商业银行贷款利率决定因素研究——基于贝叶斯模型平均法

Study on the Determinants of Lending Interest Rates of China's Commercial Banks: A Bayesian Model Averaging Approach

近年来,我国利率市场化改革加快推进,存贷款利率管制有序放开,商业银行贷款利率定价的自主权进一步扩大。本文选取了M_2增速、银行间债券7天回购利率、商业银行成本收入比、商业银行净息差、流动性比例、资本利润率、企业资产负债率、CPI增速、GDP增速、居民储蓄率等10个解释变量,运用贝叶斯模型平均方法建立模型,探讨了各解释变量对商业银行贷款利率的解释力和影响程度。本文的实证研究结果支持了传统的定性分析,显示了商业银行经营目标设定、自身管理水平以及央行货币政策对于贷款利率的影响作用。此外,本文结合实证结论,对央行和银行业监管机构如何有效引导商业银行适当降低贷款利率,逐步解决企业"融资难、融资贵"的问题提出了政策建议。

In recent years, China＇s interest rate marketization reform has been accelerated. Deposit andloan interest rate controls have been liberalized, and the autonomy of commercial banks＇ loan pricing has beenenhanced. We selects M2 quarterly growth rate, 7-day repo rate of inter-bank bond, commercial banks＇ cost-toincomeratio, net interest margin, liquidity ratio, return on equity, corporate＇ asset-liability ratio, CPI quarterlygrowth rate and GDP quarterly growth rate as explanatory variables, then analyze the explanatory power of eachvariable on commercial banks＇ loan pricing using Bayesian model averaging method. The empirical results of thispaper support conclusions of the traditional qualitative analysis, and highlight the great influence of commercialbanks＇ ROE target, management ability and the central bank＇s monetary policy on commercial banks＇ loan prices.Finally, we provide some policy recommendations for China＇s banking regulatory authorities and the central bankon how to effectively guide commercial banks to reduce loan prices and relieve corporate financing difficulties.