中国宏观金融网络与风险:基于国家资产负债表数据的分析  

China's Macro-financial Network and Risk Analysis Based on National Balance Sheets

作　　者：刘磊 张晓晶 Liu Lei;Zhang Xiaojing

机构地区：[1]中国社会科学院经济研究所国家金融与发展实验室 [2]中国社会科学院金融研究所

出　　处：《世界经济》2020年第12期27-49,共23页The Journal of World Economy

基　　金：国家社会科学基金重点课题“宏观金融网络视角下的合意杠杆研究”(19AJL006);国家社会科学基金重大招标课题“宏观经济稳增长与金融系统防风险动态平衡机制研究”(19ZDA095)的阶段性成果。

摘　　要：宏观经济部门之间通过资产负债关系相互连接,形成宏观金融网络,金融风险在部门内部和部门之间通过资产负债关联进行传染,使得最终损失被放大。本文运用投入产出分析中的网络矩阵方法构建了违约风险和流动性风险的传导模型,并提出了基于部门比较的系统重要性指数以及基于全局的宏观金融风险指数等量化标准。通过最新的国家资产负债表数据分析发现,2009年以来系统性风险出现上升趋势,其中金融部门的系统重要性最高,而居民和政府部门相对独立。政策模拟表明,清理僵尸企业会产生3.8倍的乘数效应,但同时也会优化宏观金融网络结构,降低系统性风险。鉴于系统性风险自2008年起快速上升,我们建议:要坚持结构性去杠杆方向;去杠杆的重点在于调整宏观金融网络结构;在去杠杆过程中谨防处置风险的风险。Macroeconomic sectors are interconnected through financial assets and liabilities,which form a macro-financial network,and these present risk exposure within and between them through asset-liability linkages,which amplifies final losses.This paper uses the network matrix method in the input-output analysis to construct a default risk and liquidity risk contagion model,proposing quantitative standards such as a system importance index based on sectorial comparison and a global macro-financial risk index.Using the latest analysis of China’s national balance sheet data,systemic risks are found to show an upward trend since 2009.The financial sector is of the greatest systemic importance,while residents and government departments are relatively independent.Policy simulation suggests that cleaning up zombie enterprises will produce a multiplier effect of 3.8 times,but it will also optimise the macro-financial network structure and reduce systemic risks.Given the sharp increase in systemic risks since 2008,it is suggested that a continuous structural deleveraging process should be carried out that emphasizes the improvement of the macro-financial network structure and is aware of the risk caused by risk disposal.

关 键 词：宏观金融网络 金融稳定 国家资产负债表 

分 类 号：F832[经济管理—金融学]