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Self-organization of knowledge economies

Author Info

Listed author(s):
  • Lafond F.D.

    (UNU-MERIT)

Abstract

Suppose that homogenous agents fully consume their time to invent new ideas andlearn 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 downward curvature. For infinite population it converges to the Yule-Simon distribution. The power law is steeper when innovation is high. Diffusion follows S-shaped curves.

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File URL: http://pub.maastrichtuniversity.nl/c00039da-45fd-432a-8b79-77bd81e89610
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Paper provided by United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT) in its series MERIT Working Papers with number 040.

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Date of creation: 2013
Handle: RePEc:unm:unumer:2013040
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Find related papers by 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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  1. Zilibotti, Fabrizio & König, Michael & Lorenz, Jan, 2016. "Innovation vs. imitation and the evolution of productivity distributions," Theoretical Economics, Econometric Society, vol. 11(3), September.
  2. Sen, Amartya, 2001. "Development as Freedom," OUP Catalogue, Oxford University Press, number 9780192893307, April.
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  7. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
  8. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
  9. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
  10. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, Oxford University Press, vol. 108(1), pages 137-156.
  11. Cohen, Wesley M & Levinthal, Daniel A, 1989. "Innovation and Learning: The Two Faces of R&D," Economic Journal, Royal Economic Society, vol. 99(397), pages 569-596, September.
  12. Lafond, Francois, 2012. "Learning and the structure of citation networks," MERIT Working Papers 071, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  13. Stefano Breschi & Francesco Lissoni, 2009. "Mobility of skilled workers and co-invention networks: an anatomy of localized knowledge flows," Journal of Economic Geography, Oxford University Press, vol. 9(4), pages 439-468, July.
  14. Matthew O. Jackson & Brian W. Rogers, 2007. "Meeting Strangers and Friends of Friends: How Random Are Social Networks?," American Economic Review, American Economic Association, vol. 97(3), pages 890-915, June.
  15. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
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