Ukrainian banking system efficiency after double reducing of the number of bank institutions
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DOIhttp://dx.doi.org/10.21511/bbs.13(4).2018.05
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Article InfoVolume 13 2018, Issue #4, pp. 51-60
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The article intends to evaluate the efficiency and performance of Ukrainian banking system based on two stages. The first stage, when the number of banks was on average the same during that period, and the second stage, that began in 2015 and when the number of banks began to fall quickly up to 82 institutions in 2018. The study is based on the model of dynamics norm of the banking system efficiency for two periods.
The concept of efficiency was used based on the methods of non-parametric statistic to obtain performance estimates. The implementation of a dynamic model, based on the peculiarities of the banking system functioning, allows to obtain a generalized assessment of the economic efficiency of banking activity before and after critical change in the number of bank institutions. The correlation matrix between financial indicators of the banking system activity was created and the dynamic norm for the two periods was calculated. Given the analytical comparison of indicators, more effective period was identified. The general results of the study indicate that the overall efficiency of the banking system started to grow up since 2015.
- Keywords
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JEL Classification (Paper profile tab)G10, G21
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References29
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Tables8
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Figures2
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- Figure 1. Dynamics of number of banks in Ukraine, 2008–2018
- Figure 2. Forming a model of the banking system a dynamic norm
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- Table 1. Indicators for calculating the dynamic norm
- Table 2. The matrix of reference preferences for the banking system efficiency
- Table 3. Input statistic data of the Ukrainian banking system, 2013–2015, in UAH bln
- Table 4. The matrix of actual ratios of the banking system performance indicators in 2013–2015
- Table 5. Matrix of matches of actual and reference ratios of the banking system performance indicators, 2013–2015
- Table 6. Input statistic data of the Ukrainian banking system, 2016–2018, in UAH bln
- Table 7. The matrix of actual ratios of the banking system performance indicators in 2016–2018
- Table 8. Matrix of matches of actual and reference ratios of performance indicators of the banking system in 2016–2018
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- Abusharbeh, M. T. (2017). The Impact of Banking Sector Development on Economic Growth: Empirical Analysis from Palestinian Economy. Journal of Emerging Issues in Economics, Finance and Banking (JEIEFB), 6(2), 2306-2316.
- Aiello, F., & Bonanno, G. (2018). On the sources of heterogeneity in banking efficiency literature. Journal of Economic Surveys, 32(1), 194-225.
- Anderson, T. W., & Hsiao, C. (1981). Estimation of dynamic models with error components. Journal of the American Statistical Association, 76(375), 598-606.
- Andrews, D. (1993). Tests for parameter stability and structural change with unknown change point. Econometrica, 61(4), 821-856.
- Asimakopoulosa, G., Chortareasb, G., & Xanthopoulos, M. (2018). The Eurozone financial crisis and bank efficiency asymmetries: Peripheral versus core economies. Journal of Economic Asymmetries, 18.
- Bongini, P., Iwanicz-Drozdowska, M., Smaga, P., & Witkowski, B. (2017). Financial Development and Economic Growth: The Role of Foreign-Owned Banks in CESEE Countries. Sustainability, 9(3), 335-360.
- Brockett, P. L., & Golany, B. (1996). Using Rank Statistics for Determining Programmatic Efficiency Differences in Data Envelopment Analysis. Management Science, 42(3), 466-472.
- Cerović, L., Suljić Nikolaj, S., & Maradin, D. (2017). Comparative analysis of conventional and Islamic banking: importance of market regulation. Ekonomska misao, XXVI(1), 241-263.
- Chaudhary, S. (2012). Performance appraisal of Indian banking sector: A comparative study of selected public and private sector banks. International Journal of Research in Commerce and Management, 3(6), 155-164.
- Drake, L., Hall, M. J. B., & Simper, R. (2009). Bank modelling methodologies: A comparative non-parametric analysis of efficiency in the Japanese banking sector. Journal of International Financial Markets, Institutions and Money, 19(1), 1-15.
- Drucker, P. (1977). An introductory view of Management. NY: Harper College Press.
- Elmassah, S., & Al Sayed, O. (2015). Banking sector performance: Islamic and conventional banks in the UAE. International Journal of Information Technology and Business Management, 36(1), 69-81.
- Maciariello, J., & Kirby, C. (1994). Management Control Systems: Using Adaptive Systems to Attain Control (2nd ed.). Englewood Cliffs, Prentice Hall, Inc.
- Mouzas, S. (2006). Efficiency versus effectiveness in business networks. Journal of Business Research, 59(10-11), 1124-1132.
- Peck, J., & Shell, K. (2003). Equilibrium Bank Runs. Journal of Political Economy, 111, 103-123.
- Pogostinskaya, N. N., & Pogostinsky, Yu. A. (1999) System analysis of financial reporting (96 p.). SPb.: Izdv Mikhailova VA.
- Roghaniana, P., Raslia, A., & Gheysaria, H. (2012). Productivity Through Effectiveness and Efficiency in the Banking Industry. Procedia – Social and Behavioral Sciences, 40, 550-556.
- Rose, P. S. (2001). Commercial Bank Management (743 p.). McGraw-Hill.
- Rostami, M. (2015). CAMELS’ analysis in banking industry. Global Journal of Engineering Science and Research Management, 2(11), 10-26.
- Schumpeter, J. A. (1911). The Theory of Economic Development (255 p.). Oxford: Oxford University.
- Sharma, G., & Sharma, D. (2017). Comparison and Analysis of Profitability of Top Three Indian Private Sector Banks. International Journal of Engineering Technology Science and Research, 4(6), 173-180.
- Sinkey, J. F. (1992). Commercial Bank Financial Management in the Financial-services Industry (4th ed) (899 p.). Macmillan Publishing Company, Pennsylvania State University.
- Šporčić, M., & Landekić, M. (2014). Nonparametric Model for Business Performance Evaluation in Forestry. Computational and Numerical Simulations, 452-485.
- Stavárek, D., & Řepková, I. (2012). Efficiency in the Czech banking industry: A non-parametric approach. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 60(2), 357-366.
- Sultanum, B. (2014). Optimal Diamond-Dybvig Mechanism in Large Economies with Aggregate Uncertainty. Journal of Economic Dynamics and Control, 40, 95-102.
- Vighneswara, S. (2015). Modelling bank asset quality and profitability: An empirical assessment (Economics Discussion Papers, No. 2015-27).
- Yang, C. C. (2012). Service, investment, and risk management performance in commercial banks. The Service Industries Journal, 32(12), 2005-2025.
- Zhao, S. (2017). Does Financial Development Necessarily Lead to Economic Growth? Evidence from China’s Cities, 2007–2014. MATEC Web of Conferences, 100(05032).
- Zhao, Z. (2008). Parametric and nonparametric models and methods in financial econometrics. Statistics Surveys, 2, 1-42.