Türk Bankacılık Sisteminde Kredi Riski ve Modellenmesi

Abstract

An increase in credit risks in the banking sector induces economic risks and therefore affects adversely the financial stability. In reviewing the literature, NLPs are regarded as an important indicator of credit risks. It is therefore important to determine variables that may affect an increase in NLPs in order to achieve the financial stability. The aim of this paper is to analyse the relationship between variables, which are believed to affect NLPs, in the Turkish banking sector and NLPs. For this purpose, Vector Autoregression (VAR) model is used; variables in the model are chosen based on the literature. To study short-and long-run relationship between variables, Johansen Cointegration test and Error Correction Model are applied. This paper makes a contribution to the literature by analysing the link between NLPs in Turkey and 2-year bond yields in the U.S.