This article uses a two-industry model of unemployment duration and job search to estimate rates of transition of displaced workers from unemployment to employment, distinguishing between employment in a worker's previous industry and in other industries. The competing-risks model allows inferences about search strategies to be drawn from data concerning employment outcomes and allows tests of some fundamental implications of search theory. There is evidence that improvements in the prospects for employment in their previous industry induce displaced workers to reduce search intensity or increase reservation wages in other industries.

This study simultaneously estimates the likelihoods that a worker receives advance notice of a plant closing and that a notified worker quits the job before its scheduled end. The author finds that fear of early attrition is a significant determinant of a firm's decision to provide advance notice. Explicit consideration of employer's concerns may significantly improve prediction of advance notice. Copyright 1994 by MIT Press.

The rate of transition from unemployment to re-employment for a sample of displaced workers is estimated using a semiparametric specification which allows the effects of unemployment insurance benefits to vary over time. Three results which would be missed by more restrictive specifications demonstrate the value of this approach: (1) The effects of UI benefits decline and eventually disappear as the date of expiration approaches, (2) Expiration of UI benefits are an inadequate explanation of the spikes commonly observed in nonparametric sample hazard rates for re-employment, (3) UI benefits do not significantly affect the rate at which a displaced worker becomes re-employed in his or her previous industry, but reduce the rate for transitions to other industries. Copyright 1991 by MIT Press.

Workers who lose their jobs can become reemployed either by being recalled to their previous employers or by finding new jobs. Workers' chances for recall should depress their job search intensity, so the rates of exit from unemployment by these two routes should be negatively related. We look for evidence in the PSID data by estimating a semiparametric competing risks model with explicitly related hazards. Our estimates reveal a statistically precise but small negative effect of recall probabilities on the rate of new job finding.

Using data on union certification elections, we estimate the impact of unionization on firms' investment behavior. Employing both a standard q model and an “investment surprises” technique, we find that union certification significantly reduces investment in the year following the election. We find that a winning certification election has, on average, about the same effect on investment in the year following the event as would—given the elasticity measures taken from the public finance literature—a 33 percentage‐point increase in the corporate tax. The magnitude of the response in years further away from the election is less certain.

Observers of Silicon Valley's computer cluster report that employees move rapidly between competing firms, but evidence supporting this claim is scarce. Job-hopping is important in computer clusters because it facilitates the reallocation of talent and resources toward firms with superior innovations. Using new data on labor mobility, we find higher rates of job-hopping for college-educated men in Silicon Valley's computer industry than in computer clusters located out of the state. Mobility rates in other California computer clusters are similar to Silicon Valley's, suggesting some role for features of California law that make noncompete agreements unenforceable. Consistent with our model of innovation, mobility rates outside computer industries are no higher in California than elsewhere.