4.5 Article

Early Warning of Systemic Financial Risk of Local Government Implicit Debt Based on BP Neural Network Model

期刊

SYSTEMS
卷 10, 期 6, 页码 -

出版社

MDPI
DOI: 10.3390/systems10060207

关键词

local government implicit debt; systemic financial risks; early warning; BP neural network model

资金

  1. National Social Science Fund of China (the Funder: National Office for Philosophy and Social Sciences) [21BJY128]
  2. Social Science Fund of Sichuan Province (the Funder: the Sichuan Office of Philosophy and Social Science Program) [SC21B069]
  3. Sichuan Science and Technology Program (the Funder: Sichuan Science and Technology Department) [2022JDR0171]
  4. Spark Innovation Foundation of Sichuan University (the Funder: Sichuan University) [2018hhs-55]

向作者/读者索取更多资源

This paper uses macro and micro indicators to establish a BP neural network model, studies the contagion effect of local government hidden debt on systemic financial risks, and predicts the systemic financial risks in 2019. It also constructs an early warning risk system based on prefecture-level city data and investigates the early warning effect of local government implicit debt on systemic financial risk under different stress scenarios. The study finds that local government implicit debt risk, financing platform bank debt scale, PPP scale, and urban investment bond scale have a significant impact on systemic financial risks.
In recent years, local governments have boosted their local economies by raising large amounts of debt. Even though the state further strictly controls local government debt, the hidden debt formed by the local government borrowing in disguised form can infect systemic financial risks, creating an urgent need to carry out risk warning based on local government hidden debt. The paper uses the macro indicators of local government implicit debt risk at the prefecture-level city level, and introduces the micro indicators of PPP projects, financing platform bank debt, and urban investment debt to establish a BP neural network model. We not only study the contagion effect of local government hidden debt on systemic financial risks, but also predict the systemic financial risks in 2019 and construct an early warning risk system based on the prefecture-level city data from 2015 to 2018. In addition, the early warning effect of local government implicit debt on systemic financial risk under different stress scenarios is investigated. The study found that the implicit debt risk of local governments, the scale of financing platform bank debt, the scale of PPP, and the scale of urban investment bonds have a significant impact on systemic financial risks. The neural network model constructed by introducing these four variables at the same time can better predict the level of systemic financial risk. The model can also accurately predict the changes in systemic financial risks under the stress test of the increase in hidden debt of different local governments, and has a good early warning effect.

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