IDEAS home Printed from https://ideas.repec.org/p/sce/scecf1/43.html
   My bibliography  Save this paper

An R&D Race with Learning and Forgetting

Author

Listed:
  • Ulrich Doraszelski

Abstract

I develop a model of an R&D race in which firms learn and forget. The firm which makes a discovery first is awarded a prize. Firms compete to be the first by investing in R&D. As a by-product of its R&D effort, a firm accumulates knowledge. This knowledge stock is valuable even if success is not immediate. On the other hand, over time a firm's knowledge base depreciates. Unlike traditional models of symmetric R&D races, my model does not inherit the memorylessness property of the exponential distribution. Unlike models of multi-stage races where the stages or experience levels are mere labels, knowledge is productive in my model. I show that learning and forgetting shape firms' equilibrium payoffs and strategies and that many findings of the previous literature are reversed in this more general setting. The resulting patterns of strategic interactions appear to be consistent with both anecdotal evidence and empirical research on R&D races. The model does not in general allow for an analytical solution, and I employ projection methods to solve the partial differential equation that characterizes a firm's value function. Projection methods approximate the value function by a high-order polynomial. Special considerations arise since I need not only a good approximation of the value function but also good approximations of its derivatives to compute the Nash equilibrium in feedback strategies. An accuracy check indicates that the approximations yield a good description of the equilibrium payoffs and strategies. This suggests that projection techniques are promising tools for the analysis of differential games.

Suggested Citation

  • Ulrich Doraszelski, 2001. "An R&D Race with Learning and Forgetting," Computing in Economics and Finance 2001 43, Society for Computational Economics.
  • Handle: RePEc:sce:scecf1:43
    as

    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

    Keywords

    dynamic competition; action-reaction; learning and forgetting; R&D;

    JEL classification:

    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

    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:sce:scecf1:43. 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: (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/sceeeea.html .

    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.