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Robustness and ambiguity in continuous time

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  • Hansen, Lars Peter
  • Sargent, Thomas J.

Abstract

We 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) [16]. One formulation shares features of the smooth ambiguity model of Klibanoff et al. (2005) and (2009) [24] and [25]. 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 Info

Article provided by Elsevier in its journal Journal of Economic Theory.

Volume (Year): 146 (2011)
Issue (Month): 3 (May)
Pages: 1195-1223

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Handle: RePEc:eee:jetheo:v:146:y:2011:i:3:p:1195-1223

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Web page: http://www.elsevier.com/locate/inca/622869

Related research

Keywords: Ambiguity Robustness Hidden Markov model Likelihood function Entropy Statistical detection error Smooth ambiguity;

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Cited by:
  1. Jaroslav BoroviÄka & Lars Peter Hansen, 2011. "Examining Macroeconomic Models Through the Lens of Asset Pricing," Working Papers, Becker Friedman Institute for Research In Economics 2011-012, Becker Friedman Institute for Research In Economics.
  2. Corbae, Dean & Marimon, Ramon, 2011. "Introduction to Incompleteness and Uncertainty in Economics," Journal of Economic Theory, Elsevier, Elsevier, vol. 146(3), pages 775-784, May.

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