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On Estimating Multiple Treatment Effects with Regression

Paul Goldsmith-Pinkham, Peter Hull () and Michal Kolesár
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Michal Kolesár: Princeton University

Working Papers from Princeton University. Economics Department.

Abstract: We study the causal interpretation of regressions on multiple dependent treatments and flexible controls. Such regressions are often used to analyze randomized control trials with multiple intervention arms, and to estimate institutional quality (e.g. teacher value-added) with observational data. We show that, unlike with a single binary treatment, these regressions do not generally estimate convex averages of causal effects—even when the treatments are conditionally randomly assigned and the controls fully address omitted variables bias. We discuss different solutions to this issue, and propose as a solution a new class of efficient estimators of weighted average treatment effects.

Keywords: regressions; treatment effect (search for similar items in EconPapers)
JEL-codes: C30 (search for similar items in EconPapers)
Date: 2021-06
New Economics Papers: this item is included in nep-exp
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