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Stochastic market sharing, partial communication and collusion

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  • Gerlach, Heiko

    (IESE Business School)

Abstract

This paper analyzes the role of communication between firms in an infinitely repeated Bertrand game in which firms receive an imperfect private signal of a common value i.i.d. demand shock. It is shown that firms can use stochastic, inter-temporal market sharing as a perfect substitute for communication in low-demand states. Therefore, partial communication in high-demand states is sufficient to achieve the most collusive, full communication outcome. And partial communication in low-demand states does not improve on the equilibrium without communication. Communication in high-demand states allows firms to coordinate their pricing, choose the most efficient uninformed price and avoid price wars. I demonstrate that under some conditions consumers are better off with communication among colluding firms.

Suggested Citation

  • Gerlach, Heiko, 2007. "Stochastic market sharing, partial communication and collusion," IESE Research Papers D/674, IESE Business School.
  • Handle: RePEc:ebg:iesewp:d-0674
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    Cited by:

    1. Joseph E. Harrington, Jr., 2012. "A Theory of Tacit Collusion," Economics Working Paper Archive 588, The Johns Hopkins University,Department of Economics.
    2. Escobar, Juan F. & Llanes, Gastón, 2018. "Cooperation dynamics in repeated games of adverse selection," Journal of Economic Theory, Elsevier, vol. 176(C), pages 408-443.
    3. Harrington, Joseph E., 2017. "A theory of collusion with partial mutual understanding," Research in Economics, Elsevier, vol. 71(1), pages 140-158.
    4. Sahuguet, Nicolas & Walckiers, Alexis, 2017. "A theory of hub-and-spoke collusion," International Journal of Industrial Organization, Elsevier, vol. 53(C), pages 353-370.
    5. Noam Shamir, 2017. "Cartel Formation Through Strategic Information Leakage in a Distribution Channel," Marketing Science, INFORMS, vol. 36(1), pages 70-88, January.
    6. Sahuguet, Nicolas & Walckiers, Alexis, 2013. "Selling to a cartel of retailers: a model of hub-and-spoke collusion," CEPR Discussion Papers 9385, C.E.P.R. Discussion Papers.
    7. Gerlach, Heiko, 2009. "Stochastic market sharing, partial communication and collusion," International Journal of Industrial Organization, Elsevier, vol. 27(6), pages 655-666, November.
    8. Ramakanta Patra & Tadashi Sekiguchi, 2021. "Full Collusion with Entry and Incomplete Information," KIER Working Papers 1055, Kyoto University, Institute of Economic Research.
    9. Wu, Jiang & Zou, Liuxin & Gong, Yeming & Chen, Mingyang, 2021. "The anti-collusion dilemma: Information sharing of the supply chain under buyback contracts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    10. Jeanine Miklós-Thal & Catherine Tucker, 2019. "Collusion by Algorithm: Does Better Demand Prediction Facilitate Coordination Between Sellers?," Management Science, INFORMS, vol. 65(4), pages 1552-1561, April.
    11. Harrington, Joseph E. & Zhao, Wei, 2012. "Signaling and tacit collusion in an infinitely repeated Prisoners’ Dilemma," Mathematical Social Sciences, Elsevier, vol. 64(3), pages 277-289.
    12. Joseph E. Harrington, Jr. & Wei Zhao, 2012. "Signaling and Tacit Collusion in an Infinitely Repeated Prisoners' Dilemma," Economics Working Paper Archive 587, The Johns Hopkins University,Department of Economics.

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    More about this item

    Keywords

    Stochastic market sharing; communication; collusion; competition policy;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices

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