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中国管理科学 ›› 2019, Vol. 27 ›› Issue (5): 1-10.doi: 10.16381/j.cnki.issn1003-207x.2019.05.001

• 论文 •    下一篇

中国企业部门信用风险溢价期限结构与宏观经济因子

张亦春1, 陈华2, 郑晓亚3   

  1. 1. 厦门大学经济学院, 福建 厦门 361005;
    2. 中国人民银行数字货币研究所, 北京 100800;
    3. 中国建设银行股份有限公司, 北京 100033
  • 收稿日期:2017-09-27 修回日期:2018-02-11 出版日期:2019-05-20 发布日期:2019-05-25
  • 通讯作者: 陈华(1984-),男(汉族),福建龙岩人,中国人民银行数字货币研究所,副研究员,研究方向:利率期限结构与货币政策,E-mail:83258975@qq.com E-mail:83258975@qq.com
  • 基金资助:

    国家自然科学基金资助项目(71703165)

The Term Structure of Credit Risk Spreads in Chinese Enterprise Sector and Macroeconomic Determinants

ZHANG Yi-chun1, CHEN Hua2, ZHENG Xiao-ya3   

  1. 1. Financial Research Institute, Xiamen University, Xiamen 361005, China;
    2. Institute of Digital Money, The People's Bank of China, Beijing 100800, China;
    3. China Construction Bank, Beijing 100033, China
  • Received:2017-09-27 Revised:2018-02-11 Online:2019-05-20 Published:2019-05-25

摘要: 近年来,中国企业部门债务风险不断暴露,其是否会引发系统性信用危机正成为焦点。本文着眼于中国企业部门信用风险累积与暴露背后的宏观经济现实,在简约模型中引入结构向量自回归模型(SVAR),将经济冲击区分为总供给冲击、总需求冲击和货币政策冲击,以此研究各宏观经济因子对中国企业部门信用风险溢价期限结构的影响特征,从而揭示中国企业部门信用风险定价的宏观经济机理。本文发现,正向的总供给冲击和货币政策冲击有助于降低中国企业部门信用风险溢价,但正向的总需求冲击则会推高中国企业部门信用风险溢价,自2011年以来持续处于高位水平的信用风险溢价的主要根源正是4万亿经济刺激计划所带来的扩张性总需求,因此欲从根本上降低中国企业部门信用风险水平,应紧缩社会总需求,并通过制度改革和结构调整,改善社会总供给。

关键词: 信用风险溢价期限结构, 宏观经济因子, 简约模型, SVAR

Abstract: The rising credit risk in China's enterprise sector has drawn significant attention on possible systematic credit crisis in China. Therefore, unfolding the relationship between credit risk and macro factors becomes an important topic for market regulators, participants and academies, which has great academic and practical significance. However, due to methodological constraints, existing researches based on Z-score models, Logistic models or Merton models have noticeable limitations on explaining such relationship. In order to improve the stability and comprehensiveness and of the research results, reduced form model is implemented which can describe the discontinuous and sudden event of default, and the credit risk pricing formula derived is more intuitive and concise, especially the default random variable is set as the exogenous driving factor, which makes the model more flexible application. Furthermore, the economic shocks are identified as aggregate supply shock, aggregate demand shock and monetary policy shock, by incorporating structural auto regression vector, and then the effect of various macroeconomic determinants is firstly investigated on the term structure of credit risk spreads in Chinese enterprise sector, thus showing how the credit risk in Chinese enterprise sector is priced from a macroeconomic perspective. It is found that, first, the total supply of the positive impact and the impact of monetary policy helped reduce the Chinese corporate sector credit risk premium, but positive aggregate demand pushed up China corporate sector credit risk premium; second, the expansion of the total demand of 4 trillion economic stimulus plan brought about by the impact, the credit risk premium in 2011 by negative reversal for it, and made it continue to maintain at a high level; third, the expansion of monetary policy from 2010 to 2011 reduced the total social demand caused by the expansion of high credit risk premium level; fourth, as money shortage occurred, Chinese corporate sector credit risk premium rose sharply, which was not caused by macroeconomic fundamentals changes, but triggered by the impact of monetary policies; fifth, from the beginning of 2010, due to Lewis inflection point, the negative total supply impact pushed the credit risk premium to slow up. Based on the empirical outcomes, it is suggested that the essential way to reduce the credit risk in Chinese enterprise sector be the reduction in aggregate social demand and the improvement in aggregate social supply via reform and restructure.

Key words: term structure of credit risk spreads, macroeconomic determinants, reduced form model, SVAR

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