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当前全球主权债务可持续性以及违约风险传递问题依然严峻，不确定性事件的爆发可能加剧风险的传染扩散。文章采用2008年12月至2023年10月全球35个发达和发展中国家主权债务CDS利差数据，在充分考虑多种全球金融跨市场风险的基础上，同时将经济政策不确定性和地缘政治风险作为外部风险，使用TENET模型构建非线性高维尾部风险网络关联，进而利用DMA模型考察外部风险对关联程度演变的动态影响，深化了危机时期主权债务风险传染的研究。研究结果表明：第一，重大风险发生时，主权债务市场尾部风险总关联度会显著上升，但是对于经济政策不确定性和地缘政治风险的关注可以有效削弱风险传染强度；第二，经济政策不确定性的影响力更强，特别是在金融发展稳定的时期，对于经济政策的关注可以起到降低风险溢出关联的作用，对地缘政治风险关注的提高会加剧这种关联；第三，“同区域”国家之间构成主要的主权债务风险传导路径，但近年来危机时期跨组织风险交叉互溢现象逐渐显现，其中中国主权债务市场地位有所提升，与世界各国的联系愈发紧密。
Abstract：At present, sustainability and transmission of default risk in global sovereign debt remain serious, and the outbreak of uncertain events may exacerbate risk contagion. In this paper, sovereign debt CDS spread data from 35 developed and developing countries from December 2008 to October 2023. On the basis of fully considering various global financial cross-market risks, we focus on economic policy uncertainty and geopolitical risk as key risk factors. We use TENET model to construct a non-linear high-dimensional tail risk network. Furthermore, DMA model is used to investigate dynamic influence of external risks on evolution of correlation degree, which deepens the research of sovereign debt risk contagion during crisis period. The results demonstrate that:First, when significant risks occur, the total correlation of tail risk in sovereign debt market will increase significantly, but attention to economic policy uncertainty and geopolitical risk can effectively weaken the intensity of risk contagion. Second, the influence of economic policy uncertainty is more pronounced. In particular, during stable financial development period, attention to economic policy can reduce risk spillover correlation. Conversely, rising attention to geopolitical risk tends to exacerbate this correlation. Third, countries within the same region form the main pathway for sovereign debt risk transmission. However, in recent years, cross-organizational risk spillover phenomena have become increasingly evident during crisis periods, among these, the status of China′s sovereign debt market has improved, and its connectivity with other countries worldwide has been strengthening.
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(1)限于篇幅,DMA模型的推导未予给出,备索。
(2)数据来源:地缘政治风险来源于https://www.matteoiacoviello.com/gpr.htm;经济政策不确定性来源于http://www.policyuncertainty.com/。
(3)本文利用Walktrap算法识别网络的社区结构,该方法是一种基于随机游走的社区发现算法,其中顶点之间的距离通过网络中的随机游走来测量。
(4)数据来源:国家外汇管理总局,https://www.safe.gov.cn/safe/2024/0628/24679.html。
基本信息:
DOI：10.13516/j.cnki.wes.2024.10.001
中图分类号:K901.4;F113;F811.5
引用信息:
[1]陈学彬,马瑞婷,谢妍.经济政策不确定性和地缘政治风险下全球主权债务风险关联研究[J].世界经济研究,2024,No.368(10):49-62+120+136.DOI:10.13516/j.cnki.wes.2024.10.001.
基金信息:
国家自然科学基金项目“债券违约风险智能预测系统研究——基于多源异构数据和复杂关联网络”(项目编号：72371178)的资助