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Treatment effects and panel data

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  • Lechner, Michael

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Abstract

It is a major achievement of the econometric treatment effect literature to clarify under which conditions causal effects are non-parametrically identified. The first part of this chapter focuses on the static treatment model. In this part, I show how panel data can be used to improve the credibility of matching and instrumental variable estimators. In practice, these gains come mainly from the availability of outcome variables measured prior to treatment. Such outcome variables also foster the use of alternative identification strategies, in particular so-called difference-in-difference estimation. In addition to improving the credibility of static causal models, panel data may allow credibly estimating dynamic causal models, which is the main theme of the second part of this chapter.

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Bibliographic Info

Paper provided by University of St. Gallen, School of Economics and Political Science in its series Economics Working Paper Series with number 1314.

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Length: 42 pages
Date of creation: Jun 2013
Date of revision:
Handle: RePEc:usg:econwp:2013:14

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Keywords: Matching; instrumental variables; local average treatment effects; difference-in-difference estimation; dynamic treatment effects;

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  1. Klein, T.J., 2008. "Heterogeneous Treatment Effects: Instrumental Variables Without Monotonicity?," Discussion Paper, Tilburg University, Center for Economic Research 2008-45, Tilburg University, Center for Economic Research.
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