Abstract
This paper approaches the dynamic analysis of the effects of training programs for the unemployed in West Germany, or in general the effects of sequences of interventions, from a potential outcome perspective. The identifying power of different assumptions concerning the connection between the dynamic selection process and the outcomes of different sequences is discussed. When participation in the particular sequence of programs is decided period by period depending on its success so far, many parameters of interest are no longer identified. Nevertheless, some interesting dynamic forms of the average treatment effect are identified by a sequential randomization assumption. Based on this approach, we present some new results on the effectiveness of West-German training programs.
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Michael Lechner has further affiliations with ZEW, Mannheim, CEPR, London, IZA, Bonn, and PSI, London. Financial support from the Swiss National Science Foundation (grants 4043-058311 and 4045-050673) and the IAB, Nuremberg (grants 6-531A and 6-531A.1), is gratefully acknowledged. We presented previous drafts of this paper at seminars and workshops at the Universities of Cambridge, Juan Carlos III Madrid, Geneva, and Strasbourg, at INSEE–CREST, Paris, at IFAU in Uppsala, at the ESEM in Lausanne, at the EC2 in Louvain-la-Neuve, and at the annual meeting of the econometrics section of the German Economic Association in Rauischholzhausen. We thank participants for helpful comments. We also very much appreciate comments by Bruno Crépon, Bernd Fitzenberger, Guido Imbens, Jim Heckman, and Jeff Smith, as well as by anonymous referees. They helped to improve and simplify a previous version of the paper considerably.
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Lechner, M., Miquel, R. Identification of the effects of dynamic treatments by sequential conditional independence assumptions. Empir Econ 39, 111–137 (2010). https://doi.org/10.1007/s00181-009-0297-3
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DOI: https://doi.org/10.1007/s00181-009-0297-3
Keywords
- Labor market effects of training programs
- Dynamic treatment regimes
- Nonparametric identification
- Causal effects
- Sequential randomization
- Program evaluation
- Treatment effects
- Dynamic matching
- Panel data