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Self-organization of knowledge economies

Listed author(s):
  • Lafond, François

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.

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File URL: http://www.sciencedirect.com/science/article/pii/S0165188914003297
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Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 52 (2015)
Issue (Month): C ()
Pages: 150-165

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Handle: RePEc:eee:dyncon:v:52:y:2015:i:c:p:150-165
DOI: 10.1016/j.jedc.2014.12.004
Contact details of provider: Web page: http://www.elsevier.com/locate/jedc

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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. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
  3. Robert E. Lucas Jr. & Benjamin Moll, 2014. "Knowledge Growth and the Allocation of Time," Journal of Political Economy, University of Chicago Press, vol. 122(1), pages 1-51.
  4. Sen, Amartya, 2001. "Development as Freedom," OUP Catalogue, Oxford University Press, number 9780192893307.
  5. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, Oxford University Press, vol. 108(1), pages 137-156.
  6. Boyan Jovanovic & Rafael Rob, 1989. "The Growth and Diffusion of Knowledge," Review of Economic Studies, Oxford University Press, vol. 56(4), pages 569-582.
  7. 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.
  8. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
  9. 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.
  10. 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).
  11. 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.
  12. 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.
  13. 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.
  14. 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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