Do banking system transparency and competition affect nonperforming loans in the Chinese banking sector?
Usman Bashir, Yugang Yu, Muntazir Hussain, Xiao Wang, Ahmed Ali
Abstract
Usman Bashir, Yugang Yu, Muntazir Hussain, Xiao Wang, Ahmed Ali
Abstract
The increasing importance of transparency practices and the improving status of bank competition in China are rarely explored in nonperforming loans (NPLs) literature. Thus, the purpose of this study is to examine banking system transparency and competition along with macroeconomic and bank-specific variables as determinants of NPL. We use the two-step system GMM dynamic panel model for Chinese banks based on annual data from 2000 to 2014. Our results indicate that high transparency in the Chinese banking system decreases poor-quality assets but not in the case of government-owned banks, whereas increase in competition increases NPL. Moreover, we find mixed results in the context of macroeconomics and bank-specific variables. Our study has practical implications in risk management practices and macro prudential policies.
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The increasing importance of transparency practices and the improving status of bank competition in China are rarely explored in nonperforming loans (NPLs) literature. Thus, the purpose of this study is to examine banking system transparency and competition along with macroeconomic and bank-specific variables as determinants of NPL. We use the two-step system GMM dynamic panel model for Chinese banks based on annual data from 2000 to 2014. Our results indicate that high transparency in the Chinese banking system decreases poor-quality assets but not in the case of government-owned banks, whereas increase in competition increases NPL. Moreover, we find mixed results in the context of macroeconomics and bank-specific variables. Our study has practical implications in risk management practices and macro prudential policies.
Key concepts: Non-performing loan, Transparency (behavior), Competition (biology), Business, Chinese financial system, Financial system, Context (archaeology), Panel data