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No Switchbacks: Rethinking Aspiration-Based Dynamics in the Ultimatum Game

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  • Jeffrey Carpenter

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  • Peter Matthews

    ()

Abstract

The stylized facts of ultimatum bargaining in the experimental lab are that offers tend to be near an equal split of the surplus and low, near perfect offers are routinely rejected. Bimmore et al (1995) use aspiration-based evolutionary dynamics to model the evolution of fair play in a binary choice version of this game, and show that incredible threats to reject low offers persist in equilibrium. We focus on two possible extensions of this analysis: (1) the model makes assumptions about agent motivations (aspiration levels) and the structure of the game (binary strategy space) that have not yet been tested experimentally, and (2) the standard dynamic is based on the problematic assumption that unhappy games who switch strategies may end up using the same strategy that was just rejected. To examine the implications of not allowing agents to “switch back” to their original strategy, we develop a “no switchback dynamic” and run a new, binary choice, experiment with induced aspirations. We find that the resulting dynamic predicts the evolution of play better than the standard dynamic and that aspirations are a significant motivator for our participants.

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File URL: http://www.middlebury.edu/services/econ/repec/mdl/ancoec/0218.pdf
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Bibliographic Info

Paper provided by Middlebury College, Department of Economics in its series Middlebury College Working Paper Series with number 0218.

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Length: 30 pages
Date of creation: Jun 2002
Date of revision:
Handle: RePEc:mdl:mdlpap:0218

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Keywords: ultimatum game; learning; aspirations; switchbacks; replicator dynamics;

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  1. Bolton Gary E. & Zwick Rami, 1995. "Anonymity versus Punishment in Ultimatum Bargaining," Games and Economic Behavior, Elsevier, vol. 10(1), pages 95-121, July.
  2. Jeffrey Carpenter, 2002. "Bargaining Outcomes as the Result of Coordinated Expectations: An Experimental Study of Sequential Bargaining," Middlebury College Working Paper Series 0204, Middlebury College, Department of Economics.
  3. Friedman, Daniel, 1996. "Equilibrium in Evolutionary Games: Some Experimental Results," Economic Journal, Royal Economic Society, vol. 106(434), pages 1-25, January.
  4. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, December.
  5. V. Prasnikar & A. Roth, 1998. "Considerations of fairness and strategy: experimental data from sequential games," Levine's Working Paper Archive 451, David K. Levine.
  6. Karandikar, Rajeeva & Mookherjee, Dilip & Ray, Debraj & Vega-Redondo, Fernando, 1998. "Evolving Aspirations and Cooperation," Journal of Economic Theory, Elsevier, vol. 80(2), pages 292-331, June.
  7. Guth, Werner & Schmittberger, Rolf & Schwarze, Bernd, 1982. "An experimental analysis of ultimatum bargaining," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 367-388, December.
  8. Gale, John & Binmore, Kenneth G. & Samuelson, Larry, 1995. "Learning to be imperfect: The ultimatum game," Games and Economic Behavior, Elsevier, vol. 8(1), pages 56-90.
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Cited by:
  1. Benchekroun, Hassan & Long, Ngo Van, 2008. "The build-up of cooperative behavior among non-cooperative selfish agents," Journal of Economic Behavior & Organization, Elsevier, vol. 67(1), pages 239-252, July.
  2. Jeffrey Carpenter & Peter Matthews, 2002. "Social Reciprocity," Middlebury College Working Paper Series 0229, Middlebury College, Department of Economics.
  3. Jeffrey Carpenter, 2002. "When In Rome: Conformity and the Provision of Public Goods," Middlebury College Working Paper Series 0217, Middlebury College, Department of Economics.
  4. Carpenter, Jeffrey P., 2003. "Is fairness used instrumentally? Evidence from sequential bargaining," Journal of Economic Psychology, Elsevier, vol. 24(4), pages 467-489, August.

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