The Incidence of Unemployment: Identifying Quit and Layoffs
We analyse what determines the incidence of unemployment among Danish employees by estimation of a logit model for becoming unemployed. Our data is incomplete in the sense that we do not observe whether a transition was caused by the person quitting or being laid off, so we apply the EM-algorithm to this problem. The models are extended to account for the panel data structure of the data set by including random effects. We use exclusion restrictions to identify quits and layoffs. We find many quitters among young and old women but only few among men.
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