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Matching Estimation of Dynamic Treatment Models : Some Practical Issues

Lechner and Miquel (2001) approached the causal analysis of sequences of interventions from a potential outcome perspective based on selection on observable type of assumptions (sequential conditional independence assumptions). Lechner (2004) proposed matching estimators for this framework. However, many practical issues that might have substantial consequences for interpretation of the results have not been thoroughly investigated so far. This paper discusses some of these practical issues. The discussion is related to estimates
based on an artificial data set for which the true values of the parameters are known and that shares many features of data that could be used for an empirical dynamic matching analysis.
   
type book chapter (English)
   
keywords Dynamic treatment regimes, nonparametric identification, causal effects, sequential randomisation, programme evaluation, treatment effects, dynamic matching, panel data
   
book title Modelling and Evaluating Treatment Effects in Econometrics
editor Dann Millimet, Jeffrey Smith, Edward Vytlacil
date of appearance 2008
publisher Elsevier
series title Advances in Econometrics (21)
ISBN 9780762313808
page(s) 289-333
citation Lechner, M. (2008). Matching Estimation of Dynamic Treatment Models: Some Practical Issues. In Millimet, D., Smith, J., & Vytlacil, E. (Eds.), Modelling and Evaluating Treatment Effects in Econometrics (pp. 289-333): Elsevier. - ISBN 9780762313808.