Open AccessTesting ambiguity theories with a mean‐preserving design
Author(s) -
Yang ChunLei,
Yao Lan
Publication year - 2017
Publication title -
quantitative economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.062
H-Index - 27
eISSN - 1759-7331
pISSN - 1759-7323
DOI - 10.3982/qe460
Subject(s) - ambiguity , ambiguity aversion , order (exchange) , mathematical economics , decision maker , expected utility hypothesis , monotonic function , set (abstract data type) , risk aversion (psychology) , econometrics , economics , mathematics , computer science , operations research , mathematical analysis , finance , programming language
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.