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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.

Suggested Citation

  • 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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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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.
    2. 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, Kiel Institute for the World Economy (IfW), vol. 6, pages 1-15.

    More about this item

    Keywords

    error specification; expected utility theory; experiment; probability weighting; rank dependent utility; risk;

    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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