Free guide by de Chaisemartin's team helps you pick the right DiD estimator
avicgoldfarb · x · 2026-11-03
Clément de Chaisemartin's team launched a free interactive guide, "Which Difference-in-Differences Estimator Should I Use?", for empirical researchers.
The premise: there is no universally best DiD estimator—the right choice depends on your research design and target effect. The guide walks you through questions that characterize your design (binary vs. nonbinary treatment, absorbing vs. reversible, staggered adoption, repeated treatment changes, lagged effects, presence of never-treated or quasi-untreated groups), then points to compatible heterogeneity-robust estimators relying only on no-anticipation and parallel-trends assumptions.
Extras: a Stata command whichDIDshouldIuse that automatically characterizes your design, a design-to-estimator comparison table based on their textbook with commands/packages for pre-trend tests, and ChatDID for follow-up questions.
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