Efficient Estimation for Staggered Rollout Designs

Jonathan Roth and Pedro H. C. Sant’Anna

Journal of Political Economy Microeconomics, 2023, vol. 1, issue 4, 669 - 709

Abstract: We study estimation of causal effects in staggered-rollout designs—that is, settings where there is staggered treatment adoption and the timing of treatment is as good as randomly assigned. We derive the most efficient estimator in a class of estimators that nests several popular generalized difference-in-differences methods. A feasible plug-in version of the efficient estimator is asymptotically unbiased, with efficiency (weakly) dominating that of existing approaches. We provide both t-based and permutation-test-based methods for inference. In an application to a training program for police officers, confidence intervals for the proposed estimator are as much as eight times shorter than those for existing approaches.

Date: 2023
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Working Paper: Efficient Estimation for Staggered Rollout Designs (2023)
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