IDEAS home Printed from https://ideas.repec.org/p/aep/anales/4433.html
   My bibliography  Save this paper

Collusion and Artificial Intelligence: A computational experiment with sequential pricing algorithms under stochastic costs

Author

Listed:
  • Gonzalo Ballestero

Abstract

No abstract is available for this item.

Suggested Citation

  • Gonzalo Ballestero, 2021. "Collusion and Artificial Intelligence: A computational experiment with sequential pricing algorithms under stochastic costs," Asociación Argentina de Economía Política: Working Papers 4433, Asociación Argentina de Economía Política.
    • Handle: RePEc:aep:anales:4433
    as

    Download full text from publisher

    File URL: https://aaep.org.ar/works/works2021b/4433.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Timo Klein, 2021. "Autonomous algorithmic collusion: Q‐learning under sequential pricing," RAND Journal of Economics, RAND Corporation, vol. 52(3), pages 538-558, September.
    2. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2020. "Artificial Intelligence, Algorithmic Pricing, and Collusion," American Economic Review, American Economic Association, vol. 110(10), pages 3267-3297, October.
    3. Maskin, Eric & Tirole, Jean, 1988. "A Theory of Dynamic Oligopoly, II: Price Competition, Kinked Demand Curves, and Edgeworth Cycles," Econometrica, Econometric Society, vol. 56(3), pages 571-599, May.
    4. Green, Edward J & Porter, Robert H, 1984. "Noncooperative Collusion under Imperfect Price Information," Econometrica, Econometric Society, vol. 52(1), pages 87-100, January.
    5. Calzolari, Giacomo & Calvano, Emilio & Denicolo, Vincenzo & Pastorello, Sergio, 2021. "Algorithmic collusion with imperfect monitoring," CEPR Discussion Papers 15738, C.E.P.R. Discussion Papers.
    6. Leufkens, Kasper & Peeters, Ronald, 2011. "Price dynamics and collusion under short-run price commitments," International Journal of Industrial Organization, Elsevier, vol. 29(1), pages 134-153, January.
    7. Calvano, Emilio & Calzolari, Giacomo & Denicoló, Vincenzo & Pastorello, Sergio, 2021. "Algorithmic collusion with imperfect monitoring," International Journal of Industrial Organization, Elsevier, vol. 79(C).
    8. Joseph E Harrington, 2018. "Developing Competition Law For Collusion By Autonomous Artificial Agents," Journal of Competition Law and Economics, Oxford University Press, vol. 14(3), pages 331-363.
    9. Eckert, Andrew, 2004. "An alternating-move price-setting duopoly model with stochastic costs," International Journal of Industrial Organization, Elsevier, vol. 22(7), pages 997-1015, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gonzalo Ballestero, 2022. "Collusion and Artificial Intelligence: A Computational Experiment with Sequential Pricing Algorithms under Stochastic Costs," Working Papers 118, Red Nacional de Investigadores en Economía (RedNIE).
    2. Gonzalo Ballestero, 2021. "Collusion and Artificial Intelligence: A computational experiment with sequential pricing algorithms under stochastic costs," Young Researchers Working Papers 1, Universidad de San Andres, Departamento de Economia, revised Oct 2022.
    3. Simon Martin & Alexander Rasch, 2022. "Collusion by Algorithm: The Role of Unobserved Actions," CESifo Working Paper Series 9629, CESifo.
    4. Martin, Simon & Rasch, Alexander, 2022. "Collusion by algorithm: The role of unobserved actions," DICE Discussion Papers 382, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    5. Normann, Hans-Theo & Sternberg, Martin, 2023. "Human-algorithm interaction: Algorithmic pricing in hybrid laboratory markets," European Economic Review, Elsevier, vol. 152(C).
    6. Timo Klein, 2021. "Autonomous algorithmic collusion: Q‐learning under sequential pricing," RAND Journal of Economics, RAND Corporation, vol. 52(3), pages 538-558, September.
    7. Martin, Simon & Rasch, Alexander, 2024. "Demand forecasting, signal precision, and collusion with hidden actions," International Journal of Industrial Organization, Elsevier, vol. 92(C).
    8. Dolgopolov, Arthur, 2024. "Reinforcement learning in a prisoner's dilemma," Games and Economic Behavior, Elsevier, vol. 144(C), pages 84-103.
    9. Colombo, Stefano & Filippini, Luigi & Pignataro, Aldo, 2024. "Information sharing, personalized pricing, and collusion," Information Economics and Policy, Elsevier, vol. 66(C).
    10. Leonardo Madio & Aldo Pignataro, 2022. "Collusion sustainability with a capacity constrained firm," "Marco Fanno" Working Papers 0295, Dipartimento di Scienze Economiche "Marco Fanno".
    11. Ivan Conjeaud, 2023. "Algorithmic collusion under competitive design," Papers 2312.02644, arXiv.org, revised Sep 2024.
    12. Justin P. Johnson & Andrew Rhodes & Matthijs Wildenbeest, 2023. "Platform Design When Sellers Use Pricing Algorithms," Econometrica, Econometric Society, vol. 91(5), pages 1841-1879, September.
    13. Lucila Porto, 2022. "Q-Learning algorithms in a Hotelling model," Asociación Argentina de Economía Política: Working Papers 4587, Asociación Argentina de Economía Política.
    14. Sara Fish & Yannai A. Gonczarowski & Ran I. Shorrer, 2024. "Algorithmic Collusion by Large Language Models," Papers 2404.00806, arXiv.org, revised Nov 2024.
    15. Fourberg, Niklas & Marques Magalhaes, Katrin & Wiewiorra, Lukas, 2023. "They Are Among Us: Pricing Behavior of Algorithms in the Field," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 277958, International Telecommunications Society (ITS).
    16. Hans-Theo Normann & Martin Sternberg, 2021. "Human-Algorithm Interaction: Algorithmic Pricing in Hybrid Laboratory Markets," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2021_11, Max Planck Institute for Research on Collective Goods, revised 13 Apr 2022.
    17. Marcel Wieting & Geza Sapi, 2021. "Algorithms in the Marketplace: An Empirical Analysis of Automated Pricing in E-Commerce," Working Papers 21-06, NET Institute.
    18. Martino Banchio & Giacomo Mantegazza, 2022. "Artificial Intelligence and Spontaneous Collusion," Papers 2202.05946, arXiv.org, revised Sep 2023.
    19. Calvano, Emilio & Calzolari, Giacomo & Denicoló, Vincenzo & Pastorello, Sergio, 2021. "Algorithmic collusion with imperfect monitoring," International Journal of Industrial Organization, Elsevier, vol. 79(C).
    20. Leonardo Madio & Aldo Pignataro, 2022. "Collusion Sustainability with a Capacity Constrained Firm," CESifo Working Paper Series 10170, CESifo.

    More about this item

    Keywords

    Artificial Intelligence; Algorithmic Collusion; Competition Policy;
    All these keywords.

    JEL classification:

    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aep:anales:4433. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Juan Manuel Quintero (email available below). General contact details of provider: https://edirc.repec.org/data/aaeppea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.