摘要
本文以贷款违约率作为评估银行系统信用风险的指标,使用Logit模型将贷款违约率转化为综合指标Y,以指标Y作为因变量与宏观经济因素进行多元线性回归分析,通过假设情境法进行宏观压力测试,定量分析宏观经济因素波动对中国银行体系贷款违约率的影响。研究结果显示:名义国内生产总值、消费者价格指数、真实房地产价格指数和名义流动贷款利率对银行体系贷款违约率的影响显著。本文构建了两种宏观经济极端情境——名义国内生产总值大幅下降和通货膨胀率骤升,在这两种情境设定下,银行体系的贷款违约率都出现了不同程度的大幅度提高。
This paper mainly studies on the application of macro stress-testing in assessment of the bank＇s credit risk. On the basis of comparatively analyzing the mature models to establish the model fitting for China＇s situation, this paper sets overdue loans ratio as a credit risk indicator, uses Logit equation transferring it into a composite indicator which could reflect the banking system＇s default probability, and then establishes linear regression model with macroeconomic factors. At last the paper gives quantitative analysis on how macroeconomic factors could affect default probability of China＇s banking system with a hypothetical situation of stress tests. The paper practices stress-testing under two macroeconomic stress scenarios repectively, then finds that： macroeconomic variables like the nominal gross domestic product, the consumer price index, the real price of real estate index, and the nominal liquid lending rates all have significant impact on loans default ratio of the banking system. On the scenarios about sharp decline of NGDP and surge of CPI, default probability of banking system＇s loans goes up sharply.
出处
《数量经济技术经济研究》
CSSCI
北大核心
2009年第4期117-128,共12页
Journal of Quantitative & Technological Economics
关键词
宏观压力测试
信用风险
贷款违约率
逾期贷款率
Macro Stress-testing
Credit Risk
Defualt Probability
Overdue Loans Ratio
