Dynamic Quotas with Learning
Copyright policy )Dynamic Quotas with Learning
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.
- University of California United States
- University of California, Berkeley United States
- University of California, Santa Barbara United States
searching, quotas, asymmetric infonnation, searching, abatement cost, benefit-cost analysis, information theory, pollution, probabilities, quotas, asymmetric infonnation
searching, quotas, asymmetric infonnation, searching, abatement cost, benefit-cost analysis, information theory, pollution, probabilities, quotas, asymmetric infonnation
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