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Classifying Behaviors in Risky Choices

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  • Kontek, Krzysztof

Abstract

This paper presents a nonparametric approach to classification of data from lottery experiments. Using very basic mathematical tools the paper endeavors to answer the questions: How to determine the “average” subject in a group? How to find a subject presenting the most similar behavior to a given one? How to detect outlier subject(s)? How to classify behaviors by their dissimilarity from the perfectly rational decision maker? How to rank subjects by risk attitudes? How to cluster subjects? This paper demonstrates that the answer to all of these questions may be found non-parametrically, without the use of any specific model.

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File URL: http://mpra.ub.uni-muenchen.de/23845/
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File URL: http://mpra.ub.uni-muenchen.de/23862/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 23845.

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Date of creation: 12 Jul 2010
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Handle: RePEc:pra:mprapa:23845

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Related research

Keywords: Lottery experiments; Certainty Equivalents; Risk Attitude; Cluster Analysis; Nonparametric Methods; Relative Utility Function.;

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  1. 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.
  2. Kontek, Krzysztof, 2010. "Multi-Outcome Lotteries: Prospect Theory vs. Relative Utility," MPRA Paper 22947, University Library of Munich, Germany.
  3. Schmidt, Ulrich & Traub, Stefan, 2009. "An experimental investigation of the disparity between WTA and WTP for lotteries," Open Access Publications from Kiel Institute for the World Economy 28786, Kiel Institute for the World Economy (IfW).
  4. Wakker,Peter P., 2010. "Prospect Theory," Cambridge Books, Cambridge University Press, number 9780521748681, April.
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