Gender Wage Discrimination Bias? A Meta-Regression Analysis

Hendrix College, Minneapolis, Minnesota, United States
The Journal of Human Resources (Impact Factor: 2.37). 09/1998; 33(4):947-973. DOI: 10.2307/146404
Source: RePEc


This study provides a quantitative review of the empirical literature on gender wage discrimination. Although there is considerable agreement that gender wage discrimination exists, estimates of its magnitude vary widely. Our meta-regression analysis (MRA) reveals that the estimated gender gap has been steadily declining and the wage rate calculation to be crucial. Large biases are likely when researchers omit experience or fail to correct for selection bias. Finally, there appears to be significant gender bias in gender research. However, it is a virtuous variety where researchers tend to compensate for potential bias implicit in their gender membership.

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    • "The perceived lack of fit (Heilman, 1983, 2012) or incongruity (Eagly & Karau, 2002) between women's assumed capabilities and the demands of leadership positions evokes the impression that women are not equipped to handle such male-typed tasks. This fact has various negative consequences for women aspiring to these positions (see Eagly & Karau, 2002; Heilman, 2012; for overviews): it fosters a male bias in hiring decisions (Schein, 2001), wage decisions (Eagly & Karau, 2002; Stanley & Jarrell, 1998), and employmentrelated recommendations (Heilman & Okimoto, 2008; Heilman, Wallen, Fuchs, & Tamkins, 2004). "

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    • "The Blinder-Oaxaca decomposition originated and has been widely used in the study of labor market discrimination (Blinder 1973; Oaxaca 1973). Economists and sociologists have, for instance , used it to decompose wage and earnings differences based on gender (e.g., Stanley and Jarrell 1998; Weichselbaumer and Winter-Ebmer 2005) and race (e.g., Darity, Guilkey, and Winfrey 1996; Kim 2010). Although Blinder-Oaxaca decompositions have been a mainstay of empirical research on discrimination, they can be, in principle, applied to explain differences in any continuous outcome across any two groups. "
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    ABSTRACT: This article introduces the R package oaxaca to perform the Blinder-Oaxaca decom-position, a statistical method that decomposes the gap in mean outcomes across two groups into a portion that is due to differences in group characteristics and a portion that cannot be explained by such differences. Although this method has been most widely used to study gender-and race-based discrimination in the labor market, Blinder-Oaxaca decompositions can be applied to explain differences in any continuous outcome across any two groups. The oaxaca package implements all the most commonly used variants of the Blinder-Oaxaca decomposition for linear regression models, calculates bootstrapped standard errors for its estimates, and allows users to visualize the decomposition results.
    • "Another line of the literature suggests that there is inequality in earnings by gender (Hecker, 1998; Marini, 1989; Stanley & Jarrell, 1998; Suter & Miller, 1973; Takahashi & Takahashi, 2011). While many may assume that the income differential is due to discrimination against women, some researchers suggest that the temporary withdrawal from the labor market for child bearing and rearing (Mincer & Ofek, 1982) and differences in the type of schooling or career path (Brown & Corcoran, 1996; Daymont & Andrisani, 1984; Gerhart, 1990) can explain some of the gender differences in payrolls. "
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    International Journal of Public Administration 10/2014; 37(12). DOI:10.1080/01900692.2014.928312
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