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Researcher's Dilemma

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  • Mariotti, Thomas
  • Bobtcheff, Catherine
  • Bolte, Jérôme

Abstract

We propose and analyze a general model of priority races. Researchers privately have breakthroughs and decide how long to let their ideas mature before disclosing them, thereby establishing priority. Two-researcher, symmetric priority races have a unique equilibrium that can be characterized by a differential equation. We study how the shape of the breakthrough distribution and of the returns to maturation affect maturation delays and research quality, both in dynamic and comparative-statics analyses. Making researchers better at discovering new ideas or at developing them has contrasted effects on research quality. Being closer to the technological frontier enhances the value of maturation for researchers, which mitigates the negative impact on research quality of the race for priority. Finally, when researchers differ in their abilities to do creative work or in the technologies they use to develop their ideas, more efficient researchers always let their ideas mature more than their less efficient opponents. Our theoretical results shed light on academic competition, patent races, and innovation quality.

Suggested Citation

  • Mariotti, Thomas & Bobtcheff, Catherine & Bolte, Jérôme, 2015. "Researcher's Dilemma," CEPR Discussion Papers 10858, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:10858
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    Cited by:

    1. Dirk Bergemann & Marco Ottaviani, 2021. "Information Markets and Nonmarkets," Cowles Foundation Discussion Papers 2296, Cowles Foundation for Research in Economics, Yale University.
    2. Mueller-Langer, Frank & Fecher, Benedikt & Harhoff, Dietmar & Wagner, Gert G., 2019. "Replication studies in economics—How many and which papers are chosen for replication, and why?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 48(1), pages 62-83.
    3. Song, Yangbo & Zhao, Mofei, 2021. "Dynamic R&D competition under uncertainty and strategic disclosure," Journal of Economic Behavior & Organization, Elsevier, vol. 181(C), pages 169-210.
    4. Mariotti, Thomas & Décamps, Jean-Paul & Gensbittel, Fabien, 2021. "Investment Timing and Technological Breakthrough," CEPR Discussion Papers 16246, C.E.P.R. Discussion Papers.
    5. Leonid Tiokhin & Minhua Yan & Thomas J. H. Morgan, 2021. "Competition for priority harms the reliability of science, but reforms can help," Nature Human Behaviour, Nature, vol. 5(7), pages 857-867, July.
    6. Mohan, Vijay, 2019. "On the use of blockchain-based mechanisms to tackle academic misconduct," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    7. Damien Besancenot & Radu Vranceanu, 2015. "Fear Of Novelty: A Model Of Scientific Discovery With Strategic Uncertainty," Economic Inquiry, Western Economic Association International, vol. 53(2), pages 1132-1139, April.
    8. Chen, Chia-Hui & Ishida, Junichiro & Mukherjee, Arijit, 2023. "Pioneer, early follower or late entrant: Entry dynamics with learning and market competition," European Economic Review, Elsevier, vol. 152(C).
    9. Bobtcheff, Catherine & Mariotti, Thomas & Levy, Raphaël, 2021. "Negative results in science: Blessing or (winner’s) curse," TSE Working Papers 21-1202, Toulouse School of Economics (TSE).
    10. Sadler, Evan, 2021. "Dead ends," Journal of Economic Theory, Elsevier, vol. 191(C).
    11. Groen-Xu, Moqi & Bös, Gregor & Teixeira, Pedro A. & Voigt, Thomas & Knapp, Bernhard, 2023. "Short-term incentives of research evaluations: Evidence from the UK Research Excellence Framework," Research Policy, Elsevier, vol. 52(6).
    12. Hoppe-Wewetzer, Heidrun & Katsenos, Georgios & Ozdenoren, Emre, 2023. "The effects of rivalry on scientific progress under public vs private learning," Journal of Economic Theory, Elsevier, vol. 212(C).
    13. Baruffaldi, Stefano & Poege, Felix, 2020. "A Firm Scientific Community: Industry Participation and Knowledge Diffusion," IZA Discussion Papers 13419, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    Priority races; Private information;

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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