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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.
    • Handle: RePEc:arx:papers:2310.15796
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    File URL: http://arxiv.org/pdf/2310.15796
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    References listed on IDEAS

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    6. Holger Dette & Kevin Kokot & Stanislav Volgushev, 2020. "Testing relevant hypotheses in functional time series via self‐normalization," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 629-660, July.
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