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作 者:王周伟[1] 赵启程 李方方 WANG Zhou-wei;ZHAO Qi-cheng;LI Fang-fang(School of Finance and Business,Shanghai Normal University,Shanghai 200234,China)
机构地区:[1]上海师范大学商学院
出 处:《中国软科学》2019年第12期81-95,共15页China Soft Science
基 金:国家自然科学基金面上项目《结构变化中银行系统性金融风险的多维多重传染研究》(71973098);教育部人文社科规划基金项目(17YJA790075)《空间网络视域中的地方政府债务系统性风险评估研究》
摘 要:区域经济网络关联会引致风险空间溢出传染。就网络关联框架中如何测度风险价值,本文构建公共经济风险价值模型,分析地方政府债务风险形成的高度复杂网络关联特征,利用空间面板杜宾模型的分位数回归,估算地方政府债务风险价值,分解测度出空间溢出与反馈传染效应,识别出系统重要性因素及系统重要性地区和系统脆弱性地区。研究发现:空间分位数回归模型和普通分位数回归模型测算的VaR值均通过了有效性检验,但地方政府债务风险之间存在着显著的高度复杂网络关联传染,空间分位数回归模型对VaR值的估算效果优于普通分位数回归模型;系统重要性因素的总效应较大,主要有城镇化水平、债务负担率与政府刚性支出等;系统重要性地方政府多集中于华东地区;而系统脆弱性地区多集中于西部地区。这为地方政府债务系统性信用风险实施分类宏观审慎监管提供了一些思路。Regional economic network association can cause risk spatial spillover contagion. On how to measure Value-at-Risk in the framework of network correlation, this paper builds a public economic Value-at-Risk model based on spatial correlation, analyses the spatial characteristics of the formation of local government debt risk, estimates the value of local government debt risk by using quantile regression of spatial econometric model, decomposes and measures the spatial spillover contagion effect, and identifies the important factors of the system and the important areas and vulnerable areas of the system. The results show that: the VaR calculated by the spatial quantile regression model and the ordinary quantile regression model have passed the accuracy test, but the local government debt risk has obvious spatial spillover contagion, and the spatial quantile regression model is better than the ordinary quantile regression model in estimating the VaR values;the total effect of the systemic important factors is larger, mainly urbanization level, debt negative. The system importance of local governments is mostly concentrated in the eastern region, while the system vulnerability areas are mostly concentrated in the western region. This provides some ideas for macroprudential supervision of systemic credit risk of local government debt.
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