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对模型不确定性的稳健性推动更快的二氧化碳减排

Robustness to Model Uncertainties Drives More Rapid CO2 Emissions Reductions

Lisa Rennels, Frank Errickson, David Smith, Bryan Parthum, Klaus Keller, David Anthoff

arXiv 2607.07655首次发表:更新:

AI 中文总结

研究评估气候政策经济影响时模型不确定性带来的挑战,采用稳健决策框架评估减排政策,发现从最大化预期结果转向厌恶遗憾的框架会促使更积极减排,因相关不确定性会带来不对称后果。

AI 中文摘要

评估气候政策的经济影响对设计应对气候变化的措施很重要。一种评估减排政策选项的典型方法是使用综合气候 - 经济模型来分析减少温室气体排放成本与减少气候损害效益之间的权衡。然而,这些模型的不确定性给政策制定者带来了重大挑战。我们使用稳健决策框架来评估减排政策以应对这一困难。我们表明,从最大化预期结果的决策框架转向厌恶遗憾的框架会建议更积极的减排。社会经济轨迹以及气候损害的幅度和函数形式的不确定性造成了弱减排政策的不对称后果,促使在面对不确定性时积极减排和采取预防措施。

英文摘要

Evaluating the economic impacts of climate policies is important for designing a response to climate change. One typical approach to assessing mitigation policy options uses integrated climate-economy models to analyze tradeoffs between the costs of reducing greenhouse gas emissions and the benefits of reducing climate damages. However, the uncertainty characterizing these models poses significant challenges for policymakers. We address this difficulty using a robust decision-making framework to evaluate mitigation policy. We show that a shift from a decision framework that maximizes expected outcomes to one that is averse to regret suggests more aggressive emissions reductions. Uncertainties about socioeconomic trajectories and the magnitude and functional form of climate damages create the asymmetric consequences of weak mitigation policy that encourage aggressive emissions reductions and precaution in the face of uncertainty.

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