低碳转型风险的“涟漪效应”  

Ripple Effect of Low-Carbon Transition Risks

作　　者：郑挺国[1] 张宏音 叶仕奇 ZHENG Ting-guo;ZHANG Hong-yin;YE Shi-qi(Center for Macroeconomic Research,Xiamen University;School of Economics,Xiamen University;The Wang Yanan Institute for Studies in Economics,Xiamen University;Center for Forecasting Science,Academy of Mathematics and Systemic Science,Chinese Academy of Sciences;Paula and Gregory Chow Institute For Studies in Economics,Xiamen University)

机构地区：[1]厦门大学宏观经济研究中心、经济学院统计与数据科学系、王亚南经济研究院 [2]厦门大学王亚南经济研究院 [3]中国科学院数学与系统科学研究院预测科学研究中心 [4]厦门大学邹至庄经济研究院

出　　处：《中国工业经济》2024年第4期37-56,共20页China Industrial Economics

基　　金：国家社会科学基金重大项目“大数据方法在宏观经济预测中的应用研究”(批准号23&ZD074);国家自然科学基金青年学生基础研究项目“多矩阵自回归模型扩展及在经济领域中的应用”(批准号723B2020)。

摘　　要：“双碳”目标背景下,有效识别并量化金融市场内的低碳转型风险,对于维护国家经济低碳转型过程中的经济金融安全以及防范系统性金融风险具有重要的现实意义。本文提出属性分类建模法,将上市公司的碳排放、贝塔系数、市值、市净率等属性特征与前沿张量自回归模型相结合,构建基于多维度属性风险关联指数和关联网络的风险传导效应分析框架,用以刻画低碳转型风险在属性结构中的“连漪效应”。结果显示:多维属性视角下,中国股票市场中的“涟漪效应”体现为具有相似属性特征的上市公司之间的风险关联效应;低碳转型风险的“连漪效应”传导中心位于“高碳排、低市净率、高市值、低贝塔”类别。随着风险逐步沿属性特征向外扩散,风险关联强度逐渐减小;中国提出“双碳”目标后,各层涟漪的风险关联强度均呈现显著上升趋势;高碳排属性是低碳转型风险“涟漪效应”的主要驱动属性,但在“双碳”目标约束下,其驱动作用向低市净率、高市值属性转移,转型风险呈现出跨属性传导的特征。本文为碳中和背景下完善适应于低碳转型风险的宏观审慎政策框架、构建低碳转型风险防治体系提供了理论依据。The issue of global climate change is of paramount importance to the community with a shared future for mankind,emerging as the most pressing global agenda.Countries worldwide have introduced emission reduction policies to propel low-carbon transition.Against the background of the"dual carbon"goal in China,effectively identifying and quantifying low-carbon transition risks within financial markets holds significant value for maintaining both economic and financial security during the low-carbon transition and for preventing systemic financial risks.Based on the tensor autoregressive(TenAR)model,this paper incorporates the fundamental principles of the Fama-French three-factor model and proposes a modeling method for listed company attribute classification.Based on the attribute classification results,this paper decomposes the return series of A-share listed companies into tensor time series.Furthermore,by estimating the frontier TenAR model,it introduces a framework for measuring risk connectedness indices and constructing risk connectedness networks tailored to different attribute structures.Additionally,this paper combines the ripple effect of the stock market with information cascades from behavioral economics to provide a theoretical foundation for the horizontal and vertical transmission of low-carbon transition risks.Based on horizontal and vertical transmission characteristics,this paper,in empirical analyses,further identifies the low-carbon transition risk transmission paths of the ripple effect,and explores their driving factors and dynamic characteristics under low-carbon policies.Research results of this paper imply a significant ripple effect in the Chinese stock market,manifested by the strong risk connectedness effect among similar attribute categories.Along the horizontal path of the ripple effect of low-carbon transition risks,the risk aggregation center lies within the category of"high carbon emission,low price-to-book,high market value,and low beta"(CE4,PBl,MV3,Betal).Along the vertical path,lo

关 键 词：低碳转型风险 属性分类法 张量自回归模型 金融风险关联网络 

分 类 号：F124[经济管理—世界经济]