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What's Trending in Difference-in-Differences? A Synthesis of the Recent Econometrics Literature

Jonathan Roth, Pedro H. C. Sant'Anna, Alyssa Bilinski, John Poe

arXiv 4 Jan 2022 · Econometrics · publishedJournal of Econometrics (2023) · 1,780 citations (OpenAlex)

arXiv:2201.01194 · PDF · DOI · OpenAlex · Extracted main text

Abstract

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.

Citation extraction

104
references
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in-text mentions
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distinct cited
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main-text words

appendix boundary found by appendix_command · 95% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Callaway and Sant’Anna (2021) Difference-in-Differences with multiple time periods1.000214100%
2Sun and Abraham (2021) Estimating dynamic treatment effects in event studies with heterogeneous treatment effects1.000113100%
3de Chaisemartin and D'Haultfœuille (2020) Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects1.00073100%
4Borusyak, Jaravel and Spiess (2021) Revisiting Event Study Designs: Robust and Efficient Estimation1.00053100%
5Roth and Sant'Anna (2021) Efficient Estimation for Staggered Rollout Designs0.92843100%
6Roth (2022) Pre-test with Caution: Event-study Estimates After Testing for Parallel Trends self0.87472100%
7Rambachan and Roth (2022) A More Credible Approach to Parallel Trends0.87462100%
8Wooldridge (2021) Two-Way Fixed Effects, the Two-Way Mundlak Regression, and Difference-in-Differences Estimators0.81142100%
9Abadie (2005) Semiparametric Difference-in-Differences Estimators0.81142100%
10Goodman-Bacon (2021) Difference-in-differences with variation in treatment timing0.81142100%

Showing the top 10 of 106 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Refining the Notion of No Anticipation in Difference-in-Differences Studies1.000195
2Difference-in-Differences Designs: A Practitioner's Guide1.00063
3Inference with few treated units1.00064
4Causal Models for Longitudinal and Panel Data: A Survey1.00053
5When Can We Use Two-Way Fixed-Effects (TWFE): A Comparison of TWFE and Novel Dynamic Difference-in-Differences Estimators1.00054
6Big Wins, Small Net Gains: Direct and Spillover Effects of First Industry Entries in Puerto Rico1.00055
7Robust Inference for Weighted Estimands1.00053
8Difference-in-Differences with Unpoolable Data0.92843
9Quantitative methods in finance0.87452
10Selection and parallel trends0.84354