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Judging statistical models of individual decision making under risk using in- and out-of-sample criteria

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  • Drichoutis, Andreas
  • Lusk, Jayson

Abstract

Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare two popular error specifications (Luce vs. Fechner), with and without accounting for contextual utility, for two different conceptual models (expected utility and rank-dependent expected utility) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing specifications. Overall, a mixture model combining the two conceptual models assuming Fechner error and contextual utility provides the best fit of the data both in- and out-of-sample.

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  • Drichoutis, Andreas & Lusk, Jayson, 2012. "Judging statistical models of individual decision making under risk using in- and out-of-sample criteria," MPRA Paper 38951, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:38951
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    Cited by:

    1. Drichoutis, Andreas C. & Koundouri, Phoebe, 2012. "Estimating risk attitudes in conventional and artefactual lab experiments: The importance of the underlying assumptions," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-15.
    2. Andreas C. Drichoutis & Varvara Kechagia, 2016. "The effect of olfactory sensory cues on economic decision making," Working Papers 2016-4, Agricultural University of Athens, Department Of Agricultural Economics.
    3. Tsang, Ming, 2020. "Estimating uncertainty aversion using the source method in stylized tasks with varying degrees of uncertainty," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 84(C).
    4. Kechagia, Varvara & Drichoutis, Andreas C., 2017. "The effect of olfactory sensory cues on willingness to pay and choice under risk," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 70(C), pages 33-46.
    5. Drichoutis, Andreas C. & Nayga, Rodolfo M., 2013. "Eliciting risk and time preferences under induced mood states," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 45(C), pages 18-27.
    6. Thomas Meissner & David Albrecht, 2022. "Debt Aversion: Theory and Measurement," Papers 2207.07538, arXiv.org, revised Jul 2022.
    7. Andreas C. Drichoutis & Jayson L. Lusk, 2016. "What can multiple price lists really tell us about risk preferences?," Journal of Risk and Uncertainty, Springer, vol. 53(2), pages 89-106, December.
    8. Drichoutis, Andreas C. & Nayga, Rodolfo M., 2022. "Game form recognition in preference elicitation, cognitive abilities, and cognitive load," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 49-65.
    9. Petrolia, Daniel R., 2016. "Risk preferences, risk perceptions, and risky food," Food Policy, Elsevier, vol. 64(C), pages 37-48.
    10. Thomas Meissner & Xavier Gassmann & Corinne Faure & Joachim Schleich, 2023. "Individual characteristics associated with risk and time preferences: A multi country representative survey," Journal of Risk and Uncertainty, Springer, vol. 66(1), pages 77-107, February.
    11. Maurizio Canavari & Andreas C. Drichoutis & Jayson L. Lusk & Rodolfo M. Nayga, Jr., 2018. "How to run an experimental auction: A review of recent advances," Working Papers 2018-5, Agricultural University of Athens, Department Of Agricultural Economics.
    12. Mariam Raheem & Ain ul Momina, 2021. "Do Underlying Risk Preferences explain Individuals’ Cognitive Ability? Evidence from a Sample of Pakistani Students," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 26(1), pages 85-122, Jan-June.

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    More about this item

    Keywords

    error specification; expected utility theory; experiment; probability weighting; rank dependent utility; risk;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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