IDEAS home Printed from https://ideas.repec.org/a/eee/dyncon/v52y2015icp150-165.html
   My bibliography  Save this article

Self-organization of knowledge economies

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165188914003297
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jedc.2014.12.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. , & 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.
    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. 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.
    5. 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.
    6. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
    7. Robin Cowan & Nicolas Jonard, 2004. "Network structure and the diffusion of knowledge," Post-Print hal-00279020, HAL.
    8. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, Oxford University Press, vol. 108(1), pages 137-156.
    9. 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.
    10. Lafond, Francois, 2012. "Learning and the structure of citation networks," MERIT Working Papers 2012-071, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    11. Borghans, Lex & Meijers, Huub & ter Weel, Bas, 2013. "The importance of intrinsic and extrinsic motivation for measuring IQ," Economics of Education Review, Elsevier, vol. 34(C), pages 17-28.
    12. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
    13. Boyan Jovanovic & Rafael Rob, 1989. "The Growth and Diffusion of Knowledge," Review of Economic Studies, Oxford University Press, vol. 56(4), pages 569-582.
    14. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    15. 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.
    16. Ramón Gutiérrez Jáimez & José Rodríguez Avi, 1997. "Family of Pearson discrete distributions generated by the univariate hypergeometric function 3F2(α1, α2, α3; γ1, γ2; λ)," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 13(2), pages 115-125, June.
    17. Derek De Solla Price, 1976. "A general theory of bibliometric and other cumulative advantage processes," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 27(5), pages 292-306, September.
    18. 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.
    19. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mitri Kitti & Matti Pihlava & Hannu Salonen, 2016. "Search in Networks: The Case of Board Interlocks," Discussion Papers 116, Aboa Centre for Economics.
    2. Orlando Gomes & J. C. Sprott, 2017. "Sentiment-driven limit cycles and chaos," Journal of Evolutionary Economics, Springer, vol. 27(4), pages 729-760, September.
    3. Anatoliy Alabugin & Sergei Aliukov & Tatyana Khudyakova, 2022. "Review of Models for and Socioeconomic Approaches to the Formation of Foresight Control Mechanisms: A Genesis," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    4. Cremonini, Marco, 2016. "Introducing serendipity in a social network model of knowledge diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 64-71.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    2. 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;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 145-165, October.
    3. Verónica Robert & Gabriel Yoguel & Octavio Lerena, 2017. "The ontology of complexity and the neo-Schumpeterian evolutionary theory of economic change," Journal of Evolutionary Economics, Springer, vol. 27(4), pages 761-793, September.
    4. Rosina Moreno & Ernest Miguélez, 2012. "A Relational Approach To The Geography Of Innovation: A Typology Of Regions," Journal of Economic Surveys, Wiley Blackwell, vol. 26(3), pages 492-516, July.
    5. Jess Benhabib & Jesse Perla & Christopher Tonetti, 2021. "Reconciling Models of Diffusion and Innovation: A Theory of the Productivity Distribution and Technology Frontier," Econometrica, Econometric Society, vol. 89(5), pages 2261-2301, September.
    6. Zakaria Babutsidze & Maurizio Iacopetta, 2016. "Innovation, growth and financial markets," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 1-24, March.
    7. Tubiana, Matteo & Miguelez, Ernest & Moreno, Rosina, 2022. "In knowledge we trust: Learning-by-interacting and the productivity of inventors," Research Policy, Elsevier, vol. 51(1).
    8. Pier Patrucco, 2008. "The economics of collective knowledge and technological communication," The Journal of Technology Transfer, Springer, vol. 33(6), pages 579-599, December.
    9. Cremonini, Marco, 2016. "Introducing serendipity in a social network model of knowledge diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 64-71.
    10. Halleck-Vega, Solmaria & Mandel, Antoine & Millock, Katrin, 2018. "Accelerating diffusion of climate-friendly technologies: A network perspective," Ecological Economics, Elsevier, vol. 152(C), pages 235-245.
    11. , & Lorenz, Jan & ,, 2016. "Innovation vs. imitation and the evolution of productivity distributions," Theoretical Economics, Econometric Society, vol. 11(3), September.
    12. Gong, Guan & Keller, Wolfgang, 2003. "Convergence and polarization in global income levels: a review of recent results on the role of international technology diffusion," Research Policy, Elsevier, vol. 32(6), pages 1055-1079, June.
    13. Cantono, Simona, 2012. "Unveiling diffusion dynamics: an autocatalytic percolation model of environmental innovation diffusion and the optimal dynamic path of adoption subsidies," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201222, University of Turin.
    14. Miguélez, Ernest & Moreno, Rosina, 2015. "Knowledge flows and the absorptive capacity of regions," Research Policy, Elsevier, vol. 44(4), pages 833-848.
    15. Ernest Miguélez & Rosina Moreno, 2013. "“Mobility, networks and innovation: The role of regions’ absorptive capacity”," IREA Working Papers 201316, University of Barcelona, Research Institute of Applied Economics, revised Oct 2013.
    16. Julien Berthoumieu, 2015. "Technology Diffusion via Patent Collaborations: The Case of European Integration," Working Papers hal-01224761, HAL.
    17. Thomas Doring & Jan Schnellenbach, 2006. "What do we know about geographical knowledge spillovers and regional growth?: A survey of the literature," Regional Studies, Taylor & Francis Journals, vol. 40(3), pages 375-395.
    18. Diemer, Andreas & Regan, Tanner, 2022. "No inventor is an island: Social connectedness and the geography of knowledge flows in the US," Research Policy, Elsevier, vol. 51(2).
    19. Cantner, Uwe & Graf, Holger & Herrmann, Johannes & Kalthaus, Martin, 2016. "Inventor networks in renewable energies: The influence of the policy mix in Germany," Research Policy, Elsevier, vol. 45(6), pages 1165-1184.
    20. Hanaki, Nobuyuki & Nakajima, Ryo & Ogura, Yoshiaki, 2010. "The dynamics of R&D network in the IT industry," Research Policy, Elsevier, vol. 39(3), pages 386-399, April.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:dyncon:v:52:y:2015:i:c:p:150-165. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.elsevier.com/locate/jedc .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jedc .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.