Sequential ε-Contamination with Learning

Hiroyuki Kato, Kiyohiko G. Nishimura and Hiroyuki Ozaki
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Hiroyuki Kato: Department of Management and Economics, Kaetsu University
Kiyohiko G. Nishimura: National Graduate Institute for Policy Studies (GRIPS) and CARF, University of Tokyo
Hiroyuki Ozaki: Faculty of Economics, Keio University

No CARF-F-468, CARF F-Series from Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo

Abstract: The ε-contamination has been studied extensively as a convenient and operational specification of Knightian uncertainty. However, it is formulated in a static, one-shot economic environment. This paper extends this concept into a dynamic and sequential framework, allowing learning and guaranteeing time consistency of intertemporal decision. We develop the theory of the rectangular ε-contamination, which can be represented by a sequence of ε's that "contaminates" the conditional principal probability measure. We then compare this sequential (thus closed-loop) rectangular ε-contamination with the initial-period one-shot (thus open-loop) ε-contamination, which is a straightforward extension of the static ε-contamination.

Pages: 22
Date: 2019-12
New Economics Papers: this item is included in nep-mic
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