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Dec, 2023
激励感知的合成对照:通过激励式探索实现准确的反事实估计
Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration
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Daniel Ngo, Keegan Harris, Anish Agarwal, Vasilis Syrgkanis, Zhiwei Steven Wu
TL;DR
我们提出了一种在面板数据设置中激励探索的合成控制方法,通过利用信息设计和在线学习的工具,为单位提供适用的干预建议,从而在不需要明确的单位结果重叠假设的情况下获得有效的对照估计。
Abstract
We consider a
panel data
setting in which one observes measurements of units over time, under different interventions. Our focus is on the canonical family of
synthetic control methods
(SCMs) which, after a pre-i
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