The Evolution of Non-Performing Credit Limits During Crisis Period


The control of non-performing loans is a vital priority and necessity for the proper operation of financial institutions. The necessity of reduction of non-performing loans expressed supremely in the recent global financial crisis, which began in the U.S. in 2006 and spread to the rest of the world - especially in European Union, where it evolved into a sovereign debt crisis. As was expected, the transmitted financial crisis, received large dimensions, due to the fact that large credit institutions was exposed in the so-called “junk bonds.” The financial crisis reached the threshold of Greece in the last quarter of 2008 [1]. Especially in the case of Greece, the crisis was denatured extensively to debt crisis and received great proportions due to the extremely high public debt, thereby plunging the economy into great recession. Unlike the public debt, private debt in Greece is lower than that of other European countries, as a result of, in general, conservative credit policies of the Greek banks. The purpose of this paper is to study the effect of independent variables in identifying non-performing loans during crisis period, using a binomial logistic regression. We use a unique data of small business loans granted by one of the four systemic banks of Greece. Specifically we study a sample of credit limits granted to micro and small enterprises. Νon-performing loans significantly increased as the recession of Greek economy deepens. Moreover we find that in general the variables affect in the same way the creation of non-performing loans during the studied period. Specifically, binomial logistic regression shows a positive correlation between non-performing loans and factors “Adverse” and “Age”. In contrast, we find a negative correlation between the probability of classifying a loan as non-performing and the independent variables “Collateral”, “Own Facilities”, “Property” and “Years of operation”. Finally the predicted performance of the binomial logistic regression reduced as the crisis deepens.