What’s trending in difference-in-differences? A synthesis of the recent econometrics literature
By Jonathan Roth, Pedro H. C. Sant’Anna, A. Bilinski, John Poe. Journal of Econometrics, 2022
1,521 citations recorded by the source corpus.
This paper synthesizes recent advances in the econometrics of difference-in-differences (DiD) and provides concrete recommendations for practitioners. We begin by articulating a simple set of ``canonical'' assumptions under which the econometrics of DiD are well-understood. We then argue that recent advances in DiD methods can be broadly classified as relaxing some components of the canonical DiD setup, with a focus on $(i)$ multiple periods and variation in treatment timing, $(ii)$ potential violations of parallel trends, or $(iii)$ alternative frameworks for inference. Our discussion highlights the different ways that the DiD literature has advanced beyond the canonical model, and helps to clarify when each of the papers will be relevant for empirical work. We conclude by discussing some promising areas for future research.
Subfields: Economics and Econometrics, Education, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/327d5280c3086f801187f1309321672bdbf9214b
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Citations in the corpus
- Contamination Bias in Linear Regressions (2021, neutral): “See Roth et al. (2022) for a recent review of the literature.”
- Assessing the Effectiveness of Energy Efficiency Measures in the Residential Sector Gas Consumption Through Dynamic Treatment Effects: Evidence from England and Wales (2022, background): “…these quasi-experimental design as they assume that the treatment effect is constant, between groups and overtime (de Chaisemartin and D ’ Haultfoeuill, 2020; de Chaisemartin and d ’ Haultfoeuille, 2021; Callaway and Sant ’ Anna, 2021; Sun and Abraham, 2021; Roth et al., 2022; Goodman-Bacon, 2021).”