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Ambiguity, measurability and multiple priors
Author(s) -
Massimiliano Amarante
Publication year - 2005
Publication title -
economic theory
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.572
H-Index - 58
eISSN - 1432-0479
pISSN - 0938-2259
DOI - 10.1007/s00199-004-0559-4
Subject(s) - prior probability , mathematics , convexity , class (philosophy) , ambiguity , event (particle physics) , feature (linguistics) , mathematical economics , set (abstract data type) , measure (data warehouse) , knightian uncertainty , discrete mathematics , computer science , artificial intelligence , bayesian probability , statistics , data mining , linguistics , physics , philosophy , quantum mechanics , financial economics , economics , programming language
The paper provides a notion of measurability for Multiple Prior Models characterized by nonatomic countably additive priors. A notable feature of our definition of measurability is that an event is measurable if and only if it is unambiguous in the sense of Ghirardato, Maccheroni and Marinacci [6]. In addition, the paper contains a thorough description of the basic properties of the family of measurable/unambiguous sets, of the measure defined on those and of the dependence of the class of measurable sets on the set of priors. The latter is obtained by means of an application of Lyapunov’s convexity theorem. Copyright Springer-Verlag Berlin/Heidelberg 2005Ambiguous events, Multiple priors, Lyapunov’s convexity theorem.,

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