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Stochastic market sharing, partial communication and collusion

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  • Gerlach, Heiko

Abstract

This paper analyzes the role of communication between firms in an infinitely repeated Bertrand game in which firms receive private signals of a common value i.i.d. demand shock. It is shown that firms can use stochastic, inter-temporal market sharing as a substitute for communication in low demand states. Partial communication in high demand states is sufficient to achieve the most collusive, full communication outcome and strictly dominates partial communication in low demand states. 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, 2009. "Stochastic market sharing, partial communication and collusion," International Journal of Industrial Organization, Elsevier, vol. 27(6), pages 655-666, November.
  • Handle: RePEc:eee:indorg:v:27:y:2009:i:6:p:655-666
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    Cited by:

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    3. 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.
    4. 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.
    5. Harrington, Joseph E., 2017. "A theory of collusion with partial mutual understanding," Research in Economics, Elsevier, vol. 71(1), pages 140-158.
    6. Danial Asmat, 2021. "Collusion Along the Learning Curve: Theory and Evidence From the Semiconductor Industry," Journal of Industrial Economics, Wiley Blackwell, vol. 69(1), pages 83-108, March.
    7. 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).
    8. 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.
    9. 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.
    10. Joseph E. Harrington, Jr., 2012. "A Theory of Tacit Collusion," Economics Working Paper Archive 588, The Johns Hopkins University,Department of Economics.
    11. Gerlach, Heiko & Li, Junqian, 2022. "Experts, trust and competition," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 552-578.
    12. Gerlach, Heiko, 2009. "Stochastic market sharing, partial communication and collusion," International Journal of Industrial Organization, Elsevier, vol. 27(6), pages 655-666, November.
    13. Ramakanta Patra & Tadashi Sekiguchi, 2021. "Full Collusion with Entry and Incomplete Information," KIER Working Papers 1055, Kyoto University, Institute of Economic Research.
    14. 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.

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    More about this item

    Keywords

    Stochastic market sharing Communication Collusion Competition policy;

    JEL classification:

    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • D - Microeconomics

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