A dynamic model of network formation with strategic interactions  /
König, Michael,2008 active 
Tessone, Claudio J.(Claudio Juan),1974-
Zenou, Yves.
Centre for Economic Policy Research (Great Britain)
London : Centre for Economic Policy Research,
2009.
In order to understand the different characteristics observed in real-world networks, one needs to analyze how and why networks form, the impact of network structure on agents' outcomes, and the evolution of networks over time. For this purpose, we combine a network game introduced by Ballester et al. (2006), where the Nash equilibrium action of each agent is proportional to her Bonacich centrality, with an endogenous network formation process. Links are formed on the basis of agents' centrality while the network is exposed to a volatile environment introducing interruptions in the connections between agents. A remarkable feature of our dynamic network formation process is that, at each period of time, the network is a nested split graph. This graph has very nice mathematical properties and are relatively easy to characterize. We show that there exists a unique stationary network (which is a nested split graph) whose topological properties completely match features exhibited by real-world networks. We also find that there exists a sharp transition in efficiency and network density from highly centralized to decentralized networks.
Labour economics and Public policy.
Title from cover.
In order to understand the different characteristics observed in real-world networks, one needs to analyze how and why networks form, the impact of network structure on agents' outcomes, and the evolution of networks over time. For this purpose, we combine a network game introduced by Ballester et al. (2006), where the Nash equilibrium action of each agent is proportional to her Bonacich centrality, with an endogenous network formation process. Links are formed on the basis of agents' centrality while the network is exposed to a volatile environment introducing interruptions in the connections between agents. A remarkable feature of our dynamic network formation process is that, at each period of time, the network is a nested split graph. This graph has very nice mathematical properties and are relatively easy to characterize. We show that there exists a unique stationary network (which is a nested split graph) whose topological properties completely match features exhibited by real-world networks. We also find that there exists a sharp transition in efficiency and network density from highly centralized to decentralized networks.