How to explain non-performing loans by many corporate governance variables simultaneously? A corporate governance index is built to US commercial banks
Bilel Jarraya () and
Research in International Business and Finance, 2017, vol. 42, issue C, 645-657
This 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.
Keywords: Global financial crisis; Corporate governance index; Non-performing loans; GMM dynamic panel data estimator; PCA method (search for similar items in EconPapers)
JEL-codes: G01 G21 G34 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:42:y:2017:i:c:p:645-657
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