| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w28449 |
| 来源ID | Working Paper 28449 |
| Addressing Partial Identification in Climate Modeling and Policy Analysis | |
| Charles F. Manski; Alan H. Sanstad; Stephen J. DeCanio | |
| 发表日期 | 2021-02-08 |
| 出版年 | 2021 |
| 语种 | 英语 |
| 摘要 | Numerical simulations of the global climate system provide inputs to integrated assessment modeling for estimating the impacts of greenhouse gas mitigation and other policies to address global climate change. While essential tools for this purpose, computational climate models are subject to considerable uncertainty, including inter-model “structural” uncertainty. Structural uncertainty analysis has emphasized simple or weighted averaging of the outputs of multi-model ensembles, sometimes with subjective Bayesian assignment of probabilities across models. However, choosing appropriate weights is problematic. To use climate simulations in integrated assessment, we propose instead framing climate model uncertainty as a problem of partial identification, or “deep” uncertainty. This terminology refers to situations in which the underlying mechanisms, dynamics, or laws governing a system are not completely known and cannot be credibly modeled definitively even in the absence of data limitations in a statistical sense. We propose the min-max regret (MMR) decision criterion to account for deep climate uncertainty in integrated assessment without weighting climate model forecasts. We develop a theoretical framework for cost-benefit analysis of climate policy based on MMR, and apply it computationally with a simple integrated assessment model. We suggest avenues for further research. |
| 主题 | Microeconomics ; Economics of Information ; Environmental and Resource Economics ; Environment |
| URL | https://www.nber.org/papers/w28449 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/586122 |
| 推荐引用方式 GB/T 7714 | Charles F. Manski,Alan H. Sanstad,Stephen J. DeCanio. Addressing Partial Identification in Climate Modeling and Policy Analysis. 2021. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w28449.pdf（896KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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