A Design-Based Perspective on Synthetic Control Methods

Understand

Since their introduction in Abadie and Gardeazabal (2003), Synthetic Control (SC) methods have quickly become one of the leading methods for estimating causal effects in observational studies in settings with panel data.

• Formal discussions often motivate SC methods by the assumption that the potential outcomes were generated by a factor model.
• Here we study SC methods from a design-based perspective, assuming a model for the selection of the treated unit(s) and period(s).
• We show that the standard SC estimator is generally biased under random assignment.