1201.4564v2.pdf (316.39 kB)
Homophily and long-run integration in social networks
journal contributionposted on 2013-11-26, 10:32 authored by Yann Bramoullé, Sergio Currarini, Matthew O. Jackson, Paolo Pin, Brian W. Rogers
We model network formation when heterogeneous nodes enter sequentially and form connections through both random meetings and network-based search, but with type-dependent biases. We show that there is “long-run integration”, whereby the composition of types in sufficiently old nodesʼ neighborhoods approaches the global type-distribution, provided that the network-based search is unbiased. However, younger nodesʼ connections still reflect the biased meetings process. We derive the type-based degree distributions and group-level homophily patterns when there are two types and location-based biases. Finally, we illustrate aspects of the model with an empirical application to data on citations in physics journals.
We gratefully acknowledge financial support from the NSF under grant SES-0961481.
CitationJournal of Economic Theory, 2012, 147 (5), pp. 1754-1786
Author affiliation/Organisation/COLLEGE OF SOCIAL SCIENCE/Department of Economics
- AM (Accepted Manuscript)