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Difference-in-Differences with Interval Data

Author

Listed:
  • Daisuke Kurisu
  • Yuta Okamoto
  • Taisuke Otsu

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).

Suggested Citation

  • Daisuke Kurisu & Yuta Okamoto & Taisuke Otsu, 2025. "Difference-in-Differences with Interval Data," Papers 2512.08759, arXiv.org.
    • Handle: RePEc:arx:papers:2512.08759
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    References listed on IDEAS

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