Chapter 10 Notes

Evidence from Court Cases

2010: $175 million settlement of a class action case against Novartis Pharmaceuticals • Denied advancement to female sales representatives and was unresponsive to their complaints 2008: $33 million settlement of sex discrimination lawsuit against Smith Barney • Routinely assigned smaller and less valuable accounts to female brokers 2004: $54 million settlement of sex discrimination lawsuit against Morgan Stanley • Withheld raises and desirable assignments from women who took maternity leave

Gender Gap in Top Corporate

A different study of the S&P 1500 firms found that 2.5% of executives in their sample were women and earned 45% less than their male counterparts • Female execs were younger, with less seniority, which contributed to this difference • Most of the difference was attributed to the fact that women managed smaller companies and were less likely to be the CEO, chair, or president of their company Remember: discrimination doesn't have to be overt or conscious behavior • Often subtle and difficult to document, let alone remove

Work-Family Conflicts

A survey of top executives in 10 major U.S firms found the following: A study of top MBA programs found women were more likely to have taken time out since graduation, and that came with a huge wage penalty

Decline in the Unexplained Gap

Also over this time period, the unexplained portion of the gender differential decreased 1. Likely that discrimination against women declined • Views of women's weaker attachment to the labor force eroded over time • Feedback effects • Changes in attitudes may have made such discriminatory tastes or prejudices increasing less socially acceptable 2. Plausible that women enhanced their unmeasured skills compared to men • Gender differences in college major, math SAT scores have both decreased • Men's and women's attitudes toward money and work have become more similar in recent years 3. The labor market demand shifts that widened overall wage inequality appear to have favored women relative to men • Manufacturing employment declined • Technological changed favored white-collar jobs o Interpersonal skills have become more valuable 4. Favorable shifts in the composition of the female labor force • As female labor force expanded, the women who entered tended to be those with relatively high (unmeasured) skills

Government

As of the largest election, women comprised • 23% of the U.S Senate • 19.3% of the U.S House of Representatives • 12% of governors • 25.4% of state legislators

Concerns

As we have previously discussed, omitted factors could also be affecting the estimates of discrimination • Particularly in these studies: Tastes for particular types of work and availability for travel So while there is some evidence of discrimination, it is not possible to ascribe a specific portion of gender differences in occupations to discrimination vs. individual choices that men and women make • Both are likely important

Biases in the Estimate of Discrimination

As with most statistical studies, these results are not conclusive What other information could we be missing that would affect workers' wages • Some can't be easily quantified o Motivation, work effort, willingness to compete • Some are unavailable in specific data sets o College major, math scores The omission of this information can other overestimate or underestimate the amount of labor market discrimination If men are more highly motivated, or there are gender differences in college major, this could overestimate the extent of labor market discrimination • Part of the "unexplained" gender differential could be due to omitted factors If women possess greater impersonal skills, which should increase their productivity and thus wages, this could underestimate the extent of labor market discrimination • Not included in the "unexplained" gender differential due to omitted factors In general, the unexplained gap is viewed as an overestimate of discrimination due to omitted factors

MBAs

Bertrand, Goldin, and Katz (2010) examined earnings of MBAs who graduated between 1990 and 2006 from the Booth School of Business of the University of Chicago The gender gap, similar to the lawyers, started out small at the start of their careers, but after averaging across the whole sample (MBAs 1-16 years removed from graduation), men earned 33% more than women The gap was largely explained by the career-family tradeoffs (workforce disruptions, or fewer weeks worked by women) Men also had a slight academic advantage (higher GPA and more finance courses) After accounting for these and other factors, men still earned nearly 7% more

Consequences of Occupational Segregation

Chapter 7: Women are concentrated in relatively low-paying occupations • Women more likely to be in clerical, service, and professional occupations (elementary and secondary school teaching and nursing) • Men more likely to work in higher-paying blue-collar occupations, higher-paying professional occupations (lawyer, physician, STEM) Requirements or skills of male and female jobs may help to account for pay differences between them • Maybe male jobs require more education and training than female jobs • More physical strength, inconvenient hours, etc.

Causes of Occupational Segregation

Chapter 9: Human capital theory suggestions that women choose predominantly female occupations presumably because they require smaller human capital investments and lower wage penalties for time spent out of the market Chapter 8: Socialization and subtle barriers to impede women's access to training in traditionally male fields There is some persuasive evidence of the importance of discrimination • Women are less likely to be promoted • Women may encounter discrimination in access to on the job training

Possible Sources of the Unexplained Gap

Childbearing: Children have a negative effect on women's wages • Not only due to workforce interruptions, discrimination against mothers • Losses in the returns to firm-specific training • Extra caregiving and housework burdens • Accepting lower wages in exchange for greater job flexibility • Feedback effects Gender Differences in Soft Skills: Typically not included in date sets • Women, on average, place a lesser value on money and work than men due

College Graduates

Corbett and Hill (2012) examined gender wage differences in 2009 among those who had graduated one year earlier • Average age of 23, mostly single with no children • Data from the Department of Education, information on major, GPA, type of college (private v. public) Before decomposition, women earned 18% less than men, on average College major was an important factor • Men are more likely to have majored in relatively higher-paying fields like engineering and computer science • Women are more likely to have majored in fields like education and the social sciences that tend to lead to lower-paying jobs When college major, occupation, and other variables were controlled for, the gender pay gap was substantially reduced, but still found an unexplained pay gap of 7% Sizeable gap potentially due to discrimination Likely that the gap will increase as they age, if men fare better in terms of wages and promotions

Occupational Differences

Differences in the employment of men and women across occupational categories account for 27% of the pay difference between men and women in 1998, almost a third of the pay difference (32.9%) in 2010 A substantial body of research that looks at over 400 detailed occupational categories finds a negative relationship between percent female in an occupation and the wage of the occupation • Predominantly female jobs pay less than predominantly male jobs for both men and women, all else equal Even within female-dominated occupations, women tend to earn less than their male counterparts

Indirect Effects

If discriminatory differences in the treatment of equality qualified men and women is widespread and persistent, this could adversely affect the behavior of women • Decision on whether to continue their schooling • Participate in training programs • Remain in the Labor Force Discrimination lowers the returns to human capital investments for women, so they have less incentive to make those investments These indirect effects can also be called feedback effects

Interpretation

If the actual gender wage ratio is 80%, that means women's wages are, on average 80% of men's wages If women had the same education and experience, industry and occupational distribution and union coverage as men, the gender wage ratio would rise to 91% • This accounts for the explained gap Women would still earn less than similar men even when all measured characteristics are taken into account

The "Pipeline" Effect

It is difficult to determine whether the scarcity of women at the top is due to what is called the "pipeline" effect • The fact that women are relative newcomers and it takes time to move up through the ranks • A lag should be expected in women's representation in top-level positions o Only 5% of women received master's degrees in 1970, up to 25% in 1981, and 46% in 2011 Given that the growth of women in top-level managerial jobs has been so much slower than the expansion in female receipt of MBA degrees, it seems reasonable to conclude that the pipeline effect can only partly explain the lower representation of women a h the top

Direct Effects

Labor Market Discrimination directly affects the economic status of women since men and women who are equally productive and should receive the same pay (or be in the same occupation) do not receive equal rewards When discrimination is present, women are paid less than their marginal product • The increase in output of a firm that results from the hiring of an additional worker, all other factors remaining constant Could also decrease their productivity directly • Denied access to a training program, or when customers don't want to patronize a female salesperson

Labor Market Discrimination

Labor Market Discrimination: When two equally qualified individuals are treated differently solely on the basis of their gender (race, ethnicity, age, disability, etc) In the absence of discrimination, profit-maximizing employers in a competitive labor market pay workers according to their productivity • Similar personnel decisions are made on an objective basis: Hiring, placement, or promotion • Gender would be an irrelevant consideration

Hiring Audits- Restaurants

Male and female pseudo-job seekers were given similar resumés and sent to apply for jobs waiting tables at 65 Philadelphia restaurants • In high-priced restaurants, where earnings of workers are generally higher, a female applicant's probability of getting an interview was 35% lower than a male's, and the probability of getting an offer was 40% lower

Evidence on Discrimination from Experiments

Natural Experiment: An experiment not set up by the researchers themselves Use of blind v. non-blind auditions for symphony orchestras Using audition records from 8 symphony orchestras, researchers found that the adoption of blind auditions substantially increased the probability that a woman would advance out of preliminary rounds and be the winner in the final round Blind auditions explained a quarter of the increase in the percentage female in the top five symphony orchestras in the US, from less than 5% in 1970 to 25% in 1996

Lawyers

Noonan, Corcoran, and Courant (2005) studied two cohorts of graduates from the University of Michigan Law School 15 years after graduation • One studied from '87-'93, the next from '94-'00 While the gap in pay between women and men started relatively small, by 15 years later men earned over 50% more After accounting for differences in qualifications, grades in law school, work history, and information about their employers, men earned 11% more • Female lawyers were more likely to work shorter hours, and part-time or taken time off due to childbirth

The Declining Gender Pay Gap

Now that we've looked at some sources of the gender pay gap, we want to analyze why is has decreased, focusing on our two sets of factors: supply-side and labor market discrimination As well as • Wage structure: The returns that the labor market offers for various skills and for employment in various industries or occupations • Useful to see the declining gender pay gap in the context of other shifts in earnings patterns • Rising wage inequality, or a widening dispersion in the distribution of earnings

Labor Market-wide Evidence from Statistical Analyses

One standard method of analyzing gender differences in earnings is to decompose the gender wage gap into two parts: • Explained gap: The part of the gender difference that is due to differences in human capital or other qualifications • Unexplained gap: The part that cannot be explained by these factors Using data from the Panel Study of Income Dynamics (PSID), Blau & Kahm (2006) decompose the gender wage gap for full-time workers The gender wage ratio is about 80%, since the gender wage differential is about 20% Labor market experience is a significant determinant of the gender wage differential, in 1998, this was about a 3.5-year gap in experience Women in the sample had more education than men, which works to lower the gender wage gap • Does not help explain the gender wage gap An expected, differences in occupation and industry help explain a considerable portion of the gender wage gap • With union status, these factors explain 53% of the gender wage gap

Evidence on Discrimination

Pinpointing the exact portion of the pay gap that is due to labor market discrimination is difficult There is strong evidence of pay differences between men and women that are not accounted for by extensive measured qualifications The rate of the increase in the gender-pay ratio decreased in the 1990s, though it has become erratic in the 2000s, and remained virtually unchanged since 2005 Since the gender pay ratio, increased after 1980, the gender pay gap decreased

Widening Wage Inequality

Reflects changes in wage structure- Specifically an increase in the returns to skills • The rewards that the labor market gives for various worker skills and for employment in various industries or occupations The college wage premium has been rising, contributing to the increase in wage inequality, and reasons for this increase can be attributed to both demand- and supply-side factors • Demand: Increase in relative demand for skills, due to technological change • Supply: Slower growth in the supply of college-educated workers after 1980 The rightward shift of the demand curve was larger than rightward shift in the supply curve, and the college wage premium rose

Hiring Audits- Science Labs

Science faculty were asked to provide feedback on application materials from fake senior undergraduate who had "recently" applied for a science laboratory manager position • Faculty participants rated the male applicant as significantly more competent and suitable for the position, recommended a starting salary of along $4,000 more than female applicants, and offered more career mentoring toward male applicants • Female faculty were equally likely to exhibit this bias against the female students as male faculty

Causes of Underestimation

Some of the lower qualifications of women could be directly due to labor market discrimination • Could affect things that were controlled in the decomposition o Occupation, industry, and Unionism If we only include education, experience and race from Table 10-1, our adjusted wage ratio falls from 91% to 81% This type of statistical analysis doesn't account for any feedback effects • Women not pursuing majors in traditionally male fields due to discrimination • Women receiving lower returns to labor market experience than men

Care Work

Some research has focused on paid care work • Occupations where "concern for the well-being of others is likely to affect the quality of services provided" o Nurse, teacher, college professor, childcare worker, and health aide • Expanding and disproportionately female occupations One study found that care work pays less than other occupations even after controlling for education, experience, occupation, and industry characteristics (including percent female in the occupation) Occupational Segregation can reinforce cultural notions of exaggerated differences between men and women

Is there a Glass Ceiling??

The glass ceiling is the name given to the set of subtle barriers believed by many to inhibit women and minorities from reaching the upper echelons of corporate America, government, and academia Gender Differences at the Top • In 2012, only 14.3% of all executive officers in Fortune 500 companies were women, and women held just 8.1% of the top-earner spots o Though a substantial increase from 1995 numbers, 8.7% and 1.2% respectively

Unexplained Gap

This decomposition suggests that work-related characteristics are important, but only part of the story The portion of the wage differential that is not explained by productivity-related characteristics serves as an estimate of labor market discrimination • Potentially 41% of the pay gap

Further Evidence from Statistical Analyses

Using the same statistical techniques, a number of studies focus on subgroups decomposing the gender wage gap We will consider studies on • College graduates • Lawyers • MBAs

Determinants of Trends in the Gender Wage Gap

We expect the gender wage gap to decline if either of the following happens: • Women increase their qualifications relative to men's • Labor market discrimination against women decreases Changes in the returns to qualifications (skills) and sectors (occupations and industries) will have different effects on women's and men's wages, and thus different effects on the gender wage gap We expect the gender wage gap to increase if wage structure (the returns to skill and sector) changes to reward more highly qualifications and sectors where men are better suited than women

Causes and Consequences of Gender Differences in Occupations

What are the consequences for women of occupational segregation? In particular, what is its relationship to the pay gap between men and women? What are the causes of gender differences in occupational distributions? Specifically, what role does labor market discrimination play? Does evidence indicate a "glass ceiling" that limits the upward mobility of women?

Discrimination

While the pipeline effect and work-family conflict account for some of the extremely low representation of women at the very top of corporate America, it doesn't rule out the possibility of discrimination A study of S&P 1500 firms found that • Women were more highly represented in top-level jobs when the CEO or the chairman of the board was a woman (women-led firms), than in man-led firms • Female top-level executives in women-led firms earned 10-20% more than comparable executive women in male-led firms

Children

While women are less likely than men to have children at all levels of corporate hierarchy, women at the top were actually more likely to have children than women in the lower echelons • The presence of children does not fully explain women's underrepresentation at the top

Academia

Women are • Concentrated at the lower end of the occupational hierarchy • Underrepresented at research universities • Heavily represented at liberal arts institutions, and two-year institutions Similar to the case with women in management, the pipeline effect and work-family conflict can account for some of this disparity The pipeline tends to be "leaky" as well; at each sep of the hierarchy, the representation of women decreases A number of studies find lower probabilities of promotion for women in academia, after accounting for qualifications

Results of the Blau-Kahn Study

Women improved their qualifications relative to men • Narrowed the gap in experience o 6.6 years in 1979, to 3.5 years in 1998, to 1.4 years in 2011 • Women surpassed men in educational attainment o 1979- Men were 4 pp more likely to have a college or advanced degree o 1998- Women were 2 pp more likely to have a college or advance degree (roughly holds to today) • Shifts in women's occupations • Decrease in the gender gap in unionization