single-jc.php

JACIII Vol.21 No.6 pp. 1094-1101
doi: 10.20965/jaciii.2017.p1094
(2017)

Paper:

Comparison of International Differences in the Volatility of Economic Growth and Non-Performing Loan Ratio: A Statistical Study Based on the Quantile Regression Model

Song Qin*,** and Zhenlei Wang***

*Taizhou University
Taizhou 318000, China

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

***Hangzhou Dianzi University
Hangzhou 315000, China

Received:
December 27, 2016
Accepted:
May 2, 2017
Published:
October 20, 2017
Keywords:
quantile regression, economic growth, non-performing loan ratio
Abstract

What is the level of non-performing loans in China’s banking sector and in different countries? Has the relationship between economic growth and the non-performing loan ratio changed? Is there a difference in the effect of the economic growth of different economies on the rate of non-performing loans in the banking sector? This study analyzes the relationship between economic growth and the non-performing loan ratios and characteristics of 13 countries from 2005-2014 based on quantile regression models with panel data. The results showed that the relationship between economic growth and the non-performing loan ratio was positive before the financial crisis in 2008 but was negative after 2008. The non-performing loan ratio in Canada, Mexico, and the US was low before 2008 and high after 2008. The impact of economic growth on the non-performing loan ratio was more significant for countries with a high non-performing loan ratio than for countries with a low non-performing loan ratio.

References
  1. [1] E. Fama, “Term Premiums and Default Premiums in Money Markets,” J. of Financial Economics, Vol.17, pp. 175-196, 1986.
  2. [2] T. Wilson, “Credit Portfolio Risk,” Risk Magazine, 1997.
  3. [3] G. Jimenez and J. Saurina, “Credit Cycles, Credit Risk, and Prudential Regulation,” Int. J. of Central Banking, Vol.2, pp. 65-98, 2006.
  4. [4] A. Das and S. Ghosh, “Determinants of Credit Risk in Indian State-owned Banks: An Empirical Investigation,” MPRA Paper, No.17301, 2007.
  5. [5] 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.
  6. [6] N. Gunsel, “Micro and Macro Determinants of Bank Fragility in North Cyprus Economy,” African J. of Business Management, Vol.3, pp. 1323-1329, 2012.
  7. [7] 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.
  8. [8] V. Castro, “Macroeconomic determinants of the credit risk in the banking system: the case of GIPSI,” Economic Modeling, Vol.31, pp. 672-683, 2013.
  9. [9] H. Fofack, “Nonperforming Loans in Sub-Saharan Africa: Causal Analysis and Macroeconomic Implications,” World Bank Policy Research Working Paper, No.3769, 2005.
  10. [10] B. Aver, “An Empirical Analysis of Credit Risk Factors of the Slovenian Banking System,” Managing Global Transitions, Vol.6, pp. 317-334, 2008.
  11. [11] R. P. S. Poudel, “Macroeconomic determinants of credit risk in Nepalese banking industry,” Proc. of 21st Int. Business Research Conf., 2013.
  12. [12] 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.
  13. [13] M. Zhang, “Bank’s NPL and Economical Growth,” Shanghai Economics, 2002.
  14. [14] L. JinHong, “Economic Growth, Economic Freedom and Non-Performing Loan,” Renmin University of China, 2008.
  15. [15] L. Lin and S. YanFeng, “Economic volatility, Non-Performing Loan and Banking Systemic Risk,” Studies of Int. Finance, No.6, pp. 55-63, 2009.
  16. [16] X. Wang, “Macroeconomic Influenced on Bank’s Credit Risk,” ShangDong Financial University, 2014.
  17. [17] L. Xu and G. Wu, “Study on Loan Capital and volatility of economy in China,” Economy Observer, pp. 43-45, 2011.
  18. [18] P. Yue and X. Zhen, “Economy Growth and Volatility of NPL: VAR Model,” Finance and Economy, pp. 28-31, 2011.
  19. [19] 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.
  20. [20] P. Jakubik, “Macroeconomic Environment and Credit Risk,” Czech J. of Economic and Finance, Vol.57, pp. 50-78, 2007.
  21. [21] M. D. Crouhy, D. Galai, and R. Mark, “A Comparative Analysis of Current Credit Risk Models,” J. of Banking and Finance, Vol.24, pp. 59-117, 2000.
  22. [22] T. Zhang and Z. Peng, “Study on Bad Capital Basing on Jiangxi Province Data,” Hainan Finance, Vol.10, pp. 69-75, 2010.
  23. [23] P. Lu, “Interest and Volatility of Bank’s NPL,” South-West Finance, No.371, pp. 50-53, 2012.
  24. [24] J. Li, “Bank’s NPL and Economy Cycle,” Marketing Modernization, Vol.3, p. 159, 2010.
  25. [25] F. Mosteller and J. Tukey, “Data Analysis and Regression,” Addison-Wesley, 1977.
  26. [26] R. Koenker and G. Bassett, “Regression Quantiles,” Econometrica, Vol.46, pp. 33-50, 1978.
  27. [27] R. Koenker, “Quantiles Regression,” Cambridge University Press, 2004.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Dec. 12, 2017