Testing for Equivalence of Pre-Trends in Difference-in-Differences Estimation

Holger Dette, Martin Schumann*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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.
Original languageEnglish
Pages (from-to)1289-1301
Number of pages13
JournalJournal of Business & Economic Statistics
Volume42
Issue number4
Early online date26 Feb 2024
DOIs
Publication statusPublished - 2024

Keywords

  • Bootstrap/resampling
  • Difference-in-Differences
  • Mathematical statistics
  • Regression
  • Simulation

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