Macroeconomic Drivers of Non-Performing Loans: A Meta-Regression Analysis
Macroeconomic Drivers of Non-Performing Loans: A Meta-Regression Analysis
Author(s): Martin Macháček, Ales Melecky, Monika ŠulganovaSubject(s): Economy
Published by: Vysoká škola ekonomická v Praze
Keywords: aggregate credit risk; macroeconomic credit risk drivers; non-performing loans ratio; meta-analysis; sub-samples analysis
Summary/Abstract: Common exposure to macroeconomic risk factors across financial institutions is a source of a systemic risk that influences quality of banks ́ loan portfolios. This paper focuses on the growing literature on credit risk determinants. The aim of the paper is to provide more general information on effects of macroeconomic drivers with the use of quantitative meta- analytic techniques. We consider five of the most common macroeconomic determinants of non-performing loans ratio. The meta-regression results suggest that there are some significant differences among studies, which could be identified. For instance, data specification, estimation method, number of countries and observations included in the model play a significant role. In some cases, e.g. inflation and exchange rate, the size of the effects presented in journals with impact factor are significantly different from other types of studies included in the analysis. The sub-sample analysis mostly confirms meta-regressions results.
Journal: Prague Economic Papers
- Issue Year: 27/2018
- Issue No: 3
- Page Range: 351-374
- Page Count: 24
- Language: English