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Stochastic models for risky choices: A comparison of different axiomatizations

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  • Dagsvik, John K.

Abstract

For a long time researchers have recognized the need for applying stochastic models for analyzing data generated from agents’ choice under risk. This paper compares and discusses recent axiomatizations of stochastic models for risky choice given by Blavatskyy (2008) and Dagsvik (2008). We show that some of Blavatskyy’s axioms are equivalent to some of Dagsvik’s axioms. We also propose new axioms and derive their implications. Specifically, we show that some of the results of Dagsvik (2008) can be derived under weaker axioms than those he proposed originally.

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  • Dagsvik, John K., 2015. "Stochastic models for risky choices: A comparison of different axiomatizations," Journal of Mathematical Economics, Elsevier, vol. 60(C), pages 81-88.
    • Handle: RePEc:eee:mateco:v:60:y:2015:i:c:p:81-88
    DOI: 10.1016/j.jmateco.2015.06.013
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    References listed on IDEAS

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    1. Fishburn, Peter C, 1978. "A Probabilistic Expected Utility Theory of Risky Binary Choices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 19(3), pages 633-646, October.
    2. Loomes, Graham & Sugden, Robert, 1998. "Testing Different Stochastic Specifications of Risky Choice," Economica, London School of Economics and Political Science, vol. 65(260), pages 581-598, November.
    3. Pavlo Blavatskyy, 2013. "A Simple Behavioral Characterization of Subjective Expected Utility," Operations Research, INFORMS, vol. 61(4), pages 932-940, August.
    4. Daniel McFadden, 2001. "Economic Choices," American Economic Review, American Economic Association, vol. 91(3), pages 351-378, June.
    5. Pavlo R. Blavatskyy, 2011. "A Model of Probabilistic Choice Satisfying First-Order Stochastic Dominance," Management Science, INFORMS, vol. 57(3), pages 542-548, March.
    6. Dagsvik, John K., 2008. "Axiomatization of stochastic models for choice under uncertainty," Mathematical Social Sciences, Elsevier, vol. 55(3), pages 341-370, May.
    7. Machina, Mark J, 1985. "Stochastic Choice Functions Generated from Deterministic Preferences over Lotteries," Economic Journal, Royal Economic Society, vol. 95(379), pages 575-594, September.
    8. Pavlo Blavatskyy, 2012. "Probabilistic choice and stochastic dominance," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 50(1), pages 59-83, May.
    9. Karni, Edi & Schmeidler, David, 1991. "Utility theory with uncertainty," Handbook of Mathematical Economics, in: W. Hildenbrand & H. Sonnenschein (ed.), Handbook of Mathematical Economics, edition 1, volume 4, chapter 33, pages 1763-1831, Elsevier.
    10. Graham Loomes & Inmaculada Rodríguez-Puerta & Jose-Luis Pinto-Prades, 2014. "Comment on “A Model of Probabilistic Choice Satisfying First-Order Stochastic Dominance” by Pavlo Blavatskyy," Management Science, INFORMS, vol. 60(5), pages 1346-1350, May.
    11. Faruk Gul & Wolfgang Pesendorfer, 2006. "Random Expected Utility," Econometrica, Econometric Society, vol. 74(1), pages 121-146, January.
    12. 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.
    13. John Dagsvik, 2013. "Justification of functional form assumptions in structural models: a correction," Theory and Decision, Springer, vol. 75(1), pages 79-83, July.
    14. Iverson, G. & Falmagne, J. -C., 1985. "Statistical issues in measurement," Mathematical Social Sciences, Elsevier, vol. 10(2), pages 131-153, October.
    15. Blavatskyy, Pavlo R., 2008. "Stochastic utility theorem," Journal of Mathematical Economics, Elsevier, vol. 44(11), pages 1049-1056, December.
    16. Silvapulle, Mervyn J., 1996. "On an F-type statistic for testing one-sided hypotheses and computation of chi-bar-squared weights," Statistics & Probability Letters, Elsevier, vol. 28(2), pages 137-141, June.
    17. Machina, Mark J, 1987. "Choice under Uncertainty: Problems Solved and Unsolved," Journal of Economic Perspectives, American Economic Association, vol. 1(1), pages 121-154, Summer.
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    Cited by:

    1. Blavatskyy, Pavlo, 2018. "Fechner’s strong utility model for choice among n>2 alternatives: Risky lotteries, Savage acts, and intertemporal payoffs," Journal of Mathematical Economics, Elsevier, vol. 79(C), pages 75-82.
    2. Matthew Ryan, 2018. "Uncertainty and binary stochastic choice," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(3), pages 629-662, May.
    3. Matthew Ryan, 2021. "Stochastic expected utility for binary choice: a ‘modular’ axiomatic foundation," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(2), pages 641-669, September.
    4. Dagsvik, John K., 2018. "Invariance axioms and functional form restrictions in structural models," Mathematical Social Sciences, Elsevier, vol. 91(C), pages 85-95.
    5. Blavatskyy, Pavlo, 2019. "Future plans and errors," Mathematical Social Sciences, Elsevier, vol. 102(C), pages 85-92.
    6. Ge, Ge & Godager, Geir, 2021. "Predicting strategic medical choices: An application of a quantal response equilibrium choice model," Journal of choice modelling, Elsevier, vol. 39(C).
    7. Dagsvik, John K, 2017. "Invariance Axioms and Functional Form Restrictions in Structural Models," Memorandum 08/2017, Oslo University, Department of Economics.

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