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. We argue that this observation further supports the use of synthetic control estimators in comparative case studies.
翻译:本文指出了合成控制和在线学习之间的简单联系。 具体地说,我们承认合成控制是“ 跟踪领导者”(FTL)的一个实例。 在线连接优化的标准结果意味着,即使结果由对手选择,对被处理单位的反事实结果的合成控制预测几乎也是控制单位结果的甲骨文加权平均值。 对差异数据的合成控制几乎也是“跟踪领导者”(FTL)的一个实例。 我们争辩说,这一观察进一步支持在比较案例研究中使用合成控制估计值。