We propose a novel framework for the economic assessment of environmental policy. Our main point of departure from existing work is the adoption of a satisficing, as opposed to optimizing, modeling approach. Along these lines, we place primary emphasis on the extent to which different policies meet a set of goals at a specific future date instead of their performance vis-a-vis some intertemporal objective function. Consistent to the nature of environmental policymaking, our model takes explicit account of model uncertainty. To this end, the decision criterion we propose is an analog of the well-known success-probability criterion adapted to settings characterized by model uncertainty. We apply our criterion to the climate-change context and the probability distributions constructed by Drouet et al. (2015) linking carbon budgets to future consumption. Insights from computational geometry facilitate computations considerably and allow for the efficient application of the model in high-dimensional settings.

我们提出了一个新的环境政策经济评估框架。我们与现有工作的主要出发点是采用令人满意的，而不是优化，建模方法。沿着这些思路，我们主要强调不同政策在特定的未来日期满足一组目标的程度，而不是它们相对于某些跨期目标函数的表现。与环境决策的性质一致，我们的模型明确考虑了模型的不确定性。为此，我们提出的决策标准类似于众所周知的成功概率标准，适用于以模型不确定性为特征的设置。我们将我们的标准应用于气候变化背景和 Drouet 等人构建的概率分布。(2015) 将碳预算与未来消费联系起来。来自计算几何的见解极大地促进了计算，并允许模型在高维设置中的有效应用。