Conditional Randomization Tests for the Specification of Interference Structure

ABSTRACT

This study proposes specification tests for interference structure in causal inference with spillovers. We focus on experimental settings in which the treatment assignment mechanism is known. To test whether a given exposure mapping adequately summarizes the true interference structure, we develop conditional randomization tests by utilizing the hierarchical relationship between the null and alternative exposure mappings. When there are multiple candidate exposure mappings of interest, we propose a sequential specification testing procedure that controls the false discovery rate. Through extensive simulation exercises, we demonstrate that our tests have desirable size properties and satisfactory power. To illustrate the proposed methods, we revisit two existing social network experiments: One on farmers' insurance adoption and another on anti‐conflict education programs.