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Optimal Rules for Patent Races

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  • Kenneth Judd
  • Karl Schmedders
  • Sevin Yeltekin

Abstract

There are two important rules in a patent race: what an innovator must accomplish to receive the patent and the allocation of the benefits that flow from the innovation. Most patent races end before R&D is completed and the prize to the innovator is often less than the social benefit of the innovation. We study the optimal combination of prize and minimal accomplishment necessary to obtain a patent in a dynamic multistage innovation race. A planner, who cannot distinguish between competing firms, chooses the innovation stage at which the patent is awarded and the magnitude of the prize to the winner. We examine both social surplus and consumer surplus maximizing patent race rules. We show that a key consideration is the efficiency costs of transfers and of monopoly power to the patentholder. We show that races are undesirable only when efficiency costs are low, firms have similar technologies, and the planner maximizes social surplus. However, in all other circumstances, the optimal policy spurs innovative effort through a race of nontrivial duration. Races are also used to filter out inferior innovators.

Suggested Citation

  • Kenneth Judd & Karl Schmedders & Sevin Yeltekin, "undated". "Optimal Rules for Patent Races," GSIA Working Papers 2006-E37, Carnegie Mellon University, Tepper School of Business.
  • Handle: RePEc:cmu:gsiawp:1327023263
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    Cited by:

    1. Malerba, Franco, 2007. "Innovation and the dynamics and evolution of industries: Progress and challenges," International Journal of Industrial Organization, Elsevier, vol. 25(4), pages 675-699, August.
    2. Weintraub, Gabriel Y. & Benkard, C. Lanier & Van Roy, Benjamin, 2007. "Computational Methods for Oblivious Equilibrium," Research Papers 1969, Stanford University, Graduate School of Business.
    3. Derek Clark & Christian Riis, 2007. "Contingent payments in selection contests," Review of Economic Design, Springer;Society for Economic Design, vol. 11(2), pages 125-137, September.
    4. Yuan, Michael Y., 2005. "Does decrease in copying cost support copyright term extension?," Information Economics and Policy, Elsevier, vol. 17(4), pages 471-494, October.
    5. Fershtman, Chaim & Markovich, Sarit, 2010. "Patents, imitation and licensing in an asymmetric dynamic R&D race," International Journal of Industrial Organization, Elsevier, vol. 28(2), pages 113-126, March.
    6. Doraszelski, Ulrich & Kryukov, Yaroslav & Borkovsky, Ron N., 2008. "A User's Guide to Solving Dynamic Stochastic Games Using the Homotopy Method," CEPR Discussion Papers 6733, C.E.P.R. Discussion Papers.
    7. Brüggemann, Julia & Meub, Lukas, 2017. "Experimental evidence on the effects of innovation contests," Information Economics and Policy, Elsevier, vol. 39(C), pages 72-83.
    8. Gregor Schwerhoff & Ottmar Edenhofer & Marc Fleurbaey, 2020. "Taxation Of Economic Rents," Journal of Economic Surveys, Wiley Blackwell, vol. 34(2), pages 398-423, April.
    9. Weintraub, Gabriel Y. & Benkard, C. Lanier & Van Roy, Benjamin, 2007. "Markov Perfect Industry Dynamics with Many Firms," Research Papers 1919r, Stanford University, Graduate School of Business.
    10. Fershtman, Chaim & Markovich, Sarit, 2006. "Patents, Imitation and Licensing In an Asymmetric Dynamic R&D Race," Foerder Institute for Economic Research Working Papers 275706, Tel-Aviv University > Foerder Institute for Economic Research.
    11. Brueggemann, Julia & Meub, Lukas, 2015. "Experimental evidence on the effects of innovation contests," University of Göttingen Working Papers in Economics 251, University of Goettingen, Department of Economics.
    12. Gabriel Weintraub & C. Lanier Benkard & Ben Van Roy, 2005. "Markov Perfect Industry Dynamics with Many Firms," NBER Working Papers 11900, National Bureau of Economic Research, Inc.
    13. C. Lanier Benkard & Benjamin Van Roy & Gabriel Y. Weintraub, 2005. "Markov perfect industry dynamics with many firms," Working Paper Series 2005-23, Federal Reserve Bank of San Francisco.
    14. Gabriel Y. Weintraub & C. Lanier Benkard & Benjamin Van Roy, 2010. "Computational Methods for Oblivious Equilibrium," Operations Research, INFORMS, vol. 58(4-part-2), pages 1247-1265, August.
    15. Ron N. Borkovsky & Ulrich Doraszelski & Yaroslav Kryukov, "undated". "A User''s Guide to Solving Dynamic Stochastic Games Using the Homotopy Method," GSIA Working Papers 2009-E23, Carnegie Mellon University, Tepper School of Business.

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