Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/35485
Authors: 
Crépon, Bruno
Ferracci, Marc
Jolivet, Grégory
van den Berg, Gerard J.
Year of Publication: 
2008
Series/Report no.: 
IZA discussion papers 3848
Abstract: 
This paper implements a method to identify and estimate treatment effects in a dynamic setting where treatments may occur at any point in time. By relating the standard matching approach to the timing-of-events approach, it demonstrates that effects of the treatment on the treated at a given date can be identified even though non-treated may be treated later in time. The approach builds on a no anticipation assumption and the assumption of conditional independence between the duration until treatment and the counterfactual durations until exit. To illustrate the approach, the paper studies the effect of training for unemployed workers in France, using a rich register data set. Training has little impact on unemployment duration. The contamination of the standard matching estimator due to later entries into treatment is large if the treatment probability is high.
Subjects: 
Treatment
program participation
unemployment duration
training
propensity score
matching
contamination bias
JEL: 
J64
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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