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  5. Asymptotic Learning With Ambiguous Information

American Economic Journal:
Microeconomics

ISSN 1945-7669 (Print) | ISSN 1945-7685 (Online)

Asymptotic Learning With Ambiguous Information

  • Pëllumb Reshidi
  • João Thereze
  • Mu Zhang
American Economic Journal: Microeconomics (Forthcoming)

Abstract

We study asymptotic learning when the decision maker faces ambiguity in the precision of her information sources. She aims to estimate a state and evaluates outcomes according to the worst-case scenario. Under prior-by-prior updating, we characterize the set of asymptotic posteriors the decision maker entertains, which consists of a continuum of degenerate distributions over an interval. Moreover, her asymptotic estimate of the state is generically incorrect. We show that even a small amount of ambiguity may lead to large estimation errors and illustrate how an econometrician who learns from observing others’ actions may over- or underreact to information.

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