摘要
“十三五”期间,我国防范化解金融风险攻坚战取得决定性成就,而在“十四五”规划开局之际,我国的金融风险形势面临新的挑战,防范风险仍是金融业的永恒主题。在此背景下,本文采用相对重要性分析技术方法,考察机构规模以及相关基本面因素对我国上市金融机构尾部风险的贡献程度。接着,本文结合边际效应分析技术考察机构规模对风险的异质性效应,深入分析“太大而不能倒”假说在中国的适用性。在此基础上,进一步运用前沿的面板平滑转换估计模型,研究机构规模与尾部风险的非线性关系,并分析基本面因素对该异质性效应的影响力度。研究结果表明,我国上市银行等金融机构规模的增加能够有效缓释我国金融系统的尾部风险,但该影响效应将随着特许权价值、资产质量、杠杆水平、成本水平、收入结构、贷款结构等基本面指标的变化而出现显著的非线性转变。在此基础上,对强化我国金融系统中的风险防控薄弱环节、提高金融机构的风险吸收能力提出建议,以期为我国深化金融业改革开放、推动高质量发展提供理论分析与实证检验的参考依据。
Small financial institutions frequently encounter tail risk events such as insolvency and significant decline in asset quality in the post-crisis period. These events challenge the traditional supervisory concept of "too big to fail." There is currently growing uncertainty in the capital market and increasing economic downward pressure. The Chinese capital market is also undergoing accelerating reform. It is therefore academically and practically important to investigate the intrinsic tie between bank size and tail risk and to explore the determinants of tail risk.This paper complements and expands the literature with a high level of originality. First, most domestic literature addresses risk contagion between financial institutions. There is little discussion of whether the "too big to fail" theory can be applied under China’s actual economic conditions. Second, there is currently little consensus regarding the direction of effect of bank size on tail risk. The literature suggests that the fundamental variables of financial institutions actually play an important role in this relationship(Buch et al., 2019). Research highlights the need to include fundamental variables in the model to evaluate the heterogenous impacts of institution size on risk-taking more efficiently. Third, linear baseline regression models are often used when researching driving factors of tail risk. However, examining the relationships among variables under the traditional linear empirical framework may result in great bias, as indicated by Acemoglu et al.(2015) and De Vita et al.(2018). This bias makes it difficult to identify the risk sources in the financial system. Finally, research is likely to overlook the fact that the economic reform process exhibits an incremental trajectory in China when analyzing the nonlinear interconnectedness among variables. It is therefore more appropriate to discuss the smooth evolution of tail risk in China under the panel smooth transition regression(PSTR) model. Our sample consists of 44 Chinese listed
作者
杨子晖
陈雨恬
林师涵
关子桓
YANG Zihui;CHEN Yutian;LIN Shihan;GUAN Zihuan(Lingnan College,Sun Yat-Sen University;Institute of Advanced Finance,Sun Yat-Sen University)
出处
《金融研究》
CSSCI
北大核心
2021年第3期38-57,共20页
Journal of Financial Research
基金
2017年度国家社会科学基金重大项目“基于结构性数据分析的我国系统性金融风险防范体系研究”(项目批准号:17ZDA073)的资助
