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Displacement, asymmetric information and heterogeneous human capital
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 layoffs 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 layoff 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 layoff 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 layoffs. This results from two reinforcing effects. First, plant closings have substantially more negative effects on minorities than on whites. Second, layoffs 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 off "protected" workers in mass layoffs rather than fire them for cause. As a result, relative to whites, a layoff 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 layoffs 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 layoffs 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.
AUTHORS: Hu, Luojia; Taber, Christopher
Identification of models of the labor market
This chapter discusses identification of common selection models of the labor market. We start with the classic Roy model and show how it can be identified with exclusion restrictions. We then extend the argument to the generalized Roy model, treatment effect models, duration models, search models, and dynamic discrete choice models. In all cases, key ingredients for identification are exclusion restrictions and support conditions.
AUTHORS: French, Eric; Taber, Christopher
The changing pattern of wage growth for low skilled workers
We examine the key components that determine an individual's early career wage growth and how these factors have changed for less skilled workers over the last twenty years. In particular, we examine the relative importance of accumulating work experience as compared to the quality of job matches in influencing wage growth. Our main finding is that over this period, the vast majority of the variation in wage growth is due to variability in the return to experience.
AUTHORS: Taber, Christopher; French, Eric; Mazumder, Bhashkar