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Using Experimental Data to Model Bargaining Behavior in Ultimatum Games

Author

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  • Shyam Sunder

    (Yale University, School of Management)

  • Haijin Lin

    (Carnegie Mellon University)

Abstract

Subgame perfect equilibrium predictions of ultimatum bargaining games correspond poorly to the data gathered from human subjects in laboratory environments. Attempts to reconcile this discrepancy have taken one or more of three routes: (1) expanding the agent foresight and scope of decisions, (2) explicit modeling of agents' initial beliefs and their dynamics, and (3) adding social arguments to agent preferences. We take the first two routes by including the probability of rejection by the responder in proposer's decision, and using experimental data to estimate a static model of agent beliefs. Data from previously reported experiments is compared to the predictions of the optimal decision rule to validate the proposer model. Models in which the probability of acceptance of a proposal declines with the amount offered to the responder are better able to organize the data about the behavior of both players. Explanation of responders' behavior remains weak.

Suggested Citation

  • Shyam Sunder & Haijin Lin, 2003. "Using Experimental Data to Model Bargaining Behavior in Ultimatum Games," Yale School of Management Working Papers ysm330, Yale School of Management.
    • Handle: RePEc:ysm:somwrk:ysm330
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    Cited by:

    1. Ernesto Reuben & Frans van Winden, 2005. "Negative Reciprocity and the Interaction of Emotions and Fairness Norms," Tinbergen Institute Discussion Papers 05-014/1, Tinbergen Institute.
    2. Güth, Werner & Kocher, Martin G., 2014. "More than thirty years of ultimatum bargaining experiments: Motives, variations, and a survey of the recent literature," Journal of Economic Behavior & Organization, Elsevier, vol. 108(C), pages 396-409.
    3. D.D.B. van Bragt & J.A. La Poutré, 2003. "Why Agents for Automated Negotiations Should Be Adaptive," Netnomics, Springer, vol. 5(2), pages 101-118, November.
    4. Enrico Gerding & David van Bragt & Han La Poutré, 2003. "Multi-Issue Negotiation Processes by Evolutionary Simulation, Validation and Social Extensions," Computational Economics, Springer;Society for Computational Economics, vol. 22(1), pages 39-63, August.

    More about this item

    Keywords

    Ultimatum Game; Experimental Economics; Parametric Modeling; Estimation;
    All these keywords.

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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