不同类型商业银行不良贷款率影响因素实证研究

发布时间：2018-01-18 05:36

本文关键词：不同类型商业银行不良贷款率影响因素实证研究　出处：《云南财经大学》2017年硕士论文　论文类型：学位论文

【摘要】：近年我国商业银行的不良贷款率持续攀升,截至2016年第3季度,已连涨19个季度。对影响商业银行不良贷款率的因素进行研究,能够夯实其经营基础,有利于抵御潜在风险。同时,通过对不同类型商业银行不良贷款率影响因素的分析,可以为金融监管部门决策提供一些参考。为全面地考虑不良贷款率的影响因素,本文选择含有固定效应和随机效应的混合效应模型。由于相对于样本量而言,初始解释变量的个数较多,故运用基于正交化技术的SCAD型固定效应选择方法进行固定效应的选择和估计,并对随机效应进行检验。由于数据不满足正态性假设,故进行固定效应的选择和估计以及随机效应的检验时,选择的是不依赖于正态性假设的新方法。纳入混合效应模型的初始自变量,既有银行风险类指标,也有宏观经济指标。实证结果表明,不同类型商业银行不良贷款率受不同协变量的影响,同一协变量对不同类型商业银行不良贷款率的影响或正或负。具体到宏观经济指标,国内生产总值对所有类型商业银行不良贷款率的影响都是正向的;消费者物价指数只影响城市商业银行、农村商业银行和外资银行,且为负方向;广义货币供应量对商业银行总体、股份制商业银行和外资银行的影响是正向的,对城市商业银行的影响为负;社会消费品零售总额仅从正向影响商业银行总体、国有大型商业银行和股份制商业银行。在所选的三个银行风险类指标中,拨备覆盖率对商业银行总体、国有大型商业银行、股份制商业银行和外资银行均有负向影响,而核心资本负债率和流动性比率仅对外资银行起着正向影响。对于随机效应来说,年度和季节效应对不同类型商业银行不良贷款率均影响显著,说明经济周期性在不良贷款率影响因素的研究中不容忽视。进一步地,为说明年度和季节效应对每一类型商业银行的影响差异,根据相应的随机效应检验结果,计算出了P值,并给出了比较结论。
[Abstract]:In recent years, the non-performing loan rate of commercial banks in our country has been rising continuously. As of in the third quarter of 2016, the non-performing loan rate of commercial banks has risen for 19 consecutive quarters. The research on the factors affecting the non-performing loan ratio of commercial banks can strengthen the operating foundation of commercial banks. At the same time, through the different types of commercial banks through the impact of non-performing loan ratio factors. In order to comprehensively consider the influence factors of non-performing loan ratio, this paper chooses the mixed effect model with fixed effect and random effect, because of the sample size. The number of initial explanatory variables is large, so the SCAD fixed effect selection method based on orthogonalization technique is used to select and estimate the fixed effect. The random effect is tested. Because the data do not satisfy the hypothesis of normality, the selection and estimation of the fixed effect and the test of the random effect are carried out. We choose a new method which does not depend on the hypothesis of normality. The initial independent variables of the mixed effect model include both bank risk indicators and macroeconomic indicators. The empirical results show that. The non-performing loan ratio of different types of commercial banks is affected by different covariables. The same covariable has a positive or negative effect on the non-performing loan ratio of different types of commercial banks. The impact of GDP on the non-performing loan ratio of all types of commercial banks is positive; The consumer price index only affects urban commercial banks, rural commercial banks and foreign banks, and is negative; The influence of broad money supply on commercial banks, joint-stock commercial banks and foreign banks is positive and negative on urban commercial banks. Total retail sales of consumer goods only positively affect the overall commercial banks, state-owned large commercial banks and joint-stock commercial banks. In the selected three bank risk indicators, the provision coverage of commercial banks as a whole. Large state-owned commercial banks, joint-stock commercial banks and foreign banks have a negative impact, while the core capital debt ratio and liquidity ratio only have a positive impact on foreign banks. The annual and seasonal effects have a significant impact on the non-performing loan rate of different types of commercial banks, indicating that economic periodicity can not be ignored in the study of the factors affecting the non-performing loan rate. In order to explain the difference between the annual and seasonal effects on each type of commercial bank, the P value is calculated according to the results of the random effect test, and the comparative conclusions are given.
【学位授予单位】：云南财经大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F832.4

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