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The internal consistency of the standard gamble: tests after adjusting for prospect theory

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  • Oliver, Adam

Abstract

This article reports a study that tests whether the internal consistency of the standard gamble can be improved upon by incorporating loss weighting and probability transformation parameters in the standard gamble valuation procedure. Five alternatives to the standard EU formulation are considered: (1) probability transformation within an EU framework; and, within a prospect theory framework, (2) loss weighting and full probability transformation, (3) no loss weighting and full probability transformation, (4) loss weighting and no probability transformation, and (5) loss weighting and partial probability transformation. Of the five alternatives, only the prospect theory formulation with loss weighting and no probability transformation offers an improvement in internal consistency over the standard EU valuation procedure.

Suggested Citation

  • Oliver, Adam, 2003. "The internal consistency of the standard gamble: tests after adjusting for prospect theory," LSE Research Online Documents on Economics 159, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:159
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    1. Attema, Arthur E. & Brouwer, Werner B.F. & l’Haridon, Olivier, 2013. "Prospect theory in the health domain: A quantitative assessment," Journal of Health Economics, Elsevier, vol. 32(6), pages 1057-1065.
    2. L. M. Lamers & C. A. M. Bouwmans & A. van Straten & M. C. H. Donker & L. Hakkaart, 2006. "Comparison of EQ‐5D and SF‐6D utilities in mental health patients," Health Economics, John Wiley & Sons, Ltd., vol. 15(11), pages 1229-1236, November.
    3. Brazier, J, 2005. "Current state of the art in preference-based measures of health and avenues for further research," MPRA Paper 29762, University Library of Munich, Germany.
    4. John Brazier & Christopher McCabe, 2007. "‘Is there a case for using visual analogue scale valuations in CUA’ by Parkin and Devlin a response: ‘yes there is a case, but what does it add to ordinal data?’," Health Economics, John Wiley & Sons, Ltd., vol. 16(6), pages 645-647, June.
    5. Adam Oliver, 2006. "On the lottery equivalents method: a response to Spencer et al," Health Economics, John Wiley & Sons, Ltd., vol. 15(3), pages 323-325, March.
    6. Stefan A. Lipman & Werner B.F. Brouwer & Arthur E. Attema, 2019. "QALYs without bias? Nonparametric correction of time trade‐off and standard gamble weights based on prospect theory," Health Economics, John Wiley & Sons, Ltd., vol. 28(7), pages 843-854, July.
    7. Han Bleichrodt & Jose Maria Abellan-Perpiñan & Jose Luis Pinto-Prades & Ildefonso Mendez-Martinez, 2007. "Resolving Inconsistencies in Utility Measurement Under Risk: Tests of Generalizations of Expected Utility," Management Science, INFORMS, vol. 53(3), pages 469-482, March.
    8. A. Spencer & J. Covey & S. Chilton & M. Taylor, 2005. "Testing the internal consistency of the lottery equivalents method using health outcomes: a comment to Oliver," Health Economics, John Wiley & Sons, Ltd., vol. 14(2), pages 161-167, February.
    9. Adam Oliver, 2018. "Your money and your life: Risk attitudes over gains and losses," Journal of Risk and Uncertainty, Springer, vol. 57(1), pages 29-50, August.
    10. Craig, Benjamin M. & Oppe, Mark, 2010. "From a different angle: A novel approach to health valuation," Social Science & Medicine, Elsevier, vol. 70(2), pages 169-174, January.
    11. Jose Mª Abellán Perpiñán & Fernando Ignacio Sánchez Martínez & Jorge Eduardo Martínez Pérez & Ildefonso Méndez Martínez, 2009. "The QALY model wich came in from a general population survey: roughly multiplicative, broadly nonlinear and sometimes contex-dependt," Economic Working Papers at Centro de Estudios Andaluces E2009/04, Centro de Estudios Andaluces.
    12. Adam Oliver, 2005. "Testing the internal consistency of the lottery equivalents method using health outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 14(2), pages 149-159, February.
    13. Arthur E. Attema & Han Bleichrodt & Peter P. Wakker, 2012. "A Direct Method for Measuring Discounting and QALYs More Easily and Reliably," Medical Decision Making, , vol. 32(4), pages 583-593, July.
    14. José María Abellán Perpiñán & Fernando Ignacio Sánchez Martínez & Jorge Eduardo Martínez Pérez & Ildefonso Méndez, 2012. "Lowering The ‘Floor’ Of The Sf‐6d Scoring Algorithm Using A Lottery Equivalent Method," Health Economics, John Wiley & Sons, Ltd., vol. 21(11), pages 1271-1285, November.
    15. Stefan A. Lipman & Werner B. F. Brouwer & Arthur E. Attema, 2019. "A QALY loss is a QALY loss is a QALY loss: a note on independence of loss aversion from health states," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(3), pages 419-426, April.
    16. Oliver, Adam, 2018. "Your money and your life: risk attitudes over gains and losses," LSE Research Online Documents on Economics 88583, London School of Economics and Political Science, LSE Library.
    17. Kharroubi, Samer & Brazier, John E. & O'Hagan, Anthony, 2007. "Modelling covariates for the SF-6D standard gamble health state preference data using a nonparametric Bayesian method," Social Science & Medicine, Elsevier, vol. 64(6), pages 1242-1252, March.

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    More about this item

    Keywords

    Standard gamble; Expected utility theory; Prospect theory; Loss aversion; Probability transformation. JEL classification codes: C90; D81; I10;
    All these keywords.

    JEL classification:

    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • I10 - Health, Education, and Welfare - - Health - - - General

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