<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>rishabhbijani.r-universe.dev</title><link>https://rishabhbijani.r-universe.dev</link><description>Recent package updates in rishabhbijani</description><generator>R-universe</generator><image><url>https://github.com/rishabhbijani.png</url><title>R packages by rishabhbijani</title><link>https://rishabhbijani.r-universe.dev</link></image><lastBuildDate>Sun, 06 Sep 2026 17:02:57 GMT</lastBuildDate><item><title>[rishabhbijani] staggeredGMM 0.1.0</title><author>rishabhbijani@gmail.com (Rishabh Bijani)</author><description>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)
&lt;doi:10.2139/ssrn.6558759&gt;.</description><link>https://github.com/r-universe/rishabhbijani/actions/runs/38877884967</link><pubDate>Sun, 06 Sep 2026 17:02:57 GMT</pubDate><r:package>staggeredGMM</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://rishabhbijani.r-universe.dev</r:repository><r:upstream>https://github.com/rishabhbijani/staggeredgmm</r:upstream><r:article><r:source>staggeredGMM.Rmd</r:source><r:filename>staggeredGMM.html</r:filename><r:title>Getting started with staggeredGMM</r:title><r:created>2026-07-12 19:30:20</r:created><r:modified>2026-09-06 16:10:48</r:modified></r:article></item></channel></rss>