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Treatment and Spillover Effects Under Network Interference

Michael P. Leung

University of Southern California

The Review of Economics and Statistics 2020

We study nonparametric and regression estimators of treatment and spillover effects when interference is mediated by a network. Inference is nonstandard due to dependence induced by treatment spillovers and network-correlated effects. We derive restrictions on the network degree distribution under which the estimators are consistent and asymptotically normal and show they can be verified under a strategic model of network formation. We also construct consistent variance estimators robust to heteroskedasticity and network dependence. Our results allow for the estimation of spillover effects using data from only a single, possibly sampled, network.

DOI
10.1162/rest_a_00818
Volume
102 (2)
Pages
368-380
Language
en
Export
BibTeX
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