Extended Unemployment Benefits and the Hazard to Employment [Working Paper] [Slides]
Previous studies estimating the effect of generosity of unemployment insurance (UI) on unemployment duration has found that as job-seekers approach benefit exhaustion the probability of leaving unemployment increases sharply. Such “spikes” in the hazard rate has generally been interpreted as shirking among job-seekers. This, however, has been called into question by (Card et al. 2007b); claiming that these spikes rather reflect flight out of the labor force as benefits run out. Using exogenous variation in the potential duration of UI in Sweden, I estimate the effect of a 30 week extension of UI on duration in unemployment and on UI. Moreover, I investigate whether job-seekers manipulate the hazard to employment is such that it coincides with benefit exhaustion. I find that although increasing potential UI duration by 30 weeks increases actual take up by about 2.7 weeks, overall duration in unemployment and the probability of employment is largely unaffected. Further, I find no evidence of job-seekers timing reemployment such that it coincides with UI benefit exhaustion.
Saved by the LIFO rule? – Effects of Displacement for Individuals at the Margin of Lay-off
This paper takes a novel approach in estimating the effects of involuntary job loss on future earnings, wages and employment. Whereas previous literature has relied on mass lay-off and plant closures for exogenous variation in displacement, thereby comparing workers across firms, I exploit the fact that who is laid off within a downsizing establishment is often determined by strict seniority rules, specifically the last-in-first-out (LIFO) principle. Using matched employer-employee data from Sweden, with detailed information on job start and end dates, in combination with a unique individual level dataset on lay-off notifications, I rank workers according to relative seniority and identify establishment/occupation specific discontinuities in the probability of displacement which I exploit in a regression discontinuity framework. Furthermore, I take advantage of worker heterogeneity in firm specific tenure at lay-off across thresholds to estimate the cost of job loss for different levels of tenure