Risk Assessment of Government Debt Based on Machine Learning Algorithm
Government debt risk is an important factor affecting macroeconomic stability and public expectation. The key to its prevention and control lies in early warning and early prevention. This paper builds an effective government debt risk assessment system based on machine learning algorithm. According...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/3686692 |
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| _version_ | 1832561530899529728 |
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| author | Dan Chen |
| author_facet | Dan Chen |
| author_sort | Dan Chen |
| collection | DOAJ |
| description | Government debt risk is an important factor affecting macroeconomic stability and public expectation. The key to its prevention and control lies in early warning and early prevention. This paper builds an effective government debt risk assessment system based on machine learning algorithm. According to forming the performance of local government debt risk and its internal and external influencing factors, this study applies the analytic hierarchy process, entropy method, and BP neural network method to construct the local government risk assessment index system, which includes the primary and secondary indexes including the explicit debt risk, the contingent implicit debt risk, and the financial and economic operation risk. Using this system, this study carries on the government debt risk comprehensive weight assignment, the fiscal revenue forecast, the default probability calculation, the safety scale forecast, and finally the government debt risk assessment of the validity analysis. The system can provide signal guidance and policy reference for finance to cope with risks in advance, arrange the priority order of debt repayment, optimize the structure of fiscal revenue and expenditure, etc. |
| format | Article |
| id | doaj-art-cfda372c18d34a35a39ebd16ea270e90 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-cfda372c18d34a35a39ebd16ea270e902025-02-03T01:24:49ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/36866923686692Risk Assessment of Government Debt Based on Machine Learning AlgorithmDan Chen0Finance Office, Henan Institute of Economics and Trade, Zhengzhou 450018, ChinaGovernment debt risk is an important factor affecting macroeconomic stability and public expectation. The key to its prevention and control lies in early warning and early prevention. This paper builds an effective government debt risk assessment system based on machine learning algorithm. According to forming the performance of local government debt risk and its internal and external influencing factors, this study applies the analytic hierarchy process, entropy method, and BP neural network method to construct the local government risk assessment index system, which includes the primary and secondary indexes including the explicit debt risk, the contingent implicit debt risk, and the financial and economic operation risk. Using this system, this study carries on the government debt risk comprehensive weight assignment, the fiscal revenue forecast, the default probability calculation, the safety scale forecast, and finally the government debt risk assessment of the validity analysis. The system can provide signal guidance and policy reference for finance to cope with risks in advance, arrange the priority order of debt repayment, optimize the structure of fiscal revenue and expenditure, etc.http://dx.doi.org/10.1155/2021/3686692 |
| spellingShingle | Dan Chen Risk Assessment of Government Debt Based on Machine Learning Algorithm Complexity |
| title | Risk Assessment of Government Debt Based on Machine Learning Algorithm |
| title_full | Risk Assessment of Government Debt Based on Machine Learning Algorithm |
| title_fullStr | Risk Assessment of Government Debt Based on Machine Learning Algorithm |
| title_full_unstemmed | Risk Assessment of Government Debt Based on Machine Learning Algorithm |
| title_short | Risk Assessment of Government Debt Based on Machine Learning Algorithm |
| title_sort | risk assessment of government debt based on machine learning algorithm |
| url | http://dx.doi.org/10.1155/2021/3686692 |
| work_keys_str_mv | AT danchen riskassessmentofgovernmentdebtbasedonmachinelearningalgorithm |