Performance Evaluation of Bank Branches by the DEA-Tobit Model: The Case of Agricultural Bank Branches in Guilan Province

Iranian Journal of Optimization

مقاله 5، دوره 10، شماره 2، اسفند 2018، صفحه 113-124   

نوع مقاله: Research Paper

نویسندگان

Hamidreza Alipour¹؛ Gholamreza Mahfoozi²؛ Mohsen Shafieyan^{* 3}؛ Shiva Rezaeyan⁴

¹Assistant Professor, Department of Management and Economics, Rasht Branch, Islamic Azad University, Rasht, Iran

²Assistant Professor, Department of Management, University of Guilan, Rasht, Iran.

³Young Researchers and Elite Club, Rasht Branch, Islamic Azad University, Rasht, Iran

⁴Ph.D. Candidate in Industrial Management, Department of Industrial management, Islamic Azad University, Rasht, Iran

چکیده

This paper uses data envelopment analysis (DEA) to examine the technical, pure technical, and scale efficiencies of 12 branches of the agricultural bank in Guilan province, Iran over the period of 2012-2016. The first results indicated that scale inefficiency contributed more to overall technical inefficiency than pure technical inefficiency over the studied period. Results of return to scale reveal that decreasing return to scale is the main form of scale inefficiency. Then, overall technical efficiency scores obtained from DEA was regressed over four factors determining bank efficiency (including bank size, profitability, capital adequacy, and liquidity) by the Tobit method. These four variables influenced efficiency differently. Branch size showed a negative, insignificant relationship with technical efficiency. So, it had no impact on efficiency. Profitability was the main parameter in branch efficiency following by liquidity. Profitability and liquidity influenced efficiency positively and significantly. In other words, larger and more profitable branches have higher technical efficiency.

کلیدواژه‌ها

Data envelopment analysis؛ Tobit analysis؛ overall technical efficiency؛ Banking

مراجع

Abbas, M., Azid, T., & Besar, M.H.A.H. (2016). Efficiency, effectiveness and performance profile of Islamic and conventional banks in Pakistan. Humanomics, 32(1), 2-18.

Ab-Rahim, R., Md-Nor, N.G., Ramlee, S., & Ubaidillah, N.Z. (2012). Determinants of cost efficiency in Malaysian banking. International Journal of Business and Society, 13(3), 355-374.

Aggelopoulos, E., & Georgopoulos, A. (2017). Bank branch efficiency under environmental change: A bootstrap DEA on monthly profit and loss accounting statements of Greek retail branches. European Journal of Operational Research, 261, 1170-1188.

Anastasopoulos, P.C.h., Tarko, A.P., & Mannering, F.L. (2008). Tobit analysis of vehicle accident rates on interstate highways. Accident Analysis & Prevention, 40(2), 768-775.

Asmild, M., & Zhu, M. (2016). Controlling for the use of extreme weights in bank efficiency assessments during the financial crisis. European Journal of Operational Research, 251(3), 999-1015.

Balfour, R., Joo, S.-J., Whited, H.-H.I.H., & Lin, J.W. (2015). Assessing the comparative performance of banking branches. Benchmarking, 22(5), 963-972.

Banker, R.D., Charnes, A. and Cooper, W.W. (1984). Some models for estimating technical and scale efficiency in data envelopment analysis. Management Science, 30, 1078-1092.

Brown, K.E., & Skully, M.T. (2007). Efficiency analysis of Islamic banks in Africa, Asia and the Middle East. Review of Islamic Economics, 11(2), 5-16.

Charnes, A., Cooper, W.W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429-444.

Das, A., & Ghosh, S. (2006). Financial deregulation and efficiency: An empirical analysis of Indian banks during the post reform period. Review of Financial Economics, 15(3), 193-221.

Drake, L., & Hall, M.J.B. (2003). Efficiency in Japanese Banking: An Empirical Analysis. Journal of Banking & Finance, 27(5), 891- 917.

Fujii, H., Managi, S., & Matousek, R. (2013). Indian bank efficiency and productivity changes with undesirable outputs: a disaggregated approach. Journal of banking & finance, 38(1), 41-50.

Gardener, E., Molyneux, P., & Nguyen-Linh, H. (2011). Determinants of efficiency in South East Asian banking. Service Industries Journal, 31(16), 2693-2719.

Gulati, R. (2015). Trends of cost efficiency in response to financial deregulation: The case of Indian Banks. Benchmarking, 22(5), 808-838.

Halkos, G.E., & Salamouris, D.S. (2004). Efficiency measurement of the Greek commercial banks with the use of financial ratio: a data envelopment analysis approach. Management Accounting Research, 15(2), 201-224.

Han, S., Jiang, P., & Jiang, Y. (2014). The performance of Chinese commercial banks after accession to the WTO: from an efficiency perspective. Journal of Chinese Economic and Business Studies, 12(3), 253-271.

Jackson, P.M., & Fethi, M.D. (2000). Evaluating the Efficiency of Turkish Commercial Banks: An Application of DEA and Tobit Analysis. A Paper Presented at the International DEA Symposium, University of Queensland, Brisbane, Australia, available at: http://www.le.ac.uk/ulsm/research/epru/dispaper.html.

Kao, C., & Liu, S.-T. (2009). Stochastic Data Envelopment Analysis in Measuring the Efficiency of Taiwan Commercial Banks. European Journal of Operational Research, 196(1), 312-322.

Kasman, A., & Mekenbayeva, K. (2016). Technical efficiency and total factor productivity in the kazakh banking industry. Acta Oeconomica, 66(4), 685-709.

Kutlar, A., Kabasakal, A., & Ekici, M.S. (2017). Efficiency of commercial banks in Turkey and their comparison: Application of DEA with Tobit analysis. International Journal of Mathematics in Operational Research, 10(1), 84-103.

Liu, J., Zhang, J., & Fu, Z. (2017). Tourism eco-efficiency of Chinese coastal cities e Analysis based on the DEA-Tobit model. Ocean & Coastal Management, 148, 164-170.

Naceur, S.B., Ben-Khedhiri, H., Casu, B. (2011). What Drives the Performance of Selected MENA Banks? A Meta-Frontier Analysis. IMF Working Paper, 11/34, (February, 2011), available at: http://papers.ssrn.com/sol3/ papers.cfm?abstract_id=1767802.

Noor, M.A.N.M., & Ahmad, N.H.B. (2012). The Determinants of Islamic Banks' Efficiency Changes: Empirical Evidence from the World Banking Sectors. Global Business Review, 13(2), 179-200.

Paradi. J.C., Zhu, H., & Edelstein, B. (2012). Identifying managerial groups in a large Canadian bank branch network with a DEA approach. European Journal of Operational Research, 219, 178-187.

Rahim, A., Rahman, A., & Rosman, R. (2013). Efficiency of Islamic Banks: A Comparative Analysis of MENA and Asian Countries. Journal of Economic Cooperation and Development, 34(1), 63-92.

Reisman, A., Daouas, M., Oral, M., Rebai, S., & Gatoufi, S. (2003). Impact of Deregulation on Technical and Scale Efficiencies of Tunisian Commercial Banks: Window Extended Data Envelopment Analysis. Working Paper, Faculty des Sciences Economics ET de Gestation de Tunis.

San, O.T., Theng, L.Y., & Heng, T.B. (2011). A Comparison on Efficiency of Domestic and Foreign Banks in Malaysia: A DEA Approach. Business Management Dynamics, 1(4), 33-49.

Sealey, C., & Lindley, J. (1997). Inputs, outputs, and a theory of production at depository financial institutions. Journal of Finance, 32, 1251-1266.

Secme, N.Y., Bayrakdaroglu, A., & Kahraman, C. (2009). Fuzzy performance evaluation in Turkish Banking Sector using Analytic Hierarchy Process and TOPSIS. Expert Systems with Applications, 36(9), 11699-11709.

Sherman, H.D., & Gold, F. (1985). Bank branch operating efficiency: Evaluation with Data envelopment analysis, Journal of Banking and Finance, 9(2), 297-315.

Siriopoulos, C., & Tziogkidis, P. (2010). How Do Greek Banking Institutions React After Significant Events? A DEA Approach. Omega, 38(5), 294-308.

Sufian, F. (2007). The efficiency of Islamic banking industry in Malaysia: Foreign vs domestic banks. Humanomics, 23(3), 174-192.

Sufian, F. (2009). Determinants of bank efficiency during unstable macroeconomic environment: Empirical evidence from Malaysia. Research in International Business and Finance, 23, 54-77.

Sufian, F., & Shah Habibullah, M. (2010). Developments in the efficiency of the Thailand banking sector: a DEA approach. International Journal of Development Issues, 9(3), 226-245.

Tandon, D., Tandon, K., & Malhotra, N. (2014). An Evaluation of the Technical, Pure Technical and Scale Efficiencies in the Indian Banking Industry using Data Envelope Analysis. Global Business Review, 15(3), 545-563.

Tobin, J. (1958). Estimation of relationships for limited dependent variables. Econometrica, 26(1), 24-36.

Tsolasa, I.E., & Charles, V. (2015). Incorporating risk into bank efficiency: A satisficing DEA approach to assess the Greek banking crisis. Expert Systems with Applications, 42(7), 3491-3500.

Wang, K., Huang, W., Wu, J., & Liu, Y.-N. (2014). Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA. Omega, 44, 5-20.

Wanke, P., Barros, C.P., & Emrouznejad, A. (2016). Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banks. European Journal of Operational Research, 249(1), 378-389.

Yang, C., & Liu, H.-M. (2012). Managerial efficiency in Taiwan bank branches: A network DEA. Economic Modelling, 29(2), 450-461.