AN ECONOMETRIC MODEL OF NETWORK FORMATION WITH DEGREE HETEROGENEITY

• 成果类型: Article
• 署名作者: Graham, Bryan S.
• 署名单位: University of California System; University of California Berkeley; National Bureau of Economic Research
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA12679
• 发表日期: 2017
• 页码: 1033-1063
• 关键词: nonlinear panel models; social networks; Economic networks; Random graphs

摘要

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, beta(0), 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 {A(i0)}(i=1)(N) 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.