IDEAS home Printed from
   My bibliography  Save this article

Collective Learning, Innovation and Growth in a Boundedly Rational, Evolutionary World


  • Silverberg, Gerald
  • Verspagen, Bart


We formulate a simple multiagent evolutionary scheme as a model of collective learning, i.e., a situation in which firms experiment, interact, and learn from each other. This scheme is then applied to a stylized endogenous growth economy in which firms have to determine how much to invest in R&D, where innovations are the stochastic product of their R&D activity, spillovers occur, but technological advantages are only relative and temporary and innovations actually diffuse, both at the intra- and interfirm levels. The model demonstrates both the existence of a unique long-run growth attractor (in the linear case) and distinct growth phases on the road to that attractor. We also compare the long-run growth patterns for a linear and a logistic innovation function, and produce some evidence for a bifurcation in the latter case.

Suggested Citation

  • Silverberg, Gerald & Verspagen, Bart, 1994. "Collective Learning, Innovation and Growth in a Boundedly Rational, Evolutionary World," Journal of Evolutionary Economics, Springer, vol. 4(3), pages 207-226, September.
  • Handle: RePEc:spr:joevec:v:4:y:1994:i:3:p:207-26

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item


    Access and download statistics


    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:spr:joevec:v:4:y:1994:i:3:p:207-26. 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: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

    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.