Dynamic Quotas with Learning

Larry S. Karp and Christopher Costello ()

No 914, Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series from Department of Agricultural & Resource Economics, UC Berkeley

Abstract: We study the optimal quota sequence, in a stationary environment, where a regulator and a non-strategic firm have asymmetric information, The regulator is able to learn about the unknown cost parameter by using a quota that is slack with positive probability, It is never optimal for the regulator to learn gradually, In the first period, he either ignores the possibility of learning, or he tries to improve his information, Regardless of the outcome in the first period, he never experiments in subsequent periods.

Keywords: quotas; asymmetric infonnation; searching (search for similar items in EconPapers)
Date: 2000-10-18
Note: oai:cdlib1:are_ucb-1223

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Working Paper: Dynamic quotas with learning (2000)
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