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Information shocks and the empirical evaluation of training programs during unemployment spells
Author(s) -
Crépon Bruno,
Ferracci Marc,
Jolivet Gregory,
Berg Gerard J.
Publication year - 2018
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2621
Subject(s) - unemployment , seekers , set (abstract data type) , training (meteorology) , duration (music) , estimation , demographic economics , economics , computer science , econometrics , labour economics , macroeconomics , political science , art , physics , literature , meteorology , law , programming language , management
Summary 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.