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Report | Wages, Incomes, and Wealth

“Women’s work” and the gender pay gap : How discrimination, societal norms, and other forces affect women’s occupational choices—and their pay

Report • By Jessica Schieder and Elise Gould • July 20, 2016

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What this report finds: Women are paid 79 cents for every dollar paid to men—despite the fact that over the last several decades millions more women have joined the workforce and made huge gains in their educational attainment. Too often it is assumed that this pay gap is not evidence of discrimination, but is instead a statistical artifact of failing to adjust for factors that could drive earnings differences between men and women. However, these factors—particularly occupational differences between women and men—are themselves often affected by gender bias. For example, by the time a woman earns her first dollar, her occupational choice is the culmination of years of education, guidance by mentors, expectations set by those who raised her, hiring practices of firms, and widespread norms and expectations about work–family balance held by employers, co-workers, and society. In other words, even though women disproportionately enter lower-paid, female-dominated occupations, this decision is shaped by discrimination, societal norms, and other forces beyond women’s control.

Why it matters, and how to fix it: The gender wage gap is real—and hurts women across the board by suppressing their earnings and making it harder to balance work and family. Serious attempts to understand the gender wage gap should not include shifting the blame to women for not earning more. Rather, these attempts should examine where our economy provides unequal opportunities for women at every point of their education, training, and career choices.

Introduction and key findings

Women are paid 79 cents for every dollar paid to men (Hegewisch and DuMonthier 2016). This is despite the fact that over the last several decades millions more women have joined the workforce and made huge gains in their educational attainment.

Critics of this widely cited statistic claim it is not solid evidence of economic discrimination against women because it is unadjusted for characteristics other than gender that can affect earnings, such as years of education, work experience, and location. Many of these skeptics contend that the gender wage gap is driven not by discrimination, but instead by voluntary choices made by men and women—particularly the choice of occupation in which they work. And occupational differences certainly do matter—occupation and industry account for about half of the overall gender wage gap (Blau and Kahn 2016).

To isolate the impact of overt gender discrimination—such as a woman being paid less than her male coworker for doing the exact same job—it is typical to adjust for such characteristics. But these adjusted statistics can radically understate the potential for gender discrimination to suppress women’s earnings. This is because gender discrimination does not occur only in employers’ pay-setting practices. It can happen at every stage leading to women’s labor market outcomes.

Take one key example: occupation of employment. While controlling for occupation does indeed reduce the measured gender wage gap, the sorting of genders into different occupations can itself be driven (at least in part) by discrimination. By the time a woman earns her first dollar, her occupational choice is the culmination of years of education, guidance by mentors, expectations set by those who raised her, hiring practices of firms, and widespread norms and expectations about work–family balance held by employers, co-workers, and society. In other words, even though women disproportionately enter lower-paid, female-dominated occupations, this decision is shaped by discrimination, societal norms, and other forces beyond women’s control.

This paper explains why gender occupational sorting is itself part of the discrimination women face, examines how this sorting is shaped by societal and economic forces, and explains that gender pay gaps are present even  within  occupations.

Key points include:

• Gender pay gaps within occupations persist, even after accounting for years of experience, hours worked, and education.
• Decisions women make about their occupation and career do not happen in a vacuum—they are also shaped by society.
• The long hours required by the highest-paid occupations can make it difficult for women to succeed, since women tend to shoulder the majority of family caretaking duties.
• Many professions dominated by women are low paid, and professions that have become female-dominated have become lower paid.

This report examines wages on an hourly basis. Technically, this is an adjusted gender wage gap measure. As opposed to weekly or annual earnings, hourly earnings ignore the fact that men work more hours on average throughout a week or year. Thus, the hourly gender wage gap is a bit smaller than the 79 percent figure cited earlier. This minor adjustment allows for a comparison of women’s and men’s wages without assuming that women, who still shoulder a disproportionate amount of responsibilities at home, would be able or willing to work as many hours as their male counterparts. Examining the hourly gender wage gap allows for a more thorough conversation about how many factors create the wage gap women experience when they cash their paychecks.

Within-occupation gender wage gaps are large—and persist after controlling for education and other factors

Those keen on downplaying the gender wage gap often claim women voluntarily choose lower pay by disproportionately going into stereotypically female professions or by seeking out lower-paid positions. But even when men and women work in the same occupation—whether as hairdressers, cosmetologists, nurses, teachers, computer engineers, mechanical engineers, or construction workers—men make more, on average, than women (CPS microdata 2011–2015).

As a thought experiment, imagine if women’s occupational distribution mirrored men’s. For example, if 2 percent of men are carpenters, suppose 2 percent of women become carpenters. What would this do to the wage gap? After controlling for differences in education and preferences for full-time work, Goldin (2014) finds that 32 percent of the gender pay gap would be closed.

However, leaving women in their current occupations and just closing the gaps between women and their male counterparts within occupations (e.g., if male and female civil engineers made the same per hour) would close 68 percent of the gap. This means examining why waiters and waitresses, for example, with the same education and work experience do not make the same amount per hour. To quote Goldin:

Another way to measure the effect of occupation is to ask what would happen to the aggregate gender gap if one equalized earnings by gender within each occupation or, instead, evened their proportions for each occupation. The answer is that equalizing earnings within each occupation matters far more than equalizing the proportions by each occupation. (Goldin 2014)

This phenomenon is not limited to low-skilled occupations, and women cannot educate themselves out of the gender wage gap (at least in terms of broad formal credentials). Indeed, women’s educational attainment outpaces men’s; 37.0 percent of women have a college or advanced degree, as compared with 32.5 percent of men (CPS ORG 2015). Furthermore, women earn less per hour at every education level, on average. As shown in Figure A , men with a college degree make more per hour than women with an advanced degree. Likewise, men with a high school degree make more per hour than women who attended college but did not graduate. Even straight out of college, women make $4 less per hour than men—a gap that has grown since 2000 (Kroeger, Cooke, and Gould 2016).

Women earn less than men at every education level : Average hourly wages, by gender and education, 2015

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The data underlying the figure.

Source :  EPI analysis of Current Population Survey Outgoing Rotation Group microdata

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Steering women to certain educational and professional career paths—as well as outright discrimination—can lead to different occupational outcomes

The gender pay gap is driven at least in part by the cumulative impact of many instances over the course of women’s lives when they are treated differently than their male peers. Girls can be steered toward gender-normative careers from a very early age. At a time when parental influence is key, parents are often more likely to expect their sons, rather than their daughters, to work in science, technology, engineering, or mathematics (STEM) fields, even when their daughters perform at the same level in mathematics (OECD 2015).

Expectations can become a self-fulfilling prophecy. A 2005 study found third-grade girls rated their math competency scores much lower than boys’, even when these girls’ performance did not lag behind that of their male counterparts (Herbert and Stipek 2005). Similarly, in states where people were more likely to say that “women [are] better suited for home” and “math is for boys,” girls were more likely to have lower math scores and higher reading scores (Pope and Sydnor 2010). While this only establishes a correlation, there is no reason to believe gender aptitude in reading and math would otherwise be related to geography. Parental expectations can impact performance by influencing their children’s self-confidence because self-confidence is associated with higher test scores (OECD 2015).

By the time young women graduate from high school and enter college, they already evaluate their career opportunities differently than young men do. Figure B shows college freshmen’s intended majors by gender. While women have increasingly gone into medical school and continue to dominate the nursing field, women are significantly less likely to arrive at college interested in engineering, computer science, or physics, as compared with their male counterparts.

Women arrive at college less interested in STEM fields as compared with their male counterparts : Intent of first-year college students to major in select STEM fields, by gender, 2014

Source:  EPI adaptation of Corbett and Hill (2015) analysis of Eagan et al. (2014)

These decisions to allow doors to lucrative job opportunities to close do not take place in a vacuum. Many factors might make it difficult for a young woman to see herself working in computer science or a similarly remunerative field. A particularly depressing example is the well-publicized evidence of sexism in the tech industry (Hewlett et al. 2008). Unfortunately, tech isn’t the only STEM field with this problem.

Young women may be discouraged from certain career paths because of industry culture. Even for women who go against the grain and pursue STEM careers, if employers in the industry foster an environment hostile to women’s participation, the share of women in these occupations will be limited. One 2008 study found that “52 percent of highly qualified females working for SET [science, technology, and engineering] companies quit their jobs, driven out by hostile work environments and extreme job pressures” (Hewlett et al. 2008). Extreme job pressures are defined as working more than 100 hours per week, needing to be available 24/7, working with or managing colleagues in multiple time zones, and feeling pressure to put in extensive face time (Hewlett et al. 2008). As compared with men, more than twice as many women engage in housework on a daily basis, and women spend twice as much time caring for other household members (BLS 2015). Because of these cultural norms, women are less likely to be able to handle these extreme work pressures. In addition, 63 percent of women in SET workplaces experience sexual harassment (Hewlett et al. 2008). To make matters worse, 51 percent abandon their SET training when they quit their job. All of these factors play a role in steering women away from highly paid occupations, particularly in STEM fields.

The long hours required for some of the highest-paid occupations are incompatible with historically gendered family responsibilities

Those seeking to downplay the gender wage gap often suggest that women who work hard enough and reach the apex of their field will see the full fruits of their labor. In reality, however, the gender wage gap is wider for those with higher earnings. Women in the top 95th percentile of the wage distribution experience a much larger gender pay gap than lower-paid women.

Again, this large gender pay gap between the highest earners is partially driven by gender bias. Harvard economist Claudia Goldin (2014) posits that high-wage firms have adopted pay-setting practices that disproportionately reward individuals who work very long and very particular hours. This means that even if men and women are equally productive per hour, individuals—disproportionately men—who are more likely to work excessive hours and be available at particular off-hours are paid more highly (Hersch and Stratton 2002; Goldin 2014; Landers, Rebitzer, and Taylor 1996).

It is clear why this disadvantages women. Social norms and expectations exert pressure on women to bear a disproportionate share of domestic work—particularly caring for children and elderly parents. This can make it particularly difficult for them (relative to their male peers) to be available at the drop of a hat on a Sunday evening after working a 60-hour week. To the extent that availability to work long and particular hours makes the difference between getting a promotion or seeing one’s career stagnate, women are disadvantaged.

And this disadvantage is reinforced in a vicious circle. Imagine a household where both members of a male–female couple have similarly demanding jobs. One partner’s career is likely to be prioritized if a grandparent is hospitalized or a child’s babysitter is sick. If the past history of employer pay-setting practices that disadvantage women has led to an already-existing gender wage gap for this couple, it can be seen as “rational” for this couple to prioritize the male’s career. This perpetuates the expectation that it always makes sense for women to shoulder the majority of domestic work, and further exacerbates the gender wage gap.

Female-dominated professions pay less, but it’s a chicken-and-egg phenomenon

Many women do go into low-paying female-dominated industries. Home health aides, for example, are much more likely to be women. But research suggests that women are making a logical choice, given existing constraints . This is because they will likely not see a significant pay boost if they try to buck convention and enter male-dominated occupations. Exceptions certainly exist, particularly in the civil service or in unionized workplaces (Anderson, Hegewisch, and Hayes 2015). However, if women in female-dominated occupations were to go into male-dominated occupations, they would often have similar or lower expected wages as compared with their female counterparts in female-dominated occupations (Pitts 2002). Thus, many women going into female-dominated occupations are actually situating themselves to earn higher wages. These choices thereby maximize their wages (Pitts 2002). This holds true for all categories of women except for the most educated, who are more likely to earn more in a male profession than a female profession. There is also evidence that if it becomes more lucrative for women to move into male-dominated professions, women will do exactly this (Pitts 2002). In short, occupational choice is heavily influenced by existing constraints based on gender and pay-setting across occupations.

To make matters worse, when women increasingly enter a field, the average pay in that field tends to decline, relative to other fields. Levanon, England, and Allison (2009) found that when more women entered an industry, the relative pay of that industry 10 years later was lower. Specifically, they found evidence of devaluation—meaning the proportion of women in an occupation impacts the pay for that industry because work done by women is devalued.

Computer programming is an example of a field that has shifted from being a very mixed profession, often associated with secretarial work in the past, to being a lucrative, male-dominated profession (Miller 2016; Oldenziel 1999). While computer programming has evolved into a more technically demanding occupation in recent decades, there is no skills-based reason why the field needed to become such a male-dominated profession. When men flooded the field, pay went up. In contrast, when women became park rangers, pay in that field went down (Miller 2016).

Further compounding this problem is that many professions where pay is set too low by market forces, but which clearly provide enormous social benefits when done well, are female-dominated. Key examples range from home health workers who care for seniors, to teachers and child care workers who educate today’s children. If closing gender pay differences can help boost pay and professionalism in these key sectors, it would be a huge win for the economy and society.

The gender wage gap is real—and hurts women across the board. Too often it is assumed that this gap is not evidence of discrimination, but is instead a statistical artifact of failing to adjust for factors that could drive earnings differences between men and women. However, these factors—particularly occupational differences between women and men—are themselves affected by gender bias. Serious attempts to understand the gender wage gap should not include shifting the blame to women for not earning more. Rather, these attempts should examine where our economy provides unequal opportunities for women at every point of their education, training, and career choices.

— This paper was made possible by a grant from the Peter G. Peterson Foundation. The statements made and views expressed are solely the responsibility of the authors.

— The authors wish to thank Josh Bivens, Barbara Gault, and Heidi Hartman for their helpful comments.

About the authors

Jessica Schieder joined EPI in 2015. As a research assistant, she supports the research of EPI’s economists on topics such as the labor market, wage trends, executive compensation, and inequality. Prior to joining EPI, Jessica worked at the Center for Effective Government (formerly OMB Watch) as a revenue and spending policies analyst, where she examined how budget and tax policy decisions impact working families. She holds a bachelor’s degree in international political economy from Georgetown University.

Elise Gould , senior economist, joined EPI in 2003. Her research areas include wages, poverty, economic mobility, and health care. She is a co-author of The State of Working America, 12th Edition . In the past, she has authored a chapter on health in The State of Working America 2008/09; co-authored a book on health insurance coverage in retirement; published in venues such as The Chronicle of Higher Education ,  Challenge Magazine , and Tax Notes; and written for academic journals including Health Economics , Health Affairs, Journal of Aging and Social Policy, Risk Management & Insurance Review, Environmental Health Perspectives , and International Journal of Health Services . She holds a master’s in public affairs from the University of Texas at Austin and a Ph.D. in economics from the University of Wisconsin at Madison.

Anderson, Julie, Ariane Hegewisch, and Jeff Hayes 2015. The Union Advantage for Women . Institute for Women’s Policy Research.

Blau, Francine D., and Lawrence M. Kahn 2016. The Gender Wage Gap: Extent, Trends, and Explanations . National Bureau of Economic Research, Working Paper No. 21913.

Bureau of Labor Statistics (BLS). 2015. American Time Use Survey public data series. U.S. Census Bureau.

Corbett, Christianne, and Catherine Hill. 2015. Solving the Equation: The Variables for Women’s Success in Engineering and Computing . American Association of University Women (AAUW).

Current Population Survey Outgoing Rotation Group microdata (CPS ORG). 2011–2015. Survey conducted by the Bureau of the Census for the Bureau of Labor Statistics [ machine-readable microdata file ]. U.S. Census Bureau.

Goldin, Claudia. 2014. “ A Grand Gender Convergence: Its Last Chapter .” American Economic Review, vol. 104, no. 4, 1091–1119.

Hegewisch, Ariane, and Asha DuMonthier. 2016. The Gender Wage Gap: 2015; Earnings Differences by Race and Ethnicity . Institute for Women’s Policy Research.

Herbert, Jennifer, and Deborah Stipek. 2005. “The Emergence of Gender Difference in Children’s Perceptions of Their Academic Competence.” Journal of Applied Developmental Psychology , vol. 26, no. 3, 276–295.

Hersch, Joni, and Leslie S. Stratton. 2002. “ Housework and Wages .” The Journal of Human Resources , vol. 37, no. 1, 217–229.

Hewlett, Sylvia Ann, Carolyn Buck Luce, Lisa J. Servon, Laura Sherbin, Peggy Shiller, Eytan Sosnovich, and Karen Sumberg. 2008. The Athena Factor: Reversing the Brain Drain in Science, Engineering, and Technology . Harvard Business Review.

Kroeger, Teresa, Tanyell Cooke, and Elise Gould. 2016.  The Class of 2016: The Labor Market Is Still Far from Ideal for Young Graduates . Economic Policy Institute.

Landers, Renee M., James B. Rebitzer, and Lowell J. Taylor. 1996. “ Rat Race Redux: Adverse Selection in the Determination of Work Hours in Law Firms .” American Economic Review , vol. 86, no. 3, 329–348.

Levanon, Asaf, Paula England, and Paul Allison. 2009. “Occupational Feminization and Pay: Assessing Causal Dynamics Using 1950-2000 U.S. Census Data.” Social Forces, vol. 88, no. 2, 865–892.

Miller, Claire Cain. 2016. “As Women Take Over a Male-Dominated Field, the Pay Drops.” New York Times , March 18.

Oldenziel, Ruth. 1999. Making Technology Masculine: Men, Women, and Modern Machines in America, 1870-1945 . Amsterdam: Amsterdam University Press.

Organisation for Economic Co-operation and Development (OECD). 2015. The ABC of Gender Equality in Education: Aptitude, Behavior, Confidence .

Pitts, Melissa M. 2002. Why Choose Women’s Work If It Pays Less? A Structural Model of Occupational Choice. Federal Reserve Bank of Atlanta, Working Paper 2002-30.

Pope, Devin G., and Justin R. Sydnor. 2010. “ Geographic Variation in the Gender Differences in Test Scores .” Journal of Economic Perspectives , vol. 24, no. 2, 95–108.

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The Enduring Grip of the Gender Pay Gap

Table of contents, how the gender pay gap increases with age, mothers with children at home tend to be less engaged with the workplace, while fathers are more active, employed mothers earn about the same as similarly educated women without children at home; both groups earn less than fathers, progress in closing the gender pay gap has slowed despite gains in women’s education, gender pay gap differs widely by race and ethnicity, broader economic forces may impact men’s and women’s earnings in different ways, what’s next for the gender pay gap.

The gender pay gap – the difference between the earnings of men and women – has barely closed in the United States in the past two decades. In 2022, American women typically earned 82 cents for every dollar earned by men. That was about the same as in 2002, when they earned 80 cents to the dollar. The slow pace at which the gender pay gap has narrowed this century contrasts sharply with the progress in the preceding two decades: In 1982, women earned just 65 cents to each dollar earned by men.

There is no single explanation for why progress toward narrowing the pay gap has all but stalled in the 21st century. Women generally begin their careers closer to wage parity with men, but they lose ground as they age and progress through their work lives, a pattern that has remained consistent over time. The pay gap persists even though women today are more likely than men to have graduated from college. In fact, the pay gap between college-educated women and men is not any narrower than the one between women and men who do not have a college degree. This points to the dominant role of other factors that still set women back or give men an advantage.

One of these factors is parenthood. Mothers ages 25 to 44 are less likely to be in the labor force than women of the same age who do not have children at home, and they tend to work fewer hours each week when employed. This can reduce the earnings of some mothers, although evidence suggests the effect is either modest overall or short-lived for many. On the other hand, fathers are more likely to be in the labor force – and to work more hours each week – than men without children at home. This is linked to an increase in the pay of fathers – a phenomenon referred to as the “ fatherhood wage premium ” – and tends to widen the gender pay gap.

Related: Gender pay gap in U.S. hasn’t changed much in two decades

Family needs can also influence the types of jobs women and men pursue , contributing to gender segregation across occupations. Differential treatment of women, including gender stereotypes and discrimination , may also play a role. And the gender wage gap varies widely by race and ethnicity.

Pew Research Center conducted this study to better understand how women’s pay compared with men’s pay in the U.S. in the economic aftermath of the COVID-19 outbreak .

The study is based on the analysis of monthly Current Population Survey (CPS) data from January 1982 to December 2022 monthly files ( IPUMS ). The CPS is the U.S. government’s official source for monthly estimates of unemployment . For a quarter of the sample each month, the CPS also records data on usual hourly earnings for hourly workers and usual weekly earnings and hours worked for other workers. In this report, monthly CPS files were combined to create annual files to boost sample sizes and to analyze the gender pay gap in greater detail.

The comparison between women’s and men’s pay is based on their median hourly earnings. For workers who are not hourly workers, hourly earnings were computed as the ratio of usual weekly earnings to usual weekly hours worked. The samples include employed workers ages 16 and older with positive earnings, working full time or part time, including those for whom earnings were imputed by the Census Bureau . Self-employed workers are excluded because their earnings are not recorded in the CPS.

The COVID-19 outbreak affected data collection efforts by the U.S. government in its surveys, especially in 2020 and 2021, limiting in-person data collection and affecting the response rate. It is possible that some measures of economic outcomes and how they vary across demographic groups are affected by these changes in data collection.

“Mothers” and “fathers” refer to women and men 16 and older who have an own child younger than 18 living in the household.

The U.S. labor force, used interchangeably with the workforce in this analysis, consists of people 16 and older who are either employed or actively looking for work.

White, Black and Asian workers include those who report being only one race and who are not Hispanic. Hispanics are of any race. Asian workers include Pacific Islanders. Other racial and ethnic groups are included in all totals but are not shown separately.

“High school graduate” refers to those who have a high school diploma or its equivalent, such as a General Education Development (GED) certificate, and those who had completed 12th grade, but their diploma status was unclear (those who had finished 12th grade but not received a diploma are excluded). “Some college” include workers with an associate degree and those who attended college but did not obtain a degree.

Younger women – those ages 25 to 34 and early in their work lives – have edged closer to wage parity with men in recent years. Starting in 2007, their earnings have consistently stood at about 90 cents to the dollar or more compared with men of the same age. But even as pay parity might appear in reach for women at the start of their careers, the wage gap tends to increase as they age.

Consider, for example, women who were ages 25 to 34 in 2010. In that year, they earned 92% as much as men their age, compared with 83% for women overall. But by 2022, this group of women, now ages 37 to 46, earned only 84% as much as men of the same age. This pattern repeats itself for groups of women who were ages 25 to 34 in earlier years – say, 2005 or 2000 – and it may well be the future for women entering the workforce now.

A good share of the increase in the gender pay gap takes place when women are between the ages of 35 and 44. In 2022, women ages 25 to 34 earned about 92% as much as men of the same ages, but women ages 35 to 44 and 45 to 54 earned 83% as much. The ratio dropped to 79% among those ages 55 to 64. This general pattern has not changed in at least four decades.

The increase in the pay gap coincides with the age at which women are more likely to have children under 18 at home. In 2022, 40% of employed women ages 25 to 34 had at least one child at home. The same was true for 66% of women ages 35 to 44 but for fewer – 39% – among women ages 45 to 54. Only 6% of employed women ages 55 to 64 had children at home in 2022.

Similarly, the share of employed men with children at home peaks between the ages of 35 to 44, standing at 58% in 2022. This is also when fathers tend to receive higher pay, even as the pay of employed mothers in same age group is unaffected.

Parenthood leads some women to put their careers on hold, whether by choice or necessity, but it has the opposite effect among men. In 2022, 70% of mothers ages 25 to 34 had a job or were looking for one, compared with 84% of women of the same age without children at home. This amounted to the withdrawal of 1.4 million younger mothers from the workforce. Moreover, when they are employed, younger mothers tend to put in a shorter workweek – by two hours per week, on average – than other women their age. Reduced engagement with the workplace among younger mothers is also a long-running phenomenon.

Fathers, however, are more likely to hold a job or be looking for one than men who don’t have children at home, and this is true throughout the prime of their working years , from ages 25 to 54. Among those who do have a job, fathers also work a bit more each week, on average, than men who do not have children at home.

As a result, the gender gap in workplace activity is greater among those who have children at home than among those who do not. For example, among those ages 35 to 44, 94% of fathers are active in the workforce, compared with 75% of mothers – a gap of 19 percentage points. But among those with no children at home in this age group, 84% of men and 78% of women are active in the workforce – a gap of 6 points.

These patterns contribute to the gap in workplace activity between men and women overall. As of 2022, 68% of men ages 16 and older – with or without children at home – are either employed or seeking employment. That compares with 57% of women, a difference of 11 percentage points. This gap was as wide as 24 points in 1982, but it narrowed to 14 points by 2002. Men overall also worked about three hours more per week at a job than women in 2022, on average, down from a gap of about six hours per week in 1982.

Parenthood affects the hourly earnings of employed women and men in unexpected ways. While employed mothers overall appear to earn less than employed women without children at home, the gap is driven mainly by differences in educational attainment between the two groups. Among women with similar levels of education, there is little gap in the earnings of mothers and non-mothers. However, fathers earn more than other workers, including other men without children at home, regardless of education level. This phenomenon – known as the fatherhood wage premium – is one of the main ways that parenthood affects the gender pay gap among employed workers.

Motherhood does have important effects on the potential earnings of women. Women who experience breaks in their careers after becoming mothers sacrifice at least some of their earnings . Some mothers may never work for pay after having children, passing on earnings altogether. But it is difficult to know what the earnings of mothers might have been and, as a result, it is hard to know for certain what the full effect of motherhood is on women’s earnings. Estimates suggest that motherhood may account for much of the current shortfall in the earnings potential of women overall. 1

Among employed men and women, the impact of parenting is felt most among those ages 25 to 54, when they are most likely to have children under 18 at home. In 2022, mothers ages 25 to 34 earned 85% as much as fathers that age, but women without children at home earned 97% as much as fathers. In contrast, employed women ages 35 to 44 – with or without children – both earned about 80% as much as fathers. The table turns for women ages 45 to 54, with mothers earning more than women with no children at home. Among those ages 35 to 44 or 45 to 54, men without children earned only 84% as much as fathers.

But these patterns in the earnings of employed mothers and women with no children at home are influenced greatly by differences in education levels between the two. Among employed women ages 25 to 34, some 61% of women without children at home had a bachelor’s degree or higher level of education in 2022, compared with 37% of mothers. It follows that among women ages 25 to 34, those without children at home (a more highly educated group, on average) earned more than women with at least one child at home. Conversely, employed mothers ages 45 to 54 were more likely than other women to have at least a bachelor’s degree – 58% vs. 42%. For that reason, mothers ages 45 to 54 earned more than women without children. 2

When the earnings of mothers are compared with those of women without children at home who have the same level of education, the differences either narrow or go away. Among employed women ages 25 to 34 with at least a bachelor’s degree, both mothers and women without children at home earned 80% as much as fathers in 2022. Among women ages 25 to 34 with a high school diploma and no further education, mothers earned 79% as much as fathers and women with no children at home earned 84% as much. The narrowing of the gap in earnings of mothers and women without children at home after controlling for education level also extends to other age groups.

Thus, among the employed, the effect of parenthood on the gender pay gap does not seem to be driven by a decrease in mothers’ earnings relative to women without children at home. Instead, the widening of the pay gap with parenthood appears to be driven more by an increase in the earnings of fathers. Fathers ages 25 to 54 not only earn more than mothers the same age, they also earn more than men with no children at home. Nonetheless, men without children at home still earn more than women with or without children at home.

Although there is little gap in the earnings of employed mothers and women with no children at home who have the same level of education, there is a lingering gap in workplace engagement between the two groups. Whether they had at least a bachelor’s degree or were high school graduates, mothers ages 25 to 34 are less likely to hold a job or be looking for one. Similarly, younger mothers on average work fewer hours than women without children at home each week, regardless of their education level. The opposite is true for fathers compared with men without children at home.

The share of women with at least a bachelor’s degree has increased steadily since 1982 – and faster than among men. In 1982, 20% of employed women ages 25 and older had a bachelor’s degree or higher level of education, compared with 26% of employed men. By 2022, 48% of employed women had at least a bachelor’s degree, compared with 41% of men. Still, women did not see the pay gap close to the same extent from 2002 to 2022 as they did from 1982 to 2002.

In part, this may be linked to how the gains from going to college have changed in recent decades, for women and men alike. The college wage premium – the boost in earnings workers get from a college degree – increased rapidly during the 1980s. But the rise in the premium slowed down over time and came to a halt around 2010. This likely reduced the relative growth in the earnings of women.

Although gains in education have raised the average earnings of women and have narrowed the gender pay gap overall, college-educated women are no closer to wage parity with their male counterparts than other women. In 2022, women with at least a bachelor’s degree earned 79% as much as men who were college graduates, and women who were high school graduates earned 81% as much as men with the same level of education. This underscores the challenges faced by women of all education levels in closing the pay gap.

Notably, the gender wage gap has closed more among workers without a four-year college degree than among those who do have a bachelor’s degree or more education. For example, the wage gap for women without a high school diploma narrowed from 62% in 1982 to 83% in 2022 relative to men at the same education level. But it closed only from 69% to 79% among bachelor’s degree holders over the same period. This is because only men with at least a bachelor’s degree experienced positive wage growth from 1982 to 2022; all other men saw their real wages decrease. Meanwhile, the real earnings of women increased regardless of their level of education.

As women have improved their level of education in recent decades, they’ve also increased their share of employment in higher-paying occupations, such as managerial, business and finance, legal, and computer, science and engineering (STEM) occupations. In 1982, women accounted for only 26% of employment in managerial occupations. By 2022, their share had risen to 40%. Women also substantially increased their presence in social, arts and media occupations. Over the same period, the shares of women in several lower-paying fields, such as administrative support jobs and food preparation and serving occupations, fell significantly.

Even so, women are still underrepresented in managerial and STEM occupations – along with construction, repair and production, and transportation occupations – when compared with their share of employment overall. And there has been virtually no change in the degree to which women are over represented in education, health care, and personal care and services occupations – the last of which are lower paying than the average across all occupations. The distribution of women and men across occupations remains one of the drivers of the gender pay gap . But the degree to which this distribution is the result of personal choices or gender stereotypes is not entirely clear.

Looking across racial and ethnic groups, a wide gulf separates the earnings of Black and Hispanic women from the earnings of White men. 3 In 2022, Black women earned 70% as much as White men and Hispanic women earned only 65% as much. The ratio for White women stood at 83%, about the same as the earnings gap overall, while Asian women were closer to parity with White men, making 93% as much.

The pay gap narrowed for all groups of women from 1982 to 2022, but more so for White women than for Black and Hispanic women. The earnings gap for Asian women narrowed by about 17 percentage points from 2002 to 2022, but data for this group is not available for 1982.

To some extent, the gender wage gap varies by race and ethnicity because of differences in education, experience, occupation and other factors that drive the gender wage gap for women overall. But researchers have uncovered new evidence of hiring discrimination against various racial and ethnic groups, along with discrimination against other groups, such as LGBTQ and disabled workers. Discrimination in hiring may feed into differences in earnings by shutting out workers from opportunities.

Changes in the gender pay gap are also shaped by economic factors that sometimes drive men’s and women’s earnings in distinctive ways. Because men and women tend to work in different types of jobs and industries, their earnings may respond differently to external pressures.

More specifically, men’s earnings essentially didn’t change from 1982 to 2002. Potential reasons for that include a more rapid decline in union membership among men, a shift away from jobs calling for more physical skills, and global competition that sharply reduced employment in manufacturing in the 1980s. At the same time, women’s earnings increased substantially as they raised their level of education and shifted toward higher-paying occupations.

But in some ways, the economic climate has proved less favorable for women this century. For reasons that are not entirely clear, women’s employment was slower to recover from the Great Recession of 2007-2009. More recently, the COVID-19 recession took on the moniker “ she-cession ” because of the pressure on jobs disproportionately held by women . Amid a broader slowdown in earnings growth from 2000 to 2015, the increase in women’s earnings from 2002 to 2022 was not much greater than the increase in men’s earnings, limiting the closure in the gender pay gap over the period.

Higher education, a shift to higher-paying occupations and more labor market experience have helped women narrow the gender pay gap since 1982. But even as women have continued to outpace men in educational attainment, the pay gap has been stuck in a holding pattern since 2002, ranging from 80 to 85 cents to the dollar.

More sustained progress in closing the pay gap may depend on deeper changes in societal and cultural norms and in workplace flexibility that affect how men and women balance their careers and family lives . Even in countries that have taken the lead in implementing family-friendly policies, such as Denmark, parenthood continues to drive a significant wedge in the earnings of men and women. New research suggests that family-friendly policies in the U.S. may be keeping the pay gap from closing. Gender stereotypes and discrimination, though difficult to quantify, also appear to be among the “last-mile” hurdles impeding further progress.

What is the gender wage gap in your metropolitan area? Find out with our pay gap calculator

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It's Equal Pay Day. The gender pay gap has hardly budged in 20 years. What gives?

Stacey Vanek Smith

Women earn about 82 cents for every dollar men make, according to the U.S. Government Accountability Office. That means on March 14, women's pay catches up to what men made in 2022. Klaus Vedfelt/Getty Images hide caption

Women earn about 82 cents for every dollar men make, according to the U.S. Government Accountability Office. That means on March 14, women's pay catches up to what men made in 2022.

Tuesday is Equal Pay Day: March 14th represents how far into the year women have had to work to catch up to what their male colleagues earned the previous year.

In other words, women have to work nearly 15 months to earn what men make in 12 months.

82 cents on the dollar, and less for women of color

This is usually referred to as the gender pay gap. Here are the numbers: - Women earn about 82 cents for every dollar a man earns - For Black women, it's about 65 cents - For Latina women, it's about 60 cents

Those gaps widen when comparing what women of color earn to the salaries of White men . These numbers have basically not budged in 20 years . That's particularly strange because so many other things have changed:

- More women now graduate from college than men - More women graduate from law school than men - Medical school graduates are roughly half women

That should be seen as progress. So why hasn't the pay gap improved too?

On Equal Pay Day, women are trying to make a dollar out of 83 cents

Francine Blau, an economist at Cornell who has been studying the gender pay gap for decades, calls this the $64,000 question. "Although if you adjust for inflation, it's probably in the millions by now," she jokes.

The Indicator from Planet Money

Women, career and family: a conversation with claudia goldin, the childcare conundrum.

Blau says one of the biggest factors here is childcare. Many women shy away from really demanding positions or work only part time because they need time and flexibility to care for their kids . "Women will choose jobs or switch to occupations or companies that are more family friendly," she explains. "But a lot of times those jobs will pay less." Other women leave the workforce entirely. For every woman at a senior management level who gets promoted, two women leave their jobs , most citing childcare as a major reason.

The "unexplained pay gap"

Even if you account for things like women taking more flexible jobs, working fewer hours, taking time off for childcare, etc., paychecks between the sexes still aren't square. Blau and her research partner Lawrence Kahn controlled for "everything we could find reliable data on" and found that women still earn about 8% less than their male colleagues for the same job .

"It's what we call the 'unexplained pay gap,'" says Blau, then laughs. "Or, you could just call it discrimination."

Planet Money

Mind the pay gap, mend the gap.

One way women could narrow the unexplained pay gap is, of course, to negotiate for higher salaries. But Blau points out that women are likely to experience backlash when they ask for more money. And it can be hard to know how much their male colleagues make and, therefore, what to ask for.

That is changing: a handful of states now require salary ranges be included in job postings.

The big reveal: New laws require companies to disclose pay ranges on job postings.

Blau says that information can be a game changer at work for women and other marginalized groups: "They can get a real sense of, 'Oh, this is the bottom of the range and this is the top of the range. What's reasonable to ask for?'"

A pay raise, if the data is any indication.

Where there's gender equality, people tend to live longer

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Expert Commentary

Pay gap between men and women: What the research says

Research shows that the pay gap in the U.S. narrowed in the 1980s and 1990s as women gained work and educational experience, but the gap persists today and has not changed much in recent years.

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This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Clark Merrefield, The Journalist's Resource January 24, 2020

This <a target="_blank" href="https://journalistsresource.org/economics/pay-gap/">article</a> first appeared on <a target="_blank" href="https://journalistsresource.org">The Journalist's Resource</a> and is republished here under a Creative Commons license.<img src="https://journalistsresource.org/wp-content/uploads/2020/11/cropped-jr-favicon-150x150.png" style="width:1em;height:1em;margin-left:10px;">

In the lead-up to the 2020 elections, the  Journalist’s Resource team is combing through the Democratic presidential candidates’ platforms and reporting what the research says about their policy proposals. We want to encourage deep coverage of these proposals — and do our part to help deter  horse race journalism , which research suggests can lead to inaccurate reporting and an uninformed electorate. We’re focusing on proposals that have a reasonable chance of becoming policy. For us, that means at least 3 of the 5 top-polling candidates say they intend to tackle the issue. Here, we look at what the research says about the pay gap between men and women.

Candidates favoring legislation or using executive authority to try to close the pay gap

Michael Bennet *, Pete Buttigieg *, John Delaney *, Tulsi Gabbard *, Deval Patrick *, Bernie Sanders *, Tom Steyer ,* Elizabeth Warren *, Andrew Yang *

What the research says

Women working full-time in the U.S. made a median of $821 each week in 2019, compared with a weekly median of $1,007 for men — that’s about 81 cents women earned for every dollar men earned — according to the Bureau of Labor Statistics . The pay gap between men and women refers to that 19-cent-per-dollar discrepancy. Research shows that the pay gap narrowed in the 1980s and 1990s as women gained work and educational experience, but the gap persists today and has not changed much in recent years.

Key context

The Equal Pay Act of 1963 provides federal protection so that men and women receive “equal pay for equal work,” according to the Equal Employment Opportunity Commission, the federal agency that enforces workplace laws. Work tasks must be similar but they don’t have to be identical to be considered legally “equal.” Title VII of the Civil Rights Act of 1964 more broadly outlaws workplace discrimination on the basis of sex, including pay discrimination.

“Gender wage gap” is the phrase politicians, academics and journalists sometimes use to describe the per-dollar difference between what men and women earn. Courts haven’t settled if federal law also covers people on the basis of gender identity and sexual orientation, or if protections are limited to biological sex alone. This is the difference between sex and gender identity, according to the National Institutes of Health :

Sex is biological. It’s based on your genetic makeup. Males have one X and one Y chromosome in every cell of the body. Females have two X chromosomes in every cell. These cells make up all your tissues and organs, including your skin, heart, stomach, muscles, and brain. Gender is a social or cultural concept. It refers to the roles, behaviors, and identities that society assigns to girls and boys, women and men, and gender-diverse people. Gender is determined by how we see ourselves and each other, and how we act and interact with others.

Whether Title VII extends beyond a biological interpretation of “sex” will be clarified when the Supreme Court decides R.G. & G.R. Harris Funeral Homes Inc. v. Equal Employment Opportunity Commission . The case centers on a funeral home that fired a transgender employee after she began living as a woman in 2013. The justices heard arguments in October 2019, but there’s no timeframe for when they’ll issue an opinion .

Elizabeth Warren is one candidate still in the race who has proposed an in-depth pay gap policy that specifically addresses the pay gap for black women. Black women make about 68 cents for every dollar a white man makes, according to the 2019 BLS numbers.

Joe Biden has released a broad plan that aims to ensure “women of all ages have a fair chance to earn a good living” and mentions that the “Obama-Biden Administration fought for equal pay for women,” but doesn’t offer specifics related to closing the pay gap.

Pay transparency — making pay rates public — is something candidates sometimes talk about as a solution to narrow the pay gap. In Canada, faculty salaries above a certain level at public universities were made public by law starting in the mid-1990s. Researchers writing in a November 2019 National Bureau of Economic Research working paper find “robust evidence that the laws reduced the gender pay gap between men and women by approximately 30%.”

“One effect of the provision of information on gender-based salary disparities within an organization is that it may lead individuals to privately demand higher pay from their employer,” the authors write.

Another NBER working paper , from January 2018, finds that after private-sector pay transparency legislation passed in 2006 in Denmark, the gender pay gap there declined by 7% over the following two years.

When it comes to the size of the median hourly wage gap, the U.S. ranks among the worst of 30 high-income countries — better than Finland, the United Kingdom, Estonia and the Republic of Korea, but worse than Spain, Australia, France, Italy and others — according to the 2018-2019 Global Wage Report from the United Nations’ International Labour Organization .

Formative findings

Researchers largely agree that the pay gap between men and women narrowed most in the 1980s and 1990s and has leveled since the early 2000s. The closing gap in the 1980s was driven by women improving their qualifications, gaining work experience and moving into professional and managerial roles, according to a 2001 analysis from Cornell University labor economists Francine Blau and Lawrence Kahn .

By 2010, factors like education and work experience explained little of the persistent gap, according to a 2017 paper by Blau and Kahn in the Journal of Economic Literature . The gap for top-paying jobs, like executive-level positions or slots at major law firms, has closed more slowly than for jobs at middle and lower pay tiers. Workforce interruptions and women working fewer hours than men are to blame for the gap that remains at the top, the authors find when reviewing the literature.

“Considerable empirical evidence indicates a negative relationship between children and women’s wages, commonly known as the motherhood wage penalty,” the authors write.

Recent data on full-time wage and salary workers from the Bureau of Labor Statistics show a wide range of pay gaps by occupation. Chief executives, surgeons and financial advisors are among the occupations with the biggest pay gaps between men and women. Occupations in which women make more per dollar than men include fast food servers , paralegals, editors and receptionists.

A Pew Research report , published January 30, 2020, finds more women than men working in certain high-skill, higher-paying jobs, based on 2018 data — a trend that may have contributed to the overall gap being smaller today than 40 years ago. Women are now more likely than men to hold jobs that require strong social skills, like sales managers, and also occupations that require critical thinking and writing skills, like teaching, according to the report.

Though the overall pay gap is much smaller than it used to be, the fact remains that federal legislation, like the EPA and Title VII, has allowed redress through the courts but hasn’t eliminated the gap. The most recent federal legislation linked to equal pay is the Lilly Ledbetter Fair Pay Act of 2009 , the first law Barack Obama signed as president.

Ledbetter worked as a shift supervisor at Goodyear Tire & Rubber Company through the 1980s and most of the 1990s. She sued Goodyear in 1998 after she discovered she was making less than her male counterparts. The Supreme Court threw out her case because, according to Title VII at the time, plaintiffs had to file suit within 180 days of the first act of discrimination. The act named for her amends Title VII and re-starts that 180-day countdown each time there is a discriminatory pay action — like each time an employee receives a paycheck.

Though the act makes it possible for someone like Ledbetter — who found out about pay inequality well after the initial fact — to file suit, the act hasn’t led to a huge increase in claims of pay discrimination because of sex with the Equal Employment Opportunity Commission, according to a 2017 paper in Advancing Women in Leadership .

Recent research

There are 24 states with equal pay laws that “differ in some material way” from the EPA, according to University of Florida law professor Stephanie Bornstein , writing in 2018 in the Maryland Law Review .

“Three states in particular, California, Massachusetts, and Oregon, have succeeded in enacting the most far-reaching legislation to date that promises to offer new solutions to remedy both gender and racial pay gaps,” Bornstein writes.

Laws in those three states aren’t identical, but each protects more classes of people from pay discrimination than the EPA does. California in particular has a long track record of attempting to address equal pay discrepancies. The state passed its first equal pay act in 1949 — 14 years before the federal equal pay law — and strengthened statewide protections in 2015 .

In September 2018, California passed a law mandating representation from women on corporate boards. By the end of 2019, public companies based in the state had to have at least one female director, with more female directors required by 2021, depending on the size of the board. California is the first state to set such quotas. Women hold 20% of board seats among the 3,000 most valuable publicly traded companies in the U.S., according to executive data collection and analysis firm Equilar.

Research indicates that having more women in top management positions can help close the pay gap and improve company performance. An October 2007 analysis in the American Sociological Review suggests that “the presence of high-status female managers has a much larger impact on gender wage inequality” than promoting women to lower-level managerial positions.

“This finding highlights — in a new way — the significance of the ‘glass ceiling,’” the authors write. “If our findings hold, not only are qualified women blocked from upper-level managerial positions and denied the benefits of those jobs, but their absence has ripple effects that shape workplace outcomes for non-managerial women as well.”

Another analysis , from January 2012 in the Strategic Management Journal , takes 15 years of data from top managers at U.S. firms listed on the S&P 1500 stock market and finds that “a given firm generates on average 1% (or over $40 million) more economic value with at least one woman on its top management team than without any women on its top management team and also enjoys superior accounting performance.”

Corporate board quotas by gender may, however, lead to short-term losses. Firms affected by a board quota that went into effect in Norway in 2006 “undertake fewer workforce reductions than comparison firms, increasing relative labor costs and employment levels and reducing short-term profits,” finds a July 2013 paper in the American Economic Journal .

Similarly, a January 2019 research paper from the Kenan Institute of Private Enterprise at the University of North Carolina at Chapel Hill finds short-term losses in stock value for companies headquartered in California when the state’s board quota law was signed. The authors tie short-term losses particularly to companies that don’t have access to a “local pool of female directors.” In other words, the search for women directors would be more costly and time consuming for those companies.

“We acknowledge, however, that these policies may have positive long-term effects on women’s labor market outcomes, may enhance fairness and equity in the workplace, and ultimately may lead to improved outcomes for firms’ stakeholders,” the authors write.

Closing the remaining pay gap between men and women may come down to shifts in workplace and cultural values — not just how long people work, but when during the day work is done. Harvard University economist Claudia Goldin offers this perspective in the American Economic Review :

The solution does not (necessarily) have to involve government intervention and it need not make men more responsible in the home (although that wouldn’t hurt). But it must involve changes in the labor market, especially how jobs are structured and remunerated to enhance temporal flexibility. The gender gap in pay would be considerably reduced and might vanish altogether if firms did not have an incentive to disproportionately reward individuals who labored long hours and worked particular hours.

Labor law experts Gary Siniscalco , Lauri Damrell and Clara Morain Nabity put equal weight on the need for legislation and the need for society writ large to recognize underlying cultural reasons for the persistent pay gap.

For example, they offer that women working in different industries may value their time and interests outside of work differently. Divergent pay between men and women, in some cases, may come down to personal choice, like the decision to start a family or not.

The authors explain, writing in the American Bar Association Journal of Labor and Employment Law :

Whether these decisions are voluntary ‘choices’ or fueled by implicit or overt bias is extraordinarily difficult to discern and varies greatly from woman to woman, employer to employer, and job to job. Therefore, solutions cannot fit into a one-size-fits-all mold. Placing blame on employers and focusing narrowly on antidiscrimination legislation ignores a broader problem based on deeply entrenched societal assumptions related to how we collectively define our roles as women and men.

Further reading

National Board Quotas and the Gender Pay Gap among European Managers

David J. Maume, Orlaith Heymann and Leah Ruppanner. Work, Employment and Society. August 2019.

The gist: “Drawing a sample of managers in the 2010 European Social Survey, the gender gap in pay was decomposed, finding that employer devaluation of women accounted for the majority of the gender gap in pay.”

Does the Equal Pay Act Prohibit Discrimination on the Basis of Sexual Orientation or Gender Identity?

Adam Romero. Alabama Civil Rights & Civil Liberties Law Review , 2019.

The gist: “This article is the first to consider whether the Equal Pay Act’s prohibition of sex-based wage disparities encompasses wage disparities on the basis of sexual orientation or gender identity.”

A Systematic Review of the Gender Pay Gap and Factors That Predict It

Sebawit G. Bishu and Mohamad G. Alkadry. Administration & Society , March 2016.

The gist: “Confirming findings from past studies, this study also finds that the public sector performs relatively better in most aspects of the gender pay gap and factors that espouse it.”

Expert sources

Sebawit G. Bishu , assistant professor of public administration, University of Colorado Denver; research fellow, Harvard Kennedy School’s Women and Public Policy Program.

Stephanie Bornstein , associate professor of law, University of Florida Levin College of Law.

Claudia Goldin , Henry Lee Professor of Economics, Harvard University.

Adam Romero , director of legal scholarship and federal policy, UCLA School of Law.

Elena Simintzi , assistant professor of finance, University of North Carolina at Chapel Hill.

This article was updated on January 31 to include the January 2020 Pew Research report .

*Dropped out of race since publication date.

About The Author

Clark Merrefield

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How to Actually Close the Gender Pay Gap

More from our inbox:, it’s not a ‘broken home’, no more moviegoing for me.

To the Editor:

“ Salary Transparency Fails to Fix the Gender Pay Gap ” (Business, July 4) contains numerous examples and anecdotes about the benefits of taking actions to close the gender pay gap.

We agree that transparency is an important component to building inclusive cultures — but it goes beyond knowing what your co-worker earns.

The gender pay gap is a result of pay inequity and unequal representation at all pay levels throughout an organization. Therefore, instituting a pay transparency policy without taking other actions — such as regularly conducting pay equity analyses; banning salary history requests by employers; and evaluating recruitment, promotion, and talent development systems for bias — would still leave an organization with a pay gap.

There is no “one and done” action that will close a company’s gender pay gap. Instituting salary transparency is an “ and” — a policy that should be put in place in addition to taking steps to ensure an equal playing field.

Serena Fong Andrew Grissom New York Ms. Fong is vice president, strategic engagement, and Mr. Grissom is senior associate librarian at Catalyst, a nonprofit promoting gender equity in the workplace.

Re “ A ‘Broken Home’ Didn’t Break Me, or My Kids ” (Opinion guest essay, nytmes.com, July 5):

I am grateful for Joyce Maynard’s tender essay on the long view of divorce. As a child of divorced parents, I, too, wish that my parents hadn’t lined us up on the living room couch and told us that they were getting a divorce. But as the oldest, I felt the burden of their unhappiness on us, and that, too, was too much for children to bear.

Now 40 years later, in a loving marriage of my own and with children and grandchildren, I have one thing to ask of a society so sensitive about language. It’s time to drop the expression “broken home.” Each time I hear the expression, it breaks my heart a little. I want to shout back: “I am not broken. I am strong. And I am loved.”

Erica Brown Silver Spring, Md.

Re “ Sorry, We Aren’t Going Back to the Movies ” (Sunday Review, July 11):

Kara Swisher certainly has it right. Why would anyone want to go back to the movies? To breathe in stale, recirculated air? To eat overpriced, lousy popcorn? To sit near rude people who can’t shut their mouths or turn their phones off? Fuhgedaboutit!

I’m perfectly content to watch movies on my big screen and enjoy all the comforts of home.

An additional plus has been this: By wearing a mask for the last year and a half whenever I ventured out, I not only didn’t get the virus, but also for the first time I can remember I didn’t catch a cold or anything else during this entire period.

So why would I go back to an uncomfortable germ factory when I can enjoy my entertainment with family and friends and open my own bottle of wine or stir (not shake) my own martini?

Steven Morris Mount Pleasant, S.C.

Everything you need to know about pushing for pay equity

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Workers worldwide look forward to payday. But while a paycheck may bring a sense of relief, satisfaction, or joy, it can also represent an injustice—a stark reminder of persistent inequalities between men and women in the workplace.

The gender pay gap stands at 20 per cent , meaning women workers earn 80 per cent of what men do. For women of colour, migrant women, those with disabilities, and women with children, the gap is even greater.

The cumulative effect of pay disparities has real, daily negative consequences for women, their families, and society, especially during crises. The widespread effects of COVID-19 have plunged up to 95 million people into extreme poverty, with one in every 10 women globally living in extreme poverty . If current trends continue, 342.4 million women and girls will be living on less than $2.15 a day by 2030.

What do we mean by equal pay for work of equal value?

Equal pay for work of equal value, as defined by the ILO Equal Remuneration Convention , means that all workers are entitled to receive equal remuneration not only for identical tasks but also for different work considered of equal value. This distinction is crucial because jobs held by women and men may involve varying qualifications, skills, responsibilities, or working conditions, yet hold equal value and warrant equal pay.

In 2020, New Zealand passed the Equal Pay Amendment Bill , ensuring that women and men are paid equally for work that’s different but has equal value, including in chronically underpaid female-dominated industries. 

It is also important to recognize that remuneration is more than a basic wage; it encompasses all the elements of earnings. This includes overtime pay, bonuses, travel allowances, company shares, insurance, and other benefits.

Why does the gender pay gap persist?

The gender pay gap originates from ingrained inequalities. Women, particularly migrant women, are overrepresented in the informal sector. Look around you, from street vending to domestic service, from coffee shop attendants to subsistence farming. Women fill informal jobs that often fall outside the domains of labour laws, trapping them in low-paying, unsafe working environments, without social benefits. These poor conditions for women workers perpetuate the gender pay gap.

Women also do  three more hours of daily care work  than men , globally. This includes household tasks such as cooking, cleaning, fetching firewood and water, and taking care of children and the elderly. Although care work is the backbone of thriving families, communities, and economies, it remains undervalued and underrecognized. Try calculating your daily load with  UN Women’s unpaid care calculator .

The  motherhood penalty exacerbates pay inequity, with working mothers facing lower wages, a disparity that jumps as the number of children a woman has increases. Lower wages for mothers are linked to reduced working time, employment in more family-friendly jobs that tend to be lower paying, hiring and promotion decisions that penalize the careers of mothers, and a lack of programmes to support women’s return to work after time out of the labour market.

Restrictive, traditional gender roles are also spurring pay inequalities. Gender stereotypes steer women away from occupations traditionally dominated by men and push them toward care-focused work that is often regarded as “unskilled,” or “soft-skilled” and therefore, lower paid.

Furthermore, discriminatory hiring practices and promotion decisions that prevent women from gaining leadership roles and highly paid positions sustain the gender pay gap.

Why is pay equity an urgent issue?

Pay equity matters because it is a glaring injustice and subjects millions of women and families to lives of entrenched poverty and opportunity gaps. At the current rate, we risk leaving more than 340 million women and girls in abject poverty by 2030 , and an alarming 4 per cent could grapple with extreme food insecurity by that year.

Women also experience significantly lower social protection coverage than men, a discrepancy that largely reflects and reproduces their lower labour force participation rates, higher levels of temporary and precarious work, and informal employment. All these factors contribute to lower income , savings, and pensions of women and gendered poverty in old age.

What should be done?

As more women are plunged into poverty, the fight for equal pay and pay equity takes on a new sense of urgency because those who earn the least are most damaged by income discrepancy.

In the United States, Black women earn only 63.7 cents , Native women 59 cents , and Latinas 57 cents for every dollar that white men earn. Where money is tight, lower pay can prevent women and families from putting food on the table, securing safe housing, and accessing critical medical care and education—impacts that can perpetuate cycles of poverty across generations.

It is urgent that we put female workers on equal footing as male workers. In a world on the brink of a looming care deficit,  women make up 67 per cent of workers providing essential health and social care services globally . Governments must address underpaid and undervalued jobs in the care sector, including in education, health care and social services, all jobs that women predominantly occupy.

What does the data say about pay equity around the world? 

Unequal pay is a stubborn and universal problem. Despite significant progress in women’s education and labour market participation, progress in closing the gender pay gap has been too slow. At this pace, it will take  almost 300 years to achieve economic gender parity .

Women workers’ average pay is generally lower than men’s in all countries and for all levels of education, and age groups, with women earning on average 80 per cent what men ear n. Women in male-dominated industries may earn more than those in female-dominated industries, but the gender pay gap persists across all sectors.

While gender pay gap estimates can vary substantially across regions and even within countries, higher income countries tend to have lower levels of wage inequality compared to low and middle-income countries. However, estimates of the gender pay gap understate the real extent of the issue, particularly in developing countries, because of a lack of information about informal economies, which are disproportionately made up of women workers, so the full picture is likely worse than what the available data shows us.

Explore  UN Women’s report on the gender pay gap in Eastern and Southern Africa .

Closing the gender pay gap requires a set of measures that push for decent work for all people. This includes measures that promote the formalization of the informal economy, bringing informal workers under the umbrella of legal and effective protection and empowering them to better defend their interests.

Ensuring workers’ right to organize and bargain collectively is an important part of the solution. Women must be involved in employer and union leadership, enabling legislation that establishes comprehensive frameworks for gender equality in the workplace.

Economic empowerment Chief at UN Women Dr. Jemimah Njuki says that, “The gender pay gap requires all stakeholders, including employers, governments, trade unions take full responsibility and work side by side to address these challenges. Women deserve equal pay for work of equal value”.

[Last updated February 2024] 

• Gender wage gap
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The Gender Pay Gap and the Equality

This essay will discuss the gender pay gap and its implications for gender equality. It will explore the causes of the pay gap, including discrimination, occupational segregation, and societal norms. The piece will also consider the economic and social consequences of the pay gap and the measures being taken to address this inequality, such as legislation, corporate policies, and advocacy efforts. You can also find more related free essay samples at PapersOwl about Discrimination.

How it works

• 1 Introduction
• 2 Pro Arguments
• 3 Con Arguments
• 4 Conclusion

Introduction

The gender pay gap and the equality of pay rates have always been topics of discussion in today’s society. Equal pay means that individuals accomplishing the same work should be compensated equivalently in regards to completion. Issues are raised between the earning differences between men and women due to the lack of equal pay between the two genders. By referring back to U.S. history on the subject, we found that the issue dates back over 100 years ago and grasps the concept around competencies and skills ultimately undervalued from women whose jobs are paid less than that of men, as a result, contradicting their effort in volume of production at work while also hindering their chances of potential growth in an organization.

The importance of unfair pay can be a detrimental factor when it comes to sustaining income necessary for present and future survival. Our position argues that the gender pay gap is not a myth, and must be taken seriously in order to ensure everyone has an equal chance of being recognized for the hard work they put into society.

Pro Arguments

One of the main elements to the gender pay gap being real is gender discrimination. Gender discrimination can result from women being excluded from meetings, promotions, and not being offered a job because the employer believes women are not as smart or determined enough as men in the workplace. As mentioned by Hessaramiri and Kleiner, male decision makers believe that men are superior, so they make decisions with that thought in mind (2001, p.44). Employers who do not hire women because they believe that a man will perform more efficiently is discriminating against women by stereotyping them. As discussed in The Complex Causes of the Gender Pay Gap, when employers are presented with identical resumes for male and female candidates, employers will more likely end up offering the job to a male (Wagner, 2015, p.17). Having identical qualifications to men, women are not considered at a man’s level, which is discrimination. Donna Kassman was overlooked for a promotion even though she was more than qualified (Widmer, p.23).

Unequal career advancement widens the pay gap for both females and males. According to a recent student founded by SHRM, women earn 0.79 cents for every dollar a man earns (Miller, S). These statistics have been unchanged for several years considering the similarities of jobs and qualifications. This highlights the underlying issue of gender pay gap that has still yet to be brought into major topic discussions to be acted upon. In addition, studies show 36% of men felt that women should not earn the same amount as they do if able to take family leave. However, this is a somewhat arguable point since there is indeed a discriminatory act towards pay differences due to personal matter. This could be a personal opinion looking into the negative sides of women taking time off to care for a child and not focusing on their work. The differences in how men and women are seen towards one another sets the stage for even further pressures in the workplace.

54% of women experience harassment in the workplace (Zetlin, 2018). Due to these pressures women receive from men, the concept of a wage gap between the two genders further defines itself. Women decide to leave these “male-dominated” industries to protect their values and themselves, but in turn hurt their chances of promotions and career advancement. The “leaving” of women in these jobs is more of them being pushed out of these roles due to their refusal of complying with their male co-workers’ ideas. According to The Cut, “Sexual harassment has been identified as one of the most damaging and ubiquitous barriers to career success and satisfaction for women,” (Covert, 2017, para. 2). Since the harassment of women is so common in the workplace, females experience lower incomes because they are shut out from certain promotions. This causes women to face even more obstacles when finding a job, thus earning less than their male co-workers.

Con Arguments

Women are willingly choosing low paying job as a result to the difference in pay wage. When speaking about the wage gap, people often tend to look at the same job with same skills to compare the differences each gender is getting pay for. Often times, this leads to findings that women are getting paid less than men per hour or annually for the same/similar job. However, research has shown that women are more likely to choose a career field that will result in lower pay for their earnings in total. Based on research by Harvard Business Review, “Many college majors that lead to high-paying roles in tech and engineering are male dominated, while majors that lead to lower-paying roles in social sciences and liberal arts tend to be female dominated, placing men in higher-paying career pathways, on average” (Carmichael, S). Yes, this is also a contributing factor adding up to wage gap. Overall, data does not account for the reason why women pick a career that lead to a lower pay but all comes down to their behaviors and choices leading up to the outcomes of their career. The argument here is that both women and men can be in the same major but it is the personal characteristics and determination that establish an outcome, or career, they want to achieve.

Women bringing the pay gap upon themselves by choosing to go into lower-paying jobs is a myth. Even though a large percentage of women are employed in lower paying jobs, their difference in industry choice compared to men still depicts a gap in wages per occupation, favoring the male gender. Regardless of the industry, women consistently earn less than their male colleagues. For example, it is fair to say that society views nursing and secretarial jobs as a more female-dominated industry; however, studies from Fortune Magazine depict that women still earn less than men in these fields. To further the argument, there is evidence that in most occupations across the board, wages fall when more women are present in the industry and in turn, the wages rise when there are more males present in the industry. In response to these unfair wages in the workplace, women ask for pay raises but only receive them 15% of the time while males receive their pay raises 20% of the time (Vagins, 2019) A reason for this is that females asking for a higher salary are seen as aggressive and are thus refused their request.

It is believed the gender pay gap is a myth considering the hours worked by both men and women, women make the choice to not work as many hours as men. Working overtime is not exclusive to only one gender, so when men decide to work more overtime, of course men will make more money than women. In a study by the Bureau of Labor Statistics, 27 percent of men compared to 15 percent of women work over 41 hours (Hymowitz, 2011, p.4). There is more than enough evidence to claim that women prefer to work fewer hours than men. As stated in Why the Gender Gap Won’t Go Away, despite the gap in earnings, women still decide to work fewer hours than men (Hymowitz, 2011). If women want the pay gap to be closed, all they must simply do is work the same hours as men. Their choice ends up causing the wage gap to show up with skewed results. There is a problem with this argument. Women do have a choice to work the hours they want, but the lack of work-family life balance programs lead women to choose lower paying jobs with more flexible hours.

Some believe the pay gap is due to women having children and leaving work to look after them. This myth is false because right off the bat, the gap in wages is present even before women create families, indicating that a distinction between male and female wages is already established. Fortune Magazine depicts that women before the age of 24 already earn less than their male co-workers; thus, proving that the differences in wages are present even before the main “child bearing” years experienced by women. When the hiring process is underworks, pregnant women are seen differently than men. Mothers-to-be as well as women already with children experience discrimination from employers and are “six times less likely” to be considered for a job when compared to childless women and men (Dunn, 2019, para. 11). While women are seen as less reliable to meet deadlines and scheduled appointments than men because of their “motherhood” tasks, men are seen as needing to be rewarded for having a new child and thus receive “daddy bonuses” to help their family out (Miller, 2018). SHRM explains that women who take a mid-career break from work earn less than men who also take similar mid-career breaks.

During our research to reveal that the gender pay gap is a myth, we found reasonable evidence to fortify our statements. Our analytical research proves that the lack of equal pay in society is indeed still in question by government entities as well as small sized companies to large sized corporations from across all job industries. Behavioral and work-life balance contributes to women earning less than men since it is found that they tend to work less according to the Bureau of Labor Statistics. We can conclude that personal factors such as lower paying jobs within respective career choices and degrees leads women to earn less. Even in so-called women dominated field, the research found relatively disproportionate annual pay between men and women. With the given evidence in our report, there should be a dramatic change in how equal pay is approached as well as the issue of the gender pay gap.”

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The Gender Pay Gap and Strategies for Equality Essay

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Implementing gender equality policies is necessary to give women equal chances. To guarantee the presence of women in working groups, adequate oversight is required. Equal chances for women should be provided to prevent female aggression. They can compete in labor in the organization relative to males. When women are denied chances in society, they speak up for their rights and engage in violent behavior (Corporate Responsibility Magazine’s 100 Best Corporate Citizens, n.d.). To promote equality and further the socialization process, it is essential to regularly review an organization’s records to ensure that women are employed there.

Consequently, these normative theories critically assess the problem and offer answers by endorsing a person’s arguments by their preferences. These theories study how gender norms and inequality are maintained using a conflict perspective. These theories, further, will encourage women’s employment decisions and provide them with happiness if they want to do so. Whether a practice is morally excellent or immoral, deontological ethics is the branch that adheres to a code of ethics. These actions do not consider their effects. In contrast, a utilitarian ethic asserts that a method should be implemented with highly favorable results.

To address the gender wage gap, additional job options are needed. As CEO, you should put policies into place that will give women in the organization chances to work in appropriate positions. By including more women and avoiding including more males than women, the disparity may be reduced to 10%. Because some jobs may only be done, especially by males, the gap cannot be zero. Men are powerful enough to do every activity, but women cannot accomplish every duty correctly. The gap will therefore persist but may be closed.

Corporate Responsibility Magazine’s 100 Best Corporate Citizens . (n.d.). Web.

• The Employee Assessment Program
• Employee Performance and Motivation Factors
• Accounting Research: Normative and Positive Approaches
• Application of normative case theories
• Leadership and National Oversight
• Synergizing Success: Team Leadership and Cohesion
• The Evolution in the World of Employment
• Human Resource Department of Blue Cross Blue Shield of Michigan
• Kiewit Company Developing a Talent Pool
• Discussion: Benefits of Part-Time Workers
• Chicago (A-D)
• Chicago (N-B)

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Governmentwide Gender and Racial/Ethnic Pay Gap Analysis Summary 

Executive summary.

On June 25, 2021, President Biden signed Executive Order 14035 (86 FR 34593), titled “Diversity, Equity, Inclusion, and Accessibility in the Federal Workforce.” To address any pay inequities and advance equal pay, section 12 of EO 14035 required the Director of the Office of Personnel Management (OPM) to review Governmentwide regulations and, as appropriate and consistent with applicable law, consider prohibiting the use of an applicant’s salary history during the hiring process to set pay or when setting pay for a current Federal employee. On January 30, 2024, OPM issued final regulations to advance pay equity in Governmentwide pay systems (89 FR 5737). OPM shared high-level gender and racial/ethnic group pay gap data for September 2021 in the supplementary information accompanying the regulations. This report shares more detailed pay gap data, primarily for September 2022.

The gender pay gap for the Federal Government’s civilian workforce in 2022 was 5.6 percent, an improvement from 5.9 percent in 2021. The Federal gender pay gap is far smaller than the national gender pay gap, which sits at 16 percent. 1 From 1992 to 2022, the pay gap for the Federal workforce has decreased from 24.5 percent to the current 5.6 percent. In addition, in recent years women in the Senior Executive Service, the senior-most leadership ranks of the Federal Government, are paid approximately the same as their male counterparts.

OPM also conducted analysis regarding pay gaps for groups of employees identified by both gender and race/ethnicity. OPM calculated pay gaps comparing (1) women to men in the same racial/ethnic group to understand disparities by gender and (2) men and women in each racial/ethnic group compared to White men to understand overlapping disparities by gender and race/ethnicity. This analysis revealed that pay gaps varied significantly depending on the specific population.

Many factors may contribute to the overall gender and race/ethnicity pay gaps in the Federal Government. In conducting its data analysis, OPM observed evidence of some of these factors at play. For example, more women than men occupy positions classified at lower General Schedule (GS) grades with lower pay, while more men than women occupy positions classified at higher GS grades with higher pay.

This report summarizes OPM’s key findings. More detailed data is available in the appendices.

U.S. Census Bureau. “Figure 6. Female-to-Male Earnings Ratio and Median Earnings of Full-Time, Year-Round Workers 15 Years and Older by Sex: 1960 to 2021.” https://www.census.gov/content/dam/Census/library/visualizations/2022/demo/p60-276/figure6.pdf

Previous Pay Gap Data Analysis

As a result of EO 14035, OPM is building on previous work focused on the issue of gender pay equality. In 2014, OPM issued a Governmentwide Strategy to Advance Pay Equality in the Federal Government in response to a 2013 Presidential memorandum. 2 OPM calculated the gender pay gap, which is the percentage difference between the average salaries of men and women, for 1992, 2002, and 2012. OPM also collected information agencies provided in response to an OPM data call memorandum.

OPM worked with agencies to implement all the recommendations in the Governmentwide strategy. These actions are summarized in a 2015 memorandum. 3 OPM’s actions are also summarized in Appendix VI to GAO’s 2020 report “Gender Pay Differences: The Pay Gap for Federal Workers Has Continued to Narrow, but Better Data on Promotions Are Needed.” 4 OPM has periodically updated its pay gap data analysis since issuing the 2014 Governmentwide strategy.

Data Sources

OPM used data reported by agencies to two OPM central data systems for the data analyses described in this report. These information systems are used to support statistical analyses of Federal personnel management programs. Data from the Enterprise Human Resources Integration—Statistical Data Mart (EHRI-SDM) was used for the analyses of the workforce starting in 2012. The Central Personnel Data File (CPDF), the predecessor system to EHRI-SDM, was used for the analyses of the 1992 and 2002 workforce. Most of the analysis results in this report focus on September 2022 data. Information on EHRI-SDM coverage is available on OPM’s web site. 5

Both systems, EHRI-SDM and CPDF, are composed of two primary data files. The Status File documents the characteristics of employees (e.g., gender, race, salary, etc.) at a specific point in time. The Dynamics File documents personnel actions (e.g., accessions, separations, promotions, etc.) over a period of time. OPM’s analysis focused on data from the Status File.

Data Elements

OPM used certain data elements in CPDF and EHRI-SDM to define the population of interest. In general, the studied population was limited to—

• Employees employed in the Executive branch;
• Employees in a pay status;
• Employees with a “permanent” appointment (i.e., appointment without time limitation); and
• Employees with a nonseasonal full-time work schedule.

OPM separately analyzed as distinct populations the General Schedule system and the Federal Wage System, the major pay systems covering white-collar employees and blue-collar employees, respectively. “White Collar” refers to employees with the PATCO occupational codes (professional, administrative, technical, clerical, other). “Blue Collar” refers to employees with a blue-collar occupational category code (trade, craft, and laboring occupations). OPM used the Pay Plan data element to identify employees in the core pay plans within those two systems--codes GS, GL, and GM for the General Schedule and codes WG, WL, WS, WD, and WN for the Federal Wage System. Since the employee population in the core General Schedule pay plans (GS, GL, GM) makes up approximately 77 percent of the total white-collar employee population in September 2022, the core General Schedule is of special interest. Accordingly, OPM also presents separate data for those core General Schedule pay plans. 6 As leaders in key positions just below the top Presidential appointees, we also present separate data for the Senior Executive Service. There is also some data for employees in Senior Level (SL) and Scientific or Professional (ST) positions.

OPM also used other data elements in CPDF and EHRI-SDM to define various subpopulations or subcategories. In this report, data elements used to create subpopulations are referred to as “factors.” Each data element or factor has a set of codes that define subpopulations within the context of the factor. For example, one factor is the employee’s agency. Codes identify different agencies. Each agency represents a subpopulation. For purposes of our study, we grouped together selected agencies—for example, smaller agencies were combined into a catch-all “other” category.

OPM used the following data elements as subpopulation-defining factors:

• Grade (for General Schedule employees)
• Occupational series
• Pay plan (pay system)
• Race or national origin (ethnicity and race identification)

Detailed information regarding these data elements and associated codes for subpopulations can be found in the OPM Guide to Data Standards. 7

Data for the Asian racial/ethnic group is combined with data for the Native Hawaiian/Pacific Islander racial/ethnic group.

OPM used the data element “Adjusted Basic Pay” in computing average salary rates for various subpopulations. Adjusted basic pay includes base pay plus any applicable locality payment or special rate supplement.

Calculations

In comparing female salaries to male salaries, OPM used male salaries as the base for comparison. Thus, in this report, OPM expresses the average female salary as a percentage of the average male salary. For example, for the total Executive branch population in September 2022, the average female salary was 94.4 percent of the average male salary. The shorthand term used in this report for this percentage is the “female salary percentage.” In addition, the gender pay disparity or “pay gap” is expressed in this report as a percentage by (1) subtracting the average male salary from the average female salary and (2) dividing the resulting difference by the average male salary. If the female salary percentage is already computed, 100 percent is subtracted from the female salary percentage to derive the pay gap percentage. For example, if the female salary percentage is 94.4 percent, the pay gap is –5.6 percent (94.4 – 100 = –5.6). In other words, the average female salary is 5.6 percent below the average male salary. 8 (In this report, we show the overall pay gap as a positive number, since it is understood that the gap represents the degree to which female pay is below male pay, unless the female average salary exceeds the male average salary.)

Similarly, in comparing salaries for different racial/ethnic groups for males and females, generally OPM used White male salaries as the base for comparison. Thus, in this report, OPM expresses the average salary for a certain ethnic/racial group and gender as a percentage of the average White male salary. For example, for the total Executive branch population in September 2022, the average Black/African American female salary was 85.1 percent of the average White male salary. In addition, the pay disparity or “pay gap” for males and females in each racial/ethnic group is expressed in this report as a percentage by (1) subtracting the average White male salary from the average male or female salary for the racial/ethnic group and (2) dividing the resulting difference by the average White male salary. If the percentage of White male average salary is already computed, 100 percent is subtracted from that percentage to derive the pay gap percentage. For example, if the Black/African American female percentage of White male salary is 85.1 percent, the pay gap is –14.9 percent (85.1 – 100 = –14.9). In other words, the average Black/African American female salary is 14.9 percent below the average White male salary.  (In this report, OPM shows the overall pay gap as a positive number, since it is understood that the gap represents the degree to which male and female pay for each racial/ethnic group is below White male pay, unless the male or female pay for the racial/ethnic group exceeds White male pay.)  OPM also calculated gender pay gaps by racial/ethnic groups comparing females to males in the same racial/ethnic group using the calculation described in the previous paragraph.

Office of Personnel Management. “Governmentwide Strategy on Advancing Pay Equality in the Federal Government,” April 2014. https://www.opm.gov/policy-data-oversight/pay-leave/reference-materials/reports/Governmentwide-Strategy-on-Advancing-Pay-Equality-in-the-Federal-Government.pdf

Office of Personnel Management. “Additional Guidance on Advancing Pay Equality in the Federal Government,” July 2015. https://www.chcoc.gov/content/additional-guidance-advancing-pay-equality-federal-government

Government Accountability Office. “Gender Pay Differences: The Pay Gap for Federal Workers Has Continued to Narrow, but Better Data on Promotions Are Needed,” December 2020. https://www.gao.gov/products/gao-21-67 (GAO notes on its website that the one recommendation from the report for the Equal Employment Opportunity Commission was implemented and has been closed. There were no recommendations for OPM.)

Office of Personnel Management. “About Our Data (EHRI-SDM).” https://www.fedscope.opm.gov/datadefn/aehri_sdm.asp

The General Schedule system also includes pay plans GP and GR, which cover doctors and dentists receiving title 38 market pay. Since the pay levels for GP-GR employees are dramatically higher than those for GS-GL-GM employees, after the GP and GR codes took effect in 2006, we have not included them with the core General Schedule plans that were separately analyzed. All General Schedule doctors and dentists were included in the core system (GS-GL-GM) in study years 1992 and 2002.

Office of Personnel Management. “Guide to Data Standards”. https://www.opm.gov/policy-data-oversight/data-analysis-documentation/data-policy-guidance/#url=Data-Standards

The gender pay gap would be slightly larger if the gap represented the amount by which the average female salary would need to increase to match the average male salary. For example, 5.6 percent divided by 94.4 percent equals 5.9 percent.

OPM’s Data Analysis Findings

This section summarizes the detailed data tables in each of the appendices to this report. Selected, key data tables from the appendices are also shown as graphs in this section.

Appendix 1 Findings

Federal gender pay gaps and related data over time.

Table 1a in Appendix 1 shows the female-to-male salary percentage for the Federal Government’s civilian workforce over time. The female-to-male salary percentage is the female average salary as a percentage of male average salary.

Table 1b in Appendix 1 shows the gender pay gaps for the Federal Government’s civilian workforce over time. The pay gap percentage is the percentage that female average salary is below male average salary.

The tables begin with data OPM collected for its 2014 Governmentwide Strategy on Advancing Pay Equality in the Federal Government (1992-2002-2012 study years) and continue with pay gap analysis OPM has conducted since then. The tables show data for White Collar, General Schedule, Senior Executive Service, Blue Collar, and Total Executive Branch populations. “White Collar” includes all white collar employees, including those in the General Schedule and Senior Executive Service. “Blue Collar” includes all blue collar employees, including those in the Federal Wage System.

The gender pay gap for the Executive branch has dramatically shrunk from 24.5 percent in 1992 to 5.6 percent in 2022. There have been large decreases for White Collar and General Schedule populations. The Blue Collar pay gap has fluctuated slightly over time and there is almost no pay gap in the Senior Executive Service in recent years. Table 1b gender pay gap data are represented in the graph below.

Gender Pay Gaps for the Federal Government

Appendix 2 Findings

Female distribution & pay gaps by federal government civilian occupational group or pay system.

Appendix 2 shows overall data for White Collar, General Schedule, Senior Executive Service, Blue Collar, and Total Executive Branch populations for September 2022, including percentage of male and female employees (as shown in the graph below), male and female average salaries, and overall pay gaps.

While Senior Executive Service has almost no pay gap, the percentage of females in the Senior Executive Service is 39.3 percent, which is less than the percentage of females in the entire Executive Branch (44.1 percent). The Blue Collar pay system, which has the largest pay gap of the pay system categories studied (17.4 percent), has the smallest percentage of females (11.1 percent).

Percentage of Employees in the Executive Branch by Gender

Source: EHRI-SDM. Nonseasonal, full-time, permanent Executive branch employees in a pay status.

Appendix 3 Findings

Gender pay gaps by subpopulation.

Appendix 3 shows gender pay gaps by the following factors: age range, agency, GS grade level, and racial/ethnic group. Data for each of the four factors is shown in separate Tables 3a-3d in Appendix 3 . Each table provides data on (1) subpopulations as percentage of total population (e.g., what percentage each racial/ethnic group is of all racial/ethnic groups), (2) percentage of each subpopulation that is female, and (3) female average salary as percentage of male average salary for each subpopulation.

There are varying differences (some significant) in the female salary percentages across subpopulations. Given the significance of the occupation series factor (see Appendix 5 ), the differences in female salary percentages for subpopulations of non-occupation-related factors may reflect—to a significant degree—the varying occupational distribution of employees in the different subpopulations. For example, the female salary percentage was 97.8 percent (a pay gap of 2.2 percent) for the subpopulation of employees who are in the 25-34 age range and was 91.5 percent (a pay gap of 8.5 percent) for those in the 55-64 age range (see Table 3a of Appendix 3 and the graph below). These two subpopulations likely have significantly different occupational distributions. Similarly, differences in subpopulations for different agencies may largely reflect the difference in occupational distribution among those agencies. (See Table 3b of Appendix 3 .)

Gender Pay Gaps by Age Category

Under the GS Grade Level factor, we see that 10 out of 13 grade levels showed the female average salary as equal to or higher than the male average salary. (See Table 3c of Appendix 3 and the graph below.) The remaining female salary percentages were 99.3 or a less than 1 percent pay gap (grade 5 and grade 7) and 97.4 or a 2.6 percent pay gap (grade 8). These data indicate that, for each GS grade, females and males had close to the same average position in range (average step position). The explanation for the difference in the overall female salary percentage for the General Schedule of 91.1 percent (see Table 1a in Appendix 1) and these subpopulation percentages near 100 percent is that relatively more females were found in lower grades, which appears to reflect differences in occupational distribution. For grades 1-8, the number of females exceeded the number of males, with the percentage of employees who were female ranging from about 52 to 71 percent. At grades 9-15, the percentage of employees who were female ranged from about 42 to 50 percent. Grades directly link to pay ranges—i.e., there are generally lower pay rates and ranges at lower grades and higher pay rates and ranges at higher grades. Thus, grade is the primary driver of average pay levels.

Female/Male Salary Percentage for GS Grades

Under the Racial/Ethnic Groups factor, we see the largest pay gap between males and females in the American Indian or Alaskan Native racial/ethnic group, which also had the smallest percentage of the total population. (See Table 3d of Appendix 3 and the graph below.) In the Black/African American racial/ethnic group, the female average salary was slightly higher than the male average salary.

Female/Male Salary Percentage for Each Racial/Ethnic Group

Due to the small populations for grades 1, 2, and 3, those grades were merged to form a single subpopulation; resulting in 13 grade levels instead of 15.

Appendix 4 Findings

Detailed data by occupational series.

Appendix 4 shows detailed data for subpopulations under the Occupational Series factor in 2022—i.e., the female/male average salary percentages and pay gaps for specific occupational series. Appendix 4 also shows the population-weighted average salary percentage as a contrast to the overall raw salary percentage. The population-weighted average can shed light on the effect of the varying male-female distribution across occupational series.

The population-weighted average salary percentages were 98.0 percent for All White Collar (Table 4a of Appendix 4 ), 98.2 percent for the General Schedule (Table 4c of Appendix 4 ), 94.9 percent for Blue Collar employees (Table 4e of Appendix 4 ), and 97.8 percent for the Executive branch (Table 4g of Appendix 4 ). These percentages were close to 100 percent and above the corresponding overall raw female salary percentages. This indicates that male-female distributions across the occupational series groups appear to explain much of the overall gender pay disparity. Appendix 4 also summarizes data on female/male salary percentages by occupational group. For White Collar employees, for 94 out of the 330 occupational groups (28 percent), the female average salary equaled or exceeded the male average salary (i.e., equal to or greater than 100 percent). For an additional 153 occupational groups (46 percent), the female salary percentage was 95-99.9 percent. For 83 occupational groups (25 percent), the female salary percentage was less than 95 percent. (See Table 4b of Appendix 4 .)

For the General Schedule, for 86 out of the 313 occupational groups (27 percent), the female average salary equaled or exceeded the male average salary (i.e., equal to or greater than 100 percent). For an additional 156 occupational groups (50 percent), the female average salary percentage was 95-99.9 percent. For 71 occupational groups (23 percent), the female salary percentage was less than 95 percent. (See Table 4d of Appendix 4. )

For Blue Collar employees, for 33 out of the 142 occupational groups (23 percent), the female average salary equaled or exceeded the male average salary (i.e., equal to or greater than 100 percent). For an additional 58 occupational groups (41 percent), the female average salary percentage was 95-99.9 percent. For 51 occupational groups (36 percent), the female salary percentage was less than 95 percent. (Data is redacted when occupations have fewer than 10 females.) (See Table 4f of Appendix 4 .)

For Executive branch employees, 128 out of the 471 occupational groups (27 percent), the female average salary equaled or exceeded the male average salary (i.e., equal to or greater than 100 percent). For an additional 210 occupational groups (45 percent), the female average salary percentage was 95-99.9 percent. For 133 occupational groups (28 percent), the female salary percentage was less than 95 percent. (See Table 4h of Appendix 4 .)

Appendix 5 Findings

Summary of population-weighted averages by factor.

Appendix 5 shows a summary of female average salary as a percentage of male average salary for various factors, where the percentage is a population-weighted average that reflects the relative size of the subpopulations for each factor.

For example, for the Age factor, there are age ranges (e.g., 25-34, 35-44) that define subpopulations for the factor. For each subpopulation, female average salary is expressed as a percentage of male average salary. A weighted average is computed using the size of each subpopulation as a percentage of the total population. This weighted average can shed light on the effect of the varying male-female distribution across subpopulation categories. The population-weighted average should be compared to the overall raw average for the given snapshot date.

The factor based on occupational series produced the highest population-weighted averages. (See also the graph below.) In 2022, the weighted average for the Occupational Series factor of 98.0 percent for White Collar employees, which is about 7 percentage points above the corresponding overall raw average of 90.5 percent (see Table 5b of Appendix 5 ). This data suggests that specific occupation series explain much of the gender pay disparity.

After the occupation series factor, the Race/Ethnic categories factor produced the highest population-weighted average for White Collar and General Schedule employees. OPM studied pay gaps by racial/ethnic group separately. (See Appendices 6-11.)

Population-Weighted Averages for White Collar Employees

Appendix 6 Findings

Male and female pay gaps relative to white males by racial/ethnic group.

Appendix 6 shows male and female average salaries for each racial/ethnic group and pay gaps relative to White males for White Collar, General Schedule, Senior Executive Service, Senior Level/ Scientific or Professional, Blue Collar, and Total Executive Branch populations in September 2022.

In the Executive Branch, the average salary for males and the average salary for females in the Asian & Native Hawaiian/Pacific Islander racial/ethnic group exceeded the average salary for White Males. The pay gaps for males and females in the other racial/ethnic groups ranged from 5.6 percent for White females to 26.2 percent for American Indian/Alaskan Native females. (See Table 6a of Appendix 6 .)

In the General Schedule, the average salary for males in the Asian & Native Hawaiian/Pacific Islander racial/ethnic group exceeded the average salary for White males. The pay gaps for other males and females in the other racial/ethnic groups compared to White males ranged from 1.0 percent for Asian & Native Hawaiian/Pacific Islander females to 27.6 percent for American Indian/Alaskan Native females. (See Table 6b of Appendix 6 .)

For White Collar employees, the average salary for males and females in the Asian & Native Hawaiian/Pacific Islander racial/ethnic group exceeded the average salary for White Males. The pay gaps for males and females in the other racial/ethnic groups compared to White males ranged from 9.6 percent for White females to 28.8 percent for American Indian/Alaskan Native females. (See Table 6c of Appendix 6.)

For Blue Collar employees, the average salary for males in the Asian & Native Hawaiian/Pacific Islander racial/ethnic group exceeded the average salary for White males. The pay gaps for other males and females in the other racial/ethnic groups compared to White males ranged from 0.7 percent for Other (more than one race) males to 29.3 percent for American Indian/Alaskan Native females. (See Table 6d of Appendix 6.)

For the Senior Executive Service, pay gaps ranged from 0.5 percent for Black/African American males to 3.5 percent for Other (more than one race) males compared to White males. (See Table 6e of Appendix 6 .)

For Senior Level/Scientific or Professional employees, the average salary for Asian & Native Hawaiian/Pacific Islander females exceeded the average salary for White males. Pay gaps for the other racial/ethnic groups compared to White males ranged from 0.3 percent for Asian & Native Hawaiian/Pacific Islander males and Hispanic/Latino males to 2.7 percent for Hispanic/Latino females. Some data is not shown due to small population size. (See Table 6f of Appendix 6 .)

Not shown due to small population size

Appendix 7 Findings

Summary of male and female distributions in each racial/ethnic group.

For each analyzed population (Executive branch, SES, and SL/ST), Appendix 7 shows male and female employment counts in each racial/ethnic group, percentage of males in each racial/ethnic group, percentage of females in each racial/ethnic group, the percentage of the total population that is in each racial/ethnic group, and the distribution of males and females in each racial/ethnic group across the total population.

About 61 percent of Executive branch employees identified as belonging to the White racial/ethnic group. About 19 percent of Executive branch employees identified as belonging to the Black/African American racial ethnic group. The other racial/ethnic groups each comprised less than 10 percent of the Executive branch population. (See Table 7a of Appendix 7 .)

There is less diversity in the Senior Executive Service and Senior Level/Scientific or Professional populations. About 74 percent of the Senior Executive Service and 82 percent of the Senior Level/Scientific or Professional population identified as belonging to the White racial/ethnic group, respectively. In addition, the percentage of those populations that are male was also higher compared to the Executive branch as a whole (61 percent of the Senior Executive Service population and 71 percent of the Senior Level/Scientific or Professional population are male, respectively, compared to 56 percent of the Executive branch population that are male). (See Table 7b and Table 7c of Appendix 7 .)

In the Executive branch, there are more females than males in the American Indian/Alaskan Native and Black/African American racial/ethnic groups. The other racial ethnic groups have more males than females. (See Table 7a of Appendix 7 .)

Appendix 8 Findings

Population-weighted average percent of white male salary for each racial/ethnic group.

Appendix 8 shows averages that are weighted based on White Collar occupational series population percentages. These are calculated by dividing the number of employees in a given racial/ethnic group who are in each occupation by the total number of employees in the given racial/ethnic group; each population percentage is then multiplied by the Percent-of-White Male Average Salary for each occupation and all the results are summed to derive the population-weighted average percent-of-White-male average salary. Appendix 8 also shows corresponding pay gap percentages derived by subtracting the population-weighted average percent-of-White-male average salary from 100 percent.

In most cases, the averages that are weighted based on occupation population percentages are greater than the corresponding raw percentages of White male average salary, resulting in smaller pay gaps. For example, the White Collar occupation population-weighted average pay gap for American Indian/Alaskan Native females relative to White males is 8.1 percent compared to the raw pay gap of 28.8 percent relative to White males. (See Appendix 6 , Table 6c.) This data suggests that the distribution of employees across occupation series explains some of the gender and racial/ethnic pay disparity.

Appendix 9 Findings

Number and percentage of gs employees by grade and racial/ethnic group.

Appendix 9 shows the number and percentage of General Schedule employees at various grades by each racial/ethnic group. In other words, the percentages represent the percent of employees out of the total number in a given racial/ethnic group that are at a given grade. For example, 20 percent for White employees at GS-13 means that 20 percent of White employees are in the GS-13 grade. GS-12 is the most populous grade for each racial/ethnic group.

There is a higher concentration of employees at lower GS grades in the American Indian/Alaskan Native racial/ethnic group than appears in the other racial/ethnic groups. This data suggests that higher employment at the lower grades partly explains the large pay gap for the American Indian/Alaskan Native racial/ethnic group compared to White males.

Percentage of General Schedule Employees by Grade and Racial/Ethnic Group

*Graph represents data found in Appendix 9

Appendix 10 Findings

Gaps for gs employees for each racial/ethnic group by grade level.

For each racial/ethnic group and gender at each General Schedule grade, Appendix 10 shows the male average salary, female average salary, percent of White male average salary, and pay gaps relative to White males. The pay gaps varied depending on the subpopulation and grade level compared. We note that differences in average salary at various grades can reflect various factors, including (1) use of discretionary authority to set a newly hired employee's salary above step 1, (2) use of quality step increases, (3) how long the employee has been in the grade (which may relate to the employee's age and/or to whether the grade is a full performance level for the employee's occupation) and (4) whether the grade is a level in an employee's career ladder (which means the employee will generally be in that grade for 1-2 years and is more likely to have a lower step in that grade). Certain occupations have different career ladders and full performance levels; thus occupational distribution may explain some of the gaps between racial/ethnic group by GS grade level. In many cases, there is no pay gap for a subpopulation when compared to While males or the average salary of the subpopulation and gender exceeded the average salary of White males. For example—

• The average salary for American Indian/Alaskan Native males exceeded the average salary for White males at grades 1-3, 7, and 9-11. Pay gaps at the other grades ranged from 0.1 percent at grade 6 to 4.4 percent at grade 4.
• The average salary for American Indian/Alaskan Native females exceeded the average salary for White males at grades 1-3, 5-7 and 9-12. Pay gaps at the other grades ranged from 1.1 percent at grade 13 to 3.6 percent at grade 15.
• The average salary for males in the Asian & Native Hawaiian/Pacific Islander racial/ethnic group exceeded the average salary for White males at all grade levels except grades 1-3 (pay gap of 4.4 percent).
• The average salary for females in the Asian & Native Hawaiian/Pacific Islander racial/ethnic group exceeded the average salary for White males at all grade levels.
• The average salary for Black/African American males exceeded the average salary for White males at every grade except 10 (pay gap of 1.0 percent) and 12 (no pay gap).
• The average salary for Black/African American females exceeded the average salary for White males at every grade except 8 (pay gap of 1.6 percent)
• The average salary for Hispanic/Latino males exceeded the average salary for White males at grades 6-12. Pay gaps at the other grades ranged from 1.3 percent at grade 13 to 2.9 percent at grade 4.
• The average salary for Hispanic/Latino females exceeded the average salary for White males at grades 1-3, 6, and 9-12. Pay gaps at the other grades ranged from 0.2 percent at grade 4 to 2.6 percent at grade 8.
• The average salary for White females exceeded the average salary for White males at grades 6, 10, 11,13, and 15. The average salary for White females at grade 12 equaled the average salary for White males. Pay gaps at other grades ranged from 0.2 percent at grade 14 to 2.7 percent at grade 8.
• The average salary for Other (more than one race) males exceeded the average salary for White males at grade 5 and 6. Pay gaps at the other grades ranged from 0.6 percent at grades 7, 9, and 10, to 5.4 percent at grade 4.
• The average salary for Other (more than one race) females exceeded the average salary for White males at grades 6 and 10. There was no pay gap at grade 11. Pay gaps at the other grades ranged from 0.8 percent at grade 15 to 4.2 percent at grade 8.

Appendix 11 Findings

Pay gaps and population weighted averages for each racial/ethnic group by white collar occupational series.

Appendix 11 shows detailed data for subpopulations under the Occupational Series factor in 2022 (i.e., occupational series). This appendix also shows the population-weighted average percentage as a contrast to the overall raw percentage. (See discussion under Appendix 4.) The pay gaps (if any) varied depending on the subpopulation and occupational series. A high-level summary of pay gaps by subpopulation and occupational series group is provided below.

• The population-weighted percentages were 93.9 percent for American Indian/Alaskan Native males, 101.9 percent for Asian and Native Hawaiian/Pacific Islander males, 98.2 percent for Black/African American males, 96.8 percent for Hispanic/Latino males, and 94.0 percent for Other (more than one race) males. (See Table 11b in Appendix 11 .)
• The population-weighted percentages were 97.5 percent for White females, 91.9 percent for American Indian/Alaskan Native females, 102.2 percent for Asian and Native Hawaiian/Pacific Islander females, 98.9 percent for Black/African American females, 94.9 percent for Hispanic/Latino females, and 92.6 percent for Other (more than one race) females. (See Table 11d in Appendix 11 .)
• These percentages were greater than the corresponding overall raw percentage of White male average salary for White Collar employees in Appendix 6, apart from data for the Asian and Native Hawaiian/Pacific Islander racial/ethnic group for which salaries exceeded White male average salaries. The distribution of racial/ethnic groups across the occupational series groups appear to explain some of the racial/ethnic pay disparities.
• For 8 (14.3 percent) out of the 56 occupational series groups with American Indian/Alaskan Native male representation, the average American Indian/Alaskan Native male salary equaled or exceeded the White male average salary (i.e., was equal to or greater than 100 percent). For an additional 18 occupational series groups (32.1 percent), the American Indian/Alaskan Native male salary percentage was 95-99.9 percent. For 30 occupational series groups (53.6 percent), the American Indian/Alaskan Native male salary was less than 95 percent. (See Table 11e in Appendix 11 .)
• For 71 (51.1 percent) out of the 139 occupational series groups with Asian and Native Hawaiian/Pacific Islander male representation, the average Asian and Native Hawaiian/Pacific Islander male salary equaled or exceeded the White male average salary (i.e., was equal to or greater than 100 percent). For an additional 49 occupational series groups (35.3 percent), the Asian and Native Hawaiian/Pacific Islander male salary percentage was 95-99.9 percent. For 19 occupational series groups (13.7 percent), the Asian and Native Hawaiian/Pacific Islander male salary was less than 95 percent. (See Table 11e in Appendix 11 .)
• For 75 (37.3 percent) out of the 201 occupational series groups with Black/African American male representation, the average Black male salary equaled or exceeded the White male average salary (i.e., was equal to or greater than 100 percent). For an additional 84 occupational series groups (41.8 percent), the Black male salary percentage was 95-99.9 percent. For 42 groups (20.9 percent), the Black male salary was less than 95 percent. (See Table 11e in Appendix 11 .)
• For 29 (18.1 percent) out of the 160 occupational series groups with Hispanic/Latino male representation, the average Hispanic/Latino male salary equaled or exceeded the White male salary (i.e., equal to or greater than 100 percent). For an additional 73 occupational series groups (45.6 percent), the Hispanic/Latino male salary percentage was 95-99.9 percent. For 58 groups (36.3 percent), the Hispanic/Latino male salary was less than 95 percent. (See Table 11e in Appendix 11 .)
• For 12 (14.1 percent) out of the 85 occupational series groups with Other (more than one race) male representation, the average Other male salary equaled or exceeded the White male average salary (i.e., equal to or greater than 100 percent). For an additional 37 occupational series groups (43.5 percent), the Other male salary percentage was 95-99.9 percent. For 36 occupational series groups (42.4 percent), the Other male salary was less than 95 percent. (See Table 11e in Appendix 11 .)
• For 78 (24.8 percent) out of the 314 occupational series groups with White female representation, the average White female salary equaled or exceeded the White male average salary (i.e., equal to or greater than 100 percent). For an additional 141 occupational series groups (44.9 percent), the White female salary percentage was 95-99.9 percent. For 95 occupational series groups (30.3 percent), the White female salary percentage was less than 95 percent. (See Table 11e in Appendix 11 .)
• For 4 (7.1 percent) out of the 56 occupational series groups with American Indian/Alaskan Native female representation, the average American Indian/Alaskan Native female salary equaled or exceeded the White male average salary (i.e., equal to or greater than 100 percent). For an additional 17 occupational series groups (30.4 percent), the American Indian/Alaskan Native female salary percentage was 95-99.9 percent. For 35 occupational series groups (62.5 percent), the American Indian/Alaskan Native female salary percentage was less than 95 percent. (See Table 11e in Appendix 11 .)
• For 59 (42.4 percent) out of the 139 occupational series groups with Asian and Native Hawaiian/Pacific Islander female representation, the average Asian and Native Hawaiian/Pacific Islander female salary equaled or exceeded the White male average salary (i.e., equal to or greater than 100 percent). For an additional 47 occupational series groups (33.8 percent), the White female salary percentage was 95-99.9 percent. For 33 occupational series groups (23.7 percent), the Asian and Native Hawaiian/Pacific Islander female salary percentage was less than 95 percent. (See Table 11e in Appendix 11 .)
• For 77 (38.3 percent) out of the 201 occupational series groups with Black/African American female representation, the average Black female salary equaled or exceeded the White male average salary (i.e., equal to or greater than 100 percent). For an additional 67 occupational series groups (33.3 percent), the Black female salary percentage was 95-99.9 percent. For 57 occupational series groups (28.4 percent), the Black female salary percentage was less than 95 percent. (See Table 11e in Appendix 11 .)
• For 28 (17.5 percent) out of the 160 occupational series groups with Hispanic/Latino female representation, the average Hispanic/Latino female salary equaled or exceeded the White male average salary (i.e., equal to or greater than 100 percent). For an additional 60 occupational series groups (37.5 percent), the Hispanic/Latino female salary percentage was 95-99.9 percent. For 72 occupational series groups (45.0 percent), the Hispanic/Latino female salary percentage was less than 95 percent. (See Table 11e in Appendix 11 .)
• For 6 (7.1 percent) out of the 85 occupational series groups with Other (more than one race) female representation, the average Other female salary equaled or exceeded the White male average salary (i.e., equal to or greater than 100 percent). For an additional 27 occupational series groups (31.8%), the Other female salary percentage was 95-99.9 percent. For 52 occupational series groups (61.2%), the Other female salary percentage was less than 95 percent. (See Table 11e in Appendix 11 .)

Regularly conducting pay equity audits to assess whether similarly situated individuals are equitably compensated for similar work is part of the equity roadmap contained in the Biden-Harris Administration Governmentwide DEIA strategic plan. 10 OPM will continue to periodically analyze Governmentwide pay gap data. OPM will also be updating the guidance issued in 2015 11 on conducting gender data analysis to include also examining data by racial/ethnic group, similar to this Governmentwide data analysis.

The Federal Government strives to be a model employer, one that values DEIA. OPM will take further actions to support reducing gender and racial/ethnic pay gaps in the Federal Government, including submitting a report to the President describing any changes to Government-wide and agency-specific compensation practices recommended and adopted pursuant to section 12 of EO 14035.

Footnote 10

The White House. “Governmentwide Strategic Plan to Advance Diversity, Equity, Inclusion, and Accessibility in the Federal Workforce,” November 2021. https://www.whitehouse.gov/wp-content/uploads/2021/11/Strategic-Plan-to-Advance-Diversity-Equity-Inclusion-and-Accessibility-in-the-Federal-Workforce-11.23.21.pdf

Footnote 11

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• Appendix 11

Salary History Bans Fall Short As Men Voluntarily Reveal Pay, Study Shows

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Men are more likely to reveal previous pay in job interviews.

Salary history bans, or laws that prohibit employers from asking about prospective employees’ pay at previous jobs, have been implemented in 21 states to address pay gaps. However, a new study finds a significant limitation to the bans—men are disclosing their previous salaries anyway.

Asking job candidates about their pay at previous jobs is problematic because women have historically been paid less than men. A woman underpaid in a previous job could be forced to carry the lower wage forward if she had to disclose her salary history. The goal of bans that prevent employers from asking about previous salaries is to prevent this perpetuation of inequality.

Although bans on salary history forbid employers from seeking information on past pay, applicants are not prevented from disclosing this information on their own. This could benefit those who have been well-compensated in the past, and they might reveal this information to gain a competitive edge. Employers, recognizing this, may start to make assumptions about candidates who don't mention their salary history, possibly viewing them as less likely to have been highly paid in the past.

In the new study, researchers surveyed close to 1,000 U.S. workers. A collaboration between Columbia University, Cornell University and Tufts University professors, the results have been posted on the IZA -Institute for Labor Economics website for discussion.

When employers don’t ask about salary history, the study found that men are about 12% more likely than women to volunteer their previous pay. The authors label this difference the “gender disclosure gap.” Generally, the higher someone’s previous pay, the more likely they were to volunteer their pay history. However, even well-paid women were less likely than their male counterparts to disclose their previous pay if not directly asked.

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When job candidates disclose their past salary, it's a bell that can't be unrung. The researchers explain that in states like New York, New Jersey, and Massachusetts, where laws prohibit employers from inquiring about salary history, employers can still verify any voluntarily provided salary information. This verified information can then be used to set wages or make hiring decisions, potentially impacting the fairness and objectivity the bans aim to promote. Even in states where voluntarily disclosed salary information cannot be legally verified, the information remains in the employer's mind and may influence their pay or hiring decisions.

One troubling study finding for advocates of the bans was the rise in voluntary salary disclosures over time. The researchers conducted two surveys, the first in 2019 and again 1.5 years later. The unprompted volunteering of salary histories increased by 6-8% over this time. The researchers speculate that this could be related to the implementation of bans, but can’t confirm this from their data.

Perhaps most worrisome is the researchers’ hypothesis that employers will deduce that those who do not disclose their salary must have been paid less in the past. If men typically reveal their past wages more than women, this would result in an inclination to assume that women had been paid less in their former positions. The researchers did not address this question directly and suggest it’s a valuable avenue for future research.

The results of this study call into question the effectiveness of laws that make it illegal to ask about salary history in interviews. “Our results suggest that laws prohibiting employers from asking about pay history might not be reliable ways to ensure pay equity at the point of entry,” the researchers write.

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Gender Pay Gap

Introduction.

The gender gap refers to the difference between the average earnings of men and women in a specific workforce. The measure of the gender gap has been internationally accepted. It has, over the years, been used to measure the position of women in the economy by comparing them to men. Even though some people refute the gender pay gap, multiple types of research have proved its existence. Worldwide average results on the existing pay gap revealed that for every dollar a man makes, a woman makes 77 cents. The inequality in gender payments has, in the long run, proved to cause massive effects on women, whereby most end up retiring in poverty. The gender pay gap has been demonstrated in all countries and employment sectors. Many researchers have continued to argue that the gender pay gap has made it hard for women to accumulate wealth and compete with their men counterparts. The gender pay gap is, therefore, a complex issue that requires robust solutions that are based on inclusivity.

According to the Australian government (2), the gender pay gap is experienced by women during their ingestion in the workforce. The gender pay gap, in addition to other economic factors, makes women less likely to make career advances and secure savings for their future, making it more likely that they might end up living in poverty in old age. Gender pay gap results from cultural workplace problems that include negative trends in undervaluing the significant contributions of women in their places of work (Australian government 3). The undervaluing of women in their work areas leads to their underrepresentation in senior and executive management roles. The existing gender pay gap in Australia is due to bias and discrimination during the hiring and paying process. Additionally, the gender pay gap has proved to be a result of women and men working in different industries in different jobs, with women-dominated industries attracting lower wages.

Additionally, the United States also faces the challenge of the gender pay gap. Even though the government has proved to be working towards bridging the gender pay gap, women in the United States continue to receive little annual remuneration compared to Men (Barroso and Brown 2). A report released in 2020 revealed that women received 84 percent of the 100 percent earned by men. According to (Barroso and Brown 4), the gender gap in the United States is due to many underlying factors such as educational attainment, occupational segregation, and work experience. Over the few years, women have proved to try to bridge the gender pay gap by venturing into male-dominated jobs and professions. However, the number that ventures in traditionally male-dominated careers are few as their more significant number is represented in lower-paying jobs, which further explains the gender pay gap.

Research through the use of surveys on the five American based medical related career fields revealed the existence of a gender pay gap. The medical field occupations under scrutiny included; physicians, nurses, surgeons, healthcare practitioners, technical and healthcare support, and direct care jobs (Barry 4). The American Community Survey revealed through public microdata that women received lower occupational wages in all medical careers except the physician occupation. Additionally, the research proved the existence of a negative growth among women compared to men, a trend that further contributes towards widening the gender pay gap in most medical-related careers.

The gender pay gap was also witnessed in a nonprofit organization. According to (Finley et al. 1362), women in nonprofit organizations recorded a pay that was 8.9 percent lower than that of men. Some nonprofit organizations are, however, in a bid to close the gender pay gap by allowing negotiations and ensuring equal compensation across all genders. Additionally, Finley et al. (1367) argue that the labor force participation rates and risk preferences are some of the highest contributing factors to the gender pay gap.

Additionally, according to Magda et al. (2238), there exists a higher gender pay gap in foreign-owned firms compared to domestically-owned firms. The gender pay gaps vary according to the jobs involved; however, the most significant gaps are often witnessed on top and at the bottom. Also, women’s job returns are much lower than men’s in domestic firms; wage premia widen within-firm wage distribution, a factor that has further led to the widening of the gender pay gap.

In many countries, women receive less pay than men. Pay discrimination exists in most employment dimensions, and much evidence supports the allegation. Therefore, it is time to face the facts and find probable solutions for the gender pay gap epidemic. Governments and individuals have acknowledged the existence of gender pay gaps. In some instances, the gender pay gap is witnessed due to unavoidable factors such as level of education and experience. However, in other instances, the gender pay gap is being witnessed due to the continued workplace cultures that undermine the role of women in places of work and therefore end up discriminating against them during the section process. The gender pay gap has proved to have long-term effects on women because they cannot carry out career advancement and save a little for the future, a factor that contributes to their poverty during retirement days. The government should therefore take the matter with the utmost seriousness it deserves and ensure the gender pay gap has been bridged to ensure gender equality.

Works Cited

Barroso, Amanda, and Anna Brown. “Gender Pay Gap in U.S. Held Steady in 2020.” Pew Research Center, Pew Research Center, 8 June 2022, https://www.pewresearch.org/fact-tank/2021/05/25/gender-pay-gap-facts/.

Barry, Janis. “Real wage growth in the U.S. health workforce and the narrowing of the gender pay gap.” Human resources for health 19.1 2021: 1–9.

Finley, Andrew R., Curtis M. Hall, and Amanda R. Marino. “Negotiation and executive gender pay gaps in nonprofit organizations.”  Review of Accounting Studies  27.4 2022: 1357–1388.

Government, Australian. “What Is the Gender Pay Gap?” WGEA, 2018, https://www.wgea.gov.au/the-gender-pay-gap

Magda, Iga, and Katarzyna Sałach. “Gender pay gaps in domestic and foreign-owned firms.”  Empirical Economics  61.4 (2021): 2237-2263.

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Jennifer Lawrence’s Essay on Wage Inequality Is Anything but Unlikable

Late last year, leaked emails from the Sony hack revealed that Jennifer Lawrence (and costar Amy Adams ) made less money from their film American Hustle than their male counterparts. The 25-year-old actress, who has never been one to shy away from saying what’s on her mind , had remained quiet on the salary controversy. This morning, however, she tackled the wage gender gap in Hollywood with a new essay for the Lenny newsletter .

In her piece, “Why Do These Dudes Make More Than Me?” Lawrence explained that she initially hesitated to speak on this particular issue because she doesn’t like to join conversations that “feel like they’re trending” (Equal pay has, after all, been all the rage in Hollywood .) But, after realizing that with talk comes change, she finally decided to open up on her experience with wage inequality.

Lawrence begins by acknowledging that her problems are hard to relate to, but regardless of the size of her paycheck, she has suffered a gender bias . Not only did Lawrence make less than Bradley Cooper , Jeremy Renner, and Christian Bale for American Hustle , but as the highest-paid actress in the world, she’s also still trailing behind highest-earning actor, Robert Downey, Jr. (Downey, Jr. made $80 million, while Lawrence earned $52 million.) In her piece, she blames herself for being a poor negotiator and writes that the fear of seeming “difficult” and “spoiled” kept her from pushing for a better deal in the past. Lawrence ends the essay by saying that she’s tired of choosing to seem likable over getting what she deserves.

It’s almost funny that one of the world’s most popular movie stars was scared to come off as unlikable. This fear has been an issue many other powerful women have had to deal with in the past. Recall last year’s “ Ban Bossy ” campaign from Facebook COO Sheryl Sandberg, who started the movement after saying she was tired of hearing the word being used as a derogatory term for decisive women. And who can forget the vitriol (and subsequent online threats) Emma Watson received after she proudly declared herself a feminist during her powerful U.N. speech .

While words like bossy and feminist have long carried negative connotations, Lawrence’s essay also highlights other potentially problematic terms, such as difficult and spoiled . The actress referenced an instance when she offended a man by giving her opinion in a clear and “no-bullshit way.” “I’m over trying to find the ‘adorable’ way to state my opinion and still be likable!” she wrote. “Fuck that.”

The actress has since learned her lesson. This summer, Lawrence secured a deal for her upcoming film, Passengers , in which she makes considerably more money than her costar Chris Pratt . Lawrence’s negotiating feat, along with today’s Lenny essay, shows it’s important for an actress, especially America’s sweetheart, to say—curses and all—exactly what’s on her mind.

Watch Jennifer Lawrence nail the awkward interview.

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• Human Rights

Gender Pay Gap

Updated 17 April 2021

Subject Human Rights ,  Racism

Downloads 42

Category Social Issues ,  Sociology

Topic Gender Stereotypes ,  Gender Wage Gap ,  Segregation

The Gender Wage Gap is the distinction between the average weekly full-time equivalent wages of women and men, expressed as a percentage of men's income (Miller, 2017). This disparity is a product of several variables that determine the place and role of women in society, namely social, family and stereotypes. These social stereotypes determine which job women and men can perform and which can not perform. Industrial segregation is characterized by the same stereotypes as men and women who work in various industries and occupational segregation, that is, those who work in different occupations. According to IWPR’s report women are almost half of the workforce they are the sole or co-breadwinner in half of American families with children and they receive more graduate degrees than men, yet, on average, women continue to earn considerably less than men (Fact Sheet,, 2017). Does this simply mean women choose low-paying jobs compared to men? Do women work only part-time hence the low income? Does sex, race and gender discrimination influence how much women are paid at the work place? This paper seeks to answer the aforesaid questions and identify the gender bias that exists at work place that results in women earning less than men.Keywords: Gender pay gap, occupational segregation, discrimination.The History of Gender Wage BillAccording to the Office for National Statistics (ONS) which collects data on earnings in the UK, the average pay of women working full-time was only 90.6% of men’s pay in 2016. This means that compared to men, women stopped earning on the 10th November 2016 – they were effectively working for no money after this date, which is referred to as Equal Pay Day (Anitha, 2017). The reality of the matter is when women are earning the plight of their families is at stake especially for single mothers who are sole providers for their families. The revolution of equal pay in the UK started in the 1920s and 30s, state policy in the UK reflected the common practice of lower wages for women, both in pay rates and in the lower rates of unemployment benefit, to which they were entitled (Anitha, 2017). It is in this era that women activists started campaigning for equal pay among men and women and shamed the injustices experienced by women at work places. Women groups, trade unions and women’s suffrage had to mobilize working women to fight for their rights and demand equal employment benefits compared to their male counterparts. The issue of equal pay was again raised again and again and it became an increasingly articulated demand by trade unions and women’s organizations from 1950s onwards (Anitha, 2017).The good news is that the gender wage gap is shrinking, if slowly, in comparison to 1970, white women earned 70 cents on the dollar but, now, women are more educated and more experienced, and society in general is more aware of the gap than ever before (Anitha, 2017). Thus global companies like Companies like Salesforce and Pintrest have consequently made global headlines promising to close the Wage gap in their own capacity. The discrepancy in the Wage Gap came as a result of societal stereotypes who assumed that generally men are ambitious than women, that women’s place is care giving, that is having babies and raising a family, some argued that women willingly opt for low-paying jobs compared to men all these allegations are fallacies that have been proved wrong over the course of time.The provisions regarding equal pay are now in the Equality Act 2010 and according to this Act, men and women are entitled to equal pay and conditions if they are doing the same job; like work (work that is the same or broadly similar); work rated as equivalent (different work, but which is rated under a job evaluation scheme as equivalent); or work of equal value (that is, work that requires similar effort, skill and decision-making (Anitha, 2017).Gender Wage Gap Is a Societal ProblemWage equality isn’t and should not only be a woman’s issue but a concern the society should care about. It is not the choice of women to be women better still it is not their choice to be paid way less than men but that is exactly what happens. Are women being punished simply for being women? Is the society okay with that? In a response to the gender gap, the UK Government published a booklet called “negotiating your salary.” It claims to help women “understand the secrets to success in negotiation” and the Minister responsible at the time said:“I want women to feel able to hold employers to account if they feel they are not being paid the same as their male colleagues and I hope this new booklet will be an important tool in helping them do that” (McCormack, 2015). Equality aside the pay gap isn’t economically fit as research as shown that companies perform better when more women hold leadership and managerial positions. For example, CNBC quotes a 2011 survey by Catalyst showing that company boards made up of 19 to 44 percent women achieved 26 percent more return on invested capital than those firms with no women board members (McCormack, 2015). Sadly the pay gap is seen even in the family setting, whereby the boy child is seen to be favored in terms of the allowance allocated to him by the parents compared to the girl child.According to a research conducted in Australia by Gai McGrath, Westpac’s general manager of retail banking confirmed that boys earned 6.6 percent more pocket money than girls, he confirmed that paying girls less pocket money than boys “sends a powerful message that girl’s and women’s work isn’t as valuable as that of boy’s.” (McCormack, 2015). Radical Actions To Close Pay Gap In FutureBelieve or not according to a report by the World Economic Forum best known for its high-profile gathering each year in Davos, Switzerland, found that economic disparity between women and men around the world was rising even though the gap was closing on other measures, such as education (Treanor, 2016). The same report predicted that it could take 118 years for economic parity to be achieved as the economic gap is caused by a number of factors, including women being paid almost half of what men receive, working on average 50 minutes a day longer and having a much slimmer chance of reaching senior roles (Treanor, 2016).There are a number of benefits derived from closing the pay gap, namely;Equal job opportunities and social justice – By closing the pay gap companies can create a cohesive organization where all parties are treated as equals. Valuing all employees, that is, male and females equally can greatly motivate them to perform better and enhance financial independence. When women are empowered, their families and society at large is empowered.Greater profitability to the company and the economy at large – Women should be given an equal opportunity as men to contribute to the growth of the economy and be compensated equally as men. Women are unexploited potential in the labor force, and companies should take good advantage of that and utilize women skills, however they should ensure they handsomely compensate them for services rendered. Beneficial to both employer and employee – It is pivotal for any serious organization to ensure they adhere to equal pay on all its employees for profit maximization and productivity. According to (Syed & Kramar, 2013), in the recent decades, significant demographic changes such as, increased women participation have placed greater pressure on both governments and the private sector to initiate and implement creative solutions to train, integrate and retain a rapidly changing and diverse working population. The traditional approach of identifying pay gap is based upon identification of gender bias in a particular industry however wider analysis has shown how the problem is industry based, rather than job based (Cox, 2012). All jobs in feminized industries tend to be lower paid than similar ones in male-dominated industries; unfortunately, the reverse doesn’t happen in masculinized industries, gender gaps are highest in industries such as finance and mining (Cox, 2012).According to a report prepared by (Cox, 2012), shows that fields dominated by women—such as nursing, social work, and teaching are typically less compensated than fields that are predominantly male, like finance. This has less to do with the skills involved and more to do with gendered preconceptions of what kind of work is valuable (Cox, 2012).Ways To Eliminate Pay GapThrough Pay Transparency, especially top management. Transparency answers any concerns arising relating to pay gap at work places despite of gender. Case Example: ‘Transparency is a core tenet at data analytics startup SumAll, it’s what’s helped the four-year old company grow at a rapid clip, according to its cofounder and CEO Dane Atkinson. He says SumAll has realized 1000% growth each year of operation and has amassed 350,000 clients’ (Dishman, 2017).Equal pay to all employees, who are in the same job bracket. Companies should ensure they accord women employees with the respect they do their male counter parts. Women need to have a sense of belonging in the company. Male colleagues should also ensure they treat their female colleagues as team mates and work together harmoniously for the greater good of the firm.Pay Gap TheoriesThere are various theories used to thoroughly explain the origin of pay gap and discrimination at work place, namely:The human capital Model- Gender differences in qualifications have been analyzed within the human capital model, which basic idea is that every person has some form of human capital (Grybaite, 2006). This simply means the skills and abilities acquired through trainings, education and experience. This further determines the earnings the employees get. Gender roles also affect the time women have for paying work , because traditionally the place of women is at home, hence they are expected to take care of household chores before they go to work. This further limits the time and energy they have to work for pay. According to human capital critics, women and men cannot be studied as autonomous individuals and the different conditions they face in their working life must be put in material and social context (Grybaite, 2006).Labor Market Discrimination- the portion of the gap that is not due to gender differences in qualifications is generally presumed to due to labor market discrimination (Grybaite, 2006). It’s good to note that skilled workers are paid better than unskilled workers. However economic discrimination arises when identical workers receive different pay doing the same job, or are given different chances of employment or promotion (Grybaite, 2006). This simply means women are paid lesser than men for the same work performed. The standard economic analysis of discrimination is based on Gary Becker work, who assumed that some individuals have a taste for discrimination (Grybaite, 2006). Becker analysis of discrimination is inlayed within the convectional economic analysis of utility-maximizing firms that often straiten their behavior (Grybaite, 2006). Crowding Model- developed by Barbara Bergmann is useful to understand sex inequality in labor market and consequently pay gap, but this theory does not answer the important question as to why female jobs are crowded (Grybaite, 2006). For firms to be competitive they ought to treat all their employees equally.Conclusion There has been narrowing of the gap in gender pay from 1980, especially amongst younger employees, nevertheless, it still continues. For instance, an analysis by Pew Research Center shows that women grossed 83 percent if what men were paid for both part-time and full-time US employees. On the basis of this approximation, an additional 44 work days would be required for women to gross what men got in 2015. Comparatively, women grossed 80 percent of what men got in 2015 while examining year-round, full-time employees according to US Census Bureau. Nonetheless, in 2015, the wage gap is less for individuals aged between 25-34. Females in this group grossed 90 cents for each dollar earned by a man in within a similar age group (Blau et al., 2015). The approximated 17 percent gap in gender pay for every worker in 2015 reduced from 1980's 36 cents. The gap for young females has narrowed over time even more. Thus, in the 80s women grossed 67 percent of what men earned, in comparison to 2015's 90 percent. But why is there persistence of gap in gender pay? A 2013 PEW research found out that women are most likely to claim that they took leave from their professions to care for their families. Such kind of interruptions and breaks usually have an effect on earnings in the long-run. Roughly, 4 in 10 mothers claimed that at some time in their career, they took considerable time off (39 percent) or decreased their work hours (forty two cent) to care for family members or child. Roughly about twenty seven claimed they had left work altogether for taking care of such domestic duties. Less men claimed the same (Blau et al., 2015).Although females have raised their positions in well-remunerating careers traditionally men's domain, for example managerial and professional jobs, women in entirety continue being overrepresented in poorly paying careers, and this might also lead to gender disparities in pay. Some aspects of the pay disparity might also be because of gender discrimination. Women, in a 2013 survey were about two times as likely as men to claim they had faced gender discrimination at work. Moreover, both women and men experience inequalities at their place of work-with 77 percent of women and 63 percent of men claiming that there is need to review the gender pay gap . Even as labor activists are advocating for equal wage, women should go a step further and ensure they negotiate for their salaries, increment and even promotions. This is because there is an inverse relationship between advocating for themselves and likability (Grybaite, 2006). Women should also get into male-dominated fields and excel in them in order to be treated with the seriousness they deserve. Women should be empowered economically in order for them to be dependent on themselves and not men. Other changes that assist in closing the wage gap include companies being compelled to carry out regular salary audits so that they can proactively not only monitor but also tackle gender-based variations, women can be trained and equipped with superior negotiating skills for equal pay, advocating for themselves as far as benefits, promotions and salary is concerned. Finally policy makers must come up with new pay fairness acts or enhance existing ones so as to harmonise the gender pay gap. In future research must be undertaken on the best changes that must be undertaken so as provide both women and men equality in their places of work and make sure that there is zero gender discrimination or disparity as far as work and pay are concerned. ReferencesAnitha, S., (2017). The history of the struggle for equal pay. Striking Women. New York, Cengage Learning. Blau, F. D., Gielen, A. C., & Zimmermann, K. F. (2015). Gender, inequality, and wages. Oxford, UK: Oxford University Press.Cox, E., (2012). The reality of the gender wage gap. The Coversation.Oxford, UK: Oxford University Press.Dishman, L., (2017). A Definitive Strategy To Eliminate the Gender Pay Gap. Fast Company. CengageBooks. New JerseyInstitute for Women's Research., (2017). The Gender Wage Gap by Occupation 2016; and by Race and Ethnicity . Institute for Women's Policy ResearchMcCormack, C., (2015). Why The Gender Pay Gap Is A Societal Problem, Not A Women's Issue. Elite Daily. New York.Miller, C., (2017). The Gender Pay Gap Is Largely Because of Motherhood. The Upshot.CengageLearning.New YorkSyed, J., & Kramar, R. (2017). Human Resource Management: A Global and Critical. New York. Treanor, J., (2016). Global economic disparity between men and women. The guardian. UK.

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VA urges lawmakers to approve $15B to fund budget gap or risk delays, cuts to veterans’ benefits and care

The Department of Veterans Affairs on Thursday, July 18, 2024, said Congress must move quickly to approve supplemental funding for the agency to close an estimated $15 billion spending gap through fiscal 2025 to avoid delays and cuts to veterans’ benefits and care. (Stars and Stripes)

WASHINGTON — The Department of Veterans Affairs on Thursday said Congress must move quickly to approve supplemental funding for the agency to close an estimated $15 billion spending gap through fiscal 2025 to avoid delays and cuts to veterans’ benefits and care.

Disability compensation and pension benefit payments to veterans scheduled to be delivered by Oct. 1 are “at risk of being delayed,” if the VA does not receive an estimated $3 billion to address a budget shortfall for the remainder of fiscal 2024, which ends Sept. 30, said Terrence Hayes, the VA press secretary.

He also said the VA might be forced to cut veterans services and care in fiscal 2025 if Congress does not agree to increase the agency’s $369 billion spending plan.

A $12 billion budget shortfall is projected next fiscal year without the additional funds.

“If the Veterans Health Administration does not receive additional funding, VA will continue to provide high-quality health care to veterans — but will make adjustments to remain within the current budget for fiscal year 2025,” Hayes said.

Demand for VA services exceeded expectations as a record number of veterans now seek VA services and benefits, he said. At the same time, the VA is reporting higher prices for prescription drugs and more hiring costs to fill critical vacancies at VA hospitals and clinics.

Democratic lawmakers from the House and Senate Veterans’ Affairs committees expressed support Thursday for providing the funds to cover the shortfall, while some Republican members criticized the VA for not anticipating higher spending needs.

“More veterans and their families are accessing their earned benefits than ever before, and they should not be shortchanged. This is a cost of war, and I will continue working to do right by each and every one of them,” said Sen. Jon Tester, D.-Mont., who is chairman of the Senate VA Committee.

But Rep. Mike Bost, R-Ill., chairman of the House VA Committee, accused VA Secretary Denis McDonough and other VA leaders of misleading lawmakers in testimony at budget hearings in the spring.

“This is not just fiscal mismanagement. It is strategic whiplash,” Bost said about the $15 billion shortfall through 2025.

Chief financial officers from the Veterans Benefits Administration and Veterans Health Administration apprised lawmakers this week of the anticipated budget shortfall and their expectations for additional funds, the VA said.

Rep. Mark Takano of California, the top Democrat on the House VA Committee, said he is encouraging fellow lawmakers to work with the VA to cover the shortfall and ensure benefits to veterans continue.

“Spending conversations for [fiscal 2025] are still very much ongoing, and there is time to address this like adults before the next fiscal year. We will need to have the hard, honest conversation of how we will pay for health care that veterans have earned,” he said.

But Takano said he continues to be concerned about rising costs for covering private health care for veterans who seek non-VA medical services in their communities.

Veterans are able to get treatment from private health care providers related to injuries and illnesses from military duty if the needed services are not readily available at VA facilities near their homes.

Takano warned a cost shift is underway to the private sector that risks reducing the quality of care at VA hospitals and clinics.

“I have been sounding the alarm for months about the push for privatization through community care, and how community care is more expensive and has far less oversight than direct VA care,” he said.

Hayes said the agency will not continue its recent pace of hiring at VA hospitals and clinics to meet veterans’ demand for more services following passage of the Sergeant First Class Heath Robinson Honoring our Promise to Address Comprehensive Toxics Act, or PACT Act .

The law provides medical care and monthly disability compensation to veterans diagnosed with diseases connected to toxic exposures from burn pits, radiation at weapons testing sites, and aerial spraying of Agent Orange and other herbicides.

Since the PACT Act became law, more than 710,000 veterans have enrolled in VA health care, Hayes said. Additional funds from Congress will enable the VA to fill vacancies and new positions in critical areas, he said.

“VA will continue to strategically hire in several key areas, such as mental health care and at targeted locations — such as locations with ongoing increases in health care enrollees,” Hayes said.

The VA does not have a hiring freeze, he said. However, some VA nurses held a rally in Washington last month to protest what they described as a national shortage of nurses at VA hospitals and clinics.

“The VA is working closely with Congress and the White House Office of Management and Budget to resolve these potential shortfalls in a way that prevents any adverse impacts on veterans and allows us to continue to deliver care and benefits to veterans at record rates,” Hayes said.

previous coverage

• VA projects $15B shortfall driven by costs for veterans benefits, prescription drugs and a bigger workforce
• Senators, advocates fear private community health care is eroding VA medical services

related stories

• Lawmakers, veterans urge FDA to approve ecstasy for treating PTSD in clinical settings
• Combat-injured veterans face a new battle at home — restoring retirement benefits to military careers cut short

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Home — Essay Samples — Social Issues — Equality — Gender pay gap phenomenon

Gender Pay Gap Phenomenon

• Categories: Equality Gender

About this sample

Words: 1007 |

Published: Mar 28, 2019

Words: 1007 | Pages: 2 | 6 min read

Works Cited

• Campbell, E. Q. (2017). Women in sports: 50 fearless athletes who played to win. Mango Media Inc.
• Bornstein, S. (2018). The gender pay gap: An international perspective. Routledge.
• Equality and Human Rights Commission. (2018). The gender pay gap. Retrieved from https://www.equalityhumanrights.com/en/advice-and-guidance/gender-pay-gap
• Forbes. (2017). The world's highest-paid athletes.
• Forbes. (2018). The world's highest-paid athletes.
• Liao, M. (2020). A survey of the gender pay gap in sports. Social Science Research Network.
• Liu, Y. (2021). The gender pay gap in professional sports: A review of empirical research. Social Science Research Network.
• Moses, M. (2019). Women's soccer and the gender pay gap: A critical analysis of the US Women's National Soccer Team. Societies, 9(4), 82.
• T13. (2018). ¿Por qué la diferencia de sueldos entre Neymar y Endler en el PSG es tan abismal? Retrieved from https://www.t13.cl/noticia/deportest13/por-que-diferencia-sueldos-entre-neymar-y-endler-psg-es-tan-abismal
• World Economic Forum. (2021). Global gender gap report 2021. Retrieved from https://www.weforum.org/reports/gender-gap-2021-report-100-years-pay-equality.

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Breaking news, mortgage rate lock-in gap: some states have it worse in u.s. housing market.

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With mortgage rates soaring, America’s housing market is stuck in a “mortgage rate lock-in effect,” where homeowners are unwilling to sell since it means they’ll have to trade in their low-interest-rate loan for one at today’s higher rates.

A new report by  U.S. News & World Report  has found that this lock-in effect is much worse in some states than others.

It all depends on the state’s “lock-in gap,” which is the average mortgage interest rate the homeowners are currently paying subtracted from the rate available to them for purchasing another property. This gap can fluctuate based on location, due to things like local real estate laws or the number of lenders in the area.

Here are the report’s key findings:

• The average rate on outstanding mortgages in the U.S. is 4.1%, according to the Federal Housing Finance Agency.
• The average rate on a new mortgage in the U.S. (as of July 2, when the study was conducted) is 7.25%.
• Nationally, the average “lock-in gap” is 3.15 percentage points between rates on new and existing mortgages.
• The national average loan amount is $357,000, so the monthly mortgage payment at 4.1% would be $1,817. With a mortgage at 7.25%, that monthly payment would jump to $2,435. That means homebuyers who buy a new house will end up paying an average of $618 more per month. Plus, homeowners in states with the widest lock-in gaps will experience an even higher cost increase.

The states with the worst mortgage ‘lock-in gaps’

Colorado has the widest mortgage rate lock-in gap in the country. Here’s how U.S. News & World Report breaks down these numbers:

• Colorado homeowners’ existing mortgage rate is 3.8% (the lowest of any state).
• A new mortgage in Colorado (as of July 2) will get you an average rate of 7.25%. That’s a spread of 3.45 percentage points between rates on new and existing mortgages.
• For the state’s average loan amount of $454,000, a monthly payment at 3.8% would be $2,077. That would jump to $3,097 at 7.25%. That’s a difference of $1,020, or 49.1%.

Behind Colorado with the widest lock-in gaps are Utah (3.445 percentage points), Iowa (3.375), Minnesota (3.35), North Dakota (3.35), Oregon (3.35), South Dakota (3.35), and Washington (3.35).

The states with the narrowest lock-in gaps

Homeowners in states with slim lock-in gaps will see less of a cost increase if they sell their homes and then buy at current mortgage rates.

Texas boasts the narrowest mortgage rate lock-in gap in the country. Here’s how that plays out:

• Texas homeowners are holding on to mortgages with rates averaging 4.3%, one of the country’s highest.
• Current mortgage rates offered in Texas (as of July 2) average 6.85%, the lowest of any state.
• That’s a spread of 2.55 percentage points between rates on new and existing mortgages.
• For Texas’ average loan amount of $336,000, a monthly payment at 4.3% would be $1,862. That would increase to $2,202 at 6.85%. That’s a difference of $340 per month.

Behind Texas with the narrowest lock-in gaps are New York (2.575 percentage points), New Mexico (2.575), Michigan (2.675), and Rhode Island (2.775).

How much more would repeat homebuyers pay per month?

In states with high housing costs, homeowners’ mortgage payments could go up by more than $1,000 per month if they sold and then bought at current mortgage rates.

The study found that homeowners in Hawaii would see their average monthly payments go up the most, by $1,591.

California homeowners would see their average monthly payments spike by $1,470.

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Other states with the highest potential payment spikes include the following:

• District of Columbia would see their payments go up by $1,193.
• Utah would see their payments go up by $1,083.
• Washington would see their payments go up by $1,058.
• Colorado would see their payments go up by $1,020.

Look before you leap

“My business is definitely feeling the impact of higher interest rates on our ability to resell projects,” says real estate investor Doug Greene, of Signature Properties in Philadephia. “Buyers are reluctant to take the leap at a much higher rate and monthly payment.”

Although these statistics can indeed be sobering, there’s still some hope on the horizon for homebuyers, particularly if they already own a home and have built up some equity.

“Depending on when they purchased their home, they could have substantial equity,” says Rose Krieger, senior home loan specialist at Churchill Mortgage in Spokane Valley, WA. “This means they may have a larger down payment to compensate for the rate and price.”

If that down payment is 20% or more, homeowners would also eliminate the need for mortgage insurance on a conventional loan, further lowering their proposed monthly payment.

But the answer is never one size fits all, says Shmuel Shayowitz, president and chief lending officer of private mortgage banker Approved Funding. So you should always consult a mortgage and financial adviser to crunch the numbers before deciding whether to sell or stay put.

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