Matching Estimation of Dynamic Treatment Models : Some Practical Issues
Series
Advances in econometrics
ISBN
978-0-7623-1380-8
Type
book section
Date Issued
2008
Author(s)
Editor(s)
Smith, Jeffrey
Vytlacil, Edward
Millimet, Dann
Abstract
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.
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.
Language
English
Keywords
Dynamic treatment regimes
nonparametric identification
causal effects
sequential randomisation
programme evaluation
treatment effects
dynamic matching
panel data
HSG Classification
contribution to scientific community
Refereed
No
Book title
Modelling and Evaluating Treatment Effects in Econometrics
Publisher
Emerald Group Publishing Limited
Publisher place
Bingley
Number
Vol. 21
Start page
289
End page
333
Pages
45
Subject(s)
Eprints ID
55440
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