系统重要性地方政府债务的识别研究

Research on the Identification of Systemically Important Local Government Debt

从规模、关联性、复杂性和跨区域性四个维度建立了系统重要性地方政府债务识别指标体系,运用熵值法和灰色关联分析法对系统重要性地方政府债务进行了识别,结果表明:各省级地方政府债务在四个维度上均具有较大的差异;熵值法赋权表明关联性指标中的地区生产总值、金融机构融资额的权重最大;熵值法和灰色关联分析法对系统重要性地方政府债务识别的结果基本一致;综合两种方法测算了各省地方政府债务系统重要性综合指数并进行了聚类分析,结果表明江苏、广东、山东、四川的地方政府债务为中国系统重要性地方政府债务。

According to the four dimensions of scale,relevance,complexity and inter regional,this paper establishes an index system of the systemically important local government debt,and,with the use of the entropy method and gray correlation analysis method,identifies the systemically important local government debt. The results are as follows: The local government debt in the four dimensions have a large difference; Entropy weighting shows that GDP and financing of financial institutions belonging to the relevance index take the maximum weight; These two methods generate basically consistent results. Based on those two methods,the paper further measures and analyzes the comprehensive systemically important local government debt index system. The results indicate that the local government debt of Jiangsu Province,Guangdong Province,Shandong Province and Sichuan Province are systemically important local government debt.