资本比率与利率差:面板阈值回归方法

M. Botshekan, A. Golbabaei
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引用次数: 2

摘要

本文利用美国参保商业银行的平衡年度观测数据,采用带有一个和两个阈值变量的面板阈值回归模型,将样本分别分为两个和四个制度,研究了滞后资本比率对利率息差的非线性影响。我们使用的阈值变量是资本比率的变化,资本比率变化的主要组成部分,即资本的变化或风险加权资产的变化和ROE的变化。在单门槛模型中,资本比率变化越大、资本对资本比率变化的贡献越大、风险加权资产对资本比率变化的贡献越大,对应的制度显示出滞后资本比率对利差的影响更强。在使用滞后ROE变化作为阈值变量的情况下,令人惊讶的是,较少受ROE下降影响的银行(由于增加资本比率)更倾向于提高利率利差来抵消下降。在具有两个阈值变量和四个机制的面板阈值回归模型中,我们发现了类似的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Capital Ratio and the Interest Rate Spread: The Panel Threshold Regression Approach
Using balanced annual observations of insured US commercial banks, this paper investigates the nonlinear impacts of the lagged capital ratio on the interest rate spread by employing the panel threshold regression model with one and two threshold variables which divide our sample into two and four regimes, respectively. The threshold variables we use are the change in capital ratio, the main components of change in the capital ratio, namely change in the capital or change in risk-weighted asset and ROE changes. In single threshold models, regimes that correspond to the higher change in capital ratio, higher contribution of capital to the change in capital ratio, and higher contribution of the risk-weighted asset to the change in the capital ratio show a stronger impact of the lagged capital ratio on the interest rate spread. In the case of using lagged ROE changes as threshold variable, surprisingly banks that are less exposed to the fall in ROE (as a result of increasing the capital ratio) tend more to raise the interest rate spread to offset the fall. In the panel threshold regression model with two threshold variables and four regimes, we find similar results.
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