Discussion on: Instrumented difference-in-differences, by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy and Dylan S. Small

I discuss the assumptions needed for identification of average treatment effects and local average treatment effects in instrumented difference-in-differences (IDID), and the possible trade-offs between assumptions of standard IV and those needed for the new proposal IDID, in one- and two-sample settings. I also discuss the interpretation of the estimands identified under monotonicity. I conclude by suggesting possible extensions to the estimation method, by outlining a strategy to use data-adaptive estimation of the nuisance parameters, based on recent developments.

Automated summary

This article discusses the assumptions necessary for identifying average treatment effects and local average treatment effects in instrumented difference-in-differences (IDID). It also explores the potential trade-offs between the assumptions of standard instrumental variable (IV) methods and those needed for the proposed IDID method in both one- and two-sample settings. Furthermore, the interpretation of estimands identified under the assumption of monotonicity is discussed.