staggeredGMM: GMM Estimation of Treatment Effects Under Staggered Adoption
Estimates cohort-by-time average treatment effects under
staggered treatment adoption by the generalized method of moments.
Three weighting schemes are provided, corresponding to a
pooled stationary covariance, a cohort-specific stationary covariance,
and an unrestricted within-cohort covariance. Optional adjustment for
baseline covariates by outcome regression, and a serial-correlation
robust over-identification test of parallel trends and no
anticipation, are also supported. The methods are described in Arora
and Bijani (2026) <doi:10.2139/ssrn.6558759>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
fixest, MASS, stats, utils |
| Suggests: |
covr, data.table, knitr, rmarkdown, testthat (≥ 3.1.5) |
| Published: |
2026-09-15 |
| DOI: |
10.32614/CRAN.package.staggeredGMM (may not be active yet) |
| Author: |
Rishabh Bijani 
[aut, cre, cph],
Parush Arora
[aut, cph] |
| Maintainer: |
Rishabh Bijani <rishabhbijani at gmail.com> |
| BugReports: |
https://github.com/RishabhBijani/staggeredGMM/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/RishabhBijani/staggeredGMM |
| NeedsCompilation: |
no |
| Citation: |
staggeredGMM citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
staggeredGMM results |
Documentation:
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