single-jc.php

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.

Cite this article as:
Z. Wang and S. Qin, “Research on Non-Performing Loans Ratio’s Controlling: Evidence from 13 Commercial Banks,” J. Adv. Comput. Intell. Intell. Inform., Vol.21 No.6, pp. 1079-1086, 2017.
Data files:
References
  1. [1] A. Berger and R. DeYoung, “Problem Loans and Cost Efficiency in Commercial Banks,” J. of Banking and Finance, Vol.21, pp. 849-870, 1997.
  2. [2] M. M. Cornett, E. Ors, and H. Tehranian, “Bank Performance Around the Introduction of Section 20 Subsidiary,” Finance, Vol.57, pp. 501-521, 2002.
  3. [3] R. De Young and K. Roland, “Product Mix and Earnings Volatility at Commercial Banks Evidence from a Degree of Total Leverage Model,” J. of Financial Intermediation, Vol.10, pp. 54-84, 2001.
  4. [4] K. J. Stiroh, “Diversification in Banking: Is Noninterest Income the Answer?,” J. of Money, Credit and Banking, Vol.36, pp. 853-882 , 2004.
  5. [5] K. J. Stiroh and A. Rumble, “The Dark Side of Diversification: The Case of US Financial Holding Companies,” J. of Banking and Finance, Vol.30, pp. 2131-2161, 2006.
  6. [6] C. J. Godlewski, “Capital Regulation and Credit Risk Taking: Empirical Evidence from Banks in Emerging Market Economies,” Working Paper, available at SSRN: http://ssm.com/abstract=588163, 2004.
  7. [7] T. García Marco and M. D. Robles Fernández, “Risk-taking Behavior and Ownership in the Banking Industry: the Spanish Evidence,” J. of Economics and Business, Vol.60, No.4, pp. 332-354, 2007.
  8. [8] D. E. Allen, R. R. Boffey, and R. J. Powell, “The Impact Of Contagion On Non-Performing Loans: Evidence From Australia And Canada,” J. of Business and Policy Research, Vol.7, No.2, July Issue, pp. 13-24, 2012.
  9. [9] K. Harada and T. Ito, “Did Mergers Help Japanese Mega-Banks Avoid Failure? Analysis of the Distance to Default of Banks,” Int. J. of Finance and Economics, Vol.3, pp. 195-211, 2008.
  10. [10] R. Gropp, M. Lo Duca, and J. Vesala, “Cross-border Bank Contagion in Europe,” Working Paper Series 0662, European Central Bank, 2006.
  11. [11] C. R. Merton, “On the Pricing of Corporate Debt: The Risk Structure of Interest Rates,” J. of Finance, Vol.29, pp. 449-470 , 1974.
  12. [12] B. Aver, “An Empirical Analysis of Credit Risk Factors of the Slovenian Banking System,” Managing Global Transitions, Vol.6, pp. 317-334, 2008.
  13. [13] I. Bucur and S. Dragomirescu, “The Influence of Macroeconomic Conditions on Credit Risk: Case of Romanian Banking System,” Studies and Scientific Researches, Economics Edition, No.19, 2014.
  14. [14] M. D. Crouhy, D. Galai, and R. A. Mark, “Comparative Analysis of Current Credit Risk Models,” J. of Banking and Finance, Vol.24, pp. 59-117, 2000.
  15. [15] V. Castro, “Macroeconomic determinants of the credit risk in the banking system: the case of GIPSI,” Economic Modeling, Vol.31, pp. 672-683, 2013.
  16. [16] A. Das and S. Ghosh, “Determinants of Credit Risk in Indian State-owned Banks: An Empirical Investigation,” MPRA Paper No.17301, 2007.
  17. [17] E. Fama, “Term Premiums and Default Premiums in Money Markets,” J. of Financial Economics, Vol.17, pp. 175-196, 1986.
  18. [18] H. Fofack, “Nonperforming Loans in Sub-Saharan Africa: Causal Analysis and Macroeconomic Implications,” World Bank Policy Research Working Paper, No.3769, 2005.
  19. [19] N. Gunsel, “Micro and Macro Determinants of Bank Fragility in North Cyprus Economy,” African J. of Business Management, Vol.3, pp. 1323-1329, 2012.
  20. [20] G. Jimenez and J. Saurina, “Credit Cycles, Credit Risk, and Prudential Regulation,” Int. J. of Central Banking, Vol.2, pp. 65-98, 2006.
  21. [21] P. Jakubik, “Macroeconomic Environment and Credit Risk,” Czech J. of Economic and Finance, Vol.57, pp. 50-78, 2007.
  22. [22] Z. Wang, “A Statistical Research on Determiing Impacts on Non-Performing Loans Ratio In Commercial Banks,” ZheJiang GongShang University, 2014.
  23. [23] M. Nkusu, “Nonperforming Loans And Macrofinancial Vulnerabilities In Advanced Economies,” IMF Working Paper, WP/11/161, 2011.
  24. [24] M. Tracey, “The Impact Of Non-Performing Loans On Loan Growth: An Econometric Case of Jamacia and Trinidad and Tobago,” 2011.
  25. [25] P. Louzis, T. Vouldis, and L. Metaxas, “Macroeconomic and bank-specific determinants of non-performing loans in Greece: a Comparative study of mortgage, business and consumer loan portfolios,” J. of Banking and Finance, Vol.36, pp. 1012-1027, 2012.
  26. [26] R. P. S. Poudel, “Macroeconomic determinants of credit risk in Nepalese banking industry,” Proc. of 21st Int. Business Research Conf., 2013.
  27. [27] V. Salas and J. Saurina, “Credit risk in two institutional regimes: Spanish commercial and savings banks,” J. of Financial Services Research, Vol.22, pp. 203-224, 2002.
  28. [28] N. Zribi and Y. Boujelbene, “The factors influencing bank credit risk: the case of Tunisia,” J. of Accounting and Taxation, Vol.3, pp. 70-78, 2011.
  29. [29] R. D. Lisa, S. Zedda, F. Vallascas, F. Campolongo, and M. Marchesi, “Modelling Deposit Insurance Scheme Losses In A Basel 2 Framework,” J. of Financial Services Research, Vol.40, No.3, pp. 123-141, 2011.
  30. [30] B. Bernanke, M. Gertler, and S. Gilchrist, “The Financial Accelerator In A Quantitative Business Cycle Framework,” NBER Working Paper, No.6455, 1998.
  31. [31] E. I. Altman and G. Sabato, “Effects of the New Basel Capital Accord on Bank Capital Requirements For Smes,” J. of Financial Services Research, Vol.28, No.1-3, pp. 15-42, 2005.
  32. [32] K. Paetzmann, “Enterprise Risk Management: How Governance Regulation Affects Management Accounting and Control,” Zeitschrift FÜR Planung & Unternehmensste – Uerung, Vol.16, No.3, pp. 267-288, 2005.
  33. [33] S. Barisitz, “Nonperforming Loans In CESEE: What Do They Comprise?” Focuse on European Economic Integration, pp. 46-68, 2011.
  34. [34] S. Jha and X. Hui, “A Comparison Of Financial Performance Of Commercial Banks: A Case Study of Nepal,” African J. of Business Management, Vol.6, No.25, pp. 7601-7611, 2012.
  35. [35] P. Crosbie and J. Bohn, “Modeling Default Risk,” Moody’s KMV Company, 2003.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 18, 2024