Changes-In-Changes For Discrete Treatment

TL;DR

This paper extends the changes-in-changes (CIC) model to handle multiple discrete treatment categories, enabling more accurate analysis in settings with multi-level treatments, which was not possible with the original binary-focused model.

Contribution

The paper introduces a generalized CIC model that incorporates multiple treatment levels using a rank invariance assumption, filling a gap in existing econometric methods.

Findings

Enables analysis of multi-category discrete treatments in CIC framework

Maintains robustness with a generalized rank invariance assumption

Extends CIC applicability beyond binary and continuous treatments

Abstract

This paper generalizes the changes-in-changes (CIC) model to handle discrete treatments with more than two categories, extending the binary case of Athey and Imbens (2006). While the original CIC model is well-suited for binary treatments, it cannot accommodate multi-category discrete treatments often found in economic and policy settings. Although recent work has extended CIC to continuous treatments, there remains a gap for multi-category discrete treatments. I introduce a generalized CIC model that adapts the rank invariance assumption to multiple treatment levels, allowing for robust modeling while capturing the distinct effects of varying treatment intensities.