Treatment effects and panel data

Michael Lechner

No 1314, Economics Working Paper Series from University of St. Gallen, School of Economics and Political Science

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.

Keywords: Matching; instrumental variables; local average treatment effects; difference-in-difference estimation; dynamic treatment effects (search for similar items in EconPapers)
JEL-codes: C22 C23 C32 C33 (search for similar items in EconPapers)
Pages: 42 pages
Date: 2013-06
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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