Synthetic controls with imperfect pretreatment fit

Artikel

We analyze the properties of the Synthetic Control (SC) and related estimators when the pre-treatment fit is imperfect. In this framework, we show that these estimators are generally biased if treatment assignment is correlated with unobserved confounders, even when the number of pre-treatment periods goes to infinity. Still, we show that a demeaned version of the SC method can improve in terms of bias and variance relative to the difference-in-difference estimator. We also derive a specification test for the demeaned SC estimator in this setting with imperfect pre-treatment fit. Given our theoretical results, we provide practical guidance for applied researchers on how to justify the use of such estimators in empirical applications.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 12 ; Year: 2021 ; Issue: 4 ; Pages: 1197-1221 ; New Haven, CT: The Econometric Society

Classification and Topics

• Classification: Wirtschaft ; Estimation: General ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
• Subject: Synthetic control ; difference-in-differences ; policy evaluation ; linearfactor model

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Ferman, Bruno ; Pinto, Cristine Campos de Xavier
• Event: Veröffentlichung
• (who): The Econometric Society
• (where): New Haven, CT
• (when): 2021

Further information

• DOI: doi:10.3982/QE1596
• Handle: http://hdl.handle.net/10419/253607
• Last update: 10.03.2025, 11:43 AM CET