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Self-organization of knowledge economies

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  • Lafond, François

Abstract

Suppose that homogeneous agents fully consume their time to invent new ideas and learn ideas from their friends. If the social network is complete and agents pick friends and ideas of friends uniformly at random, the distribution of ideas׳ popularity is an extension of the Yule–Simon distribution. It has a power-law tail, with an upward or a downward curvature. For infinite population it converges to the Yule–Simon distribution. The power law is steeper when innovation is high. Diffusion follows logistic curves.

Suggested Citation

  • Lafond, François, 2015. "Self-organization of knowledge economies," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 150-165.
    • Handle: RePEc:eee:dyncon:v:52:y:2015:i:c:p:150-165
    DOI: 10.1016/j.jedc.2014.12.004
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    2. Mitri Kitti & Matti Pihlava & Hannu Salonen, 2016. "Search in Networks: The Case of Board Interlocks," Discussion Papers 116, Aboa Centre for Economics.
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    5. Cremonini, Marco, 2016. "Introducing serendipity in a social network model of knowledge diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 64-71.

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    More about this item

    Keywords

    Innovation; Diffusion; Two-mode networks; Power law;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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