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Signaling in Deterministic and Stochastic Settings

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  • Thomas D. Jeitschko

    (Department of Economics, Michigan State University)

  • Hans-Theo Normann

    (Department of Economics, Goethe University Frankfurt)

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

  • Thomas D. Jeitschko & Hans-Theo Normann, 2009. "Signaling in Deterministic and Stochastic Settings," Royal Holloway, University of London: Discussion Papers in Economics 09/12, Department of Economics, Royal Holloway University of London.
  • Handle: RePEc:hol:holodi:0912
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    References listed on IDEAS

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    6. 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.
    7. Haucap, Justus & Herr, Annika & Frank, Björn, 2011. "In vino veritas: Theory and evidence on social drinking," DICE Discussion Papers 37, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    8. Clémence Christin, 2013. "Entry Deterrence Through Cooperative R&D Over-Investment," Recherches économiques de Louvain, De Boeck Université, vol. 79(2), pages 5-26.
    9. Stühmeier Torben & Wenzel Tobias, 2012. "Regulating Advertising in the Presence of Public Service Broadcasting," Review of Network Economics, De Gruyter, vol. 11(2), pages 1-23, June.
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    More about this item

    Keywords

    experiments; noise; signalling; learning; 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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