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JACIII Vol.21 No.6 pp. 1079-1086
doi: 10.20965/jaciii.2017.p1079
(2017)

Paper:

Research on Non-Performing Loans Ratio’s Controlling: Evidence from 13 Commercial Banks

Zhenlei Wang*,† and Song Qin**,***

*HangZhou DianZi University
No.9-319, 2

nd Street, Jianggan, Hangzhou, Zhejiang 310018, China

Corresponding author

**Taizhou University, TaiZhou 318000, P.R.China

***Huazhou University of Science and Technology, Wuhan 430074, China

Received:
December 27, 2016
Accepted:
May 2, 2017
Published:
October 20, 2017
Keywords:
distance to default, non-performing debt, panel data, commercial bank
Abstract

The People’s Bank of China in 2013 released a report revealing that the balance of non-performing loans of Chinese banking financial institutions had rebounded for the first time since 2005. In this situation, establishing early warning models – to recognize the factors that influence non-performing loans, and take effective measures to prevent defaults and control the banks’ credit assets – has become a major new issue. This paper examines the determinants of the non-performing loans (NPL) ratio in the Chinese banking sector from 2005 to 2011 using a panel data model. This model incorporates a new factor called distance to default (DD). The results show that the rates of change of total asset size, commercial loan ratio, and distance to default correlate negatively with NPL. There are positive correlations between capital return ratio, net interest margin, and single-lag NPL with NPL. However, there is no significant correlation between the proportion of shareholders’ equity, or the proportion of total loans, and NPL. In conclusion, this study suggests that regulators should consider and pay more attention to all these banks’ operational indicators to control NPL.

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Last updated on Dec. 15, 2017