THE EFFICIENCY OF BANKS AND THE FINANCIAL CRISIS IN A DEVELOPING ECONOMY: THE CASE OF JORDAN

This paper measures and evaluates the relative efficiency of the Jordanian banks over the period 2005-2010. The measurement of efficiency is estimated using Data Envelopment Analysis (DEA). Sample data contains 12 banks; three of them are Islamic banks. Constant return to scale (CRS) and variable return to scale (VRS) were used in order to measure the relative efficiency of the Jordanian banks, using annual data from 2005 through 2010. The results show that, on the technical efficiency scale only a few Jordanian banks were efficient in managing their financial resources and generating profit. Furthermore, only few banks were found to be efficient on the scale of pure technical efficiency and only so in a few years. The financial crisis was found to have a significant impact on banks’ efficiency. These findings can be used by the regulators, policy makers and banks management to further investigate the reasons behind the inefficient decision-making units (DMUs).

[1]  R. RajivD.BANKE.  Estimating most productive scale size using data envelopment analysis , 2003 .

[2]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[3]  H. Sherman,et al.  Bank branch operating efficiency: Evaluation with Data Envelopment Analysis , 1985 .

[4]  A. Maghyereh.  The Effect of Financial Liberalization on the Efficiency of Financial Institutions: The Case of Jordanian Commercial Banks , 2004 .

[5]  N. Avkiran.  The evidence on efficiency gains: The role of mergers and the benefits to the public , 1999 .

[6]  K. A. Bubshait,et al.  Evaluation of Bank Branches by Means of Data Envelopment Analysis , 1993 .

[7]  Allen N. Berger,et al.  The efficiency of financial institutions: A review and preview of research past, present and future , 1993 .

[8]  K. Kourouche,et al.  Measuring efficiency and productivity in the Australian banking sector , 2008 .

[9]  Cornelis van de Panne,et al.  Sampling size and efficiency bias in data envelopment analysis , 1998, Adv. Decis. Sci..

[10]  M. Sathye.  Privatization, Performance, and Efficiency: A Study of Indian Banks , 2005 .

[11]  P. Andersen,et al.  A procedure for ranking efficient units in data envelopment analysis , 1993 .

[12]  Kaoru Tone,et al.  Data Envelopment Analysis , 1996 .

[13]  K. Kourouche,et al.  Regulatory Policy and the Efficiency of the Banking Sector in Australia , 2008 .

[14]  M. Hassan,et al.  AN EMPIRICAL STUDY OF RELATIVE EFFICIENCY OF THE BANKING INDUSTRY IN BAHRAIN , 2004 .

[15]  Necmi K. Avkiran,et al.  An application reference for data envelopment analysis in branch banking: helping the novice researcher , 1999 .

[16]  Saeed Al-Muharrami,et al.  The causes of productivity change in GCC banking industry , 2007 .

[17]  Minwir Al-Shammari,et al.  Modeling the operating efficiency of banks: a nonparametric methodology , 1998 .

[18]  A. Charnes,et al.  Data Envelopment Analysis Theory, Methodology and Applications , 1995 .

[19]  L. Seiford,et al.  Profitability and Marketability of the Top 55 U.S. Commercial Banks , 1999 .

[20]  Yaakov Roll,et al.  An application procedure for DEA , 1989 .

[21]  A. Charnes,et al.  Polyhedral Cone-Ratio DEA Models with an illustrative application to large commercial banks , 1990 .

[22]  K. Alkhathlan,et al.  Are Saudi Banks Efficient? Evidence Using Data Envelopment Analysis (DEA) , 2010 .

[23]  Geeta Krishnasamy,et al.  Malaysian post merger banks’ productivity: application of Malmquist productivity index , 2004 .

[24]  F. Sufian,et al.  The determinants of Islamic banks' efficiency changes: Empirical evidence from the MENA and Asian banking sectors , 2009 .

[25]  Tim Coelli,et al.  A Guide to Frontier version 4. 1: A Computer Program for Stochastic Frontier Production and Cost Fu , 1996 .

[26]  Douglas D. Evanoff,et al.  Productive efficiency in banking , 2008 .

[27]  Ali Emrouznejad,et al.  Data envelopment analysis with classification and regression tree – a case of banking efficiency , 2010, Expert Syst. J. Knowl. Eng..

[28]  Jill Johnes,et al.  The efficiency of Islamic and conventional banks in the Gulf Cooperation Council (GCC) countries: An analysis using financial ratios and data envelopment analysis , 2009 .

[29]  Ramakrishnan Ramanathan,et al.  Performance of banks in countries of the Gulf Cooperation Council , 2007 .

[30]  A. Mobarak,et al.  Financial development in the Middle East and North Africa , 2003 .

[31]  Douglas D. Evanoff,et al.  Preview of the Great Lakes economy looking north and south , 1991 .

[32]  Allen N. Berger,et al.  Efficiency of financial institutions: International survey and directions for future research , 1997 .

[33]  Canan Yildirim.  Evolution of banking efficiency within an unstable macroeconomic environment: the case of Turkish commercial banks , 2002 .

[34]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[35]  Sunil Kumar,et al.  An Examination of Technical, Pure Technical, and Scale Efficiencies in Indian Public Sector Banks using Data Envelopment Analysis , 2008 .

[36]  Ali Emrouznejad,et al.  Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years , 2008 .

[37]  Andreas Kleine,et al.  A general model framework for DEA , 2004 .

[38]  John J. Rousseau,et al.  Two-person ratio efficiency games , 1995 .

[39]  A. Charnes,et al.  Sensitivity and stability of efficiency classifications in Data Envelopment Analysis , 1996 .

[40]  S. Miller,et al.  The technical efficiency of large bank production , 1996 .

[41]  Gonzalo Perez,et al.  Data Envelopment Analysis as a Tool to Evaluate Efficiency of Army Real Property Management Activities (RPMA) Spending , 1988 .

[42]  Lawrence M. Seiford,et al.  Recent developments in dea : the mathematical programming approach to frontier analysis , 1990 .