Implications of Policy Interventions on Eliminating Gender Gaps

This paper studies policy interventions intended to eliminate gender differences in labor market outcomes, principally wages. Because gender is an individual attribute rather than a manipulable treatment, the ideal experiment of randomly assigning gender to evaluate its effects is infeasible. Policies that remove gender labels from the employment process are the closest feasible counterpart. We quantify both the intended and unintended consequences of the policies through simulated interventions of an estimated equilibrium model of statistical discrimination with dynamic choices of education and labor market participation. In the short run the policy that requires gender free applications in the market for skilled labor eliminates wage gaps but once education choices respond the effects are attenuated. A more comprehensive policy that enforces gender free compensation reverses the wage gap in skilled markets and eliminates it in unskilled labor markets, even once education adjusts. These interventions impact college rates, the college premium gap and participation rates as well. The final section studies these interventions using a difference-in-differences (DID) approach to analyze the simulated data. With education fixed, the DID method recovers the policy effects but this is not the case once education adjusts, reflecting the effects of the intervention on both treated and control groups through equilibrium adjustments in beliefs.