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(Empirical) Bayes Approaches to Parallel Trends

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  • Soonwoo Kwon
  • Jonathan Roth

Abstract

We consider Bayes and Empirical Bayes (EB) approaches for dealing with violations of parallel trends. In the Bayes approach, the researcher specifies a prior over both the pretreatment violations of parallel trends δpre and the posttreatment violations δpost. The researcher then updates their posterior about the posttreatment bias δpost given an estimate of the pre-trends δpre. This allows them to form posterior means and credible sets for the treatment effect of interest, δpost. In the EB approach, the prior on the violations of parallel trends is learned from the pretreatment observations. We illustrate these approaches in two empirical applications.

Suggested Citation

  • Soonwoo Kwon & Jonathan Roth, 2024. "(Empirical) Bayes Approaches to Parallel Trends," AEA Papers and Proceedings, American Economic Association, vol. 114, pages 606-609, May.
    • Handle: RePEc:aea:apandp:v:114:y:2024:p:606-09
    DOI: 10.1257/pandp.20241048
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    1. Charles F. Manski & John V. Pepper, 2018. "How Do Right-to-Carry Laws Affect Crime Rates? Coping with Ambiguity Using Bounded-Variation Assumptions," The Review of Economics and Statistics, MIT Press, vol. 100(2), pages 232-244, May.
    2. Roth, Jonathan & Sant’Anna, Pedro H.C. & Bilinski, Alyssa & Poe, John, 2023. "What’s trending in difference-in-differences? A synthesis of the recent econometrics literature," Journal of Econometrics, Elsevier, vol. 235(2), pages 2218-2244.
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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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