论文标题
社会互动下的统计治疗规则
Statistical Treatment Rules under Social Interaction
论文作者
论文摘要
在本文中，我们在存在社会互动的情况下研究治疗分配规则。我们在匿名相互作用假设下构建一个分析框架，在该假设中，决策问题开始选择治疗部分。我们提出了一项多项式经验成功（MES）规则，其中包括曼斯基（Manski）（2004）作为特殊情况。我们根据MES规则研究了预期效用的非质合界。最后，我们证明，MES规则以Minimax后悔标准实现了渐近的最优性。
In this paper we study treatment assignment rules in the presence of social interaction. We construct an analytical framework under the anonymous interaction assumption, where the decision problem becomes choosing a treatment fraction. We propose a multinomial empirical success (MES) rule that includes the empirical success rule of Manski (2004) as a special case. We investigate the non-asymptotic bounds of the expected utility based on the MES rule. Finally, we prove that the MES rule achieves the asymptotic optimality with the minimax regret criterion.
