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Self-Organized Criticality In Evolutionary Systems With Local Interaction

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  • Albert Díaz-Guilera

    (Universidad de Barcelona)

  • Alex Arenas Moreno

    (Universitat Rovira i Virgili)

  • Conrad J. Pérez Vicente

    (Universidad de Barcelona)

  • Fernando Vega Redondo

    (Instituto Valenciano de Investigaciones Económicas)

Abstract

This paper studies a stylized model of local interaction where agents choose from an ever increasing set of vertically ranked actions, e.g. technologies. The driving forces of the model are infrequent upward shifts ("updates"), followed by a rapid process of local imitation ("diffusion"). Our main focus is on the long-run regularities displayed by the long-run distribution of diffusion waves and their implication on the performance of the system. By integrating analytical techniques and numerical simulations, we come to the following two main conclusions: (1) When the penalty for "technological dis-coordination" (the single key parameter of the model) is high enough, the system behaves critically, in the sense customarily used in physics -that is, diffusion waves have their size (or reach) distributed according to power laws. (2) If the performance of the system is evaluated by how fast or cost-efficiently it attains any given technological level, the optimal configuration obtains (in parameter space) close to the frontier of the critical region. There, the system no longer displays synchronized behavior but starts to exhibit persistent and critical long-run heterogeneities. In the heuristic language used by Kauffman (1993), the above two conclusions may be interpreted as an indication that (performance-sensitive) evolutionary forces induce the system to be placed "at the edge of order and chaos".

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Bibliographic Info

Paper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2000-30.

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Length: 35 pages
Date of creation: Dec 2000
Date of revision:
Publication status: Published by Ivie
Handle: RePEc:ivi:wpasad:2000-30

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  1. Matthew O. Jackson & Alison Watts, 2000. "On the Formation of Interaction Networks in Social Coordination Games," Econometric Society World Congress 2000 Contributed Papers 0778, Econometric Society.
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  5. John B Van Huyck & Raymond C Battalio & Richard O Beil, 1997. "Tacit coordination games, strategic uncertainty, and coordination failure," Levine's Working Paper Archive 1225, David K. Levine.
  6. Economides, Nicholas, 1996. "The economics of networks," International Journal of Industrial Organization, Elsevier, vol. 14(6), pages 673-699, October.
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  9. Segerstrom, Paul S & Anant, T C A & Dinopoulos, Elias, 1990. "A Schumpeterian Model of the Product Life Cycle," American Economic Review, American Economic Association, vol. 80(5), pages 1077-91, December.
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  11. Sanjeev Goyal & Fernando Vega-Redondo, 2000. "Learning, Network Formation and Coordination," Econometric Society World Congress 2000 Contributed Papers 0113, Econometric Society.
  12. Bryant, John, 1983. "A Simple Rational Expectations Keynes-Type Model," The Quarterly Journal of Economics, MIT Press, vol. 98(3), pages 525-28, August.
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  15. Crawford, Vincent P., 1991. "An "evolutionary" interpretation of Van Huyck, Battalio, and Beil's experimental results on coordination," Games and Economic Behavior, Elsevier, vol. 3(1), pages 25-59, February.
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Cited by:
  1. Rainer Andergassen & Franco Nardini, 2005. "Firms’ Network Formation Through The Transmission Of Heterogeneous Knowledge," Computing in Economics and Finance 2005 322, Society for Computational Economics.
  2. R. Andergassen & F. Nardini & M. Ricottilli, 2004. "The Emergence of Paradigm Setters through Firms' Interaction and Network Formation," Working Papers 525, Dipartimento Scienze Economiche, Universita' di Bologna.
  3. Fosco, Constanza & Mengel, Friederike, 2011. "Cooperation through imitation and exclusion in networks," Journal of Economic Dynamics and Control, Elsevier, vol. 35(5), pages 641-658, May.
  4. Andergassen, Rainer & Nardini, Franco & Ricottilli, Massimo, 2006. "Innovation waves, self-organized criticality and technological convergence," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 710-728, December.
  5. R. Andergassen & F. Nardini & M. Ricottilli, 2013. "Innovation diffusion, technological convergence and economic growth," Working Papers wp912, Dipartimento Scienze Economiche, Universita' di Bologna.
  6. John Duffy & Andreas Blume & Ted Temzelides, 2006. "Self-Organized Criticality in a Dynamic Game," Working Papers 276, University of Pittsburgh, Department of Economics, revised Aug 2008.
  7. Giovanni Pegoretti & Francesco Rentocchini & Giuseppe Vittucci Marzetti, 2012. "An agent-based model of innovation diffusion: network structure and coexistence under different information regimes," Journal of Economic Interaction and Coordination, Springer, vol. 7(2), pages 145-165, October.
  8. Cui, Zhiwei, 2014. "More neighbors, more efficiency," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 103-115.
  9. R. Andergassen & F. Nardini & M. Ricottilli, 2008. "Innovation and growth through local and global interaction," Working Papers 637, Dipartimento Scienze Economiche, Universita' di Bologna.
  10. R. Andergassen & F. Nardini & M. Ricottilli, 2005. "Firms' Network Formation Through the Transmission of Heterogeneous Knowledge," Working Papers 543, Dipartimento Scienze Economiche, Universita' di Bologna.

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