Efficient Estimation for Staggered Rollout Designs

Event Date: 6 October 2021

Speaker: Jonathan Roth, assistant professor in the economics department at Brown University

Time: 4 pm

Please contact Rachel Hill (r.hill@strath.ac.uk) for Zoom details.

Abstract:

This paper studies efficient estimation of causal effects when treatment is (quasi-) randomly rolled out to units at different points in time. We solve for the most efficient estimator in a class of estimators that nests two-way fixed effects models and other 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. We illustrate the performance of the plug-in efficient estimator in simulations and in an application to Wood et al. (2020a)'s study of the staggered rollout of a procedural justice training program for police officers. We find that confidence intervals based on the plug-in efficient estimator have good coverage and can be as much as five times shorter than confidence intervals based on existing state-of-the-art methods. As an empirical contribution of independent interest, our application provides the most precise estimates to date on the effectiveness of procedural justice training programs for police officers.

If you would like to read the full paper, please click here.

Published: 5 October 2021