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Insider Imitation

Author

Listed:
  • Erik Madsen

    (NYU - New York University [New York] - NYU - NYU System)

  • Nikhil Vellodi

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

We study how regulating data usage impacts innovation in digital markets. Platforms commonly use proprietary data about third-party sellers to inform their own competing offerings, dampening incentives for innovation. We model this interaction and characterize how data usage restrictions reshape these incentives. An outright ban on data usage may boost or curtail innovation, depending upon the thickness of the right tail of demand for new products. More flexible rules controlling when and what data is made available can always improve the effectiveness of regulation. Our results contribute to an ongoing policy discussion regarding competition in digital markets.

Suggested Citation

  • Erik Madsen & Nikhil Vellodi, 2024. "Insider Imitation," Post-Print hal-04465669, HAL.
    • Handle: RePEc:hal:journl:hal-04465669
    DOI: 10.2139/ssrn.3832712
    as

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    Cited by:

    1. Federico Etro, 2024. "e‐Commerce platforms and self‐preferencing," Journal of Economic Surveys, Wiley Blackwell, vol. 38(4), pages 1516-1543, September.

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