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Cited by 31Advanced Causal Inference TechniquesSpatial and Panel Data AnalysisEvaluation and Performance Assessment

Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey

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de Chaisemartin, Clément, D'Haultfoeuille, Xavier·2022·National Bureau of Economic Research
DOI 10.3386/w29691
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Abstract

Linear regressions with period and group fixed effects are widely used to estimate policies' effects: 26 of the 100 most cited papers published by the American Economic Review from 2015 to 2019 estimate such regressions.It has recently been show that those regressions may produce misleading estimates, if the policy's effect is heterogeneous between groups or over time, as is often the case.This survey reviews a fast-growing literature that documents this issue, and that proposes alternative estimators robust to heterogeneous effects.

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  • A recent literature has identified problems with difference-in-differences designs that rely on the staggered introduction of a program across groups over time.

    “A recent literature has identified problems with difference-in-differences designs that rely on the staggered introduction of a program across groups over time (see, e.g., Goodman-Bacon, 2021; de Chaisemartin & D'Haultfoeuille, 2022).”

    From College Costs, Financial Aid, and Student Decisions (2022) · cites this paper as de Chaisemartin & D'Haultfoeuille, 2022

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Research works printed but not linked: 26

  1. Bilinski, A. and Hatfield, L. A. (2018), Nothing to see here? non-inferiority approaches to parallel trends and other model assumptions. arXiv preprint arXiv:1805.03273. · arXiv
  2. Borusyak, K., Jaravel, X. and Spiess, J. (2021), Revisiting event study designs: Robust and efficient estimation. arXiv preprint arXiv:2108.12419. · arXiv
  3. Callaway, B., Goodman-Bacon, A. and Sant'Anna, P. H. (2021), Difference-in-differences with a continuous treatment. arXiv preprint arXiv:2107.02637. · arXiv
  4. Callaway, B. and Sant'Anna, P. H. (2021), 'Difference-in-differences with multiple time periods', Journal of Econometrics 225, 200-230.
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  7. de Chaisemartin, C. and D'Haultfœuille, X. (2015), Fuzzy differences-in-differences. ArXiv e- prints, eprint 1510.01757v2.
  8. de Chaisemartin, C. and D'Haultfœuille, X. (2018), 'Fuzzy differences-in-differences', The Review of Economic Studies 85(2), 999-1028.
  9. de Chaisemartin, C. and D'Haultfœuille, X. (2020), 'Two-way fixed effects estimators with het- erogeneous treatment effects', American Economic Review 110(9), 2964-2996.
  10. de Chaisemartin, C. and D'Haultfœuille, X. (2021a), Difference-in-differences estimators of in- tertemporal treatment effects. arXiv preprint arXiv:2007.04267. · arXiv
  11. de Chaisemartin, C. and D'Haultfœuille, X. (2021b), Two-way fixed effects regressions with several treatments. arXiv preprint arXiv:2012.10077. · arXiv
  12. de Chaisemartin, C., D'Haultfoeuille, X., Pasquier, F. and Vazquez-Bare, G. (2022), Difference-in-differences estimators of the effect of a continuous treatment. arXiv preprint arXiv:2201.06898. · arXiv
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  15. Gentzkow, M., Shapiro, J. M. and Sinkinson, M. (2011), 'The effect of newspaper entry and exit on electoral politics', American Economic Review 101(7), 2980-3018.
  16. Gobillon, L. and Magnac, T. (2016), 'Regional policy evaluation: Interactive fixed effects and synthetic controls', Review of Economics and Statistics 98(3), 535-551.
  17. Graham, B. S. and Powell, J. L. (2012), 'Identification and estimation of average partial effects in "irregular" correlated random coefficient panel data models', Econometrica 80(5), 2105-2152.
  18. Jakiela, P. (2021), Simple diagnostics for two-way fixed effects. arXiv preprint arXiv:2103.13229. · arXiv
  19. Kahn-Lang, A. and Lang, K. (2020), 'The promise and pitfalls of differences-in-differences: Reflections on 16 and pregnant and other applications', Journal of Business & Economic Statistics 38(3), 613-620.
  20. Liu, L., Wang, Y. and Xu, Y. (2021), A practical guide to counterfactual estimators for causal inference with time-series cross-sectional data. arXiv preprint arXiv:2107.00856. · arXiv
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  22. Marcus, M. and Sant'Anna, P. H. (2021), 'The role of parallel trends in event study settings: An application to environmental economics.', Journal of the Association of Environmental and Resource Economists 8(2), 235-275.
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Cited by

Sorted by citations

Authors
de Chaisemartin, C., & D'Haultfoeuille, X.
Venue
National Bureau of Economic Research
Publisher
National Bureau of Economic Research
Published
2022-01
DOI
10.3386/w29691
OpenAlex
W4256413215
Cited by
31
References
7
Citations by year
2025: 3 · 2024: 3 · 2023: 19 · 2022: 6
Type
report
Language
en
Open access
Locations
National Bureau of Economic Research (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
Keywords
two-way fixed effects, difference-in-differences, treatment effect heterogeneity, policy evaluation, robust estimators, causal inference

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