IDEAS home Printed from https://ideas.repec.org/p/yor/yorken/99-31.html
   My bibliography  Save this paper

Which Error Theory is Best?

Author

Listed:
  • John Hey
  • Enrica Carbone

Abstract

Two recent papers, Harless and Camerer (1994) and Hey and Orme (1994), are both addressed to the same question: which is the `best' theory of decision making under risk? As an essential part of their separate approaches to an answer to this question, both sets of authors had to make an assumption about the underlying stochastic nature of their data. In this context this implied an assumption about the `errors' made by the subjects in the experiments generating the data under analysis. The two different sets of authors adopted different assumptions: the purpose of this current paper is to compare and contrast these two different error stories - in an attempt to discover which of the two is `best'.

Suggested Citation

  • John Hey & Enrica Carbone, "undated". "Which Error Theory is Best?," Discussion Papers 99/31, Department of Economics, University of York.
  • Handle: RePEc:yor:yorken:99/31
    as

    Download full text from publisher

    File URL: https://www.york.ac.uk/media/economics/documents/discussionpapers/1999/9931.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John D. Hey & Chris Orme, 2018. "Investigating Generalizations Of Expected Utility Theory Using Experimental Data," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 3, pages 63-98, World Scientific Publishing Co. Pte. Ltd..
    2. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    3. Harless, David W & Camerer, Colin F, 1994. "The Predictive Utility of Generalized Expected Utility Theories," Econometrica, Econometric Society, vol. 62(6), pages 1251-1289, November.
    4. Shugan, Steven M, 1980. "The Cost of Thinking," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 7(2), pages 99-111, Se.
    5. Enrica Carbone & John D. Hey, 2018. "Discriminating between Preference Functionals: A Preliminary Monte Carlo Study," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 4, pages 99-118, World Scientific Publishing Co. Pte. Ltd..
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Gul, Faruk, 1991. "A Theory of Disappointment Aversion," Econometrica, Econometric Society, vol. 59(3), pages 667-686, May.
    8. Viscusi, W Kip, 1989. "Prospective Reference Theory: Toward an Explanation of the Paradoxes," Journal of Risk and Uncertainty, Springer, vol. 2(3), pages 235-263, September.
    9. Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
    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. Andrea Morone, 2008. "Comparison of Mean-Variance Theory and Expected-Utility Theory through a Laboratory Experiment," Economics Bulletin, AccessEcon, vol. 3(40), pages 1-7.
    2. Michael Moutoussis & Raymond J Dolan & Peter Dayan, 2016. "How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-17, July.
    3. John Hey, 2018. "Comparing Theories: What Are We Looking For?," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 14, pages 331-352, World Scientific Publishing Co. Pte. Ltd..

    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. Kontek, Krzysztof, 2015. "Fanning-Out or Fanning-In? Continuous or Discontinuous? Estimating Indifference Curves Inside the Marschak-Machina Triangle using Certainty Equivalents," MPRA Paper 63965, University Library of Munich, Germany.
    2. Belianin, A., 2017. "Face to Face to Human Being: Achievements and Challenges of Behavioral Economics," Journal of the New Economic Association, New Economic Association, vol. 34(2), pages 166-175.
    3. Krzysztof Kontek, 2018. "Boundary effects in the Marschak-Machina triangle," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(6), pages 587-606, November.
    4. repec:cup:judgdm:v:13:y:2018:i:6:p:587-606 is not listed on IDEAS
    5. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    6. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    7. 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.
    8. John Hey, "undated". "Experiments and the Economics of Individual Decision Making Under Risk and Uncertainty," Discussion Papers 95/49, Department of Economics, University of York.
    9. Zachary Breig, 2020. "Prediction and Model Selection in Experiments," The Economic Record, The Economic Society of Australia, vol. 96(313), pages 153-176, June.
    10. Coelho, Philip R. P. & McClure, James E., 1998. "Social context and the utility of wealth: Addressing the Markowitz challenge," Journal of Economic Behavior & Organization, Elsevier, vol. 37(3), pages 305-314, November.
    11. Levy, Haim & Levy, Moshe, 2002. "Experimental test of the prospect theory value function: A stochastic dominance approach," Organizational Behavior and Human Decision Processes, Elsevier, vol. 89(2), pages 1058-1081, November.
    12. James Andreoni & Charles Sprenger, 2011. "Uncertainty Equivalents: Testing the Limits of the Independence Axiom," NBER Working Papers 17342, National Bureau of Economic Research, Inc.
    13. Pavlo Blavatskyy, 2018. "A second-generation disappointment aversion theory of decision making under risk," Theory and Decision, Springer, vol. 84(1), pages 29-60, January.
    14. Liang Zou, 2006. "An Alternative to Prospect Theory," Annals of Economics and Finance, Society for AEF, vol. 7(1), pages 1-28, May.
    15. Blavatskyy, Pavlo R., 2012. "The Troika paradox," Economics Letters, Elsevier, vol. 115(2), pages 236-239.
    16. Ulrich Schmidt, 2001. "Lottery Dependent Utility: a Reexamination," Theory and Decision, Springer, vol. 50(1), pages 35-58, February.
    17. Simone Cerreia‐Vioglio & David Dillenberger & Pietro Ortoleva, 2015. "Cautious Expected Utility and the Certainty Effect," Econometrica, Econometric Society, vol. 83, pages 693-728, March.
    18. Bocqueho, Geraldine & Jacquet, Florence & Reynaud, Arnaud, 2011. "Expected Utility or Prospect Theory Maximizers? Results from a Structural Model based on Field-experiment Data," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114257, European Association of Agricultural Economists.
    19. Simone Cerreia-Vioglio & David Dillenberger & Pietro Ortoleva & Gil Riella, 2019. "Deliberately Stochastic," American Economic Review, American Economic Association, vol. 109(7), pages 2425-2445, July.
      • Simone Cerreia-Vioglio & David Dillenberger & Pietro Ortoleva & Gil Riella, 2012. "Deliberately Stochastic," PIER Working Paper Archive 17-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 May 2017.
    20. Thomas Epper & Helga Fehr-Duda & Adrian Bruhin, 2011. "Viewing the future through a warped lens: Why uncertainty generates hyperbolic discounting," Journal of Risk and Uncertainty, Springer, vol. 43(3), pages 169-203, December.
    21. Riddel, Mary C. & Shaw, W. Douglass, 2006. "A Theoretically-Consistent Empirical Non-Expected Utility Model of Ambiguity: Nuclear Waste Mortality Risk and Yucca Mountain," Pre-Prints 23964, Texas A&M University, Department of Agricultural Economics.

    More about this item

    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:yor:yorken:99/31. 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: Paul Hodgson (email available below). General contact details of provider: https://edirc.repec.org/data/deyoruk.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.