An econometric model of network formation with degree heterogeneity

Bryan Graham

No CWP08/17, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: I introduce a model of undirected dyadic link formation which allows for assortative matching on observed agent characteristics (homophily) as well as unrestricted agent level heterogeneity in link surplus (degree heterogeneity). Like in fixed effects panel data analyses, the joint distribution of observed and unobserved agent-level characteristics is left unrestricted. Two estimators for the (common) homophily parameter, ß0 , are developed and their properties studied under an asymptotic sequence involving a single network growing large. The first, tetrad logit (TL), estimator conditions on a sufficient statistic for the degree heterogeneity. The second, joint maximum likelihood (JML), estimator treats the degree heterogeneity {Ai0}Ni=1 as additional (incidental) parameters to be estimated. The TL estimate is consistent under both sparse and dense graph sequences, whereas consistency of the JML estimate is shown only under dense graph sequences. Supplement for CWP 08/17

Keywords: Network formation; homophily; degree heterogeneity; scale-free networks; incidental parameters; asymptotic bias; fixed effects; conditional likelihood; dependent U-Process (search for similar items in EconPapers)
JEL-codes: C31 C33 C35 (search for similar items in EconPapers)
Date: 2017-02-10
New Economics Papers: this item is included in nep-dcm, nep-ecm, nep-net and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (120)

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Related works:
Journal Article: An Econometric Model of Network Formation With Degree Heterogeneity (2017)
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