IDEAS home Printed from https://ideas.repec.org/p/gfe/pfrp00/00029.html
   My bibliography  Save this paper

Il paradosso di S. Pietroburgo, una rassegna

Author

Listed:
  • Ruggero Paladini

    (Università Sapienza di Roma - Dipartimento di Studi Giuridici, Filosofici ed Economici)

Abstract

In 1738 Daniel Bernoulli presented for the first time a study with a functional relationship between utility and wealth. The goal was to provide a solution to a "curious" paradox on probability theory. Almost three centuries after the St. Petersburg paradox is still debated. Two strands of research can be identified: the first, both theoretically and with surveys, examines the reasons for the subjective behavior of a player who is not willing to offer, if not a modest sum, to play a game that has an infinite expected value. The second one is the analysis by computer simulations of a large number of games, where unexpected statistical distributions emerge. From all of the studies it turns out that not only players offer very modest figures, but also that no gambling house will ever offer a St. Petersburg game.

Suggested Citation

  • Ruggero Paladini, 2017. "Il paradosso di S. Pietroburgo, una rassegna," Public Finance Research Papers 29, Istituto di Economia e Finanza, DSGE, Sapienza University of Rome.
    • Handle: RePEc:gfe:pfrp00:00029
    as

    Download full text from publisher

    File URL: https://www.dsge.uniroma1.it/sites/default/files/pubblicazioni/economia/e-pfrp29.pdf
    Download Restriction: no
    ---><---

    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. Hsu, Wen-Tai & Lu, Yi & Ng, Travis, 2014. "Does competition lead to customization?," Journal of Economic Behavior & Organization, Elsevier, vol. 106(C), pages 10-28.
    3. Yaari, Menahem E, 1987. "The Dual Theory of Choice under Risk," Econometrica, Econometric Society, vol. 55(1), pages 95-115, January.
    4. Assaf Eisdorfer & Carmelo Giaccotto, 2016. "The St. Petersburg paradox and capital asset pricing," Annals of Finance, Springer, vol. 12(1), pages 1-16, February.
    5. Eike B. Kroll & Bodo Vogt, 2009. "The St. Petersburg Paradox despite risk-seeking preferences: An experimental study," FEMM Working Papers 09004, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    6. Ruggero Paladini, 2014. "Da Bentham alla tassazione ottimale," Public Finance Research Papers 2, Istituto di Economia e Finanza, DSGE, Sapienza University of Rome.
    7. Pavlo R. Blavatskyy, 2005. "Back to the St. Petersburg Paradox?," Management Science, INFORMS, vol. 51(4), pages 677-678, April.
    8. 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.
    9. Aumann, Robert J., 1977. "The St. Petersburg paradox: A discussion of some recent comments," Journal of Economic Theory, Elsevier, vol. 14(2), pages 443-445, April.
    10. Tibor Neugebauer, 2010. "Moral Impossibility in the Petersburg Paradox : A Literature Survey and Experimental Evidence," LSF Research Working Paper Series 10-14, Luxembourg School of Finance, University of Luxembourg.
    11. Robert William, Vivian, 2013. "Ending the myth of the St Petersburg paradox," MPRA Paper 50515, University Library of Munich, Germany.
    12. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    13. repec:cup:judgdm:v:4:y:2009:i:4:p:256-272 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ruggero Paladini, 2020. "Is there a fair price in St. Petersburg repeated games? An empirical analysis," Public Finance Research Papers 44, Istituto di Economia e Finanza, DSGE, Sapienza University of Rome.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. James C. Cox & Eike B. Kroll & Marcel Lichters & Vjollca Sadiraj & Bodo Vogt, 2019. "The St. Petersburg paradox despite risk-seeking preferences: an experimental study," Business Research, Springer;German Academic Association for Business Research, vol. 12(1), pages 27-44, April.
    2. Christian Seidl, 2013. "The St. Petersburg Paradox at 300," Journal of Risk and Uncertainty, Springer, vol. 46(3), pages 247-264, June.
    3. Daniel Muller & Tshilidzi Marwala, 2019. "Relative Net Utility and the Saint Petersburg Paradox," Papers 1910.09544, arXiv.org, revised May 2020.
    4. Yukalov, V.I., 2021. "A resolution of St. Petersburg paradox," Journal of Mathematical Economics, Elsevier, vol. 97(C).
    5. Basieva, Irina & Khrennikova, Polina & Pothos, Emmanuel M. & Asano, Masanari & Khrennikov, Andrei, 2018. "Quantum-like model of subjective expected utility," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 150-162.
    6. Tibor Neugebauer, 2010. "Moral Impossibility in the Petersburg Paradox : A Literature Survey and Experimental Evidence," LSF Research Working Paper Series 10-14, Luxembourg School of Finance, University of Luxembourg.
    7. Kaivanto, Kim, 2008. "Alternation Bias and the Parameterization of Cumulative Prospect Theory," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 91-107.
    8. 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.
    9. V. I. Yukalov, 2021. "A Resolution of St. Petersburg Paradox," Papers 2111.14635, arXiv.org.
    10. Marc Scholten & Daniel Read, 2014. "Prospect theory and the “forgotten” fourfold pattern of risk preferences," Journal of Risk and Uncertainty, Springer, vol. 48(1), pages 67-83, February.
    11. Andersen, Steffen & Harrison, Glenn W. & Lau, Morten Igel & Rutström, Elisabet E., 2010. "Behavioral econometrics for psychologists," Journal of Economic Psychology, Elsevier, vol. 31(4), pages 553-576, August.
    12. Kim Kaivanto & Eike Kroll, 2014. "Alternation bias and reduction in St. Petersburg gambles," Working Papers 65600286, Lancaster University Management School, Economics Department.
    13. Salvatore Greco & Fabio Rindone, 2014. "The bipolar Choquet integral representation," Theory and Decision, Springer, vol. 77(1), pages 1-29, June.
    14. Blavatskyy, Pavlo, 2016. "Probability weighting and L-moments," European Journal of Operational Research, Elsevier, vol. 255(1), pages 103-109.
    15. Diecidue, Enrico & Schmidt, Ulrich & Zank, Horst, 2009. "Parametric weighting functions," Journal of Economic Theory, Elsevier, vol. 144(3), pages 1102-1118, May.
    16. Martín Egozcue & Luis Fuentes García & Ričardas Zitikis, 2023. "The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1369-1402, April.
    17. Steffen Andersen & James C. Cox & Glenn W. Harrison & Morten Lau & Elisabet E. Rutstroem & Vjollca Sadiraj, 2011. "Asset Integration and Attitudes to Risk: Theory and Evidence," Working Papers 2011_10, Durham University Business School.
    18. Jan V. Hansen & Rasmus H. Jacobsen & Morten I. Lau, 2016. "Willingness To Pay For Insurance In Denmark," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(1), pages 49-76, January.
    19. Pavlo R. Blavatskyy, 2016. "Risk preferences of Australian academics: where retirement funds are invested tells the story," Theory and Decision, Springer, vol. 80(3), pages 411-426, March.
    20. Benjamin Y. Hayden & Michael L. Platt, 2009. "The mean, the median, and the St. Petersburg paradox," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(4), pages 256-272, June.

    More about this item

    Keywords

    expected value; utility function; fractal distributions.;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gfe:pfrp00:00029. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Valeria De Bonis (email available below). General contact details of provider: https://edirc.repec.org/data/ierosit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.