Identifying Threshold Effects in Credit Risk Stress Testing
AbstractUsing data from Argentina, Australia, Colombia, El Salvador, Peru, and the United States, we identify three types of threshold effects when assessing the impact of economic activity on nonperforming loans (NPLs). For advanced financial systems showing low NPLs, there is an embedded self-correcting adjustment when NPLs exceed a minimum threshold. For financial systems in emerging markets in Latin America showing higher NPLs, there is instead a magnifying effect once NPLs cross a (higher) threshold. GDP growth apparently affects NPLs only below a certain threshold, which is consistent with observed lower elasticity of credit risk to changes in economic activity in boom periods.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by International Monetary Fund in its series IMF Working Papers with number 04/150.
Date of creation: 01 Aug 2004
Date of revision:
Contact details of provider:
Postal: International Monetary Fund, Washington, DC USA
Phone: (202) 623-7000
Fax: (202) 623-4661
Web page: http://www.imf.org/external/pubind.htm
More information through EDIRC
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-10-22 (All new papers)
- NEP-FIN-2005-10-22 (Finance)
- NEP-FMK-2005-10-22 (Financial Markets)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Bruce E. Hansen & Mehmet Caner, 1997.
"Threshold Autoregressions with a Unit Root,"
Boston College Working Papers in Economics
381, Boston College Department of Economics.
- Potter, Simon M, 1995.
"A Nonlinear Approach to US GNP,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 10(2), pages 109-25, April-Jun.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
- Hansen, Bruce E. & Seo, Byeongseon, 2002.
"Testing for two-regime threshold cointegration in vector error-correction models,"
Journal of Econometrics,
Elsevier, vol. 110(2), pages 293-318, October.
- Tom Doan, . "RATS programs to replicate Hansen/Seo paper on threshold cointegration," Statistical Software Components RTZ00092, Boston College Department of Economics.
- Grigori Fainstein & Igor Novikov, 2011. "The Comparative Analysis of Credit Risk Determinants In the Banking Sector of the Baltic States," Review of Economics & Finance, Better Advances Press, Canada, vol. 1, pages 20-45, June.
- Tom Pak-wing Fong & Chun-shan Wong, 2008. "Stress Testing Banks' Credit Risk Using Mixture Vector Autoregressive Models," Working Papers 0813, Hong Kong Monetary Authority.
- Grigori Fainstein & Igor Novikov, 2011. "The role of macroeconomic determinants in credit risk measurement in transition country: Estonian example," International Journal of Transitions and Innovation Systems, Inderscience Enterprises Ltd, vol. 1(2), pages 117-137.
- Marcucci, Juri & Quagliariello, Mario, 2009. "Asymmetric effects of the business cycle on bank credit risk," Journal of Banking & Finance, Elsevier, vol. 33(9), pages 1624-1635, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jim Beardow) or (Hassan Zaidi).
If references are entirely missing, you can add them using this form.