Identifying Threshold Effects in Credit Risk Stress Testing

Abstract

This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate. Using 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.

Bank-specific and macroeconomic determinants of non-performing loans in the Republic of Macedonia: Comparative analysis of enterprise and household NPLs

“…With regard to the dependent variable, the empirical literature usually suggests usage of two indicators: the ratio of non-performing to total loans (Gasha & Morales, 2004;Jimenez & Saurina, 2006;Fain stein & Novikov, 2011;Festic, Kavkler, & Repina, 2011;Pestova & Mamonov, 2012;Castro, 2012), and the change of the status of nonperforming loans or credit losses Quagliariello, 2008 and2009). In addition, losses due to unrepaid loans are also used in exploring the credit risk, (Bikker & Hu, 2002;Pain, 2003;Pesola, 2005;Quagliariello 2007;Glogowski, 2008).…”