Abstract

PurposeThis paper explores the wages of White, Black, Hispanic, Asian, Native American and “other race” women and men once differences in basic characteristics among these 12 groups are accounted for. The authors aim to extend comparisons beyond those of women and men of the same race or the various races within a given gender.Design/methodology/approachTo undertake the conditional analysis, first, the authors propose a simple re-weighing scheme that allows to build a counterfactual economy in which workers' attributes for all gender–race/ethnicity groups are the same. Second, the authors use a well-known re-weighting scheme that involves logit estimations.FindingsOnly Hispanic men, Native American men and Asian women have conditional wages around average. Black men and, especially, White, Black, Hispanic, Native American and “other race” women have conditional wages clearly below average, whereas those of Asian and White men are well above average. The wage differential between a privileged and a deprived group is disentangled into the premium of the former and the penalty of the latter, which brings a new perspective to what has been done in the literature based on pairwise comparisons. In this intersectional framework, the authors document that gender penalizes more than race.Originality/valueThis paper examines intergroup earnings differentials using a methodology that allows to examine 12 gender–race/ethnicity groups jointly, which is this work's distinctive feature. The authors' intersectional framework allows to picture the effect of gender and race/ethnicity more broadly than what the literature has shown thus far.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.