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Ambiguity framed

Author

Listed:
  • Mark Schneider

    (Chapman University)

  • Jonathan W. Leland

    (National Science Foundation)

  • Nathaniel T. Wilcox

    (Chapman University)

Abstract

In his exposition of subjective expected utility theory, Savage (1954) proposed that the Allais paradox could be reduced if it were recast into a format which made the appeal of the independence axiom of expected utility theory more transparent. Recent studies consistently find support for this prediction. We consider a salience-based choice model which explains this frame-dependence of the Allais paradox. We then derive the novel prediction that the presentation format responsible for reductions in Allais-style violations of expected utility theory will also reduce Ellsberg-style violations of subjective expected utility theory. This format makes the appeal of Savage’s “sure thing principle” more transparent. We design an experiment to test this prediction and find strong support for such frame-dependence of ambiguity aversion in Ellsberg-style choices. In particular, we observe markedly less ambiguity-averse behavior in Savage’s matrix format than in a more standard “prospect” format. This finding poses a new challenge for the leading models of ambiguity aversion.

Suggested Citation

  • Mark Schneider & Jonathan W. Leland & Nathaniel T. Wilcox, 2018. "Ambiguity framed," Journal of Risk and Uncertainty, Springer, vol. 57(2), pages 133-151, October.
  • Handle: RePEc:kap:jrisku:v:57:y:2018:i:2:d:10.1007_s11166-018-9290-6
    DOI: 10.1007/s11166-018-9290-6
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    • Mark Schneider & Jonathan Leland & Nathaniel T. Wilcox, 2016. "Ambiguity Framed," Working Papers 16-11, Chapman University, Economic Science Institute.

    References listed on IDEAS

    as
    1. Marciano Siniscalchi, 2009. "Vector Expected Utility and Attitudes Toward Variation," Econometrica, Econometric Society, vol. 77(3), pages 801-855, May.
    2. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Consumer Choice," Journal of Political Economy, University of Chicago Press, vol. 121(5), pages 803-843.
    3. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2012. "Salience Theory of Choice Under Risk," The Quarterly Journal of Economics, Oxford University Press, vol. 127(3), pages 1243-1285.
    4. Conlisk, John, 1989. "Three Variants on the Allais Example," American Economic Review, American Economic Association, vol. 79(3), pages 392-407, June.
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    6. Leland, Jonathan, 2010. "The hunt for a descriptive theory of choice under risk--A view from the road not taken," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 39(5), pages 568-577, October.
    7. Burke, Michael S & Carter, John R. & Gominiak, Robert D. & Ohl, Daniel F, 1996. "An Experimental Note on the Allais Paradox and Monetary Incentives," Empirical Economics, Springer, vol. 21(4), pages 617-632.
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    11. Grant, Simon & Kajii, Atsushi, 2007. "The epsilon-Gini-contamination multiple priors model admits a linear-mean-standard-deviation utility representation," Economics Letters, Elsevier, vol. 95(1), pages 39-47, April.
    12. Chew Soo Hong & Mark Ratchford & Jacob S. Sagi, 2018. "You Need to Recognise Ambiguity to Avoid It," Economic Journal, Royal Economic Society, vol. 128(614), pages 2480-2506, September.
    13. Jonathan W. Leland & Mark Schneider, 2016. "Salience, Framing, and Decisions under Risk, Uncertainty, and Time," Working Papers 16-08, Chapman University, Economic Science Institute.
    14. Nathaniel T Wilcox, 2006. "Theories of Learning in Games and Heterogeneity Bias," Econometrica, Econometric Society, vol. 74(5), pages 1271-1292, September.
    15. Botond Koszegi & Adam Szeidl, 2013. "A Model of Focusing in Economic Choice," The Quarterly Journal of Economics, Oxford University Press, vol. 128(1), pages 53-104.
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    More about this item

    Keywords

    Ellsberg paradox; Ambiguity aversion; Framing effects; Expected utility; Allais paradox; Salience theory; Independence axiom;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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