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分类管控下的债务风险与风险传染网络研究
更新日期:2021-06-09     浏览次数:121
核心提示:摘要防范化解重大风险,守住不发生系统性金融风险的底线是我国经济工作的重心之一。本文针对部门债务,从债务口径、债务结构和偿付风险3个层次深入研究

摘要 防范化解重大风险,守住不发生系统性金融风险的底线是我国经济工作的重心之一。本文针对部门债务,从债务口径、债务结构和偿付风险3个层次深入研究了实体经济债务风险的关键问题,提出了分类管控我国债务风险的理论模型。从部门间债务的比较分析中,本文发现非金融企业债务在实体经济债务中具有极高的系统重要性,针对这一特点,我们构建了双层交易对手方风险传染网络模型。以江苏省和山东省产业债发行人担保网为样本,基于该模型研究了区域非金融企业间债务风险传染结构,并根据综合节点度与对外风险敞口两类指标识别出若干核心风险传染节点。研究发现我国非金融企业部门内的债务间存在较强关联性,是潜在的区域系统性风险源。本文认为,我国当前的宏观债务问题存在国情特殊性,应尽快建立符合中国国情的债务风险和压力分析评估体系,为防范金融风险提供分类施策工具。 Preventing and resolving the major risks and keeping systematic risk free is one of the priorities of China's economic work.Aiming at sectoral debt,this paper studies the key issues of debt risk in the real economy from the three levels of debt caliber,debt structure and repayment risk,and proposes a theoretical model for the classified management of debt risk in China.From the comparative analysis of inter-departmental debt,this paper finds that non-financial corporate debt is systemically important in real economic debt.In response to this feature,we have constructed a two-tier counteiparty risk contagion network model.We selected Jiangsu and Shandong industrial bond isguarantee nets as samples.based on this model,we studied the risk contagion structure among suer regional non-financial companies,identifying several core risk contagious nodes by using a comprehensive indicator including node degree and external risk exposure.It is found that there is a strong correlation between the debts in China^s non-financial corporate sector,which is a potential source of regional systematic risk.This paper believes that China s current macro-debt problem has special national conditions,and a debt risk and stress evaluation system which meets China's national conditions should be established as soon as possible to provide a classified policy tool for preventing financial risks.
作者 吴德胜 曹渊 汤灿 郝希阳 Wu Desheng
机构地区 中国科学院大学
出处 《管理世界》 北大核心 2021年第4期35-51,M0004,232,共19页 Journal of Management World
基金 国家杰出青年科学基金(71825007) 中科院A类战略性先导科技专项(XDA 23020203) 中科院前沿科学重点项目(QYZDB-SSW-SYS021) 中科院国际合作项目(211211KYSB20180042)的资助 科技部国家重点研发计划(2016YFC0503606)。