Efficiency and Determinants in Libyan Banks
This paper provides a comparative analysis regarding the performance of 17 Libyan banks over the period 2004 up to 2010. According to the relevant literature, there are few studies that combine both the Data Envelopment Analysis (DEA) technique and Tobit model for assessing the efficiency levels and subsequently examining the determinants of efficiency for the banking sector in Libya. For this study, the DEA technique was used to estimate cost, allocative, and technical efficiency of sampled banks by using DEAP software. In the second stage, Tobit regression model was used to identify potential determinants of efficiency by using Stata10 software. The results showed that the specialized banks have exhibited higher mean cost efficiency relative to commercial and private banks. The results of efficiency determinants showed positive relationship between bank efficiency, and return on investment (ROA); risk; and size of operation (SO). This paper concludes with some policy implications of the results.
Al-Khasawneh, J. A., and Essaddam, N. (2012). Market reaction to the mergers announcements of USA banks: A nonparametric X- efficiency framework, Global Finance Journal, 23(3), 167 – 183.
Allen, F. and Carletti, E. (2010). The roles of banks in financial systems. In A. Berger, P. Molyneux and J. O. S.
Wilson (Eds.), the Oxford Handbook of Banking, Oxford: Oxford University Press, 32-57.
Asteriou, D., and Hall, S. G. (2007). Applied Economics, Second edition, Palgrave Macmillan, New York.
Bauer, P., W., Berger, A., N., Ferrier, G. D., and Humphrey, D., B. (1998). Consistency Conditions for Regulatory
Analysis of Financial Institutions: A Comparison of Frontier Efficiency Methods. Journal of Economics and Business, 50 (2), 85 – 114.
Berger, Allen N., & DeYoung, R. (1997). Problem Loans and Cost Efficiency in Commercial .Banks. Journal of Banking and Finance, 21, 1997.
Berg, S., Forsund, F., Hjalmarsson, L., and Suominen, M., (1993), Banking efficiency in the Nordic countries. Journal of banking and finance, 17, 71 – 388.
Bryce, C. L. (1996), Alternative approaches to estimating the efficiency of health maintenance organizations. ProQuest Dissertations & Theses: The Sciences and Engineering Collection.
Casu, B., and Molyneux, P. (2003). A Comparative Study of Efficiency in European Banking. Applied Economics, 35, 1865-1876.
Charnes, A., Cooper, W., Lewin, A., and Seiford, L. (1994). Data Envelopment Analysis Theory, Methodology and Applications, Massachusetts, USA: Kluwer Academic Publisher Group.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429– 444.doi:10.1016/0377-2217 (78)90138-8.
Coelli, T., Rao, D.S.P. and Batesse, G.E. (1998), An Introduction to Efficiency and Productivity Analysis, Kluwer Academic Publishers, Boston, MA.
Cooper, W. W., Seiford, L. M., Tone, K. (2003). Data Envelopment Analysis: A comprehensive text with models, applications, references, and DEA solver software. Massachusetts, USA: Kluwer Academic Publisher Group.
Cullinane, K., Wang, T. F., Song, D. W., and Ji, P. (2006). The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis. Transportation Research Part A: Policy and Practice, 40 (4), 354 – 374.
Cummins, J. D., and Zi, H. (1996). Measuring cost efficiency in the US Life Insurance Industry: Econometric and Mathematical programming approaches. Working paper, retrieved 1 Feb. 2012 from http://fic.wharton.upenn.edu/fic/papers/97/9703.pdf.
Delis, M.D. and Papanikolaou, N.I (2009). Determinants of Bank Efficiency: Evidence from a Semi-parametric Methodology. MPRA Paper No. 13893. Retrieved from http://mpra.ub.uni-muenchen.de/13893.
Drake, L., Hall, M. J. B., and Simper, R. (2009). Bank modelling methodologies: A comparative non-parametric analysis of efficiency in the Japanese banking sector, Journal of International Financial Markets, 19, pp. 1 – 15.
Ebong. B(2010). The banking industry and Nigerian economy: Post consolidation, Union Bank PLC, Abuja, Nigeria, 1-5.
EL Moussawi, C., and Obeid, H. (2011). Evaluating the Productive Efficiency of Islamic Banking in GCC: A Non- Parametric Approach, International Management Review, 7 (1), 10 – 21.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Roya Statistical Society, Series A, 120(III), 253–281. Retrieved from http://www.jstor.org/stable/2343100.
Fiorentino, E., Karmann, A., and Koetter, M. (2006). The cost efficiency of German banks: a comparison of SFA and DEA, Discussion Paper Series 2: Banking and Financial Studies, 10, 1 – 33.
Hasan, I., and Marton, K. (2003). Development and efficiency of the banking sector in a transitional economy: a Hungarian experience. Journal of Banking Finance, 27 (12), 2249–2271.
Hassan, M. K., Al-Sharkas, A., and samad, A. (2004). An empirical study of relative efficiency of the banking industry in Bahrain, Studies in economics and finance, 22 (2), 40 -69.
Havrylchyk, O. (2006). Efficiency of Polish banking Industry: Foreign versus domestic banks, Journal of Banking and Finance. 30(7), 1975 – 1996.
Isik, I. and Hassan, M.K. (2002). Technical, scale and allocative efficiencies of Turkish banking industry, Journal of Banking and Finance, 26 (4), 719-766.
Jacobs, R. (2001). Alternative methods to examine Hospital efficiency: Data Envelopment Analysis and Stochastic Frontier Analysis, Health Care Management Science, 4 (2), 103 – 115.
Kamaruddin, B. B. (2007). Efficiency evaluation of Islamic banking in the dual banking system: An analysis of commercial banks in Malaysia, Thesis, Unversiti Utara Malaysia.
Kamarudin, F., et al. (2019). Bank Efficiency in Malaysia a DEA Approach, Journal of Central Banking Theory and Practice, 1, 133 – 162.
Manadhar, R. and Tang, J. (2002). The evaluation of bank branch performance using data envelopment analysis: a framework. Journal of High Technology Management Research, 13 (1), 1–17.
Miller, S.M., Noulas, A.G. (1996). The technical efficiency of large bank production, Journal of Banking and Finance, 20 (3), 495–509.
Mireles, I., Ogilvie, S., Shedid, R. (2009). Libya. retrieved 13 Jan. 2012 from: http://fic.wharton.upenn.edu/fic/africa/Libya%20Final.pdf.
Mohammed, S. A. (2002). Finance-growth nexus in Sudan: empirical assessment based on an application of the autoregressive distributed lag (ARDL) model. Arab Planning .Institute in Kuwait, API/WPS 0803.
Mokhtar, H. S. A., Abdullah, N., and Al – Habashi M. S. (2008). Efficiency and competitions of Islamic banking in Malaysia, Humanomics, 24 (1), 28 – 48.
Mostafa M. (2007). Benchmarking top Arab banks' efficiency through efficient frontier analysis, Industrial Management & Data Systems, 107 (6), 802 – 823.
Norman, M., and Stoker, B. (1991). Data Envelopment Analysis: The Assessment of Performance. England: John Wiley& Sons Ltd.
Panorama report (2008). Modernizing the banking sector and investing globally, Libya, retrieved 20 Feb 2012 from: http://www.panoramareportsltd.com/pdf/libya.pdf.
Resti, A. (1997). Evaluating the cost – efficiency of the Italian banking system: What can be learned from the joint application of parametric and nonparametric techniques, Journal of Banking and Finance, 21(2), 122 – 139.
Saidenberg, M. and Philip S. (1999). Are Banks Still Important for Financing Large Businesses?. Current Issues in Economics and Finance, 5(12), Federal Reserve Bank of New York.
Sealey, C. and Lindley, J.T. (1977). Inputs, outputs and a theory of production and cost at depository financial institutions, Journal of Finance, 32 (4), 1251-66.
Sufian, F. (2007), The efficiency of Islamic banking industry in Malaysia Foreign vs domestic banks, Humanomics, Vol. 23 (3), pp. 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. (2011). Benchmarking the efficiency of the Korean banking sector: A DEA.approach. Benchmarking: An International Journal, 8 (1), 107 – 127.
Thanassoulis, E. (2003). Introduction to the theory and application of Data Envelopment Analysis. Text book, Library of congress control number: 2001034441 ISBN – 13: 978- 0-7923-7429-9.
Wu, D., Yang, Z. and Liang, L. (2006), Using DEA-neural network approach to evaluate branch efficiency of a large Canadian bank, Expert Systems with Applications, 31, pp. 108-15.
Zhu, J., (2003), Quantitative Models for Performance Evaluation and Benchmarking: data envelopment analysis with spreadsheets and DEA Excel solver. Worcester Polytechnic Institute, Massachusetts, USA.
Copyright (c) 2020 Khalad Alrafadi
This work is licensed under a Creative Commons Attribution 4.0 International License.