Azerbaycan Bankacılık Sisteminin Etkinliğinin Veri Zarflama Analizi ile Ölçülmesi (2015-2019)

Yıl 2022, , 119 - 137, 30.04.2022

Fuad Selamzade , Alig Baghirov

https://doi.org/10.18506/anemon.888731

Cited By: 1

Öz

Azerbaycan'da bankacılık sisteminin gelişmesi için para politikası uygulamak Azerbaycan Cumhuriyet Merkez Bankası'nın görevidir. Merkez Bankası, ülke genelinde ekonominin büyümesi için banka kaynaklarının dengeli ve verimli kullanılmasından sorumludur. Bu çalışmanın amacı, 2015-2019 yılları arasında Azerbaycan'da faaliyet gösteren 25 bankanın tamamının verimliliğinin girdi yönelimli Veri Zarflama Analizinin ölçeğe gore sabit getiri, ölçeğe gore değişken getiri ve Süper Etkinlik modelleri ile ölçülmesidir. Analiz sonucuna göre verimli ve verimsiz bankalar belirlenmiş ve karşılaştırılmış ve verimsiz bankalar için potansiyel iyileştirme önerileri geliştirilmiştir. Bununla bankacılık sistemine yönelik kaynakların daha verimli kullanılabileceği düşünülmüştür. Bu çalışma sonucunda yıllar içinde bankacılık sisteminin etkinliğinin arttığı görülmüştür. Etkin olmayan bankalara, referans olarak Günay Bank, Bank VTB, AFB Bank ve Bank of Baku gibi etkin bankalardan etkinlik oranlarına göre etkinliklerini artırmaları önerilmiştir. Müşterilerden alınacak mevduat hacmini artırmak için de mevduat maliyetlerinin düşürülmesi önerilir. Azerbaycan'da faaliyet gösteren bankaların ortalama etkinlik puanı 2015 yılında 0,75, 2019 yılında 0,95 olarak gerçekleşmiştir. Bu araştırmanın, gelecekteki araştırmacılar, bankalar ve banka çalışanları ve analistler için bir kaynak kaynağı olması beklenmektedir.

Anahtar Kelimeler

VZA, CCR Modeli, BCC Modeli, Süper Etkinlik, Azerbaycan, Bank Sistemi

Measuring the Efficiency of the Azerbaijan Banking System with Data Envelopment Analysis (2015-2019)

Öz

It is the duty of the Central Bank of the Azerbaijan Republic to apply monetary policy for the development of the banking system in the country. The Central Bank is responsible for the balanced and efficient use of banks' resources for the growth of the economy throughout Azerbaijan. In this study, the measurement of the efficiency of all 25 banks operating in Azerbaijan between 2015 - 2019 was investigated with constant return to scale, variable return to scale and Super efficiency models of an input-oriented Data Envelopment Analysis. According to the analysis results, efficient and inefficient banks were identified and compared, and potential improvement suggestions were developed for inefficient banks. With this, it was thought that the resources for the banking system could be used more efficiently. It has been recommended to the inefficient banks that they should increase their efficiency based on the effectiveness rates from the efficient banks such as Gunay Bank, Bank VTB, AFB Bank and Bank of Baku as reference. It is also recommended to reduce deposit costs in order to increase the volume of deposits to be received from customers. According to the findings, the efficiency of the banking system has increased over the years, and as a result, the average efficiency score of banks operating in Azerbaijan was 75 in 2015 and 95 in 2019. This research will be a source of resources for future researchers, banks, and bank employees and analysts.

Anahtar Kelimeler

DEA, CCR model, BCC Model, Super Efficiency, Azerbaijan, Banking System

Kaynakça

• Ariff, M. & Can, L. (2008). Cost and profit efficiency of Chinese banks: A non-parametric analysis. China Economic Review, 19(2), 260-273.
• Balci, E. & Ayvaz, B. (2020). Efficiency and productivity analysis in Turkish banking sector with data envelopment analysis and Malmquist index. Southeast Europe Journal of Soft Computing, 9(1), 9-23.
• Banker, R.D., Charnes, A., & Cooper, W.W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092
• Benston, G. J. (1965). Branch banking and economies of scale, Journal of Finance 20(2), 312-331.
• Berger, A. & Humphrey, D. (1997). Efficiency of financial institutions: International survey and directions for future research, European Journal of Operational Research 98(2), 175-212.
• Beridze, J. & Anbar, A. (2019). Efficiency analysis in Georgian banking sector: An application of data envelopment analysis, BMIJ, 7(2): 1076-1096. doi: 10.15295/bmij.v7i2.1127
• Charnes, A., Cooper, W.W., & Rhodes, E (1978). Measuring the efficiency of decision-making units, European Journal of Operation Research, 2, 429-444.
• Coelli, T., Prasada, D. S., & Battese, G.E., (1998), An introduction to efficiency and productivity analysis, Kluwer Academic Publisher. Cooper, W.W, Lawrence, W., Seiford, L. M., & Zhu, J. (2011). Handbook on data envelopment analysis. Second Edition. London: Springer New York Dordrecht Heidelberg.
• Cooper. W.W, Seiford, L. M., & Tone. K, (2007), Data envelopment analysis: A comprehensive text with models, applications, references and DEA-Solver software, Kluwer Academic Publishers,
• Drake, L., Hall, M.J.B., & Simper, R. (2009). Bank modelling methodologies: A comparative non-parametric analysis of efficiency in the Japanese banking sector, Int. Fin. Markets, Inst. and Money 19, 1–15
• Dutta, P., Jain, A., & Gupta, A. (2020), Performance analysis of non-banking finance companies using two-stage data envelopment analysis. Ann Oper Res 295, 91–116,
• Hammami, H., Ngo, T., Tripe, D., & Vo, D. T. (2020) Ranking with a Euclidean common set of weights in data envelopment analysis: with application to the Eurozone banking sector. Ann Oper Res, S.I.: MOPGP19. 1-20, Doi: 10.1007/s10479-020-03759-6
• Hjalmarsson, L., Andersson, I., & Mlima, A., (2000). Swedish banking efficiency and productivity in an international perspective, Estocolmo: Supplement Number 28 to the Government Inquiry on the International Competitiveness of the Swedish Financial Sector.
• Humphrey, D. B. (1985), Costs and scale economies in bank intermediation, In Aspinwall, R.C. & Eisenbeis, R. A. (Ed.), Handbook for Banking Strategy, pp. 745-783, New York: John Wiley and Sons.
• Kucukaksoy, I. & Selcan, O. (2013). Türk bankacılık sektöründe faaliyet gösteren bankaların etkinliklerinin veri zarflama analizi yöntemi ile ölçülmesi: 2004-2011 yılları uygulaması. Ekonometri & İstatistik e-Publisher, (18), 56-80 Kumar, S. & Gulati, R. (2008). An examination of technical, pure technical, and scale efficiencies in Indian Public Sector Banks using data envelopment analysis. Eurasian Journal of Business and Economics, 1(2), 33–69.
• Kutlar, A. & Babacan, A. (2008). A Comparison of the effectivity of Cumhuriyet university with state universities: An application of DEA technique, KOSBED, (15): 148-172.
• Kutlar, A. & Salamov, F. (2016). Evaluation of effectiveness of Azerbaijan public hospitals with data envelopment analysis, KOSBED, (31): 1 – 17
• Li, F., Wu, L., Zhu, Q., Yu, Y., Kou, G., & Liao, Y. (2020). An Eco-inefficiency dominance probability approach for Chinese banking operations based on data envelopment analysis, Complexity in Economics and Business, Article ID 3780232, 1-14, DOI:10.1155/2020/3780232
• Memmedov, S. (1997). Bank işi, Azerbaycan Neşriyatı. Bakü Mihmandarli, N. (1993), Azerbaycan, ITO, 15(2), 541-549
• Mikayilov, Q. & Mukhtarov, Ş. (2013), Azerbaycan bankacılık sisteminin finansal analizi: 2006-2011, Journal of Qafqaz University- Economics and Administration, 1(1), 75-83
• Nuri, A. O. & Süleymanov, E. (2010). Azerbaycan ekonomisi. Bakü: Şark-Garb Matbaası.
• Safarli, E. & Gumush, G. K. (2012). The effect of macroeconomic factors on the performance of Azerbaijan banking system, Journal of Money, Investment and Banking, 25, 59-69.
• Sealey, C.W. Jr. & Lindley, J.T. (1977). Inputs, outputs, and a theory of production and cost at depository financial institutions. Journal of Finance 32(4), 1251-1266.
• Seiford, L.M. & Thrall, R.M., (1990). Recent developments in DEA: The mathematical programming Appoach to Frontier Analysis, J Econometrics, 4, s.7-38.
• Selçuk, H. (2004), Azerbaycan'da bankacilik -yeni yüzyılda Azerbaycan'ın sosyo-ekonomik yapısı içinde. Tasam Publications, 43-70
• Torun, N. (2020), Sağlık hizmetlerinde etkinlik ölçümü, Ankara: Gazi
• Tsionas, M.G. (2020). A coherent approach to Bayesian data envelopment analysis, European Journal of Operational Research, 281(2), 439-448, Doi:10.1016/j.ejor.2019.08.039
• Yagubov, S. & Yagubov, U. (2020). The efficiency of Azerbaijani banks: an empiric analysis, 55th International Scientific Conference on Economic and Social Development – Baku/Azerbaijan, 581-587.
• Yeşilyurt, Ö., & Salamov, F. (2017). Evaluation of efficiency and factors influencing the efficiency in the health systems of Turkic states with super-efficiency and Tobit models. Balkan and Near Eastern Journal of Social Sciences, 3(2), 128–138.
• Yuksel, O. (2021). Comparison of Health Efficiencies of Provinces in Azerbaijan. International Journal of Academic Value Studies (Javstudies JAVS), 7(4), 443–450.
• Yüksel, O., & Yiğit, V. (2020). Ağız ve Diş Sağlığı Merkezlerinin Verimlilik Analizi Marmara Bölgesi Örneği. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 8(3), 883–894.
• Yuksel, S., Mukhtarov, S., & Mammadov, E. (2016). Comparing the efficiency of Turkish and Azerbaijani banks: An application with data envelopment analysis, International Journal of Economics and Financial Issues, 6(3), 1059-1067