Information shocks and the empirical evaluation of training programs during unemployment spells

Bruno Crépon, Marc Ferracci, Gregory Jolivet, Gerard J. van den Berg*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)

4 Citations (Scopus)
38 Downloads (Pure)

Abstract

We study the role of notifications in the evaluation of training programs for unemployed workers. Using a unique administrative data set containing the dates when information is exchanged between job seekers and caseworkers, we address three questions: Do information shocks, such as notification of future training, have an effect on unemployment duration? What is the joint effect of notification and training programs on unemployment? Can ignoring information shocks lead to a large bias in the estimation of the effect of training programs? We discuss these issues through the lens of a job search model and then conduct an empirical analysis following a “random effects” approach to deal with selectivity. We find that notification has a strong positive effect on the training probability but a negative one on the probability of leaving unemployment. This “attraction” effect highlights the importance of accounting for notifications in the evaluation of active labor market policies.

Original languageEnglish
Pages (from-to)594-616
Number of pages23
JournalJournal of Applied Econometrics
Volume33
Issue number4
DOIs
Publication statusPublished - 1 Jun 2018

Structured keywords

  • ECON Applied Economics

Keywords

  • notification
  • duration analysis
  • program evaluation
  • dynamic treatment assignment
  • unobserved heterogeneity
  • policy evaluation

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