Classifying Behaviors in Risky Choices

17 Pages Posted: 12 Jul 2010 Last revised: 14 Jul 2010

Date Written: July 12, 2010

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 making? 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

JEL Classification: C02, C14, C81, C91, D03, D81

Suggested Citation

Kontek, Krzysztof, Classifying Behaviors in Risky Choices (July 12, 2010). Available at SSRN: https://ssrn.com/abstract=1638984 or http://dx.doi.org/10.2139/ssrn.1638984

Krzysztof Kontek (Contact Author)

Warsaw School of Economics (SGH) ( email )

aleja Niepodleglosci 162
PL-Warsaw, 02-554
Poland

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