Eliciting ambiguity aversion in unknown and in compound lotteries: a smooth ambiguity model experimental study

Attanasi, Giuseppe; Gollier, Christian; Montesano, Aldo; Pace, Noemi

doi:10.1007/s11238-013-9406-z

Cited by 30 publications

(17 citation statements)

References 52 publications

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“…The way we relate ambiguity to confidence is also in line with Attanasi, et al (2014)'s belief elicitation under ambiguity [11], where ambiguity is generated in a two-stage setting à la Klibanoff, et al (2005) [12] by relying on different "external" sources in the first stage (i.e., binomial distribution, uniform distribution, unknown distribution) at a between-subject level. Each external source is generated by a common mechanism of uncertainty at a within-subject level.…”

Section: Introductionsupporting

confidence: 59%

Measuring and Disentangling Ambiguity and Confidence in the Lab

Cagno

Grieco

2019

Games

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In this paper we present a novel experimental procedure aimed at better understanding the interaction between confidence and ambiguity attitudes in individual decision making. Different ambiguity settings not only can be determined by the lack of information in possible scenarios completely “external” to the decision-maker, but can also be a consequence of the decision maker’s ignorance about her own characteristics or performance and, thus, deals with confidence. We design a multistage experiment where subjects face different sources of ambiguity and where we are able to control for self-assessed levels of competence. By means of a Principal Component Analysis, we obtain a set of measures of “internal” and “external” ambiguity aversion. Our regressions show that the two measures are significantly correlated at the subject level, that the subjects’ “internal” ambiguity aversion increases in performance in the high-competence task and that “external” ambiguity aversion moderately increases in earnings. Self-selection does not play any role.

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Section: Introductionsupporting

confidence: 59%

Measuring and Disentangling Ambiguity and Confidence in the Lab

Cagno

Grieco

2019

Games

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“… 4 A related paper by Attanasi et al (2014) tests the behavioral predictions of the smooth model using several decision tasks with varying levels of ambiguity (perceived ambiguity). …”

mentioning

confidence: 99%

Estimating ambiguity preferences and perceptions in multiple prior models: Evidence from the field

et al. 2015

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We develop a tractable method to estimate multiple prior models of decision-making under ambiguity. In a representative sample of the U.S. population, we measure ambiguity attitudes in the gain and loss domains. We find that ambiguity aversion is common for uncertain events of moderate to high likelihood involving gains, but ambiguity seeking prevails for low likelihoods and for losses. We show that choices made under ambiguity in the gain domain are best explained by the α-MaxMin model, with one parameter measuring ambiguity aversion (ambiguity preferences) and a second parameter quantifying the perceived degree of ambiguity (perceptions about ambiguity). The ambiguity aversion parameter α is constant and prior probability sets are asymmetric for low and high likelihood events. The data reject several other models, such as MaxMin and MaxMax, as well as symmetric probability intervals. Ambiguity aversion and the perceived degree of ambiguity are both higher for men and for the college-educated. Ambiguity aversion (but not perceived ambiguity) is also positively related to risk aversion. In the loss domain, we find evidence of reflection, implying that ambiguity aversion for gains tends to reverse into ambiguity seeking for losses. Our model’s estimates for preferences and perceptions about ambiguity can be used to analyze the economic and financial implications of such preferences.

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“…Finally, the smooth ambiguity model has been used in important asset demand analyses, such as 1 Ghirardato (2004), p. 36. 2 Camerer and Weber (1992) and Attanasi, Gollier, Montesano, and Pace (2014) and the references cited therein.…”

Section: Introductionmentioning

confidence: 99%

The Identification of Attitudes towards Ambiguity and Risk from Asset Demand

Polemarchakis

Selden²,

Song

2017

SSRN Journal

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Individuals behave differently when they know the objective probability of events and when they do not. The smooth ambiguity model accommodates both ambiguity (uncertainty) and risk. For an incomplete, competitive asset market, we develop a revealed preference test for asset demand to be consistent with the maximization of smooth ambiguity preferences; and we show that ambiguity preferences constructed from finite observations converge to underlying ambiguity preferences as observations become dense. Subsequently, we give sufficient conditions for the asset demand generated by smooth ambiguity preferences to identify the ambiguity and risk indices as well as the ambiguity probability measure. We do not require ambiguity beliefs to be observable: in a generalized specification, they may not even be defined. An ambiguity free asset plays an important role for identification.

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Eliciting ambiguity aversion in unknown and in compound lotteries: a smooth ambiguity model experimental study

Cited by 30 publications

References 52 publications

Measuring and Disentangling Ambiguity and Confidence in the Lab

Measuring and Disentangling Ambiguity and Confidence in the Lab

Estimating ambiguity preferences and perceptions in multiple prior models: Evidence from the field

The Identification of Attitudes towards Ambiguity and Risk from Asset Demand

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