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Explaining preference reversal with third-generation prospect theory


  • Ulrich Schmidt

    () (Lehrstuhl fuer Finanzmarkttheorie, Universitaet Hannover)

  • Chris Starmer

    () (School of Economics, University of Nottingham)

  • Robert Sugden

    () (School of Economic and Social Studies, University of East Anglia)


We present a new theory of decision under risk called third-generation prospect theory. A novel feature of our version of prospect theory is that, by allowing reference points to be uncertain, it is able to accommodate the phenomenon of preference reversal. While several previous theories of preference reversal have been proposed, thus far it has resisted explanation via any empirically plausible model of preferences. We investigate whether our explanation is empirically plausible. We find that the standard patterns of preference reversal are predicted for typical parameterisations of prospect theory already established in the empirical literature. Consequently we suggest that our model constitutes a best buy theory: it offers the predictive power of previous variants of prospect theory and adds to that an explanation of preference reversal. The latter comes ‘free of charge’ since it involves no extra parameters and no re-parameterisation.

Suggested Citation

  • Ulrich Schmidt & Chris Starmer & Robert Sugden, 2005. "Explaining preference reversal with third-generation prospect theory," Discussion Papers 2005-19, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
  • Handle: RePEc:not:notcdx:2005-19

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    References listed on IDEAS

    1. Loomes, Graham & Sugden, Robert, 1998. "Testing Different Stochastic Specifications of Risky Choice," Economica, London School of Economics and Political Science, vol. 65(260), pages 581-598, November.
    2. Cubitt, Robin P & Sugden, Robert, 2001. "Dynamic Decision-Making under Uncertainty: An Experimental Investigation of Choices between Accumulator Gambles," Journal of Risk and Uncertainty, Springer, vol. 22(2), pages 103-128, March.
    3. George Loewenstein & Ted O'Donoghue & Matthew Rabin, 2003. "Projection Bias in Predicting Future Utility," The Quarterly Journal of Economics, Oxford University Press, vol. 118(4), pages 1209-1248.
    4. Nicholas Bardsley & Robin Cubitt & Graham Loomes & Peter Moffatt & Chris Starmer & Robert Sugden, 2009. "Experimental Economics: Rethinking the Rules," Economics Books, Princeton University Press, edition 1, number 9074.
    5. Thierry Post & Martijn J. van den Assem & Guido Baltussen & Richard H. Thaler, 2008. "Deal or No Deal? Decision Making under Risk in a Large-Payoff Game Show," American Economic Review, American Economic Association, vol. 98(1), pages 38-71, March.
    6. Machina, Mark J, 1989. "Dynamic Consistency and Non-expected Utility Models of Choice under Uncertainty," Journal of Economic Literature, American Economic Association, vol. 27(4), pages 1622-1668, December.
    7. Michèle Cohen & Johanna Etner & Meglena Jeleva, 2008. "Dynamic Decision Making when Risk Perception Depends on Past Experience," Theory and Decision, Springer, vol. 64(2), pages 173-192, March.
    8. Robin Cubitt & Chris Starmer & Robert Sugden, 2001. "Discovered preferences and the experimental evidence of violations of expected utility theory," Journal of Economic Methodology, Taylor & Francis Journals, vol. 8(3), pages 385-414.
    9. Chris Starmer, 2000. "Developments in Non-expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk," Journal of Economic Literature, American Economic Association, vol. 38(2), pages 332-382, June.
    10. Loewenstein, George & Adler, Daniel, 1995. "A Bias in the Prediction of Tastes," Economic Journal, Royal Economic Society, vol. 105(431), pages 929-937, July.
    11. Beattie, Jane & Loomes, Graham, 1997. "The Impact of Incentives upon Risky Choice Experiments," Journal of Risk and Uncertainty, Springer, vol. 14(2), pages 155-168, March.
    12. Joseph Johnson & Jerome Busemeyer, 2001. "Multiple-Stage Decision-Making: The Effect of Planning Horizon Length on Dynamic Consistency," Theory and Decision, Springer, vol. 51(2), pages 217-246, December.
    13. 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.
    14. Graham Loomes, 2005. "Modelling the Stochastic Component of Behaviour in Experiments: Some Issues for the Interpretation of Data," Experimental Economics, Springer;Economic Science Association, vol. 8(4), pages 301-323, December.
    15. Cubitt, Robin P & Starmer, Chris & Sugden, Robert, 1998. "Dynamic Choice and the Common Ratio Effect: An Experimental Investigation," Economic Journal, Royal Economic Society, vol. 108(450), pages 1362-1380, September.
    16. Machina, Mark J, 1987. "Choice under Uncertainty: Problems Solved and Unsolved," Journal of Economic Perspectives, American Economic Association, vol. 1(1), pages 121-154, Summer.
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    Cited by:

    1. Simon Gaechter & Eric Johnson & Andreas Herrmann, 2007. "Individual-Level Loss Aversion In Riskless And Risky Choices," Discussion Papers 2007-02, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    2. Basili, Marcello & Chateauneuf, Alain & Fontini, Fulvio, 2008. "Precautionary principle as a rule of choice with optimism on windfall gains and pessimism on catastrophic losses," Ecological Economics, Elsevier, vol. 67(3), pages 485-491, October.

    More about this item


    Prospect theory; preference reversal; reference dependence;

    JEL classification:

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


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