Decision Under Risk

Wu, George; Zhang, Jiao; Gonzalez, Richard

doi:10.1002/9780470752937.ch20

Cited by 89 publications

(41 citation statements)

References 152 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We favor this specification because it has proven to account well for individual heterogeneity (Wu, Zhang, and Gonzalez, 2004) and the parameters are nicely interpretable. The parameter γ largely governs the slope of the curve and measures sensitivity towards changes in probability.…”

Section: Econometric Modelmentioning

confidence: 99%

Risk and Rationality: Uncovering Heterogeneity in Probability Distortion

2009

View full text Add to dashboard Cite

It has long been recognized that there is considerable heterogeneity in individual risk taking behavior but little is known about the distribution of risk taking types. We present a parsimonious characterization of risk taking behavior by estimating a finite mixture regression model for three different experimental data sets, two Swiss and one Chinese, over a large number of real gains and losses. We find two distinct types of individuals: In all three data sets, the choices of roughly 80% of the subjects exhibit significant deviations from linear probability weighting, consistent with prospect theory. 20% of the subjects weight probabilities near linearly and behave essentially as expected value maximizers. Moreover, individuals are cleanly assigned to one type with probabilities close to unity. The reliability and robustness of our classification suggest using a mix of preference theories in applied economic modeling.

show abstract

Section: Econometric Modelmentioning

confidence: 99%

Risk and Rationality: Uncovering Heterogeneity in Probability Distortion

2009

View full text Add to dashboard Cite

show abstract

“…However, there are interpretations of the processes involved in the IGT other than impaired selfcontrol that can explain impaired performance on this task, such as learning outcome probabilities of each of the decks, developing a long-term strategy (Manes et al, 2002;Wu et al, 2005), or reversal learning (Dunn et al, 2006;Fellows & Farah, 2005).…”

Section: Risk-taking Behaviormentioning

confidence: 99%

The Common Neural Basis of Exerting Self-Control in Multiple Domains

Cohen

Lieberman

2010

Self Control in Society, Mind, and Brain

118

106

View full text Add to dashboard Cite

People regularly exert control over impulsive thoughts and behaviors in order to make appropriate decisions and take appropriate actions even when they are more difficult or less pleasant than alternative choices. A common theme in mental illnesses characterized by impulsivity, such as ADHD and substance abuse, is an impaired self-control mechanism. Therefore, understanding the mechanisms underlying an intact control mechanism can not only shed light on how healthy people exert self-control over their thoughts and behaviors, but help us to understand what is impaired in patient populations as well. The right ventrolateral prefrontal cortex (VLPFC) is a region in the brain that is commonly activated when people are exerting many different forms of self-control. It is noted that other prefrontal regions also consistently activated when one exerts self-control, such as the dorsolateral prefrontal cortex, anterior cingulate cortex, orbitofrontal cortex, and medial prefrontal cortex, may be recruited for other task demands and not self-control specifically. Although the right VLPFC has been linked to other functions as well, this review will focus on the hypothesized general role that it plays during acts of self-control. There are infinite manners in which one can exert self-control. We limit our discussion to six forms of conscious, explicit control that are commonly addressed in the literature: motor response inhibition, suppressing risky behavior, delaying gratification, regulating emotion, memory inhibition, and thought suppression. First, we review the literature exploring the involvement of the right VLPFC in each type of self-control separately. Next, we explore the small amount of literature comparing different forms of self-control to each other and discuss the possibility that these forms of self-control are related constructs. We also discuss the anatomical positioning of the right VLPFC and point out that it is well suited to serving a key role in exerting self-control. Finally, we conclude that although more direct research must be conducted before firm conclusions can be made, there is evidence that the right VLPFC is utilized when exerting self-control regardless of the specific domain of control.

show abstract

“…We favor this specification because it has proven to account well for individual heterogeneity (Wu, Zhang, and Gonzalez, 2004). The parameter γ largely governs the slope of the curve, whereas the parameter δ largely governs its elevation.…”

Section: Econometric Modelmentioning

confidence: 99%

Risk and Rationality: Uncovering Heterogeneity in Probability Distortion

2010

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract It has long been recognized that there is considerable heterogeneity in individual risk taking behavior but little is known about the distribution of risk taking types. We present a parsimonious characterization of risk taking behavior by estimating a finite mixture regression model for three different experimental data sets, two Swiss and one Chinese, over a large number of real gains and losses. We find two distinct types of individuals: In all three data sets, the choices of roughly 80% of the subjects exhibit significant deviations from rational probability weighting consistent with prospect theory. 20% of the subjects weight probabilities linearly and behave essentially as expected value maximizers. Moreover, the individuals are assigned to one of these two groups with probabilities of close to one resulting in a low measure of entropy. The reliability and robustness of our classification suggest using a mix of preference theories in applied economic modeling. Terms of use: Documents in

show abstract

Decision Under Risk

Cited by 89 publications

References 152 publications

Risk and Rationality: Uncovering Heterogeneity in Probability Distortion

Risk and Rationality: Uncovering Heterogeneity in Probability Distortion

The Common Neural Basis of Exerting Self-Control in Multiple Domains

Risk and Rationality: Uncovering Heterogeneity in Probability Distortion

Contact Info

Product

Resources

About