Efficiency and stability in the connections model with heterogeneous nodes
By Norma Olaizola and
Federico Valenciano ()
Journal of Economic Behavior & Organization, 2021, vol. 189, issue C, 490-503
Abstract:
This paper studies the connections model (Jackson and Wolinsky, 1996) when nodes may have different values. It is shown that efficiency is reached by a strongly hierarchical structure that we call strong NSG-networks: Nested Split Graph networks where the hierarchy or ranking of nodes inherent in any such network is consistent with the rank of nodes according to their value, perhaps leaving some of the nodes with the lowest values disconnected. A simple algorithm is provided for calculating these efficient networks. We also introduce a natural extension of pairwise stability assuming that players are allowed to agree on how the cost of each link is split and prove that stability in this sense for connected strong NSG-networks entails efficiency.
Keywords: Networks; Connections model; Heterogeneity; Efficiency; Stability (search for similar items in EconPapers)
JEL-codes: A14 C72 D85 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167268121002870
Full text for ScienceDirect subscribers only
Related works:
Working Paper: Efficiency and stability in the connections model with heterogeneous node (2021) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:189:y:2021:i:c:p:490-503
DOI: 10.1016/j.jebo.2021.06.046
Access Statistics for this article
Journal of Economic Behavior & Organization is currently edited by Houser, D. and Puzzello, D.
More articles in Journal of Economic Behavior & Organization from Elsevier
Bibliographic data for series maintained by Catherine Liu ().