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Experimental evidence for attractions to chance

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  • Albers, Wulf

    (Center for Mathematical Economics, Bielefeld University)

Abstract

Divide the decision-maker's future into: (i) a pre-outcome period (lasting from the decision until the outcome of that decision is known), and (ii) a sequel post-outcome period (beginning when the outcome becomes known). Anticipated emotions in both periods may influence the decision, in particular, with regard to an outcome that matters to the person, the enjoyable tension from not yet knowing what this outcome will be. In the experiments presented, lottery choice can be explained by this attraction to chance, and cannot be explained by either convex von Neumann-Morgenstern utility, or by rank-dependent risk-loving weights: attraction to chance is a separate motivator. Copyright Verein fü Socialpolitik and Blackwell Publishers Ltd 2000.
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Suggested Citation

  • Albers, Wulf, 2017. "Experimental evidence for attractions to chance," Center for Mathematical Economics Working Papers 317, Center for Mathematical Economics, Bielefeld University.
  • Handle: RePEc:bie:wpaper:317
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    References listed on IDEAS

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    1. Robin Cubitt & Chris Starmer & Robert Sugden, 1998. "On the Validity of the Random Lottery Incentive System," Experimental Economics, Springer;Economic Science Association, vol. 1(2), pages 115-131, September.
    2. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    3. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    4. Pope, Robin, 1999. "Reconciliation with the Utility of Chance by Elaborated Outcomes Destroys the Axiomatic Basis of Expected Utility Theory," Discussion Paper Serie B 449, University of Bonn, Germany.
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    Cited by:

    1. Battigalli, Pierpaolo & Dufwenberg, Martin, 2009. "Dynamic psychological games," Journal of Economic Theory, Elsevier, vol. 144(1), pages 1-35, January.
    2. Heldmann, Marcus & Vogt, Bodo & Heinze, Hans-Jochen & Münte, Thomas, 2009. "Different methods to define utility functions yield different results and engage different neural processes," FEMM Working Papers 09014, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    3. Bischoff, Ivo, 2007. "Institutional choice versus communication in social dilemmas--An experimental approach," Journal of Economic Behavior & Organization, Elsevier, vol. 62(1), pages 20-36, January.
    4. Fischbacher, Urs & Thöni, Christian, 2008. "Excess entry in an experimental winner-take-all market," Journal of Economic Behavior & Organization, Elsevier, vol. 67(1), pages 150-163, July.
    5. Kjell Hausken, 2007. "Book Review," Theory and Decision, Springer, vol. 62(3), pages 303-309, May.
    6. Heufer, Jan, 2013. "Quasiconcave preferences on the probability simplex: A nonparametric analysis," Mathematical Social Sciences, Elsevier, vol. 65(1), pages 21-30.
    7. Timm Teubner & Marc T. P. Adam & Claudia Niemeyer, 2015. "Measuring risk preferences in field experiments: Proposition of a simplified task," Economics Bulletin, AccessEcon, vol. 35(3), pages 1510-1517.
    8. Pope, Robin & Leitner, Johannes & Leopold-Wildburger, Ulrike, 2009. "Expected utility versus the changes in knowledge ahead," European Journal of Operational Research, Elsevier, vol. 199(3), pages 892-901, December.
    9. Pope, Robin, 2004. "Biases from omitted risk effects in standard gamble utilities," Journal of Health Economics, Elsevier, vol. 23(4), pages 695-735, July.

    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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