Synthetic Control Method: A Tool for Comparative Case Studies in Economic History

David Gilchrist, Thomas Emery, Nuno Garoupa, Rok Spruk

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The Synthetic Control Method (SCM) has become a widely used tool in both identifying and estimating the causal impact of policies, shocks and interventions of interest on economic and social outcomes. The technique has become particularly popular in estimating the effect of these shocks on a single treated unit. As a transparent and data-driven statistical technique, the goal of the SCM is to construct an artificial control group for the treated unit that has similar pre-treatment characteristics but has not undergone the treatment itself thus developing a plausible counter factual against which impacts resulting from structural changes can be evaluated as part of an historical investigation. The Method works well when the control group balances pre-intervention outcomes and auxiliary covariates as much as possible. In spite of its widespread adoption, the use of the SCM in comparative economic history has lagged behind other areas of economics. In this article, we critically review the properties of the SCM and discuss the necessary conditions for a plausible application of the technique to comparative economic history in support of research designed to answer some of the long-running historical questions and demonstrate the potential to use SCM in comparative economic history studies by estimating the impact of oil discovery in 1920s on Venezuela’s long-term economic growth.
Original languageEnglish
JournalJournal of Economic Surveys
Publication statusE-pub ahead of print - 11 Feb 2022


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