Optimal Learning and Ellsberg’s Urns

Larry Epstein and Shaolin Ji ()
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Shaolin Ji: Institute of Financial Studies, Shandong University

No WP2017-010, Boston University - Department of Economics - Working Papers Series from Boston University - Department of Economics

Abstract: We consider the dynamics of learning under ambiguity when learning is costly and is chosen optimally. The setting is Ellsberg’s two-urn thought experiment modified by allowing the agent to postpone her choice between bets so that she can learn about the composition of the ambiguous urn. Signals are modeled by a diffusion process whose drift is equal to the true bias of the ambiguous urn and they are observed at a constant cost per unit time. The resulting optimal stopping problem is solved and the effect of ambiguity on the extent of learning is determined. It is shown that rejection of learning opportunities can be optimal for an ambiguity averse agent even given a small cost.

Keywords: ambiguity; learning; partial information; optimal stopping; drift-diffusion model (search for similar items in EconPapers)
Pages: 26 pages
Date: 2017-08
New Economics Papers: this item is included in nep-exp, nep-mic and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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