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Rank dependent expected utility theory explains the St. Petersburg paradox

Author

Listed:
  • Ali al-Nowaihi

  • Sanjit Dhami

  • Jia Zhu

Abstract

We show that rank dependent expected utility theory can explain the St. Petersburg paradox. This complements recent work by Blavatskyy (2005), Camerer (2005), Rieger and Wang (2006) and Pfiffelmann (2011).

Suggested Citation

  • Ali al-Nowaihi & Sanjit Dhami & Jia Zhu, 2015. "Rank dependent expected utility theory explains the St. Petersburg paradox," Discussion Papers in Economics 15/22, Division of Economics, School of Business, University of Leicester.
    • Handle: RePEc:lec:leecon:15/22
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    File URL: https://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp15-22.pdf
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    References listed on IDEAS

    as
    1. Marc Rieger & Mei Wang, 2006. "Cumulative prospect theory and the St. Petersburg paradox," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 28(3), pages 665-679, August.
    2. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    3. 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.
    4. Han Bleichrodt & Jose Luis Pinto, 2000. "A Parameter-Free Elicitation of the Probability Weighting Function in Medical Decision Analysis," Management Science, INFORMS, vol. 46(11), pages 1485-1496, November.
    5. Pavlo R. Blavatskyy, 2005. "Back to the St. Petersburg Paradox?," Management Science, INFORMS, vol. 51(4), pages 677-678, April.
    6. Samuelson, Paul A, 1977. "St. Petersburg Paradoxes: Defanged, Dissected, and Historically Described," Journal of Economic Literature, American Economic Association, vol. 15(1), pages 24-55, March.
    7. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
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    Keywords

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    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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