Probability and Risk: Foundations and Economic Implications of Probability-Dependent Risk Preferences

Fehr-Duda, Helga; Epper, Thomas

doi:10.1146/annurev-economics-080511-110950

Cited by 142 publications

(100 citation statements)

References 100 publications

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“…Directly comparing MEU and DEU yields a clear verdict in favor of the Dual (p < 0.001, Clarke test). This reflects the fact that for the stake sizes here employed, variation of risk preferences across the probabilistic dimension is much more important than variation across stakes (Fehr-Duda and Epper 2012). This could change when stakes get truly important-an issue to which we will return in experiment 2.…”

Section: Fitting Prospect Theory Parametersmentioning

confidence: 95%

Accommodating stake effects under prospect theory

Bouchouicha

Vieider

2017

J Risk Uncertain

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One of the stylized facts underlying prospect theory is a fourfold pattern of risk preferences. People have been shown to be risk seeking for small probability gains and large probability losses, while being risk averse for large probability gains and small probability losses. Another fourfold pattern of risk preferences over outcomes, postulated by Harry Markowitz in 1952, has received much less attention and is currently not integrated into prospect theory. In two experiments, we show that risk preferences may change over outcomes. While we find people to be risk seeking for small outcomes, this turns to risk neutrality and later risk aversion as stakes increase. We then show how a one-parameter logarithmic utility function fits such stake effects significantly better under prospect theory than the power or exponential functions mostly used when fitting prospect theory models. We further investigate the extent to which the use of ill-suited functional forms to represent utility may result in violations of prospect theory, and whether such violations disappear when using logarithmic utility.

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Section: Fitting Prospect Theory Parametersmentioning

confidence: 95%

Accommodating stake effects under prospect theory

Bouchouicha

Vieider

2017

J Risk Uncertain

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“…Experimental evidence suggests that the probability weighting function is systematically affected by specific characteristics of the decision situation, whereas the curvature of the utility function is not (Fehr-Duda and Epper 2012). For example, departures from linear weighting are more pronounced for more emotional consequences such as an electric shock than for less emotional consequences such as a financial payment (Rottenstreich and Hsee 2001), and high-stake prospects are evaluated less optimistically than low-stake prospects (Fehr-Duda et al 2010).…”

Section: Decision Under Described Ambiguitymentioning

confidence: 99%

Beware of black swans: Taking stock of the description–experience gap in decision under uncertainty

et al. 2014

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Uncertainty pervades most aspects of life. From selecting a new technology to choosing a career, decision makers rarely know in advance the exact outcomes of their decisions. Whereas the consequences of decisions in standard decision theory are explicitly described (the decision from description (DFD) paradigm), the consequences of decisions in the recent decision from experience (DFE) paradigm are learned from Mark Lett (2014) experience. In DFD, decision makers typically overrespond to rare events. That is, rare events have more impact on decisions than their objective probabilities warrant (overweighting). In DFE, decision makers typically exhibit the opposite pattern, underresponding to rare events. That is, rare events may have less impact on decisions than their objective probabilities warrant (underweighting). In extreme cases, rare events are completely neglected, a pattern known as the "Black Swan effect." This contrast between DFD and DFE is known as a description-experience gap. In this paper, we discuss several tentative interpretations arising from our interdisciplinary examination of this gap. First, while a source of underweighting of rare events in DFE may be sampling error, we observe that a robust description-experience gap remains when these factors are not at play. Second, the residual description-experience gap is not only about experience per se but also about the way in which information concerning the probability distribution over the outcomes is learned in DFE. Econometric error theories may reveal that different assumed error structures in DFD and DFE also contribute to the gap.

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“…Yet, there has been some controversy on whether the fact itself that individuals purchase insurance for such small risk at a price that is twice the expected loss can be considered consistent with EU theory, especially in light of the relatively small estimates of absolute risk aversion; see, e.g., Camerer (2000), Rabin andThaler (2001), andFehrDuda andEpper (2012).…”

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confidence: 99%

Estimating Risk Preferences in the Field

Barseghyan

Molinari

O’Donoghue

et al. 2018

Journal of Economic Literature

109

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We survey the literature on estimating risk preferences using field data. We concentrate our attention on studies in which risk preferences are the focal object and estimating their structure is the core enterprise. We review a number of models of risk preferences—including both expected utility (EU) theory and non-EU models—that have been estimated using field data, and we highlight issues related to identification and estimation of such models using field data. We then survey the literature, giving separate treatment to research that uses individual-level data (e.g., property-insurance data) and research that uses aggregate data (e.g., betting-market data). We conclude by discussing directions for future research. ( JEL C51, D11, D81, D82, D83, G22, I13)

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Probability and Risk: Foundations and Economic Implications of Probability-Dependent Risk Preferences

Cited by 142 publications

References 100 publications

Accommodating stake effects under prospect theory

Accommodating stake effects under prospect theory

Beware of black swans: Taking stock of the description–experience gap in decision under uncertainty

Estimating Risk Preferences in the Field

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