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Testing for equivalence of pre-trends in Difference-in-Differences estimation

Author

Listed:
  • Holger Dette

    (Ruhr University Bochum)

  • Martin Schumann

    (Maastricht University)

Abstract

The plausibility of the ``parallel trends assumption'' in Difference-in-Differences estimation is usually assessed by a test of the null hypothesis that the difference between the average outcomes of both groups is constant over time before the treatment. However, failure to reject the null hypothesis does not imply the absence of differences in time trends between both groups. We provide equivalence tests that allow researchers to find evidence in favor of the parallel trends assumption and thus increase the credibility of their treatment effect estimates. While we motivate our tests in the standard two-way fixed effects model, we discuss simple extensions to settings in which treatment adoption is staggered over time.

Suggested Citation

  • Holger Dette & Martin Schumann, 2023. "Testing for equivalence of pre-trends in Difference-in-Differences estimation," Papers 2310.15796, arXiv.org, revised Dec 2025.
    • Handle: RePEc:arx:papers:2310.15796
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    References listed on IDEAS

    as
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    3. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
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    6. Badi H. Baltagi, 2021. "The Two-Way Error Component Regression Model," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 47-74, Springer.
    7. Rafael Di Tella & Ernesto Schargrodsky, 2004. "Do Police Reduce Crime? Estimates Using the Allocation of Police Forces After a Terrorist Attack," American Economic Review, American Economic Association, vol. 94(1), pages 115-133, March.
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