There is increasing interest in allocating treatments based on observed individual characteristics: examples include targeted marketing, individualized credit offers, and heterogeneous pricing. Treatment personalization introduces incentives for individuals to modify their behavior to obtain a better treatment. Strategic behavior shifts the joint distribution of covariates and potential outcomes. The optimal rule without strategic behavior allocates treatments only to those with a positive Conditional Average Treatment Effect. With strategic behavior, we show that the optimal rule can involve randomization, allocating treatments with less than 100% probability even to those who respond positively on average to the treatment. We propose a sequential experiment based on Bayesian Optimization that converges to the optimal treatment rule without parametric assumptions on individual strategic behavior.
翻译:针对观察到的个体特征进行治疗个性化分配越来越受关注:例如有针对性的营销、个性化的信贷选择和异质性定价。治疗个性化分配引入了个体为了获得更好的治疗而改变行为的激励。策略行为改变了协变量和潜在结果的联合分布。没有策略行为时,最优规则只将治疗分配给平均条件治疗效果为正的人。有了策略行为,我们发现最优规则可以涉及随机化,即使对于那些平均情况下对治疗有积极反应的人,治疗也可能被分配不到 100%。我们提出了一种基于贝叶斯优化的顺序实验,它可以在不需要个体策略行为参数假设的情况下收敛到最优的治疗规则。