A Network Formation Model Based on Subgraphs

101 Pages Posted: 9 Oct 2015 Last revised: 10 Jul 2018

See all articles by Arun G. Chandrasekhar

Arun G. Chandrasekhar

Stanford University - Department of Economics

Matthew O. Jackson

Stanford University - Department of Economics; Santa Fe Institute; Canadian Institute for Advanced Research (CIFAR)

Date Written: November 1, 2016

Abstract

We develop a new class of random-graph models for the statistical estimation of network formation that allow for substantial correlation in links. Various subgraphs (e.g., links, triangles, cliques, and stars) are generated and their union results in a network. We provide estimation techniques for recovering the rates at which the underlying subgraphs were formed. We illustrate the models via a series of applications including testing for incentives to form cross-caste relationships in rural India, testing to see whether network structure is used to enforce risk-sharing, testing as to whether networks change in response to a community's exposure to microcredit, and show that these models significantly outperform stochastic block models in matching observed network characteristics. We also establish asymptotic properties of the models and various estimators, which requires proving a new Central Limit Theorem for correlated random variables.

Keywords: Subgraphs, Random Networks, Random Graphs, Exponential Random Graph Models, Exponential Family, Social Networks, Network Formation, Consistency, Sparse Networks

JEL Classification: D85, C51, C01, Z13

Suggested Citation

Chandrasekhar, Arun G. and Jackson, Matthew O., A Network Formation Model Based on Subgraphs (November 1, 2016). Available at SSRN: https://ssrn.com/abstract=2660381 or http://dx.doi.org/10.2139/ssrn.2660381

Arun G. Chandrasekhar

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States

Matthew O. Jackson (Contact Author)

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States
1-650-723-3544 (Phone)

HOME PAGE: http://www.stanford.edu/~jacksonm

Santa Fe Institute

1399 Hyde Park Road
Santa Fe, NM 87501
United States

Canadian Institute for Advanced Research (CIFAR) ( email )

180 Dundas Street West, Suite 1400
Toronto, Ontario
Canada

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