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Self-organization of knowledge economies

  • Lafond, Francois

    ()

    (UNU-MERIT / MGSoG)

Suppose that homogenous 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 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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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
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Handle: RePEc:unm:unumer:2013040
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  1. 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.
  2. Cowan, Robin & Jonard, Nicolas, 2004. "Network structure and the diffusion of knowledge," Journal of Economic Dynamics and Control, Elsevier, vol. 28(8), pages 1557-1575, June.
  3. Paul M Romer, 1999. "Endogenous Technological Change," Levine's Working Paper Archive 2135, David K. Levine.
  4. Sen, Amartya, 2001. "Development as Freedom," OUP Catalogue, Oxford University Press, number 9780192893307, March.
  5. 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.
  6. 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).
  7. Geroski, Paul A, 1999. "Models of Technology Diffusion," CEPR Discussion Papers 2146, C.E.P.R. Discussion Papers.
  8. 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.
  9. Benjamin Moll & Robert E. Lucas, 2011. "Knowledge Growth and the Allocation of Time," 2011 Meeting Papers 1030, Society for Economic Dynamics.
  10. Jovanovic, Boyan & Rob, Rafael, 1989. "The Growth and Diffusion of Knowledge," Review of Economic Studies, Wiley Blackwell, vol. 56(4), pages 569-82, October.
  11. König, Michael & Lorenz, Jan & Zilibotti, Fabrizio, 2012. "Innovation vs imitation and the evolution of productivity distributions," CEPR Discussion Papers 8843, C.E.P.R. Discussion Papers.
  12. 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 569-96, September.
  13. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-31, March.
  14. Kirman, Alan, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, MIT Press, vol. 108(1), pages 137-56, February.
  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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