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Beyond choice: investigating the sensitivity and validity of measures of strength of preference

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  • David Butler
  • Andrea Isoni
  • Graham Loomes
  • Kei Tsutsui

Abstract

Many experiments investigating different decision theories have relied heavily on pairwise choices between lotteries. These are easy to incentivise, but often yield only limited dichotomous information. This paper considers whether respondents’ judgments about their strength of preference (SoP) for one alternative over another can usefully supplement standard choice data. We report extensive evidence that such judgments show sensitivity to variations in question format and parameter values in the directions we should expect, not only within-subject but also between-sample. We illustrate how such judgments can usefully supplement standard pairwise choice data and enrich our understanding of observed behaviour. Copyright The Author(s) 2014

Suggested Citation

  • 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.
    • Handle: RePEc:kap:expeco:v:17:y:2014:i:4:p:537-563
    DOI: 10.1007/s10683-013-9383-7
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    References listed on IDEAS

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    1. Seidl, Christian, 2002. "Preference Reversal," Journal of Economic Surveys, Wiley Blackwell, vol. 16(5), pages 621-655, December.
    2. 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.
    3. David Buschena & David Zilberman, 2008. "Generalized expected utility, heteroscedastic error, and path dependence in risky choice," Journal of Risk and Uncertainty, Springer, vol. 36(2), pages 201-201, April.
    4. 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..
    5. 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.
    6. 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.
    7. David Butler & Andrea Isoni & Graham Loomes & Daniel Navarro-Martinez, 2014. "On the Measurement of Strength of Preference in Units of Money," The Economic Record, The Economic Society of Australia, vol. 90, pages 1-15, June.
    8. 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..
    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. Frederick Mosteller & Philip Nogee, 1951. "An Experimental Measurement of Utility," Journal of Political Economy, University of Chicago Press, vol. 59, pages 371-371.
    11. Pavlo R. Blavatskyy, 2011. "A Model of Probabilistic Choice Satisfying First-Order Stochastic Dominance," Management Science, INFORMS, vol. 57(3), pages 542-548, March.
    12. 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.
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    Citations

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    Cited by:

    1. Georgios Gerasimou, 2019. "Simple Preference Intensity Comparisons," Discussion Paper Series, School of Economics and Finance 201905, School of Economics and Finance, University of St Andrews, revised 27 Apr 2020.
    2. Fabrice Lec & Serge Macé, 2018. "The curse of hope," Theory and Decision, Springer, vol. 84(3), pages 429-451, May.
    3. Daniel Navarro-Martinez & Graham Loomes & Andrea Isoni & David Butler & Larbi Alaoui, 2018. "Boundedly rational expected utility theory," Journal of Risk and Uncertainty, Springer, vol. 57(3), pages 199-223, December.
    4. Qiu, Jianying, 2015. "Completing incomplete preferences," MPRA Paper 72933, University Library of Munich, Germany, revised 18 Jul 2016.
    5. 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.
    6. Arts, Sara & Ong, Qiyan & Qiu, Jianying, 2020. "Measuring subjective decision confidence," MPRA Paper 117907, University Library of Munich, Germany.
    7. Qiu, Jianying, 2015. "Completing incomplete preferences," MPRA Paper 91692, University Library of Munich, Germany, revised 18 Jul 2016.
    8. Arts, Sara & Ong, Qiyan & Qiu, Jianying, 2020. "Measuring subjective decision confidence," MPRA Paper 106811, University Library of Munich, Germany.
    9. Carlos Alós-Ferrer & Johannes Buckenmaier & Michele Garagnani, 2020. "Stochastic choice and preference reversals," ECON - Working Papers 370, Department of Economics - University of Zurich, revised Jul 2021.

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    More about this item

    Keywords

    Strength of preference; Risky choice; Individual decisions; Experimental methods; B40; C91; D03; D81;
    All these keywords.

    JEL classification:

    • B40 - Schools of Economic Thought and Methodology - - Economic Methodology - - - General
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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