Displacement, Asymmetric Information, and Heterogeneous Human Capital

Gibbons and Katz's asymmetric information model of the labor market predicts that wage losses following displacement should be larger for layoffs than for plant closings. This was borne out in their empirical work. In this article, we examine how the difference in wage losses across plant closing and layoff varies with race and gender. We find that the basic prediction by Gibbons and Katz holds only for white males. We augment their asymmetric information model with heterogeneous human capital and show that this augmented model can match the data.