Unemployment Insurance, Recalls and Experience Rating

GATE WP 2014 – April 2020

47 Pages Posted: 28 May 2020

See all articles by Julien Albertini

Julien Albertini

University of Lyon 2

Xavier Fairise

affiliation not provided to SSRN

Anthony Terriau

Université du Maine - Groupe d' Analyse des Itineraires et Niveaux Salariaux (GAINS)

Date Written: April 25, 2020

Abstract

In the US, almost half of unemployment spells end through recall. In this paper, we show that the probability of being recalled is much higher among unemployment benefit recipients than non-recipients. We argue that a large part of the observed difference in recall shares is accounted for by the design of the unemployment insurance financing scheme characterized by an experience rating system. We develop a search and matching model with different unemployment insurance status, endogenous separations, recalls and new hires. We quantify what would have been the labor market under alternative financing scheme. In the absence of the experience rating, the hiring and separations would have been higher in the long run and more volatile. Experience rating system contributes significantly to the difference in recalls between the recipients and the non-recipients.

Keywords: Search and Matching, Layoffs, Recalls, Experience Rating, Unemployment Insurance

JEL Classification: E23, E32, J63, J64, J65

Suggested Citation

Albertini, Julien and Fairise, Xavier and Terriau, Anthony, Unemployment Insurance, Recalls and Experience Rating (April 25, 2020). GATE WP 2014 – April 2020, Available at SSRN: https://ssrn.com/abstract=3589296 or http://dx.doi.org/10.2139/ssrn.3589296

Julien Albertini (Contact Author)

University of Lyon 2 ( email )

Xavier Fairise

affiliation not provided to SSRN

Anthony Terriau

Université du Maine - Groupe d' Analyse des Itineraires et Niveaux Salariaux (GAINS) ( email )

72085 Le Mans Cedex 9
France

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
28
Abstract Views
257
PlumX Metrics