Classifying Behaviors in Risky Choices

Krzysztof Kontek ()

MPRA Paper from University Library of Munich, Germany

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.

Keywords: Lottery experiments; Certainty Equivalents; Risk Attitude; Cluster Analysis; Nonparametric Methods; Relative Utility Function. (search for similar items in EconPapers)
JEL-codes: C02 C14 C81 C91 D03 D81 (search for similar items in EconPapers)
Date: 2010-07-12
New Economics Papers: this item is included in nep-cbe, nep-exp and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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https://mpra.ub.uni-muenchen.de/23845/1/MPRA_paper_23845.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/23862/1/MPRA_paper_23862.pdf revised version (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:23845

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