Peer Effects and Peer Avoidance: Epidemic Diffusion in Coevolving Networks
We study the long-run-emergency of behavioral patterns in dynamic complex networks. Individuals display two kinds of behavior: G("good") or B ("bad"). We assume that agents have an innate tendency towards G, but can also be led towards B though the influence of peer bad behavior. We model the implications of those peer effects as an epidemic process in the standard SIS (Susceptible-Infected-Susceptible) framework. The key novelty of our model is that, unlike in received epidemic literature, the network is taken to change over time within the same time scale as behavior. Specifically, we posit that links connecting two G agents last longer, reflecting the idea that B agents tend to be avoided. The main concern of the paper is to understand the extent to which such biased network turnover may play a significant role in supporting G behavior in a social system. And indeed we find that network coevolution has nontrivial and interesting effects on long-run behavior. This yields fresh insights on the role of (endogenous) peer pressure on the diffusion of (a)social behavior as well as on the traditional study of disease epidemics.
|Date of creation:||2008|
|Date of revision:|
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- Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
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