Heterogeneous Effects of Endogenous Treatments with Interference and Spillovers in a Large Network

TL;DR

This paper develops a new econometric framework to identify and estimate heterogeneous effects of endogenous treatments in large networks with interference and spillovers, applied to import competition and U.S. labor markets.

Contribution

It introduces a novel approach to model endogenous treatment as an equilibrium outcome considering spillovers, and provides estimation strategies with large-sample properties.

Findings

Negative marginal exposure effects of import competition on local labor markets

Spillovers amplify the effects among treated neighbors and localities with lower import competition

Empirical results rely on the proposed econometric framework for credible inference

Abstract

This paper studies the identification and estimation of heterogeneous effects of an endogenous treatment under interference and spillovers in a large single-network setting. We model endogenous treatment selection as an equilibrium outcome that explicitly accounts for spillovers and derive conditions guaranteeing the existence and uniqueness of this equilibrium. We then identify heterogeneous marginal exposure effects (MEEs), which may vary with both the treatment status of neighboring nodes and unobserved heterogeneity. We develop estimation strategies and establish their large-sample properties. Equipped with these tools, we analyze the heterogeneous effects of import competition on U.S. local labor markets in the presence of interference and spillovers. We find negative MEEs, consistent with the existing literature. However, these effects are amplified by spillovers in the presence of treated neighbors and among localities that tend to select into lower levels of import competition. These additional empirical findings are novel and would not be credibly obtainable without the econometric framework proposed in this paper.