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Synthetic Difference-In-Differences Estimation With Staggered Treatment Timing

SSRN Electronic Journal
2022
  • 10
    Citations
  • 4,651
    Usage
  • 5
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    10
    • Citation Indexes
      10
  • Usage
    4,651
    • Abstract Views
      3,497
    • Downloads
      1,154
  • Captures
    5
  • Ratings
    • Download Rank
      37,471

Article Description

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.

Bibliographic Details

Zachary Porreca

Elsevier BV

econometrics; difference-in-differences; synthetic control method; staggered treatment

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