Climate change is becoming an urgent issue for the global economy. Our study employs a multivariate extreme value regression model that incorporates a LASSO-type estimator to investigate the tail dependence of the global sovereign credit default swap market conditional on climate change. Herein, we propose an extremal connectedness measure based on tail dependence to construct a sovereign credit network. The findings show that extreme weather or climate disasters significantly impact country-specific sovereign risk with heterogeneous network structure outcomes. Specifically, extreme weather conditions have a strong impact on countries' sovereign credit and magnify their influence on the global sovereign credit network. Furthermore, we identify an asymmetric risk spillover effect in the global sovereign credit network, where the degree of risk spillover is higher under extremely hot weather conditions. Our analysis provides new insights into the role of climate change in sovereign risk.

气候变化正在成为全球经济面临的紧迫问题。我们的研究采用了一个多元极值回归模型，该模型结合了 LASSO 型估计量来研究气候变化条件下全球主权信用违约互换市场的尾部依赖性。在此，我们提出了一种基于尾部依赖的极值连通性度量来构建主权信用网络。研究结果表明，极端天气或气候灾害会显着影响具有异质网络结构结果的国家特定主权风险。具体而言，极端天气状况对各国主权信用产生强烈影响，并放大其对全球主权信用网络的影响。此外，我们确定了全球主权信用网络中的不对称风险溢出效应，在极端炎热的天气条件下，风险溢出程度更高。我们的分析为气候变化在主权风险中的作用提供了新的见解。