This study considers testing the specification of spillover effects in causal inference. We focus on experimental settings in which the treatment assignment mechanism is known to researchers and develop a new randomization test utilizing a hierarchical relationship between different exposures. Compared with existing approaches, our approach is essentially applicable to any null exposure specifications and produces powerful test statistics without a priori knowledge of the true interference structure. As empirical illustrations, we revisit two existing social network experiments: one on farmers' insurance adoption and the other on anti-conflict education programs.
翻译:本研究考虑在因果推断中测试外溢效应的规格。我们侧重于研究人员了解治疗分配机制的实验环境,并利用不同照射之间的等级关系开发一种新的随机化测试。与现有方法相比,我们的方法基本上适用于任何无效暴露规格,并在没有事先了解真实干扰结构的情况下生成强有力的测试统计数据。作为经验性说明,我们重新审视了两个现有的社会网络实验:一个是关于农民保险的采用,另一个是关于对抗冲突的教育方案。