Source preference and ambiguity aversion: models and evidence from behavioral and neuroimaging experiments

The Anscombe-Aumann (AA) model, originally introduced to give a normative basis to expected utility, is nowadays mostly used for another purpose: to analyze deviations from expected utility due to ambiguity (unknown probabilities). The AA model makes two ancillary assumptions that do not refer to ambiguity: expected utility for risk and backward induction. These assumptions, even if normatively appropriate, fail descriptively. This paper relaxes these ancillary assumptions to avoid the descriptive violations, while maintaining AA's convenient mixture operation. Thus, it becomes possible to test and apply all AA-based ambiguity theories descriptively while avoiding confounds due to violated ancillary assumptions. The resulting tests use only simple stimuli, avoiding noise due to complexity. We demonstrate the latter in a simple experiment where we find that three assumptions about ambiguity, commonly made in AA theories, are violated: reference independence, Han Bleichrodt and Horst Zank made useful comments. An anonymous referee substantially improved the paper. Electronic supplementary materialThe online version of this article (https://doi.org/10.1007/s11166-018-9273-7) contains supplementary material, which is available to authorized users.

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“…7 See Chew et al (2008), Kahneman and Tversky (1975 pp. 30-33), Nau (2006), Neilson (2010), and Skiadas' (2015 source-dependent theory).…”

Section: Background (Substantive and Ancillary Assumptions) And Outlinementioning

confidence: 99%

Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications

Trautmann

Wakker

2018

J Risk Uncertain

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“…27 Instruction details and further data summary are provided in the Appendix. 26 See also Huettel, Stowe, Gordon, Warner, and Platt (2006), Chew, Li, Chark, and Zhong (2008), and Dolan (2007). 27 This does not mean that subjects who chose B do not understand the draw-twice design.…”

Section: Evidence About Comprehension On the Ambiguous Urnmentioning

confidence: 99%

Testing ambiguity theories with a mean-preserving design

Yang

Yao

2017

Quantitative Economics

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Prominent models such as maxmin expected utility/alpha‐multiprior (MEU/ α‐MP) and Klibanoff, Marinacci, and Mukerji (KMM) interpret ambiguity aversion as aversion against second‐order risks associated with ambiguous acts. We design an experiment where the decision maker draws twice with replacement in the typical Ellsberg two‐color urns, but with a different color winning each time. Given this set of mean‐preserving prospects, MEU/α‐MP, KMM, and Savage's subjective expected utility all predict unequivocally that risk‐averse decision makers (DMs) will avoid the 50–50 urn that exhibits the highest risk conceivable, while risk‐seeking DMs do the opposite. However, we observe a substantial number of violations in the experiments. It appears that the ambiguity premium is partially paid to avoid the ambiguity issue per se, which is distinct from notions of second‐order risk. This finding is robust even when there is only partial ambiguity, and is applicable to all models that satisfy a monotonicity condition.

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“…His Section 3 criticizes KMM for deviating from multiple priors. Chew et al (2008) provided a static alternative, with no stages, to recursive utility. It distinguished between different sources of events (subgroups of events), assuming expected utility within each source, and taking utility source dependent.…”

Section: An Intuitive Objectionmentioning

confidence: 99%