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Price-based vs. quantity-based environmental regulation under Knightian uncertainty: An info-gap robust satisficing perspective

机译:骑士不确定性下基于价格与基于数量的环境监管:信息鸿沟稳健的满足视角

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Conventional wisdom among environmental economists is that the relative slopes of the marginal social benefit and marginal social cost functions determine whether a price-based or quantity-based environmental regulation leads to higher expected social welfare. We revisit the choice between price-based vs. quantity-based environmental regulation under Knightian uncertainty; that is, when uncertainty cannot be modeled with known moments of probability distributions. Under these circumstances, the policy objective cannot be to maximize the expected net benefits of emissions control. Instead, we evaluate an emissions tax and an aggregate abatement standard in terms of maximizing the range of uncertainty under which the welfare loss from error in the estimates of the marginal benefits and costs of emissions control can be limited. The main result of our work is that the same criterion involving the relative slopes of the marginal benefit and cost functions determines whether price-based or quantity-based control is more robust to unstructured uncertainty. Hence, not only does the relative slopes criterion lead to the policy that maximizes the expected net benefits of control under structured uncertainty, it also leads to the policy that maximizes robustness to unstructured uncertainty.
机译:环境经济学家的传统观点是,边际社会收益和边际社会成本函数的相对斜率决定着基于价格的还是基于数量的环境监管会导致更高的预期社会福利。我们重新审视了Knightian不确定性下基于价格的环境监管和基于数量的环境监管之间的选择;也就是说,当不确定性无法用概率分布的已知时刻建模时。在这种情况下,政策目标不能是使排放控制的预期净收益最大化。相反,我们根据最大不确定性范围来评估排放税和总减排标准,在不确定性范围内可以限制边际效益和排放控制成本估算中的错误所造成的福利损失。我们工作的主要结果是,涉及边际收益和成本函数的相对斜率的相同标准决定了基于价格的控制还是基于数量的控制对于非结构化不确定性是否更健壮。因此,相对斜率准则不仅会导致在结构化不确定性条件下最大化预期控制净收益的政策,而且还会导致对非结构化不确定性最大化鲁棒性的政策。

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