This study examines the gender wage gap in the US using two separate cross-sections from the Current Population Survey (CPS). The extensive literature on this subject includes papers which use wage decompositions to divide gender wag gaps into “explained” and “unexplained” components. Problems with this approach include the heterogeneity of the sample data. In order to address the difficulties of comparing like with like this study uses a number of different matching techniques to obtain estimates of the gap. By controlling for a wide range of other influences, in effect, we estimate the direct effect of simply being female on wages. However, to form a complete picture, one should consider that gender wages are affected by a number of other factors such as parenthood, gender segregation, part-time working and unionization. This means that it is not just the core “like for like” comparison between male and female wages that matters but also how gender wage differences interact with other relevant risk factors which are more common for women. That these interactions exist has already been discussed in the literature but evidence that precisely or systematically estimates such effects remains scarce. The most innovative contribution of this study is to do that. Our findings imply that the idea of a single uniform gender pay gap is perhaps less useful than an understanding of how gender wages are shaped by multiple different forces.
gender pay Current Population Survey part-time working gender segregation unionization sample selection bias matching IPWRA USA