The Gender Pay Gap, Fringe Benefits, and Occupational Crowding

Abstract

Using data from the 1991 National Longitudinal Survey of Youth, the authors estimate earnings equations for each of seven occupational categories and the aggregate sample. When fringe benefits are excluded from the compensation measure, a gender coefficient is statistically significant (that is, women are found to have received significantly lower compensation than men) within six of the seven occupational categories, the exception being the most female-dominated category. When an index of compensation that includes fringe benefits is used, however, a gender coefficient is significant in only one category, which contains relatively heterogeneousjobs. Gender-specific regressions are used to estimate what part of the earnings gap between men and women is due to differences in traits. The results indicate that occupational assignment is the primary determinant of the pay gap, a result that is consistent with a "crowding" explanation of that gap. M ost studies of the gender pay gap have used the wage rate to measure compensation. Non-pecuniary dimensions of work and fringe benefits are usually ignored or are included as explanatory control variables. It is possible that the gender pay gap is actually smaller than is indicated by traditional analysis if the jobs chosen by women have higher non-pecuniary rewards than those chosen by men. That is, women may choosejobs, asJoni Hersch (1991) has

Estimating Pay Gaps for Workers With Disabilities: Implications From Broadening Definitions and Data Sets

“…This is universally so in the existing literature on the pay gap experienced by people with disabilities and is mostly true in the pay gap literature across other demographic groups (see Altonji & Blank, 1999, for a survey of the early literature; and for more recent studies on discrimination and demographic differentials, see Bertrand & Mullainathan, 2004;Blau, Ferber, & Winkler, 2010;Fryer & Levitt, 2004;List, 2004;Neal, 2004). The good news is that some recent studies of gender pay gaps have started to advance the use of broader definitions of pay (Levy, 2006;Pierce, 2001Pierce, , 2010Solberg & Laughlin, 1995;Zhao, 2012).…”

Beyond human capital explanations for the gender pay gap among executives: investigating board embeddedness effects on discrimination

“…Researchers identified characteristics on company as well as individual levels that drive those compensation differences (Arulampalam et al 2007;Solberg and Laughlin 1995;Blau and Kahn 1999;Rubery 1995). The gender pay gap is very often attributed to human capital differences between women and men: Work experience due to parental leave (Blau and Kahn 2007), education received (Blau and Kahn 2001), differences in occupations (Daymont and Andrisani 1984), differences about choices concerning career, job, and family (Tharenou 2008) as well as negotiation skills (Greig 2008;Kaman and Hartel 1994), non-cognitive skills such as assertiveness and confidence (Grove et al 2011), lower preferences for performing in a competition and lower overconfidence (Niederle and Vesterlund 2007), and expectations of what can be earned (Major and Konar 1984) are factors identified to drive the gender pay gap.…”

“…This result indicates that even after controlling for human capital variables as well as various other influences, a female executive still receives a lower compensation than a comparable male. Thus, human capital which researchers identified as main reason for the gender pay gap (Bowles et al 2007;Blau and Kahn 2007;Solberg and Laughlin 1995;Kaman and Hartel 1994) is not the only driver of compensation levels. With this result, we show that a pay gap among German executives in fact exists.…”

Health Insurance and the Wage Gap

“…The data for the project come from two different supplements to the Current Population Survey: the February Contingent and Alternative Employment Arrangement Supplements in 1995and 2001and the March Annual Demographic Files for 1981-2001.…”