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Noisy signaling: Theory and experiment

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  • de Haan, Thomas
  • Offerman, Theo
  • Sloof, Randolph

Abstract

We introduce noise in the signaling technology of an otherwise standard wasteful signaling model (Spence, 1973). We theoretically derive the properties of the equilibria under different levels of noise and we experimentally test how behavior changes with noise. We obtain three main insights. First, if the amount of noise increases, high types aiming for separation (must) increase their signaling expenditures. This theoretical prediction is confirmed in our experiment. Second, for intermediate and high levels of noise, a separating and pooling equilibrium co-exist. In the experiment, subjects tend to shift from coordinating on a separating outcome to a pooling one as noise increases. Third, a surprising theoretical insight is that a separating equilibrium ceases to exist for low levels of noise (and an unfavorable prior). Yet in the experiment subjects then do coordinate on separation. A simple attraction learning model incorporating belief learning, imitation and reinforcement, explains this stable non-equilibrium behavior.

Suggested Citation

  • de Haan, Thomas & Offerman, Theo & Sloof, Randolph, 2011. "Noisy signaling: Theory and experiment," Games and Economic Behavior, Elsevier, vol. 73(2), pages 402-428.
  • Handle: RePEc:eee:gamebe:v:73:y:2011:i:2:p:402-428
    DOI: 10.1016/j.geb.2011.04.006
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    3. Bos, Olivier & Gomez-Martinez, Francisco & Onderstal, Sander & Truyts, Tom, 2021. "Signalling in auctions: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 448-469.
    4. Linde, Jona & Gietl, Daniel & Sonnemans, Joep & Tuinstra, Jan, 2023. "The effect of quantity and quality of information in strategy tournaments," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 305-323.
    5. Maik Hesse & Timm Teubner & Marc T. P. Adam, 2022. "In Stars We Trust – A Note on Reputation Portability Between Digital Platforms," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(3), pages 349-358, June.
    6. Benndorf, Volker & Kübler, Dorothea & Normann, Hans-Theo, 2015. "Privacy concerns, voluntary disclosure of information, and unraveling: An experiment," European Economic Review, Elsevier, vol. 75(C), pages 43-59.
    7. 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.
    8. Jeitschko, Thomas D. & Normann, Hans-Theo, 2012. "Signaling in deterministic and stochastic settings," Journal of Economic Behavior & Organization, Elsevier, vol. 82(1), pages 39-55.
    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. Taeuscher, Karl, 2019. "Reputation and new venture performance in online markets: The moderating role of market crowding," Journal of Business Venturing, Elsevier, vol. 34(6).
    11. Volker Benndorf, 2018. "Voluntary Disclosure of Private Information and Unraveling in the Market for Lemons: An Experiment," Games, MDPI, vol. 9(2), pages 1-17, May.
    12. TRUYTS, Tom, 2012. "Stochastic signaling: information substitutes and complements," LIDAM Discussion Papers CORE 2012022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Francesc Dilmé, 2012. "Dynamic Quality Signaling with Hidden Actions, Second Version," PIER Working Paper Archive 13-063, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 03 Oct 2013.
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    15. Schell, Sabrina & de Groote, Julia K. & Moog, Petra & Hack, Andreas, 2020. "Successor selection in family business—A signaling game," Journal of Family Business Strategy, Elsevier, vol. 11(3).

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    More about this item

    Keywords

    Signaling games; Noise; Separation; Experiments;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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