Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects

By Alberto Abadie. Journal of Economic Literature, 2021

1,195 citations recorded by the source corpus.

Probably because of their interpretability and transparent nature, synthetic controls have become widely applied in empirical research in economics and the social sciences. This article aims to provide practical guidance to researchers employing synthetic control methods. The article starts with an overview and an introduction to synthetic control estimation. The main sections discuss the advantages of the synthetic control framework as a research design, and describe the settings where synthetic controls provide reliable estimates and those where they may fail. The article closes with a discussion of recent extensions, related methods, and avenues for future research. (JEL B41, C32, C54, E23, F15, O47)

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/71aac04dbe2c31b39f6fbdaac10feacb446c9139

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Citations in the corpus

Cluster-robust inference: A guide to empirical practice (2022, methodology): “The “design-based” approach to inference, which is analyzed in detail in Abadie et al. (2017), is conceptually different from the model-based framework.”
What’s trending in difference-in-differences? A synthesis of the recent econometrics literature (2022, background): “Much of the DiD and SC literatures have evolved separately, using different data-generating processes as the baseline (Abadie, 2021).”
Populist Leaders and the Economy (2020, methodology): “Our main empirical tool for this will be the synthetic control method (SCM), proposed by Abadie and Gardeazabel (2003), Abadie, Diamond, and Hainmueller (2010), and Abadie (2021), including recent advances in SCM methods with multiple treated units and staggered treatments.”