A0232
Title: Causal inference with noncompliance and unknown interference
Authors: Takahide Yanagi - Kyoto University (Japan) [presenting]
Tadao Hoshino - Waseda University (Japan)
Abstract: The aim is to investigate a treatment effect model in which individuals interact in a social network and they may not comply with the assigned treatments. We introduce a new concept of exposure mapping, which summarizes spillover effects into a fixed dimensional statistic of instrumental variables, and we call this mapping the instrumental exposure mapping (IEM). We investigate identification conditions for the intention-to-treat effect and the average causal effect for compliers, while explicitly considering the possibility of misspecification of IEM. Based on our identification results, we develop nonparametric estimation procedures for the treatment parameters. Their asymptotic properties, including consistency and asymptotic normality, are investigated using an approximate neighborhood interference framework. For an empirical illustration of our proposed method, we revisit experimental data on the anti-conflict intervention school program.
