Group-Heterogeneous Changes-in-Changes and Distributional Synthetic Controls

TL;DR

This paper introduces new methods for changes-in-changes and distributional synthetic controls that account for group-level heterogeneity, allowing for more flexible and accurate causal inference in complex settings.

Contribution

It extends existing CIC and DSC frameworks to handle heterogeneous groups and different periods, improving their applicability and robustness.

Findings

New CIC method finds control groups with similar unobserved group traits.

DSC method allows control units from different periods with comparable heterogeneity.

Implementation strategies for the proposed methods are briefly discussed.

Abstract

We develop new changes-in-changes (CIC) and distributional synthetic controls (DSC) types of methods when there exists group-level heterogeneity. For CIC, we allow individuals to belong to heterogeneous groups, extending Athey and Imbens (2006) by finding appropriate control groups that share similar group-level unobserved characteristics to the treatment groups. For DSC, we show that the synthetic control units are not necessarily from the same period as in Gunsilius (2023); they may come from different periods in which they have comparable group-level heterogeneity to the treatment group. Implementation of these new methods is briefly discussed.