E3S Web Conf.
Volume 235, 20212020 International Conference on New Energy Technology and Industrial Development (NETID 2020)
|Number of page(s)||6|
|Section||Industrial Technology Development and Industrial Structure Adjustment and Upgrading|
|Published online||03 February 2021|
Local government debt risk measurement and early warning structural system building — Research Based on KMV and TOPSIS Models
Tianjin Polytechnic University, Jiangsu, China
In this paper, by using the Statistical analysis Software SPSS20, 30 and Cities of our country’s local government structural debt risk has been carried on the empirical analysis, using the entropy weight method to determine the specific weight of each index, reduced the subjective factors of influence on the result of the index weight distribution, expectations of local government debt defaults and the situation of the comprehensive evaluation index of local government debt. By comparing the size of the threshold value, to determine the risk of local government debt, the results show that in 7 provinces and cities in China are in the state of no warning of local debt risk, in 10 provinces and cities are in the state of mild warning. Means and Cities are in the State of Moderate warning, In other words, it means it’s time to generate the risk of local government debt. In the State of high warning, most means and cities need to take scientific measures to generate the risk of local government debt.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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