信贷扩张、房价波动与银行系统性风险——基于SVAR的实证分析

发布时间：2018-05-08 15:25

本文选题：信贷 + 房价　；参考：《金融与经济》2015年11期

【摘要】：经过对国内外文献的总结发现,银行同业拆借市场日渐成为我国系统性危机发生的结点,因此本文选择三个月同业拆借利率作为系统性风险的代理变量,构建结构向量自回归模型(SVAR),对信贷规模、房价波动与银行系统性风险三者之间的关系以及传导机制进行分析。通过格兰杰因果检验、脉冲响应以及方差分解等方法分析表明:信贷、房价与银行系统性风险三者间存在循环的影响机制。过度的信贷支持引发房价剧烈波动,进一步地引发银行系统性危机,当系统性风险上升到一定水平时,信贷规模将会受到限制。此外,信贷、房地产以及银行系统性风险三者的相互影响在第4个月达到最大,影响期限约为10个月,因此实施宏观调控应当逆向调节,且注意时滞、调控效果和影响期限。
[Abstract]:After summing up the domestic and foreign literature, it is found that the interbank lending market is becoming the node of the systemic crisis in our country, so this paper chooses the three-month interbank offered rate as the proxy variable of the systemic risk. A structural vector autoregressive model is constructed to analyze the relationship among credit scale, house price volatility and systemic risk of banks, as well as the transmission mechanism. The Granger causality test, impulse response and variance decomposition analysis show that there is a cyclic influence mechanism among credit, house price and systemic risk of banks. Excessive credit support leads to sharp fluctuations in house prices and further to a systemic crisis in banks. When systemic risk rises to a certain level, the size of credit will be limited. In addition, the mutual influence of credit, real estate and bank systemic risk reaches the maximum in the fourth month, and the influence period is about 10 months. Therefore, the macro-control should be adjusted in reverse, and pay attention to the time delay, the control effect and the influence period.
【作者单位】：南京师范大学;金融工程研究所;
【基金】：国家社科青年项目“中国商业银行系统风险演化、测度和控制机制(12CJY108)”
【分类号】：F832.4;F299.23

【参考文献】