IDEAS home Printed from https://ideas.repec.org/a/aea/aejmic/v11y2019i4p186-215.html
   My bibliography  Save this article

Learning Theory and Heterogeneous Play in a Signaling-Game Experiment

Author

Listed:
  • Drew Fudenberg
  • Emanuel Vespa

Abstract

We study the effect of how types are assigned to participants in a signaling-game experiment. The sender has two actions, In and Out, and two types. In one treatment, types are i.i.d. in every period, and senders gather experience with both types. In the other, types are assigned once-and-for-all, and feedback is type specific. The theory of learning in games predicts that the non-Nash but self-confirming equilibrium where some fraction of types play Out can persist in the fixed-type treatment but not when types are i.i.d. Our results confirm that more senders do play Out in the fixed-type treatment.

Suggested Citation

  • Drew Fudenberg & Emanuel Vespa, 2019. "Learning Theory and Heterogeneous Play in a Signaling-Game Experiment," American Economic Journal: Microeconomics, American Economic Association, vol. 11(4), pages 186-215, November.
  • Handle: RePEc:aea:aejmic:v:11:y:2019:i:4:p:186-215
    Note: DOI: 10.1257/mic.20180317
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/doi/10.1257/mic.20180317
    Download Restriction: no

    File URL: https://www.aeaweb.org/doi/10.1257/mic.20180317.data
    Download Restriction: no

    File URL: https://www.aeaweb.org/doi/10.1257/mic.20180317.appx
    Download Restriction: no

    File URL: https://www.aeaweb.org/doi/10.1257/mic.20180317.ds
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Giuseppe Danese & Luigi Mittone, 2020. "On pledging one's trustworthiness through gifts: an experimental inquiry," CEEL Working Papers 2001, Cognitive and Experimental Economics Laboratory, Department of Economics, University of Trento, Italia.
    2. Johannes Hoelzemann & Nicolas Klein, 2021. "Bandits in the lab," Quantitative Economics, Econometric Society, vol. 12(3), pages 1021-1051, July.

    More about this item

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aea:aejmic:v:11:y:2019:i:4:p:186-215. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.