A1180
Title: Unobserved heterogeneous spillover effects in instrumental variable models
Authors: Huan Wu - University of North Carolina at Chapel Hill (United States) [presenting]
Abstract: A general framework is developed for identifying causal effects in settings with spillovers, where both outcomes and endogenous treatment decisions are influenced by peers within a known group. The generalized local average controlled spillover and direct effects (LACSEs and LACDEs) are introduced, which extend the local average treatment effect framework to settings with spillovers and establish sufficient conditions for their point identification without restricting the cardinality of the support of instrumental variables. These conditions clarify the necessity of commonly imposed restrictions to achieve point identification with binary instruments in related studies. The marginal controlled spillover and direct effects (MCSEs and MCDEs) are then defined, which naturally extend the marginal treatment effect framework to settings with spillovers and are nonparametrically point identified from continuous variation in instruments. These marginal effects serve as building blocks for a broad class of policy-relevant treatment effects, including some causal spillover parameters in the related literature. Semiparametric and parametric estimators are developed, and an application using Add Health data reveals heterogeneity in education spillovers within best-friend networks.
