Estimating a Dynamic Adverse-Selection Model: Labor Force Experience and the Changing Gender Earnings Gap


Empirical Micro Seminar
University of Pennsylvania

3718 Locust Walk
309 McNeil

Philadelphia, PA

United States

Joint with: Gayle George-Levi

This paper investigates the role of labor-market attachment, on-the-job human-capital accumulation, occupational sorting, and discrimination in the narrowing gender wage gap over the past three decades. This paper contributes in three ways: First, we formulate a dynamic adverse-selection in which self-fulfilling beliefs about future employment spells arise endogenously in equilibrium, affecting gender differences in labor-market experience, and occupational sorting. Second, we develop a new three-step estimation technique that allows us to estimate the model without solving it. This is particularly important with this class of model because it may exhibit multiple equilibria. We estimate the model using the PSID. Third, we decompose the changes in the gender earnings gap into the different components and quantify the effect of statistical discrimination on the changes in labor-market experience and the earnings gap. Increase in overall productivity, demographic changes and statistical discrimination patterns account for a large percentage of the decline in the gender earnings gap and the increase in female labor market experience. Whereas, relative increase in productivity in professional occupations raise representation of women in professional occupations.

For more information, contact Petra Todd.

Limor Golan

Carnegie Mellon University

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