Tymon Słoczyński

Associate Professor of Economics @BrandeisU, interested in microeconometrics, applied econometrics, causal inference, and economic history.

[Tymon Słoczyński @TymonSloczynski]

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

[Tymon Słoczyński @TymonSloczynski]

@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;)

[Jeffrey Wooldridge @jmwooldridge]

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.

[Brandeis Department of Economics @BrandeisEcon]

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.

[AEA Journals @AEAjournals]

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

[Tymon Słoczyński @TymonSloczynski]

@jondr44 Congratulations, Jon!

[Jonathan Roth @jondr44]

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 🧵.

[Tymon Słoczyński @TymonSloczynski]

@kylefbutts @hannah_denker Congratulations, Kyle!

[Tymon Słoczyński @TymonSloczynski]

Application (unilateral divorce laws → female suicide, 1964–1996): TWFE ≈ –0.6 (ns). ATT estimators ≈ –10.2 (p=0.001) and –5.5 (p=0.138). Internal validity of TWFE ≈ 0 (uniform), rising to ~40–60% with estimated effects. Not very representative here. 13/13

[Tymon Słoczyński @TymonSloczynski]

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

[Tymon Słoczyński @TymonSloczynski]

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