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Using Experimental Data to Model Bargaining Behavior in Ultimatum Games

Haijin Lin
University of Houston

Shyam Sunder
Yale School of Management


April 2001

Yale SOM Working Paper No. ES-08

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.




Keywords: Ultimatum Game, Experimental Economics, Parametric Modeling, Estimation

JEL Classifications: C72, C78, C92

Working Paper Series

Date posted: May 07, 2001 ; Last revised: January 30, 2003

Suggested Citation

Sunder, Shyam and Lin, Haijin, Using Experimental Data to Model Bargaining Behavior in Ultimatum Games (April 2001). Yale SOM Working Paper No. ES-08. Available at SSRN: http://ssrn.com/abstract=268755 or doi:10.2139/ssrn.268755


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Contact Information

Shyam Sunder (Contact Author)
Yale School of Management ( email )
135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States
203-432-6160 (Phone)
203-432-6974 (Fax)
HOME PAGE: http://www.som.yale.edu/faculty/sunder/
Haijin Lin
University of Houston ( email )
390F Melcher Hall
Bauer College of Business
Houston, TX 77204-6021
United States
7137437771 (Phone)
Feedback to SSRN (Beta)


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