Artikel
Synthetic controls with imperfect pretreatment fit
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.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 12 ; Year: 2021 ; Issue: 4 ; Pages: 1197-1221 ; New Haven, CT: The Econometric Society
- Klassifikation
-
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
- Thema
-
Synthetic control
difference-in-differences
policy evaluation
linearfactor model
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Ferman, Bruno
Pinto, Cristine Campos de Xavier
- Ereignis
-
Veröffentlichung
- (wer)
-
The Econometric Society
- (wo)
-
New Haven, CT
- (wann)
-
2021
- DOI
-
doi:10.3982/QE1596
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Ferman, Bruno
- Pinto, Cristine Campos de Xavier
- The Econometric Society
Entstanden
- 2021
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