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Learning Under Ambiguity

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Author Info

  • Larry Epstein

    ()
    (University of Rochester)

  • Martin Schneider

    ()
    (New York University)

Abstract

This paper considers learning when the distinction between risk and ambiguity matters. It first describes thought experiments, dynamic variants of those provided by Ellsberg, that highlight a sense in which the Bayesian learning model is extreme - it models agents who are implausibly ambitious about what they can learn in complicated environments. The paper then provides a generalization of the Bayesian model that accommodates the intuitive choices in the thought experiments. In particular, the model allows decision-makers’ confidence about the environment to change — along with beliefs — as they learn. A calibrated portfolio choice application shows how this property induces a trend towards more stock market participation and investment.

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File URL: http://rcer.econ.rochester.edu/RCERPAPERS/rcer_527.pdf
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Bibliographic Info

Paper provided by University of Rochester - Center for Economic Research (RCER) in its series RCER Working Papers with number 527.

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Length: 35 pages
Date of creation: Apr 2006
Date of revision:
Handle: RePEc:roc:rocher:527

Contact details of provider:
Postal: University of Rochester, Center for Economic Research, Department of Economics, Harkness 231 Rochester, New York 14627 U.S.A.

Related research

Keywords: ambiguity; learning; noisy signals; ambiguous signals; quality information; portfolio choice; portfolio diversification; Ellsberg Paradox;

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References

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