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Generalized Partition and Subjective Filtration

dc.contributor.author Dillenberger, D
dc.contributor.author Sadowski, Philipp
dc.date.accessioned 2016-12-07T14:47:27Z
dc.date.available 2016-12-07T14:47:27Z
dc.date.issued 2012-09-13
dc.identifier.uri https://hdl.handle.net/10161/13228
dc.description.abstract We study an individual who faces a dynamic decision problem in which the process of information arrival is unobserved by the analyst, and hence should be identified from observed choice data. An information structure is objectively describable if signals correspond to events of the objective state space. We derive a representation of preferences over menus of acts that captures the behavior of a Bayesian decision maker who expects to receive such signals. The class of information structures that can support such a representation generalizes the notion of a partition of the state space. The representation allows us to compare individuals in terms of the preciseness of their information structures without requiring that they share the same prior beliefs. We apply the model to study an individual who anticipates gradual resolution of uncertainty over time. Both the filtration (the timing of information arrival with the sequence of partitions it induces) and prior beliefs are uniquely identified.
dc.format.extent 30 pages
dc.relation.ispartof Economic Research Initiatives at Duke (ERID)
dc.subject Resolution of uncertainty
dc.subject valuing binary bets more
dc.subject generalized partition
dc.subject subjective filtration
dc.title Generalized Partition and Subjective Filtration
dc.type Journal article
pubs.issue 132
pubs.organisational-group Duke
pubs.organisational-group Economics
pubs.organisational-group Trinity College of Arts & Sciences


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