Small worlds: Modeling attitudes toward sources of uncertainty

Chew, Soo Hong; Sagi, Jacob S.

doi:10.1016/j.jet.2007.07.004

Cited by 175 publications

(121 citation statements)

References 27 publications

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“…Source Preference of Chew and Sagi (2008) Chew and Sagi's (2008) model directly distinguishes among the even-chance bets from the three primitive sources of uncertainty in our experimental design: pure risk derived from the known composition of half red and half black in {50}, full ambiguity based on the unknown compositions of red and black in [0 100] A , and additionally the all-red or allblack ambiguity in {0 100} A . These three sources generate 50-50 probabilities that may be differentiated in terms of preference.…”

Section: A2 Recursive Rank-dependent Utilitymentioning

confidence: 99%

“…In contrast, it is possible for general non-expected utility preferences, for example, quadratic preference (Chew, Epstein, and Segal (1991)), to exhibit non-monotone behavior in interval and two-point ambiguity. See Chew, Miao, and Zhong (2013) for a discussion of Chew and Sagi's (2008) source preference model without reduction.…”

Section: A2 Recursive Rank-dependent Utilitymentioning

confidence: 99%

“…In line with Chew and Sagi's (2008) source preference approach, Abdellaoui, Baillon, Placido, and Wakker (2011) proposed a model with a source-dependent probability weighting function in conjunction with a cumulative prospect theory specification. As in the preceding exposition of source-dependent SEU, being silent on how compound lotteries may be evaluated in the absence of RCLA, this model exhibits considerable flexibility in modeling choice behavior in our setting and can distinguish among the three main sources of uncertainty should we take the view that each partial ambiguity lottery itself represents a possibly distinct source.…”

Section: A2 Recursive Rank-dependent Utilitymentioning

confidence: 99%

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Partial Ambiguity

Chew¹,

Miao²,

Zhong³

2017

Econometrica

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We extend Ellsberg's two‐urn paradox and propose three symmetric forms of partial ambiguity by limiting the possible compositions in a deck of 100 red and black cards in three ways. Interval ambiguity involves a symmetric range of 50 − n to 50 + n red cards. Complementarily, disjoint ambiguity arises from two nonintersecting intervals of 0 to n and 100 − n to 100 red cards. Two‐point ambiguity involves n or 100 − n red cards. We investigate experimentally attitudes towards partial ambiguity and the corresponding compound lotteries in which the possible compositions are drawn with equal objective probabilities. This yields three key findings: distinct attitudes towards the three forms of partial ambiguity, significant association across attitudes towards partial ambiguity and compound risk, and source preference between two‐point ambiguity and two‐point compound risk. Our findings help discriminate among models of ambiguity in the literature.

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Section: A2 Recursive Rank-dependent Utilitymentioning

confidence: 99%

Section: A2 Recursive Rank-dependent Utilitymentioning

confidence: 99%

Section: A2 Recursive Rank-dependent Utilitymentioning

confidence: 99%

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Partial Ambiguity

Chew¹,

Miao²,

Zhong³

2017

Econometrica

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“…As noted by , it is impossible to apply de Finetti's de…nition of subjective probability in this situation, even under an assumption that the decision maker is risk neutral. 7 The relevance of the quantity u 00 (x)=u 0 (x) as a measure of local risk aversion was independently discovered by de Finetti (1952), Pratt (1964), and Arrow (1965).…”

Section: Risk Neutral Probabilities and Their Derivativesmentioning

confidence: 99%

Risk, ambiguity, and state-preference theory

Nau

2011

Econ Theory

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The state-preference framework for modeling choice under uncertainty, in which objects of choice are allocations of wealth or commodities across states of the world, is a natural one for modeling "smooth" ambiguityaverse preferences. It does not require reference to objective probabilities, personalistic consequences, or counterfactual acts, and it allows for statedependence of utility and unobservable background risk. The decision maker's local beliefs are encoded in her risk neutral probabilities (her relative marginal rates of substitution between states) and her local risk preferences are encoded in the matrix of derivatives of the risk neutral probabilities. This matrix plays a central but generally unappreciated role in the modeling of risk attitudes in the state-preference framework. It can be computed by inverting a bordered Slutsky matrix and vice versa, it generalizes the Arrow-Pratt measure for approximating local risk premia, and its structure reveals whether the decision maker's risk preferences are ambiguity-averse as well as risk averse. Two versions of the smoothambiguity model are analyzed-the source-dependent risk aversion model and the second-order uncertainty (KMM) model-and it is shown that in both cases the overall premium for local uncertainty can be decomposed as the sum of a risk premium and an ambiguity premium.

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“…Subjects may prefer to keep control over the resolution of uncertainty, as well as display preferences for no control (paying to be released from having to choose the numbers), and preferences for randomization (paying to let a coin toss decide who will pick the numbers). Li (2011) attributes his results to preferences for different sources of uncertainty (Chew and Sagi, 2008;Tversky and Wakker, 1995) rather than to illusion of control. 2 One possible explanation for this striking difference in findings is that the literature in experimental economics has been restricted to one type only of illusion of control, obtained by giving subjects (illusory) control over the resolution of uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Click‘n’Roll: No Evidence of Illusion of Control

Filippin¹,

Crosetto²

2016

De Economist

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Evidence of Illusion of Control -the fact that people believe to have control over pure chance events -is a recurrent finding in experimental psychology. Results in economics find instead little to no support. In this paper we test whether this dissonant result across disciplines is due to the fact that economists have implemented only one form of illusory control. We identify and separately tests in an incentive-compatible design two types of control: a) over the resolution of uncertainty, as usually done in the economics literature, and b) over the choice of the lottery, as sometimes done in the psychology literature but without monetary payoffs. Results show no evidence of illusion of control, neither on choices nor on beliefs about the likelihood of winning. JEL Classifications: B49; C91; D81

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Small worlds: Modeling attitudes toward sources of uncertainty

Cited by 175 publications

References 27 publications

Partial Ambiguity

Partial Ambiguity

Risk, ambiguity, and state-preference theory

Click‘n’Roll: No Evidence of Illusion of Control

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