An Effective Treatment Approach to Difference-in-Differences with General Treatment Patterns

TL;DR

This paper introduces a novel approach for difference-in-differences analysis with complex, non-binary treatment patterns by using effective treatment as a summary, along with robust estimation methods and an R package.

Contribution

It develops a new framework for estimating treatment effects in complex treatment scenarios using effective treatment, enhancing applicability and robustness.

Findings

Effective treatment summarizes complex treatment paths.

Doubly robust estimation methods are proposed.

An R package implementation is provided.

Abstract

We consider a general difference-in-differences model in which the treatment variable of interest may be non-binary and its value may change in each period. It is generally difficult to estimate treatment parameters defined with the potential outcome given the entire path of treatment adoption, because each treatment path may be experienced by only a small number of observations. We propose an alternative approach using the concept of effective treatment, which summarizes the treatment path into an empirically tractable low-dimensional variable, and develop doubly robust identification, estimation, and inference methods. We also provide a companion R software package.