Identifying and measuring economic discrimination

Abstract

Differences in wages between men and women, white and black workers, or any two distinct groups are a controversial feature of the labor market, raising concern about discrimination by employers. Decomposition methods shed light on those differences by separating them into: (i) composition effects, which are explained by differences in the distribution of observable variables, e.g. education level; and (ii) structural effects, which are explained by differences in the returns to observable and unobservable variables. Often, a significant structural effect, such as different returns to education, can be indicative of discrimination. KEY FINDINGS Identifying and measuring economic discriminationUsing decomposition methods helps measure both the amount and source of economic discrimination between groups

Average Gaps and Oaxaca–Blinder Decompositions: A Cautionary Tale about Regression Estimates of Racial Differences in Labor Market Outcomes

“…Traditionally, unexplained gaps in mean outcomes have been examined using decomposition methods (see, e.g., Elder, Goddeeris, and Haider 2010; Fortin, Lemieux, and Firpo 2011; Firpo 2017). As noted by Charles and Guryan (2011), however, in recent empirical work researchers have typically focused on a simpler approach of estimating the following model using ordinary least squares (OLS):…”

Average Gaps and Oaxaca's Blinder Decompositions: A Cautionary Tale About Regression Estimates of Racial Differences in Labor Market Outcomes

“…Traditionally, unexplained gaps in mean outcomes were studied using decomposition methods (Elder et al 2010;Fortin et al 2011;Firpo 2017). 2 However, as noted by Charles and Guryan (2011), in recent empirical work researchers have typically focused on a simpler approach of estimating the following model using ordinary least squares:…”