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Estimation of average treatment effects in staggered difference-in-differences designs

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  • Pedro Sant'Anna

    (Vanderbilt University)

Abstract

In this presentation, I discuss the att_gt command, which implements three semiparametric estimators for a family of average treatment-effects parameters in difference-in-differences (DID) setups with multiple time periods discussed in Callaway and Sant’Anna (2020, https://doi.org/10.1016/j.jeconom.2020.12.001). The first estimator models the outcome evolution of the comparison group, the second is a properly reweighted inverse-probability weighted estimator, and the third is a doubly robust estimator that relies on less stringent modeling assumptions. Our implementation allows for the use of different comparison groups (“never-treated” or “not-yet-treated” units) and also allows for limited treatment anticipation. Our inference procedures account for multiple-testing problems. We discuss postestimation approaches that can be used in conjunction with our main implementation. We illustrate the program and provide a simulation study assessing the finite-sample performance of the inference procedures.

Suggested Citation

  • Pedro Sant'Anna, 2021. "Estimation of average treatment effects in staggered difference-in-differences designs," 2021 Stata Conference 13, Stata Users Group.
    • Handle: RePEc:boc:scon21:13
    as

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    File URL: http://fmwww.bc.edu/repec/scon2021/US21_SantAnna.pdf
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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. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    3. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 1-19.
    4. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    5. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    6. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
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