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SSRN Electronic Journal
Article . 2020 . Peer-reviewed
Data sources: Crossref
EconStor
Research . 2020
Data sources: EconStor
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Implementing the Panel Event Study

Authors: Clarke, Damian; Tapia Schythe, Kathya;

Implementing the Panel Event Study

Abstract

Many studies estimate the impact of exposure to some quasiexperimental policy or event using a panel event study design. These models, as a generalized extension of “difference-in-differences” designs or two-way fixed-effects models, allow for dynamic leads and lags to the event of interest to be estimated, while also controlling for fixed factors (often) by area and time. In this article, we discuss the setup of the panel event study design in a range of situations and lay out several practical considerations for its estimation. We describe a command, eventdd, that allows for simple estimation, inference, and visualization of event study models in a range of circumstances. We then provide several examples to illustrate eventdd’s use and flexibility, as well as its interaction with various native Stata commands, and other relevant community-contributed commands such as reghdfe and boottest.

Countries
Chile, Germany
Keywords

C1 - Econometric and Statistical Methods and Methodology: General, C1, C51, Inference, difference-in-differences, C54 - Quantitative Policy Modeling, Difference in differences, C13, C54, visualization, Visualization, inference, estimation, ddc:330, Simulation Modeling, C13 - Estimation: General, C63, C63 - Computational Techniques, Event studies, event studies, C87 - Econometric Software, Estimation, C87, C51 - Model Construction and Estimation

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    158
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
158
Top 1%
Top 10%
Top 1%
Green
bronze