Classifying Behaviors in Risky Choices Report as inadecuate




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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 subjects? 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.



Item Type: MPRA Paper -

Original Title: Classifying Behaviors in Risky Choices-

Language: English-

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

Subjects: D - Microeconomics > D0 - General > D03 - Behavioral Microeconomics: Underlying PrinciplesD - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D81 - Criteria for Decision-Making under Risk and UncertaintyC - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: GeneralC - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical MethodsC - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data ; Data AccessC - Mathematical and Quantitative Methods > C9 - Design of Experiments > C91 - Laboratory, Individual Behavior-





Author: Kontek, Krzysztof

Source: https://mpra.ub.uni-muenchen.de/23845/







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