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Journal of Labor Economics Vol. 40 No. 4 2022

Name Your Friends, but Only Five? The Importance of Censoring in Peer Effects Estimates Using Social Network Data

Alan Griffith

Abstract

Empirical peer effects research often employs censored peer data. Individuals may list only a fixed number of links, implying mismeasured peer variables. I first document that censoring is widespread in network data. I then introduce an estimator and characterize its inconsistency analytically; an assumption on the ordering of peers implies that censoring causes attenuated peer effects estimates. Next, I demonstrate the effect of censoring in two data sets, showing that estimates with censored data underestimate peer influence. I discuss interpretation of estimates, propose methods for correction and bounding, and give implications for the design of network surveys.

DOI
10.1086/717935
Volume
40
Issue
4
Pages
779-805
Language
en
Sources
openalex crossref

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