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Treatment and Spillover Effects Under Network Interference

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  • Michael P. Leung

    (University of Southern California)

Abstract

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.

Suggested Citation

  • Michael P. Leung, 2020. "Treatment and Spillover Effects Under Network Interference," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 368-380, May.
    • Handle: RePEc:tpr:restat:v:102:y:2020:i:2:p:368-380
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    References listed on IDEAS

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