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Signaling in deterministic and stochastic settings

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  • Jeitschko, Thomas D.
  • Normann, Hans-Theo

Abstract

We contrast a standard deterministic signaling game with one where the signal-generating mechanism is stochastic. With stochastic signals a unique equilibrium emerges that involves separation and has intuitive comparative-static properties as the degree of signaling depends on the prior type distribution. With deterministic signals both pooling and separating configurations occur. Laboratory data support the theory: In the stochastic variant, there is more signaling behavior than with deterministic signals, and less frequent types distort their signals relatively more. Moreover, the degree of congruence between equilibrium and subject behavior is greater in stochastic settings compared to deterministic treatments.

Suggested Citation

  • Jeitschko, Thomas D. & Normann, Hans-Theo, 2011. "Signaling in deterministic and stochastic settings," DICE Discussion Papers 35, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    • Handle: RePEc:zbw:dicedp:35
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    References listed on IDEAS

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    6. Clémence Christin, 2013. "Entry Deterrence Through Cooperative R&D Over-Investment," Recherches économiques de Louvain, De Boeck Université, vol. 79(2), pages 5-26.
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    8. Mirman, Leonard J. & Salgueiro, Egas M. & Santugini, Marc, 2014. "Noisy signaling in monopoly," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 504-511.
    9. Ennio Bilancini & Leonardo Boncinelli, 2014. "Small Noise in Signaling Selects Pooling on Minimum Signal," Center for Economic Research (RECent) 101, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    10. Catherine Gendron-Saulnier & Marc Santugini, 2013. "The Informational Benefit of Price Discrimination," Cahiers de recherche 13-02, HEC Montréal, Institut d'économie appliquée.
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    12. Miguel A. Fonseca & Francesco Giovannoni & Miltiadis Makris, 2020. "Auctions with external incentives: experimental evidence," International Journal of Game Theory, Springer;Game Theory Society, vol. 49(4), pages 1003-1043, December.
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    More about this item

    Keywords

    experiments; learning; noise; signaling; stochastic environments;
    All these keywords.

    JEL classification:

    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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