Robustness and ambiguity in continuous time
AbstractWe use statistical detection theory in a continuous-time environment to provide a new perspective on calibrating a concern about robustness or an aversion to ambiguity. A decision maker repeatedly confronts uncertainty about state transition dynamics and a prior distribution over unobserved states or parameters. Two continuous-time formulations are counterparts of two discrete-time recursive specifications of Hansen and Sargent (2007) . One formulation shares features of the smooth ambiguity model of Klibanoff et al. (2005) and (2009)  and . Here our statistical detection calculations guide how to adjust contributions to entropy coming from hidden states as we take a continuous-time limit.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Theory.
Volume (Year): 146 (2011)
Issue (Month): 3 (May)
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Web page: http://www.elsevier.com/locate/inca/622869
Ambiguity Robustness Hidden Markov model Likelihood function Entropy Statistical detection error Smooth ambiguity;
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