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Experimentation in Dynamic R&D Competition

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  • Anastasios Dosis

    (THEMA - Théorie économique, modélisation et applications - UCP - Université de Cergy Pontoise - Université Paris-Seine - CNRS - Centre National de la Recherche Scientifique, ESSEC Business School)

  • Abhinay Muthoo

    (University of Warwick [Coventry])

Abstract

We study a two-stage, winner-takes-all, R&D race, in which, at the outset, firms are uncertain regarding the viability of the project. Learning through experimentation introduces a bilateral (dynamic) feedback mechanism. For relatively low-value products , the equilibrium stopping time coincides with the socially efficient stopping time although firms might experiment excessively in equilibrium; for relatively high-value products, firms might reduce experimentation and stop rather prematurely due to the fundamental free-riding effect. Perhaps surprisingly, a decrease in the value of the product can spur experimentation.

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  • Anastasios Dosis & Abhinay Muthoo, 2019. "Experimentation in Dynamic R&D Competition," Working Papers hal-02102518, HAL.
    • Handle: RePEc:hal:wpaper:hal-02102518
    Note: View the original document on HAL open archive server: https://essec.hal.science/hal-02102518
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    References listed on IDEAS

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    Cited by:

    1. Gorno, Leandro & Iachan, Felipe S., 2020. "Competitive real options under private information," Journal of Economic Theory, Elsevier, vol. 185(C).

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    More about this item

    Keywords

    Experimentation; Learning; Dynamic R&D competition; inefficiency;
    All these keywords.

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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