The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
The eventstudyr package implements tools for estimating linear panel event study models, following the recommendations in Freyaldenhoven et al. (2021). Includes sup-t bands, testing for key hypotheses, least wiggly path through the Wald region. Allows instrumental variables estimation following Freyaldenhoven et al. (2019).
# Install from CRAN
install.packages("eventstudyr")
# Install latest version from GitHub
install.packages("devtools")
devtools::install_github("JMSLab/eventstudyr")Find a minimal example below. For more examples see the package documentation and vignette.
library(eventstudyr)
set.seed(10) # for reproducibility of sup-t bands
estimates_ols <- EventStudy(
estimator = "OLS",
data = example_data, # Use package sample data
outcomevar = "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 Panel Event-Study Design.” NBER Working Paper No. 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 at https://github.com/JMSLab/eventstudyr, March 2023.
Thank you to Eliana Sena Sarmiento and Melissa Wu for their excellent work testing and reviewing eventstudyr prior to its public release.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.