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Baillon, A.; Cabantous, L.; Wakker, P. P. (2012)
Languages: English
Types: Article
Subjects: HD61
textabstractTwo experiments show that violations of expected utility due to ambiguity, found in general decision experiments, also affect belief aggregation. Hence we use modern ambiguity theories to analyze belief aggregation, thus obtaining more refined and empirically more valid results than traditional theories can provide. We can now confirm more reliably that conflicting (heterogeneous) beliefs where some agents express certainty are processed differently than informationally equivalent imprecise homogeneous beliefs. We can also investigate new phenomena related to ambiguity. For instance, agents who express certainty receive extra weight (a cognitive effect related to ambiguity-generated insensitivity) and generate extra preference value (source preference; a motivational effect related to ambiguity aversion). Hence, incentive compatible belief elicitations that prevent manipulation are especially warranted when agents express certainty. For multiple prior theories of ambiguity, our findings imply that the same prior probabilities can be treated differently in different contexts, suggesting an interest of corresponding generalizations.
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    • 2 See Wallsten, Forsyth, & Budescu (1983). Camerer and Weber (1992), Chow and Sarin (2001), Ellsberg (1961), Ho, Keller & Keltyka (2002, 2005), and Roca, Hogarth, & Maule (2006) studied attitudes to varying degrees of imprecise probabilities. 4 See Clemen and Winkler (1986), Cooke (1991), Curley & Yates (1989), Viscusi et al.
    • (1994), and Wallsten et al. (1997). For a discussion see Larrick and Soll (2006). Underlying theoretical models are in Gajdos et al. (2008) and Kopylov (2008).
    • Fox, Craig R. & Amos Tversky (1998) “A Belief-Based Account of Decision under Uncertainty,” Management Science 44, 879-895.
    • Gajdos, Thibault, Takashi Hayashi, Jean-Marc Tallon, & Jean-Christophe Vergnaud (2008) “Attitude towards Imprecise Information,” Journal of Economic Theory 140, 27-65.
    • Gajdos, Thibault & Jean-Christophe Vergnaud (2011) “Decisions with Conflicting and Imprecise Information,” mimeo.
    • Gayer, Gabi (2010) “Perception of Probabilities in Situations of Risk; A Case Based Approach,” Games and Economic Behavior 68, 130-143.
    • Gilboa, Itzhak (1987) “Expected Utility with Purely Subjective Non-Additive Probabilities,” Journal of Mathematical Economics 16, 65-88.
    • Gilboa, Itzhak & David Schmeidler (1989) “Maxmin Expected Utility with a NonUnique Prior,” Journal of Mathematical Economics 18, 141-153.
    • Goldstein, William M. & Hillel J. Einhorn (1987) “Expression Theory and the Preference Reversal Phenomena,” Psychological Review 94, 236-254.
    • Gul, Faruk (1991) “A Theory of Disappointment Aversion,” Econometrica 59, 667- 686.
    • Hertwig, Ralf & Andreas Ortmann (2001) “Experimental Practices in Economics: A Challenge for Psychologists?,” Behavioral and Brain Sciences 24, 383-403.
    • Ho, Joanna L.Y., L. Robin Keller, & Pamela Keltyka (2002) “Effects of Outcome and Probabilistic Ambiguity on Managerial Choices,” Journal of Risk and Uncertainty 24, 47-74.
    • Ho, Joanna L.Y., L. Robin Keller, & Pamela Keltyka (2005) “How Do Information Ambiguity and Timing of Contextual Information Affect Managers' Goal Congruence in Making Investment Decisions in Good Time vs. Bad Times,” Journal of Risk and Uncertainty 31, 163-186.
    • Hogarth, Robin M. & Hillel J. Einhorn (1990) “Venture Theory: A Model of Decision Weights,” Management Science 36, 780-803.
    • Hollard, Guillaume, Sébastien Massoni, & Jean-Christophe Vergnaud (2010), “Subjective Beliefs Formation and Elicitation Rules: Experimental Evidence,” mimeo.
    • Holt, Charles A. (2007) “Markets, Games, & Strategic Behavior.” Addison-Wesley, London.
    • Viscusi, W. Kip & William N. Evans (2006) “Behavioral Probabilities,” Journal of Risk and Uncertainty 32, 5-15.
    • Viscusi, W. Kip & Wess A. Magat (1992) “Bayesian Decisions with Ambiguous Belief Aversion,” Journal of Risk and Uncertainty 5, 371-387.
    • Viscusi, W. Kip, Wesley A. Magat, Alan Carlin, & Mark K. Dreyfus (1994) “Environmentally Responsible Energy Pricing,” The Energy Journal 15, 23-42.
    • Viscusi, W. Kip, Owen R. Phillips, & Stephan Kroll (2011) “Risky Investment Decisions: How Are Individuals Influenced by Their Groups?,” Journal of Risk and Uncertainty 43, 81-106.
    • Wakker, Peter P. (2010) “Prospect Theory: for Risk and Ambiguity.” Cambridge University Press, Cambridge, UK.
    • Wallsten, Thomas S., David V. Budescu, Ido Erev, & Adele Diederich (1997) “Evaluating and Combining Subjective Probability Estimates,” Journal of Behavioral Decision Making 10, 243-268.
    • Wallsten, Thomas S., Barbara H. Forsyth, & David V. Budescu (1983) “Stability and Coherence of Health Experts' Upper and Lower Subjective Probabilities about Dose-Response Functions,” Organizational Behavior and Human Performance 31, 277-302.
    • Weber, Elke U. (1994) “From Subjective Probabilities to Decision Weights: The Effects of Asymmetric Loss Functions on the Evaluation of Uncertain Outcomes and Events,” Psychological Bulletin 115, 228-242.
    • Winkler, Robert L. (1972) “An Introduction to Bayesian Inference and Decision Theory.” Holt, Rinehart and Winston, New York.
    • Wu, George & Richard Gonzalez (1999) “Nonlinear Decision Weights in Choice under Uncertainty,” Management Science 45, 74-85.
    • Yates, J. Frank, Paul C. Price, Ju-Whei Lee, & James Ramirez (1996) “Good Probabilistic Forecasters: The “Consumer's” Perspective,” International Journal of Forecasting 12, 41-56.
    • Zeckhauser, Richard & Kip W. Viscusi (1990) “Risk with Reason,” Science 248 no. 4955, 559-564.
    • Zimper, Alexander & Alexander Ludwig (2009) “On Attitude Polarization under Bayesian Learning with Non-Additive Beliefs,” Journal of Risk and Uncertainty 39, 181-212.
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