2007
DOI: 10.1257/aer.97.2.92
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Diffusion of Behavior and Equilibrium Properties in Network Games

Abstract: We analyze games on social networks where agents select one of two actions (whether or not to adopt a new technology, withdraw money from the bank, become politically active, etc.). Agents' payoffs from each of the two actions depend on how many neighbors she has, the distribution of actions among her neighbors, and a possibly idiosyncratic cost for each of the actions. We analyze the diffusion of behavior when in each period agents choose a best response to last period's behavior. We characterize how the equi… Show more

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Cited by 264 publications
(193 citation statements)
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References 12 publications
(16 reference statements)
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“…The agent's decision may need to be based on some idea of the overall prevalence of the compatibility of the program with choices of other agents in the population. Galeotti et al (2008) and Jackson and Yariv (2007) examine such settings and show that an incomplete information setting can actually simplify the analysis of games on networks. In particular, results can be derived showing how agents' actions vary with their degree.…”
Section: Peer Interactions and Games On Networkmentioning
confidence: 99%
“…The agent's decision may need to be based on some idea of the overall prevalence of the compatibility of the program with choices of other agents in the population. Galeotti et al (2008) and Jackson and Yariv (2007) examine such settings and show that an incomplete information setting can actually simplify the analysis of games on networks. In particular, results can be derived showing how agents' actions vary with their degree.…”
Section: Peer Interactions and Games On Networkmentioning
confidence: 99%
“…Morris (2000) shows that maximal contagion occurs for sufficiently uniform local interactions and low neighbor growth. Along the same line, Lopez-Pintado (2008) and Jackson and Yariv (2007) look into the role of connectivity in diffusion, finding that stochastically dominant degree distributions to favor diffusion.…”
Section: Related Literaturementioning
confidence: 92%
“…We build high-tech innovation network with mean-field approximation [10][11] [12], with the aim to discuss the heterogeneity of degree distribution on knowledge diffusion. In addition, this article focuses on the overall impact of knowledge diffusion on the high-tech innovation network.…”
Section: Introductionmentioning
confidence: 99%