Synthetic Control as Online Linear Regression

Author:

Chen Jiafeng12

Affiliation:

1. Department of Economics, Harvard University

2. Harvard Business School

Abstract

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.

Funder

National Bureau of Economic Research

Publisher

The Econometric Society

Subject

Economics and Econometrics

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Bounded (O(1)) Regret Recommendation Learning via Synthetic Controls Oracle;2023 59th Annual Allerton Conference on Communication, Control, and Computing (Allerton);2023-09-26

2. The Lasting Effect of Yen-Buying Interventions: Two cases of Japanese FX Interventions in 1997-98 and 2022;SSRN Electronic Journal;2023

3. Par for the Course: Public Information and Stable Coin Runs;SSRN Electronic Journal;2023

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