The {fetwfe} package implements fused extended two-way fixed effects (FETWFE), a methodology for estimating treatment effects in difference-in-differences with staggered adoptions.

• For a brief introduction to the methodology, as well as background on difference-in-differences with staggered adoptions and motivation for FETWFE, see this blog post.
• For more detailed slides on the methodology (but less detailed than the paper), see here.
• Check out the most recent draft of the full paper here.
• This blog post explains a little more about what the package does under the hood, if you're interested.

fetwfePackage

To install the {fetwfe} package, simply use

install.packages("fetwfe")

You can also install the latest development version by using

# install.packages("remotes")  # if needed
remotes::install_github("gregfaletto/fetwfePackage")

The primary function in the {fetwfe} is fetwfe(), which implements fused extended two-way fixed effects. Here's some example code applying fetwfe() to the castle data set from the bacondecomp package:

library(fetwfe)
library(bacondecomp)
data(castle)
# Response: the log homicide rate. Treatment: `cdl` records the share of
# the year the castle-doctrine law was in effect, so `cdl > 0` gives the
# absorbing 0/1 treatment indicator `fetwfe()` requires.
castle$l_homicide <- log(castle$homicide)
castle$treated <- as.integer(castle$cdl > 0)
res <- fetwfe(
    pdata = castle,
    time_var = "year",
    unit_var = "state",
    treatment = "treated",
    response = "l_homicide",
    verbose = TRUE)
summary(res)

For vignettes and full documentation, check out the page for the {fetwfe} package on CRAN.

References

• Faletto, G (2025). Fused Extended Two-Way Fixed Effects for Difference-in-Differences with Staggered Adoptions. arXiv preprint arXiv:2312.05985.