same work have a business justification
and are truly a result of factors other than sex.
•
Fix the “Establishment” Requirement: The bill would clarify the establishment
provision under the Equal Pay Act, which would allow for reasonable comparisons
between employees within clearly defined geographical areas to determine fair wages.
This provision is based on a similar plan successfully used in the state of Illinois.
•
Prohibit Employer Retaliation: The legislation would deter wage discrimination by
prohibiting retaliation against workers who inquire about employers' wage practices or
disclose their own wages (NOTE: employees with access to colleagues’ wage
information in the course of their work, such as human resources employees, may still be
prohibited from sharing that information.) This non-retaliation provision would have
been particularly helpful to Lilly Ledbetter, because Goodyear prohibited employees
from discussing or sharing their wages. This policy delayed her discovery of the
discrimination against her by more than a decade.
•
Improve Equal Pay Remedies: The bill would deter wage discrimination by
strengthening penalties for equal pay violations by providing women with a fair option to
proceed in an opt-out class action suit under the Equal Pay Act, and allowing women to
receive punitive and compensatory damages for pay discrimination. The bill’s measured
approach levels the playing field by ensuring that women can obtain the same remedies
as those subject to discrimination on the basis of race or national origin.
•
Increase Training, Research and Education: The legislation would authorize
additional training for Equal Employment Opportunity Commission staff to better
identify and handle wage disputes. It would also aid in the efficient and effective
enforcement of federal anti-pay discrimination laws by requiring the EEOC to develop
regulations directing employers to collect wage data, reported by the race, sex, and
national origin of employees. The bill would also require the U.S. Department of Labor
to reinstate activities that promote equal pay, such as: directing educational programs,
providing technical assistance to employers, recognizing businesses that address the wage
gap, and conducting and promoting research about pay disparities between men and
women.
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•
Establish Salary Negotiation Skills Training: The bill would create a competitive grant
program to develop salary negotiation training for women and girls.
•
Improve Collection of Pay Information: The bill would also reinstate the Equal
Opportunity Survey, to enable targeting of the Labor Department's enforcement efforts
by requiring all federal contractors to submit data on employment practices such as
hiring^ promotions, terminations and pay. This survey was developed over two decades
and three presidential administrations, was first used in 2000, but was rescinded by the
Department of Labor in 2006.
The Paycheck Fairness Act maintains the protections currently provided to small businesses
under the Equal Pay Act, and updates its remedies and protections using familiar principles and
concepts from other civil rights laws. These new provisions are not onerous and are well-known
to employers, the legal community, and the courts. As a result, the legislation will enhance
women’s civil rights protections while simultaneously protecting the job-creating capacity of
small businesses. That’s why - in addition to AAUW and almost 300 other organizations groups such as Business and Professional Women/USA and the U.S. Women’s Chamber of
Commerce support the Paycheck Fairness Act.
Despite Progress, the Pay Gap Remains
Despite the progress that women have made, pay equity still remains out of reach and partly
unexplained. Even government economists say that a portion of the pay gap remains a mystery
even after adjusting for women’s life choices. Skeptics like to claim that there is no real pay gap
- that somehow it’s all a product of our imaginations. Worse, these critics prefer to blame
women for any pay disparities, saying that the pay gap is due to the "choices" that women make.
But excuses are excuses, and facts are facts.
Women are working harder than ever to balance the roles of work and family. They’ve
developed and supported successful legislation that has opened doors and helped to keep them in
the workforce while they raise their children. When women don’t earn equal pay, they’re not the
only ones to suffer - their families do, too. In these days when two incomes are needed to make
ends meet, and where female-headed households are so much more likely to be poor, it is
disturbing how maternal profiling is used to undercut women’s wages because of their
caregiving roles. It is also ironic and short sighted in a nation that needs women’s labor to be
competitive in a global economy.
One popular argument is that motherhood (and the choices it engenders) - rather than
discrimination - is the real culprit behind the pay gap. If that’s the case, than we have much
larger problems than the pay gap to deal with. If that’s true, than this country - including its
policy makers - needs to take a long, hard look at why the marketplace punishes women for
being mothers - or as AAUW’s research has showed, for simply their potential to be mothers while fatherhood carries no financial risk when it comes to wages and may in fact carry financial
benefits.
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Here’s the bottom line: There’s a pay gap that most economists agree can’t be explained away
completely by women’s choices - no matter how convenient, no matter how comfortable, no
matter how much easier it would be for the critics if they could do so. And we ignore it at our
peril.
AAUW plans to continue to take an active role in challenging the persistent inequity in women’s
paychecks, by unmasking the real root causes of the issue, relying on facts over inflated rhetoric,
and by urging the creation of more workplaces that are supportive of all employees with family
responsibilities, regardless of gender. We also, quite strongly, urge the Senate to join the House
and pass the Paycheck Fairness Act.
Collectively, women have demonstrated that they have the skills and the intelligence to do any
job. Women have also shown they can do these jobs while minding the home front and raising
the next generation. No one is disputing that women have made significant gains in education
and labor force participation. In fact, AAUW revels in them and our role in making them happen.
But our work is not done, and pay equity remains a pernicious problem with both daily and long
term consequences. It’s past time for women’s paychecks to catch up with our achievements.”
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Endnotes
1Jared Bernstein and Christina Romer. The Job Impact o f the American Recovery and Reinvestment Act,
Retrieved March 5,2009, from http://otrans.3cdn.net/ee40602f9a7d8172b8 ozm6bt5oi.pdf.
2 U.S. Census Bureau and the Bureau of Labor Statistics. (August 2008). Annual Demographic Survey.
Retrieved December 11, 2008, from http://pubdb3.census.gov/macro/032008/perinc/new05 000.htm.
3National Committee on Pay Equity. (September 2007). The Wage Gap Over Time: In Real Dollars,
Women See a Continuing Gap. Retrieved December 11, 2008, from http://www.pay-equity.org/infotime.html.
4 U.S. Census Bureau and the Bureau of Labor Statistics. (August 2008). Annual Demographic Survey.
Retrieved December 11,2008, from http://pubdb3.census.gov/macro/032008/perinc/new05_000.htm.
5 Institute for Women’s Policy Research. (July 2008). Improving Pay Equity Would Mean Great Gains
for Women. Retrieved December 11, 2008 from http://www.iwpr.org/pd^payequityrelease.pdf.
6AAUW Educational Foundation. (March 2003). Women at Work. Washington, DC.
7National Women’s Law Center. (2005). Tools of the Trade: Using the Law to Address Sex Segregation
in High School Career and Technical Education. Retrieved December 11, 2008, from
http://www.nwlc.org/pdf/NWLCToolsoftheTrade05.pdf.
8 See, for example, Blau, Francine and Lawrence Khan. The Gender Pay Gap: Going, Going ... But not
Gone. Paper presented at the Cornell University Inequality Symposium, October 2002.
9AAUW Educational Foundation. (2007). Behind the Pay Gap, by Catherine Hill and Judy Goldberg
Dey. Washington, DC.
10American Community Survey; http://factfinder.census.gov/servlet/STTable?_bm=y&geo_id=01000US&-qr_name=ACS_2005_EST_G00_S 1101 &-ds_jiame=ACS_2005_EST_G00_
11 AAUW Educational Foundation. (2007). Behind the Pay Gap, by Catherine Hill and Judy Goldberg
Dey. Washington, DC.
12 This is in keeping with research that shows that a “motherhood penalty” applies to most women but less
to women who maintain continuous work force attachment (Lundberg & Rose, 2000).
13DiPrete, Thomas A., & Claudia Buchmann. (2006, February). Gender-specific trends in the value of
education and the emerging gender gap in college completion. Demography, 43(1), 1-24.
14Authors calculation from tables produced by the U.S. Department of Labor, Bureau of Labor Statistics.
(2006). Median Usual Weekly Earnings, Employed Full Time, Wage and Salary Workers, 25 Years and
Older. Retrieved April 16, 2007 from http://www.bls.gov/cps/.
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I Joint Economic Committee
Testimony of Randy Albelda
Professor of Economics and
Senior Research Associate, Center for Social Policy
University of Massachusetts Boston
Boston, MA 02125
Randy.albelda@umb.edu
before the
United States Joint Economic Committee
Hearing on
“Equal Pay for Equal Work?
New Evidence on the Persistence of the Gender Pay Gap”
April 28,2009
“Madam Chairwoman and members of the committee: Thank you for this opportunity to testify
about the persistent wage gap between men and women. My name is Randy Albelda and I am a
professor of economics and senior research associate at the Center for Social Policy at the
University o f Massachusetts Boston. I am a labor economist and my expertise is on women’s
economic status.
While there has been progress is reducing the pay gap between men and women over the
last several decades, it is still the case that women, on average, make less than men.
While there are some differences in what men and women “bring” to the workplace that
influence levels of pay, these differences account for only a small part of the gender wage gap the difference in men’s and women’s pay. Further, the differences in skill levels and experience
have been narrowing over the last three decades and doing so at a faster pace than the wage gap
is narrowing. There are three enduring and intersecting reasons why women’s pay is less than
men's: workplace discrimination; occupational sorting; and family responsibilities.
The wage gap:
In the mid-1970s, the National Organization for Women issued “590” buttons, calling attention
to the fact that year-round, full-time women workers earned 59 cents to every man’s dollar.
Today we could replace those with a “78 f ’ buttons.1
This graph on the following page comes from the most recent US Census Bureau’s Income,
Poverty, and Health Insurance Coverage in the United States report. It provides a nice
illustration of the median annual earnings of year-round, full-time men and women workers from
1960 through 2007, adjusted for inflation. The most substantial gains were made in the 1980s,
with the wage ratio of women’s earnings to men’s earnings narrowing from .60 in 1980 to .72 in
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1990. In the 1990s, there was very little change in this ratio - moving from .72 in 1990 to .74 in
2000.
Figure 2.
Fetnale-to-Male Earnings Ratio and Median Earnings o f Full-Time, Year-Round Workers
15 fe a rs and Older by Sex: 1960 to 200?
Earnings in thousands (2007 dollars), ratio in percent
Recession
78 percent
■
Female-to-raaJe earnings ratio
«
Earnings o f men
,n"— p
-
,1..I L i
i
M
145,113
V
.................. I I
1965
1970
g|
135,102
1 I
................... 1 1 1 1 1 1
1975
::
... ..
'
1959
.-
....... »W
h
'''
1980
Earnings o f women
1 1 1 l .............................................I l 1 1 1 1 1
1985
1990
1995
2000
2007
Note: Data on earnings of full-time, year-round workers are not readily available before 1960. for Information on recessions, see Appendix A.
Source: U.S. Census Bureau, Current Population Survey, 1961 to 2008 Annual Social and Economic Supplements.
Different work, different pay? No. The gender pay gap persists even after taking into
account hours worked, skill levels and occupations.
As noted above, looking only at full-time year-round workers, women’s annual median earnings
are 78 percent of men’s. Similarly, the median weekly earnings of full-time wage and salary
women workers was 80 percent o f men’s in 2007.3
Women have somewhat less work time experience than men, which would explain some o f the
pay gap. However, it explains less and less of that gap over time and several studies have found
that each year o f men’s experience pays off at a higher rate than an additional year o f women’s
work experience. 4
Women workers bring higher educational levels to the workplace than do men5, which is one
reason why “human capital” endowments explain less of the pay gap now than they did in the
1980s.6 Still, female college graduates working full-time earned 80 percent less than male
college graduates just one year out of school in 2001.7
Women tend to work in different types o f jobs than do men. But, even when men and women
work in the same fields or even the same occupations, women typically earn less than men.
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The starting salaries for women college graduates were $1,443 less than they were for
men in the same fields.8
Across the occupational landscape, women make less than men. The table below depicts
the wage gap (using median usual weekly earnings of full-time wage and salary workers)
for some detailed occupations. Of the over 100 detailed occupations with median
earnings listed, there are only six in which women’s earnings are higher than those of
men.9
The Gender Wage Gap in Selected Detailed Occupations, 2006
Managerial Occupations:
Chief executives
.72
Human resource specialists.
.81
Professional Occupations
Lawyers
.70
Elementary and middle school teachers
.90
Service Occupations
Security guards
.84
Home health care aides
.89
Sales and Office Occupations
Retail salesperson
.68
Secretaries/administrative asst.
1.04
Construction occupations
.86
Production and transportation Occupations
Electronic assemblers
.76
Bus drivers
.80
Source: Table 18 of U.S. Department of Labor, U.S. Bureau of Labor Statistics, Women
in the Labor Force: A Databook (2008 Edition).
• Francine Blau and Lawrence Kahn show that in 2004 after controlling for education,
experience, occupation and industry, women earned 83.5 percent of what men did,
compared to 81.6 percent without any of those adjustments. That means these factors
explain less than 2 percentage points (10 percent) of the entire wage gap between men and
women, leaving most of it unexplained by measurable differences between men’s and
women’s attributes.10
Economists have explored the gender pay gap for many decades and produced hundreds (if not
1000s) of articles and reports to explain the reasons for the gender pay gap. No matter how
sophisticated and complex their models, they always find that some portion of the wage gap is
unexplained by the sets of variables for which they can measure differences between men’s and
women’s education levels, work experiences, ages, occupation or industry in which they work,
or region of the country they reside. Because the wage differences cannot be explained by any of
the differences in workers’ traits, this unexplained portion of the wage gap is attributed to gender
discrimination.
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• A recent meta-regression analysis that compiled the results of 49 econometric studies of
the gender wage gap over the last decade found that on average, there was still a
substantial gap - women earned 70 percent of what men did, after adjusting for all the
various factors that help explain wage difference.11
• In a forthcoming study of college professors in one specific college of a large public
university, researchers controlled for years experience, mobility, teaching and research
productivity, and department and found that even in the identical job in the same
institution women made three percent less than men.12
Progress toward pay equity has stalled over the last decade.
• The unexplained portion of gender gap (the part attributable to discrimination) got
considerably smaller in the 1980s and hardly fell at all in the 1990s.13
There are three intersecting reasons why women’s pay is less than men’s: workplace
discrimination; occupational sorting; and family responsibilities.
• Lilly Ledbetter’s experience reminds us that workplace discrimination still exists.
Routinely women are not hired at all, hired at lower wages and not promoted over
equally qualified men. This shows up in economists’ studies as the part of the earnings
gaps that can’t be attributed to anything else. In addition, using experimental
approaches, economists find considerable evidence of hiring discrimination as well.14
•
Women are in different occupations than men. Men are much more likely to be in
construction and manufacturing jobs which pay more than female dominated jobs with
comparable skill levels such as administrative assistants and retail salespersons.15 While
about one-third of all women are in professional and managerial jobs, these too are often
sex segregated, with women predominating in teaching, nursing and social work jobs and
men predominating in architecture, engineering and computer occupations. Finally,
women predominate in both high and low paying jobs in the “care sector” - the industries
which educate our children, provide us with health services, and take care of young
children, disabled adults and the elderly. There is a care work wage penalty. Careful
research has shown that care workers, in part because they compete with unpaid workers
at home, are not rewarded commensurately with their skills and experience. This sector
is large. About 20 percent of all workers work in the care sector and women comprise 75
percent of all workers.17
•
Family responsibilities squeeze women’s work time and preclude them from taking and
keeping jobs that make few or no accommodations fo r these responsibilities. Jobs that
require long hours, often pay well and provide a strong set of employer benefits, but
employers also usually assume the workers in those jobs are unencumbered by household
and family responsibilities. This “ideal” worker can (and often does) work overtime or
just about any time an employer wants.18 Workers with family responsibilities do not
have that flexibility. Regardless of their skill levels, these workers often must work fewer
hours or trade off wages for more time flexibility. Research clearly demonstrates a
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mothers’ wage penalty. Mothers’ earn less than women with the same sets of skills and
are rewarded less for experience than are men or women who are not mothers. Some of
this is a result of time demands and less job flexibility, but some is attributable to
discrimination against workers with family responsibilities.19
The recession makes addressing this issue especially important because women’s earnings
are a vital, if not main component, of family well-being.
One third of all households are headed by women. Of these households, one-quarter are
families with children.20 Women are almost always the only support of these
households.
One half of households have married couples.21 If these households, 64 percent of wives
are employed, compared to 48 percent in 1970. Further, wives’ earnings comprise 35
percent of family income, up from 27 percent in 1970 22
In this recession, more men have lost jobs than women have, since men - so far —are
disproportionately found in the hardest hit sectors.23 As a result, even more households
are more dependent on women’s earnings. Unequal pay hurts these households.
The stimulus package will help both men and women, but differently.
o Increased funds for physical infrastructure, improved medical record keeping, and
green energy investments will likely create many more jobs for men than women.
Assuring access to these jobs and trade apprenticeship programs would be useful
for women’s employment in these male-dominated and often well-paying jobs.
o
Increased funding to the states, especially for health care and education, will help
reduce the number of layoffs for more women, since they are more heavily
employed in these sectors than are men. However, state budget deficits are deep
and even with stimulus funds there will be large cuts to the care sector, which will
increase women’s unemployment. The cuts will also put more pressure on
women’s unpaid work time, as their families lose needed care.
Reducing the pay gap
There are several things that would boost women’s wages and reduce the pay gap.
Addressing Workplace Discrimination
•
Ensure that our current anti-discrimination laws are enforced.
•
Pass the Paycheck Fairness Act. This will strengthen penalties for discrimination and
prohibit employer retaliation for workers who inquiry about wage practices.
Pass the Employee Free Choice Act. Unions boost women’s wages and improve the
likelihood they will have health insurance at work.24 Unions also provide workers
structured mechanisms to pursue employer discrimination claims.
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Addressing Occupational Sorting
•
Increase the minimum wage since women predominate in low-wage jobs.
•
Support improved wages for care workers. Care work is heavily supported by federal,
state and local government funds. This is because care work has many positive spillover
effects, making it a vital public good. Government funds for child care and elder care
can assure that workers in these fields are compensated appropriately and have
opportunities for professional development.
•
Target stimulus money to assure that women are included in physical infrastructure
projects.
Addressing Family Responsibility Discrimination
•
Make sure that current laws that protect workers with caregiving responsibilities, such as
the Family and Medical Leave Act, are enforced.
•
Extend the Family and Medical Leave Act to cover more workers.
•
Support the Family Leave Insurance Act o f 2009 which would provide workers with 12
weeks of paid family and medical leave.
•
Develop legislation that encourages employers to negotiate with employees over flexible
work arrangements.
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Endnotes
1In 2007, year-round, full-time women earners made $35,102 while men earned $45,113. Carmen
DeNavas-Walt, Bernadette D. Proctor, and Jessica C. Smith, U.S. Census Bureau, Current Population
Reports, P60-235, Income, Poverty, and Health Insurance Coverage in the United States: 2007, U.S.
Government Printing Office, Washington, DC, 2008; Table 1.
2 Ibid, Table A-2.
3U.S. Department of Labor, U.S. Bureau of Labor Statistics, Highlights of Women’s Earnings in 2007,
Report 1008, October 2008, Chart 1 (accessed 4-23-09 at http://www.bls.gov/cps/cpswom2007.pdf>.
4 Lalith Munasinghe, Tania Reif and Alice Henriques, “Gender gap in wage returns to job tenure and
experience. Labour Economics, 2008: 1296-1916. This study looked at US men’s and women job
experience in the early part of their careers with longitudinal data (National Longitudinal Survey of
Youth) for the years 1979-1994 (ages 14-22 in 1979 (making the sample between 29-37 years old in
1994). They found men with high school degrees or less worked an average of 6.7 years compared to
women’s 5.9 years. For those with more than a high school degree, the average amount of work
experience was 7.8 years for men and 7.3 years for women. Men worked, on average, about 6 more
hours per week than did women. Men accrued 15 percent higher wage growth from an additional year of
experience than women. Similar results can be found in Audrey Light and Manuelita Ureta, “EarlyCareer Work Experience and Gender Wage Differentials” Journal of Labor Economics 1995,13 (1) and
Pamela Loprest, “Gender Differences in Wage Growth and Job Mobility” American Economic Review
1992, 82 (5).
5 In 2007, 35 percent of all women ages 25-64 in the labor force had a college degree compared to 33
percent of men. Conversely, 42 percent of men ages 25-64 in the labor force had a high school diploma
or less education compared to 35 percent of women. Calculated by author from data provided in U.S.
Department of Labor, U.S. Bureau of Labor Statistics, Women in the Labor Force: A Databook (2008
Edition) Table 8, (accessed 4-23-09 at http://www.bls.gov/cps/wlf-table8-2008.pdf).
6Francine Blau and Lawrence Kahn, “The US Gender Pay Gap in the 1990s: Slowing Convergence,”
Industrial and Labor Relations Review, 2006, 60(l):45-66.
7Judy Goldberg Dey and Catherine Hill, Behind the Pay Gap, Washington DC: American Association of
University Women Educational Foundation, 2007.
8Judith McDonald and Robert Thornton, “Do New Male and Female College Graduates Receive Unequal
Pay?” Journal of Human Resources, 2007, 52(1): 32-48.
9 U.S. Department o f Labor, U.S. Bureau of Labor Statistics, Women in the Labor Force: A Databook
(2008 Edition) Table 18, (accessed 4-23-09 at http://www.bls.gov/cps/wlf-table8-2008.pdf).
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I December 2010
I Joint Economic Committee
10The authors use Current Population Survey data and look at average hourly wages for full-time
workers. Francine Blau and Lawrence Kahn, “The Gender Pay Gap” The Economists’ Voice, Berkeley
Electronic Press, 2007: 1-6.
11Stephen Stanley and T.D. Jarrell, “Declining Bias and Gender Wage Discrimination? A Meta
Regression Analysis. Journal of Human Resources, 2004, 36(3): 828-838.
12Melissa Binder et al. “Gender Pay Differences for the Same Work: Evidence from a United States
Public University” forthcoming, Feminist Economics.
13Francine Blau and Lawrence Kahn, “The US Gender Pay Gap in the 1990s: Slowing Convergence,”
Industrial and Labor Relations Review, 2006, 60(l):45-66.
14David Neumark, using equally experienced male and female “pseudo” applicants, found high-priced
restaurants were much more likely to both interview or offer jobs to men (“Sex Discrimination in
Restaurant Hiring: An Audit Study,” Quarterly Journal of Economics, 1996, 111(3): 915-41). Claudia
Golden and Cecilia Rouse found that the probability that women would advance and be hired by
symphony orchestras was higher when auditions were “blind” (i.e. the gender of the applicant auditioning
was unknown) than when they were not (“Orchestrating Impartiality: The Impact of ‘Blind’ Auditions on
Female Musicians,” American Economic Review, 2000, 90(4): 715-41).
15 In 2007, the median weekly salary of someone in construction occupations was $619 but as a secretary
was $583; for a production occupations the week median salary was $559 compared to $494 for a retail
salesperson. U.S. Department of Labor, U.S. Bureau of Labor Statistics, Women in the Labor Force: A
Databook (2008 Edition) Table 18 (accessed 4-23-09 at http://www.bls.gov/cps/wlf-table8-2008.pdf).
16Paula England, Michelle Budig and Nancy Folbre, “Wages of Virtue: The Relative Pay of Care Work”
Social Problems 2002;49(4):455-474; and Nancy Folbre, The Invisible Heart: Economics and Family
Values, New York: New Press, 2001.
17Randy Albelda, Mignon Duffy and Nancy Folbre, “Taking Care: The Costs and Contributions of Care
Work in Massachusetts” University of Massachusetts, forthcoming.
18 See Randy Albelda, Robert Drago and Steven Shulman, Unlevel Playing Fields: Understanding Wage
Inequality and Discrimination, Boston, MA: Economics Affairs Bureau 2004, Chapter 7; Joan Williams,
Unbending Gender: Why Family and Work Conflict and What to Do About It. New York: Oxford
University Press, 2001; Robert Drago, Striking a Balance: Work, Family, Life, Boston, MA: Dollars and
Sense, 2007.
19Wendy Single-Rushton and Jane Waldfogel, “Motherhood and Women’s Earnings in Anglo-American,
Continental European, and Nordic Countries” Feminist Economics 2007,13(2): 55-91; Joni Hersh and
Leslie Stratton., “Housework and Wages” Journal of Human Resources 2002, 37(1):217-229; and
Deboarah Anderson, Melissa Binder and Kate Krause, “Experience, Heterogeneity, Work Effort and
Work-Schedule Flexibility” Industrial and Labor Relations Review, 2003, 56(2): 273-294; and Michelle
Budig and Paula England, “The Wage Penalty for Motherhood” American Sociological Review, 2001,
66(2), 204-225
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| December 2010
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20U.S. Census Bureau, America’s Families and Living Arrangements: 2007, Tables FI and FM-1,
(accessed 2-13-09 from http://www.census.gov/population/socdemo/hh-fam/cps2007/tabFl-all.xls and
http://www.census.gov/population/socdemo/hh-fam/fml.xls.
21 Ibid.
22U.S. Department of Labor, U.S. Bureau of Labor Statistics, Women in the Labor Force: A Databook
(2008 Edition), Tables 23 and 24 (accessed 4-23-09 at http://www.bls.gov/cps/wlf-table8-2008.pdf).
23 Heather Boushey, Equal Payfor Breadwinners, Washington, DC: Center for American Progress, 2009.
24 John Schmitt Unions and Upward Mobilityfor Women Workers, Washington DC: Center for Economic
and Policy Research, 2008.
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Prepared by the Majority Staff of the Joint Economic Committee
December 2010
Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
Testimony of Andrew Sherrill
Director
Education, Workforce, and Income Security Issues
Government Accountability Office
before the
United States Joint Economic Committee
Hearing on
“Equal Pay for Equal Work?
New Evidence on the Persistence of the Gender Pay Gap”
April 28, 2009
WOMEN'S PAY
Converging Characteristics of Men and Women in the Federal Workforce Help Explain
the Narrowing Pay Gap (GAQ-09-621T)
GAO Highlights
What GAO Found
Why GAO Did This Study
The gender pay gap—the difference between men’s and
women’s average salaries—declined significantly in the
federal workforce between 1988 and 2007. Specifically, the
gap declined from 28 cents on the dollar in 1988 to 19 cents
in 1998 and further to 11 cents in 2007. For the 3 years we
examined, all but about 7 cents o f the gap can be explained
by differences in measurable factors such as the occupations
of men and women and, to a lesser extent, other factors such
as education levels and years of federal experience. The pay
gap narrowed as men and women in the federal workforce
increasingly shared similar characteristics in terms of the
jobs they held, their educational attainment, and their levels
of experience. For example, the professional, administrative,
and clerical occupations—which accounted for 68 percent of
all federal jobs in 2007—have become more integrated by
gender since 1988. Some or all of the remaining 7 cent gap
might be explained by factors for which we lacked data or
are difficult to measure, such as work experience outside the
federal government. Finally, it is important to note that this
analysis neither confirms nor refutes the presence of
discriminatory practices.
Previous research has found that,
despite improvements over time,
women generally earned less
than men in both the general and
federal workforces, even after
controlling for factors that might
explain differences in pay. To
determine the extent to which the
pay gap exists in the federal
workforce, GAO addressed the
following question: To what
extent has the pay gap between
men and women in the federal
workforce changed over the past
20 years and what factors
account for the gap? This
testimony is based on a report
that GAO is releasing today
(GAO-Q9-279).
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Pay gap between men and women (in cents)
GAO Highlights (continued)
30
Why GAO Did This Study
To answer this question, GAO used
data from the Office of Personnel
Management’s (OPM) Central
Personnel Data File (CPDF)— a
database that contains salary and
employment data for the majority
o f employees in the executive
branch. GAO used these data to
analyze (1) “snapshots” of the
workforce as a whole at three
points in time (1988, 1998, and
2007) to show changes over a 20year period, and (2) the group, or
cohort, of employees who began
their federal careers in 1988 to
track their pay over a 20-year
period and examine the effects of
breaks in service and use of unpaid
leave. GAO is not making any
recommendations.
OPM and the Equal Employment
Opportunity Commission reviewed
the report on which this statement
is based. They generally agreed
with our methods and findings and
provided technical comments that
we incorporated as appropriate.
Unexplained pay gap
Part of the pay gap resulting from differences in
other measurable characteristics
Part of the pay gap resulting from differences in
experience levels
Part of the pay gap resulting from differences in
education levels
Part of the pay gap resulting from differences in
occupations
1988
1998
2007
Year
Source: GAO analysis of CPDF data.
GAO’s case study analysis of workers who entered the
workforce in 1988 found that the pay gap between men
and women in this group grew overall from 22 to 25 cents
on the dollar between 1988 and 2007. As with the overall
federal workforce, differences between men and women
that can affect pay explained a significant portion of the
pay gap over the 20-year period. In particular, differences
in occupations explained from 11 to 19 cents of the gap
over this period. In contrast, differences in breaks in
federal service and use of unpaid leave explained little of
the pay gap. However, the results of this analysis are not
necessarily representative of other cohorts.
“Chair Maloney and Members of the Committee:
View G A 0 0 9 -6 2 IT or key components.
For more information, contact Andrew Sherrill at
(202) 512-7215 or shemlla@gao.gov.
I
am pleased to be here today to discuss the gender
in the federal workforce. Previous research shows that
despite improvements over time, a pay gap remains
between men and women in both the U.S. workforce as a
whole and within the federal government. For example, in
2003, GAO found that women in the general workforce earned, on average, 80 cents
for every dollar earned by men in 2000 when differences in work patterns, industry, occupation,
marital status, and other factors were taken into account.1 Our prior work has also made
recommendations to strengthen federal agencies’ enforcement of laws addressing gender pay
disparities in the private sector and among federal contractors.2 My statement is based on our
report that is being released today, titled Women’s Pay: Gender Pay Gap in the Federal
Workforce Narrows as Differences in Occupation, Education, and Experience Diminish. 3 To
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I December 2010
I Joint Economic Committee
prepare the report, we used data from the Office of Personnel Management’s (OPM) Central
Personnel Data File (CPDF)—a database that contains salary and employment-related
information for the majority of civilian employees in the executive branch.4 We used CPDF data
to analyze (1) “snapshots” of the federal workforce in 1988, 1998, and 2007 to show changes in
the workforce as a whole over a 20-year period; and (2) the cohort (or group) of employees who
entered the federal workforce in 1988 to track differences in pay between men and women and
the effects of breaks in service and unpaid leave over a 20-year period. The report includes a
detailed description of our scope and methodology. We conducted our work in accordance with
GAO’s Quality Assurance Framework.
My statement today focuses on the following question; To what extent has the pay gap between
men and women in the federal workforce changed over the past 20 years and what factors
account for the gap?
In summary, we found that the pay gap—the difference between men’s and women’s average
pay—in the federal workforce declined from 28 cents on the dollar in 1988 to 19 cents in 1998
and further to 11 cents in 2007. For each of the 3 years we examined, all but about 7 cents of the
gap could be explained by differences in measurable factors between men and women, including
their occupations, and, to a lesser extent, their educational levels and years of federal experience.
5 The gap diminished over time largely because men and women in the federal workforce are
more alike in these characteristics than they were in past years. For the cohort of employees who
entered in 1988, we found that their pay gap grew from 22 to 25 cents on the dollar by the end of
the 20-year period. Again, differences between men’s and women’s characteristics that can affect
pay, especially occupation, explained a significant portion of the pay gap. Specifically,
differences in the occupations held by men and women in this group explained between 11 and
19 cents of the pay gap over the 20-year period. On the other hand, differences in breaks in
federal service and use of unpaid leave explained little of the pay gap. For both analyses, factors
for which we lacked data or are difficult to measure, such as experience outside the federal
government, may account for some or all of the remaining pay gap that we could not explain,
and this analysis neither confirms nor refutes the presence of discriminatory practices.
Background
The federal government has experienced significant changes over the past 20 years, particularly
in the people it employs and the type of work its employees perform. Since 1988, the federal
workforce has become increasingly concentrated in the professional and administrative fields,
which typically require a college education. Conversely, the past 20 years have seen significant
decreases in clerical and blue-collar occupations. While we are not certain what accounts for the
decline in these occupations, possible reasons include the phasing out of many defense-related
jobs after the end of the Cold War, increased use of automation, and contracting out to the
private sector. Overall, the federal workforce has more education and experience than it did 20
years ago. The proportion of federal employees with a bachelor’s degree or higher increased
from 33 percent in 1988 to 44 percent in 2007. Similarly, the average years of federal service
increased from 13 to 15 years over this period, and the proportion of employees with over 20
years of experience increased from 21 to 34 percent.
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Joint Economic Committee
Converging Characteristics Explain Substantial Decline in the Federal Pay Gap between
1988 and 2007
Before accounting for differences in measurable factors, we found that the pay gap between men
and women in the federal workforce declined significantly between 1988 and 2007. Specifically,
for every dollar earned by men in 1988, women earned 28 cents less. This gap closed to 19 cents
by 1998 and closed further to 11 cents by 2007. Using a statistical model we developed, we were
able to estimate the extent to which different measurable factors contributed to the pay gap.
Besides gender, these measurable factors included work characteristics, such as occupational
category, agency, and state; worker characteristics, such as education level, years of federal
experience, bargaining unit status, part-time work status, and veteran status; and demographic
characteristics such as age, race and ethnicity, and disability status. Our statistical results show
that differences in measurable factors account for much of the gap in the years we examined. As
shown in figure 1, the individual factors that contributed most to the pay gap were differences
between men and women in the occupations they held, their educational levels, and their years of
federal experience.
Figure 1: Federal Workers: Proportion of the Pay Gap Explained by Differences in
Measurable Factors 'between Men and Women and Remaining Unexplained Gap
Pay gap between men and women (in cents)
30
25
20
IS
10
5
0
1988
1998
2007
Year
iitfeiences in other measurable characteristics
" - i
. i . s-
r ~ I. . j<
<-
i ;
'
lifferences in experience levels
„»[•■ differences in education levels
j Sting from differences in occupations
While occupation, education, and federal experience accounted for much of the pay gap, the
convergence between men and women with respect to these factors largely explains why the gap
diminished over time.
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I December 2010
I Joint Economic Committee
• Occupation: We found that the pay gap decreased in part because clerical, professional,
and administrative occupational categories—which together accounted for 68 percent of
federal jobs in 2007—became more integrated by gender between 1988 and 2007. In
particular, changes in the government’s clerical workforce explain a large reduction in
the pay gap. In 1988, the clerical workforce—which accounted for 38 percent of all
female federal workers—was among the lowest paid. From 1988 to 2007, the clerical
workforce shrank in size by about 61 percent, and also became more integrated—i.e., the
proportion of women decreased from 85 percent to 69 percent. In addition, the proportion
of women in professional positions rose from 30 percent to 43 percent, and those in
administrative positions rose from 38 percent to 45 percent.
• Education: The pay gap also decreased as men and women in the federal workforce
became increasingly similar in their levels of education. In 1988, only 23 percent of
women held a bachelor’s degree or higher compared with 40 percent of men. By 2007,41
percent of women held a bachelor’s degree or higher, compared with 47 percent of men.
• Federal experience: Finally, men and women in the federal government became
increasingly similar in their levels of experience. On average, men in 1988 had 14.4 years
of federal experience, compared with 10.8 for women—nearly a 4-year difference. By
2007, women had slightly more experience on average with 15.5 years of federal
experience compared with 15.2 for men.
In each of the 3 years we examined, our model could not account for about 7 cents of the pay
gap. While we cannot be sure what accounts for this portion of the gap, it is possible that other
factors for which we lacked data or are difficult to measure, such as work experience outside the
federal government, could account for some of the unexplained gap. In addition, it is important
to note that this analysis neither confirms nor refutes the presence of discriminatory practices.
The Pay Gap for Employees Who Joined the Federal Workforce in 1988 Grew Overall, but
Breaks in Service and Unpaid Leave Contributed Little to the Gap
The gender pay gap for workers who entered the federal workforce in 1988 grew between 1988
and 2007. Specifically, it grew from 22 cents in 1988 to a maximum of 28 cents in 1993 through
1996 and then declined to 25 cents in 2007. As with our analysis of the workforce, differences in
measurable factors—especially in occupation—explained much of the pay gap in each year. For
example, occupational differences explained between 11 and 19 cents of the gap over this period,
due in part to more women than men holding clerical jobs, which were among the lowest paid in
the federal workforce. The unexplained portion of the pay gap also grew over time, increasing
from 2 cents in 1988 to 9 cents in 2007, as shown in figure 2. However, other factors not
captured by our data could account for some of the unexplained pay gap.
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use of the CPDF data to be appropriate. EEOC stated that our study has a solid research design
and modeling analysis and will serve as an important source of information to the federal sector.
They provided suggestions for clarification of our analyses and technical comments, which we
incorporated as appropriate.
Madam Chair, this concludes my remarks. I would be happy to answer any questions you or
other members of the committee may have.”
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Endnotes
1GAO, Women’s Earnings: Work Patterns Partially Explain Difference between Men’s and
Women’s Earnings, GAO-04-35 (Washington, D.C.: Oct. 31,2003).
2 GAO, Women’s Earnings: Federal Agencies Should Better Monitor Their Performance in
Enforcing Anti-Discrimination Laws, GAO-08-799 (Washington, D.C.: Aug. 11, 2008).
3 GAO, Women’s Earnings: 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).
4 The CPDF does not include information for certain executive branch agencies, such as the
intelligence services, agencies in the judicial branch, and most agencies in the legislative
branch. The CPDF also does not include the U.S. Postal Service or members of the armed
forces.
5 In this report, measurable factors are those factors for which we have CPDF data.
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Prepared by the Majority Staff of the Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
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.
GAO Contact and Acknowledgments
For further information, please contact Andrew Sherrill at (202) 512-7215 or Sherrilla@gao.gov.
Contacts for our Offices of Congressional Relations and Public Affairs can be found on the last
page of this statement. Also contributing to this statement were Michele Grgich, Assistant
Director; Erin Godtland; and Daniel R. Concepcion, Education, Workforce, and Income
Security; Benjamin Bolitzer, Douglas Sloane, Shana Wallace, and Gregory H. Wilmoth, Applied
Research and Methods; Ronald Fecso, Chief Statistician; Belva Martin, George Stalcup, and
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Testimony of Andrew Sherrill
Director
Education, Workforce, and Income Security Issues
Government Accountability Office
before the
United States Joint Economic Committee
Hearing on
“New Evidence on the Gender Pay Gap for Women and Mothers in Management”
September 28,2010
WOMEN IN MANAGEMENT
Female Managers’ Representation, Characteristics, and Pay (GAO-10-1064T)
“Chair Maloney and Members of the Committee:
I am pleased to be here today as you examine issues related to women in management. Although
women’s representation across the general workforce is growing, there remains a need for
information about the challenges women face in advancing their careers. In 2001, using 1995 and
2000 data from the Current Population Survey, we found women were less represented in
management than in the overall workforce in 4 of the 10 industries reviewed. We also found
differences in the characteristics and pay of male and female managers, which we explored using
statistical modeling techniques. To respond to your request that we update this information to
2007, we addressed the following three questions: (1) What is the representation of women in
management positions compared to their representation in nonmanagement positions by
industry? (2) What are the key characteristics of women and men in management positions by
industry? and (3) What is the difference in pay between women and men in full-time
management positions by industry? My remarks today are based on our report, released at this
hearing, Women in Management: Analysis o f Female Managers ’ Representation,
Characteristics, and Pay.
To examine these questions, we analyzed data from the U.S. Census Bureau’s American
Community Survey (ACS) for the years 2000 through 2007.3 We selected ACS rather than the
Current Population Survey due to the greater number of observations in ACS. We analyzed
managers across all of the broad industry categori es used in ACS, representing the entire
workforce, except for the agriculture and mining sectors, individuals living in group quarters,
and those who were not living in a U.S. state or the
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Joint Economic Committee
District of Columbia.4 We defined “managers” as all individuals classified under the “manager
occupation” category in ACS, which includes a wide range of more than 1,000 job titles. In our
multivariate analysis of the differences in pay between male and female managers working full
time and year round by industry,5 we used annual earnings as our dependent variable, adjusting
for certain characteristics that were available in the dataset and are commonly used to estimate
adjusted pay differences. These include age, hours worked beyond full time, race and ethnicity,
state, veteran status, education level, citizenship, marital status, and presence of children in the
household.6 We assessed the reliability of the ACS generally and of critical data elements and
determined that they were sufficiently reliable for our analyses. We conducted our work from
February 2010 to September 2010 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.
In summary, when looking across all industries combined from 2000 to 2007, female managers’
representation and differences between female and male managers’ characteristics remained
largely similar. However, differences narrowed substantially in level of education and slightly in
payIn 2007, women comprised an estimated 40 percent of managers and 49 percent of
nonmanagers on average for the 13 industry sectors we analyzed—industries that
comprised almost all of the nation’s workforce-—compared to 39 percent of managers and
49 percent of nonmanagers in 2000. In all but three industry sectors women were less
than proportionately represented in management positions than in nonmanagement
positions in 2007. Women were more than proportionately represented in management
positions in construction and public administration, and there was no statistically
significant difference between women’s representation in management and
nonmanagement positions for the transportation and utilities sector (see figure 1). On
average for the 13 industry sectors, an estimated 14 percent of managers in 2007 were
mothers—with their own children under age 18 living in the household—compared to 17
percent of nonmanagers.
Prepared by the Majority Staff of the Joint Economic Committee
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
The estimated difference in pay between female managers working M l time and male managers
working foil time narrowed slightly between 2000 and 2007 after adjusting for selected factors
that were available and are commonly used in examining salary levels, such as age, hours
worked beyond full time, and education (see figure 3). When looking at all industry sectors
together and adjusting for these factors, we estimated that female managers earned 81 cents for
every dollar earned by male managers in 2007, compared to 79 cents in 2000. The estimated
adjusted pay difference varied by industry sector, with female managers’ earnings ranging from
78 cents to 87 cents for every dollar earned by male managers in 2007, depending on the industry
sector.
,
Figure 3: Estimated Pay Differences for Full-Time Managers. 2000-2007
Full-time
manager pay
{in dollars)
All
managers
Managers
with children®
Managers
without children*
Male
0.50
//
0 .0
mmmmmmmmmmmmmmmmmmmmmm
mm m m mm m m m m m m m m m m m m m m m m m
mmmmmmmmmmmmmmmmmmmmmmm
00 01 02 03 04 05 06 07
00 Of 02 03 04 05 OS 07
00 01 02 03 04 05 06 07
Year
Year
Year
Source: GAO analysts of American Community Survey data.
Note: The narrowing of the gap between 2000 and 2007 for all managers and managers without
children in the household was statistically significant at the 95 percent confidence level. For 2001 2007, tie margins of error for pay gaps differed for any single year by no greater than plus or minus 2
cents.
•Children refer to children under age 18 living in a household with a manager.
bFor this analysis, we adjusted for age, hours worked beyond full time, race and ethnicity, state,
veteran status, education, industry sector, citizenship, marital status, and presence of children in the
household. We adjusted for industry sector to control for the possibility that pay differences could
occur because female managers tended to be employed in industries that had lower rates of pay.
However, we acknowledge that the distribution of female managers by industry sector itself might
reflect some level of discrimination associated with hiring, promotion, or other employer practices. For
the subsequent industry-specific analyses, we adjusted for the same variables, except we excluded
industry sector.
Our analysis is descriptive in nature and neither confirms nor refutes the presence of
discriminatory practices. Some of the unexplained differences in pay seen here could be
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A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
explained by factors for which we lacked data or are difficult to measure, such as level of
managerial responsibility, field of study, years of experience, or discriminatory practices, all of
which are cited in the research literature as affecting earnings. More detailed information on the
characteristics of women in management in specific industries could help policymakers to
identify possible actions to help women advance to management positions. For example, starting
in 2009, the ACS included a question on field of study, a variable recognized as important in
examining differences in pay and advancement. Improvements to the type of data available, such
as this one, could help researchers to better understand the determinants of salary and
advancement.
The Departments of Commerce and Labor provided technical comments on a draft of our report,
which we incorporated as appropriate.
Madam Chair, this concludes my prepared remarks. I would be happy to answer any questions
that you or the other members of the committee may have.”
For further information on this testimony, please contact Andrew Sherrill 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 statement. Individuals making key contributions to this
testimony include Gretta Goodwin (Assistant Director), Kate Blumenreich, Lindsay Read, James
Bennett, Susan Bernstein, Ben Bolitzer, Russ Burnett, Heather Hahn, Anna Maria Ortiz, and
Shana Wallace. Also contributing to this work were Ron Fecso, James Rebbe, and Patrina Clark.
Andrew Sherrill,
Director Education, Workforce, and Income Security Issues
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Endnotes
GAO, Women in Management: Analysis o f Selected Data from the Current Population Survey, GAO-02156 (Washington, D.C.: Oct. 23, 2001).
2
GAO, Women in Management: Analysis o f Female Managers ’Representation, Characteristics, and Pay,
GAO-10-892R (Washington, D.C.: Sept. 20, 2010).
3
We reported on the years 2000 through 2007 to avoid concerns about the role of the recession that began
in December, 2007 and to avoid any complications to the analysis due to the change of survey questions
in the data set we used that were made in 2008. The ACS became nationally representative in 2000, and
thus was not available for the analysis we did in the 2001 report on women in management.
4
We excluded agriculture because, according to the Bureau of Labor Statistics, farmers may have other
sources of income, such as from federal subsidies, which may not be reported in ACS as income and
would complicate our analysis on pay differentials. We excluded mining because we found a relatively
limited number of observations in the mining industry. According to ACS, group quarters is a place
where people live or stay, in a group living arrangement that is owned or managed by an entity or
organization providing housing and/or services for the residents. Examples include college residence
halls, nursing homes, group homes, military barracks, correctional facilities, and mental hospitals.
Our definition of individuals working full time were those who, over the past 12 months, reported
usually working greater than or equal to 35 hours per week and 50 weeks per year, and reported positive
wages earned.
6
.
When we looked at all industries together, we also adjusted for industry sector.
?Our definition of individuals working part-time included those who were not working full time, but
reported usually working some hours per week, weeks worked, and wages earned, all over the past 12
months.
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A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
Testimony of Ilene H. Lang
President & Chief Executive Officer.
Catalyst, Inc.
before the
United States Joint Economic Committee
Hearing on
“New Evidence on the Gender Pay Gap for Women and Mothers in Management”
September 28,2010
Targeting Inequity: The Gender Gap in U.S. Corporate Leadership
INTRODUCTION
“He has monopolized nearly all the profitable employments, and from those she is permitted to
follow, she receives but a scanty remuneration. - The Declaration of Sentiments, Seneca Falls,
NY, July 20, 1848
Generations have passed since this nation’s first women’s summit issued the Declaration of
Sentiments, yet stark gender gaps in business leadership and pay persist. The latest data reveals
leadership gaps across all Fortune 500 industries and a glacial rate of progress for women in
business. Women constitute nearly half the total work force,1 earn 57 percent of Bachelor’s
degrees, 60 percent of Master’s degrees,2 and control or influence 73 percent of the consumer
decisions3 in America. Yet among Fortune 500 companies, women make up less than three
percent of CEOs4 and hold roughly 15 percent of board seats.5 And in 2009, women made up
only 6.3 percent of Executive Officer top earning positions within the Fortune 500.6 These
inequities don’t just hurt women. They harm families, employers, and the U.S. economy.
Catalyst believes that until women achieve parity in pay and business leadership, they will be
marginalized in every other arena.
Founded in 1962, Catalyst is the leading nonprofit organization working globally to advance
women and business. With offices in New York, Silicon Valley, Toronto, and Zug, Switzerland,
we count as members more than 400 companies, firms, business schools, and associations from
around the world. Our Advisory Services assesses global and regional challenges to support our
members and policy makers as they build, sustain and leverage female talent in the markets in
which they operate. And our research—widely considered the “gold standard” on women in
corporate leadership—identifies major barriers to women’s advancement and predicts the most
effective strategies for creating sustainable change.
When looking at inequity in the United States, Catalyst focuses on the Fortune 500 because these
corporations are a barometer of American corporate culture. If inequities persist in America’s
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I December 2010
I Joint Economic Committee
most powerful and influential companies, they are present in smaller businesses too. Because our
Census includes the entire population of Fortune 500 companies, we know this is a precise count
of women leaders in our nations’ top 500 businesses. Our findings, cited in media around the
world, reveal the challenges and opportunities for working women and their employers.
In this report, we document that the number of women in Fortune 500 leadership positions
decreases the further up the corporate ladder one goes and how women’s representation in
leadership has remained flat over time, regardless of industry. We show how the Fortune 500
leadership gap persists even though women comprise nearly half of the U.S. labor force7 and
earn more advanced degrees than men.8 We discuss how the low representation of women top
earners underscores that women continue to be underrepresented in the highest paying positions
in corporate America and how the pay gap for women begins with their very first job. Finally,
we present the correlation between women’s representation in corporate leadership and corporate
financial performance, the vital role women play in the United States economy, and the
necessary steps to end gender inequity.
Women lag men in leadership positions despite being nearly SOpercent o f the labor force.
Women are a critical part of the U.S. labor force, but according to our data, they are stuck in
lower levels of management with little, if any, movement upward. If corporate America were a
true meritocracy, there would be equal representation of women and men in every job level.
Instead, it looks like a pyramid where women are clustered in the lower ranks and lower paying
positions, and where few ascend to senior management. CEO or board positions.
Women in Fortune 500 Companies9
/ 2 .6 % '\
CEOs
15.2% Board
Seats
6.3% Top Earners
.
13.5% Executive Officers
\
25.9% Senior Officers & Managers
39.8% Low-Mid Officers & Managers &
Professionals
46.4% Total Employees
Women *s representation in Fortune 500 leadership is stagnant over time.
Progress for women in leadership has moved at a glacial pace. The percentage of women CEOs
in the Fortune 500 increased by less than two-and-half percentage points over the past 14 years;
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Fortune 500 Women CEOs10
'o
12% .
:
....
1996 1997 1398 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Over the past 13 years, the share of women Corporate Officers increased by less than six
percentage points and has remained flat for the past four years:
Fortune 500 Corporate Officer Positions Held by Women11
\%
1996
1997
1998
1999
2000
2002
2005
2006
2007
2008
The trend line for corporate board positions has remained stagnant over the past six years,
increasing only five percentage points over the past decade:
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1 December 2010
I Joint Economic Committee
Fortune 500 Board Seats Held by Women12
15,2%
j
i
1996 1997 1398 1999 2000 2001 2003 2005 2006 200? 2008
Women’s leadership representation has failed to grow appreciably— regardless of industry.
Women are severely underrepresented in leadership positions across industry sectors. The
percentage o f women Executive Officers and board directors in Fortune 500 companies is stuck
in the teens and single digits, while only about 26% of Senior Officers and Managers are women.
Fortune 500 Catalyst Data and EEOC Data by NAICS Industry
Com panics13
Women
Employees 44
CEOs13
Directors*
Executive
Officers1*
Senior
Officers &
Managers 11
Low-Mid Officer*
& Managers**
Professionals*1
Total
Employees21
Retail Trade
11.9%
38.6%
6.8%
18.2%
17.9%
29.7%
42.7%
53.0%
55.6%
Finance & Insurance
16.1%
U.8%
2*5%
16,8%
ia i%
33.3%
47-4%
50.7%
58.2%
19.6%
11.6%
1.0%
12.7%
9.4%
16.8%
21.0%
26.5%
26.2%
16.3%
8.9%
8.6%
16.6%
13.7%
23.5%
31.0%
42.8%
33.9%
5,4%
6.5%
3.7%
14.5%
12.4%
31.9%
36,8%
36.0%
40.1%
24.2%
Manufacturing Durable Goods
M anufacture Nondurable Goods
Information
Transportation &
Warehousing
Accommodations &
Food Services
Professional &
Business Services
Utflities
Wholesale Trade
Mining, Quarrying,
and Oil & Gas
Extraction
5.4%
6,0%
0.0%
10.8%
22.6%
18.8%
27,3%
18.4%
2.0%
5.3%
0.0%
18.1%
15.5%
32.4%
46,8%
50.6%
54.0%
3,4%
2.4%
0.0%
17.6%
13.0%
28.9%
33.3%
39.6%
38.8%
6.5%
2.2%
0,0%
16.9%
11.7%
18.5%
17,3%
30.5%
23.4%
5.0%
1.7%
0.0%
15.7%
2L1%
22.4%
34.4%
49.1%
42.6%
3.2%
0.6%
0.0%
9.0%
10.7%
12.3%
15.3%
26.7%
20.9%
3.0%
15.2%
13.5%
25.9%
37.0%
41.8%
46.4%
Overall
Women lag men in Fortune 500 leadership— including in female-prevalent industries.
One might expect female-prevalent industries would have high representations of women in
leadership, but they do not. In fact, in the industries displayed below, the percentage of womenheld board seats and corporate officer positions is not substantially different from, those of other
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I December 2010
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Financial Performance at Companies with Three or More Women Directors36
16.7%
J
Return on Equity
Return on Sales
Return on tr tested Capital
The percent o f women board directors is a predictor of more women Corporate Officers.
Our report, Advancing Women Leaders, revealed that the percent of women in the boardroom
predicts the percent of women in senior positions. This report showed that the percent of women
in the boardroom impacts women in line roles more than women in staff roles/7 As Catalyst’s
Bottom Line research has shown, high numbers of women board directors and corporate officers
are correlated with increased financial performance. So increasing women’s representation in the
boardroom and subsequently in corporate leadership holds great promise for companies’
financial results.
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I December 2010
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CONCLUSION
The gender leadership and pay gaps are alive and well.
Women lag men in Fortune 500 leadership positions40—and the rate of change per year remains
flat across industries, including female-dominated sectors.41 Women are underrepresented in the
highest earning positions in Fortune 500 companies.42 And the glass ceiling starts at the very
first job for our most talented young women.4
“Giving it more time” is not the answer. These inequities persist despite the fact that for many
years women have both earned more advanced degrees than men44 and have comprised nearly 50
percent of the U.S. labor force 45 Aggressive efforts are required to ensure that the talent pipeline
fueling our nation’s most powerful companies—and in effect, our economy—remains full of
diverse talent. Companies that exclude women from leadership lose out on half of the talent pool.
This is like playing cards with half a deck.
The solutions are clear.
When top leadership understands the clear financial case for advancing women to leadership, it
sets the tone throughout the organization. Yet the very systems that are put in place to develop
the best talent are often fraught with unintended biases that promote only those whose leadership
skills match the mostly male leadership currently in place.4 This problem reinforces
assumptions about what a successful leader looks and acts like and produces “more of the same.”
Meritocracy and representation should go hand-in-hand. When an organization values women
and men equally, the gender balance should be the same at the bottom, in the middle, and the top.
The fact that it isn’t indicates systemic barriers that interfere with progress for half of the talent
pool. This is a waste of human capital. Companies must make sure that top and middle
management is held accountable for results in attaining an inclusive workplace. Companies must
seek to advance women to leadership and pay equity throughout the system.
Research indicates that inclusive workplaces enhance results because independent thought leads
to more innovation.47 A business where women and men are equally represented at all levels
better reflects stakeholders and the marketplace it serves. Only through our focused efforts can
we address the challenges first spelled out in The Declaration of Sentiments more than 160 years
ago. The pay and leadership gaps don’t just harm women. Men, families, businesses, and the
U.S. economy all pay a steep price. It is a price that we cannot afford.
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I December 2010
I Joint Economic Committee
Endnotes
1Bureau of Labor Statistics, Annual averages tables from the 2009 Current Population Survey (2010).
2Digest of Education Statistics (National Center for Education Statistics, 2009).
3 Michael J. Silverstein and Kate Sayre, with John Butman, Women Want More: How to Capture Your
Share of the World’s Largest, Fastest-Growing Market (New York: HarperCollins, 2009).
4 Catalyst, Women CEOs of the Fortune 1000 (2010).
5Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009 Catalyst Census: Fortune 500 Women
Board Directors (Catalyst, 2009).
6Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009 Catalyst Census: Fortune 500 Women
Executive Officers and Top Earners (Catalyst, 2009).
7Bureau of Labor Statistics, Annual averages tables from the 2009 Current Population Survey (2010).
8Digest of Education Statistics (National Center for Education Statistics, 2009) and Nathan E. Bell,
Graduate Enrollment and Degrees: 1999 to 2009 (Council of Graduate Schools, 2010).
9 Pyramid statistics do not sum to 100.0% because categories are not mutually exclusive. Fortune 500
Total Employees, Low-Mid Officers & Managers and Professionals, and Senior Officers & Managers:
Unpublished aggregate EEOC data for 2009 Fortune 500 companies based on 2009 EEO-1 survey;
Fortune 500 Executive Officer and Top Earner positions: Rachel Soares, Nancy M. Carter, and Jan
Combopiano, 2009 Catalyst Census: Fortune 500 Women Executive Officers and Top Earners (Catalyst,
2009); Fortune 500 board seats: Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009 Catalyst
Census: Fortune 500 Women Board Directors (Catalyst, 2009); Fortune 500 CEOs: Catalyst, Women
CEOs of the Fortune 1000 (2010).
10The chart displays the percent of women CEOs at the time Fortune magazine publishes their annual
Fortune 500 list. Catalyst, Women CEOs in the Fortune Lists: 1972-2010 (2010); the most recent data
displays the percent of women CEOs. Catalyst, Women CEOs o f the Fortune 1000 (2010).
11 Catalyst, 2005 Catalyst Census of Women Corporate Officers and Top Earners of the Fortune 500
(2006); Catalyst, 2006 Catalyst Census of Women Corporate Officers and Top Earners of the Fortune 500
(2007); Catalyst, 2007 Census of Women Corporate Officers and Top Earners of the Fortune 500 (2007);
Catalyst, 2008 Catalyst Census of Women Corporate Officers and Top Earners of the Fortune 500 (2008);
Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009 Catalyst Census: Fortune 500 Women
Executive Officers and Top Earners (Catalyst, 2009).
12 Catalyst, 2005 Catalyst Census of Women Board Directors of the Fortune 500 (2006); Catalyst, 2006
Catalyst Census of Women Board Directors of the Fortune 500 (2007); Catalyst, 2007 Catalyst Census of
Women Board Directors of the Fortune 500 (2007); Catalyst, 2008 Catalyst Census of Women Board
Directors of the Fortune 500 (2009); Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009
Catalyst Census: Fortune 500 Women Board Directors.
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13Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009 Catalyst Census (Catalyst, 2009).
14Unpublished aggregate EEOC data for 2009 Fortune 500 companies based on 2009 EEO-1 survey.
15 Catalyst, Women CEOs of the Fortune 1000 (2010).
16Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009 Catalyst Census: Fortune 500 Women
Board Directors (Catalyst, 2009).
17Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009 Catalyst Census: Fortune 500 Women
Executive Officers and Top Earners (Catalyst, 2009).
18Unpublished aggregate EEOC data for 2009 Fortune 500 companies based on 2009 EEO-1 survey.
19Unpublished aggregate EEOC data for 2009 Fortune 500 companies based on 2009 EEO-1 survey.
20Unpublished aggregate EEOC data for 2009 Fortune 500 companies based on 2009 EEO-1 survey.
21 Unpublished aggregate EEOC data for 2009 Fortune 500 companies based on 2009 EEO-1 survey.
22 Catalyst, 2006 Catalyst Census of Women Board Directors of the Fortune 500 (2007); Catalyst, 2007
Catalyst Census of Women Board Directors of the Fortune 500 (2007); Catalyst, 2008 Catalyst Census of
Women Board Directors o f the Fortune 500 (2009); Rachel Soares, Nancy M. Carter, and Jan
Combopiano, 2009 Catalyst Census: Fortune 500 Women Board Directors', Catalyst, 2006 Catalyst
Census of Women Corporate Officers and Top Earners of the Fortune 500 (2007); Catalyst, 2007 Census
of Women Corporate Officers and Top Earners of the Fortune 500 (2007); Catalyst, 2008 Catalyst Census
of Women Corporate Officers and Top Earners of the Fortune 500 (2008).
23 Catalyst, 2006 Catalyst Census of Women Board Directors of the Fortune 500 (2007); Catalyst, 2007
Catalyst Census of Women Board Directors of the Fortune 500 (2007); Catalyst, 2008 Catalyst Census of
Women Board Directors of the Fortune 500 (2009); Rachel Soares, Nancy M. Carter, and Jan
Combopiano, 2009 Catalyst Census: Fortune 500 Women Board Directors', Catalyst, 2006 Catalyst
Census of Women Corporate Officers and Top Earners of the Fortune 500 (2007); Catalyst, 2007 Census
of Women Corporate Officers and Top Earners of the Fortune 500 (2007); Catalyst, 2008 Catalyst Census
of Women Corporate Officers and Top Earners of the Fortune 500 (2008).
24 Catalyst, 2006 Catalyst Census of Women Board Directors o f the Fortune 500 (2007); Catalyst, 2007
Catalyst Census of Women Board Directors of the Fortune 500 (2007); Catalyst, 2008 Catalyst Census of
Women Board Directors of the Fortune 500 (2009); Rachel Soares, Nancy M. Carter, and Jan
Combopiano, 2009 Catalyst Census: Fortune 500 Women Board Directors', Catalyst, 2006 Catalyst
Census of Women Corporate Officers and Top Earners o f the Fortune 500 (2007); Catalyst, 2007 Census
of Women Corporate Officers and Top Earners of the Fortune 500 (2007); Catalyst, 2008 Catalyst Census
of Women Corporate Officers and Top Earners of the Fortune 500 (2008).
25 Current Population Survey, Bureau of Labor Statistics, “Table 2: Employment status of the civilian
noninstitutional population 16 years and over by sex, 1973 to date,” Annual Averages 2009 (2010).
http://www.bls.gov/cps/cpsaat2.pdf
26Digest of Education Statistics (National Center for Education Statistics, 2009) and Nathan E. Bell,
Graduate Enrollment and Degrees: 1999 to 2009 (Council of Graduate Schools, 2010).
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27Digest of Education Statistics (National Center for Education Statistics, 2009) and Nathan E. Bell,
Graduate Enrollment and Degrees: 1999 to 2009 (Council of Graduate Schools, 2010).
28 ** Category includes the following degrees: Chiropractic, Dentistry, Law, Medicine, Optometry,
Osteopathic Medicine (D.O.), Pharmacy (Pharm.D.), Podiatry (D.P.M., D.P., or Pod.D.), Theology
(M.Div., M.H.L., B.D., or Ordination), Veterinary Medicine (D.V.M.). National Center for Education
Statistics, Digest of Education Statistics, "Table 268: Degrees conferred by degree-granting institutions,
by level of degree and sex of student: Selected years, 1869-70 through 2017-18" (2008).
29 Catalyst, 2005 Catalyst Census of Women Corporate Officers and Top Earners of the Fortune 500
(2006); Catalyst, 2006 Catalyst Census of Women Corporate Officers and Top Earners of the Fortune 500
(2007); Catalyst, 2007 Census of Women Corporate Officers and Top Earners of the Fortune 500 (2007);
Catalyst, 2008 Catalyst Census of Women Corporate Officers and Top Earners of the Fortune 500 (2008);
Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009 Catalyst Census: Fortune 500 Women
Executive Officers and Top Earners (Catalyst, 2009).
30Nancy M. Carter and Christine Silva, Pipeline’s Broken Promise (Catalyst, 2010).
31 Nancy M. Carter and Christine Silva, Pipeline’s Broken Promise (Catalyst, 2010).
32 Catalyst, The Bottom Line: Connecting Corporate Performance and Gender Diversity (2004).
33 Catalyst, The Bottom Line: Connecting Corporate Performance and Gender Diversity (2004).
34 Lois Joy, Nancy M. Carter, Harvey M. Wagner, and Sriram Narayanan, The Bottom Line: Corporate
Performance and Women’s Representation on Boards (Catalyst, 2007).
35 Lois Joy, Nancy M. Carter, Harvey M. Wagner, and Sriram Narayanan, The Bottom Line: Corporate
Performance and Women’s Representation on Boards (Catalyst, 2007).
36 Lois Joy, Nancy M. Carter, Harvey M. Wagner, and Sriram Narayanan, The Bottom Line: Corporate
Performance and Women’s Representation on Boards (Catalyst, 2007).
37 Lois Joy, Advancing Women Leaders: The Connection Between Women Board Directors and Women
Corporate Officers (Catalyst, 2008).
38 Lois Joy, Advancing Women Leaders: The Connection Between Women Board Directors and Women
Corporate Officers (Catalyst, 2008).
39 Lois Joy, Advancing Women Leaders: The Connection Between Women Board Directors and Women
Corporate Officers (Catalyst, 2008).
40 Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009 Catalyst Census: Fortune 500 Women
Executive Officers and Top Earners (Catalyst, 2009); Rachel Soares, Nancy M. Carter, and Jan
Combopiano, 2009 Catalyst Census: Fortune 500 Women Board Directors', Unpublished aggregate
EEOC data for 2009 Fortune 500 companies based on 2009 EEO-1 survey.
41 Catalyst, 2006 Catalyst Census of Women Board Directors o f the Fortune 500 (2007); Catalyst, 2007
Catalyst Census of Women Board Directors of the Fortune 500 (2007); Catalyst, 2008 Catalyst Census of
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Women Board Directors o f the Fortune 500 (2009); Rachel Soares, Nancy M. Carter, and Jan
Combopiano, 2009 Catalyst Census: Fortune 500 Women Board Directors; Catalyst, 2006 Catalyst
Census of Women Corporate Officers and Top Earners of the Fortune 500 (2007); Catalyst, 2007 Census
of Women Corporate Officers and Top Earners of the Fortune 500 (2007); Catalyst, 2008 Catalyst Census
of Women Corporate Officers and Top Earners of the Fortune 500 (2008).
42 Rachel Soares, Nancy M. Carter, and Jan Combopiano, 2009 Catalyst Census: Fortune 500 Women
Executive Officers and Top Earners (Catalyst, 2009).
43Nancy M. Carter and Christine Silva, Pipeline’s Broken Promise (Catalyst, 2010).
44Digest o f Education Statistics (National Center for Education Statistics, 2009) and Nathan E. Bell,
Graduate Enrollment and Degrees: 1999 to 2009 (Council of Graduate Schools, 2010).
45 Bureau of Labor Statistics, Annual averages tables from the 2009 Current Population Survey (2010).
46 Anika K. Warren, Cascading Gender Biases, Compounding Effects: An Assessment of Talent
Management Systems (Catalyst, 2009).
47 Scott Page, The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and
societies (Princeton University Press, 2007); Fidan Ana Kurtus, “The Effect of Heterogeneity on the
Performance of Employees and Organizational Divisions of the Firm,” (paper presented at the annual
conference of the Society for Labor Economics, New York, NY, May 9-10, 2008); Corinne Post and
Emilio De Lia, et al “Capitalizing On Thought Diversity For Innovation,” Research Technology
Management,vol. 2, no. 6 (Nov/Dec 2009): p. 14-25.
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Appendix
Testimony Data
For the purposes of this testimony, Catalyst utilized data from the following sources. To examine
trends about women board directors, Catalyst analyzed data from the years 1996 - 1999; 2003;
and 2005-2009. To examine trends about women Corporate Officers, Catalyst analyzed data
from the years 1996-2000; 2002; and 2005-2008. To examine the current representation of
women Executive Officers, Catalyst analyzed data from 2009. To investigate the current status
of women in the pipeline to senior leadership positions, Catalyst obtained from the Equal
Opportunity Employment Commission (EEOC) unpublished aggregate data from the 2009 EEO1 survey for the 496 companies included in the 2009 Catalyst Census reports.1 For each
company, the EEOC data comprises all full-time and part-time employees2 at the time the
company submitted the consolidated EEO-1 form.3
To examine trends in women’s representation by industry, Catalyst explored the historical status
of women in male-dominated and female-prevalent industries, as well as the largest industry on
the Fortune 500 list. Male-dominated industries are those in which women account for 25% or
less of all individuals employed in the field.4 Because there are very few female-dominated
industries,5 Catalyst examined female-prevalent industries, or those in which women account for
more than 40% of all those employed in the field. The manufacturing industry, which accounts
for about one-third of Fortune 500 companies, has been the largest industry for many years.
To examine the current pipeline of women leaders by industry sector, Catalyst excluded any
industry sector with fewer than 10 companies represented in the 2009 Fortune 500 list:
Agriculture, Forestry, Fishing and Hunting (3 companies); Arts, Entertainment, and Recreation
(0); Construction (9); Educational Services (0); Health Care and Social Assistance (6); Real
Estate and Rental and Leasing (7); Other Services Except Public Administration (0); and Public
Administration (0).
Catalyst Census Objectives and Methodology
Catalyst designed the annual Census report series to establish an accurate gauge of women’s
representation at the highest levels of corporate America, both in the boardroom and in senior
leadership positions. The purpose of this research is to provide points of comparison across time
with the goal of promoting women’s advancement in business and garnering attention for this
issue.
Catalyst’s research methodology is a true census that counts all elements of the population. This
research design differentiates our research from studies that utilize survey methodologies
because it removes the need for a sample, thereby producing a more precise picture of women’s
status and progress. Catalyst studies Fortune 500 companies as the population for the Census
report series because not only are these the largest companies by revenue in the United States
each year, but they are also widely recognized as the most powerful and influential businesses.
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Historical Methodology o f Catalyst Census: Fortune 5006
General Report
From 1996-2005, the Catalyst Fortune 500 Census used a consistent two-part methodology to
study women in corporate leadership, both on boards and in management positions. First,
Catalyst gathered data from publicly available sources, including annual reports, proxy
statements, and company websites. Catalyst then authenticated the public source data through a
verification process. Catalyst sent a letter to contacts at each of the Fortune 500 companies to
verify or correct the public source data by letter, fax, or telephone. In any instance where a
company failed to respond to multiple requests for verification, Catalyst utilized publicly
available information for analysis. While Catalyst outlined guidelines for companies to identify
Corporate Officers through the verification process, companies ultimately self-defined their
Corporate Officers.
In 2005, Catalyst compared the data gathered from public sources to the verified data and found
no statistical difference. From 2006-2008, Catalyst gathered data from publicly available annual
reports, proxy statements, and company websites. Because companies choose the individuals
listed in public sources, companies were still involved in the process o f defining their Corporate
Officers.
In 2009, Catalyst implemented a change in methodology to facilitate a focus on top leadership
and provide a more reliable comparison across companies and industries. Catalyst gathered data
from publicly available Securities and Exchange Commission (SEC) annual filings submitted by
June 30, 2009. For insurance companies that do not file with the SEC, Catalyst obtained data
from the National Association of Insurance Commissioners’ (NAIC) regulatory database of key
annual statements submitted by June 30, 2009. Data collected by the SEC and NAIC comply
with federal or state requirements governing the content and timing of the filings, resulting in
more equivalent comparisons across companies. Although companies ultimately determine
which individuals qualify to be listed in the filings, the decision is based on common definitions
and regulations.
As a result of the change in data collection method, the population counted in the 2009 Catalyst
Census: Fortune 500 Women Board Directors report is composed o f those listed in SEC filings
as serving on the board up to the annual meeting of shareholders and those listed in NAIC filings
as Directors. The population of directors was not significantly altered by the methodology
change, permitting comparisons to data from previous Catalyst Censuses of Board Directors.
The population counted in the 2009 Catalyst Census: Fortune 500 Women Executive Officers
and Top Earners report is composed of those listed as Executive Officers7 in SEC filings and
those listed as Officers in NAIC filings. Executive Officers are generally a subset of the
Corporate Officer population as defined in previous Catalyst Census reports. The population
change makes comparisons to data from previous Catalyst Censuses of Corporate Officers
inappropriate. In practice, the typical differences between Executive and Corporate Officers are:
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Appointed or elected by the board of directors
Includes CEO and up to two reporting levels
below
Defined by SEC
December 2010
Joint Economic Committee
Selected by CEO
Includes CEO and up to four reporting levels
below
Defined by company
Industry Data Collection and Analysis
From 1996-2005, industry classifications were based on the fifty or more industry groups from
each year’s Fortune list. The exact number and name of the industry groups varied with each list.
From 2006-2008, industry classifications were coded by Catalyst into the 20 two-digit sector
codes of the North American Industrial Classification System (NAICS). Not all 20 sector codes
are represented on the Fortune list every year.
In 2009, industry classifications were coded by Catalyst into the 20 two-digit NAICS sectors
with two modifications adopted from the NAICS Supersectors for the Current Employment
Statistics Program. Manufacturing (Sectors 31-33) was reclassified into two sectors: Durable
Goods and Nondurable Goods. Three sectors, Professional, Scientific, and Technical Services
(Sector 54); Management of Companies and Enterprises (Sector 55); and Administrative and
Support and Waste Management and Remediation Services (Sector 56) were aggregated into one
sector, Professional and Business Services. As a result of these changes, there were 19 industries.
Race/Ethnicity Data Collection and Analysis
From 2001-2009, Catalyst utilized many sources to gather data about the race/ethnicity of
women board directors, including previous Catalyst Census data, people of color associations’
publications, and biographies. Catalyst also emailed and telephoned contacts at Fortune 500
companies to request the verification of the collected race/ethnicity data. Additionally, Catalyst
wrote to women board directors for self-verification through email and mail. Each year, data
analysis is based on a sample of companies that either a) have complete race/ethnicity data for
each woman board director or b) have no women board directors.8
Catalyst Bottom Line Objectives and Methodology
Catalyst designed the Bottom Line report series to investigate the hypothetical link between
gender diversity in corporate leadership, both in senior management and in the boardroom, and
financial performance. These are correlational studies that do not prove or imply causation.
For each report, Catalyst compiled a list of all companies that appeared in the Fortune 500 for a
specific time period, after accounting for name changes and merger and acquisitions activity.
Financial data for the companies examined were obtained from the Standard & Poor’s
Compustat database. Gender diversity data for senior leadership teams and boards of directors
were compiled from Catalyst’s Fortune 500 Census report series.
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To analyze the data, Catalyst divided companies into quartiles based on the average percentage
of women leaders across the specific time period. The top quartile included the companies with
the highest average percentage of women leaders, while the bottom quartile included the
companies with the lowest average percentage of women leaders.
The Bottom Line: Connecting Corporate Performance and Gender Diversity
Data and Analysis
Catalyst compiled a list of all companies appearing in the Fortune 500 from 1996 to 2000. The
sample was narrowed by excluding companies with fewer than four years o f data on financial
performance and gender diversity of the top management team, resulting in a sample of 353
companies. The top quartile contained 88 companies, while the bottom quartile contained 89
companies.
The Return on Equity (ROE) measure for each company is the average of annual ROEs from
1996 to 2000. An average of the annual ROEs for the period shows the returns for the long-term,
reducing the impact of any unusual year-to-year fluctuations. The Total Return to Shareholders
(TRS) measure is the cumulative total shareholder return over the period 1996 to 2000 for which
data are available. This measure adjusts for both stock splits and stock dividends. Gender
diversity of top management teams was determined by averaging the annual percentages of
women Corporate Officers over the period between 1996 and 2000.
The Bottom Line: Corporate Performance and Women's Representation on Boards
Data and Analysis
Catalyst compiled a list of all companies that appeared in the Fortune 500 in 2001 and 2003,
resulting in a sample of 520 companies. The top quartile contained 132 companies, while the
bottom quartile contained 129 companies.
The ROE, the Return on Sales (ROS), and the Return on Invested Capital (ROIC) measures for
each company are the average of each from 2001 to 2004. Gender diversity of the board of
directors was determined by averaging the annual percentages of women board directors in 2001
and 2003.
Catalyst Advancing Women Leaders Methodology
Catalyst designed the Advancing Women Leaders report to investigate the hypothetical link
between the representation of women on boards in the past and the future representation of
women in Corporate Officer ranks. Catalyst also sought to expand research in this area by
investigating the potential connection between women on boards and women in line positions.
This is a correlational study that does not prove or imply causation.
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Data and Analysis
Catalyst compiled a list of all companies that appeared in the Fortune 500 in 2000, 2001, and
2006, resulting in a matched sample of 359 companies. For these companies, Catalyst utilized
women Corporate Officer data from the 2000 and 2006 Catalyst Census reports, as well as
women board director data from the 2001 Catalyst Census report.
Using regression analysis, Catalyst examined the relationship between the percentage of women
board directors that a Fortune 500 company had in 2001 and the percentage of women Corporate
Officers the same company had in 2006. The analysis controlled for the effects of industry,
revenue, and the percentage o f corporate officer positions held by women in 2000.
Definitions
Corporate Officers. Corporate Officers are recognized as the leaders of a company. They have
day-to-day responsibilities for operations, policymaking responsibility, and the power to legally
bind their corporations. In practice, Corporate Officers typically are within four reporting levels
of the CEO and are defined by the company. Nomenclature used by companies includes groups
such as: company officers, corporate management, executive management, senior officers, senior
management, and senior leadership team. Common titles of corporate officers include: “Chief’
titles, Executive Vice President, Senior Vice President, and Vice President. Catalyst ceased
studying the Fortune 500 Corporate Officer population in 2008.
Executive Officers. Executive Officers are a specific group of individuals, legally defined by the
Securities and Exchange Commission (SEC) in the United States as: “a company’s president, any
vice-president of the registrant in charge of a principal business unit, division or function (such
as sales, administration or finance), any other officer who performs similar policy making
functions for company. Executive officers of subsidiaries may be deemed executive officers of
the registrant if they perform such policy making functions for the registrant.”9 In practice,
Executive Officers represent the highest level of senior leadership, typically within two reporting
levels of the CEO and generally appointed by the board o f directors. Executive Officers
represent a segment of the Corporate Officer population as defined in previous Catalyst Census
reports. Catalyst has been studying the Executive Officer population since 2009.
Fortune 500. Fortune magazine’s ranking of the top 500 U.S. incorporated companies filing
financial statements with the government is based on each company’s gross annual revenue.
Included in the list are public companies, private companies, and cooperatives that file a 10-K
with the Securities and Exchange Commission (SEC), and mutual insurance companies that file
with state regulators.10
Line Officers. Line officers are responsible for a company’s profits and losses. Examples
include positions within functions such as supply chain, marketing, or sales.
Low-Mid Level Officials & Managers and Professionals. Catalyst combined two categories to
create the Low-Mid Level Officials & Managers and Professionals level of the “Women in
Fortune 500 Companies” chart. Please refer to EEOC definitions for more information.11
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Quartile analysis. Catalyst divided the sample o f companies into four sections based on
women’s representation. The top quartile included the companies with the highest average
percentage of women leaders, while the bottom quartile included the companies with the lowest
average percentage of women leaders.
Race/Ethnicity. The race/ethnicity category definitions used by Catalyst were established by the
U.S. Census Bureau. Catalyst uses 6 categories to report information about race/ethnicity.12
Return on Equity (ROE). The ratio of after-tax net profit to stockholders’ equity.
Return on Invested Capital (ROIC). The ratio of after-tax net operating profit to invested
capital.
Return on Sales (ROS). The pre-tax net profit divided by revenue.
Senior Level Officials & Managers. Please refer to EEOC definitions for more information.13
Staff Officers. Staff officers are responsible for the auxiliary functioning of the business.
Examples include positions within functions such as human resources, corporate affairs, legal,
and finance.
Top Earner. As per Item 402 of Regulation S-K (§ 229.402), paragraph (a)(3), federal securities
laws require the disclosure of the total compensation of at least five individuals: the principal
executive officer (CEO), the principal financial officer (CFO), and the company’s three most
highly compensated executive officers (excluding the CEO/CFO) as of the company’s fiscal year
end. Furthermore, companies must disclose the total compensation of up to two additional
individuals who would have been top earners except for the fact that these individuals were not
employed as Named Executive Officers as of the company’s fiscal year end.14
Catalyst reports on top earners for Fortune 500 companies that file annual 10-K reports and
Proxy statements with the Securities and Exchange Commission (SEC). In 2009, Catalyst
defined top earners as those current Executive Officers whose total compensation is among the
top five amounts disclosed; prior to 2009 Catalyst defined top earners as those current Corporate
Officers whose total compensation is among the top five amounts disclosed. A company can thus
have five or fewer top earners. Because Catalyst views the representation of women top earners
as a proxy for status in the organization rather than a method to measure pay inequity, Catalyst
does not track the compensation amounts of top earners.
Total Return to Shareholders (TRS). The sum of stock price appreciation plus reinvestment of
dividends declared over a calendar year.
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I Joint Economic Committee
Endnotes
12009 analysis is based on 496 companies. Catalyst excluded four companies due to specific events: two
declared bankruptcy, one was acquired, and one delisted with the SEC.
2Employees are defined as “any individual on the payroll of an employer who is an employee for
purposes of the employers withholding of Social Security taxes except insurance sales agents who are
considered to be employees for such purposes solely because of the provisions of 26 USC 3121 (d) (3)
(B) (the Internal Revenue Code).”
3 Equal Employment Opportunity, Standard Form 100, Employer Information Report EEO-1 Instruction
Booklet (2006) http://www.eeoc.gov/emplovers/eeolsurvev/2007instructions.cfm.
4 Current Population Survey, Bureau of Labor Statistics, "Table 18: Employed persons by detailed
industry, sex, race, and Hispanic or Latino ethnicity." 2009 Annual Averages (2010).
5By definition, female-dominated industries would be those in which men account for 25% or less of all
those employed in the field. In 2009, only one 2-digit NAICS code industry qualified as femaledominated: Health Care and Social Assistance. However, this industry has fewer than 10 companies in the
2009 Fortune 500 list, making comparisons inappropriate.
6Please refer to each publication’s methodology section or appendix for more detailed information about
the methodology (e.g., verification rates for each year).
7Please refer to the definitions section of the appendix for the definition of Executive Officer.
8Please refer to each publication for more detailed information about the number of companies included
in the race/ethnicity data analysis.
9 § 240.3b-7 Definition of “executive officer.” [47 FR 11464, Mar. 16,1982, as amended at 56 FR 7265,
Feb. 21, 1991] (http://ecfr.gpoaccess.gov/cgi/t/text/text-idx?c=ecfr&sid=47b43cbb88844faad586861
c05c81595&rgn=div5&view=text&node=l 7:3.0.1.1. l&idno=l 7#17:3.0.1.1.1.1.54.45).
10 Fortune Magazine, Fortune 500 http://monev.cnn.com/magazines/fortune/fortune500/2Q09/faq/.
11 Equal Employment Opportunity Commission, Employer Information Report EEO-1 Instruction
Booklet (2006). http://www.eeoc.gov/emplovers/eeolsurvev/upload/instructions form.pdf.
12U.S. Census Bureau, Office o f Management and Budget, Revisions to the Standards for the
Classification of Federal Data on Race and Ethnicity.
http://www.census.gov/population/www/socdemo/race/Ombdirl5.html.
13 Equal Employment Opportunity Commission, Employer Information Report EEO-1 Instruction
Booklet (2006). http://www.eeoc.gov/emplovers/eeolsurvev/upload/instructions form.pdf.
14 Code of Federal Regulations, Amendment from September 08, 2006, § 229.402 (Item 402) Executive
compensation.
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Invest in Women, Invest in America:
December 2010
A Comprehensive Review of Women in the U.S. Economy
Joint Economic Committee
Testimony of Michelle J. Budig
Associate Professor of Sociology
Faculty Associate, Center for Public Policy Administration
W33cd Machmer Hall
University of Massachusetts
Amherst, MA 01003-9278
budig@soc.umass.edu
413-545-5972
before the
United States Joint Economic Committee
Hearing on
“New Evidence on the Gender Pay Gap for Women and Mothers in Management”
September 28, 2010
INTRODUCTION
“Chairwoman Maloney and members of the committee, I thank you for the opportunity to speak.
My name is Michelle Budig, and I am an Associate Professor of Sociology and Faculty
Associate at the Center for Public Policy Administration at the University of Massachusetts. My
expertise is in gender, work, and family issues, and most relevant to today, the wage penalty for
motherhood and work-family policy.
Today I will testify that a significant portion of the persistent gender gap in earnings, among
workers with equivalent qualifications and in similar jobs, is attributable to parenthood.
Specifically, to the systematically lower earnings of mothers and higher earnings of fathers,
among comparable workers. Thus, public policies that target the difficulties families face in
balancing work and family responsibilities, as well as discrimination by employers by
workers’ parental status, may be the most effective at reducing the gender pay gap.
My testimony today will address 4 points. First, I will discuss the relative absence of wives and
mothers among managers and leaders of organizations. Second, I will compare gender pay gaps
among young childless workers and among parents. Third, I will summarize statistical evidence
of unaccountably lower wages for mothers and higher wages for fathers. Finally, I will present
research on work-family policies and their impact on the wage penalty for motherhood, with an
eye to drawing policy implications for the United States.
The report presented by the GAO demonstrated that, relative to men, women in management are
younger and less educated. This begs the question, where are the older, more educated and
experienced, female mangers? And why are they under-represented? A generation ago we might
have hypothesized this relative absence of more senior women was simply due to the lack of
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qualified and experienced women in potential pool of women managers. However, since the
1980s, these qualifications and experience differences between women and men have eroded, so
much so that women now earn college degrees at higher rates than men.1 If a lack of qualified
candidates cannot explain the absence of experienced female managers, what can?
My research and others demonstrates that a significant portion of gender-based differences in
employment, earnings, and experiences of discrimination are increasingly related to
parenthood, and the greater struggles of mothers to balance careers and family demands.
POINT ONE: PARENTHOOD, GENDER, AND EMPLOYMENT
Let us first step back from the pay gap to look at gender differences in the family structures of
managers in the GAO report.
Wives and mothers are relatively more absent among managers, compared with the
representation of husbands and fathers.
If we subtract the rates of marriage among men from those among women, we might compute a
Managerial Gender Marriage Gap: Women managers are far less likely to be married overall,
compared with male managers. This gap in marital rates ranges from 8 to 19 percentage points
across industries, with an average gap of 15 percentage points.
Second, if we subtract the rates of parenthood among men from those among women, we would
compute a Managerial Gender Parenthood Gap: Women managers are less likely to be mothers,
and have smaller family sizes, relative to male managers. The parenthood gap ranges from 0 to 9
percentage points across industries, with an average gap of 6 percentage points.
The absence of mothers and the rise in childlessness among highly skilled women is also found
in national data. Table 1 in your handout shows that, controlling for differences in age, marital
status, education, and other household income, the gender employment gap among the childless
is minimal whereas the gender employment gap among parents is quite large.
Table 1. Likelihood of Being Employed by Parenthood and Gender
Childless Men
Childless Women
Fathers
Mothers
88.5%
82.2%
93.0%
73.4%
Note: Currrent Population Survey data, from statistical models controlling for age, marital
status, education, and other household income), Non-institutionalized Civilians, Aged 25-492
Childlessness has risen among American women since the 1970s, and particularly among highly
educated women. In 2004, among college educated white women in their 40s, fully 27% were
childless.3 Researchers estimate about 44% of this childlessness is voluntary, while 56% is due to
age-related infertility.4 A major reason why women delay or forego motherhood is due to the
perceived and experienced incompatibility between careers and motherhood.5
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I Joint Economic Committee
Thus, high-achieving women are forgoing families at rates not observed among highachieving men.
Before we move on to considering the link between the persistent gender pay gap and
parenthood among the employed, we need to recognize that we are missing the mothers from
these statistics. Thus, the mothers who persist are a qualitatively select group, or potentially the
cream of the crop, if you will. This implies that our current estimates of the gender pay gap may
be much smaller than they would be if mothers were not disproportionately absent from the work
force.
POINT TWO: GENDER PAY GAPS AMONG THE CHILDLESS AND AMONG PARENTS
In the GAO report, among the mothers who persist in management, their gender pay gap
relative to fathers is far larger (ranging from 21% to 34%) than the gender pay gap among
childless managers (17% to 24%).
The shrinking gender gap among young childless workers has captured national attention this
month with the highly publicized study by James Chung of Reach Advisors, on the lack of a
gender gap among childless workers. Chung, who analyzes data from the American Community
Survey, shows that among 20-something unmarried, childless workers in urban areas, there is no
gender pay gap.6 Moreover, in multiple instances in this unencumbered group, women out-eam
men. Chung notes that these women are also largely unmarried.
Estimates from my research of the gender pay gaps among full-time workers are presented in
table 2 in your handout. Whereas childless women earn 94 cents of a childless man’s dollar,
mothers earn only 60 cents of a father’s dollar.
Table 2. Unadjusted Gender Pay Gap for Full-time Employed Civilians, Aged 25 to 497
Women’s Pay per $1 Male
Dollar
Mother’s Pay per $1
Father Dollar
Childless Woman’s Pay
per $1 Childless Man’s
Dollar
790
600
940
Note: Author’s calculations from Current Population Survey data.
While causality is complex, there is a strong empirical association between the gender gap (pay
differences between women and men) and the family gap (pay differences between households
with and without children) .8, 9, 10 Economist Jane Waldfogel’s research (1998a) shows that 40%
to 50% of the gender gap can be explained by the impact of parental and marital status on
men’s and women’s earnings. Moreover, Waldfogel (1998b) shows that while the gender pay gap
has been decreasing, the pay gap related to parenthood is increasing.
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A Comprehensive Review of Women in the U.S. Economy
I Joint Economic Committee
This greater gender inequality found among parents brings me to my next point, the wage
penalty for motherhood.
POINT THREE, PART A: THE WAGE PENALTY FOR MOTHERHOOD
The finding that having children reduces women’s earnings, even among workers with
comparable qualifications, experience, work hours, and jobs, is now well established in the social
science literature. n , n , 13, 14, 15, 16,17 In your handout, Table 3 shows the effect of children on
earnings from my published research. All women experience reduced earnings for each
additional child they have. This penalty ranges in size from -15% per child among low-wage
workers to about 4% per child among high-wage workers.
That mothers work less and may accept lower earnings for more family-friendly jobs explains
part of the penalty experienced by low wage workers, and that mothers have less experience, due
to interruptions for childbearing, explains a part of the penalty for high-wage workers.
But a significant motherhood penalty persists even in estimates that account for these
differences, such that the size of the wage penalty after all factors are controlled is roughly
3% per child. This means we would expect the typical full-time female worker in 2009 to
earn roughly $1,100 less per child in annual wages, all else equal.
Table 3. Effect Each Additional Child on Women’s Hourly Wage19
Low-Wage
Women
(5th Percentile)
-15.1%
Baseline M odela
Average Earner High-Wage Women
(50th Percentile)
(95th Percentile)
-5.7%
-3.9%
+ Controls for Work Hours b
-10.6%
^ .0 %
-5.0%
+ Controls for Education,
experience, seniority0
-11.1%
-2.4%
-2.3%
+ Controls for Job Characteristics d
-4.4%
-1.4%
-2.5%
Controlling for all differences,
averaging across all women
-3.0%
= $1,100
Notes: aModel controls for number of children, age of respondent, region of country, population density,
marital status, spouse’s annual earnings, and spouse’s work hours.
bModel also controls for usual weekly hours and annual weeks worked.
eModel also controls for education, experience, seniority, and employer changes.
dModel also controls for level of job gender segregation, professional/managerial status, public sector,
irregular shift work, self-employed status, employer-sponsored health insurance, employer-sponsored life
insurance, labor union membership, and 12 dummies for industrial sector.
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Joint Economic Committee
What lies behind this motherhood penalty that is unexplained by measurable characteristics of
workers and jobs? One factor may be employer discrimination against mothers. It is difficult to
obtain data on discrimination and virtually impossible to match it to outcomes in large-scale
national surveys. However, evidence from experimental and audit studies support arguments
of employer discrimination against mothers in callbacks for job applications, hiring
decisions, wage offers, and promotions.20 Stanford sociologist Shelley Correll’s experimental
research shows that, after reviewing resumes that differed only in noting parental status, subjects
in an experiment systematically rated childless women and fathers significantly higher than
mothers on competency, work commitment, promotability, and recommendations for hire. Most
telling, Correll and colleagues found that raters gave mothers the lowest wage offers, averaging
$13,000 lower than wage offers for fathers.
This privileging of fathers brings me to my next point.
P O IN T THREE, P A R T B : THE WAGE B O N U S FO R FATH ERH O O D
The motherhood penalty compares women against women to see how children depress their
wages. While it is well known that fathers earn more than mothers, new research is highlighting
the importance of fatherhood among men in enhancing their wages.21, 22A portion of fathers’
higher earnings can be explained by the facts fathers tend to work more hours, have more
experience, and have higher ranking occupations, relative to childless men. But after we adjust
for these differences, we still find a wage bonus for fatherhood, and one that increases with
educational attainment. Figure 1 in your handout shows that, controlling for an array of labor
market characteristics, men of all racial/ethnic groups receive a fatherhood bonus in
annual earnings, and this bonus is greatest among white and Latino college graduates,
whose wages, all else equal, are $4,000 to $5,000 higher than childless men.
Figure 1. The Effect of Fatherhood (in Dollars) by Educational
A tta in m e n t and R ace/Ethncity
S6.000.00
$5,25?
55,000.00
54,000.00
$3,000,0
HS
: to
$2,000,00
j
Dropout
|
HS
j
G ra d u ate j
: : 538
■ Some
College
$ 1,000,00
$0,(30
L a tin o
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African American
In vest in W om en, Invest in A m erica:
A Comprehensive Review of Women in the U.S. Economy
D ecem b er 2010
Joint Economic Committee
Note: figure taken from Hodges, Melissa J. and Michelle J. Budig. 2010. “Who Gets the Daddy
Bonus? Organizational Hegemonic Masculinity and the Impact of Fatherhood on Men’s
Earnings.” Gender & Society 24(6): December Issue.
Putting these sets of findings together, we see that parenthood exacerbates gender
inequality in American workplaces. Mothers lose while fathers gain from parenthood, and
these penalties and bonuses are found beyond the differences between parents and childless
persons in terms of hours worked, job experience, seniority, and a wide host of other
relevant labor market characteristics.
POINT FOUR: POLICY IMPLICATIONS
What kinds of policies might enable mothers to maintain employment, workplaces assist parents
in balancing work and family demands, and reducing the gender gap in pay attributable to wage
bonuses for fatherhood and wage penalties for motherhood?
In an NSF-funded cross-national study of 22 nations I’ve been conducting with colleague Joy a
Misra and student collaborator Irene Boeckmann, we’ve identified three key policies that are
linked to smaller motherhood penalties:
Universal Early Childhood Education for preschool children and increased availability of
affordable, high-quality care for very young children reduces the motherhood wage
penalty.
Figure 2 in your handout shows the wage penalty for motherhood dramatically declines with
the availability of publicly funded childcare for infants under 2 years old. Whereas we
observe motherhood penalties of over 6% per child in countries lacking such care, the
motherhood penalty declines toward zero as the enrollment of children in publicly funded infant
care approaches 40%.
Figure 2. Net Per Child Effect on Ln Annual Earninp, by the Percentage of Children Age 0 to 2 Who
Are Enrolled in Publicly Funded Childcare
AM
15
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40
In vest in W om en, Invest in A m erica:
A Comprehensive Review of Women in the U.S. Economy
D ecem b er 2010
Joint Economic Committee
Note: figure taken from Budig, Michelle J., Joya Misra, and Irene Boeckmann. 2010. “The
Cross-National Effects of Work-Family Policies on the Motherhood Wage Penalty: Findings
from Multilevel Analyses.” Paper presented at the 2010 Annual Meetings of the Population
Association of America (Dallas, TX).
Universal moderate length job-protected leave following the birth/adoptlon of a child.
In the US, FMLA was designed to provide short-term unpaid leave to new parents, as well as
other family caregivers. But less than a majority of gainfully employed American workers are
covered by this act, due to exemptions of employer types from the law. Of those employers
covered by FMLA, researchers estimate only 54% to 77% are in compliance with the law.23, 24
FMLA needs to be extended to all workplaces and workers, and ideally should be longer
than 12 weeks.
Cross-nationally, job-protected leaves range up to 3 years, as can be seen on figure 3 in your
hand out. Our research shows that countries with very short and countries with very long leaves
have the highest motherhood penalties. Job-protected leaves of roughly one year do the best at
minimizing the wage penalty for motherhood. Obviously, this is far beyond what is currently
offered by FMLA, but emphasizes the importance of such leave in minimizing gender inequality.
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A Comprehensive Review of Women in the U.S. Economy
I D ecem b er 2010
I Joint Economic Committee
Figure 3. Net Per Child Effect on Ln Annual Earnings by MaximumNumber of Weeks of Parental Care
Leave Available to Mothers
'•3.0%.
-g.ox
/
....-.....................................................
- -.
;■
- .' a ' "■
. ..20' ' ' ; . "
; . \ V ; : : ® \ .•.
O ' ”#*---
: too
:
. ' 120
--
> , v is o --
Note: figure taken from Budig, Michelle J., Joya Misra, and Irene Boeckmann. 2010. “The
Cross-National Effects of Work-Family Policies on the Motherhood Wage Penalty: Findings
from Multilevel Analyses.” Paper presented at the 2010 Annual Meetings of the Population
Association of America (Dallas, TX).
Short-term paid Maternity AND Paternity leave
Short-term paid maternity leave (6 to 12 weeks) reduces the likelihood that women will have to
exit jobs to recover from childbirth, and increases their ability to return to the same employer
upon re-entry. The ability to return to work with the same employer following the birth of a child
greatly reduces the wage penalty for motherhood.25 The effects of paid leave reserved for fathers
on the wage penalty for motherhood, cross-nationally are also dramatic. Our research shows that
countries that offer non-transferable paid leave to fathers evidence significantly lower wage
penalties to mothers.
Addressing workplace discrimination against mothers and those making use of family
benefits.
Some American workplaces offer various work-family benefits designed to help parents manage
work and family responsibilities, such as paid leave, flexible scheduling, flexible work
location, part-time options, and childcare assistance, these benefits vary in availability and
usage across workplaces. Research finds that many employees are unaware of the benefits
available, and many employees fear negative impacts on their careers for making use of such
policies.26 Moreover, some research indicates that usage o f these policies can exacerbate the
motherhood wage penalty. 27 Federal-level work-family policies could eliminate many of
these problems with uneven access across workplaces to work-family assistance, and
discrimination against those workers who make use of legally sanctioned work-family
benefits.
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Joint Economic Committee
CONCLUSION
A significant portion of the persistent gender gap in earnings is attributable to parenthood,
specifically, the systematically lower earnings of mothers and higher earnings of fathers, among
comparable workers. To reduce the gender pay gap, public policies should target the
difficulties families face in balancing work and family responsibilities, as well as
discrimination by employers based on workers’ parental status.
I thank you for your time, I hope my testimony is of use to this committee.
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A Comprehensive Review of Women in the U.S. Economy
I Joint Economic Committee
Endnotes
1U.S. Bureau o f Labor Statistics, Employment and Earnings: January 2010, Table 7, (accessed 9-22
2010 at http://www.bls.gov/cps/cpsa2009.pdf).
2 Misra, Joya, Michelle J. Budig and Irene S. Boeckmann. 2010. “Cross-National Patterns in Individual
and Household Employment and Work Hours by Gender and Parenthood.” Forthcoming at Research in
the Sociology of Work. Presented at the 2010 annual meetings of the American Sociological Association
(Atlanta, GA).
3 Lundquist, Jennifer Hickes, Michelle J. Budig, and Anna Curtis. 2009. “Race and Childlessness in
America, 1988-2002.” Journal of Marriage and the Family 71:741-755.
4 Abma, Joyce C. and Gladys M. Martinez. 2006. “Childlessness Among Older Women in the United
States: Trends and Profiles.” Journal of Marriage and the Family 68:1045-1056.
5 Jacobs, Jerry and Kathleen Gerson, 2004. The Time Divide: Work, Family, and Gender Inequality.
Cambridge, MA: Harvard University Press.
6 http://www.time.eom/time/business/article/0.8599.2015274.00.html
7Misra, Joya, Michelle J. Budig and Irene S. Boeckmann. 2010. “Cross-National Patterns in Individual
and Household Employment and Work Hours by Gender and Parenthood.” Forthcoming at Research in
the Sociology o f Work. Presented at the 2010 annual meetings of the American Sociological Association
(Atlanta, GA).
8Polachek, S.W. 2006. “How the Life-Cycle Human Capital Model Explains Why the Gender Wage Gap
Narrowed.” Pp. 102-124 in The Declining Significance of Gender? F.D. Blau, M.C. Brinton, and D.B.
Grusky, eds. New York: Russell Sage Foundation.
9 Waldfogel, Jane. 1998a. “Understanding the ‘Family Gap’ in Pay for Women with Children.” Journal of
Economic Perspectives 12(1): 137-56.
10Waldfogel, Jane. 1998b. “The Family Gap for Young Women in the United States and Britain: Can
Maternity Leave Make a Difference?” Journal o f Labor Economics 16 (3): 505-545.
11 Anderson, D., M. Binder, and K. Krause. 2003. “The Motherhood Wage Penalty Revisited: Experience,
Heterogeneity, Work Effort, and Work-Schedule Flexibility.” Industrial and Labor Relations Review
56:273-94.
12Avellar, S. and P. Smock. 2003. “Has the Price of Motherhood Declined over Time? A Cross-Cohort
Comparison of the Motherhood Wage Penalty.” Journal o f Marriage and the Family 65:597-607.
13Budig, Michelle J. and Paula England. 2001. “The Wage Penalty for Motherhood.” American
Sociological Review 66:204-25.
14Budig, Michelle J. and Melissa J. Hodges. 2010. “Differences in Disadvantage: Variation in the
Motherhood Penalty Across White Women’s Earnings Distribution.” American Sociological Review 75
(5): Oct. (In press).
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15Glauber, R. 2007a. “Marriage and the Motherhood Wage Penalty among African Americans,
Hispanics, and Whites.” Journal of Marriage and the Family 69:951-61.
16Taniguchi, H. 1999. “The Timing of Childbearing and Women’s Wages.” Journal of Marriage and the
Family 61:1008-19.
17Waldfogel, J. 1997. “The Effect of Children on Women’s Wages.” American Sociological Review
62:209-17.
18Median earnings taken from IWPR report, “Gender Wage Gap 2009”, accessed 9/22/2010,
(http://www.iwpr.org/pdf/C3 50.pdf)
19Table taken from Budig, Michelle J. and Melissa J. Hodges. 2010. “Differences in Disadvantage:
Variation in the Motherhood Penalty Across White Women’s Earnings Distribution.” American
Sociological Review 75(5): Oct.
20 Correll, Shelley J., Stephen Benard, and In Paik. 2007. “Getting a Job: Is There a Motherhood
Penalty?” American Journal o f Sociology 112:1297-1338.
21 Glauber, Rebecca. 2007. “Race and Gender in Families and at Work: The Fatherhood Wage Premium.”
Gender & Society 22: 8-30.
22Hodges, Melissa J. and Michelle J. Budig. 2010. “Who Gets the Daddy Bonus? Organizational
Hegemonic Masculinity and the Impact of Fatherhood on Men’s Earnings.” Gender & Society
24(6):December Issue.
23 Armenia, Amy, Naomi Gerstel, and Coady Wing. 2009. “Estimating and Predicting Compliance with
FMLA: Pressures from Above and Below.” Paper presented at the Annual Meetings of the Southern
Sociological Society.
24Gerstel, Naomi and Amy Armenia. 2009. “Giving and Taking Family Leaves: Right or Privilege.” Yale
Journal of Law and Feminism. 21(1): 161-184.
25 Gangl, Markus and Andrea Ziefle. 2009. “Motherhood, Labor Force Behavior, and Women’s Careers:
An Empirical Assessment of the Wage Penalty for Motherhood in Britain, Germany, and the United
States.” Demography 46:341-69.
26 Hochschild, Arlie. 2001. The Time Bind: When Work Becomes Home and Home Becomes Work. Owl
Books.
27Glass, Jennifer. 2004. “Blessing or Curse? Work-Family Policies and Mothers’ Wage Growth Over
Time.” Work and Occupations 31:367-94.
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Joint Economic Committee
HANDOUT
Table 1. Likelihood of Being Employed by Parenthood and Gender
Fathers
Childless Men
Childless Women
73.4%
93.0%
82.2%
88.5%
Mothers
Note: From statistical models controlling for age, marital status, education, and other household
income), Non-institutionalized Civilians, Aged 25-49.
Tables 1 and 2 calculated from data presented in Misra, Joya, Michelle J. Budig and Irene S.
Boeckmann. 2010. “Cross-National Patterns in Individual and Household Employment and
Work Hours by Gender and Parenthood.” Forthcoming at Research in the Sociology o f Work.
Presented at the 2010 annual meetings of the American Sociological Association (Atlanta, GA).
Table 2. Unadjusted Gender Pay Gap for Non-institutionalized, Full-time Employed Adults,
Women’s Pay per $1 Male
Dollar
Mother’s Pay per $1
Father Dollar
Childless Woman’s Pay
per $1 Childless Man’s
Dollar
790
600
940
Table 3. Effect Each Additional Child on Women’s Hourly Wage
Low-Wage
Women
(5th Percentile)
Average Earner
(50th Percentile)
High-Wage Women
(95th Percentile)
Baseline M odela
-15.1%
-5.7%
-3.9%
+ Controls for Work Hours b
-10.6%
-4.0%
-5.0%
+ Controls for Education,
experience, seniorityc
-11.1%
-2.4%
-2.3%
+ Controls for Job Characteristics d
-4.4%
-1.4%
-2.5%
Controlling for all differences,
averaging across all women
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VerDate Nov 24 2008
Invest in W om en, Invest in A m erica:
A Comprehensive Review of Women in the U.S. Economy
D ecem b er 2010
Joint Economic Committee
Figure 2. Net Per Child Effect on Ln Annual Earnings, by the Percentage of Children Age 0 to 2 Who
Are Enrolled in Publicly Funded Childcare
Figures 2 and 3 from: Budig, Michelle J., Joya Misra, and Irene Boeckmann. 2010. “The Cross
National Effects of Work-Family Policies on the Motherhood Wage Penalty: Findings from
Multilevel Analyses.” Paper presented at the 2010 Annual Meetings of the Population
Association of America (Dallas, TX).
Figure 3. Net Per Child Effect on Ln Annual Earnings by Maximum Number of Weeks of Parental Care
Leave Available to Mothers
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Invest in W om en, In vest in A m erica:
A Comprehensive Review of Women in the U.S. Economy
I D ecem b er 2010
I Joint Economic Committee
The Earnings Penalty for Part-Time Work; An Obstacle to Equal Pay
A Report by the Joint Economic Committee
Representative Carolyn B. Maloney, Chair
April 20,2010 (Equal Pay Day)
Introduction
Equal Pay Day highlights an issue of social and policy significance: the gap between the
earnings of men and women. Estimates of the gender pay gap vary, but it is clear that women
earn less than men.1 This gap has arisen for a variety of reasons, but one dimension of the
problem involves the earnings penalty for part-time work. Closing the pay gap between full-time
and part-time workers will contribute significantly to closing the pay gap between men and
women. The part-time earnings penalty has had a particularly large impact on the economic well
being of families during the Great Recession since the number of part-time workers who would
like full-time employment has risen by 4.4 million workers since December 2007.
Part-Time Workers Are Disproportionately Female.
In 2009, over 17 million women worked part time. Out o f the pool of individuals who work part
time, nearly two-thirds are women. (Sec Figure 1.)
i
[
.......... .... .................. ............
" .... ... ........ ..... ........ ...... .............................. ...I
:
Figure 1. Nearly Two-Thirds of Part-Time Workers Are Women
i
:
N ote: Cmploved persons d ie classified ds fu ll- c»i pai t-tim e v /u ik e is based o il th eii usual w eekly h o u rs at dll jo b s regardless o f the nu m be r o f tio iu sth e v dre a t w o rk
'
;
du rin g th e refe re nce v/eek Per sons absent fro m w o rk also are classified accoi cling to th eii usual status
bource:JEC M a jo rity V taff calculations fro m Bureau o f Laboi Statistics. C u rre n t P o pu latio n Survey 2009
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Prepared by the Majority Staff of the Joint Economic Committee
In vest in W om en, Invest in A m erica:
A Comprehensive Review of Women in the U.S. Economy
D ecem b er 2010
Joint Economic Committee
While most working women work foil time, one-quarter (26 percent) of all employed women
work part time, compared to 13 percent of employed men. (See Figure 2.) In many of the
occupations with large shares of part-time workers, employment is dominated by women.
Women make up over half (56 percent) of the employees working in food preparation and
serving related jobs, where 49 percent of workers are employed part time. Over three-quarters
(77 percent) of personal care and service positions are held by women - an occupation where 43
percent of employees work part time.
Figure 2. One-in-Four Employed Women Usually Works Part Time
N ote : E m ployed pe i sons ai e classified as lu ll- 01 pai t tu n e . . u ik w s based on th en usual v.enkly h o u i s a t nil jo b s ie £ aid le ss o t th e n n m b e i o f iio n ts th f» v a ie a l ..;<>ik
d u rin g th e re fe ie n c e . /e ek. Pei sons absen t fio in ,.;o ik also ai e classified accotcling to th e ii usu al sta tus
S o uic e : JE< M a jo n tv S ta ll calc u la tio n s fro m [’.m e a u o t Laboi Statistics O n te n t P o p u la tio n S urvey 2 0 0 9
Part-Time Workers Face an Earnings Penalty.
Part-time workers across a spectrum of occupations earn hourly wages below those of full-time
workers, which contributes to the wage gap between men and women. For example, for every
dollar of earnings a full-time worker receives in a sales or related occupation, a part-time worker
receives 58 cents. A similar story is true for workers in computer and mathematical occupations:
a part-time worker receives about 63 cents for every dollar of earnings a full-time worker
receives. (See Figure 3.)
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Endnotes
*' One widely cited estimate of the gap in pay shows that women’s earnings were 77 percent of men’s
earnings in 2008, or about $5 per hour less than men. National Committee on Pay Equity, available at
http://www .pav-equ itv. org/info-time.html. 2008 data based on full-time workers. To calculate average
hourly wage differences, it is assumed that workers work 40 hours per week.
“ Bertrand, Marianne, Claudia Goldin, and Lawrence Katz. “The Dynamics of the Gender Gap for
Young Professionals in the Financial and Corporate Sectors.” December 2009 working paper. See
htt p://www.economi cs .harvard.edit/
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In vest in W om en, Invest in A m erica:
A Comprehensive Review of Women in the U.S. Economy
I D ecem b er 2010
j Joint Economic Committee______
Large Gender Pay Gap for Older Workers Threatens Economic Security of Older Women
A Report by the Joint Economic Committee
Representative Carolyn B. Maloney, Chair
December 2010
Much is often made about the significant narrowing of the gender pay gap over the past three
decades. However, in 2009, full-time working women 50 and older earned only three-fourths of
what full-time working men the same age earned. The wage penalty paid by older women is
often overlooked because of the improvement in the overall gender wage gap. This sizable
gender pay gap for older workers threatens the retirement security of our country’s older women
and families that depend on their earnings for their well-being.
The wage gap is larger for older workers than for younger workers. In 2009, women 50 and
older working full-time earned only 75 percent of their male counterparts’ earnings, leaving a 25
percent gap (see chart and table). For full-time workers 16 and older, women’s median weekly
earnings were 80 percent of their male counterparts’, leaving a 20 percent gap between women’s
and men’s earnings. According to the Bureau of Labor Statistics, the gender wage gap for
workers ages 45-54 years narrowed between 1979 and 2009. For workers 65 and older the gap
was essentially flat over that period, despite some fluctuations.1
Employment patterns, including industry, occupation and career interruptions, affect the gender
pay gap. Researchers have documented several sources of the greater earnings disparity for
older men and women. First, women have historically been more likely to be employed in lowerpaying industries such as the health care and education industries.2 Second, across industries,
women tend to be employed in lower-paying occupations. For example, 23 percent of women
working full-time in 2009 were employed in office and administrative support occupations,
compared to only 7 percent of men working full-time.3 Occupational segregation has
repercussions for women’s economic security. Jobs traditionally held by women have long been
undervalued by society and are therefore paid less than jobs typically held by men. Third,
women are more likely than men to work part-time or temporarily exit the labor force at some
point during their careers, often to raise children. Such interruptions over one’s career can result
in lower earnings growth over time.4
Persistent discrimination over the course of women’s careers would exacerbate the gender wage
gap in older workers. Across myriad studies, a portion of the wage gap remains unexplained and
could be caused by persistent gender-based discrimination.5 Discrimination-based wage
differences early in women’s careers would be compounded over time and could explain the
larger pay gap for older women. A lifetime of lower earnings leaves older women more likely to
live in poverty than men.
The size of the gender pay gap for older workers varies by state. State-by-state analysis
conducted by the Joint Economic Committee reveals that there is a wide range in the gender pay
gap for older workers across states, ranging from a gap of 13 percent in Arkansas to a gap of 37
percent in Kentucky (see table). In nearly all states, the gender pay gap for older workers is
larger than the overall gender pay gap within the state. States where the gender pay gap for older
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Invest in Women, Invest in America:
I December 2010
A Comprehensive Review of Women in the U.S. Economy
I Joint Economic Committee
Table: Median Weekly Earnings by Age and Sex, 2009
State
Full-Time Workers 16 Years and Older
Men’s Median
Ratio,
Women’s
Weekly
Women's
Median
Earnings
Earnings to
Weekly
(Dollars)
Men's
Earnings
Earnings
(Dollars)
Gender
Wage Gap
for Workers
16 and older
Full-Time Workers 50 Years and Older
Ratio, Women's
Men's
Women’s
Earnings to
Median
Median
Men's Earnings
Weekly
Weekly
Earnings
Earnings
(Dollars)
(Dollars)
Gender Wage
Gap for
Workers 50
and older
Alabama
596
800
74.5%
25.5%
610
909
67.1%
Alaska
729
1009
72.2%
27.8%
n.a.
n.a.
n.a.
32.9%
n.a.
Arizona
654
860
76.0%
24.0%
667
939
72.6%
27.4%
Arkansas
547
620
88,2%
11.8%
654
752
87.0%
13.0%
California
753
849
88.7%
11.3%
856
1007
85.0%
15.0%
Colorado
723
873
82.8%
17.2%
773
1060
72.9%
27.1%
Connecticut
824
1099
75.0%
25.0%
891
1198
74.4%
25.6%
Delaware
699
825
84.7%
15.3%
n.a.
n.a.
n,a.
n.a.
District of Columbia
938
972
96.5%
3.5%
n.a.
n.a.
n.a.
n.a.
Florida
626
772
81,1%
18.9%
692
899
77.0%
23.0%
Georgia
664
789
84.2%
15.8%
727
870
83.6%
16.4%
Hawaii
620
761
81.5%
18.5%
673
890
75.6%
24.4%
24.0%
Idaho
578
724
79.8%
20.2%
612
805
76.0%
Illinois
636
851
74.7%
25.3%
673
963
69.9%
30.1%
Indiana
627
796
78.8%
21.2%
644
893
72.1%
27.9%
Iowa
625
777
80.4%
19.6%
656
861
76.2%
23.8%
Kansas
591
786
75,2%
24.8%
624
898
69.5%
30.5%
Kentucky
567
728
77.9%
22.1%
568
904
62.8%
37.2%
Louisiana
518
797
65.0%
35.0%
605
919
65.8%
34.2%
Maine
623
798
78.1%
21.9%
676
914
74.0%
26.0%
Maryland
797
913
87.3%
12.7%
843
1142
73.8%
26.2%
Massachusetts
797
1044
76.3%
23.7%
791
1234
64.1%
35.9%
Michigan
658
895
73.5%
26.5%
707
1041
67.9%
32.1%
Minnesota
733
877
83.6%
16.4%
758
1008
75.2%
24.8%
Mississippi
521
655
79.5%
20.5%
573
848
67.6%
32.4%
Missouri
596
773
77.1%
22.9%
614
893
68.8%
31.2%
Montana
549
710
77.3%
22.7%
n.a.
n.a.
n.a.
n.a.
Nebraska
607
752
80.7%
19.3%
692
S79
78.7%
21.3%
Nevada
635
787
80.7%
19.3%
645
905
71.3%
28.7%
New Hampshire
716
966
74.1%
25.9%
746
1067
69.9%
30.1%
New Jersey
761
994
76.6%
23.4%
868
1214
71.5%
28.5%
New Mexico
618
793
77.9%
22.1%
701
921
76.1%
23.9%
New York
720
858
83.9%
16.1%
738
949
77.8%
22.2%
North Carolina
617
698
88.4%
11.6%
625
864
72.3%
27.7%
North Dakota
570
757
75.3%
24.7%
n.a.
n.a.
n.a.
n.a.
Ohio
623
784
79.5%
20.5%
656
902
72.7%
27.3%
26.0%
Oklahoma
591
678
87.2%
12.8%
635
858
74.0%
Oregon
652
849
76.8%
23.2%
727
956
76.0%
24.0%
Pennsylvania
654
825
79.3%
20.7%
689
923
74.6%
25.4%
Rhode Island
701
901
77.8%
22.2%
n.a.
1025
n.a.
n.a.
South Carolina
581
724
80.2%
19.8%
595
795
74.8%
25.2%
South Dakota
567
698
81.2%
18.8%
n.a.
n.a.
n.a.
n.a.
Tennessee
580
735
78.9%
21.1%
636
854
74.5%
25.5%
Texas
596
732
81.4%
18.6%
671
896
74.9%
25.1%
Utah
608
809
75.2%
24.8%
696
888
78.4%
21.6%
Vermont
668
816
81.9%
18.1%
n.a.
n.a.
n.a.
n.a.
Virginia
705
877
80.4%
19.6%
782
1083
72.2%
27.8%
Washington
726
959
75.7%
24.3%
831
1151
72.2%
27.8%
West Virginia
603
753
80.1%
19.9%
660
894
73.8%
26.2%
Wisconsin
660
831
79.4%
20.6%
675
965
69,9%
30.1%
Wyoming
616
917
67.2%
32.8%
n.a.
n.a.
n.a.
n.a.
United States
657
819
80.2%
19.8%
713
953
74.8%
25.2%
n.a. = D ata is not available due to a small sam ple size.
Source: Joint Economic Committee Majority StafFbasedon data from the Bureau of Labor Statistics (BLS). Data for full-time workers 16 and older was published in BLS Report 1025, Highlights o f Women’s
Earnings in 2009, Table 3 (June 20 J0). Data for full-time workers 50 and older has not been previously published.
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Endnotes
1Bureau of Labor Statistics. Highlights of Women’s Earnings in 2009. June 2010.
2 See Joint Economic Committee. Women and the Economy 2010: 25 Years of Progress But Challenges
Remain. August 2010.
3Bureau of Labor Statistics. Highlights of Women’s Earnings in 2009. June 2010. Table 2.
4 CONSAD Research Corporation. An Analysis of the Reasonsfor the Disparity in Wages Between Men
and Women: Final Report. Prepared for U.S. Department of Labor, Employment Standards
Administration. January 12, 2009.
http://www.consad.com/content/reports/Gender%20Wage%20Gap%20Final%20Report.pdf
5 For example, and a summary of other relevant work, see Blau, Francine D. and Lawrence M. Kahn,
2006. "The U.S. Gender Pay Gap in the 1990s: Slowing Convergence." Industrial and Labor Relations
Review. 60(1): 45-66. http://www.nber.org/papers/wl0853.pdf.
6 See Joint Economic Committee. Women and the Economy 2010: 25 Years of Progress But Challenges
Remain. August 2010.
7Bureau of Labor Statistics. Current Population Survey. 2009 Annual Averages.
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Invest in Women, Invest in America:
I December 2010
A Comprehensive Review of Women in the U.S. Economy
I Joint Economic Committee
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
Comprehensive Health Care Reform: An Essential Prescription for Women
A Report by the Joint Economic Committee
Representative Carolyn B. Maloney, Chair
Senator Charles E. Schumer, Vice Chair
October 8, 2009
Executive Summary
The status-quo health insurance system is serving women poorly. An estimated 64 million
women lack adequate health insurance.1Over half of all medical bankruptcies impact a woman.2
For too many women and their families today, quality, affordable health care is out of reach.
Women are more vulnerable to high health care costs than men. Several factors explain why.
First, women’s health needs differ from men’s, so women are obliged to interact more regularly
with the health care system - regardless of whether they have adequate insurance coverage or
not. Second, women are more likely to be economically vulnerable and therefore face
devastating consequences when faced with a mounting pile of medical bills. The inability of the
current system to adequately serve women’s health care needs has come at great expense. One
recent study estimates that women’s chronic disease conditions cost hundreds of billions of
dollars every year.3
The following brief provides an overview of the basic facts regarding women’s insurance
coverage, and the consequences of our broken health insurance system on women’s health - both
physical and financial. Specifically:
•
Over one million women have lost their health insurance due to a spouse’s job loss
during the current economic downturn. Women have lost 1.9 million jobs since the
recession began in December 2007, and many of those women saw their health insurance
benefits disappear along with their paychecks.4 Second, women whose spouses lose their
jobs are also vulnerable to losing their health benefits, be-cause so many women receive
coverage through a spouse’s job-based plan. The Joint Economic Committee estimates
that 1.7 million women have lost health insurance benefits because of the contraction in
the labor market since December 2007. 68 per-cent (1,153,166) lost their insurance due to
a spouse’s job loss. 32 percent (547,285) of those women lost their insurance due to their
own job loss.
•
As a consequence of single mothers’ job loss, the Joint Economic Committee
estimates that at least 276,000 children have lost health insurance coverage.5 The
weak job market has been rough on single mothers; the number of unemployed female
heads of household has increased 40 percent over the past twelve months.6 For many of
these women, the loss of a job means not only a disappearing paycheck, but also the
disappearance o f employer-sponsored health insurance coverage for their families.
•
Women between the ages of 55 and 64 are particularly vulnerable to losing their
health insurance benefits because of their husbands’ transition from employer-
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Prepared by the Majority Staff of the Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
sponsored coverage to Medicare. One recent study concludes that a husband’s
transition from employer-sponsored coverage to Medicare at age 65 can be problematic
for his younger wife. Many of these wives depended on their spouse’s employer-based
coverage and are not yet age-eligible for Medicare. As a result, 75 percent of these
women reported delaying filling prescriptions or taking fewer medications than
prescribed because of cost.7
•
Younger women are particularly vulnerable to lacking adequate health insurance
coverage. Over one-quarter (26 percent) of all young women (ages 19-24) do not have
health insurance coverage. The weak job market has hit young workers particularly hard,
with the unemployment rate amongst young women at 15.5 percent in September 2009,
substantially higher than the national unemployment rate of 9.8 per-cent. The dismal job
market means that young women are less likely than ever to have access to job-based
coverage, and many women who once received coverage through a parent’s health
insurance plan have seen this coverage evaporate with their parents’ jobs.
•
39 percent of all low-income women lack health insurance coverage. Because of wide
variability in state Medicaid eligibility rules, millions of American women fall through
the safety net every day. The devastating impact o f the recession on state budgets has
forced some states to further tighten Medicaid eligibility rules at precisely the time when
need is growing fastest.
•
The health consequences of inadequate coverage are more severe for women than
for men. Women are more likely than men to run into problems receiving adequate
medical care. Over a quarter (27 percent) of women had health problems requiring
medical attention but were not able to see a doctor, compared to 21 percent of men.
Similarly, nearly a quarter (22 percent) of women reported that they were un-able to fill a
needed prescription, as compared to 15 percent o f men.
•
While the financial burden of inadequate health insurance coverage weighs heavily
on all Americans, uninsured and under-insured women suffer more severe economic
consequences than do men. Women are more likely than men to deplete their savings
accounts in order to pay medical bills. One-third of under-insured women deplete their
savings to pay medical bills, as compared to a quarter of under-insured men. The
disparity is comparable amongst the uninsured (34 percent of uninsured women as
compared to 29 percent of uninsured men).
The comprehensive health care reform proposals offered by the Obama Administration and
currently taking shape under the leadership of Democrats in the House and Senate include
numerous provisions that are critical to providing quality, affordable health care for all
Americans, both women and men. Many of these solutions are a key part of the prescription for
easing the burden on America’s women, for whom the status quo health care system is a failure.
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
Comprehensive Health Care Reform: An Essential Prescription for Women
The status-quo health insurance system poorly serves women. An estimated 64 million women
lack adequate health insurance.9 Over half of all medical bankruptcies impact a woman.10 For
too many women and their families today, quality, affordable health care is out of reach.
Women are more vulnerable to high health care costs than men. Several factors explain why.
First, women’s health needs differ from men’s, so women are obliged to interact more regularly
with the health care system - regardless of whether they have adequate insurance coverage or
not. Women’s reproductive health concerns, including pregnancy and childbirth, contraception,
and the consequences of sexually-transmitted diseases, require more contact with medical pro
viders.11 Women are more likely than men to have one or more chronic diseases, including
diabetes, asthma, and hypertension, all of which require ongoing coordinated care.12 Second,
women are more likely to be economically vulnerable and therefore face devastating
consequences when faced with a mounting pile of medical bills. Women comprise more than
half of America’s poor, and millions of working women continue to earn less than their male
counter-parts.13 Regardless of marital status, women are more likely to be responsible for their
children’s health and well-being.14
The inability of the current system to adequately serve women’s health care needs has come at
great expense. One recent study estimates that women’s chronic disease conditions cost hundreds
of billions of dollars every year.15 The direct costs of women’s cardiovascular disease, which
impacts 43 million American women, are estimated at $162 billion annually. The direct medical
costs of diabetes on women total over $58 billion. The direct medical costs of osteoporosis,
which impacts 8 million women, are estimated at nearly $14 billion annually. The direct medical
costs of breast cancer are estimated at $9 billion.
The following brief provides an overview of the basic facts regarding women’s insurance
coverage, and the consequences of our broken health insurance system on women’s health - both
physical and financial.
Women are no more likely than men to be uninsured, but the sources of women’s health
insurance policies are quite different from men’s. As a result, women are especially
vulnerable to losing their health insurance coverage.
Because women are less likely than men to be employed full-time, they are less likely to be
eligible for employer-provided health benefits. 27 percent of employed women work part-time,
and are therefore excluded from their employers’ health insurance benefit plans. In contrast, just
13 percent of working men are part-time employees.16
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Prepared by the Majority Staff of the Joint Economic Committee
In vest in W om en, In vest in A m erica:
A Comprehensive Review of Women in the U.S. Economy
I D ecem b er 2010
I Joint Economic Committee
Figure 1. Health Insurance Status of Non-Elderly Adults
100%
90 %
80 %
70 %
60 %
50 %
40 %
30 %
20 %
10%
0%
W om en
M en
Pvon-etaeriyadiiits are ages 18-64. Nurrbers may n o isu rr to lO u -i cue to rounding.
Source JsintEcon orri; Ccrrrrittee calculations ?rcrr the 2009 A5EC Supsslerr-entto the C3S
Women are nearly twice as likely as men to depend on a family member (typically a spouse) for
health insurance benefits. 25 percent of non-elderly women receive health insurance coverage as
a dependent on a family members’ job-based health insurance plan, as compared to just 13
percent of men. Women are particularly vulnerable to losing health insurance coverage when
they are dependent on someone else for their benefits.
First, the weak job market means that a woman is vulnerable to losing employer-based coverage
because of loss of her own job or her spouse’s job loss. Women have lost 1.9 million jobs since
the recession began in December 2007, and many of those women saw their health insurance
benefits disappear along with their paychecks.17 Many more women have lost their employerprovided health insurance benefits as businesses have cut back on employees’ hours. 3.3 million
women who usually work full-time are currently working part-time because full-time work is not
available, more than twice as many than when the recession began in December 2007. Many of
these women are no longer eligible for employer-sponsored coverage.18 As noted above,
women’s health insurance coverage is impacted not only by their own employment, but also by
their spouse’s employment. Women whose spouses lose their jobs are also vulnerable to losing
their health benefits, because so many women receive coverage through their spouses’ job-based
plans. Men have lost 5 million jobs since the recession began, resulting in over one million wives
losing their health insurance coverage and joining the ranks of the uninsured. The combination of
women’s job loss and their spouse’s job loss means that women are doubly vulnerable to losing
their health insurance coverage in today’s weak economy.
Using these job loss statistics and the share of men and women receiving health insurance
benefits through employer-sponsored plans, we estimate that 1.7 million women have lost health
insurance benefits because of the contraction in the labor market since December 2007. 32
percent (547,285) of those women lost their insurance due to their own job loss. 68 percent
(1,153,166) lost their insurance due to a spouse’s job loss. In contrast, 3.1 million men have lost
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D ecem b er 2010
Joint Economic Committee
insurance on the individual market pays 45 percent more in monthly premiums for the exact
same plan purchased by a 25 year-old male.~"
Adult women comprise 38 percent of the uninsured. Certain groups of women are far more
likely to be uninsured or under-insured than others. While just 18 percent of all women are
uninsured, much larger shares of certain groups of women are left without coverage today.
Figure 3 Distribution of the uninsured, (Total=46.3 million)
C hilcren are unaer IS /ears olcs.
Source io m f E con om ic C om m itte e calculations fro m th e 2009 A S E C S u p p le
Roughly one quarter (24 percent) of all single mothers do not have health insurance coverage. 37
percent of all children without health insurance live in single-parent families, the vast majority of
which are headed by a working single mother.23 The weak job market has been rough on single
mothers; the number of unemployed female heads of household has increased 40 percent over
the past twelve months.24 For many of these women, the loss of a job means not only a
disappearing paycheck, but also the disappearance of employer-sponsored health insurance
coverage.
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The safety net program covers just 45 percent o f low-incom e Americans, leaving millions o f
low-income women without access to affordable health insurance coverage.29 Facing serious
budgetary pressures due to the recession, some states have further pared back Medicaid
eligibility and/or benefits at precisely the time when increasing numbers o f families desperately
need access to public benefits.30
Figure 5. Un-and Underinsured Women, by Income
■ Uninsured at any tim e in past year
78%
-
All
Low Income
■ Insured all year, underinsured
Moderate Income
Middle Income
U n d e r in s u re d is d e fin e d as in s u re d ail yea r b u t e x p e rie n c e d o n e o f th e fo llo w in g : m e d ica l e x p e n se s e q u a le d
e q u a le d 5
%
o r m o re o f in c o m e if lo w in c o m e (<2O0?cFPL); o r d e d u c tib le s e q u a le d 5
%
High Income
o r m o re o f in c o m e ; m e d ica l e xp en ses
o r m o re o f in c o m e . S u b g ro u p s may n o t sum, to ta l because o f ro u n d in g .
Lo w in c o m e is < $ 2 0k. m o d e ra te in c o m e is $ 2 0 k -S 3 9 .9 k , m id d le in c o m e is $ 4 0 k -$ 5 9 .9 k , high in c o m e is $ 6 Q k o r g re a te r.
So urce: T he C o m m o n w e a lth Fund B ie nn ia l H ea lth in s u ra n ce S u rve y, 20 07 .
While millions o f women lack access to health insurance, millions more women are
“underinsured,” or covered by health insurance benefits that leave them vulnerable to significant
financial hardship. Under an expanded definition o f lack o f access to health insurance coverage
that includes both the uninsured and underinsured, the percentage o f women lacking adequate
health coverage rises to 45 percent. Over three-quarters (78 percent) o f low-income women lack
adequate coverage. 60 percent o f moderate-income women lack adequate coverage. Even
amongst relatively w ell-off Americans, access to adequate coverage remains tenu-ous.31
Health insurance coverage also varies substantially by race. Minority women, especially Hispanics and Native Americans, have the greatest rates o f non-insurance - 36 percent o f Hispanic
women lack health coverage, as do 32 percent o f Native American women.
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j December 2010
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I Joint Economic Committee
Uninsured women are far less likely than other women to receive recommended preventative
care. Over half (55 percent) of women over age 50 have not received the recommended
mammogram, a critical screen for breast cancer that allows providers to catch cancer in its early
and treatable stages when conducted on a regular basis. Over a third (37 percent) of uninsured
women have not received the recommended pap smear, a critical screen allowing for early
detection of cervical cancer. And 40 percent of uninsured women do not have access to a regular
doctor.
Significant and troubling racial disparities in women’s access to preventative care exist. The high
cost of medical care and lack of access to affordable health insurance coverage are likely to
explain much of the disparity. Nearly a quarter (23 percent) of minority women report that they
were unable to visit a doctor due to cost, as compared to 15 percent of white women. Lack of
access to medical care due to cost is particularly problematic for Native American and His-panic
women, with 26 percent and 27 percent respectively reporting no doctor’s visit in the last year
due to prohibitive costs. Access to dental coverage remains highly unequal, with 36 per-cent of
all minority women reporting no dental check-up in the last two years as compared to 25 percent
of white women. Some preventative medical care remains underutilized by all women,
regardless of race. Despite recommendations from the American Cancer Society that all women
over 40 receive annual mammogram exams, a quarter of all women report no mammogram in the
i
last two years. 37
Women’s reproductive health is severely compromised by un- and under-insurance, with
consequences for both women and their children.
The average American woman will spend roughly five years being pregnant, recovering from
pregnancy or trying to get pregnant, and three decades trying to avoid an unintended preg
nancy.38 Women’s specific health concerns regarding pregnancy and childbirth, access to safe
and affordable contraception, and the severe consequences of sexually transmitted diseases re
quire continuous engagement with the health care system.
The consequences of poor access to reproductive health care are severe for women. Women are
more likely than men to contract serious sexually-transmitted diseases, including genital herpes,
gonorrhea, and Chlamydia, and limited access to regular medical care reduces the likelihood of
early detection and effective treatment of these diseases.39 Women without health insurance are
30 percent less likely to use contraceptive methods requiring a prescription, which are more
effective at preventing unintended pregnancies than over-the-counter birth control methods
alone.40 Reproductive health care providers often provide the screenings for female-specific
diseases (including breast, cervical, ovarian, uterine, and endometrial cancers) that are less likely
to prove fatal with early screening and treatment. Yet limited access to regular care diminishes
the likelihood of preventative screenings, as noted above, and further compromises women’s
reproductive health.
Women’s limited access to quality, affordable health care also compromises children’s health.
Quality pre-natal and post-partum care is strongly linked to healthy outcomes for new infants as
well as their mothers. 1 Large disparities in maternal mortality and infant health persist by race
and income, suggesting a link between health care access and health outcomes.4"
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I Joint Economic Committee
Figure 15. Non-Elderly Adults with Medical Bill Problems in the Last
Year, by Insurance Status and Gender
■ Men
■ Women
60%
All
Insured all year, not
underinsured
Insured all year,
underinsured
Uninsured at any time
"M edical bill problem s" sre defined as one or m ore o f the follow ing: problem s or inability to pay m edical bills: contacted by s co llection agency regarding
unpaid medical bills: had to change way of life to pay m edical bills. U nderinsured is defined as insured all year but e xp e rie n ce d one of the following: medical
expenses e qualed lO^a or more of incom e; m edical e xp e n se s equaled 5 ? io r more of incom e if low incom e (< 2 0 0 % o f the fed eral poverty hnej; or deductibles
equaled 5 % or more or incom e. No n-elderly adults are ages 19-64.
So u rce-T h e Com m onwealth Fund Biennial Health Insurance Survey. 2007
Figure 16. Non-Elderly Adults Depleting Savings to Pay Medical Bills,
by Insurance Status and Gender
■ Men
All
■ Women
Insured all year, not
underinsured
Insured all year,
underinsured
Uninsured at any time
Under insured is defined as insured ell year but e xp e rie n ce s o r e c f the following: medical e xpe nse s equaled 10% or more o f incom e; m edical expenses
equaled S% or more of incom e if low incom e (^ 2 00 ?sof the fe d eral po verty line); or dedu ctib les equaled 5% or m ore of incom e. Non-elderly adults are
ages 19-64.
'
Source' The Com m onwealth Fund Biennial Health insurance Survey. 2037.
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December 2010
Joint Economic Committee
Inadequate insurance coverage not only puts women’s physical health in danger; it also
imperils women’s financial health. Women bear a heavier financial burden due to un- and
under-insurance than do un- and under-insured men.
37 percent of women had medical bill problems in the last year, as compared to 29 percent of
men. Amongst the under-insured, 57 percent of women had medical bill problems as compared
to 47 percent of men. Amongst those with no insurance at all, the share of both men and women
with medical bill problems are even more dramatic - 60 percent of uninsured women and 51
percent of uninsured men.
Many Americans are taking desperate measures to cope with the medical bills that pile up
following an illness. Women are more likely than men to deplete their savings accounts in order
to pay medical bills. One-third (33 percent) of under-insured women deplete their savings to pay
medical bills, as compared to a quarter (25 percent) of under-insured men. The disparity is com
parable amongst the uninsured (34 percent of uninsured women as compared to 29 percent of
uninsured men).
Comprehensive health-care reform is critical to women’s physical and financial health. By
simultaneously addressing coverage issues and health care costs, Congress will be tackling
two problems that weigh heavily on women and their families - lack of access to affordable
coverage and skyrocketing medical costs for those who do have insurance. Specifically:
•
A ban on gender rating will put an end toward discriminatory practices that charge
women substantially more than similarly-situated men for the same health benefits
policies. America’s health insurers support this reform, recognizing that gender rating is
unfair to our nation’s mothers and daughters.43
•
A ban on denial o f coverage based on pre-existing conditions ( “guaranteed issue’’’) will
ensure that individuals are not denied insurance coverage because of a medical condition.
For millions of breast cancer survivors and others with diseases specific to women,
guaranteed issue will make insurance coverage accessible and affordable.
•
Inclusive health insurance “exchanges ” will expand access to health insurance coverage
for the millions of women who are not offered employer-based coverage or for those
whom employer-based offerings are not adequate or affordable, especially those who
work part-time and are thus ineligible for benefits and for women who lose their coverage
when an older spouse becomes eligible for Medicare.
•
By requiring well-visits and preventative medicine with no cost-sharing as part of any
policy offered by an insurer participating in the health insurance exchange, health care
reform will expand access to necessary and cost-effective preventative screenings and
treatments for all women.
•
Caps on out-of-pocket spending for any policy offered through the health insurance
exchange will insure that a medical crisis no longer comes with the risk of a family
financial crisis. Prohibiting insurers from nullifying previously-offered coverage after
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I December 2010
I Joint Economic Committee
costs have been incurred (no “rescissions ”) will give families peace of mind in knowing
that their health insurance policies must cover what they promise to cover; the rules of
the game can no longer be changed mid-way through the process. For the millions of
women diagnosed requiring medical attention each year, this security is key.
•
The goal of health care reform is to provide affordable health insurance to all Americans,
whether or not they have access to employer-provided health insurance benefits. A public
option may be one of the cheapest ways to ensure that all Americans have access to an
affordable, quality insurance plan that meets certain standards.
•
Public subsidies to help middle-income families pay for health insurance coverage will
be a boon for women, whose earnings are typically lower than men’s.44 Medicaid
expansions will disproportionately benefit women, who are more likely than men to be
poor. 45
The proposals under discussion would allow the millions of American women who are satisfied
with their health care coverage and their medical care to maintain the status quo. But it would
provide an important and urgent set of solutions for the 64 million women without adequate
health insurance. The time has come for comprehensive health care reform.
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December 2010
Joint Economic Committee
Endnotes
1. Rustgi, Sheila et al. 2009. Women at Risk: Why Many Women Are Foregoing Needed Health Care.
Washington, D.C.: The Commonwealth Fund.
(http://www.c0mm0nwealthfund.0rg/~/media/Files/Publicati0ns/Issue per-cent20Brief/2009/Mav/Women
percent20at percent20Risk/PDF 1262 Rustgi women at risk issue brief Final.pdf).
2. Himmelstein, David et al. 2009. “Medical Bankruptcy in the United States, 2007: Results of a National
Study.” The American Journal of Medicine. 122(8)(August 2009).
(http://pnhp.org/new bankruptcy studv/Bankruptcy-2009.pdf).
3. Wood, Susan et al. 2009. Women’s Health and Health Care Reform: The Economic Burden of Disease
in Women. Washington, D.C.: The Jacobs Institute of Women’s Health at the George Washington
University School of Public Health and Health Services.
4. The most recent data available are for August 2009.
5. Had the 111th Congress not expanded the State Children’s Health Insurance Program (S-CHIP)
eligibility this winter, the number of children losing health coverage likely would be even greater.
6. The most recent data available are for September 2009. See also the Joint Economic Committee’s May
2009 report on working mothers in the recession, Women in the Recession: Working Mothers Face High
Rates of Un-employment, (http://jec.senate.gov~).
7. Schumacher, Jessica R., et al. 2009. “Insurance Disruption Due to Spousal Medicare Transitions:
Implications for Access to Care and Health Utilization for Women Approaching Age 65.” Health Services
Research 44(3)(June). (http://www.hsr.org/hsr/abstract.isp?aid=44347877138).
8. Bureau of Labor Statistics Household Survey. Data are for women ages 16-24, with the most recent
data available are for September 2009.
9. Rustgi, Sheila et al. 2009.
10. Himmelstein, David et al. 2009.
11. Chavkin, Wendy and Sara Rosenbaum. 2008. “Women’s Health and Health Care Reform: The Key
Role of Comprehensive Reproductive Health Care.” New York, New York: Columbia University
Mailman School of Pub-lic Health, (http://www.iiwh.org/attachments/Women percent20and
percent20Health percent20Care percent20Re-form.pdf).
12. Patchias, E. and Waxman J. 2007. Women and Health Coverage: The Affordability Gap. Washington,
D.C.: The Commonwealth Fund and the National Women’s Law Center.
(http://www.nwlc.org/pdf/NWLCCommonwealthHealthInsuranceIssueBrief2007.pdf).
13. Institute for Women’s Policy Research. 2009. The Gender Wage Gap: 2008. Washington, D.C.:
Institute for Women’s Policy Research, (http://www.iwpr.org/pdf/C350.pdf). Cawthome, Alexandra.
2008. “The Straight Facts on Women in Poverty.” Washington, D.C.: Center for American Progress.
(http://www.americanprogress.org/issues/2008/10/women poverty.html).
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
14. U.S. Census Current Population Survey. 2009. America’s Families and Living Arrangements: 2008.
See Table FG5. (http://www.census.gov/population/www/socdemo/hh-fam/cps2008.html). See also the
Kaiser Family Foundation’s 2004 Women’s Health Survey.
(http://www.kff.org/womenshealth/upload/2004-Kaiser-Women-s-Health-Survey-Presentation.pdf).
15. Wood, Susan et al. 2009.
16. Joint Economic Committee calculations from Bureau of Labor Statistics Household Survey. The most
recent data available are for September 2009.
17. The most recent data available are for August 2009.
18. Joint Economic Committee calculations from Bureau of Labor Statistics Household Survey. The most
recent data available are for September 2009.
19. The Joint Economic Committee’s calculations incorporate the number of jobs lost by men and
women, the prob-ability that a given individual had an employer-sponsored plan (either as a policy-holder
or as a dependent), as well as industry-specific weights to account for the distribution of job losses and
health insurance across indus-tries. We compute job-loss related health insurance losses separately for
each gender. Data for industry-specific health insurance coverage status by gender comes from the March
2008 Supplement to the Current Population Survey (CPS), which is the most recently available detailed
data on health insurance coverage. Data on job loss comes from the Bureau of Labor Statistics’
Establishment Survey, from December 2007 through August 2009 representing the most current available
detailed data. Data for industry-specific marriage rates by gender are from the June 2009 CPS, the most
recent data available. A complete methodological appendix is available from the Joint Economic
Committee upon request.
20. In one recent nationally-representative survey, amongst employers who reported taking steps to
reduce costs in the last 12 months, 29 percent reported reducing health care benefits or increasing
employee costs as a in the last 12 months. See Galinsky, Ellen and James. T. Bond. 2009. The Impact of
the Recession on Employers.” Washing-ton, D.C.: Families and Work Institute.
21. Schumacher, Jessica R., et al. 2009.
22. National Women’s Law Center. 2008. Nowhere to Turn: How the Individual Health Insurance Market
Fails Women. Washington, D.C.: National Women’s Law Center.
(http://action.nwlc.org/site/PageNavigator/nowheretotum Report). See the final section on recommended
policy prescriptions for a widely-agreed upon fix to the problem of discriminatory gender rating practices.
23. Joint Economic Committee calculations using data from the U.S. Census Bureau 2009 ASEC
Supplement, Table HI08. Health Insurance Coverage Status and Type of Coverage by Selected
Characteristics for Children Under 18: 2008.
(http://www.census.gov/hhes/www/cpstables/032009/health/h08 000.htm).
24. Joint Economic Committee calculations from Bureau of Labor Statistics Household Survey, current as
of September 2009.See the Joint Economic Committee’s May 2009 report on working mothers in the
recession, Women in the Recession: Working Mothers Face High Rates of Unemployment.
(http://iec.senate.gov).
25. The Joint Economic Committee’s calculations incorporate the change in the number of employed
female heads-of-household, the number of children impacted by that change, and the probability that
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those children received health insurance through a mother’s employer. Because data on the number of
employed female heads-of-household from Bureau of Labor Statistics Household Survey are not
seasonally-adjusted, the Joint Economic Committee uses the annual change in the number of employed
female heads-of-household from September 2008 to September 2009, rather than the change over the
course of the recession. Had the 111th Congress not expanded the State Children’s Health Insurance
Program (S-CHIP) eligibility this winter, the number of children losing health coverage likely would be
even greater.
26. FamiliesUSA. 2009. Understanding COBRA and Mini-COBRA Premium Assistance. Washington,
D.C. FamiliesUSA. (http://www.familiesusa.org/issues/private-insurance/understanding-cobrapremium.html V
27. Bureau o f Labor Statistics Household Survey. Data are for women ages 16-24, with the most recent
data avail-able are for September 2009.
28. Collins, SaraR. April 23, 2009. Young and Vulnerable: The Growing Problem of Uninsured Young
Adults and How Policies Can Help. Washington, D.C.: Commonwealth Fund.
(http://www.commonwealthfund.Org/~/media/Files/Publications/Testimony/2009/Apr/Testimonv
percent20Young percent20and percent20Vulnerable/1264 Collins New York Civ council hearing young adults 04232009 testimony.pdf): National
Conference on State Legislatures, 2008. Covering Young Adults Through Their Parents ’ or Guardians ’
Health Policy.
(http://www.ncsl.org/issuesresearch/health/healthinsurancedependentstatus/tabid/14497/default.aspx~).
29. Under federal rules, state Medicaid programs must cover pregnant women and children under age 6
whose family incomes are below 133 percent of the federal poverty line and children age 6 to 18 whose
family incomes are be-low 100 percent of the federal poverty line. Beyond that, the federal government
allows states to set their own eligibility guidelines. In some states, such as Louisiana, out-of-work
families qualify for Medicaid only if their in-comes are at least 11 percent below the federal poverty line
($2,426 for a family of four). Unemployment benefits are counted as income, which means that many
unemployed families find themselves without health insurance, but with too much income to qualify for
Medicaid. See Galewitz, Phil. “Medicaid: True or False?” Kaiser Health News, July 1, 2009.
30. Numerous states have already enacted limits to Medicaid eligibility, and several more are considering
proposed cuts. See, for example: Kelley, Debbie. “Advocates say Medicaid cuts will hurt
developmentally disabled.” Denver Post, July 1, 2009.
('http://www.denverpost.com/breakingnews/ci 12733118~): California Budget Project. June 1, 2009. More
Than 1.9 Million Californians Could Lose Access to Health Coverage Under the Governor’s May Re
vision. Sacramento, CA: California Budget Project.
(http://www.cbp.org/documents/090521 Health Cuts Statewide Fact Sheet.pdf).
31. Note that the definition of “low-income” varies somewhat here because the data is from a separate
survey. In-come groups are defined according to absolute dollar values rather than in terms of the federal
poverty line. For instance, low-income is defined as under $20,000 rather than 100 percent of the federal
poverty line.
32. Difficulty obtaining needed care is defined as reporting any one of the following four problems: 1) did
not fill a needed prescription 2) did not see a needed specialist 3) skipped a recommended medical test,
treatment, or follow-up 4) had a medical problem but did not visit a doctor or clinic.
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
33. U.S. Census Bureau . Income, Poverty, and Health Insurance Coverage in the United States: 2008.
(http://www.census.gov/prod/2009pubs/p60-236.pdf)
34. U.S. Census Current Population Survey. 2009. America’s Families and Living Arrangements: 2008. r
See Table FG5. (http://www.census.gov/population/www'socdemo/hh-fam/cps2008.html').
35. For a literature review on the health benefits of prevention, see Partnership for Prevention. 2007.
Preventative Care: A National Profile on Use, Disparities, and Health Benefits. Washington, D.C.:
Partnership for Prevention, (http://www.prevent .org/images/stories/2007/ncpp/ncpp percent20preventive
percent20care percent20report .pdf). For a review of the economic arguments for prevention, see Woolf,
Steven H. 2009. “A Closer Look at the Economic Arguments for Prevention.” Journal of the American
Medical Association 301(2009):536-538. (http://iama.ama-assn.org/cgi/content/full/301/5/536)
(subscription required). See (http://www.rwif.org/pr/product.jsp?id=38410) for a free abstract.
36. The Kaiser Family Foundation. 2004 Kaiser Women’s Health Survey.
37. Note that some studies have found significant racial differences in the timing of mammograms. For
instance, a recent study found that 18 percent of white women with breast cancer were inadequately
screened with mammography prior to breast cancer, as compared to 34 percent of African-American
women with breast cancer. See Smith-Bindman, Rebecca. 2006. “Does utilization of screening
mammography explain the racial and ethnic differences in breast cancer?” Annals of Internal Medicine
144(8): 614-6. (http://www.ncbi.nlm.nih.gov/pubmed/16618951 ?ordinalpos=l &itool=EntrezSvstem2.PEntrez.Pubmed.Pubmed ResultsPanel.Pubmed DiscoveryPanel.Pubmed
RVAbstractPlus); Chan, Nancy. April 17, 2006. “Mammography screenings for breast cancer show racial
and ethnic dis-parities.” UCSF News Office, (http://news.ucsf.edu/releases/mammographv-screeningsfor-breast-cancer-show-racial-and-ethnic-disparities/).
38. Chavkin and Rosenbaum. 2008.
39. Alan Guttmacher Institute. 2002. Sexual and Reproductive Health: Women and Men.
(http://www.guttmacher.org/pubs/fb 10-02.pdf).
40. Culwell, Kelly R. and Joe Feinglass. 2007. “The Association of Health Insurance with Use of
Prescription Contraceptives.” Perspectives on Sexual and Reproductive Health 39(4): 224-230. For data
on the efficacy of prescription versus over-the-counter birth control methodologies, see the Mayo Clinic’s
Birth Control Guide (http://www.nlm.nih.gov/medlineplus/birthcontrol.html).
41. McCormick, Marie C. and Joanna E. Seigel. 1999. Prenatal Care: Effectiveness and Implementation.
New York, NY: Cambridge University Press; Butz, Arlene M. et al. 1993. “Infant Health Care Utilization
Predicted by Pattern of Prenatal Care.” Pediatrics. 92(1): 50-54; Conway, Karen Smith and Andrea
Kutinova. 2006. “Maternal Health: Does Prenatal Care Make a Difference?” Health Economics 15(5):
461-488; Centers for Disease Control and Prevention Health Resources and Services Administration.
Healthy People 2010, esp. Chapter 16, “Maternal, Infant, and Child Health.”
(http://www.healthvpeople.gOv/document/HTML/Volume2/16MICH.htm# Toc494699663).
42. Chavkin and Rosenbaum. 2008.
43. The health insurance industry’s trade group, AHIP, has repeatedly stated its support for a ban on
discriminatory rating practices, including gender rating. See, for example, Edney, Anna. 2009. “AHIP
Pleads Its Case: Regulate Us.” National Journal. May 6, 2009.
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('http://undertheinfluence.nationalioumal.com/2009/Q5/ahip-pleads-its-case-regulate.php). The insurance
industry recognizes that discriminatory rating practices drive down coverage rates, as shown in multiple
empirical studies. See, for example, Wachenstein, Leigh and Hans Leida. 2007. “The Impact of
Guaranteed Issue ad Community Rat-ing Reforms on Individual Insurance Markets.” Seattle, WA:
Milliman, Inc. (http://www.ahip.org/content/default.aspx?docid=20736Y Note that the ban on gender
rating practices is often referred to as part of the “guaranteed issue” policy, which would prohibit insurers
from denying coverage based on pre-existing conditions, race, gender, or other basic characteristics.
44. Institute for Women’s Policy Research. 2009.
45. Cawthome, Alexandra. 2008.
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Prepared by the Majority Staff of the Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Expanding Access to Paid Sick Leave:
The Impact of the Healthy Families Act on America’s Workers
A Report by the Joint Economic Committee
Representative Carolyn B. Maloney, Chair
Senator Charles E. Schumer, Vice Chair
March 2010
Executive Summary
Paid sick leave is a critical element of job security for American workers, yet forty percent of
employees in the private sector today have no such leave.1 For many workers, a day home sick or day off of work to care for a sick child - means forgoing a paycheck. At a time when millions
of families are living paycheck to paycheck, the lack of paid sick leave forces sick employees to
go to work and sick children to attend classes. Going to work sick or “presenteeism” is a public
health issue, with sick workers spreading contagious disease to fellow co-workers and customers.
The reduced productivity of workers who come to work sick and spillover impacts on other
employees is bad for businesses.2 The provision of paid sick leave through the Healthy Families
Act would dramatically expand access to paid sick leave, with salutary effects for society as a
whole as well as the families for whom it would impact.
This report represents the first estimates of the impact of the Healthy Families Act (S. 1152 and
H.R. 2460) on access to paid sick leave. The bill would guarantee that workers in the United
States at firms that employ at least 15 employees accrue at least one hour of paid sick leave for
every 30 hours worked.
Using a combination of published and unpublished data from the Bureau of Labor Statistics, the
Joint Economic Committee estimates:
•
As a result of the Healthy Families Act, at least 30.3 million additional workers would
have access to paid sick leave.3
•
The Healthy Families Act would significantly expand access to paid sick leave for many
of America’s most vulnerable workers, including lower-wage workers, women, and
minorities.4
o
Almost half of the increased access to paid sick leave (14.7 million additional
workers) would accrue to workers in the bottom wage quartile.
o
Nearly half (13.3 million workers) of the increased access to paid sick leave
would accrue to women workers.
o
Almost one-third of the increased access to paid sick leave would accrue to
minority workers, including 3.9 million additional African-American workers and
5.6 million additional Latino workers.
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•
December 2010
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The Healthy Families Act would also significantly expand access to paid sick leave for
workers in professions with critical public health implications. For instance, 5.9 million
additional food service and preparation workers would have access to paid sick leave due
to the Healthy Families Act.5
Introduction
Paid sick leave is a critical element of job security and quality for American workers, yet forty
percent of private sector workers today have no such leave.6 Paid sick leave not only gives
workers the opportunity to regain their health. Paid leave also allows employees to return to
work fully productive, and helps stop the spread of disease to co-workers and customers. As a
result, paid sick leave can reduce employers’ overall costs while simultaneously contributing to
the health of the nation. The United States is amongst only a handful of nations that has no
legislation requiring paid sick leave for workers.7 Voters agree that paid sick days are a critical
aspect of job quality. 86 percent of Americans favor a law that guarantees paid sick leave for all
workers.8
The recession has hammered home the impossible choice a sick worker faces when forced to
decide between a paycheck and his or her health. The weak labor market means that many
families are living paycheck-to-paycheck, and simply cannot afford to forgo money or to put
their job in jeopardy. Yet millions of workers are unable to miss work without forgoing a
paycheck - or risking job loss. 17 percent of Americans report that they have lost a job or were
told they would lose their job if they took time off due to personal or family illness.9
Evidence suggests that employers have been rolling back sick leave coverage in recent years,
particularly for low-wage workers who are already struggling to make ends meet. In New York
City, for instance, paid sick leave coverage for near-poor workers decreased from 56 percent in
2007 to just 33 percent in 2009.10 As a result, millions of employees go to work sick every day,
exposing their colleagues and customers to illness and dragging down productivity. 68 percent of
workers without paid sick leave have gone to work with symptoms of a contagious illness such
as the flu, compared to 53 percent of those with paid sick leave.11 A worker who goes to work
sick rather than staying home and resting may end up even sicker, eventually leading to longer
absenteeism from work.
The H1N1 outbreak in the spring of 2009 further highlighted the problem with the status quo of
no federal policy around paid sick leave. The Centers for Disease Control and Prevention (CDC)
recommended “social-distancing” as a strategy for prevention, asking workers with flu-like
symptoms to remain home and away from others until 24 hours after all symptoms have
resolved.12 Yet millions of workers face economic hardship if they heed the CDC’s advice,
because remaining home means forgone wages. When Americans were asked about likely
problems they would encounter with staying home for the standard course of the H1N1 virus, the
most frequent answer (44 percent) was that they or a household member would “lose pay and
have money problems,” and 25 percent reported that they would be likely to lose their job or
business.13
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A Comprehensive Review of Women in the U.S. Economy
D ecem b er 2010
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To make matters worse, workers in occupations with critical public health implications have very
low rates of access to paid leave. For instance, just 27 percent of food preparation and food
service workers have access to paid sick leave. Similarly, just 27 percent of child care workers
have access to paid sick leave.1 These workers are amongst America’s lowest-paid, with
average annual wages of around $20,000 - half the national average annual wage.13
The Healthy Families Act (S. 1152 and H.R. 2460) would have a substantial impact on job
quality and job security for American workers. The Healthy Families Act would guarantee that
workers in the United States at firms that employ at least 15 employees accrue at least one hour
of paid sick leave for every 30 hours worked. As a result of this legislation, at least 30.3 million
additional workers would have access to paid sick leave.16 The Healthy Families Act would
significantly expand access to paid sick leave for many of America’s most vulnerable workers,
including lower-wage workers, women, and minorities. The Healthy Families Act would also
significantly expand access to paid sick leave for workers in professions with critical public
health implications, including food services.
The Healthy Families Act Expands Paid Sick Leave Access for Private Sector Workers
The Healthy Families Act would dramatically expand access to paid sick leave for private-sector
workers. Currently, just 61 percent of the private-sector workforce (62.4 million workers) has
access to paid sick leave. This means that nearly 40 million private-sector workers do not have
access to paid sick leave today.17 30.3 million additional workers would receive coverage under
the Healthy Families Act, bringing coverage levels up to over 90 percent in the private-sector
workforce.18
Specifically, the Healthy Families Act would increase access to paid sick leave for all workers in
firms with 15 or more employees. Today, just 64 percent (53.8 million) of those workers have
access to paid sick leave. The Healthy Families Act would guarantee that all workers in those
firms had access to paid sick leave, adding coverage to 30.3 million new workers with the end
result that all 84.1 million Americans in firms with more than 15 employees would have access
to paid leave. 19
Figure 1. Over 30 Million Additional Workers Gain Access
to Paid Sick Leave Under the Healthy Families Act
N ew ly Covered Under HFA =
30 3 million
workers
C urrently Covered -
53.8 m illio n
w orkers
HFA increases paid sick
leave access by 56%.
N ew ly covered
w o rk e rs + c u rre n tly
covered w orkers =
84.1 m illio n
Am ericans w ith
access to paid sick
leave und e r HFA
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The Healthy Families Act Expands Access to Paid Sick Days for Women
Because the economic hardship associated with a day of unpaid leave is particularly acute for
women, access to paid sick leave is of particularly importance for this group of workers. This is
especially true for female heads of household, who are solely responsible for their families’
wellbeing. Largely because of their sole-eamer status, female headed households are amongst the
nation’s poorest, with nearly 29 percent of female-headed households falling below the poverty
level. 23
Two-thirds (64.3 percent) of mothers work outside the home, and women’s earnings make up a
substantial share of family income.24 The typical working wife now brings home 42.2 percent of
her family’s earnings, which means that families are dependent on women’s earnings for their
financial well-being.25 While women’s work outside the home is of paramount importance,
mothers still bear primary responsibility for a child’s health.26 80 percent of mothers assume
primary responsibility in the family for taking their children to doctor’s appointments. Half of all
working mothers must miss work if their child is sick, compared to 30 percent of working
fathers. And half of all working mothers who do stay home with children when they are sick
report that they do not get paid when they must do so.27 Access to paid sick leave is thus of
particular importance for working women because of the double burden they face - both self
care and care for an ill child.
Currently, more than a third (37 percent) of working women in establishments with more than 15
employees lacks access to paid sick leave. The Healthy Families Act would expand access to
paid sick days to an additional 13.3 million female workers in these firms, raising the number of
women with paid sick leave access to over 40.9 million. This represents a 48 percent increase in
the share of working women with access to paid sick leave.28
Figure 3. O ver 13 M illion A dditional W orking W om en Gain
A ccess to Paid Sick Leave U nder th e H ealthy Families Act
HFA increases paid sick
Newly-Covered Under HFA =
Currently-Covered =
13 3 m illio n
w o rk e rs
2 7.6 m illio n
w o rk e rs
leave access by 48% for
working w om en.
Newly-covered
workers + currentlycovered workers =
40.9 million
working w om en
with access to paid
sick leave under
HFA
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ill. Moreover, many of those workers in occupations with critical public health implications are
amongst America’s lowest-paid. Child care workers earn an average of $20,350 annually, while
food preparation workers typically earn an average of $20,220 annually.32 These figures are less
than half the national average annual wage for all occupations, $42,270, which suggests that
workers in these occupations are also amongst the nation’s most economically vulnerable and
therefore, amongst the least likely to be able to afford to forgo a day’s pay in order to recover at
home and avoid spreading infectious illnesses.
Despite the importance of access to paid leave for these critical occupations, food preparation
workers and “personal care workers” are amongst the least likely to have such benefits today.33
Just 28 percent of child care workers in establishments o f 15 or more employees have access to
paid sick leave today. 48 percent of personal care workers in such establishments have access to
paid sick leave today.34 The Healthy Families Act would substantially expand access to paid sick
leave for workers in these occupations with critical public health implications.
Under the Act, paid sick leave for food services workers in covered firms would expand by 259
percent, covering 6.0 million additional food service workers and resulting in a total of at least
8.2 million food service workers with paid sick leave coverage. Paid sick leave for personal care
workers in covered firms would expand by 107 percent, covering an additional 1.4 million
personal care workers and resulting in a total of at least 2.7 million personal care workers with
paid sick leave coverage.35
Figure 5 6 0 Million More Food Service Workers and 1.4
Million More Personal Care Workers Will Have Access to
Paid Sick Leave Under The Hfealthy Families Act
Coverage fo r food service w orkers w ilt
expand by 259% under HFA.
Coverage fo r personal care w orkers
w ill expand by over 107% under HFA.
8 3 million food service workers covered
2.7 million personal care workers covered
New
Access
Food Preparation and Services
Personal Care and Services
!
Conclusion
American workers can ill-afford to choose between their health and a paycheck, particularly in
today’s economic climate. Yet the status quo requires the majority to do just that, as the lack of
federal legislation mandating access to paid sick days means that millions of employees must
forgo their earnings if they are to stay home to care for their own health or that of a sick child.
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The status quo represents not only poor public health policy, as workers sick on the job and
children ill at school contribute to the spread of contagious disease. It’s also poor economic
policy, as sick workers create a drag on their own and co-workers’ productivity.
The Healthy Families Act would insure that all workers in firms with 15 or more employees are
able to earn paid sick leave, insuring a healthier and more productive America. As the analysis
above has detailed, the impact of the Healthy Families Act would be substantial for all
Americans, but it would be particularly beneficial for a number of especially vulnerable groups
of workers. Lower-wage workers, who are more likely to be unable to weather the blow of a day
without pay, would benefit from this legislation. Female workers, who are both more
economically vulnerable than their average male counterparts and are more likely to be
responsible for their family’s health and well-being, would benefit. Minorities, who are more
likely to be in lower-wage jobs and therefore less likely to be able to go a day without pay,
benefit from this legislation. And occupations with critical public health implications - including
the low-paid fields of food service and personal care workers - would benefit immensely.
Paid sick leave is a critical element for workers’ economic security. The dramatic expansion of
access to paid sick leave under the Healthy Families Act would play a critical role in ensuring
that families maintain stable economic footing in unsteady times.
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I December 2010
I Joint Economic Committee
Endnotes
1. 66 percent of all civilian workers in the United States have access to paid sick leave, according to the
Bureau of Labor Statistics. Bureau of Labor Statistics. 2009. “Employee Benefits in the United States,
March 2009.” Table 6. http://www.bls.gov/news.release/pdf/ebs2.pdf.
2. For example, see Goetzel, Ron Z., Long, Stacey R., Ozminkowski, Ronald J., Hawkins, Kevin,
Wang, Shaohung, and Lynch, Wendy. 2004. “Health, Absence, Disability, and Presenteeism Cost
Estimates of Certain Physical and Mental Health Conditions Affecting U.S. Employers.” Journal of
Occupational and Environmental Medicine. Lovell, Vicki. 2004. No Time to Be Sick: Why Everyone
Suffers When Workers Don’t Have Paid Sick Leave. Washington, DC: Institute for Women’s Policy
Research. Available at http://www.iwpr.org/pdf/B242.pdf. Stewart, W., Matousek, D., and Verdon, C.
2003. The American Productivity Audit and the Campaign for Work and Health. The Center for Work
and Health, Advance PCS.
3. This analysis focuses on the impact of the Healthy Families Act on the private-sector workforce only.
Private-sector workers have lower levels of access to paid sick leave than do public sector workers.
For example, according to the Bureau of Labor Statistics, 89 percent of state and local government
workers have access to paid sick leave as compared to just 61 percent of the private-sector workforce.
The Healthy Families Act would apply to both the public and private sector, therefore the Joint
Economic Committee’s estimates presented in the following analysis likely understate the full impact
of the Healthy Families Act on access to paid sick leave. See Bureau of Labor Statistics. 2009.
“Employee Benefits in the United States, March 2009.” Table 6.
http://www.bls.gov/news.release/pdf7ebs2.pdf.
4. Joint Economic Committee calculations based on unpublished data from the Bureau of Labor
Statistics’ 2009 National Compensation Survey and the March 2009 Current Population Survey.
Methods available from the Joint Economic Committee upon request.
5. Joint Economic Committee calculations based on unpublished data from the Bureau of Labor
Statistics’ 2009 National Compensation Survey.
6. 66 percent of all civilian workers in the United States have access to paid sick leave, according to the
Bureau of Labor Statistics. Bureau of Labor Statistics. 2009. “Employee Benefits in the United States,
March 2009.” Table 6. http://w ww.bls.gov/news.release/pdf/ebs2.pdf.
7. Heymann, Jody and Alison Earle. 2009. Raising the Global Floor: Dismantling the Myth That We
Can’t Afford Good Working Conditionsfor Everyone. Stanford, CA: Stanford Politics and Policy. See
http://researchtoaction.mcgill.ca/public html/wfei/index.php.
8. Smith, Tom W. 2008. “Paid Sick Days: A Basic Labor Standard for the 21 st Century.” Chicago, IL:
National Opinion Research Center. http://www.norc.org/NR/rdonlvres/D1391669-AlEA-4CF49B36-5FB1C1B595AA/O/PaidSickDavsReport.pdf.
9. Smith, Tom W. 2008. “Paid Sick Days: A Basic Labor Standard for the 21st Century.” Chicago, IL:
National Opinion Research Center. http://www.norc.org/NR/rdonlyres/Dl 391669-A1EA-4CF49B36-5FB1C1B595AA/O/PaidSickDavsReport.pdf.
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10. Reiss, Jeremy and Nancy Rankin. 2009. “Sick in the City: What the Lack of Paid Leave Means for
New Yorkers. An Analysis of Eight Years of Findings From The Unheard Third” New York:
Community Service Society/A Better Balance.
http://www.abetterbalance.org/cms/index2.php?option=com docman&task=doc view&gid=72&Item
id=99999999.
11. Smith, Tom W. 2008. “Paid Sick Days: A Basic Labor Standard for the 21st Century.” Chicago, IL:
National Opinion Research Center. http://www.norc.org/N1R/rdonlyres/D1391669-AlEA-4CF49B36-5FB1C1B5 95AA/O/PaidSickDavsReport.pdf.
12. Centers for Disease Control and Prevention. October 23, 2009. “CDC Recommendations for the
Amount of Time Persons with Influenza-Like Illness Should Be Away from Others.”
http://www.cdc.gov/hl nl flu/guidance/exclusion.htm.
13. Blendon, Robert, G. Steel Fisher, J. Benson, K. Weldon, and M. Herrmann. 2009. “Influenza A
(H1N1)/Swine Flu Survey III. http://www.hsph.harvard.edu/news/press-releases/20Q9releases/national-survev-americans-influenza-a-hlnl-outbreakfall-winter.html.
14. Unpublished data from the Bureau of Labor Statistics’ National Compensation Survey, March 2009.
15. Bureau of Labor Statistics. 2008. “May 2008 National Occupational Employment and Wage
Estimates.” http://www.bls.gov/oes/2008/may/oes nat.htm#b25-Q000.
16. This analysis focuses on the impact of the Healthy Families Act on the private-seetor workforce only.
Private-sector workers have lower levels of access to paid sick leave than do public sector workers.
For example, according to the Bureau of Labor Statistics, 89 percent of state and local government
workers have access to paid sick leave as compared to just 61 percent of the private-sector workforce.
The Healthy Families Act would apply to both the public and private sector, therefore the Joint
Economic Committee’s estimates presented in the following analysis likely understate the full impact
of the Healthy Families Act on access to paid sick leave. See Bureau of Labor Statistics. 2009.
“Employee Benefits in the United States, March 2009.” Table 6.
http://www.bls.gov/news.release/pdf/ebs2.pdf.
17. Current access figures are from unpublished data provided by the Bureau of Labor Statistics National
Compensation Survey. These figures are likely to overstate current access to leave because many
employers impose a job tenure requirement on workers prior to offering access to paid sick leave. As
a result, the Joint Economic Committee’s estimate of the impact of the Healthy Families Act is
conservative, because the analysis may over-estimate access in the absence of the legislation.
Specifically, the Bureau of Labor Statistics’ survey is unable to ascertain whether a given worker has
met an employers’ job tenure requirements, therefore many employers may actually overstate their
workforce’s access to paid sick leave. Prior research has demonstrated that correcting for workers’
job tenure substantially lowers the share of Americans with access to paid sick days relative to the
raw data presented by the Bureau of Labor Statistics. See Lovell, Vicky. 2004. “No Time To Be Sick:
Why Everyone Suffers When Workers Don’t Have Paid Sick Leave.” Washington, DC: Institute for
Women’s Policy Research, http://www.iwpr.org/pdf/B242.pdf. Unfortunately, due to data restrictions,
a similar correction to the Bureau of Labor Statistics most recent data is not possible. Thus the Joint
Economic Committee estimates may overstate status-quo access to paid sick leave by relying on the
uncorrected Bureau of Labor Statistics data.
'
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I December 2010
I Joint Economic Committee
18. Joint Economic Committee calculations based on unpublished data from the Bureau of Labor
Statistics’ National Compensation Survey.
19. Joint Economic Committee calculations based on unpublished data from the Bureau of Labor
Statistics’ National Compensation Survey.
20. Current access figures for the full population are from unpublished data from the Bureau of Labor
Statistics’ National Compensation Survey.
21. Joint Economic Committee calculations based on unpublished data from the Bureau of Labor
Statistics’ National Compensation Survey.
22. For a literature review on the relationship between poverty, inequality, and health outcomes, see, for
example, Deaton, Angus and Christina Paxson. 2001. “Mortality, Education, Income and Inequality
Amongst American Cohorts.” In Wise, David, ed. Themes in the Economics of Aging. Chicago:
University of Chicago Press, http://www.nber.org/papers/w7140.
23. United States Census Bureau, Current Population Survey, 2009 Annual Social and Economic
Supplement. “Table POV04: Families by Age of Householder, Number of Children, and Family
Structure, 2008.” http://www.census.gov/hhes/www/cpstables/Q32QQ9/pov/new04 100 01 .htm.
24.
Boushey, Heather. 2009. “The New Breadwinners.” In Boushey, Heather and Ann O’Leary, eds. The
Shriver Report: A Woman's Nation Changes Everything. Washington, D.C.: Center for American
Progress.
25. Boushey, Heather. 2009. “The New Breadwinners.” In Boushey, Heather and Ann O’Leary, eds. The
Shriver Report: A Woman's Nation Changes Everything. Washington, D.C.: Center for American
Progress.
26.
Salganicoff, Alina and Usha R. Ranji. 2005. Women and Health Care: A National Profile.
Washington, D.C.: Kaiser Family Foundation. http://www.kff.org/womenshealth/upload/Womenand-Health-Care-A-National-Profile-Kev-Findings-from-the-Kaiser-Women-s-Health-Survev.pdf.
27. Institute for Women’s Policy Research. 2007. “Women and Paid Sick Days: Crucial for Family Well
Being.” Washington, D.C.: Institute for Women’s Policy Research.
http://www.iwpr.org/pdf/B254 paidsickdavsFS.pdf.
28. Joint Economic Committee calculations based on unpublished data from the Bureau of Labor
Statistics’ 2009 National Compensation Survey and the March 2009 Current Population Survey.
Methods available from the Joint Economic Committee upon request.
29. Working Poor Families Project. 2008. “Still Working Hard, Still Falling Short: New Findings on the
Challenges Confronting America’s Workers. Baltimore, MD: Annie E. Casey Foundation.
http://www.aecf.0rg/~/media/Publicati0nFiles/Nati0nalDataBriefFINAL.pdf.
30. Waldron, Tom, Brandon Roberts, and Andrew Reamer. 2004. “Working Hard, Falling Short:
America’s Working Families and the Pursuit of Economic Security.” Baltimore, MD; and New York,
NY: Annie E. Casey Foundation, Ford Foundation, and the Rockefeller Foundation.
http://www.casevfoundation.org/upload/publicationfiles/working%20hard.pdf.
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31. Joint Economic Committee calculations based on unpublished data from the Bureau of Labor
Statistics’ 2009 National Compensation Survey and the March 2009 Current Population Survey.
Methods available from the Joint Economic Committee upon request.
32. Bureau of Labor Statistics. 2008. “May 2008 National Occupational Employment and Wage
Estimates.” http://www.bls.gov/oes/2008/mav/oes nat.htm#b25-0000.
33. “Personal care workers” is category provided by the Bureau of Labor Statistics that includes child
care and home health workers, and perhaps many others with direct contact with the public including children, the elderly, the infirm, and others with heightened vulnerability to contagious
disease.
34. Current access figures for the full population are from unpublished data from the Bureau of Labor
Statistics’ National Compensation Survey.
35. Joint Economic Committee calculations based on unpublished data from the Bureau of Labor
Statistics’ 2009 National Compensation Survey.
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Prepared by the Majority Staff of the Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Testimony of Ellen Galinsky
President and Co-Founder
&
James T. Bond
Vice President for Research
Families and Work Institute
267 Fifth Avenue, 2nd Floor
New York, NY 10016
(212) 465-2044
before the
United States Joint Economic Committee
Hearing on
“Balancing Work and Family in the Recession: How Employees and Employers are
Coping”
July 23,2009
THE IMPACT OF THE RECESSION ON EMPLOYERS
ACKNOWLEDGEMENTS
We are deeply grateful to members of the Board of Directors of the Families and Work Institute
(FWI) who encouraged us to spend our own funds to conduct this timely study on The Impact o f
the Recession on Employers and for their astute guidance in suggesting the actual questions we
should pursue.
Our biggest thanks go to Board member Ted Childs of Ted Childs LLC and to Lois Backon,
FWI’s Vice President. It is because of their creative and committed leadership of FWI’s Work
Life Legacy Awards event—as well as because of FWI’s Director of Development Carol BryceBuehanan’s passionate leadership of the Institute’s Corporate Leadership Circle—that we have
the unrestricted funding to be able to do the right study, at the right time!
Our thanks to the work-life scholars and work-life leaders who were so thorough and thoughtful
in their reviews of the study’s questionnaire, especially Kathleen Christensen of the Alfred P.
Sloan Foundation and Katie Corrigan and Chai Feldblum of Workplace Flexibility 2010 at
Georgetown Law Center.
We want to acknowledge the outstanding efforts of management and staff o f Harris Interactive,
Inc., especially David Krane, Vice President, Kaylan Orkis, Research Associate, and Humphrey
Taylor, Chairman of The Harris Poll. We also thank the many U.S. employers who took part in
the telephone interviews.
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December 2010
Joint Economic Committee
We are indeed lucky to have such an exemplary staff at Families and Work Institute—they have
supported this study in so many ways. First and foremost is Kerstin Aumann, who provided wise
research counsel every step of the way. Kelly Sakai and Shanny Peer provided extremely helpful
feedback on the many drafts of this questionnaire. We also thank John Boose for his terrific
design for the report and Barbara Noreia-Broms for her careful proof reading. We are grateful to
Natalie Elghossain for her skillful assistance in compiling and analyzing the quotes from the
open-ended responses of employers and to Courtney Dem for her invaluable assistance in putting
the final touches on this study.
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
TABLE OF CONTENTS
185
186
187
187
188
194
List of Tables
Overview of Findings
Introduction
Study Questions
Overall Findings
How Have Employers with Different Characteristics
Responded to the Recession?
Employers that Differ in the Proportion of Women and
Men
Employers that Differ in the Proportion of Hourly
Employees
Employers that Differ in the Proportion of Unionized
Employees
Nonprofit Versus For-Profit Organizations
Employers that Differ in Size
Conclusion
Research Design and Methodology
Endnotes
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202
205
209
213
213
214
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I December 2010
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LIST OF TABLES
Table 2
Table 3
Table 4
Table 5
Table 6
Table 7
Table 8
Table 9
Table 10
Table 11
Table 12
Table 13
Table 14
Table 15
Table 16
Table 17
Table 18
190
What have employers done to reduce costs during the past 12
months?
Specific steps taken by employers to support employees
Workplace flexibility during the recession
How have employers’ strategies to reduce costs in response to
the current recession varied in relation to the proportion of
women employees?
Specific steps taken by employers to support employees that
vary in proportion of women to men employees
Workplace flexibility during the recession among employers
that vary in proportion of women to men employees
How have employers’ strategies to reduce costs in response to
the current recession varied in relation to the proportion of
hourly employees?
Specific steps by employers to support employees that vary in
proportion of hourly employees
Workplace flexibility during the recession among employers
that vary in the proportion of hourly employees
How have employers’ strategies to reduce costs in response to
the current recession varied in relation to the proportion of
unionized employees?
Specific steps taken by employers to support employees that
vary in proportion of unionized employees
Workplace flexibility during the recession among employers
that vary in proportion of unionized employees
How have employers’ strategies to reduce costs in response to
the current recession varied in relation to their nonprofit or
for-profit status?
Specific steps taken by employers to support employees that
vary in relation to their nonprofit or for-profit status
Workplace flexibility during the recession among nonprofit
and for-profit employers 21
How have employers’ strategies to reduce costs in response to
the current recession varied in relation to their employee size?
Specific steps taken by employers to support employees that
vary in relation to employee size
Workplace flexibility during the recession among employers
that vary in relation to employee size
192
193
195
196
197
199
200
201
203
204
205
206
207
208
210
211
212
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Table 1
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
OVERVIEW OF FINDINGS
We all know that the recession has taken a severe toll on employers and on their human resource
practices and policies, but no one has been quite sure how severe. Families and Work Institute’s
new nationally representative study of 400 employers reveals that two thirds (66%) of employers
have suffered declining revenues over the past year, with another 28% reporting that the
revenues have held more or less steady. Only 6% have experienced growth.
Employers have had to respond, and most (77%) have done so by finding ways to cut or control
costs. Among those that have seen their revenues decline, nine in ten have turned to cost-cutting
measures—most frequently decreasing or eliminating bonuses, eliminating salary increases,
laying off employees and instituting hiring freezes. Layoffs are, in fact, commonplace, as we
know from monthly unemployment figures from the U.S. Department of Labor, Bureau of Labor
Statistics. In fact, 64% of the employers needing to turn to cost-cutting strategies have reduced
the number of employees on their payrolls.
Despite this very bad news, it does appear that that between 34% to 44% of employers are trying
to help employees manage the recession—they help employees who have been laid off find jobs,
they help employees manage their own finances more effectively, and they connect them to
publicly funded benefits and services.
There has been a great deal of debate about what is happening with flexibility during the
recession. Since many employers saw flexibility tied to improving retention, 1 would they reduce
the workplace flexibility they offer during times of layoffs?
The answer is a resounding no. Most employers are either maintaining the workplace flexibility
they offer (81%) or increasing it (13%) during the recession. Perhaps they view flexibility as
affecting employee engagement, or perhaps they want to focus on retaining the key employees
who remain. While more than a quarter (28%) have turned to involuntary reduction in hours, a
comparable percentage (29%) have used voluntary reductions in hours. And perhaps
surprisingly, 57% report giving employees some or a lot o f say about the schedules they now
work.
We know from national unemployment figures that more men than women have lost jobs in the
recession, and this study similarly finds that men are more likely than women to work for
employers that have laid off employees. But the differences don’t stop there—men are also more
likely to work for employers that have reduced working hours, changed the scheduling of work
hours and reduced salaries.
In addition, employees from for-profit firms are at greater risk of negative financial outcomes
during the recession than those at nonprofits. Beyond these findings, there are fewer major
differences than expected among employers with varying employee populations in how they are
handling the recession, including those with more hourly employees or more unionized
employees. Although our most recent study o f employers found that small and large employers
were equally flexible,2 this study now finds that large employers are more likely (25%) than
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Joint Economic Committee
small employers (12%) to have increased flexible work options such as flexible schedules and
flexible workplace options because of the recession.
Introduction
Economic recessions are associated with significant revenue and earning declines for most
employers, and, consequently, with higher rates of unemployment and underemployment for
American employees—as well with as other changes in life on the job.
In order to better understand the impact of the current recession on the U.S. labor force and on
employers, the Families and Work Institute (FWI) surveyed a random sample of U.S. employers
with 50 or more employees in May o f 2009. Please see the information in Research Design and
Methodology on page 25 for a description of the study design and implementation.
Although the popular media has addressed this issue at some length in recent months, the
information presented has been largely anecdotal or based on surveys of specific populations,
such as consultants surveying their clients or membership organizations surveying their
members. It is important to move beyond speculation to see how a nationally representative
sample of employers is dealing with the recession and its impact on its human resource policies
and practices. That is the purpose of this study.
Study questions
This study is designed to address the following questions among a nationally representative
sample of U.S. employers with 50 or more employees:
1. What percentage of employers have taken steps to reduce labor and operational costs in the
past 12 months?
2. Among these, what specific cost reduction strategies have they used?
3. What are employers doing to help employees deal with the recession?
4. What is happening with workplace flexibility during the recession?
5. Do the strategies employers use for dealing with the recession differ for employers that have
larger proportions of women or men; of hourly or salaried employees; of unionized or non
unionized employees? Do they differ for employers that are nonprofit or for-profit? And do they
differ for employers of various sizes?
6. What are employers doing that they think would serve as useful examples for other
employers? Throughout the report, we include employers’ responses to this open-ended question.
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Prepared by the Majority Staff of the Joint Economic Committee
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
j Joint Economic Committee
Overall findings
Table 1 addresses the first two study questions—the percentage of employers that have taken
steps to reduce labor and operational costs in the past 12 months and the specific cost reduction
strategies they have used.
The most obvious indication of the recession’s impact on employers is that two thirds
(66%) of employers report that their revenues declined in the past 12 months.
• In addition, 28% of employers say revenues remained at approximately the same level,
while
only 6% report higher revenues.
Most employers (77%) have made some effort to reduce or control costs during the
recession.
• Among employers that have experienced lower revenues, 90% have taken steps to
reduce labor and operational costs versus 50% of other employers.
In response to our open-ended question about promising practices, some employers reported that
they have turned to their employees for suggestions on cost-cutting measures. These include
informal requests to more formal procedures:
We generated a cost-savings program where employees submitted cost-saving ideas—the
implementing o f employees ’ ideas is going to save a lot o f money.
We have organized an active cost committee that is made up o f administration and
laborers that have meetings once a month and make recommendations.
Decreasing or eliminating bonuses, eliminating salary increases, laying off employees and
instituting hiring freezes are the most frequent strategies employers have used to control
costs.
As can be seen in Table 1, among those employers that implement cost-saving strategies, 69%
have decreased or eliminated bonuses and salary increases; 64% have laid off employees to
reduce costs; 61% have implemented a hiring freeze; and 57% have eliminated all travel that is
not essential to their businesses.
Other strategies have been used much less frequently, though some of these other strategies to
reduce costs may have actually saved jobs—for example, reductions in hours to lower labor
costs, increased telecommuting to save on occupancy costs and increased use of compressed
workweeks.
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In their comments, employers describe some of these practices:
IVe’ve had employees go a week a month without working and without pay, and we do
this on a revolving basis throughout the location or department. It has worked well to
share the pain and maintain morale.
The biggest [strategy] is using compressed workweeks, because it doesn’t have an impact
on employees ’ wages, but has an impact on operational costs.
We reduced working hours. That was our biggest cost-saving strategy. Our employees
and unions supported that choice.
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Table 1: What have employers done to reduce costs during the past 12 months?
Reduction of costs during recession
% of employers
Employer has taken at least one step to reduce labor and operational costs in the past
12 months
.
77%
Among those employers who have taken steps to reduce labor and operational costs in tie past 12 monte
{maximum N-304), what proportion have used each strategy
Decreasing/eliminating bonuses and salary increases
;
69%
|
64%
'
2, Layoffs
; 3. Hiring freeze
61%
4. Eliminating afl travel that is not essential to business
i
57%.
5. Freezing promotions
;
35%
6. Reducing health care benefits or increasing employee costs
:
29%
,
2%
8. Involuntary reductions in hours
■
28%
9. Reducing salaries/wages
1
27%
7. Voluntary reductions in hours
;..........-........
-
.... .................. .... ...... . ......
10. Increasing use of compressed workweeks
22%
11. Reducing employer contributions to 401 (k) or 403(b) plans
21%
12. Increasing telecommuting to save on occupancy costs
19%
: 13, Hiring workers who earn less
13%
14. Outsourcing work or moving employees into contract work
11 %
15. Reducing sick time
8%
16. Offering buyouts or other inducements for early retirement
7%
17. Encouraging phased retirement by working reduced hours
7%
18. Reducing paid vacation time
7%
19. Eliminating the legacy costs of a defined-benefit pension
4%
20. Eliminating health care benefits for retirees
2%
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Invest in Women, Invest in America:
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December 2010
Joint Economic Committee
Table 2 addresses the third study question: what are employers doing to help employees deal
with the recession? We see such initiatives as having the potential to help employees and
employers alike. For example, by reducing stress, health care costs could go down; by treating
employees with respect, helping them manage the recession, giving them input and providing
them with flexibility to meet personal or family needs, employee engagement could increase.
Between 34% to 44% of employers are helping their employees weather the recession by
helping those who have been laid off find other work, providing information on how to
manage their own finances and connecting them to publicly funded benefits and services.
Among employers that have laid off employees, 43% have provided them with help to find other
work and/or manage this transition. One employer says:
On a fairly personal level, I would like to say that the Human Resources departments
work rather closely with former employees to update resumes, remarket their skills and
basically just help them get re-employed. I t ’s not a formal program, but we work very
hard at it.
More than one third of employers communicate about the financial situation of their organization
very often, and another 41% do so somewhat often. An employer says:
We have board meetings twice per month, and we have an open door policy.
Communication is the key—to be available to listen to employees and their concerns.
Additionally, more than one third of employers (34%) report providing special support to help
employees manage their own financial situations. This includes helping employees deal with
their own finances more effectively in the downturn:
We have a financial advisor who we make available to our employees. He actually comes
into our office which makes it more convenient to our employees.
We use our EAP provider to provide financial counseling and assistance that we use to
assist employees with their finances. We do this both because o f the economic crisis and
as a benefit to our employees. [In addition], a group o f other businesses in the area has
identified resources that are available in the community. When a local business is in
need, this is a way we have used to become proactive—to assist those who may become
victims o f the current financial situation.
Employers also provide help in managing stress:
We have a motivated association program concerned with stress. It is directed to
employees that have financial stress, family stress.
And companies report helping others in their community who need assistance:
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j December 2010
I Joint Economic Committee
We have made donations fo r clothes, toys and food for people in the community, fo r
people in need. We ’re having a big garage sale and will donate in the community.
Employer efforts to refer low-income employees to public programs are not new or necessarily
related to the current recession. Indeed, there have been various public, NGO and private
employer initiatives addressing this issue in recent years in response to the fact that even in the
best of times, various public programs (e.g. EITC, child care subsidies, free tax preparation,
SCHIP) are underutilized by those who are eligible and could benefit from them. We find that
more than two in five employers nationally (44%) are currently making some effort to encourage
employee enrollment in public programs or to connect employees to community services.
Table 2; Specific steps taken by employers to support employees
Overall % of
employers
Specific steps by employers to support employees
Among those employers that have laid off employees: Do you provide any assistance
to employees who have been laid off to help them find other work or to manage this
transition? (N-192)
Yes
43%
37
No
All employers: How often do you communicate with your employees about the financial
situation of your organization? ( N - 398)
'
Very often
Somewhat often
Not often
All employers: Are you providing any special support to employees to help them manage
their own financial situations during this recession? {N-396}
34%
41
25
Yes
34%
No
66
All employers: Do you make a special effort to inform employees or laid-off employees who
are potentially eligible for publicly funded benefits or services about the availability of these
benefits and services? (N -383)
. Yes
No
44%
36
A very large majority of employers is either maintaining the workplace flexibility they
offer (81%) or increasing it (13%) during the recession.
Table 3 addresses the fourth study question: what is happening with workplace flexibility during
the recession?
• Among employers that have encouraged employees to choose flexible work
arrangements (telecommuting, compressed workweeks, voluntary reduced hours and
phased retirement), the majority (57%) of employers give employees a great deal or some
input into decisions about using those arrangements.
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December 2010
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• Among employers that have implemented reduced work hours—both mandatory and
voluntary—to reduce costs, a large majority (83%) has maintained the same level of
benefits for employees.
• In addition, fully 81% of employers have maintained existing flexible work options
during the recession and 13% have actually increased those options, while 6% have
reduced them.
• Finally, 26% of employers have specifically used flexible workplace options to
minimize the need for layoffs.
Table 3: Workplace flexibility during the recession
Overall % of
employers
Flexible workplace options during the recession
Among those employers that have encouraged flexible work arrangements {telecommuting,
compressed workweeks, voluntary reduced hours, phased retirement): How much input or
choice have employees had about working under the flexible arrangements now in place?
CM=156}
A lot/Some
Not much/None
Among those employers that relied upon reduced work hours (phased retirement, voluntary
part time, and mandatory part time): Do you still provide the same level of benefits to
employees who work reduced hours? (N -134)
57%
44
83%
18
Yes
No
All employers; Have you reduced, maintained or increased flexible work options such as
flexible schedules or flexible workplace options because of the current economic downturn?
(N—375}
Reduced
Maintained
Increased
6%
81
13
All employers; Have you used flexible workplace options to minimize the need to lay off
employees? (N-394)
26%
74
Yes
No
Although we didn’t ask about this in our survey, some employers report that they have tried to
find ways to improve morale and to bring fun into the workplace during these trying times:
We’vejust incorporated incentives—games to increase morale when the employees go
above and beyond. [These are] low-cost or non-monetary incentives.
We ’re looking at creative ways to havefun in the workplace at low cost. These include
secret pal, potlucks, raffles, fund drives, etc.
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A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Employers who report helping their employees manage the recession make statements such as
this one:
D on’t impair your most important asset—your human asset.
HOW HAVE EMPLOYERS WITH DIFFERENT CHARACTERISTICS RESPONDED
TO THE RECESSION?
In the remainder of the report, we address the fifth study question: do the strategies employers
use for dealing with the recession differ for employers that have larger proportions of women or
men; of hourly or salaried employees; of unionized or non-unionized employees? Do they differ
for employers that are nonprofit or for-profit? And do they differ for employers of various sizes?
Employers That Differ In the Proportion of Women and Men
Men have been disproportionately affected by the recession. They are more likely than
women to work for employers that have laid off employees, reduced working hours,
changed the scheduling of work hours and reduced salaries.
As shown in Table 4, employers with larger proportions of men than women on the payroll are
more likely to have taken steps to reduce costs (80% versus 69%). Specifically:
• Employers with more men on the payroll are more likely to have laid off employees
(71% versus 50%). Regarding layoffs, unemployment rates for men have exceeded those
for women since the beginning of the recession. In May of 2009, when this survey was
conducted, the unemployment rate for men was 9.8% versus 7.5% for women.3 Men, of
course, are more likely to be employed in goods-producing industries where job losses
have been the greatest.
• Employers with more men on the payroll are more likely to have frozen promotions
(39% versus 26%) as well as to have required employees to work reduced hours (35%
versus 17%), which typically means lower wages. National statistics from the U.S.
Department of Labor also show that men are more likely to be working reduced hours
today (under 35 hours a week) than in the past—up from 9.5% in 2007 to 10.2% in 2008.
In contrast, women’s level has remained stable—23.5% in 2007 and 23.6% in 2008.4
• In addition, employers with more men on the payroll rely more heavily on compressed
workweeks (27% versus 15%) to control costs.
• In contrast—although the numbers are quite small, employers with more women on the
payroll are more likely (6% versus 1%) to have eliminated health care benefits for
retirees. This action has significant implications not only for retirees, but for those
nearing retirement as well, especially women since they live longer than men on average
and tend to have fewer financial resources.
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Table 4: How have employers’ strategies to reduce costs in response to the current
recession varied in relation to the proportion of women employees?
Overall
%
Women
< 50%
Women
50% +
Have taken any steps to reduce costs
77%
80%
69%
1. Decreasing/eliminating bonuses and salary increases
69%
2. Layoffs
64%
3. Hiring freeze
61%
4. Eliminating all travel that is not essential to business
57%
5. Freezing promotions
35%
6. Reducing health care benefits or increasing employee costs
29%
7. Voluntary reductions in hours
29%
8.
28%
Involuntary reductions in hours
ns
71%
; ***
. 50%
'
ns
e
ns
39%
26%
:
.
;
*
ns
ns
35%
17%
9. Reducing salaries/wages
27%
10. Increasing use of compressed workweeks
22%
11. Reducing employer contributions to 40 Hk) or 403{b} plans
21 %
ns
12. Increasing telecommuting to save on occupancy costs
19%
ns
13. Hiring workers who earn less
13%
ns
14. Outsourcing work or moving employees into contract work
11%
ns
15. Reducing sick time
8%
ns
18. Offering buyouts or other inducements for early retirement
7%
ns
17. Encouraging phased retirement by working reduced hours
7%
ns
18. Reducing paid vacation time
7%
ns
19. Eliminating the legacy costs of a defined-benefit pension
4%
ns
20. Eliminating health care benefits for retirees
2%
ns
26%
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6%
1%
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IDecember 2010
Joint Economic Committee
As shown in Table 6, there are no statistically significant differences in how employers with
higher proportions o f women versus men are using workplace flexibility during the recession.
Table 6: Workplace flexibility during the recession among employers that vary in
proportion of women to men employees
Overall
Flexible workplace options during the recession
Among those employers that have encouraged flexible work
arrangements (telecommuting, compressed workweeks,
voluntary reduced hours, phased retirement); How much
input or choice have employees had about working under
the flexible arrangements now in place? (N=1565
A tot/Some
Not much/None
Women
< 50%
Women
50%
Sig.
ns
57%
44
Among those employers that relied upon reduced work
hours {phased retirement, voluntary part time and
mandatory part time); Do you still provide the same level of
benefits to employees who work reduced hours? (N -134)
Yes
■
No
All employers: Have you reduced, maintained or increased
flexible work options such as flexible schedules or flexible
workplace options because of the current economic
downturn? (N -375)
ns
83%
18
ns
Reduced
6%
Maintained
Increased
81
13
All employers: Have you used flexible workplace options to
minimize the need to fay off employees? (N -394)
Yes
No
ns
26?
74
Employers That Differ In the Proportion of Hourly Employees
There are few differences between employers with larger or smaller proportions of hourly
employees in how they control costs during the recession—only two differences were found.
Employers where more than half of the workforce is hourly are more likely to have
reduced health care coverage or to require larger co-pays, and they are more likely to call
for voluntary reductions in hours.
Table 7 compares the strategies for cost controls used by employers with larger and smaller
proportions o f hourly employees during the recession:
• Employers with more hourly employees on the payroll are more likely to have reduced
health care benefits or increased cost sharing by employees, by way o f higher premiums
(33% versus 22%).
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I December 2010
I Joint Economic Committee
• Employers with more hourly employees are also more likely to rely upon “voluntary
reductions in hours” to control costs. Voluntary part-time work is the most common
arrangement. Whether employees have truly free choice—uninfluenced by their
employers—cannot be determined with certainty from our data.
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I Joint Economic Committee
Table 7: How have employers’ strategies to reduce costs in response to the current
recession varied in relation to the proportion of hourly employees?
Overall
%
Strategy to reduce cost
Have taken any steps to reduce costs
Hourly
<=
Hourly
> 50%
50%
Sig.
77 %
ns
1.
Decreasing'eliminating bonuses and salary increases
69%
ns
2.
layoffs
64%
m
3.
Hiring freeze
61 °c
4.
Eliminating ail t ravet that is not essent'ai to business
57%
5.
Freezing promotions
35%
;
•
4
ns
:
ns
ns
6. Reducing health care benefits or increasing employee costs
29%
22%
33%
*
7. Voluntary reductions in hours
29%
21%
34%
*
8.
Involuntary reductions in hours
28%
ns
9.
Reducing salaries/wages
27%
ns
10. Increasing use of compressed workweeks
22%
ns
11. Reducing employer contributions to 401{k) or 403(b) plans
21%
ns
12. Increasing telecommuting to save on occupancy costs
19%
ns
13. Hiring workers who earn less
13%
ns
14. Outsourcing work or moving employees into contract work
11%
ns
15. Reducing sick time
8%
ns
16. Offering buyouts or other inducements for early retirement
7%
ns
17. Encouraging phased retirement By working reduced hours
7%
ns
18. Reducing paid vacation time
7%
ns
19. Eliminating the legacy costs of a defined-benefit pension
4%
ns
20. Eliminating health care benefits for retirees
2%
m
As shown in Table 8, there is only one difference between employers with a higher versus a
lower proportion o f hourly employees.
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EMPLOYERS THAT DIFFER IN THE PROPORTION OF UNIONIZED EMPLOYEES
The proportion of unionized employees in the U.S. workforce has decreased significantly in
recent years. Consequently, there are relatively few employers with large proportions of
unionized employees on the payroll. Indeed, 88% of employers have fewer than 25% of
employees who belong to a union. Since that was the lowest percentage group in our measured
distribution, we compare employers with fewer than 25% unionized employees with those that
have more.
There is only one difference in the cost control strategies used by employers with more and
fewer union employees on the payroll: offering buyouts for early retirement.
• As shown in Table 10, 18% of employers with 25% or more union employees have
offered buyouts or other inducements for early retirement versus 6% of other employers.
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I December 2010
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There are no differences between employers with higher proportions and a lower proportion of
unionized employees in their specific efforts to support employees during the recession, as
shown in Table 11.
Table 11 Specific steps taken by employers to support employees that vary in proportion
of unionized employees
Specific steps by employers to support employees
Among those employers that have laid off employees; Do
you provide any assistance to employees who haw t e n
;
laid off to help them find other work or to manage this
transition? IN = 192)
Yes
No
All employers: How often do you communicate with your
employees about the financial situation of your organization?
{N—398}
Very often
!
Somewhat often
Not often
All employers: Are you providing any special support
to employees to help them manage their own financial
situations during this recession? (N -396)
Yes
NO
:
All employers: Do you make a special effort to inform
employees or latd-off employees who are potentially eligible
for publicly funded benefits or services about the availability
of these benefits and services? {N=383)
:
Yes
No
Only one significant difference is shown m Table 12:
• Employers with more unionized employees on the payroll are more likely to have
reduced flexible work options and less likely to have increased them because of the
recession.
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December 2010
Joint Economic Committee
Table 13: How have employers’ strategies to reduce costs in response to the current
recession varied in relation to their nonprofit or for-profit status?
Overall
Strategy to reduce cost
Nonprofit
For-Profit
Sig.
Have taken any steps to reduce costs
77%
63%
82%
*##
1.
Decreasing’eliminating bonuses and salary increases
69%
54%
74%
**
2.
Layoffs
64%
43%
70%
'Qrfrlk
3.
Hiring freeze
61%
ns
4.
Eliminating all travel t h a t n o t essential to business
57%
ns
5.
Freezing c-rorxtions
35°,
ns
6.
Reducing health care aenefits or increasing employee costs
29%
ns
7.
Vc'urtarv reducticns in hours
29%
ns
8.
.1n.vclurta.ry reductions in hojrs
28%
ns
9.
R edjc:rg 5a anes/wages
27%
ns
10. Increasing use of compressed workweeks
22%
ns
11. Reducing employer contributions to 401 (k) or 403(b) plans
21%.
12. Increasing teiecomTutmg to save on occupancy costs
19%
ns
13. HHng employees who earn 'ess
13%
ns
14-. Outsoircing wor# or moving emcbyees mto contract wcr
11%
ns
15. Reducing sick time
8%
ns
16. Offenng buyouts or other inducements fc ' early teti'ement
7/ -3.'Q/
ns
17. Eneojtcgng phased *etrement by working 'educea hours
7%
ns
18. Reducing paid vacatj&n time
7%
ns
19. E’.nmatine the legacy costs c# a ce^ ned-benefit. pension
AM
■
-&/D
ns
20. El m m a trg nealth care benefits for retirees
2%
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10%
**
25%
:
n.s ■
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I December 2010
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Table 15: Workplace flexibility during the recession among nonprofit and for-profit
employers
Overall
%
Flexible workplace options during the recession
Among those employers that have ‘encouraged’ flexible
work arrangements (telecommuting, compressed
workweeks, voluntary reduced tours, phased retirement):
How much input or choice have employees had s&out
working under the flexible arrangements now in place?
(N -156)
A tot/Some
NotmudVNone
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1
;
ns
57%
44
ns
83%
18
ns
6%
81
13
ns
26%
74
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ror-rrom
1
Among those employers that relied upon reduced work
hours (phased retirement, voluntary part time and
mandatory part time): Do you still provide the same level of
benefits to employees who work reduced hours? (N -134)
Yes
No
All employers: Have you reduced, maintained or increased
flexible work options such as flexible schedules or flexible
workplace options because of the current economic
s
downturn? (N -375)
Reduced
Maintained
Increased
All employers: Have you used flexible workplace options to
minimize the need to lay off employees? (N -394)
Yes
No
Page 1210
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A Comprehensive Review of Women in the U.S. Economy
Joint Economic Committee
EMPLOYERS THAT DIFFER IN SIZE
When analyzing employer size as an independent variable, it is unnecessary to weight sample
data for size of employer as is done elsewhere in this report. Thus, we use unweighted sample
data giving us roughly equal numbers of employers in each size category: 5 0 -9 9 , 100 - 999 and
1000 or more.
To simplify the presentation and interpretation of employer-size comparisons, we exclude
medium-size employers (100 - 999) from the comparisons reported below, comparing only
employers with fewer than 100 employees (small) and those with 1000 or more employees
(large). Generally, the responses of medium-size employers fall between those of small and
large.
Three significant differences are reported in Table 16:
• Large employers are more likely (68%) than small employers (51%) to eliminate all
travel that is not directly related to doing business. Employers with 1000 or more
employees are more likely to have employees as well as clients in a variety of locations
and are, thus, affected to a greater extent than small employers by travel expenses.
• Large employers are more likely (33% versus 13%) to have increased telecommuting to
reduce occupancy costs.
• Large employers are more likely (17% versus 3%) to offer buyouts or other
inducements for early retirement.
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December 2010
Joint Economic Committee
Large employers are more likely (25%) than small employers (12%) to have increased
flexible work options such as flexible schedules and flexible workplace options because of
the recession.
• Finally, as shown in Table 18, large employers are more likely (37%) than small
employers (23%) to have used flexible workplace options to minimize the need to lay off
employees.
Table 18: Workplace flexibility during the recession among employers that vary in relation
to employee size
Flexible workplace options during the recession
Overall
<100
1000+
%
employees
em p loyees
Among those employers that have Encouraged'
flexible work arrangements (telecommuting,
compressed workweeks, voluntary reduced hours,
phased retirement): How much input or choice have
employees had about working under the flexible
arrangements now in place? {N=156)
A lot/Some
Not much/None
Among those employers that relied upon reduced
work hours (phased retirement, voluntary part time
and mandatory part time): Do you stil! provide the
same level of benefits to employees who work
SiS-
;
ns
57%
44
ns
reduced hours? (N(=134)
Yes
No
83%
18
All employers: Have you reduced, maintained or
increased flexible work options such a s flexible
schedules or flexible workplace options because
of the current econ om ic downturn? (N=375)
6%
R educed
81
13
Maintained
Increased
All employers: Have you used flexible workplace
options to minimize the need to lay off
employees? (N=394)
Yes
No
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3%
12
73
25
23%
77
37%
63
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26%
74
7%
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Invest in Women, Invest in America:
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December 2010
Joint Economic Committee
CONCLUSION
Obviously, the impact of the recession on employers is a moving target, subject to continual
change. It is our intention that this “snapshot in time”—May 2009—of a representative group of
employers will provide a picture of the trends, both the negatives and the positives. This study
makes it clear that employers are reducing labor and operational costs. This study also indicates
that employers recognize that retaining and engaging employees are critical strategies to
organizational strength during the recession and beyond.
RESEARCH DESIGN AND METHODOLOGY
Dun & Bradstreet drew a random sample of employers with 50 or more employees from its
database. It’s coverage of employers of this size is quite good, and we know of no other privately
available database that rivals it. Harris Interactive conducted 400 20-minute telephone interviews
with Directors of Human Resources or persons with primary responsibility for human resources
in (mainly smaller) organizations without HR directors. Interviews were conducted in
May o f 2009. The response rate was 21%. The maximum sampling error (i.e., margin of error) is
approximately +/- 5%.
Employer size is defined as small = 50 - 99; medium = 100 - 999; and large = 1000 or more.
Because smaller employers far outnumber larger employers in the U.S., employers were sampled
to provide similar numbers in each size category to obtain reliable population estimates for
employers of all sizes. Then, the proportions of employers of different sizes in the sample were
weighted to their proportions in the population of employers in the U.S. (as appropriate). Only
our analyses of employer size as an independent variable use unweighted sample data. The
sample excludes federal, state and local government entities, including public universities. It
includes, however, private nonprofit organizations.
We report absolute “differences” as statistically significant only when there is at least less than
one chance in 20 (p < .05 or “*”) that they occurred by chance. The symbols “**” and “***”
indicate that absolute differences are less likely than “one in 100” or “1 in 1000” times,
respectively, to have occurred by chance. When no significant difference (“ns”) is found among
groups, the reader should assume that overall sample %s apply to the groups being compared.
Only the findings from tests of linear relationships are reported in order to simplify interpretation
and presentation.
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Endnotes
1. Galinsky, E., Bond, J.T. and Sakai, K. (2008) National Study o f Employers. New York: Families and
Work Institute. http://famiIiesandwork.org/site/research/reports/2008nse.pdf
2. Ibid.
3. U.S. Department of Labor, Bureau of Labor Statistics (June 2009). “Economic News Release:
Employment Situation Summary.” http://www.bls.gov/news.release/empsit.nrO.htm
4. Galinsky, E,, Aumann, K. and Bond, J.T. (2009). Times Are Changing: Gender and Generational Work
and at Home. New York: Families and Work Institute.
http://familiesandwork.org/site/research/reports/Times_Are_Changing.pdf
5. Bond, J.T. and Galinsky, E. (November 2006). What Do We Know About Entry-Level, Hourly
Employees? Research Brief No. 1. New York: Families and Work Institute.
http://familiesandwork.org/site/research/reports/briefl.pdf
6. Salamon, L.M., Geller, S.L. and Spence, K.L. (2009) ’’Impact of the 2007-09 Economic Recession on
Nonprofit Organizations,” Communique, No. 14. Baltimore, MD: Center for Civil Society Studies, Johns
Hopkins University. http://www.ccss.jhu.edu/pdfs/LP_Communiques/LP_Communique_14.pdf
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December 2010
Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
Testimony of Karen Nussbaum
Executive Director,
Working America
815 16th St., N.W.
Washington, D.C. 20006
202-637-5137
before the
United States Joint Economic Committee
Hearing on
“Balancing Work and Family in the Recession: How Employees and Employers are
Coping”
July 23, 2009
“Thank you, Chair Maloney, Vice-Chair Schumer, and Ranking Member Brownback.
My name is Karen Nussbaum. I am here today representing a lifetime of experience representing
the concerns of working women: as the founder and director of 9to5, the National Association of
Working Women; the Director of the Women’s Bureau of the U.S. Department of Labor, the
highest seat in the federal government devoted to women’s issues; assistant to the president of
the AFL-CIO; and currently as the executive director of Working America, the community
affiliate of the AFL-CIO, an organization of 2.5 million working women and men who do not
have a union on the job. My professional experience as a working women’s advocate - and an
advocate for working men and families - spans all occupations, union and non-union.
The Deteriorating Work-Family Balance
I am glad to be here today in the company of Ellen Galinsky and Cynthia Calvert to discuss this
important issue. For generations, the problem of work and family was solved simply —pay a
family wage to a single breadwinner. Accepted norms governed employer-employee
relationships, strengthened by unions and collective bargaining. This solution did not work for
everyone - around 40% of African American women worked throughout the first half of the 20th
century, while single women of all races did not earn a family wage. But the post-World War II
economic boom saw a common increase in standard of living across all income groups, families
were tended to and communities benefitted from the volunteer activities of their members. The
American middle class blossomed in these years.
A 1974 Business Week editorial signaled a shift in employer strategy. In the face of rising
international competition, Business Week advised cutting wages and benefits and warned, "It
will be a bitter pill for most Americans to swallow - the idea of doing with less so that banks and
big businesses can have more." This signaled the inception of a low road strategy, in which
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employers reduced wages and benefits for most workers, creating a privileged group of
professional workers at the top at the expense of a broad middle class; drafted low-wage
workers, particularly women, into the workforce; and made a concerted effort to reduce worker
bargaining power.
This strategy has proven effective for employers and disastrous for workers and their families.
Working and middle-class people shared in the postwar boom, but after 1973, workplace
standards were steadily eroded and most Americans ended up doing with less.
•
•
•
•
•
Median family income stagnated, and actually dropped from 2000-2006.1
Defined benefit pensions became a thing of the past - 25 years ago more than 80% of
large and medium-sized firms offered defined benefit pensions; today, less than a third
do.
Nearly half of private sector workers have no paid sick leave.3
Nearly a quarter of workers have no paid vacation or holidays,4 and Americans work, on
average, a month longer each year than in 1983.5
More and more women are working multiple jobs and non-standard hours - more than
one out of four regularly work nights or weekends; and nearly half of all women work
different schedules than spouses or partners.6
And banks and big businesses - until they crashed - did get more.
•
•
Between 1948 and 2001, in each cyclical recovery, corporate profits grew an average of
14% while worker salaries grew at half that rate. Between 2001 and 2004, while workers’
incomes shrank by 0.6%, corporate profits grew 62.2%.7
From 1987 to 2005, the percentage of Americans without health insurance grew from
12.9% to 15.9%,8 while from 2002 to 2005 alone, insurance company profits soared by
nearly 1000%.9
A Return to Standards
Once known as “cafeteria benefits,” work and family policies such as child care or flextime were
seen as options that could be chosen to fit personal needs above and beyond the basic benefits.
While some employees - primarily urban professionals - were making choices at the cafeteria,
the great majority of working people no longer even had meat and potatoes.
Some leaders, such as former General Electric CEO Jack Welch, say that there is “no such thing
as work-life balance,”10 that working women have no choice but to sacrifice either work or
family. But Ellen Galinsky’s impressive work demonstrates that work/life policies are viable and
widespread, increase productivity and personal satisfaction. Her research demonstrates that
pursuing work/life policies in a recession is good for the bottom line.
However, after a 30-year experiment with voluntary adoption of work/family measures in the
workplace, we know that reasonable standards will not penetrate the workplace without
enforcement. A small minority of professional workers will have the benefits and arrangements
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they require, but the majority of workers will be subject to work schedules beyond their control,
minimal or no benefits and no paid leave to care for their families.
As we decide how to cope with recession, we have the perfect opportunity to take the next step
and create workplace standards that are good for the bottom line and for working families.
Freedom to Join a Union and Bargain Collectively
The most effective and flexible way to create customized improvements at the work place is by
enabling working people to talk directly with employers about what is needed - otherwise known
as collective bargaining.
A recent study by the Labor Project for Working Families found that, among hourly workers, 46
percent of unionized workers receive full pay while on leave compared to 29 percent of
nonunionized workers, while companies with 30 percent or more unionized workers are five
times as likely as companies with no unionized workers to pay the entire family health insurance
premium.11 The Employee Free Choice Act would restore the right to collective bargaining,
which would help create a contemporary version of work/life balance.
Health Care
Health care costs are crippling families and employers and crowding out the possibility of other
workplace improvements. With health insurance expenses the fastest-growing cost component
for employers,12 employers do that offer health coverage are finding it difficult to compete, both
with companies in countries that have universal coverage and with employers in the U.S. that do
not offer benefits. Meanwhile, workers’ out-of-pocket costs have soared from $1,320 in 2001 to
$3,597 in
200813 and medical debt is a factor in 62 percent of personal bankruptcies.14
Solving the health care crisis would create a new floor for the work/family balance, boosting
disadvantaged families while reassuring middle-class ones that one piece of bad luck would not
plunge them into bankruptcy.
Work/Family Standards
In addition, there are key work/family standards which provide the framework for moving
forward.
•
Paid sick days
o Paid sick days help reduce the spread of illness in workplaces, schools and child
care facilities, yet 79 percent of low-income workers - the majority of whom are
women -do not have a single paid sick day.15
o Congress should support The Healthy Families Act (H.R. 2460), which would
provide full-time employees with seven paid sick days per year - and a prorated
amount for part-time employees - to be used for short-term illness, to care for a
sick family member or for routine medical care.
Paid family leave
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•
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o
•
I December 2010
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The Family and Medical Leave Act has been a great success. Since 1993, workers
have used the FMLA more than 100 million times.16 Yet, half of the privatesector workforce is excluded from it and 4 out of 5 eligible employees who need
leave could not take it because it was unpaid.17 FMLA coverage should be
expanded and wage replacement be added.
Control over work hours/flexible work hours
o Flexibility in regards to workers’ work/life balance is particularly important given
that Americans work nearly nine weeks (350 hours) longer each year than
Western Europeans.18 In 1970, fewer than half (38 percent) of U.S. women with
school-age children were in the labor market. By 2000, more than two-thirds (67
percent) were on the job.19 In the U.S., two-thirds of working couples with kids
put in overtime.20 Flextime helps solve the common conflict between lengthening
work hours and our personal obligations. Flextime gives a worker more control
over her or his schedule on an hourly, daily, weekly, seasonal or annual basis. If
Workers are expected to flex to the job, the job should flex back.
I'd like to recognize Chair Maloney for her leadership on this issue and ongoing
commitment to working families across the country. Securing a flexible
workplace for women and families is essential to balancing the daily demands of
work and personal life, and the Working Families' Flexibility Act seeks to
advance that cause.
•
Paycheck fairness
o The Paycheck Fairness Act is not strictly a work/family policy but it does seek to
restore balance - in the wages paid to women and men. (H.R. 12) would close
loopholes in the Equal Pay Act of 1963 and is long overdue.
•
Misclassification of employees
o Misclassification of employees allows employers to save on taxes and benefits,
and harms workers and their families by excluding them from health insurance,
workers compensation, minimum wage and overtime pay, and family and medical
leave or unemployment benefits.
•
Child care and pre-school
o Affordable child care is a must for single mothers, families that require two
incomes to get by, and women who choose to continue working while their
children are you.
o Early childhood education would not only benefit children but would enable their
parents to save on childcare costs and potentially return to the workforce sooner if
they chose.
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Conclusion
It has taken decades to achieve basic workplace standards - in some cases it has been more than
a century of struggle: overtime after 40 hours, no child labor, non-discrimination, and more
recently, unpaid family leave. Many benefits workers took for granted in the 1950s are now
seriously eroded. We are now far behind all other industrial countries both in standards and
practice and we have seen that without the standards, we will not have the practice.
Now is the time to put the next generation of basic workplace safeguards in place.
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Endnotes
1 Economic Policy Institute, 2006. “State of Working America.”
http://www.stateofworkingamerica.org/tabfig/2008/01/Q3.ipg Accessed 7/19/09.
2 Jacob Hacker, 2008. Testimony Before Committee on Education and Labor, U.S. House of
Representatives Field Hearing on “The Impact of the Financial Crisis on Workers’ Retirement Security.”
http://www.iaw.berkeley.edu/files/Hacker Testimony - Oct 2008-UP .pdf Accessed 7/17/09.
3 Vicky Lovell, Institute for Women’s Policy Research, “Women and Paid Sick Days: Crucial for Family
Well-Being, 2007.”
4 Center for Economic and Policy Research, 2007. “U.S. Only Advanced Economy That Does Not
Guarantee Workers Paid Vacation.” http://www.cepr.net/index.php/press-releases/press-releases/us-onlyadvancedeconomv-that-does-not-guaranlee-workers-paid-vacation/ Accessed 7/21/09
5 Darrell Hutchens and JefFMilchen, 2003. “Americans Working More, Earning Less.”
http://www.reclaimdemocracv.org/labor/unpaid overtime rules.html Accessed 7/19/09.
6 AFL-CIO, “Ask A Working Woman Survey 2000,” poll conducted by Lake Snell Perry & Assoc.,
2000.
7 Economic Policy Institute, 2004. “When Do Workers Get Their Share?”
http://www.epi.org/economic snapshots/entrv/webfeatures snapshots 05272004/ Accessed 7/19/09.
8' U.S. Census Bureau, “Historical Health Insurance Tables.”
http://www.census.gov/hhes/www/hlthins/historic/hlthin05/hihisttl.html Accessed 7/20/09.
9 AFL-CIO, “Insurance Company Profits are Fat and Healthy.”
http://aflcio.org/issues/healthcare/upload/facts insurancecompanyprofits.pdf Accessed 7/20/09.
ia Jack Welch speaking to the Society for Human Resource Management, 6/28/09, quoted by Andrew
Leonard.
http://www.salon.com/tech/htww/2009/07/14/iack welch and women/index.html?source=newsletter
Accessed
7/17/09.
11 Jennifer MacGillvary and Netsy Firestein, 2009. “Family-Friendly Workplaces: Do Unions Make a
Difference?” http://laborcenter.berkelev.edu/iobqualitv/familvfriendlv09.pdf Accessed 7/17/09.
11 National Coalition on Health Care, http://www.nchc.org/facts/cost.shtml Accessed 7/22/09.
13 Hewitt Health Care Initiative/AFL-CIO.
http://aflcio.org/issues/healthcare/facts insurancepremiums.cfm Accessed 7/22/09.
14' CBS News. http://www.cbsnews.com/stories/2009/Q6/05/earlvshow/health/main5064981.shtml
Accessed 7/22/09.
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15 Economic Policy Institute, “Minimum Wage Issue Guide,” 2007,
www.epi.org/content.cfm/issueguides minwage Accessed 7/22/09.
16 Testimony of Debra Ness before the Committee on Health, Education, Labor and Pensions
Subcommittee on Children and Families, Feb. 13, 2008, help.senate.gov/Hearings/2008 02 13/Ness.pdf.
and “The Family and Medical Leave Act Regulations: A Report on the Department of Labor’s Request
for Information 2007 Update,” U.S. Department of Labor, June 2007, at 129.
17 Jane Waldfolgal, www.bls.gov/opub/mlr/2001/09/art2full.pdf; Jody Heymann,
www.iwpr.org/pdf/hevmann.pdf; “Balancing the Needs of Families and Employers: Family and Medical
Leave Surveys 2000 Update,” conducted by Westat for the U.S. Department of Labor.
,8' www.timeday.org (10/9/2006)
19, Win-win flexibility: New American Foundation
20 One sick child away from being fired: When “opting out” is not an option. Center for WorkLife Law.
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I December 2010
I Joint Economic Committee
Testimony of Cynthia Thomas Calvert
Deputy Director,
The Center for WorkLife Law
UC Hastings College of the Law
200 McAllister St.
San Francisco, CA 94102
before the
United States Joint Economic Committee
Hearing on
“Balancing Work and Family in the Recession: How Employees and Employers are
Coping”
July 23, 2009
Balancing Work and Family in the Recession
Introduction
“Chairman Maloney, Vice Chairman Schumer, Ranking Members Brady and Brownback, and
Members of the Joint Economic Committee, thank you for inviting me to speak about
work/family balance in the current economy. My name is Cynthia Thomas Calvert, and I am the
Deputy Director of the Center for WorkLife Law at the University of California Hastings
College of the Law. I have been researching work/life and flexible work issues for more than
twenty years, the last ten of which have been with WorkLife Law’s Director, Distinguished
Professor of Law Joan Williams. I am the co-author, with Professor Williams, of the only legal
treatise on family responsibilities discrimination, WorkLife Law ’s Guide to Family
Responsibilities Discrimination, and of Solving the Part-Time Puzzle: The Law Firm’s Guide to
Balanced Hours. As part of my work at WorkLife Law, I manage a hotline for employees who
believe they are facing FRD. My testimony today will be based largely on information learned
from the hotline.
Although I will be speaking today primarily about the employee’s perspective, it is important to
note that WorkLife Law also includes the perspective of the employer. WorkLife Law is a
nonprofit research and advocacy group with a unique “six stakeholder” model that brings
together employees, employers, plaintiffs’ employment lawyers, management-side employment
lawyers, unions, and public policymakers. WorkLife Law works with these groups to educate
them about FRD and flexible work bias, and to craft business-based solutions.
In addition to maintaining the hotline, WorkLife Law has pioneered the research of family
responsibilities discrimination (“FRD”).1 We maintain a database of nearly 2000 FRD cases and
track trends in FRD litigation. We publish an email alert for employers about recent
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developments in FRD and provide resources and training materials for employers and their
lawyers to use to prevent FRD in the workplace. We educate plaintiffs’ and employers’ lawyers
about FRD case law, and provide technical assistance to policymakers who seek to address FRD
and flexible work bias through public policy. We are currently developing a database of union
arbitration decisions that involve FRD, and we provide training and information to unions as
well. By working with all stakeholders, we obtain and present nuanced and balanced viewpoints
that enable us to create usable and effective strategies for preventing and addressing
discrimination against caregivers and flexible workers.
Bias against Employees with Family Responsibilities
FRD, also known as caregiver discrimination,2 is employment discrimination based on family
caregiving responsibilities. It manifests itself in many ways, including:
•
•
•
•
refusing to hire pregnant women;
not promoting mothers o f young children;
punishing male employees for taking time off to care for their children; and
giving unwarranted negative evaluations to employees who take leave to care for aging
parents.
FRD is typically caused by unexamined bias about how employees with family caregiving
responsibilities will or should act. For example, a supervisor may assume that a man who is
taking care of his dying father will be distracted, and therefore not promote him, even though the
man continues to perform at the same high level he always has. Although FRD is certainly not
confined to women, a large segment of the unexamined biases that cause FRD is maternal wall
bias: bias against women because they are or one day may be mothers.3 A common bias is that a
pregnant woman will not be a good employee because she will have poor attendance or will not
be as committed to her job once she is a mother, which can lead a supervisor to terminate her. An
illustration of a bias based on beliefs about how caregivers should act comes from an employee
who contacted WorkLife Law’s hotline: her supervisor apparently believed that mothers should
be at home with their children, so the supervisor cut her hours to less than half of full-time,
telling her that this would allow her to see more of her kids.
Flexible Work Bias
We are very encouraged by the findings of the Families and Work Institute showing that many
work/family programs provided by employers are relatively unchanged by the recession.4 These
findings are consistent with what WorkLife Law has learned from the employers with whom it
works: the business reasons for offering flexibility, such as retention of good workers and
increased productivity and morale, have not changed.
Unfortunately, what also has remained unchanged is the prevalence of flexible work bias.
Flexible work bias mirrors and often overlaps with family responsibilities bias. Employees who
work flexibly often encounter unspoken and often unrecognized assumptions on the part of
supervisors and co-workers about their commitment, dependability, worth, ambition,
competence, availability, and suitability for promotion. These assumptions affect how
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supervisors perceive flexible workers and their performance, which in turn affects the
assignments they receive, and how their work is evaluated and rewarded. While employers may
not be changing their work/family programs, employees may engage in “bias avoidance” by not
taking advantage of such programs for fear of being marginalized or penalized at work—
behavior that may be exacerbated by today’s economic climate in which most employees have at
least some fear of losing their jobs.
Here is an example of how flexible work bias commonly plays out in the workplace, which is
drawn from calls to our hotline: Tonya is a hard worker who regularly receives raises and is
given training opportunities to enable her to be prepared for a promotion. Once Tonya begins to
work reduced hours and to work some of the hours from home, attitudes toward her change. She
doesn’t get the challenging assignments anymore, because supervisors reserve those for the “gogetters” in the department who are more committed to their work and can be counted on to
complete assignments on time. Tonya no longer receives training opportunities, because her
employer assumes that she does not want a promotion and, even if she does, those opportunities
should be reserved for employees who are the “future” o f the company. Tonya, who used to be
able to arrive at and leave the office as desired, now finds that her hours are scrutinized. When
she is out of the office, everyone assumes it is for schedule-related reasons, even if the real
reason is a visit to a customer. Tonya’s work product is reviewed more closely now, as if it may
contain more errors due to inattention or incompetence. She receives a more critical performance
review, and, consequently, a proportionately lesser raise than when working standard hours. She
begins to understand that her future with the company has become cloudy, or perhaps has
vanished completely. Interestingly, supervisors in other departments, who work with Tonya but
are unaware of her change in schedule, think she is doing the same great job as ever, as do her
customers.
This example shows how subtle, often unrecognized assumptions can add up to create a
significant flexible work bias that sets up a lesser “flex track,” much like maternal wall or
caregiver bias sets up a “mommy track” in the workplace. Other common examples of flexible
work bias include hostile situations in which supervisors actively try to get rid of workers on
flexible schedules, either by creating situations that justify termination or by making work so
unpleasant that the employees will quit.
WorkLife Law Hotline
The flexible work bias and caregiver bias largely explain why FRD and related claims come to
our WorkLife Law hotline. Many of the employees who contact us are facing personnel actions
based on biased assumptions, not on their actual performance.
WorkLife Law has been running the hotline since 2003. In the first five years of our hotline’s
operation, we received a total of approximately 315 inquiries. The volume of calls to our hotline
then increased dramatically. In 2008, we received approximately 125 inquiries, double our
previous annual average, with the bulk of the calls coming in the last quarter. This year, in the
six-month period between January and July 15 alone, we have had approximately 92 inquiries,
which suggests that we will receive more than 175 inquiries for this calendar year.
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The inquiries come mostly from women, but also from some men. Men can face caregiver bias
and flexible work bias, and it is important to note that they also often face hostile gender bias: if
they are somewhat involved with their families, such as coaching soccer, they are “great guys”;
if they engage in regular caregiving, they are “wimps,” no longer viewed as team players, and
seen as lacking the drive necessary to get ahead.
Calls and emails to the hotline come from all types of workers. We have heard, for example,
from workers in retail, manufacturing, public safety, education, corporate management, and law
firms. We hear from hourly workers, department managers, and vice presidents. We hear
primarily from pregnant women and parents of young children, and we also hear from adult
children of aging parents, employees with sick or disabled spouses, and grandparents who are
guardians of their grandchildren.
Hotline Inquiries in the Recessionary Period
Many of the hotline calls suggest that employers are targeting family caregivers and flexible
workers for termination. Some of this appears to be attributable to hostile forms of bias, such as
in the case of one caller who reported that when she was pregnant, her supervisor told her that he
had doubts she could get her work done once she had children and she was really
inconveniencing him and her department. When she asked after returning from maternity leave if
she could work a flexible schedule, he told her no, that she could quit if she couldn’t hack it. In
the ensuing weeks, he acted abusively toward her and she did in fact quit.
Another example that suggests hostility involves a scientist who worked for Shell Oil. Shell Oil
has a reputation for having very effective flexible work policies,5 but as this example suggests, a
terrific policy can quickly be undone by a single supervisor.
This call came into our hotline in January of this year, from Tobi Kosanke. Tobi now has a
lawyer, and has filed a complaint with the EEOC. The following allegations are from that
complaint. Tobi worked from home, examining thin sections of rock through a microscope. This
arrangement was created because her daughter was bom with a medication-resistant disease that
requires her to be breastfed frequently and Tobi has health issues that prevent her from pumping
milk at work. The arrangement worked well, Tobi was very productive, had happy clients, and
won special recognition awards. After a couple of years, she got a new supervisor who referred
to her telecommuting arrangement as “a mess” she would have to fix. The new supervisor moved
Tobi to a new team and told her to return her microscope to the company. The supervisor then
told Tobi to be in the office 30 hours per week or work part-time and take a pay cut, even though
the supervisor was aware that these schedules would not allow Tobi to feed her child. Tobi took
FMLA leave and tried to wean her child, but was not successful. Faced with a choice between a
paycheck and her daughter’s health, she says she asked to work part-time or take a sabbatical,
but the company terminated her instead.
It should be noted, however, that many terminations that are not based on hostile bias may
involve bias nonetheless. An equally likely, although untested, reason for termination of family
caregivers and flexible workers in the current economy may be the pressure supervisors feel to
show good results with fewer resources as their budgets shrink. They may feel that they have to
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| December 2010
I Joint Economic Committee
weed out underperformers and trim personnel costs to maintain their bottom line. The problem
arises when supervisors assume that those employees with caregiving responsibilities or who
telecommute or work flexible schedules are the “underperformers.” Thus, the supervisors’
response to this pressure is no less based on bias: when they take personnel actions based not on
actual employee performance but on assumptions of how caregivers and flexible workers should
or will perform, they are engaging in discrimination.
We have received other inquiries from employees in the past eighteen months who have had
their flexible work arrangements eliminated, some of whom were told the elimination was for
economic reasons. Some reported that their employers eliminated the company’s flex time policy
and telecommuting policy. These callers unanimously expressed their needs for flexibility and
feelings of near desperation at facing unemployment because of their inability to work a standard
schedule. Several were working part-time for caregiving reasons, but were told that they must
return to full-time work or be terminated. The economic rationale for this is hard to understand.
Requiring employees to return to full-time work, at greater pay and with benefits, costs
employers money unless the employers are banking on reducing number of employees on the
payroll by forcing the employees to quit.
In another indication that employers may be using the recession as an excuse to terminate family
caregivers, since January 2008, we have received 45 inquiries from women who were terminated
shortly before, during, or shortly after their pregnancies. Several of these terminations were
carried out by supervisors who expressly questioned the new mothers’ ability to combine work
and family, but most were more circumspect. Several women were told there was not enough
work, but these women told us that it was because their work had been given to others. Several
were told their positions were eliminated for budgetary reasons, but the circumstances raise
questions: one was not given the option of applying for other open positions, one said there was
enough funding to move another employee to full-time hours and provide him benefits, and two
reported that their employer hired other employees in their department after terminating them.
One example from this group is particularly instructive.6 An employee had performed well at a
large company for more than six years. She had a child, and everything was fine. Her manager
worked with her on her schedule, and was happy as long as she was getting her work done. That
is lesson one: a little flexibility on the manager’s part allowed the company to retain a good
worker. She became pregnant again, and soon before she left on leave, she had a new manager.
The new manager changed her schedule, putting her on late night and very early morning shifts
that she could not work because of the lack of public transportation at those hours. That is lesson
two: WorkLife Law has noticed a pattern in court cases and calls to the hotline in which
flexibility works fine for everyone until a new manager arrives. The manager may feel a mandate
to reorganize the department or may lack a personal relationship with the employees and an
understanding of their value to the organization. But whatever the reason, the pattern typically
includes the termination of flexibility and action to terminate the employee.
This employee was the sole breadwinner for her family, however, so she did her best to make it
work with her new manager. When she went out on leave, others were hired to do her work. She
returned to work as planned, and asked if she could take one day a week off or work from home
one day a week. She didn’t receive an answer. Instead, she was laid off at the end of last year as
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A Comprehensive Review of Women in the U.S. Economy
December 2010
Joint Economic Committee
part of a recession-based, company-wide RIF, She was the only person in her department who
was let go, despite her seniority and record of satisfactory performance. This is lesson three;
having a child and asking for flexibility are two key trigger points for bias and discrimination.
Almost a third of the inquiries in the past eighteen months have come from employees who feel
squeezed between job and family demands. Some of the most heart-wrenching stories come from
this group, involving employees who literally weigh the need to put food on the table against the
need to provide for the safety and care of dependents. Three recent callers told of being fired
because they missed work because their children were hospitalized, even though they had alerted
their employer to the reason for their absences. Another caller missed one day of work because
her childcare failed and she could not leave her toddler unattended; she was fired even though
others in her company missed days o f work for other reasons and were not fired. In some of
these instances, it appears that the employer has created the situation to force the employees to
quit so the employer can avoid paying unemployment and perhaps reduce the likelihood of a
lawsuit. In one such situation, a single mother who had been working successfully for nearly a
year was placed on a schedule o f rotating shifts by a new supervisor, making it impossible for
her find childcare. Another with special needs children was told she would have to work large
amounts of overtime, although others in her department were not required to. Another caller, a
brand new mother, worked overtime for weeks on end, and when she finally asked for a break which just meant a return to standard hours for a period of time - she was fired.
While flexible work options would resolve most of these situations, the hotline callers state that
their supervisors have refused their requests for flexibility, or that they have received a message
that their use of such options would impact their careers negatively. Another way to state this is
that in workplaces where flexible work bias is weak or nonexistent, employees will resolve
work/family conflict through flexible work schedules. Where the bias is too great, they feel they
cannot. In one of the strongest examples of bias, some part-time employees reported the belief
that they were being targeted for layoffs before employees working standard schedules.7 In
today’s economy, employees simply cannot afford to do anything that would threaten their jobs.
In conclusion, bias against family caregivers and flexible workers is a pressing problem in the
workforce. Its effect on employees is clear, but we also need to remember that these biases
damage employers’ bottom lines. They cost employers not just in terms of legal liability, but also
in terms of unscheduled absenteeism, worker attrition, smaller available talent pool, lowered
productivity and morale, higher health costs, and poorer customer service.8 Employers and
employees will both benefit from bias prevention programs and from effective systems to
address bias as it occurs.
We appreciate the Committee holding this hearing and we stand ready to assist in any way in
your efforts going forward.
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Endnotes
1 E.g., Williams, Joan and Cynthia Thomas Calvert, WorkLife Law’s Guide to Family Responsibilities
Discrimination (WLL Press 2006 & updates); Joan C. Williams & Stephanie Bomstein, The Evolution of
"FReD": Family Responsibilities Discrimination and Developments in the Law of Stereotyping and
Implicit Bias, 59(6) Hastings Law Journal 1311 (2008).
FRD lawsuits can be brought as sex discrimination cases, family and medical leave retaliation, breach of
contract, and other types of lawsuits. FRD can arise at any level of an organization, from hourly shift
workers to top management. The number of FRD cases has increased rapidly. In 2006, WorkLife Law
reported a nearly 400% increase in the number of FRD lawsuits filed between 1996 and 2005 as
compared to the prior decade, 1986 to 1995. WLL is in the process of updating this data. Preliminary
results indicate a sharp increase in the number of FRD cases in 2007 (316 cases) and 2008 (348 cases) as
compared to 2006 (176 cases). Plaintiffs prevail on motions, resulting in settlements, or win verdicts in
approximately 50% of the cases. Settlements and verdicts average $100,000, and WorkLife Law has a
database of over 125 verdicts that exceed $100,000; several are multi-million dollar verdicts.
2 See Enforcement Guidance: Unlawful Disparate Treatment of Workers with Caregiving
Responsibilities, Equal Employment Opportunity Commission (2006), available at
http://www.eeoc.gov/policv/docs/caregiving.html.
3 Williams, Joan and Nancy Segal, “Beyond the Maternal Wall: Relief for Family Caregivers who are
Discriminated Against on the Job,” 26 Harv. Women’s L.J. 77 (2003).
4 Galinsky, Ellen, James T. Bond, and Kelly Sakai, 2008 National Study of Employers, Families and
Work Institute.
5 E.g., L.M. Sixel, Women's Group to Honor Winner with a Difference, Houston Chronicle, Houston
Chronicle, Jan. 17, 2004, at B1 (Shell's compressed work schedule, flexible work arrangements, and
maternity leave programs as among the reasons they received an award from Catalyst for diversity and
inclusivity); see also Shell Oil’s website,
http://www.shell.us/home/content/usa/aboutshell/careers/professionals/rewards benefits/professional rew
ardsbenefits.html#work-life balance 5 (listing Shell’s work/family programs).
6 Hotline calls are confidential. In the examples in this section, unless otherwise indicated, facts that
would identify the caller have been removed or altered.
7 In another example of flexible work bias, an employee who recently returned from her second maternity
leave was denied a promotion after she said she wanted to cut back her hours to take care of her baby’s
medical conditions. Another who cut back her hours for childcare reasons was not given any work to do.
8 See, e.g., WFC Resources, Making the business case for flexibility, available at
http://www.workfamilv.com/Work-lifeClearinghouse/UpDates/ud0043.htm (collecting studies).
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Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
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I December 2010
I Joint Economic Committee
Invest in Women, Invest in America:
I December 2010
A Comprehensive Review of Women in the U.S. Economy
I Joint Economic Committee
Social Security Provides Economic Security to Women
A Factsheet by the Joint Economic Committee
Representative Carolyn B. Maloney, Chair
October 28, 2010
Across the United States, Social Security plays an important role in retirement security—
especially for women. Women 65 and over make up nearly 10 percent of the adult U.S.
population. In Florida, older women make up 12.4 percent of the adult population, compared to
5.3 percent of the adult population in Alaska. The vast majority of these women receive Social
Security. In 2009, over 20 million women aged 65 and older received Social Security benefits,
either from retirement benefits, survivors’ insurance or disability insurance (see table).
Women are less likely than men to have income outside of Social Security to rely on in
retirement,1with Social Security accounting for two-thirds of all income for women aged 65 and
over." A woman who reaches age 65 can expect to live an additional 20 years.3 For these women,
Social Security is an essential source of income post-retirement, providing a life-long stream of
income that is protected against inflation.
Social Security benefits, while modest, are a substantial source of income for older Americans,
providing annual benefits of roughly $12,000 for women 65 and over. These benefits are
especially critical in reducing poverty among older women. Without Social Security benefits,
over half of women 65 and over would be living in poverty. With Social Security, the poverty
rate for older women falls to 12 percent. Among widows, the impact of Social Security is
particularly striking - 58 percent of widows would be living in poverty if not for Social Security
(see figure below).
As policymakers debate future changes to Social Security, they must be mindful of the important
role Social Security plays providing economic security and peace of mind to millions of
American women.
Social Security Benefits Reduce the Poverty Rate for Older Women, Especially Widows
Percent of Women 65 and Older ik in g Below the Poverty Threshold, by M arital Status, 2009
;
All
Widowed
:
Divorced/Separated
Never Married
Married
.
; Source: JEC Majority Staff calculations based on data from the C urrent Population Survey, M arch 2010.
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Prepared by the Majority Staff o f the Joint Economic Committee
Invest in Women, Invest in America:
A Comprehensive Review of Women in the U.S. Economy
I December 2010
I Joint Economic Committee
Across the Country, Over 20 Million Older Women Rely on Social Security Benefits
Women Aged 65 and Older N um le of Wome i Aged 65 and
Average Monthly Benefit of
As Percent o f Adult
Older Receiving Social Security
Women Aged 65 and Older
Population
Benefits
Receiving Benefits
United States
Alabama
9.896
20,274,175
$1,009
$958
10.6%
350,580
Alaska
5.3%
24,093
S947
Arizona
9.8%
400,721
$1,019
Arkansas
10.8%
219,997
S938
California
8,6%
1,936,591
SI,004
Colorado
7,9%
263,989
S973
Connecticut
10.5%
265,555
SI,112
Delaware
to .m
66,016
S i,067
District of Columbia
8.7%
30,326
S945
12.4%
1,500,784
S i,002
Georgia
8.2%
529,712
5982
Hawaii
93,812
$1,030
97,543
$957
Illinois
10.6%
8.9%
s .m
824,600
51,043
Indiana
10.0%
457,588
$1,050
iowa
11.2%
246,714
$990
Kansas
10.054
197,775
$1,028
Kentucky
10.0%
301,065
$930
Louisiana
9.6*
279,676
$891
11.1%
109,827
$926
Florida
idaho
Maine
Maryland
9.3%
346,725
$1,043
Massachusetts
10.2%
461,518
$1,022
Michigan
10.IK
731,503
$1,066
Minnesota
9.5K
355,993
$1,002
Mississippi
10.2K
204,285
$931
Missouri
I0.4K
439,305
$987
$946
Montana
10.2*
72,086
Nebraska
10.3%
129,945
$983
8.4%
145,052
$1,017
Nevada
New Hampshire
New Jersey
9.7%
94,663
$1,038
10.3W
623,706
$1,126
New Mexico
9.9%
128,844
$924
10.2%
1,322,678
$1,075
North Carolina
9.7%
650,506
$1,000
North Dakota
10.8%
51,301
S910
Ohio
10.6%
841,981
$987
Oklahoma
10.3%
263,810
S969
9.7%
273,355
$1,011
Pennsylvania
11.6%
1,059,007
$1,031
Rhode island
10.9%
83,099
SI,027
South Carolina
10.3%
330,669
$990
South Dakota
10.8%
63,335
$912
Tennessee
10.0%
452,099
$980
Texas
8.1K
1,263,999
S952
Utah
7.2%
121,702
$977
10.1%
48,016
51,000
New York
Oregon
Vermont
Virginia
9.1%
496,283
$1,000
Washington
8.8%
412,776
81,036
West Virginia
11.5%
154,221
$954
Wisconsin
10.0%
420,371
$1,024
8.8%
34,373
$980
Wyoming
'
Sources: JEC M ajority Staff calculations based on data from U.S. Census Bureau, American Community Survey. 2009; and Social Security
Administration, Office of Res ta rc h, Statistics, and Policy An alysis. OASDI Ben eficiaries by State and County. 2009, Tables 2 and 3.
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Invest in Women, Invest in America:
December 2010
A Comprehensive Review of Women in the U.S. Economy
Joint Economic Committee
Endnotes
1. Social Security Administration, Social Security is Important to Women, June 2010.
http://www.ssa.gov/pressoffice/factsheets/women.htm
2. JEC Majority Staff calculation based on data from March 2010 Current Population Survey.
3. Center for Disease Control, Health, United States, 2009. Table 24.
http://www.cdc.gov/nchs/data/hus/hus09.pdf
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Prepared by the Majority Staff of the Joint Economic Committee
Invest in Women, Invest in America:
I December 2010
A Comprehensive Review of Women in the U.S. Economy
I Joint Economic Committee
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United States Government Accountability Office
GAO
Report to Congressional Requesters
March 2009
WOMEN’S PAY
Gender Pay Gap in the
Federal Workforce
Narrows as
Differences in
Occupation,
Education, and
Experience Diminish
jk GAO
Accountability * Integrity * Reliability
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GAO-09-279
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Contents
1
Letter
Appendix I
Briefing Slides
Appendix II
Summary o f M ethods and Data
39
Appendix III
C ross-sectional A nalysis
46
Appendix IV
Cohort Analysis
68
Appendix V
Crosswalk betw een th e S tatistics Presented in the
Briefing Slides and Those Presented in
Appendices III and IV
81
Comments from the U.S. Office o f Personnel
Management
91
Comments from the U.S. Equal Employment
Opportunity Commission
93
Appendix VI
Appendix VII
Appendix VIII
5
GAO Contact and S ta ff Acknowledgm ents
100
Bibliography
101
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jfe.
G
A
O
Accountability * Integrity * Reliability
United States Governm ent A ccountability Office
Washington, DC 20548
March 17, 2009
.
The Honorable Edward M. Kennedy
Chairman
Committee on Health, Education, Labor
and Pensions
United States Senate
The Honorable Tom Harkin
Chairman
Subcommittee on Labor, Health and Human
Services, Education, and Related Agencies
Committee on Appropriations
United States Senate
The Honorable Carolyn B, Maloney
Chair
Joint Economic Committee
House of Representatives
Although the pay gap between men and women in the U.S. workforce has
narrowed since the 1980s, numerous studies have found that a disparity
still exists. In 2003, we found that women in the general workforce earned,
on average, 20 cents less for every dollar earned by men in 2000 when
differences in work patterns, industry, occupation, marital status, and
other factors were taken into account.1Other research indicates that this
disparity existed for federal workers as well. For example, a 1998 study
showed that the pay gap between men and women in the federal
workforce decreased significantly between 1976 and 1995, but in 1995
white women still earned 14 cents less for every dollar earned by white
men and African-American women earned 8 cents less for every dollar
earned by African-American men after available factors related to pay
were taken into account.2
‘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).
2Gregory B. Lewis, “Continuing Progress toward Racial and Gender Pay Equality in the
Federal Service: An Update,” Review of Public Personnel Administration, vol. 18, no. 2
(Spring 1998) 23-40.
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In light of concerns that a pay gap may continue to exist between men and
women in the workplace, you asked us to examine pay disparity issues and
the role the federal government has played in enforcing anti-discrimination
laws. In agreement with your staff, we addressed these questions in two
separate, consecutive reports, the first of which focused on enforcement
and outreach efforts in the private sector and among federal contractors.3
This second report addresses the following question: To what extent has the
pay gap between men and women in the federal workforce changed over
the past 20 years and what fact ors account for the gap?
To answer this question, we used two approaches to analyze data from the
Central Personnel Data File (CPDF)—maintained by the Office of
Personnel Management (OPM)—covering a 20-year period. First, we
looked at “snapshots” of the federal workforce at three points in time
(1988, 1998, and 2007) to show changes in the federal workforce over a 20year period.4Second, we examined the cohort (or group) of employees
who joined the federal workforce in 1988 and tracked their careers over
the course of 20 years to look for differences in the pay gap in this group.
We used CPDF data to generate summary statistics on the federal
workforce and to perform multivariate analyses, which we used to identify
the amount of the gender pay gap attributable to differences in measurable
factors—such as work-related and demographic characteristics of men
and women. To further inform our analyses, we reviewed existing
literature and reports on gender and pay and interviewed officials at the
Office of Personnel Management and the Equal Employment Opportunity
Commission (EEOC).
We conducted our work from March 2008 to March 2009 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
3GAO, Women’s Earnings: Federal Agencies Should Better Monitor Their Performance in
Enforcing Anti-Discrimination Laivs,” GAO-OS-799 (Washington, D.C.: Aug. 11,2008).
4The CPDF contain personnel data for most of the executive branch departments and
agencies as well as a few agencies in the legislative branch. For the purposes of this report,
we refer to workers covered by the CPDF data as the federal workforce. Our “snapshot”
findings are based on an analysis of a 20 percent random sample of federal employees in
the CPDF for each of the three points in time. See appendix n for further details on the
agencies not covered by the CPDF.
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that the information and data obtained, and the analysis conducted,
provide a reasonable basis for our findings and conclusions.
On January 26,2009, we briefed your staff on the results of our work. This
report formally conveys the information provided during that briefing (see
app. I). In summary, we found:
• From 1988 to 2007, the gender pay gap—the difference between men’s and
women’s average annual salary in the federal workforce—declined from
28 cents to 11 cents on the dollar. For each year we examined, all but
about 7 cents of the gap can be accounted for by differences in measurable
factors such as the occupations of men and women and, to a lesser extent,
other factors such as years of federal experience and level of education.
The pay gap narrowed as men and women in the federal workforce
increasingly shared similar characteristics in terms of the jobs they held,
their levels of experience, and educational attainment. Factors for which
we lacked data or are difficult to measure, such as work experience
outside the federal government and discrimination, may account for some
or all of the remaining 7 cent gap.
• Our case study analysis of workers who entered the federal workforce in
1988 showed that their pay gap grew from 22 cents in 1988 to a maximum
of 28 cents in 1993 through 1996 and then declined to 25 cents in 2007. As
with the federal workforce, differences between men and women that can
affect pay, especially occupation, accounted for a significant portion of the
pay gap over the 20-year period. In addition, our analysis found that
differences in the use of leave without pay and breaks in federal service
accounts for little of the pay gap for this group. The portion of the gap that
we could not explain increased over time from 2 cents in 1988 to 9 cents in
2007. However, the results of the 1988 cohort are not necessarily
representative of other cohorts
Ultimately, the gender pay gap for the entire federal workforce has
declined primarily because the men and women in the federal workforce
are more alike in characteristics related to pay than in past years. We
cannot be sure why a persistent unexplained pay gap remains for both our
analyses, but this may be due to the inability to account for certain factors
that cannot effectively be measured or for which data are not available.
We received written comments on a draft of this report from OPM, which
manages the CPDF data that were used in our analysis, and from EEOC.
OPM reviewed our methodology and found our use of the CPDF data to be
appropriate. They had two suggestions regarding variables in our analysis,
which we considered carefully. As a result of their comments, we clarified
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our discussion of the empirical results in the appendices, but did not alter
the main findings of our report. OPM’s full comments and our responses
to them are presented in appendix VI.
EEOC stated that our study has a solid research design and modeling
analysis and will serve as an important source of information to the federal
sector. In addition, EEOC suggested that we expand our report to show
how the gender pay gap evolved for different protected groups. We
acknowledge that the difference in wages between men and women may
vary further by race, age, disability status, and other factors that we
analyzed. However, to appropriately report on the influence of factors
related to other protected groups would require substantial analysis that is
beyond the scope of our study’s objective. EEOC also provided technical
comments for our consideration. Their full comments and our responses
to them are presented in appendix VII.
As agreed with your offices, unless you publicly announce the contents of
this report earlier, we plan no further distribution of this report until 30
days from the report date. At that time, we will provide copies to the Chair
of EEOC, the Director of OPM, relevant congressional committees, and
other interested parties. We will make copies available to others upon
request. In addition, the report will be available at no charge on GAO’s
Website at http://www.gao.gov.
If you or your staff have any questions about this report, please contact me
at (202) 512-7215 or shenilla@gao.gov. Contacts 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 this report are
listed in appendix VIII.
Andrew Sherrill
Director, Education, Workforce,
and Income Security Issues
Page 4
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VerDate Nov 24 2008
GAO-Q9-279 Women’s Pay
Appendix I: Briefing Slides
■- ■
■
•
f G AT O
.
WOMEN’S PAY: Gender Pay Gap in the Federal
Workforce Narrows as Differences in Occupation,
Education, and Experience Diminish
Briefing for Congressional Requesters
January 26,2009
‘ The briefing slides were subsequently updated to reflect com m ents that E E O C provided on o u r d r a ft report.
See appendix Vil fo r EEOC’s comments a n d our response.
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Appendix S; ISriofing Slides
;
r
v
.
. r : — .v
(j A O
,
.
'
•
'
. I f f , * * -------------------------------------------------------►
OTO.-vass
i f\
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s \
.
Overview
Key Question
• Scope and Methodology
• Summary of Results
. Background
\
Findings
Entire Federal Workforce
Case Study
'
Concfuding Observations
.
*
.
■
.
•
•
•
•
*
2
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Appendix I: Briefing Slides
Scope and Methodology
*
To answer our key question, we looked at data covering the
last 20 years in two different ways:
1, We examined the federal workforce at 3 points in time
( 1988: 1998, and 2007) to show changes in the pay gap
within the federal workforce as a whole over a 20-year
period®
2. We examined a cohort (group) of federal workers, i.e.,
those who entered the federal workforce in 1988, to look
for differences in the pay gap for this group over time5
.
■'■'■.'■'Hr.':'
"For this analysis, we used a 20 percent rarwot'i v
We followed the careers of workers in this ■
r\"e
1
<> c1> ‘ ■
n 'he CPDF for each of the 3 years.
era! workforce and later returned.
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Appendix I: Briefing Slides
.
A
& A 'P..■
■
«»»*>*■*: Ateoun&feitfty * irrtegray ►Rslfakiiisy
Scope and Methods (cont.)
• To inform our analyses, we:
• Reviewed existing literature and reports on gender and pay
• Consulted officials at the Office of Personnel Management and
the Equal Employment Opportunity Commission—agencies
that are in part responsible for overseeing the employment
practices of federal agencies
~
6
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Apih
ik I L v
1- Brii'fini! Slides
'
-
-
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am*
-
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v-rnm* wwt * »»k « • <
#
.J
j
A _ C L
Ix m W mm* fteeounSabiiity' ioSegriiv * fteltaatfity
1
Background: Federal Workers Are Classified
in Six General Categories
Occupational category
Description
Professional
Requires knowledge in a specific discipline, typically acquired through a bachelor's
or higher degree in a specialized field. Examples include accounting and
engineering.:
.
■
Administrative
Does not have a specific educational requirement, but involves skills typically
gained through general college education. Examples include human resources
management and budget analysis.
Technical
Occupations typically associated with and supportive of a professional or
administrative field. Includes medical technicians, safety technicians, and food
inspectors.
■■
■
Clerical
Involves structured work in support of office, business, or fiscal operations.
Examples include typists, dispatchers, and clerks.
Other white-collar
Includes positions that do not fall into other white-collar groups. Most of these
positions are related to law enforcement or protective services.
B lu e -co lla r
Occupations comprising the crafts, trades, and manual labor, including foremen.
Source: OPM .
10
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A ppendix I: B rfrfing Slides
iu .
ismw*
Cj A O
Background: Federal Employees Are Increasingly
Concentrated in Professional and Administrative Jobs
(cont.)
• The decline in clerical and blue-collar employment may be
due to the following trends:
• Many defense-related jobs being phased out following the
end of the Cold W ar
• Government efforts to increase efficiency through
automation and by contracting out jobs
12
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A p p e n d ix i: BWofins< SSldfS
Findings: Federal Workforce
5
Occupation, Education, and Experience are the
Measurable Factors that Contribute Most to the Gap
Federal Workers: Proportion of Pay Gap Dye to Differences in Measurable Factors between Men and Women
Pay Gap between men and women (in cents)
30
1988
1998
2007
Year
j
j Unexplained pay gap
I
] Part of the pay gap resulting from differences in other characteristics
HI
Past of the pay gap resulting from differences in experience levels
Part of the pay gap resuiting from differences in education levels
Part of the pay yap resuiting from differences in occupations
Source: GAO analysis of C PDF data.
19
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GAO-09-279 Women’s Pay
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A p p e n d ix I. B rie fin g Slides
Concluding Observations
• The decline in the pay gap for the federal workforce is
primarily due to men and women in the federal workforce
becoming more alike in characteristics related to pay
• We cannot be sure why a persistent unexplained pay gap
remains for both analyses, but this may be due to the inability
to account for certain factors that cannot effectively be
measured or for which data are not available
34
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Page 38
i
i G A O
A ccountability * Integrity * Reliability___________________________
United S tates Governm ent A ccountability Office
W ashington, DC 20548
September 20, 2010
The Honorable Carolyn B. Maloney
Chair
Joint Economic Committee
United States Congress
The Honorable John D. Dingell
House of Representatives
Subject: Women in Management: A nalysis o f Female Managers' Representation,
Characteristics, and Pay
According to data from the Bureau of Labor Statistics, women made up nearly
47 percent of the total workforce in the United States in July 2010.1Women’s
participation in the labor force, particularly among women with children, is much
higher today than several decades ago. For example, using data from the Current
Population Survey, the Bureau of Labor Statistics reported that couples in which only
the husband worked represented 18 percent of married couple families in 2007,
compared with 36 percent in 1967.2 In addition, an increasing proportion of women
are attaining higher education. Among women aged 25 to 64 in the labor force, the
proportion with a college degree roughly tripled from 1970 to 2008. Further, the Equal
Employment Opportunity Commission found that the percentage of female officials
and managers in the private sector increased from just over 29 percent in 1990 to 36.4
percent in 2002.3
Although women’s representation across the general workforce is growing, there
remains a need for information about the challenges women face in advancing their
careers. In 2001, using 1995 and 2000 data from the Current Population Survey, we
‘U.S. Department of Labor, Bureau of Labor Statistics, USDL-10-1076, The E m ploym ent S itu a tio n J u ly 2010 (Washington, D.C., Aug. 6, 2010).
2U.S. Department of Labor, Bureau of Labor Statistics, Women in the Labor Force: A Databook
(Washington, D.C., September 2009).
3U.S. Equal Employment Opportunity Commission, Glass Ceilings: The Status o f Women as Officials
and Managers in the Private Sector (Washington, D.C., March 2004). In addition, Bureau of Labor
Statistics data show that the number of employed women working as chief executives and general and
operations managers increased from 24 percent in 2004 to 27 percent in 2008.
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GAO-1Q-892R W omen in M anagem ent
found women were less represented in management than in the overall workforce in
4 of the 10 industries reviewed.4 We also found differences in the characteristics and
pay of male and female managers, which we explored using statistical modeling
techniques. To respond to your request that we update this information to 2007, this
report addresses the following three questions: (1) What is the representation of
women in management positions compared to their representation in
nonmanagement positions by industry? (2) What are the key characteristics of
women and men in management positions by industry? and (3) What is the difference
in pay between women and men in full-time management positions by industry?5
Enclosed are fact sheets that provide detailed results of our analysis (see enclosure
I). In summary, we found the following:
•
Based on our own analysis of 13 industry sectors in both 2000 and 2007, we
found that in 2007 women comprised an estimated 40 percent of managers and
49 percent of nonmanagers on average for the industry sectors we analyzed—
industries that comprised almost all of the nation’s workforce—compared to
39 percent of managers and 49 percent of nonmanagers in 2000. In all but three
industry sectors women were less than proportionately represented in
management positions than in nonmanagement positions. Women were more
than proportionately represented in management positions in construction and
public administration, and there was no statistically significant difference
between women’s representation in management and nonmanagement
positions for the transportation and utilities sector.
•
According to our estimates, female managers in 2007 had less education, were
younger on average, were more likely to work part-time,6 and were less likely
to be married or have children, than male managers. While the average female
married manager earned the majority of her own household's wages, her share
of household wages was smaller than the share contributed by the average
male married manager to his household's wages. These findings were generally
similar to findings for 2000.
•
The estimated difference in pay between female managers working full time
and male managers working full time narrowed slightly between 2000 and 2007
after adjusting for selected factors that were available and are commonly used
in examining salary levels, such as age, hours worked beyond full time, and
education. When looking at all industry sectors together and adjusting for
4GAO, Women in Management: A n a lysis o f Selected Data fr o m the Current Population Survey,
GAO-02-156 (Washington, D.C.: Oct. 23, 2001).
6We reported on the years 2000 through 2007 to avoid concerns about the role of the recession that
began in December 2007 and to avoid any complications to the analysis due to the change of survey
questions in the data set we used that were made in 2008.
6Our definition of individuals working part-time included those who were not working full time, but
reported usually working some hours per week, weeks worked, and wages earned, all over the past 12
months.
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2
these factors, we estimated that female managers earned 81 cents for every
dollar earned by male managers in 2007, compared to 79 cents in 2000. The
estimated adjusted pay difference varied by industry sector, with female
managers’ earnings ranging from 78 cents to 87 cents for every dollar earned
by male managers in 2007, depending on the industry sector.
Enclosure I also includes separate fact sheets on the findings for each industry sector
in alphabetical order by industry. Enclosure II provides summary information on the
characteristics we analyzed by industry.
Our findings were based on data we analyzed from the U.S. Census Bureau’s
American Community Survey (ACS) for the years 2000 through 2007. We selected
ACS rather than the Current Population Survey due to the greater number of
observations in ACS. We analyzed managers across all of the broad industry
categories used in ACS, representing the entire workforce, except for the agriculture
and mining sectors, individuals living in group quarters, and those who were not
living in a U.S. state or the District of Columbia.7We defined “managers” as all
individuals classified under the “manager occupation” category in ACS. In our
multivariate analysis of the differences in pay between male and female managers
working full time and year round by industry,8we used annual earnings as our
dependent variable, adjusting for certain characteristics that were available in the
dataset and commonly used to estimate adjusted pay differences. These include age,
hours worked beyond full-time, race and ethnicity, state, veteran status, education
level, citizenship, marital status, and presence of children in the household.9In
addition to analyses of ACS data, we reviewed selected GAO and other reports and
consulted with experts in conducting this analysis. We assessed the reliability of the
ACS generally and of data elements that were critical to our analyses by reviewing
documentation on the general design and methods of the ACS and on the specific
elements of the data that were used in our analysis, interviewing U.S. Census Bureau
officials knowledgeable about the ACS data, and completing our own electronic data
testing to assess the accuracy and completeness of the data used in our analyses.
Based on these efforts, we determined that they were sufficiently reliable for our
analyses. See Enclosure III for a detailed description of our methodology.
7We excluded agriculture because, according to the Bureau of Labor Statistics, farmers may have other
sources of income, such as from federal subsidies, which may not be reported in ACS as income and
would complicate our analysis on pay differentials. We excluded mining because we found a relatively
limited number of observations in the mining industry. According to ACS, group quarters is a place
where people live or stay in a group living arrangement that is owned or managed by an entity or
organization providing housing and/or services for the residents. Examples include college residence
halls, nursing homes, group homes, military barracks, correctional facilities, and mental hospitals.
8Our definition of individuals working full time were those who, over the past 12 months, reported
usually working greater than or equal to 35 hours per week and 50 weeks per year, and reported
positive wages earned.
“When we looked at all industries together, we also adjusted for industry sector.
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3
Our analysis is descriptive in nature. Our analysis neither confirms nor refutes the
presence of discriminatory practices. Some of the unexplained differences in pay
seen here could be explained by factors for which we lacked data or are difficult to
measure, such as level of managerial responsibility, field of study, years of
experience, or discriminatory practices, all of which can be found in the research
literature as affecting earnings. More detailed information on the characteristics of
women in management in specific industries could help policymakers to identify
actions, if any, to help women advance to management positions. For example,
starting in 2009, the ACS included a question on field of study, a variable recognized
as important in examining differences in pay and advancement. Improvements to the
type of data available, such as this one, could help researchers to better understand
the determinants of salary and advancement.
We conducted our work from February 2010 to September 2010 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.
Agency Comments and Our Evaluation
We provided a draft of this report to the Departments of Commerce and Labor for
review and comment. Both agencies provided technical comments, which we
incorporated where appropriate.
As agreed with your office, unless you publicly announce the contents of this report
earlier, we plan no furthers distribution until 30 days from the report date. At that
time, we will send copies of this report to the Secretaries of Commerce and Labor,
relevant congressional committees, and other interested parties. In addition, the
report will be available at no charge on GAO’s Web site at http://www.gao.gov.
4
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E n c lo su r e I
KEY CHARACTERISTICS OF WOMEN IN
MANAGEMENT
GAP
Accountability»integrity*Reliability
Analysis of All Industry Sectors Combined
Industry Characteristics
Estimates for Characteristics of Managers by Gender, 2007
The 13 broad industry sectors we
selected represent all industries in
the U.S. workforce, except
agriculture and mining, and
individuals living in group quarters,
and those who were not living in a
U.S. state or the District of
Columbia.
According to our estimates, for most industries in 2007, female managers
were younger, had less education, were more likely to work part-time, and
were less likely to be married or have children in the household than male
managers. While the average female married manager earned the majority
of her own household's wages, her share of household wages was smaller
than the share contributed by the average male married manager to his
household's wages.
Education and managers
Age of managers
Average
age
Total workers2
2 0 0 0 : 141.1 million
2 0 0 7 :147.7 million
j
4 3 .4 years
Men
1 4 5 .2
I 62%
j 67%
33%
Total management positions
2 0 0 0 : 11.7 million
2 0 0 7 : 12.9 million
1?1%
I 56°/
(or higher)
under 40 « ► 40 or older
38% [
Bachelor’s
degree
Masters
degree
I '
^
9% (Women)
I------- \
(Men)
: J 20%
2
(or higher) 1
Children and managers
Number of children in the household
Percent
who are
married
Estimated female representation
2000
Share of
household
wages
Managers: 39 percent
Nonmanagers: 49 percent
2007
Women
-■
| 55% of h
Husbands
i 75%
|
X
One
O ne \ ,
3+
Two
Source: GAO analysis of American Community Survey data.
"This refers to the number of children under age 18 living in a household with a manager.
Managers: 40 percent
Nonmanagers: 49 percent
Median salaries for full-time managers
(2007 dollars)
.
2000
Female managers: $48,000
Male managers: $70,000
2007
Female managers: $52,000
Male managers: $75,000
These results were largely similar for 2000.
While both male and female managers experienced increases
in attainment of bachelor’s degrees or higher, women’s gains
surpassed men's. According t o our estimates, male managers with a
bachelor’s degree or higher increased from 53 percent in 2000
1o 56 percent in 2007, while female managers with a bachelor’s degree
or higher increased 6 percent age points from 45 percent
in 2000 to 51 percent in 2007. Similarly, while the share of male
managers wilh a master’s degree or higher went up less than 1
percentage point from 2000 to 2007, the share of female managers
with a master’s degree or higher rose nearly 4 percentage points.
Percent working part-time
2000
Female managers: 27 percent
: Male managers: 17 percent
:
Further Analysis of Characteristics of Managers by Gender
When looking at all industries together, we estimated a statist ically
significant difference in racial composition between male and female
managers in both 2007 and 2000. However, we did not find differences
in every industiy. In all o f the industries with differences in 2007,
female managers were more likely than male managers to be African
American.
2007
Feilniafe managers: 25 percent
. ■■^. Male managers: 1,7 percent
. Source: GAO analysis of American Community Survey data.
zOur counts of total workers and management positions may differ from those of
the Census Bureau due to differences in definitions of workers and other factors.
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Page 7
E n c lo su r e I
DIFFERENCES IN PAY
G
Analysis of All Industry Sectors Combined
A O
A cco u ntab ility
*
Integrity * Reliability
Examining Pay Differences ■ E s tim a te d Pay Differences for Full-Time Managers, 2000-2007
Researchers have not agreed on
the reasons for differences in pay
between women and men. Some
maintain these pay differences are
due t;o differences in personal
characteristics of working women
and men, such as educational
attainment. Others attribute pay
differences to the types of jobs in
which women and men typically
work, writh women more often
working in lower paying
occupations and jobs than men.
Our analysis adjusted for a select
number of variables that were
available and arc commonly used
when examining pay differences.
However, wTe acknowledge that
there are many variables and
methods of analysis, other than
those we included, that, could be
used that would yield different
numbers for an adjusted pay
difference than our analysis
yielded.
Some of the unexplained
differences in pay seen here could
be explained by factors for which
we lacked data or are difficult to
measure, such as level
of managerial responsibility, field
of study, years of experience, or
discriminatory practices, all of
which may affect earnings. Our
analysis neither confirms nor
refutes the presence of
discriminatory practices.
When looking at all industry sectors together, the estimated difference
in pay between female and male managers working full time narrow-ed
slightly between 2000 and 2007 w'hen adjusting for selected factors that
are important and available when examining salary levels.
Full-time
manager pay
(in dollars)
Managers
with children8
All
managers
Managers
without children3
Male
- pay
1.00
Adjusted
j - female pay &
81e
0.0
00 01
Year
02 03
04 05
06 07
00 01
Year
02 03
04 05
06 07
00 01
Year
02
03
04 OS 06 07
Source: GAO analysis of American Community Survey data-
Note: The narrowing of the gap between 2000 and 2007 for all managers and managers without
children in the household was statistically significant at the 95 percent confidence level. For 2001
2007, the margins of error for pay gaps differed for any single year by no greater than plus or minus
2 cents. See enclosure III for a table of margins of error for each year.
“Children refer to children under age 18 living in a household with a manager.
"For this analysis, we adjusted for age, hours worked beyond full time, race and ethnicity, state,
veteran status, education, industry sector, citizenship, marital status, and presence of children in
the household. We adjusted for industry sector to control fo r the possibility that pay differences could
occur because female managers tended to be employed in industries that had lower rates of pay.
However, we acknowledge that the distribution of female managers by industry sector itself might
reflect some level of discrimination associated with hiring, promotion, or other employer practices.
For the subsequent industry-specific analyses, we adjusted for the same variables, except we
excluded industry sector.
Further Analysis of Pay Differences by Gender
The adjusted difference in pay between male and female managers
with children in the household was larger than the difference in pay
for those without children in the household. Specifically, we found
that across all the years, female managers with children in the
household earned on average 79 cents for each dollar earned by male
managers with children in the household. Female managers without
children in the household earned an average of 82 cents for each
dollar earned by male managers without children in the household.
We did not adjust for factors that may influence pay for managers
with children, such as time off of work.
The adjusted pay difference varied by industry; female managers’
earnings ranged from 78 to 87 cent s for every dollar earned by male
managers in 2007, depending on the industry.
GAO-10-892R W omen in M anagem ent
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Source: GAO analysts of American Community Survey data,
------------------------------------------------------------
.
“Results were generally similar in 2000. However, the difference in the percentage
of male and female managers who had children in the household was not
statistically significant in 2000.
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GAO-1Q-892R Women in Management
.Source: GAO analysis of American Community Survey data.
---------------------------------------------------------- -
r’Results were generally similar in 2000. However, the differences in the
percentages of male and female managers who worked part-t ime and had
children in the household were not statistically significant in 2000.
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GAO-1Q-892R Women in Management
E n c lo su r e I
Percentage of health care and social assistance
employees among all industries
HEALTH CARE AND SOCIAL ASSISTANCE
Industry Snapshot
11%
V ___^12%
Source: GAO analysis of American Community Survey data.
industry Characteristics
Estimates for Characteristics of Managers by Gender, 2007
Management, positions in the health
care and social assistance sect or
included, for example, hospil al
administrators, clinical directors,
nursing superintendents, and
community center directors. There
was a larger proportion of female
managers in health care and social
assistance than within any other
industry.
Female managers were younger and had less education on average, were
less likely to be married, and were more likely to work part-time than
male managers. The difference in the percentage of managers who had
children in the household w as not statistically significant. Among married
managers, women contributed a smaller share than men of Iheir
respective household wages."
Acjc o* managers
Average
age
*" *
45.4 years
j Men
[ 46.9
31% |
2000:15.6 million
28% |
|
Masters
degree
I
" ------J ----- igers
55%
167%
(or higher) j Men
under 40 * ►40 or older
Total workers
Bachelor's
degree
89%
, (Women)
| 34% Pen)
(or higher) j
| 72%
Men
2007:18.4 million
Marriage and managers
Total management positions
Children and managers
Percent
who are
married
2000:1.0 million
2007:1.1 million
;
Share of
household
wages
Estimated female representation
2000
[ 55% of household wages
Husbands
r j i 72%
Source: GAO analysis of American Community Survey data.
Managers: 66 percent
T h is refers to the number of children under age 18 living in a household with a manager.
Nonmanagers: 81 percent
‘There was no statistically significant difference between female and male managers.
2007
Managers: 70 percent
Nonmanagers: 80 percent
Estimated Pay Differences fo r Full-Time Managers, 2000-2007
Median salaries for full-time managers
(2007 dollars)
2000
Fem&le managers: $48,000
Male managers: $66,000
The adjusted pay difference stayed about, the same between 2000 and
2007. Female managers earned between 76 and 81 cents for every dollar
earned by male managers.
Full-time manager pay
Male
(in doiiars)
managers' pay
2007
Female managers: $52,000
Male managers: $70,000
81(5
Percent working part-time
Female m m agvrs' m\? unadjusted
2000
Female managers: 26 perce
: Male managers: 17 percent
Female
managers'
pay adjusted
0.50
//
0.0
2007
Female managers: 22 perce
.....................
2000
2001
2002
2003
2006
2007
Year
Male managers: 15 percent
Source: GAO analysis of
trt Community Survey da!
Source; GAO analysts of American Community Survey data.
6In 2000, the differences in average age and in the percentage of managers aged
40 and older were not statistically significant. Other results were similar to 2007.
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GAO-10-892R Women in Management
[n 2000, the differences between male and female managers in average age and in
the percentages of managers who were aged 40 and older, had bachelor’s and
master’s degrees, and had children in the household were not statistically
significant. Other results were similar to 2007.
GAO-1Q-892R Women in Management
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spurceiQAoanalysisofAAsricancommunitysurveydata.
Source: GAO analysis, of American Community Survey data.
------------------------------------------------------------
111 2000, tlio differences between male and female managers in average age and in
the percentages of managers who were aged 40 and older and had master’s
degrees were not statistically significant. Other results were similar to 2007.
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Page 14
Source: GAO analysis of American Community Survey data,
—----------------------------------------------------------
’Results were generally similar in 2000. However, the difference in the percentage
of male and female managers with a master’s degree was not statistically
significant.
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Page 15
GAO-1Q-892R Women in Management
Source: GAO analysts of American Community Survey data.
------------------------------------------------------------
“in 2000, the differences in the percentages of managers who were aged 40 and
older, had master’s degrees, and had children in the household were not
statistically significant. Other results were similar to 2007.
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VerDate Nov 24 2008
Source; GAO analysis of American Community Survey data.
------------------------------------------------------------
“In 2000, the differences in the percentages o f male and female managers who
were aged 40 and older, w orked part-time, and had children in the household
w ere not statistically significant. Other results were similar to results in 2007.
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GAO-10-892R Women in Management
“In 2000, the differences in the percentages of managers who were aged 40 and
older and had children in the household were not statistically significant. Ill
addition, the difference in the percentage of managers with bachelor’s degrees
was statistically significant, with female managers less likely to have a bachelor’s
degree than male managers. Other results in 2000 wen' similar to results in 2007.
GAO-1Q-892R Women in Management
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source g a o analysis o! American community survey data.
E n c lo su r e I
Percentage of transportation and utilities
employees among all industries
200C
■5%
__ _
2007
, c = r — 5%
TRANSPORTATION AND UTILITIES
Industry Snapshot
Source: GAO analysis of American Community Survey data.
Industry Characteristics
Estimates for Characteristics of Managers by Gender, 2007
Management positions within the
transportation and utilities sector
included, for example,
transportation supervisors,
electrical superintendents, and
warehouse managers.
Female managers had less education on average, were less likely to be
married or have children in the household, and were more likely to work
part-time than male managers. The differences in average age and in the
percentages of managers aged 40 and older and with master’s degrees
were not statistically significant. Among married managers, women
contributed a smaller share than men of their respective household
w ages.'1
Total workers
Education and managers
Age of managers
2000; 7.4 million
2007: 7.6 million
1 45.8 years1
Average
age
J 46-3
{or higher)
under 40 < ► 40 or older
Total management positions
28%
27%
2000: 500,000
2007: 600,000
Bachelor's
degree
72%
Master’s
laster’s
degree
I
| 12%a (Women)
.
I---- >
>rhigher) |___ | 13%
(Men)
73%
Children and managers
Estimated female representation
Number of children in the househo!db
Percent
who are
married
2000
Managers: 26 percent
Nonmanagers: 26 percent
2007
Managers: 26 percent
Share of
household
wages
Nonmanagers: 25 percent
Source: GAO analysis of American Community Survey data.
Men
5 8 % of household wages
Husbands
75%
Th e re was no statistically significant difference between female and male managers,
Median salaries for full-time managers
(2007 dollars)
2000
Female managers: $48,000
Male managers: $66,000
2007
Female managers: $52,000
Male managers: $70,000
'This refers to the number of children under age 18 living in a household with a manager.
Estimated Pay Differences for Full-Time Managers, 2000-2007
The adjusted difference in pay fluctuated between 2000 and 2007, but was
not statistically significant in 2003.
Full-time manager pay
(in dollars)
managers’ pay
«-J
Percent working part-time
2000
Female managers: 25 perce
Male managers: 11 percent
2007
Female managers: 22 perce
Male managers: 15 percent
Female
managers'
pay adjusted
0.50
//
2000
2007
2003a
Year
Source: GAO analysis of American Community Survey data.
"There was no statistically significant difference between female and male managers in 2003.
“In 2000, the differences in age and in the percentage of managers aged 40 and
older were statistically significant; on average, female managers were younger
and less likely to be 40 and older than male managers. In addition, the differences
in the percentages of managers with bachelor’s degrees and with children were
not statistically significant Other results were similar to results in 2007.
Page 20
GAO-10-892R Women in Management
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Source: GAO analysis of American Community Survey data..
‘In 2000, the difference in the percentage of managers with bachelor’s degrees
was statistically significant with female managers being less likely to have a
bachelor’s degree than male managers. The differences hi the percentages of
managers who were aged 40 and older, worked part-time, and had children in the
household were not statistically significant. Other results were similar to 2007.
GAO-1Q-892R Women in Management
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Source: g a o analysis or American community survey data.
10:54 May 11, 2011
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Enclosure III
Objectives, Scope, and Methodology
Our review focused on (1) the representation of women in management positions
compared to their representation in nonmanagement positions by industry, (2) the
key characteristics of women and men in management positions by industry, and (3)
the difference in pay between women and men in full-time management positions by
industry. To answer these questions, we analyzed data from the Public Use
Microdata Sample of the American Community Survey (ACS) for the years 2000
through 2007.
Data
For all three research questions, we used data from the U.S. Census Bureau’s (Census
Bureau) ACS database. We selected ACS rather than the Current Population Survey,
which was used in GAO’s 2001 report on this issue, due to the greater number of
observations in ACS, which allowed us to have greater precision when looking at
specific industries. ACS is an ongoing national survey conducted by the Census
Bureau that collects information from a sample of households. ACS replaced the
decennial census long-form questionnaire as a source for social, economic,
demographic, and housing information.
Industry Selection
We organized approximately 250 discrete industries represented in ACS into 13
industry sectors that generally follow the ACS broad industry sectors with some
minor modifications. For example, we renamed some sectors, and separated
educational services from health care and social assistance. The industry sectors we
included represent the entire workforce, except for the agriculture and mining
sectors.
We excluded agriculture because, according to the Bureau of Labor Statistics,
farmers may have other sources of income, such as from federal subsidies, which
may not be reported in ACS as income and would complicate our analysis on pay
differentials. We excluded mining because we found a relatively limited number of
observations in the mining industry. We also excluded from the analysis those
individuals living in group quarters and those who were not living in a U.S. state or
the District of Columbia.1These restrictions resulted in a loss of about 3 percent of
the managers and 4 percent of nonmanagers represented in 2007.
‘According to ACS, a group quarters is a place where people live or stay in a group living arrangement.
Examples include college residence halls, nursing homes, group homes, military barracks, correctional
facilities, and mental hospitals.
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GAO-10-892R Women in Management
27
Enclosure III
Definitions
•
Our definition of working M l time included those who, over the past 12
months, reported usually working 35 hours or more per week and 50 weeks or
more per year, and those with wages greater than zero.
•
Our definition of individuals working part-time included those who were not
working full time, but reported usually working some hours per week, weeks
worked, and wages earned, all over the past 12 months.
•
Workers were individuals who reported working one or more weeks during
the past 12 months and reported receiving wage and salary income. Our
sample did not include self-employed workers unless they also received wage
and salary income. We relied on the individual’s reported industry of
employment; however, it may be that some individuals are employed in
multiple industries, which our analysis did not capture.
•
We defined managers as all individuals classified under the manager
occupation category in ACS, which includes a wide range of more than 1,000
job titles.2 Job titles under the manager code include positions such as school
principals, radio station managers, zoo directors, parking garage managers,
nurse administrators, and chief executives. The ACS manager occupation does
not include first-line supervisors who have largely the same duties and same
levels of education as those they supervise.
•
Due to the structure of ACS data, our definition of having children varied
depending on whether we were looking at only women or comparing women
and men. The ACS records information on the presence of children in two
ways: (1) at the household level and (2) with respect to individuals’ own
children within the household. We used the household-level variable to
compare women and men, and the individual-level variable to calculate
estimates for women only. The two variables are generally consistent with one
another. For example, in 2007, about 36 percent of female managers had one
or more of their own children living with them (according to the individuallevel variable), and about 37 percent lived in a household where there were
one or more of the householder’s own children (according to the householdlevel variable). In both cases, a person’s “own child” includes children by
birth, marriage (step), or adoption.
According to Census Bureau officials, occupations refer to categories of job titles. Some job titles
directly match to a specific occupation, such as Chief Executive Officer to chief executive; others may
cross into more than one occupation. Occupations may also be restricted by industry.
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28
Enclosure III
Data Reliability
We assessed the reliability of the ACS generally and of data elements that were
critical to our analyses and determined that, despite the limitations outlined below,
they were sufficiently reliable for our analyses. Specifically, we:
•
reviewed documentation on the general design and methods of the ACS and on
the specific elements of the ACS data that were used in our analysis,
•
interviewed Census Bureau officials knowledgeable about the ACS data and
consulted these officials periodically throughout the course of our study, and
•
completed our own electronic data testing to assess the accuracy and
completeness of the data used in our analyses.
As a result of these efforts, we identified the following limitations with the data:
•
Inconsistency of data sample. The data sample was not consistent in size
over 2000 to 2007. Since 2000, the ACS expanded its survey across the United
States. However, currently available Public Use Microdata Sample files for the
earliest years of ACS include sufficient data from a supplemental survey effort
to generate reliable national-level estimates. Based on discussions with Census
Bureau staff responsible for the ACS sampling, we determined the overall
sample sizes are large enough to produce statistically reliable results for each
industry sector during each year. However, in cases where a difference was
not statistically significant in one year but was in another, we could not rule
out the possibility that an analysis of a larger sample would have found
statistically significant differences in both years.
Manager definition. The manager category in the ACS was a slightly
imperfect measure of the true population of managers in the workforce. The
manager category in ACS included positions which may have disparate levels
of responsibility. ACS did not include variables describing the level of
responsibility of a manager, nor years of experience. Therefore, we were not
able to analyze these separately in our analysis of pay differentials. In addition,
the “manager” category does not include persons with de facto management
responsibilities not reflected in their titles. For example, a partner in a law
firm may not be listed as a manager even though he or she may have work
responsibilities similar to those of a manager.
29
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•
Enclosure III
•
Self-guided survey. The structure of data collection for ACS may introduce
errors. Since information was collected through a self-guided survey without
interviews, there was no opportunity during data collection to clarify
responses.3
• Underreporting of part-time hours. The survey questionnaire had an openended question regarding number of hours usually worked each week. Some
researchers studying this ACS question found that part-time workers tended to
under-report their weekly hours worked.4Because part-time workers are more
likely to be women, their hourly earnings may be more likely to be over
estimated in the data. We restricted the sample for the analysis of pay
differentials to full-time workers to address this data limitation.
•
Coding of open-ended responses. There are inherent limitations in coding
open-ended responses. We interviewed Census Bureau officials and reviewed
documentation regarding their protocol for coding occupation and industry for
ACS data entry and internal controls on coding open-ended survey responses,
and have judged them to be sufficiently reliable for our purposes.
The studies by Catalyst, Inc., on the representation of women among boards of
directors and top earners at Fortune 500 companies were reviewed by multiple
analysts, including a social scientist with expertise in estimation from survey data. In
addition, we interviewed and consulted with staff members from Catalyst, Inc., who
were knowledgeable about the organization’s methods of collecting, analyzing, and
reporting data in these studies. We determined, based both on these interviews and
on our review of the studies, that the data and methods were sufficiently reliable for
generating the estimates we present in this report.
Methods
Descriptive Statistics
To analyze our first question on the representation of women in management
positions, we used ACS to estimate the percentage of management positions within
each industry held by women compared to the percentage of nonmanagement
positions held by women in the same industry to take account of industries having
different gender compositions. We performed the same analysis to compare the
percentage of managers and nonmanagers who were mothers with children under 18
in the household.
According to Census Bureau officials, Computer Assisted Telephone Interviewing and Computer
Assisted Personal Interviewing are available for respondents who do not complete the paper
questionnaire.
4Nathaniel Baum-Snow and Derek Neal, “Mismeasurement of Usual Hours Worked in the Census and
ACS,” Economics Letters, Vol. 102, Issue 1 (2009).
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Enclosure III
For the second question, we used ACS to generate descriptive statistics on male and
female managers’ education levels, age, part-time status, marital status, and the
presence and number of children in the household. For married managers, we
computed their share of household wages for the years 2000 and 2007. For full-time
managers, we computed the median salary. Where we presented data on median
salaries, we adjusted the salaries to 2007 dollars, and rounded the salaries to the
nearest one thousand.
To take account of the sample design used in the ACS, we used the person weight
present in the ACS data file.5 For each measure, we tested whether the difference
between men and women was statistically significant at a 95 percent confidence level
in 2007 or in 2000. In addition, we tested whether the change for each gender
between 2000 and 2007 was statistically significant. For the differences in
percentages, we calculated sampling errors using the design-factor method described
in Census Bureau documentation on the proper use of ACS data. For 2007, we also
estimated confidence intervals using replicate weights provided with the ACS; these
weights were not available for 2000 ACS data. When the statistical significance of
differences calculated using the two methods differed, we present the results from
the replicate method of variance estimation.
We chose to report on the years 2000 through 2007 to avoid concerns about the role
of the recession that began in December, 2007 and to avoid any complications to the
analysis due to the change of survey questions ACS made in 2008. However, for each
measure, we tested whether the difference between men and women was statistically
significant at a 95 percent confidence level in 2008 as well to see any changes since
2007. In addition, we tested whether the change between 2007 and 2008 was
statistically significant for each gender. Except for the percentage of workers that
were part-time, which was affected by a change in a survey question in 2008, we
found there were very few statistically significant differences between 2007 and 2008
for any of the descriptive statistics.
Multivariate Regression Analysis Approach
For the third question, we used multivariate regression analysis to examine the
differences in pay between male and female managers. We limited the analysis to
those working full-time, because of limitations with calculating wages and hours for
part-time workers. For each industry, and for all industries combined, we conducted
a regression analysis of full-time managers within the ACS data set, which includes
men and women. In this analysis, we used an indicator variable for gender to measure
the average difference between men and women’s salaries. By including additional
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. Specifically:
5In the ACS data, each person represents different numbers of people in the population because of the
ACS sampling design. To account for this, the Census Bureau recommends using a “person weight” to
adjust the sample to represent the full population.
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Enclosure III
•
In order to determine the extent to which gender differences persist when
other characteristics of managers are taken into account, we performed
multivariate regression analysis to predict the logarithm of annual salary.
(Without controlling for factors) Ln(annual salary)
= a + (3*(female) + s
(With controlling for factors)
= a + P*(female)
Ln(annual salary)
+ S*(set of characteristics of the individual) + s
•
Because we used the logarithm of the annual salary, the standard
interpretation of (3, the coefficient on female, is that it represents the average
log point difference between 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 percent difference
(by exp(coefficient on female)).6
•
We performed this analysis for 8 years of ACS data (2000-2007), for each
industry separately, and for all industries combined. To take account of the
sample design used in the ACS, we used the person weight present in the ACS
data file.
. •
Our regression model included age, age squared, hours worked beyond full
time, dummy variables for race,7Hispanic status, state, veteran status,
education level, citizenship, marital status, and presence of children in the
household. In addition, our regression that combined all industries included a
dummy variable for each industry.
We acknowledge there are many variables and methods of analysis that could be used
that would yield different numbers for the adjusted differences in pay. Some variables
we would have included but were not available included managerial responsibility,
field of study, and years of experience.
The estimated 95 percent confidence intervals around the estimated adjusted
differences in pay for 2000 through 2007 are presented in table 1.
6Francine Blau and Lawrence Kahn, “Gender Differences in Pay,” The Journal of Economic
Perspectives, Vol. 14, No. 4 (2000). This is an issue that is especially important if the pay gaps are
large. See Robert Halvorsen and Raymond Palmquist, “The Interpretation of Dummy Variables in
Semi-Logarithmic Equations,”American Economic Review, Vol. 70, No. 3 (1980).
7While we included nine different racial categories in the regression, more than 95 percent of the
individuals were White, African American, or Asian.
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Enclosure III
Table 1: Estimates and Confidence Intervals for the Estimated Adjusted Differences in Pay, 2000-2007
Industry
Year
Lower bound
Estimated female
managers' earnings
for every dollar
earned by a male
manager
Upper bound
All industries combined
2000
$0.77
$0.79
$0.81
2001
$0.79
$0.80
$0.81
2002
$0.79
$0.80
$0.81
2003
$0.81
$0.82
$0.83
2004
$0.80
$0.81
$0.82
2005
$0.80
$0.81
$0.82
2006
$0.81
$0.81
$0.82
2007
$0.80
$0.81
$0.82
2000
$0.78
$0.92
$1.09
2001
$0.72
$0,78
$0.84
2002
$0.77
$0,85
$0.94
2003
$0.74
$0.82
$0.91
Construction
2004
$0.71
$0.78
$0.85
2005
$0.73
$0.77
$0.81
2006
$0.78
$0.82
$0.86
2007
$0.75
$0.78
$0.82
2000
$0.79
$0.85
$0.91
2001
$0.81
$0.84
$0.88
2002
$0.82
$0,85
$0.89
2003
$0.85
$0.90
$0.95
Educational services
2004
$0.85
$0.89
$0.93
2005
$0.82
$0.85
$0.87
2006
$0.84
$0.86
$0,88
2007
$0.84
$0.86
$0,88
Financial activities
2000
$0.66
$0.72
$0.79
2001
$0.75
$0.78
$0.82
2002
$0.73
$0.76
$0.80
2003
$0.76
$0.79
$0.83
2004
$0.76
$0.80
$0.84
2005
$0,80
$0,83
$0.85
2006
$0.79
$0.81
$0.83
2007
$0.76
$0.78
$0.80
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33
Enclosure III
Year
Industry
Estimated female
managers’ earnings
for every dollar
earned by a male
manager
Lower bound
Upper bound
Health care and social assistance
2000
$0,73
$0.79
$0.85
2001
$0.75
$0.79
$0.83
2002
$0.74
$0.78
$0.81
2003
$0.72
$0.76
$0,80
2004
$0.76
$0.80
$0.84
2005
$0.75
$0.78
$0.80
2006
$0.77
$0.79
$0.81
2007
$0.78
$0.81
$0.83
2000
$0.74
$0.82
$0.90
2001
$0.76
$0.81
$0.86
2002
$0.77
$0.83
$0.90
2003
$0.76
$0.82
$0.88
2004
$0.82
$0.90
$0.97
2005
$0.81
$0.85
$0.89
2006
$0.79
$0.83
$0.87
2007
$0.81
$0,84
$0.88
2000
$0.72
$0.79
$0,87
2001
$0.78
$0.82
$0.86
2002
$0.76
$0.80
$0.85
2003
$0.73
$0.79
$0.84
2004
$0.76
$0.80
$0.85
Information and communications
Leisure and hospitality
2005
$0.77
$0.80
$0.83
2006
$0.78
$0.81
$0.83
2007
$0.78
$0.80
$0.83
2000
$0.79
$0.85
$0.90
2001
$0.77
$0.80
$0.83
2002
$0.77
$0.80
$0.83
2003
$0.78
$0.81
$0.84
2004
$0.79
$0.83
$0.86
2005
$0.82
$0.84
$0.87
2006
$0.81
$0.83
$0.86
2007
$0.82
$0.84
$0.86
Manufacturing
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Enclosure III
Lower bound
Year
Industry
Estimated female
managers’ earnings
for every dollar
earned by a male
manager
Upper bound
Other services
2000
$0.70
$0.87
$1.07
2001
$0.74
$0.80
$0,86
2002
$0.80
$0.86
$0.93
2003
$0.76
$0.82
$0.88
2004
$0.73
$0.79
$0.85
2005
$0.74
$0.78
$0.82
2006
$0.78
$0.82
$0.86
2007
$0.80
$0.84
$0.88
2000
$0,70
$0.76
$0.82
2001
$0.78
$0.81
$0.85
2002
$0.76
$0.80
$0.84
2003
$0.82
$0.86
$0.90
2004
$0.79
$0.83
$0.87
2005
$0.78
$0.80
$0.83
2006
$0.81
$0.83
$0.85
2007
$0.79
$0.81
$0.84
2000
$0.82
$0.89
$0.97
2001
$0.83
$0,87
$0.91
2002
$0.84
$0.88
$0.92
2003
$0.88
$0.93
$0.98
2004
$0.83
$0.87
$0.90
2005
$0.86
$0.88
$0.91
2006
$0.83
$0.86
$0.89
2007
$0.85
$0.87
$0.90
2000
$0.68
$0.76
$0.85
Professional business services
Public administration
Retail trade
2001
$0.70
$0.74
$0,79
2002
$0.69
$0.74
$0.80
2003
$0.78
$0.84
$0.90
2004
$0.71
$0.76
$0.82
2005
$0.77
$0.81
$0.85
2006
$0.74
$0.77
$0.81
2007
$0.77
$0.81
$0.85
2000
$0.77
$0.86
Transportation and utilities
.
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$0.97
Enclosure III
Industry
Year
Lower bound
Estimated female
managers’ earnings
for every dollar
earned by a male
manager
Upper bound
$0.88
2001
$0.76
$0.82
2002
$0.72
$0.79
$0.86
2003
$0.77
$0.90
$1.06
2004
$0.75
$0.82
$0.90
2005
$0.74
$0.77
$0.81
2006
$0.78
$0.82
$0.86
2007
$0.78
$0.81
$0.85
2000
$0.60
$0.70
$0.81
Wholesale trade
2001
$0.74
$0.80
$0.87
2002
$0.72
$0.79
$0.86
2003
$0.81
$0.88
$0.95
2004
$0.74
$0.81
$0.89
2005
$0.74
$0.79
$0.84
2006
$0.75
$0.80
$0.85
2007
$0.79
$0.83
$0.88
Source; GAO calculations based on American Community Survey data.
Note: We calculated the margin of error by using a 95 percent confidence interval of the regression coefficient estimate.
Alternative Models
To determine whether the results of our analysis for all industries combined were
sensitive to the precise variables included, we estimated alternative versions of our
reported model. Specifically, we estimated models that (1) did not include dummy
variables for each industry, (2) did not adjust for marital status or presence of
children, and (3) included an interaction effect between type of education and age.
We found that not including a dummy variable for industry produced a larger gap, but
the results of the other two models were similar. The ranges of estimates are shown
in table 2.
Table 2: Ranges of Estimates of Women’s Pay Relative to Men’s Under Alternative Models
Model
Minimum estimate
Maximum estimate
$0.77
(+/-0.02)
$0.78
(+/-0.02)
$0.79
(+/-0.02)
$0.80
(+/-0.02)
$0.79
(+/-0.01)
$0.81
(+/-0.01)
$0.82
(+/-0.01)
$0.82
(+/-0.01)
Without industry controls
Without marital status or presence
of children
Reported model
Including interaction effect between
education and age
Source: GAO analysis of American Community Survey data. The 95 percent margin of error is piaced in parenthesis. For ail models, the minimum was estimated in
2000 and the maximum was estimated in 2003.
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Enclosure III
Including Children in the Salary Gap Analysis
In addition to the analysis described above, we also estimated a segregated model
designed to examine the impact of having children in the household on the
differences in pay between men and women for our analysis of all industries
combined. To do this, we estimated the regression equation two additional times:
first for managers with children in the household, and second for managers without
children in the household.
The segregated model allowed us to say whether the differences in pay varied for
individuals with and without children in the household. Additionally, the segregated
model did not assume the importance of factors that influence income (such as
education) are the same for those with and without children in the household.
Segregated analysis also allowed us to report two results for the differences in pay:
one for managers with children in the household— comparing the salary of women
with children in the household to that of men with children in the household—and
one for managers without children in the household—comparing the salary of women
without children in the household to the salary o f men without children in the
household—in addition to any baseline differences in pay we report for all
individuals.
Document Reviews and Interviews
We reviewed selected GAO and other articles and reports on this topic and consulted
with experts and Census Bureau officials to review our methods and provide the
appropriate context for the report.
Limitations of the Analysis
This report did not attempt to provide an extensive explanation for the difference in
earnings between male and female managers, such as by comparing the relative
importance of any of the variables in explaining the differences. In addition, our
analysis was not designed to determine the presence or absence of discrimination. As
shown in table 2 above, models with different variables can result in differences in
the estimates.
Because of concerns about disclosing identities of respondents, the Census Bureau
limits reported salaries in the publicly available ACS data. The level of limit, or “topcode” varies by state and year. When the pay is top-coded, our calculations use an
underestimate of the true salary. If male managers were more likely than female
managers to earn the highest wages (and be top-coded), this may have led us to
report a smaller average difference in pay than actually exists. For all of the managers
in our data across all of the years, we found that approximately 5 percent had wages
that were top-coded. However, we did not know the extent to which the true salary is
above the top-code.
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Enclosure IV
GAO C ontact and S ta ff A cknow ledgm ents
GAO C ontact
Andrew Sherrill, (202) 512-7215 or sherrilla@gao.gov
S ta ff Acknow ledgm ents
In addition to the contact named above, Heather Hahn (Assistant Director) and Kate
Blumenreich (Analyst-in-Charge) managed this report, and James Bennett, Susan
Bernstein, Ben Bolitzer, Russ Burnett, Anna Maria Ortiz, Lindsay Read, and Shana
Wallace made significant contributions. Also contributing to this work were Patrina
Clark, Ron Fecso, and James Rebbe.
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Related GAO Products
Financial Services Industry: Overall Trends in Management-Level D iversity and
D iversity Initiatives, 1993-2008. GAO-10-736T. Washington, D.C.: May 12, 2010.
Women’s Pay: Converging Characteristics of Men and Women in the Federal
Workforce Help Explain the N arrowing Pay Gap. GAO-09-621T. Washington, D.C.:
April 28, 2009.
Women’s Pay: Gender Pay Gap in the Federal Workforce Narrows as Differences in
Occupation, Education, and Experience D im inish. GAO-09-279. Washington, D.C.:
March 17, 2009.
Women's Earnings: Federal Agencies Should B etter M onitor Their Performance in
Enforcing A nti-D iscrim ination Laws. GAO-08-799. Washington, D.C.: August 11,
2008
Financial Services Industry: Overall Trends in Management-Level D iversity and
D iversity Initiatives, 1993-2006. GAO-08-445T. Washington, D.C.: February 7, 2008.
Women and Low-Skilled Workers: Efforts in Other Countries to Help These Workers
Enter and Rem ain in the Workforce. GAO-07-989T. Washington, D.C.: June 14, 2007.
Women and Low-Skilled Workers: Other Countries’Policies and Practices That May
Help These Workers Enter and R em ain in the Labor Force. GAO-07-817. Washington,
D.C.: June 14, 2007.
Financial Services Industry: Overall Trends in Management-Level D iversity and
D iversity Initiatives, 1993-2004. GAO-06-617. Washington, D.C.: June 1, 2006.
Gender Issues: Women's Participation in the Sciences Has Increased, but Agencies
Need to Do More to Ensure Compliance w ith Title IX. GAO-04-639. Washington, D.C.:
July 22, 2004.
Women’s Earnings: Work Patterns Partially E xplain Difference between Men’s and
Women’s Earnings. GAO-04-35. Washington, D.C.: October 31, 2003.
Women in Management: A nalysis o f Current Population Survey Data. GAO-02648T. Washington, D.C.: April 22, 2002.
Women in Management: A nalysis of Selected Data from the Current Population
Survey. GAO-02-156. Washington, D.C.: October 23, 2001.
( 130989)
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