THE EFFECT OF MACRO FACTORS ON BANK CREDIT ACTIVITY IN THE REPUBLIC OF SERBIA
Keywords:
Erste bank, macroeconomic factors, short-term and long-term loans, multivariate regression models, civil sector and enterprises
Abstract
This paper investigates whether and how key macro-fundamentals in Serbia affect the volumes of issued loans of Erste bank to civil sector and enterprises in Serbia. We put an effort to determine which particular macro factor has the highest influence on issued credits of Erste bank, and to measure the exact average magnitude of these influences. The main idea is to find out how GDP, inflation, central bank referent interest rate, exchange rate changes and Euribor affect short-term and long-term credit activity of Erste bank in Serbia. The computations are done by applying several multivariate regression models. We can report that Euribor is the most important factor of all scrutinized macro-aggregates, since it affects most of the analysed bank loans. Besides Euribor, we find that other macro fundamentals influence the issued loans only sporadically. In other words, the level of GDP and inflation affect only long-term loans for enterprises, while referent interest rate has an influence only on short-term loans for civil population. Somewhat unexpected, we find that exchange rate changes have no effect on any loan of Erste bank, whatsoever, which clearly indicates that the bank protects itself very successfully against this type of macro risk.
References
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Baum, C.F., Caglayan, M., Ozkan, N. (2009). The second moments matter: the impact of macroeconomic uncertainty on the allocation of loanable funds. Economic Letters, 102 (2), 87–89., DOI: 10.1016/j.econlet.2008.11.019
Busch, C.M., & Prieto, E. (2014). Do better capitalized banks lend less? Long-run panel evidence from Germany. International Finance, 17(1), 1–23.
Caglayan, M., Xu, B. (2019). Inflation volatility effects on the allocation of bank loans. Journal of Financial Stability, 24, 27–39., 10.1016/j.jfs.2016.04.008
Chen, L., Pourahmadi, M., Maadooliat, M. (2014). Regularized multivariate regression models with skew-t error distributions. Journal of Statistical Planning and Inference, 149, 125–139., doi: 0.1016/j.jspi.2014.02.001
Den Haan, W. J., Sumner, S. W., & Yamashiro, G. M. (2007). Banks' loan portfolio and the monetary transmission mechanism. Journal of Monetary Economics, 54(3), 904–924.
Glen, J., Mondragón-Vélez, C. (2011). Business cycle effects on commercial bank loan portfolio performance in developing economies. Review of Development Finance, 1, 150–165., DOI: 10.1016/j.rdf.2011.03.002
Gu, X., Xin, Y., Xu, L (2019). Expected stock price crash risk and bank loan pricing: Evidence from China's listed firms. Pacific-Basin Finance Journal, 57, 101166. DOI: 10.1016/j.pacfin.2019.06.013
Hasanov, F.J., Bayramli, N., Al-Musehel, N. (2018). Bank-specific and macroeconomic determinants of bank profitability: evidence from an oil-dependent economy. International Journal of Financial Studies, 6(3), 78., DOI: 10.3390/ijfs6030078
Kamani, E.F. (2019). The effect of non-traditional banking activities on systemic risk: Does bank size matter? Finance Research Letters, 30, 297–305., DOI: 10.1016/j.frl.2018.10.013
Lee, J-P., Lin, E.M.H., Lin, J.J., Zhao, Y. (in press). Bank systemic risk and CEO overconfidence. North American Journal of Economics and Finance, DOI: 10.1016/j.najef.2019.03.011
Lojanica, N., Tubić-Ćurčić, T. (2019). Economic growth and economic inequality in Visegrád countries: empirical analysis. School of Business, 2, 35-51., DOI: 10.5937/skolbiz2-21327
Mori, Y., Suzuki, T. (2018). Generalized ridge estimator and model selection criteria in multivariate linear regression. Journal of Multivariate Analysis, 165, 243–261., DOI: 10.1016/j.jmva.2017.12.006
Petrella, L., Raponi, V. (2019). Joint estimation of conditional quantiles in multivariate linear regression models with an application to financial distress. Journal of Multivariate Analysis 173, 70–84., DOI: 10.1016/j.jmva.2019.02.008
Ognjanović, J., Pešterac, A. (2019). Research on the relationship between intellectual capital and indicators of work results of employees in the banking sector of the republic of Serbia. School of Business, 2, 1-22., DOI: 10.5937/skolbiz2-22612
Ongore, V.O. (2013). Determinants of Financial Performance of Commercial Banks in Kenya. International Journal of Economics and Financial Issues, 3(1), 237- 252.
Orzechowski, P.E. (2017). Bank profits, loan activity, and monetary policy: evidence from the FDIC's Historical Statistics on Banking. Review of Financial Economics 33 (2017) 55–63., DOI: 10.1016/j.rfe.2016.11.002
Otuori, O.H. (2013). “Influence of exchange rate determinants on the performance of commercial banks in Kenya”. European Journal of Management Sciences and Economics, 1(2), 86-98.
Xia, C., Zhang, A., Wang, H., Yeh, A.G.O. (2019). Predicting the expansion of urban boundary using space syntax and multivariate regression model. Habitat International, 86,126–134., DOI: 10.1016/j.habitatint.2019.03.001
Živkov D., Njegić J., Ljumović I. (2013). Linkage between external and internal imbalance: The case of Serbia. Industrija, 41(4), 127-142.
Published
2021/03/04
Section
Original Scientific Paper
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