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On Event Study Designs and Distributed-Lag Models: Equivalence, Generalization and Practical Implications

Kurt Schmidheiny () and Sebastian Siegloch ()

No 12079, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: We discuss important features and pitfalls of panel-data event study designs. We derive the following main results: First, event study designs and distributed-lag models are numerically identical leading to the same parameter estimates after correct reparametrization. Second, binning of effect window endpoints allows identification of dynamic treatment effects even when no never-treated units are present. Third, classic dummy variable event study designs can be naturally generalized to models that account for multiple events of different sign and intensity of the treatment, which are particularly interesting for research in labor economics and public finance.

Keywords: event study; distributed-lag; applied microeconomics; credibility revolution (search for similar items in EconPapers)
JEL-codes: C23 C51 H00 J08 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2019-01
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Related works:
Working Paper: On Event Study Designs and Distributed-Lag Models: Equivalence, Generalization and Practical Implications (2019) Downloads
Working Paper: On Event Study Designs and Distributed-Lag Models: Equivalence, Generalization and Practical Implications (2019) Downloads
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