Layoffs and lemons over the business cycle
Introduction
In the labor economics literature, layoffs are often viewed as a selective weeding process. For example, Laing (1994) and Gibbons and Katz (1991) develop signaling models in which firms may choose to lay off workers when they are discovered to be of low ability.1 In contrast, macroeconomists have typically focused on the type of unemployment that arises because the wage is set above the market-clearing level, but unemployed and employed workers are otherwise indistinguishable. In these models, unemployed workers are simply those who were unlucky enough to be laid off. For example, Gray's (1978) contracting model and efficiency wage models such as Shapiro and Stiglitz's (1984) model have this feature. These models have the advantage that they account more naturally than models in which unemployment is generated solely from asymmetric information for the striking tendency of unemployment to rise in recessions and fall in booms.2 However, they also lack the reasonable feature of asymmetric information models that unemployment falls disproportionately on workers who have unexpectedly low productivity. There are few models that fall between these extremes.
In this paper, I consider what happens when layoffs result from a combination of bad luck and selection. One implication of this model is that the proportion of unemployed workers who are laid off due to low productivity varies over the business cycle. The intuition is simple. Suppose that some workers are laid off in every period due to low productivity. However, the number of workers laid off simply due to bad luck is higher in recessions than in booms. In this case, workers laid off during recessions are, on average, less adversely selected than those laid off in booms. Furthermore, if the workers' productivities are not observable to firms then firms draw inferences about the workers' productivities from their past work experience. Since the signaling effect of an unemployment spell varies over the business cycle, so do the wage losses associated with unemployment.
Section snippets
Model
Consider the following simple model of unemployment over the business cycle. The model consists of firms and workers. There are two unobservable types: good and bad. Only “good” type workers contribute to production. The population fraction of good types is given by θ. The total amount of labor available in the economy is normalized to 1.
Firms produce according to the production function,
where Lt denotes the “productive” labor employed by the firm (defined below), and At is an
Wage change regressions
I estimate a linear regression model of the form,where ▵ log(wi) is the difference in the individual's real wage before, α and β are vectors of parameters, x is a vector of other covariates, and u is the state-level unemployment at the approximate time of the job displacement, and is ε an error term. This type of specification is also used, for example, in Gibbons and Katz (1991). This specification has the advantage, relative to a specification in levels, that person-specific
Conclusion
This paper shows that in a model with unemployment due to bad luck as well as selection, the composition of displaced workers varies over the business cycle, and presents some empirical evidence supporting this claim. As in Gibbons and Katz (1991), it is difficult to know whether the effect is associated with signaling or adverse selection. The workers may receive lower wages because firms take previous unemployment as a signal of low ability or simply because the firms observe that the workers
Acknowledgements
I would like to thank Daron Acemoglu, Josh Angrist, Larry Katz, Jón Steinsson and an anonymous referee for helpful discussions and comments.
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