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Synthetic Controls with Imperfect Pre-Treatment Fit

Bruno Ferman, Cristine Pinto

arXiv 19 Nov 2019 · Econometrics

arXiv:1911.08521 · PDF · Extracted main text

Abstract

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 substantially 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.

Citation extraction

42
references
119
in-text mentions
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distinct cited
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Doudchenko and Imbens (2016) Balancing, regression, difference-in-differences and synthetic control methods: A synthesis1.00053100%
2Abadie, Diamond and Hainmueller (2010) Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program0.98523596%
3Abadie, Diamond and Hainmueller (2015) Comparative Politics and the Synthetic Control Method0.92843100%
4Ferman (2019) On the Properties of the Synthetic Control Estimator with Many Periods and Many Controls self0.9209478%
5Hsiao, Steve Ching and Ki Wan (2012) A Panel Data Approach for Program Evaluation: Measuring the Benefits of Political and Economic Integration of Hong Kong with Mai…0.8947371%
6Abadie and Gardeazabal (2003) The Economic Costs of Conflict: A Case Study of the Basque Country0.87472100%
7Carvalho, Masini and Medeiros (2018) ArCo: An Artificial Counterfactual Approach for Aggregate Data0.7375340%
8Li and Bell (2017) Estimation of average treatment effects with panel data: Asymptotic theory and implementation0.7375340%
9Carvalho, Masini and Medeiros (2016) The Perils of Counterfactual Analysis with Integrated Processes0.7374350%
10Ferman and Pinto (2019) Synthetic Controls with Imperfect Pre-Treatment Fit0.7374350%

Showing the top 10 of 42 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1The Augmented Synthetic Control Method1.00054
2Using Multiple Outcomes to Improve the Synthetic Control Method1.00053
3On the Properties of the Synthetic Control Estimator with Many Periods and Many Controls0.965105
4Synthetic Difference in Differences0.92843
5Temporal Aggregation for the Synthetic Control Method0.84333
6Synthetic Controls with Staggered Adoption0.73732
7Matrix Completion Methods for Causal Panel Data Models0.64422
8An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls0.40511
9Matching Estimators with Few Treated and Many Control Observations0.40511
10Prediction Intervals for Synthetic Control Methods0.40511