Graphical abstract<'/> How to explain non-performing loans by many corporate governance variables simultaneously? A corporate governance index is built to US commercial banks
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How to explain non-performing loans by many corporate governance variables simultaneously? A corporate governance index is built to US commercial banks

机译：如何用许多公司治理变量同时解释不良贷款？美国商业银行建立了公司治理指数

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Graphical abstractDisplay OmittedAbstractThis paper aims to combine the principal component analysis and GMM dynamic panel data methods in order to estimate the effect of corporate governance system on non-performing loans. The first method is meant to construct a corporate governance index for US commercial banks. The second one allows us to study the relation between the built index and non-performing loans. The advantage of the combination of these methods is reducing the number of corporate governance variables into a single one and ensuring the consistency of GMM estimates, given that a high number of variables leads to an increase in the number of GMM instruments, which in turns results in biased estimators. Applying these methods to US commercial banks, for a period including the financial crisis years, we find that small banks are characterized by a sound corporate governance system that reduces their non-performing loans. In opposition, the corporate governance fails to protect medium and large US commercial banks from excessive risk-taking that damages their loans’ quality and even leads to enormous losses especially during the global financial crisis.
机译： 图形摘要 < ce：simple-para>省略显示 摘要 本文旨在结合主成分分析和GMM动态面板数据方法，以评估公司治理体系对不良贷款的影响。第一种方法旨在为美国商业银行构建公司治理指数。第二个因素使我们能够研究已建指数与不良贷款之间的关系。结合使用这些方法的优点是，将公司治理变量的数量减少为一个，并确保GMM估计值的一致性，因为大量变量会导致GMM工具数量的增加，从而导致有偏估计。将这些方法应用于美国商业银行，包括金融危机时期在内，我们发现小型银行的特点是拥有健全的公司治理体系，可以减少不良贷款。相反，公司治理未能保护美国中型和大型商业银行免受过度冒险的侵害，特别是在全球金融危机期间，过度冒险会损害其贷款质量，甚至导致巨大损失。

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