TY - JOUR
T1 - Do people maximize quantiles?
AU - de Castro, Luciano
AU - Galvao, Antonio F.
AU - Noussair, Charles N.
AU - Qiao, Liang
N1 - Funding Information:
The authors would like to express their appreciation to James Cox, Ernan Haruvy, Tibor Neugebauer, Julian Romero, Vjollca Sadiraj, Stefan Zeisberger and participants at Georgia State University, Michigan State University, and the Virtual Experimental Finance Workshop for helpful comments and discussions. We especially thank Glenn Harrison for providing us with a number of very valuable comments and suggestions. We would also like to thank the Economic Science Laboratory at the University of Arizona for funding. Luciano de Castro acknowledges the support of the National Council for Scientific and Technological Development – CNPq .
Funding Information:
The authors would like to express their appreciation to James Cox, Ernan Haruvy, Tibor Neugebauer, Julian Romero, Vjollca Sadiraj, Stefan Zeisberger and participants at Georgia State University, Michigan State University, and the Virtual Experimental Finance Workshop for helpful comments and discussions. We especially thank Glenn Harrison for providing us with a number of very valuable comments and suggestions. We would also like to thank the Economic Science Laboratory at the University of Arizona for funding. Luciano de Castro acknowledges the support of the National Council for Scientific and Technological Development ? CNPq.
Publisher Copyright:
© 2021 Elsevier Inc.
PY - 2022/3
Y1 - 2022/3
N2 - Quantiles are used for decision making in investment analysis and in the mining, oil and gas industries. However, it is unknown how common quantile-based decision making actually is among typical individual decision makers. This paper describes an experiment that aims to (1) compare how common is decision making based on quantiles relative to expected utility maximization, and (2) estimate risk attitude parameters under the assumption of quantile preferences. The experiment has two parts. In the first part, individuals make pairwise choices between risky lotteries, and the competing models are fitted to the choice data. In the second part, we directly elicit a decision rule from a menu of alternatives. The results show that a quantile preference model outperforms expected utility for 32%–55%, of participants, depending on the metric. The majority of individuals are risk averse, and women are more risk averse than men, under both models.
AB - Quantiles are used for decision making in investment analysis and in the mining, oil and gas industries. However, it is unknown how common quantile-based decision making actually is among typical individual decision makers. This paper describes an experiment that aims to (1) compare how common is decision making based on quantiles relative to expected utility maximization, and (2) estimate risk attitude parameters under the assumption of quantile preferences. The experiment has two parts. In the first part, individuals make pairwise choices between risky lotteries, and the competing models are fitted to the choice data. In the second part, we directly elicit a decision rule from a menu of alternatives. The results show that a quantile preference model outperforms expected utility for 32%–55%, of participants, depending on the metric. The majority of individuals are risk averse, and women are more risk averse than men, under both models.
KW - Experiment
KW - Quantile preference
KW - Risk attitude
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U2 - 10.1016/j.geb.2021.11.010
DO - 10.1016/j.geb.2021.11.010
M3 - Article
AN - SCOPUS:85120685789
SN - 0899-8256
VL - 132
SP - 22
EP - 40
JO - Games and Economic Behavior
JF - Games and Economic Behavior
ER -