Investigating the effect of shock of macroeconomic variables on the performance of the country's banking system:

اقتصاد پولی مالی

Article 1, Volume 29, Issue 24, September 2022, Pages 1-32   

Document Type: Original Article

DOI: 10.22067/mfe.2023.77234.1205

Authors

zohreh eskandaripour¹; marzieh esfandiari^{* 2}; nazar dahmarde³; Mohammad Hassan Fotros⁴

¹PhD student at Satanist and Baluchistan University

²university

³Professor of Economics, Sistan and Baluchestan University, Zahedan,

⁴Professor of Economics, Bu Ali Sina University

Abstract

Given the dependence of the country's economy on banks as the most important source of financing for companies, it is important to study the factors affecting the performance of the banking system; Therefore, in this study, the effect of exchange rate shocks, crude oil prices, total stock index and government budget on the performance (profitability) of the country's banking system in the form of 12 scenarios based on the profitability response of the banking network to 2%, 5% and 10 Shock% was addressed in the mentioned variables. For this purpose, research data were collected from the SAM matrix of the Majles Research Center in 2011 and the data-output table of the Central Bank in 2016. Also, the dynamic recursive dynamic calculus model (RDCGE) and Math Lab software were used to analyze the data. The results showed that the informal exchange rate and crude oil prices have an inverse effect and the total government stock index and budget have a direct effect on the profitability of the banking network; So that if a positive shock of 2%, 5% and 10% is applied to the informal exchange rate, the profitability of the banking network will decrease to a maximum of 1.73, 2.01 and 2.57%, respectively. Also, if a positive shock of 2%, 5% and 10% is applied to the price of crude oil, the profitability of the banking network will decrease to a maximum of 1.41, 1.63 and 2.03%, respectively. In addition, if a positive shock of 2%, 5% and 10% enters the total stock index, the profitability of the banking network will increase to a maximum of 0.47, 0.97 and 1.52%, respectively. Finally, if a positive shock of 2%, 5% and 10% enters the government budget, the profitability of the banking network will increase to a maximum of 0.38, 0.44 and 0.61%, respectively.

Keywords

Exchange rate; crude oil prices; government budget; RDCGE model

References

António, M.; Ana Paula. S., & Simon, S. (2019). Determinants of Real Estate Bank Profitability, Research in International Business and Finance, 49: 282-300.

Antonio. T. P. (2013). What determines the profitability of banks? Evidence from Spain, Accounting and Finance, 53: 561 – 586.

Bernanke, B. S.; Gertler, M., & Gilchrist, S. (1999). The Financial Accelerator in a Quantitative Business Cycle Framework, In: Taylor, J. B., Woodford, M. (Eds.). Handbook of Macroeconomics, Handbook of Macroeconomics, Vol. 1, Elsevier, PP. 1341–1393, (Chapter 21).

Bigdley, M. Esmailzadeh Moghri, A. Calendar., & Daman Kasha, m. (2021). An empirical test of the effect of business environment risk on the relationship between liquidity risk and financial performance in Iran's banking industry, Investment Knowledge, 10(40): 425-450. (in Persian)

Boys, K. A., & Florax, R.J.G.M. (2007). Meta-Regression Estimates for CGE Models: A Case Study for Input Substitution Elasticities in Production Agriculture. American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

Decaluwé, B., A. Lemelin, H., &  Maisonnave et V. Robichaud. (2013). «Pep-1-t», Standard PEP model: single-country, recursive dynamic version, Politique Économique et Pauvreté/Poverty and Economic Policy Network. Université Laval, Québec.

Ezzati, M. wise L. A., &  Farmer Saji, N. (2015). Factors affecting the profitability of Islamic banks (member countries of the Organization of the Islamic Conference). Islamic Economics and Banking, 15: 153-139. (in Persian).

Islamic Council Research Center (2011). social accounting matrix, https://rc.majlis.ir/fa/news/show/931207, (in Persian)

Javier, A., & Arce, O. (2012). Banking Competition, Housing Prices and Macroeconomic Stability, The Economic Journal, 122 December, 1346–1372.Doi:10.1111/j.1468-0297. 2012.02531.x._2012

Kafaei, S. M. A., &  Rahzani, M. (2016). Investigating the impact of macroeconomic variables on the liquidity risk of Iranian banks, Economic Research and Policy Quarterly, 25(81): 261-310. (in Persian)

Khademi, S. R. Falihi Pirbast, N. Dalmanpour, M., &  Naghi Lu, A. (2019). Investigating the effects of specific banking and macroeconomic variables on banks' profitability (comparing neoclassical and post-Keynesian schools). Financial Economics, 14(53): 252-213. (in Persian)

Khani, Z. Rajab Dari, H., &  Mousavizadeh, S. A. (2018). Investigating the effect of oil price shocks on banks' performance, Financial and Economic Policy Quarterly, 7(26): 163-183. (in Persian)

Kiyotaki, N., & Moore, J. H. (1997). Credit Cycles, Journal of Political Economy, 105(2): 211–48.

Lu, J. Lu, J., & Lv, J. (2021). Brexit: The Impact of the Fluctuation of Pound Exchange Rate on the Banking Performance and Profitability, American Journal of Industrial and Business Management, 11: 364-379.

Mehrabanpour, M. R. Naderi Nouraini, M. M. Inalo, A., &  Ashari, A. (2017). Factors affecting the profitability of banks, empirical studies of financial accounting, 14(54): 119-140. (in Persian)

Mehrgan, N., &  Deliri, H. (2012). Banks' reaction to monetary policies based on the DSGE model, Economic Research and Policy Quarterly, 21(66): 68-39. (in Persian).

Pan, Q. H., & Pan, M. L. (2014). The Impact of Macro Factors on the Profitability of China’s Commercial Banks in the Decade after WTO Accession, Journal of Social Sciences, 2: 64-69.

Petria, N. Capraru, B., &  Inhnatov, I. (2015). Determinants of bank’s profitability: evidence from EU27 banking systems, procedia economics and finance, Procedia Economics and Finance, 20: 518-524.

Sayadi, M. Danesh Jafari, d. Bahrami, J., &  Rafei, M. (2015). providing a framework for the optimal use of oil revenues; A dynamic stochastic general equilibrium (DSGE) approach. Planning and Budget Quarterly, 20 (2): 21-58. (in Persian)

Tavaklian, H., &  Kamijani, A. (2011). Monetary policy under fiscal dominance and implicit target inflation in the form of a stochastic dynamic general equilibrium model for the Iranian economy, Economic Modeling Research, 3(8): 117-87. (in Persian)

Trad, N. Trablesi, M. A., & Goux, J. F. (2017). Risk and profitability of Islamic banks: A religious deception or an alternative solution?, European Research on Management and Business Economics, 23(1): 40-45.

Uhlig, H. (1999). A Toolkit for Analysing Nonlinear Dynamic Stochastic Models Easily, In Ramon Marimon and Andrew Scott, (eds.). Computational Methods for the Study of Dynamic Economies, Oxford: Oxford University Press, 1-49.