In: Ekonomický časopis/Journal of Economics, vol. 72, no. 7-8
Zuzana KOŠŤÁLOVÁ 
Detaily:
Strany: 309 - 333
Jazyk: eng
Kľúčové slová:
early warning indicators, banking sector, financial imbalance, credit gap, Bayesian model averaging;
JEL Classification: C40, E44, G01, G21
Typ článku: Vedecký článok / Article
Typ dokumentu: PDF / PDF
O článku:
This paper tries to identify early warning indicators for the Slovak banking sector. The aim of the early warning indicators is to predict a build-up of imbalances or rising risks in the banking sector, using the credit-to-GDP gap as a proxy. Based on quarterly data from 1Q2003 to 4Q2023, we apply Bayesian model averaging (BMA) to explore the potential predictive power of 38 variables over a horizon of 4 to 12 quarters. The advantage of the BMA is that it accounts for uncertainty in the selection and combination of potential indicators. The results indicate the importance of both traditional early warning indicators – such as the unemployment rate, inflation, and interest rates – and uncertainty indicators, including sentiment-based survey data and media-derived policy uncertainty measures. Notably, the construction confidence indicator and the German Policy Uncertainty Index appear to indicate the potential for an increase in risk within the banking sector. Furthermore, our findings also underline the vulnerability of the Slovak banking sector to external shocks such as the COVID-19 pandemic, and highlight the role of household indebtedness in identifying emerging imbalances. These insights are relevant for macroprudential policy, particularly in the calibration of the countercyclical capital buffer.
This paper tries to identify early warning indicators for the Slovak banking sector. The aim of the early warning indicators is to predict a build-up of imbalances or rising risks in the banking sector, using the credit-to-GDP gap as a proxy. Based on quarterly data from 1Q2003 to 4Q2023, we apply Bayesian model averaging (BMA) to explore the potential predictive power of 38 variables over a horizon of 4 to 12 quarters. The advantage of the BMA is that it accounts for uncertainty in the selection and combination of potential indicators. The results indicate the importance of both traditional early warning indicators – such as the unemployment rate, inflation, and interest rates – and uncertainty indicators, including sentiment-based survey data and media-derived policy uncertainty measures. Notably, the construction confidence indicator and the German Policy Uncertainty Index appear to indicate the potential for an increase in risk within the banking sector. Furthermore, our findings also underline the vulnerability of the Slovak banking sector to external shocks such as the COVID-19 pandemic, and highlight the role of household indebtedness in identifying emerging imbalances. These insights are relevant for macroprudential policy, particularly in the calibration of the countercyclical capital buffer.
Ako citovať:
ISO 690:
KOŠŤÁLOVÁ, Z. 2024. Early Warning Indicators for the Slovak Banking Sector. In Ekonomický časopis/Journal of Economics, vol. 72, no.7-8, pp. 309-333. 0013-3035. DOI: https://doi.org/10.31577/ekoncas.2024.07-08.01
APA:
KOŠŤÁLOVÁ, Z. (2024). Early Warning Indicators for the Slovak Banking Sector. Ekonomický časopis/Journal of Economics, 72(7-8), 309-333. 0013-3035. DOI: https://doi.org/10.31577/ekoncas.2024.07-08.01
O vydaní:
Vydavateľ: Ekonomický ústav SAV, v.v.i. / Institute of Economic Research SAS
Publikované: 31. 12. 2024