当代财经 ›› 2019, Vol. 0 ›› Issue (06): 1819-.

• • 上一篇    

中国地方政府债务风险预警体系研究——基于层次分析法与熵值法分析

沈雨婷,金洪飞   

  1. (上海财经大学 金融学院,上海 200433)
  • 收稿日期:2019-01-27 发布日期:2021-01-21
  • 作者简介:沈雨婷,上海财经大学博士研究生,主要从事地方政府债务风险研究;金洪飞,上海财经大学教授,博士生导师,博士,主要从事金融危机研究,通讯作者联系方式jinhf@mail.shufe.edu.cn。

Research on China’s Local Government Debt Risk Early Warning System: Based on Analytic Hierarchy Process and Entropy Method Analysis

SHEN Yu-ting, JIN Hong-fei   

  • Received:2019-01-27 Published:2021-01-21

摘要: 近年来,中国地方政府债务风险问题突出,债务风险的评估及预警备受关注。通过构建基于综合指标的地方政府债务风险预警体系,对中国地方政府债务进行了经验分析。研究发现,中国地方政府债务风险总体上可控,但平均风险水平呈现略微上升趋势,部分省级地方政府风险等级有明显提高。一方面,北上广以及长三角地区因为经济增长潜力大、偿债能力强,风险等级最低;另一方面,北部及中部地区的部分省份,在隐性债务问题及融资需求等压力下,风险较高。因此,应当重视对地方政府隐性债务的清查与管理,建立有效风险预警机制,以便及时监测、防范和有针对性地化解地方政府债务风险。

关键词: 地方政府债务,债务风险,风险预警体系,综合指标

Abstract: In recent years, the problem of China’s local government debt risk is becoming prominent, and the assessment of and early warning against debt risks are receiving much attention. Through constructing a local government debt risk early warning system based on the comprehensive indicators, this paper makes an empirical analysis of China’s local government debts. The findings show that China’s local government debt risk is generally controllable, but the average risk level shows a slight upward trend, and the risk levels of some provincial-level local governments have been increased. On the one hand, Beijing, Shanghai, Guangdong and the Yangtze River Delta region have the lowest risk level because of their large economic growth potential and strong solvency; on the other hand, some provinces in the northern and central regions have higher risk levels under the pressure of hidden debt problems and financing needs. Therefore, we should pay attention to the check and management of the hidden debts of local governments, and establish an effective risk early warning mechanism, so as to timely monitor, prevent and specifically address local government debt risks.

Key words: local government debt; debt risk; risk warning system; comprehensive indicators