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Learning in Bayesian Regulation

Koray, Semih and Saglam, Ismail (2005): Learning in Bayesian Regulation.

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Abstract

We examine the issue of learning in a generalized principal-agent model with incomplete information. We show that there are situations in which the agent prefers a Bayesian regulator to have more information about his private type. Moreover, the outcome of the Bayesian mechanism regulating the agent is path-dependent; i.e. the convergence of the regulator's belief to the truth does not always yield the complete information outcome.

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