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How Artificial Intelligence and Machine Learning Can Impact Market Design

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  • Paul R. Milgrom
  • Steven Tadelis

Abstract

In complex environments, it is challenging to learn enough about the underlying characteristics of transactions so as to design the best institutions to efficiently generate gains from trade. In recent years, Artificial Intelligence has emerged as an important tool that allows market designers to uncover important market fundamentals, and to better predict fluctuations that can cause friction in markets. This paper offers some recent examples of how Artificial Intelligence helps market designers improve the operations of markets, and outlines directions in which it will continue to shape and influence market design.

Suggested Citation

  • Paul R. Milgrom & Steven Tadelis, 2018. "How Artificial Intelligence and Machine Learning Can Impact Market Design," NBER Working Papers 24282, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:24282
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. David Bounies & Antoine Dubus & Patrick Waelbroeck, 2020. "Market for Information and Selling Mechanisms," Working Papers ECARES 2020-07, ULB -- Universite Libre de Bruxelles.
    2. Eric J. Bartelsman, 2019. "From New Technology to Productivity," European Economy - Discussion Papers 113, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    3. Yueqiang Xu & Petri Ahokangas & Jean-Nicolas Louis & Eva Pongrácz, 2019. "Electricity Market Empowered by Artificial Intelligence: A Platform Approach," Energies, MDPI, vol. 12(21), pages 1-21, October.
    4. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2020. "Market for Information and Selling Mechanisms," CESifo Working Paper Series 8307, CESifo.
    5. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2022. "Collecting and Selling Consumer Information: Selling Mechanisms Matter," Working Papers hal-02288708, HAL.
    6. Dangxing Chen & Luyao Zhang, 2023. "Monotonicity for AI ethics and society: An empirical study of the monotonic neural additive model in criminology, education, health care, and finance," Papers 2301.07060, arXiv.org.
    7. Grazia Cecere & Thierry Pénard, 2020. "Introduction to the Special Issue: “From The digital economy to the digitalization of the economy”," Revue d'économie industrielle, De Boeck Université, vol. 0(4), pages 11-17.
    8. David Mayer-Foulkes, 2018. "Efficient Urbanization for Mexican Development," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(10), pages 1-1, October.
    9. Yan Chen & Peter Cramton & John A. List & Axel Ockenfels, 2021. "Market Design, Human Behavior, and Management," Management Science, INFORMS, vol. 67(9), pages 5317-5348, September.
    10. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2022. "Market for Information and Selling Mechanisms," CER-ETH Economics working paper series 22/367, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.

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    More about this item

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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