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Testing the ‘standard’ model of stochastic choice under risk

Author

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  • David Butler
  • Andrea Isoni
  • Graham Loomes

Abstract

Models of stochastic choice are intended to capture the substantial amount of noise observed in decisions under risk. We present an experimental test of one model, which many regard as the default—the Basic Fechner model. We consider one of the model’s key assumptions—that the noise around the subjective value of a risky option is independent of other features of the decision problem. We find that this assumption is systematically violated. However the main patterns in our data can be accommodated by a more recent variant of the Fechner model, or within the random preference framework. Copyright Springer Science+Business Media New York 2012

Suggested Citation

  • David Butler & Andrea Isoni & Graham Loomes, 2012. "Testing the ‘standard’ model of stochastic choice under risk," Journal of Risk and Uncertainty, Springer, vol. 45(3), pages 191-213, December.
    • Handle: RePEc:kap:jrisku:v:45:y:2012:i:3:p:191-213
    DOI: 10.1007/s11166-012-9154-4
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    References listed on IDEAS

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    1. Loomes, Graham & Moffatt, Peter G & Sugden, Robert, 2002. "A Microeconometric Test of Alternative Stochastic Theories of Risky Choice," Journal of Risk and Uncertainty, Springer, vol. 24(2), pages 103-130, March.
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    11. 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.
    12. David Butler & Andrea Isoni & Graham Loomes & Kei Tsutsui, 2014. "Beyond choice: investigating the sensitivity and validity of measures of strength of preference," Experimental Economics, Springer;Economic Science Association, vol. 17(4), pages 537-563, December.
    13. Wilcox, Nathaniel T., 2011. "'Stochastically more risk averse:' A contextual theory of stochastic discrete choice under risk," Journal of Econometrics, Elsevier, vol. 162(1), pages 89-104, May.
    14. David J. Butler & Graham C. Loomes, 2007. "Imprecision as an Account of the Preference Reversal Phenomenon," American Economic Review, American Economic Association, vol. 97(1), pages 277-297, March.
    15. Seidl, Christian, 2002. "Preference Reversal," Journal of Economic Surveys, Wiley Blackwell, vol. 16(5), pages 621-655, December.
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    18. Pavlo R. Blavatskyy & Ganna Pogrebna, 2010. "Models of stochastic choice and decision theories: why both are important for analyzing decisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(6), pages 963-986.
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    Citations

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    Cited by:

    1. Mäs, Michael & Nax, Heinrich H., 2016. "A behavioral study of “noise” in coordination games," Journal of Economic Theory, Elsevier, vol. 162(C), pages 195-208.
    2. Mäs, Michael & Nax, Heinrich H., 2016. "A behavioral study of “noise” in coordination games," LSE Research Online Documents on Economics 65422, London School of Economics and Political Science, LSE Library.
    3. Michael H. Birnbaum & Lucy Wan, 2020. "MARTER: Markov True and Error model of drifting parameters," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(1), pages 47-73, January.
    4. Graham Loomes & Ganna Pogrebna, 2014. "Testing for independence while allowing for probabilistic choice," Journal of Risk and Uncertainty, Springer, vol. 49(3), pages 189-211, December.
    5. repec:cup:judgdm:v:15:y:2020:i:1:p:47-73 is not listed on IDEAS
    6. David Butler & Andrea Isoni & Graham Loomes & Kei Tsutsui, 2014. "Beyond choice: investigating the sensitivity and validity of measures of strength of preference," Experimental Economics, Springer;Economic Science Association, vol. 17(4), pages 537-563, December.
    7. Pavlo Blavatskyy, 2018. "A Refinement of Logit Quantal Response Equilibrium," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 20(02), pages 1-14, June.

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    More about this item

    Keywords

    Choice under risk; Stochastic choice; Fechner model; Random preference; D81; C91;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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