Multi-Outcome Lotteries: Prospect Theory vs. Relative Utility
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References listed on IDEAS
- John Hey & Andrea Morone & Ulrich Schmidt, 2009.
"Noise and bias in eliciting preferences,"
Journal of Risk and Uncertainty,
Springer, vol. 39(3), pages 213-235, December.
- Hey, John Denis & Morone, Andrea & Schmidt, Ulrich, 2007. "Noise and bias in eliciting preferences," Kiel Working Papers 1386, Kiel Institute for the World Economy (IfW).
- John D Hey & Andrea Morone & Ulrich Schmidt, 2007. "Noise and Bias in Eliciting Preferences," Discussion Papers 07/04, Department of Economics, University of York.
- Kontek, Krzysztof, 2010. "Density Based Regression for Inhomogeneous Data: Application to Lottery Experiments," MPRA Paper 22268, University Library of Munich, Germany.
- Krzysztof Kontek, 2009. "Lottery valuation using the aspiration / relative utility function," Working Papers 39, Department of Applied Econometrics, Warsaw School of Economics.
- Kontek, Krzysztof, 2009. "On Mental Transformations," MPRA Paper 16516, University Library of Munich, Germany.
- Kahneman, Daniel & Tversky, Amos, 1979.
"Prospect Theory: An Analysis of Decision under Risk,"
Econometric Society, vol. 47(2), pages 263-291, March.
- Amos Tversky & Daniel Kahneman, 1979. "Prospect Theory: An Analysis of Decision under Risk," Levine's Working Paper Archive 7656, David K. Levine.
- Kontek, Krzysztof, 2010. "Mean, Median or Mode? A Striking Conclusion From Lottery Experiments," MPRA Paper 21758, University Library of Munich, Germany.
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KeywordsMulti-Prize Lotteries; Lottery / Prospect Valuation; Markowitz Hypothesis; Prospect / Cumulative Prospect Theory; Aspiration / Relative Utility Function.;
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
- D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2010-06-04 (All new papers)
- NEP-CBE-2010-06-04 (Cognitive & Behavioural Economics)
- NEP-UPT-2010-06-04 (Utility Models & Prospect Theory)
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