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Learning in a Network Economy

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  • Jie-Shin Lin

Abstract

We model a simple communication network model for the evolution of heterogeneous beliefs in an overlapping generation economy. Each agent gathers information from his contacts and forms an inflation forecast based on this information, using the belief generation procedures. When the actual inflation is realised, an agent is in a position to learn, i.e., adjust his own network strategy and belief. The learning is modelled as an evolving network process, i.e., a network of agents, with non-zero communication costs. Our simulation results suggest that the network economy as a whole acts efficiently in achieving convergence to the Pareto superior equilibrium, in which an agent’s perception of information is through communication and is subject to available resources. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Jie-Shin Lin, 2005. "Learning in a Network Economy," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 59-74, February.
    • Handle: RePEc:kap:compec:v:25:y:2005:i:1:p:59-74
    DOI: 10.1007/s10614-005-6274-9
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