Artikel
A Bayesian method for characterizing population heterogeneity
A stylized fact from laboratory experiments is that there is much heterogeneity in human behavior. We present and demonstrate a computationally practical non-parametric Bayesian method for characterizing this heterogeneity. In addition, we define the concept of behaviorally distinguishable parameter vectors, and use the Bayesian posterior to say what proportion of the population lies in meaningful regions. These methods are then demonstrated using laboratory data on lottery choices and the rank-dependent expected utility model. In contrast to other analyses, we find that 79% of the subject population is not behaviorally distinguishable from the ordinary expected utility model.
- Language
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Englisch
- Bibliographic citation
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Journal: Games ; ISSN: 2073-4336 ; Volume: 10 ; Year: 2019 ; Issue: 4 ; Pages: 1-12 ; Basel: MDPI
- Classification
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Wirtschaft
Bayesian Analysis: General
Hypothesis Testing: General
Criteria for Decision-Making under Risk and Uncertainty
- Subject
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Bayesian methods
behavioral distinguishability
identifying types
population heterogeneity
rank-dependent expected utility
- Event
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Geistige Schöpfung
- (who)
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Stahl, Dale O.
- Event
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Veröffentlichung
- (who)
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MDPI
- (where)
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Basel
- (when)
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2019
- DOI
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doi:10.3390/g10040040
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Stahl, Dale O.
- MDPI
Time of origin
- 2019
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