Unintended Consequences of Closing Pay Gaps Across Multiple Groups: A Formal Modeling and Simulation Analysis of Allocation Methods.

The article examines how firms' efforts to close pay gaps across multiple demographic groups—such as gender and race—can unintentionally conflict with goals of equitable representation within the workforce. Using formal modeling and simulations, it contrasts two approaches to closing pay gaps: the cost minimization approach (CMA), which seeks to reduce pay disparities at the lowest financial cost, and the equitable rewards approach (ERA), which prioritizes raises for employees most underpaid relative to their qualifications. The analysis reveals that the CMA incentivizes firms to concentrate raises on a small number of employees with high pay gap intersectionality (e.g., minority women), effectively enacting a form of tokenism that may undermine broader diversity goals, especially when such employees are few or when demographic traits correlate strongly with job attributes. The ERA, while more aligned with equitable representation, tends to be substantially more expensive, particularly when pay gaps are larger in high-wage jobs or when multiple pay gaps exist. The authors recommend including intersectional categories explicitly in pay gap regressions to mitigate these issues and provide empirical predictions to guide future research on pay equity and workforce diversity.