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

Alberto Abadie, MIT

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Abstract:

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.

Background:

Alberto Abadie is an econometrician and empirical microeconomist, with broad disciplinary interests that span economics, political science and statistics. Professor Abadie received his Ph.D. in Economics from MIT in 1999. Upon graduating, he joined the faculty at the Harvard Kennedy School, where he was promoted to full professor in 2005. He returned to MIT in 2016, where he is Professor of Economics and Associate Director of the Institute for Data, Systems, and Society (IDSS).

His research areas are econometrics, statistics, causal inference, and program evaluation. Professor Abadie’s methodological research focuses on statistical methods to estimate causal effects and, in particular, the effects of public policies, such as labor market, education, and health policy interventions. He is Associate Editor of Econometrica and AER: Insights, and has previously served as Editor of the Review of Economics and Statistics and Associate Editor of the Journal of Business and Economic Statistics. He is a Fellow of the Econometric Society.