Difference-in-Differences with Interval Data
Econometrics
2025-12-10 v1
Abstract
Difference-in-differences (DID) is one of the most popular tools used to evaluate causal effects of policy interventions. This paper extends the DID methodology to accommodate interval outcomes, which are often encountered in empirical studies using survey or administrative data. We point out that a naive application or extension of the conventional parallel trends assumption may yield uninformative or counterintuitive results, and present a suitable identification strategy, called parallel shifts, which exhibits desirable properties. Practical attractiveness of the proposed method is illustrated by revisiting an influential minimum wage study by Card and Krueger (1994).
Cite
@article{arxiv.2512.08759,
title = {Difference-in-Differences with Interval Data},
author = {Daisuke Kurisu and Yuta Okamoto and Taisuke Otsu},
journal= {arXiv preprint arXiv:2512.08759},
year = {2025}
}