In a seminal paper Gibbons and Katz (1991; GK) develop and empirically test an asymmetric information model of the labor market. The model predicts that wage losses following displacement should be larger for layouts than for plant closings, which was borne out by data from the Displaced Workers Survey (DWS). In this paper, we take advantage of many more years of DWS data to examine how the difference in wage losses across plant closing and layout varies with race and gender. We find that the differences between white males and the other groups are striking and complex. The lemons effect of layout holds for white males as in the GK model, but not for the other three demographic groups (white females, black females, and black males). These three all experience a greater decline in earnings at plant closings than at layouts. This results from two reinforcing effects. First, plant closings have substantially more negative effects on minorities than on whites. Second, layouts seem to have more negative consequences for white men than the other groups. These findings suggest that the GK asymmetric information model is not sufficient to explain all of the data. We augment the model with heterogeneous human capital and show that this model can explain the findings. We also provide some additional evidence suggestive that both asymmetric information and heterogeneous human capital are important. In support of both explanations, we demonstrate that the racial and gender effects are surprisingly robust to region, industry and occupation controls. To look at the asymmetric information, we make use of the Civil Rights Act of 1991 which induced employers to lay of protected workers in mass layouts rather than fire them for cause. As a result, relative to whites, a layout would be a more negative signal for blacks after 1991 than before. If information is important, this would in turn imply that blacks experience a relatively larger loss in earnings at layouts after 1991 than prior; and that's what we find in the data. In addition, as further evidence for heterogeneous human capital, we document for the first time in the literature that the two types of layoffs reported in the DWS data, namely layouts due to slack work and position abolished have very different features when compared to plant closings. Finally, we simulate our model and show that it can match the data.
asymmetric information displaced workers racial and gender wage gap discrimination heterogeneous human capital