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,...
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| Veröffentlicht in: | Modelling and evaluating treatment effects in econometrics |
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
2008
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Tag hinzufügen | Zusammenfassung: | 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. -- Dynamic treatment regimes, nonparametric identification, causal effects, sequential randomisation, programme evaluation, treatment effects, dynamic matching, panel data. |
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| ISBN: | 0762313803 9780762313808 |