Synthetic Difference-In-Differences Estimation With Staggered Treatment Timing

12 Pages Posted: 28 Jan 2022 Last revised: 23 Aug 2022

Date Written: January 24, 2022


This note formalizes the synthetic difference-in-differences estimator for staggered treatment adoption settings, as briefly described in Arkhangelsky et al. (2021). To illustrate the importance of this estimator, I use replication data from Abrams (2012). I compare the estimators obtained using SynthDiD, TWFE, the group time average treatment effect estimator of Callaway and Sant'Anna (2021), and the partially pooled synthetic control method estimator of Ben-Michael et al. (2021) in a staggered treatment adoption setting. I find that in this staggered treatment setting, SynthDiD provides a numerically different estimate of the average treatment effect. Simulation results show that these differences may be attributable to the underlying data generating process more closely mirroring that of the latent factor model assumed for SynthDiD than that of additive fixed effects assumed under traditional difference-in-differences frameworks.

Keywords: econometrics, difference-in-differences, synthetic control method, staggered treatment

JEL Classification: C01, C1, C18, C5, C54

Suggested Citation

Porreca, Zachary, Synthetic Difference-In-Differences Estimation With Staggered Treatment Timing (January 24, 2022). Available at SSRN: or

Zachary Porreca (Contact Author)

Bocconi University ( email )

Via Sarfatti, 25
Milan, MI 20136

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