Robustness and ambiguity in continuous time

Lars Peter Hansen, Thomas J. Sargent

    Research output: Contribution to journalArticlepeer-review


    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) [24,25]. Here our statistical detection calculations guide how to adjust contributions to entropy coming from hidden states as we take a continuous-time limit.

    Original languageEnglish (US)
    Pages (from-to)1195-1223
    Number of pages29
    JournalJournal of Economic Theory
    Issue number3
    StatePublished - May 2011


    • Ambiguity
    • Entropy
    • Hidden markov model
    • Likelihood function
    • Robustness
    • Smooth ambiguity
    • Statistical detection error

    ASJC Scopus subject areas

    • Economics and Econometrics


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