Conclusion to the Special Issue on the National Social Cost of Carbon

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a comparative analysis of Integrated Assessment Models for the National Social Cost of Carbon, highlighting model uncertainty and distributional implications across countries.

🏢実務担当者:Useful for understanding how social cost of carbon estimates vary across models and how carbon pricing might differentially affect countries and sectors.

🏛政策担当者:Informs the debate on setting the social cost of carbon for regulatory impact analysis and international climate finance contributions.

The results of five Integrated Assessment Models are discussed in this concluding paper. All the scenarios measure the National Social Cost of Carbon (NSCC) across approximately 200 countries in a scenario with no mitigation. Despite assuming similar population and economic growth rates (RFF-SPs), the five models imply a wide range of forecasted climate impacts. Summing the mean NSCC estimates of all countries leads to a mean global Social Cost of Carbon (SCC) that varies from $33/tCO 2 to $1,373/tCO 2 across the models. Most of the literature on climate IAM’s has focused on these SCC values. This special issue, in contrast, is focused on the NSCC. But the assumptions in each IAM model that led to different SCC values also determine the cumulative magnitude of the NSCC’s from each model. The discount rate, the climate damage function, and the modeling of uncertainty strongly influence the magnitude of the NSCC’s across models. What is unique to the analysis of the NSCC’s is how they are distributed across countries. The NSCC values explain how climate damages and therefore the benefits of mitigation are distributed across nations. The IAMs predict that China and especially the United States are particularly exposed to climate change due to their large asset bases. About half of the global damage is assumed to happen in the 10 largest countries in the world measured using GDP PPP. Most of the models predict every country has some damage but one model predicts 29 countries — mostly in high latitudes — will benefit from near term climate change. Regression analysis confirms that the distribution of climate damages across countries is primarily determined by the total size of the national economy. Because IAMs scale physical risks by economic exposure, they predict that two-thirds of the global climate burden is concentrated in the mid-to-high latitudes, where the majority of global economic activity is located. Finally, the IAMs predict a very wide range of NSCC values in 2100 ranging from a 40% increase to an eight-fold increase over current NSCC values, depending on structural assumptions regarding adaptation and catastrophic risk.

• semanticscholar https://doi.org/10.1142/s2010007826400051first seen 2026-06-29 08:47:49