کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
695479 890305 2014 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Emissions control policies under uncertainty and rational learning in a linear-state dynamic model
ترجمه فارسی عنوان
سیاست های کنترل انتشار بر اساس عدم اطمینان و یادگیری منطقی در یک مدل دینامیکی خطی وضعیت
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
چکیده انگلیسی

We compare the use of price-based policies or taxes, and quantity-based policies or quotas, for controlling emissions in a dynamic setup when the regulator faces two sources of uncertainty: (i) market-related uncertainty; and (ii) ecological uncertainty. We assume that the regulator is a rational Bayesian learner and the regulator and firms have asymmetric information. In our model the structure of Bayesian learning is general. Our results suggest that the expected level of emissions is the same under taxes and quotas. However, the comparison of the total benefits related to these policies suggests that taxes dominate quotas, that is, they provide a higher social welfare. Even though taxes have some benefits over quotas, neither learning nor ecological uncertainty affect the choice of policy, i.e., the only factor having such an impact is uncertainty in the instantaneous net emissions benefits (market-related uncertainty). Besides, the more volatile is this uncertainty, the more benefits of taxes over quotas. Ecological uncertainty leads to a difference between the emissions rule under the informed and the rational learning assumptions. However, the direction of this difference depends on the beliefs bias with regard to ecological uncertainty. We also find that a change in the regulator’s beliefs toward more optimistic views will increase the emissions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Automatica - Volume 50, Issue 3, March 2014, Pages 719–726
نویسندگان
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