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When does ambiguity fade away?

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  • Massari, Filippo
  • Newton, Jonathan

Abstract

the prior support is finite, long-run ambiguity is known to be a possible outcome only if the learning problem is misspecified (Marinacci and Massari, 2019). We show that if the prior support is naturally rich, long-run ambiguity cannot occur.

Suggested Citation

  • Massari, Filippo & Newton, Jonathan, 2020. "When does ambiguity fade away?," Economics Letters, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:ecolet:v:194:y:2020:i:c:s0165176520302512
    DOI: 10.1016/j.econlet.2020.109404
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
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    10. Massimo Marinacci, 2002. "Learning from ambiguous urns," Statistical Papers, Springer, vol. 43(1), pages 143-151, January.
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    More about this item

    Keywords

    Ambiguity; Learning; Robust statistical decisions; Misspecified learning;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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