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The Econometric Society 2022 Annual Report of the President
2022 Election of Fellows to the Econometric Society
The Econometric Society Annual Reports Report of the Treasurer
The Econometric Society Annual Reports Econometrica Referees 2021–2022
The Econometric Society Annual Reports Report of the Secretary
The Econometric Society Annual Reports Report of the Editors of the Monograph Series
Submission of Manuscripts to the Econometric Society Monograph Series
The Econometric Society Annual Reports Report of the Editors 2021–2022
Synthetic Control as Online Linear Regression
This paper notes a simple connection between synthetic control and online learning. Specifically, we recognize synthetic control as an instance of Follow‐The‐Leader (FTL). Standard results in online convex optimization then imply that, even when outcomes are chosen by an adversary, synthetic control predictions of counterfactual outcomes for the treated unit perform almost as well as an oracle weighted average of control units' outcomes. Synthetic control on differenced data performs almost as well as oracle weighted difference‐in‐differences, potentially making it an attractive choice in practice. We argue that this observation further supports the use of synthetic control estimators in comparative case studies.