Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/268034 
Year of Publication: 
2022
Series/Report no.: 
ECONtribute Discussion Paper No. 201
Publisher: 
University of Bonn and University of Cologne, Reinhard Selten Institute (RSI), Bonn and Cologne
Abstract: 
We discuss properties and pitfalls of panel-data event study designs. We derive three main results. First, assuming constant treatment effects before and/or after some event time, also known as binning, is a natural restriction imposed on theoretically infinite effect windows. Binning identifies dynamic treatment effects in the absence of never-treated units and is particularly suitable in case of multiple events. Second, event study designs with binned endpoints and distributed-lag models are numerically identical leading to the same parameter estimates after correct reparametrization. Third, classic dummy variable event study designs can be generalized to models that account for multiple events of different sign and intensity of the treatment, which are common in public and labor economics. We demonstrate the practical relevance of our methodological points in an application studying the effects of unemployment benefit duration on job search effort.
Subjects: 
event study
distributed-lag
applied microeconomics
credibility revolution
JEL: 
C23
C51
H00
J08
Document Type: 
Working Paper

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