Tracking the Gender Pay Gap: A Case Study

Abstract

This article provides a short introduction to standard considerations in the formal study of wages and illustrates the use of multiple regression and resampling simulation approaches in a case study of faculty salaries at one university. Multiple regression is especially beneficial where it provides information on strength of association, specific dollar estimates, and the option to identify outliers by gender. Resampling simulation allows for analysis at the department level and is beneficial where distributions depart substantially from normal, particularly where there are unequal error variances. Results indicate that both regression and simulation methods provided evidence of a sizable pay gap associated with gender, even after controlling for rank, academic field, and years of service. The gap occurs in fields traditionally viewed as female as well as science fields with typically lower female representation. Finally, we discuss implications for remediation based on these models.