TY - JOUR
T1 - The Variable Precision Method for Elicitation of Probability Weighting Functions
AU - Chai, Junyi
AU - Ngai, Wai Ting
N1 - Funding Information:
We are grateful for the constructive comments of the referees on an earlier version of this paper. We are also indebted to Peter Wakker for his helpful comments. The first author was supported in part by Beijing Normal University-Hong Kong Baptist University United International College Research Grant under R201917 . The second author was supported in part by the RGC Collaborative Research Fund under grant numbers E-RB0E and E-RB29 . Appendix A
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2020/1
Y1 - 2020/1
N2 - This study introduces a nonparametric method to elicit decision weights under prospect theory. These weights carry the attitudes and subjective beliefs of individuals toward risks and uncertainties. Our variable precision method adopts a dynamic mechanism that can elicit the measuring points of individual probability weighting flexibly. These points are used to exhibit violations of expected utility theory, which measures individual risk attitudes and captures subjective beliefs on probabilities. Our method is flexible, tractable, and cognitively less demanding compared with other nonparametric elicitations in the literature. Experimental studies are conducted on a sample of Hong Kong (China) residents to verify our method. Our experimental results yield a prevailing inverse-S shape. We conduct the analyses and uncover their implications by comparing them with the results of residents of Beijing, Shanghai, Paris, and Amsterdam.
AB - This study introduces a nonparametric method to elicit decision weights under prospect theory. These weights carry the attitudes and subjective beliefs of individuals toward risks and uncertainties. Our variable precision method adopts a dynamic mechanism that can elicit the measuring points of individual probability weighting flexibly. These points are used to exhibit violations of expected utility theory, which measures individual risk attitudes and captures subjective beliefs on probabilities. Our method is flexible, tractable, and cognitively less demanding compared with other nonparametric elicitations in the literature. Experimental studies are conducted on a sample of Hong Kong (China) residents to verify our method. Our experimental results yield a prevailing inverse-S shape. We conduct the analyses and uncover their implications by comparing them with the results of residents of Beijing, Shanghai, Paris, and Amsterdam.
KW - Behavioral decision making
KW - Nonparametric elicitation
KW - Probability weighting
KW - Prospect theory
KW - Tradeoff method
UR - http://www.scopus.com/inward/record.url?scp=85074436436&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.dss.2019.113166
DO - https://doi.org/10.1016/j.dss.2019.113166
M3 - Journal article
SN - 0167-9236
VL - 128
JO - Decision Support Systems
JF - Decision Support Systems
M1 - 113166
ER -