I am very happy to announce that my paper, "Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights," is forthcoming in @restatjournal. Below, I explain its contribution & implications for applied work.
https://t.co/00KwcTxenz
1/n
@mk_wronski@Michal_Bilewicz Biblioteka na Harvardzie stara się mieć wszystko lub prawie wszystko, również jeśli chodzi o książki wydane w Polsce po polsku. Więc to, że coś tam jest, o niczym nie świadczy. To dokładnie jak z listą czasopism punktowanych w Polsce;)
I'd like to announce that drlate, a Stata module for doubly robust estimation of the local average treatment effect (LATE) and the local average treatment effect on the treated (LATT), is now available in SSC.
Professor @TymonSloczynski presented his paper, "Quantifying the Internal Validity of Weighted Estimands" (with Alexandre Poirier), at the 2026 Interactions Conference, which was hosted by the Becker Friedman Institute for Economics at the University of Chicago on May 15, 2026.
Forthcoming in the AER: "The Effect of Omitted Variables on the Sign of Regression Coefficients" by Matthew A. Masten and Alexandre Poirier. https://t.co/A8RpcJ3xtE
I’m really excited about this paper! Some of my work has pointed out problems in empirical work, but this one is all about new 🔧s.
If you (or your referees) want to know about the mechanisms by which a treatment affects an outcome, you may be interested. A 🧵.
Revised version out: Quantifying the Internal Validity of Weighted Estimands (w/ Alex Poirier, Georgetown)
We study when weighted estimands such as OLS/2SLS/TWFE can be read as ATEs for a subpopulation, and how big that subpopulation can be.
Link below. 1/13
Example (3 time periods): internal validity is highest when two-thirds of units are treated in the last period – that's when TWFE weights become uniform. 12/13