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Theeventstudyr package implements tools for estimating linear panelevent study models, following the recommendations inFreyaldenhoven etal. (2021). Includes sup-t bands,testing for key hypotheses, least wiggly path through the Wald region.Allows instrumental variables estimation followingFreyaldenhoven etal. (2019).

# Install from CRANinstall.packages("eventstudyr")# Install latest version from GitHubinstall.packages("devtools")devtools::install_github("JMSLab/eventstudyr")

Find a minimal example below. For more examples see the packagedocumentationandvignette.

library(eventstudyr)set.seed(10)# for reproducibility of sup-t bandsestimates_ols<- EventStudy(estimator="OLS",data=example_data,# Use package sample dataoutcomevar="y_smooth_m",policyvar="z",idvar="id",timevar="t",controls="x_r",pre=0,post=4)plt<- EventStudyPlot(estimates=estimates_ols)plt

Simon Freyaldenhoven, Christian Hansen, Jorge Pérez Pérez, and Jesse M.Shapiro. “Visualization, Identification, and Estimation in the PanelEvent-Study Design.”NBER Working PaperNo. 29170, August 2021.

Simon Freyaldenhoven, Christian Hansen, Jorge Pérez Pérez, Jesse M.Shapiro, Veli M. Andirin, Richard Calvo, Santiago Hermo, Nathan Schor,Emily Wang. “eventstudyr package.” Code and data repository athttps://github.com/JMSLab/eventstudyr, March 2023.

Thank you to Eliana Sena Sarmiento and Melissa Wu for their excellentwork testing and reviewingeventstudyr prior to its public release.