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A Flexible, Heterogeneous Treatment Effects Difference-in-Differences Estimator for Repeated Cross-Sections

Author

Listed:
  • Deb, P.;
  • Norton, E.C.;
  • Wooldridge, J.M.;
  • Zabel, J.E.;

Abstract

This paper proposes a method for estimation of effects in difference -in-differences designs in which the start of treatment is staggered over time and treatment effects are heterogeneous by group, time and covariates, and when the data are repeated cross-sections. We show that a linear-in-parameters regression specification with a sufficiently flexible functional form consisting of group-by-time treatment effects, two-way fixed effects, and interaction terms yields consistent estimates of heterogeneous treatment effects under very general conditions. The estimates are efficient and aggregation of treatment effects and inference are straightforward. We illustrate the use of this model with two empirical examples and provide comparisons to other recently derived estimators.

Suggested Citation

  • Deb, P.; & Norton, E.C.; & Wooldridge, J.M.; & Zabel, J.E.;, 2024. "A Flexible, Heterogeneous Treatment Effects Difference-in-Differences Estimator for Repeated Cross-Sections," Health, Econometrics and Data Group (HEDG) Working Papers 24/17, HEDG, c/o Department of Economics, University of York.
    • Handle: RePEc:yor:hectdg:24/17
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    References listed on IDEAS

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    1. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    2. Angélica Meinhofer & Allison Witman & Johanna Catherine Maclean & Yuhua Bao, 2022. "Prenatal substance use policies and newborn health," Health Economics, John Wiley & Sons, Ltd., vol. 31(7), pages 1452-1467, July.
    3. Jeffrey M Wooldridge, 2023. "Simple approaches to nonlinear difference-in-differences with panel data," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 31-66.
    4. Christos Andreas Makridis, 2019. "Do Right-to-Work Laws Work? Evidence on Individuals’ Well-Being and Economic Sentiment," Journal of Law and Economics, University of Chicago Press, vol. 62(4), pages 713-745.
    5. Jonathan Roth, 2022. "Pretest with Caution: Event-Study Estimates after Testing for Parallel Trends," American Economic Review: Insights, American Economic Association, vol. 4(3), pages 305-322, September.
    6. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
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    Citations

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    Cited by:

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    2. Carsten Andersen & Timo Hener, 2026. "How Wind Turbines Affect Communities: Evidence on Health, Productivity, and Residential Sorting," ifo Working Paper Series 423, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    3. Harrington, Emma & Shaffer, Hannah, 2026. "Learning About Police Bias: Prosecutors and Police Before and After Body-Worn Cameras," IZA Discussion Papers 18528, IZA Network @ LISER.
    4. Jeffrey M. Wooldridge, 2025. "Two-way fixed effects, the two-way mundlak regression, and difference-in-differences estimators," Empirical Economics, Springer, vol. 69(5), pages 2545-2587, November.
    5. David Neumark & Emma Wohl, 2026. "Do Higher Tipped Minimum Wages Reduce Race, Ethnic, or Gender Earnings Gaps for Restaurant Workers?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 65(2), pages 176-199, April.

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    Keywords

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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