Layoffs, recalls and experience rating
Julien Albertini and
Xavier Fairise ()
Working Papers from HAL
Abstract:
In the U.S., between 30% and 50% of the unemployment spells end due to the recall of the workers to their last employer. The extensive use of rehiring may amplify labor market fluctuations and may have damaging consequence on the sustainability of the unemployment insurance (UI) system. In order to allocate the UI costs to firms with more volatile employment, the U.S. adopted an experience rating (ER) system. Under the ER system, firms are penalized for their past layoffs through a higher payroll tax in the future. In this paper we investigate the quantitative impact of the ER system on layoffs and recalls. We build a matching model in which heterogeneity in firms' layoffs history give rise to a distribution of tax rates among firms. We present a very detailed data set on firms distribution across tax rate in the U.S. from 1998 to 2016. The model matches a wide spectrum of moments of experience-rated firms distributions found in the data. Our simulations show that experience rating reduces job separations but also recalls in recessions. Unemployment would have been higher, especially in the trough of the Great Recession, in the absence of an experience rating tax.
Keywords: search and matching; layoffs; recalls; experience rating; unemployment insurance (search for similar items in EconPapers)
Date: 2018-09-24
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01879560v1
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Related works:
Working Paper: Layoffs, recalls and experience rating (2018)
Working Paper: Layoffs, Recalls and Experience Rating (2018) 
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