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Estimating cumulative prospect theory parameters from an international survey


Rieger, Marc Oliver; Wang, Mei; Hens, Thorsten (2017). Estimating cumulative prospect theory parameters from an international survey. Theory and Decision, 82(4):567-596.

Abstract

We conduct a standardized survey on risk preferences in 53 countries worldwide and estimate cumulative prospect theory parameters from the data. The parameter estimates show that significant differences on the cross-country level are to some extent robust and related to economic and cultural differences. In particular, a closer look on probability weighting underlines gender differences, economic effects, and cultural impact on probability weighting. The data set is a useful starting point for future research that investigates the impact of risk preferences on the market level.

Abstract

We conduct a standardized survey on risk preferences in 53 countries worldwide and estimate cumulative prospect theory parameters from the data. The parameter estimates show that significant differences on the cross-country level are to some extent robust and related to economic and cultural differences. In particular, a closer look on probability weighting underlines gender differences, economic effects, and cultural impact on probability weighting. The data set is a useful starting point for future research that investigates the impact of risk preferences on the market level.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Banking and Finance
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Social Sciences & Humanities > General Decision Sciences
Social Sciences & Humanities > Developmental and Educational Psychology
Social Sciences & Humanities > Arts and Humanities (miscellaneous)
Social Sciences & Humanities > Applied Psychology
Social Sciences & Humanities > General Social Sciences
Social Sciences & Humanities > General Economics, Econometrics and Finance
Physical Sciences > Computer Science Applications
Language:English
Date:April 2017
Deposited On:22 Nov 2017 14:18
Last Modified:26 Jan 2022 14:13
Publisher:Springer
ISSN:0040-5833
OA Status:Closed
Publisher DOI:https://doi.org/10.1007/s11238-016-9582-8
Related URLs:http://link.springer.com/article/10.1007/s11238-016-9582-8 (Publisher)
Other Identification Number:merlin-id:14097
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