Zimper, Alexander2013-11-112013-11-112013-07Zimper, A 2013, 'The emergence of "fifty-fifty" probability judgments through Bayesian updating under ambiguity', Fuzzy sets and systems, vol. 223, no. 7, pp. 72-88.0165-0114 (print)1872-6801 (online)10.1016/j.fss.2012.12.007http://hdl.handle.net/2263/32337This paper explains the empirical phenomenon of persistent "fifty-fifty"probability judgments through a model of Bayesian updating under ambiguity. To this purpose I characterize an announced probability judgment as a Bayesian estimate given as the solution to a Choquet expected utility maximization problem with respect to a neo-additive capacity that has been updated in accordance with the Generalized Bayesian update rule. Only for the non-generic case, in which this capacity degenerates to an additive probability measure, the agent will learn the events true probability if the number of i.i.d. data observations gets large. In contrast, for the generic case in which the capacity is not additive, the agent's announced probability judgment becomes a persistent " fifty-fifty "probability judgment after finitely many observations.en© 2013 Elsevier. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Fuzzy sets and systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Fuzzy sets and systems, vol. 223, no. 7, 2013, doi : 10.1016/j.fss.2012.12.007LearningEconomicsNon-additive measuresDecision analysisPostprint Article