Bank Efficiency and Economic Freedom: Case of Jordanian Banking System

European Journal of Scientific Research ISSN 1450-216X / 1450-202X Vol. 146 No 4 August, 2017, pp.444-454 http://www. europeanjournalofscientificresearch.com Bank Efficiency and Economic Freedom: Case of Jordanian Banking System Asma a Al-Amarneh Corresponding Author Applies Science Private University E-mail: A_alamarneh@asu.edu.jo Hadeel Yaseen University of Jordan E-mail: H.yaseen@ju.edu.jo Abstract Financial intermediaries in general and commercial banks in particular, play a crucial role in maintaining economic growth of a nation by facilitating the flow of funds to various sectors of the economy. The efficiency of the banking system is one of the most critical aspects in the financial market, since it affects the stability of the banking industry and thus have a significant impact on the effectiveness of the entire monetary system. The aim of this paper is to analyze the efficiency of the banking system in Jordan and to establish empirical evidence on the impact of economic freedom on bank efficiency during the period of 2005-2015. The efficiency scores of commercial banks are measured by using the Data Envelopment Analysis (DEA), a linear programming technique that was developed by Charnes Cooper (1978) between the years 2005-2015. The findings reported in this paper shows that following the 2008 financial crisis, the increased government intervention had a negative impact on the efficiency of the Jordanian banking sector. Keywords: Bank Efficiency, Economic Freedom, DEA, Jordan. JEL Code: G20, O10, C80. 1. Introduction Banking systems are essential for economic growth, since banks acts as a financial intermediary between investors, borrowers and the government. For this reason, governments, regulators and policy makers should keep a watchful eye on banks and their performance, as the latter is considered a central issue to the financial stability of a country. Conversely, inefficient banks are usually more exposed to risks and tends to have a higher likelihood of failure which usually leads to bankruptcy and thus a negative impact on the economy and its monetary environment. Despite that the Jordanian banking sector is deemed as one of the smallest financial systems in the world, the kingdom enjoys a well-developed bank-based financial system, as banks play a key role in funding various economic activities (World Bank, 2003). According to the Central Bank of Jordan (CBJ) 2015 annual report 1, the banking system in Jordan consists of 13 Jordanian commercial banks with (609) local branches and (163) branches abroad, 3 Islamic Banks with (113) local branches and 1 2015 ANNUAL REPORT CENTRAL BANK OF JORDAN PUBLICATIONS

Bank Efficiency and Economic Freedom: Case of Jordanian Banking System 445 (15) branches abroad. Beside that, there are (10) foreign banks (9) of them are commercial banks and one Islamic foreign bank. Over the last 10 years, the Central Bank of Jordan (CBJ) has undertaken several reforms to enhance the performance of the banking sector. The licensed banks' operations displayed a credit expansion by 9.5% to reach JD 21,103.5 million, and a growth in total deposits by 7.7% to reach JD 32,598.5 million. The increase in deposits is attributed to the increase in JD deposits by JD 2,001.4 million (8.3%) and the increase in foreign currency deposits by JD 336.1 million (5.4%). Concerning the Economic Freedom Index 2, Jordan s Economic Freedom Status is moderately free with a global rank of 38, and total index of 69.3. Jordan is ranked the fifth out of fifteen countries in the MENA region, its global score remains sound and above the regional and world averages. The 2015 annual report issued by the heritage Foundation 3 assured that; regardless of the challenging economic situation and ongoing ambiguity stemming from regional security turmoil, banking sector remains strong and well capitalized. The banking and financial regulations that endorsed by the government, goes beyond the assurance of transparency in the financial markets that can hinder efficiency, increasing the cost of financing entrepreneurial activities, besides limiting competitions. Instead, financial regulations must be applied in order to keep the soundness of the financial system and to ensure that financial service's institutions meet their basic fiduciary responsibilities. Accordingly; it is important to study the effect of government intervention on bank efficiency to provide regulators and authorities with guidance when put up strategies and regulations. Despite the large body of research dedicated to observe the efficiency of banking systems, a limited number of contributions explores the effect of economic freedom on bank s efficiency. Hence, the crucial and important aim of this research is to spread the previous literature on banks efficiency and conduct an empirical indication that examine the effect of economic freedom on a small developing economy namely, the economy of Jordan. This paper is organized as follow: next section review the existing research carried out by other academic researchers. Section three describes the research methodology followed for the completion of this study. Section four outlines and discusses the results of this study and section five outlines the conclusions, recommendations and limitations of this study. 2. Literature Review Banks efficiency can be evaluated by utilizing the financial ratio approach or the Input-output analysis by using Data Envelopment Analysis (DEA). This technique is a non-parametric linear programming which introduced by Charnes et al. (1978) and then used by a number of researchers (Banker et al., 1984, Charnes et al., 1994, Kleine, 2004). DEA is often utilized to evaluate and measure the efficiency of policymaking units at banks or economic organizations. However, for DEA to work, the relative homogeneity between units should exist; in other words, the units to be compared should have similar inputs and outputs. Several empirical studies applied DEA in order to measure bank's efficiency and examine the performance of banks that have undistinguishable inputs and outputs. For instance, in an empirical study that examined the efficiency of fifteen branches of a bank operating in Saudi Arabia by applying DEA, Al-Faraj et al. (1993) found that 12 out of 15 branches were efficient, by relying on eight inputs and seven outputs. In the same way, Al-Faraj et al. (2006) applied DEA to investigate the difference between the technical efficiency of Saudi banks with the worlds mean for the year 2002, where they found that banks enjoyed a suitable score of efficiency compared with others around the world. 2 (2015 INDEX OF ECONOMIC FREEDOM REPORT, PP: 261-262). 3 HTTP://WWW.HERITAGE.ORG/INDEX/

446 Asma a Al-Amarneh and Hadeel Yaseen In their evaluation of the relative efficiency of ten banks operating in Saudi Arabia, over the period 2003-2008. AlKhathlan and Abdul Malik (2010) applied two DEA models, namely BCC and CCR, and found banks were effective in handling financial resources. Sufian and Noor (2009) utilized the DEA technique to compare between the performance of 16 Islamic banks operating in the MENA and Asian countries, and found that Islamic banks operating in the MENA region are relatively more efficient than those operating in Asia. They also found that banks that holds a larger market share are relatively less efficient. In a study aimed at examining the efficiency of 78 Islamic banks around the world between the years 1992-2009, Noor and Ahmad (2011) found that Islamic banks enjoyed high technical efficiency and reported a positive correlation among profitability and technical efficiency of banks. Ajlouni et al. (2011) applied DEA to test the efficiency of Jordanian banks between the years 2005-2008, and investigated the determinants of efficiency in terms of bank s size and capitalization. Their results revealed that the average efficiency of sample banks was high and steady. Ajlouni et al. (2011) also revealed that bank size and capitalization should be deemed as efficiency determining factors, as their results showed that the relative efficiency of larger banks significantly outperformed small and medium sized banks and that banks with lower capital adequacy were more efficient. Hence, this indicates that Jordanian banks with higher capital adequacy avoids risk by managing safer and lower-earning portfolios. Al-Shammari and Salimi (1998) applied DEA to examine the operating efficiency of Jordanian banks between the years 1991-1994, and revealed that most Jordanian banks performed inefficiently to a certain extent. Bdour and Al-khoury (2008) examined the efficiency of Jordanian banks between the years 1998 and 2004, by utilizing the DEA technique. Their results revealed that bank efficiency surged thought the entire period, except in the years 2003 and 2004, where a drop in the efficiency of several banks was revealed. Bdour and Al-khoury (2008) also suggested that the efficiency scores imply that the liberalization program was responsible for the anticipated efficiency gains. Zeiton and Benjelloun (2013) applied DEA to examine the efficiency of 12 Jordanian banks (including 3 Islamic banks) over the period 2005-2010. Their results showed that, a limited number of Jordanian banks were deemed as technically efficient in terms of managing financial resources and generating profit. Their results also showed that the efficiency of banks was affected by the 2008 financial crisis. Ataullah and Le. (2006), used DEA to investigate the efficiency of Indian banks and then used OLS and GMM to investigate the impact of several economic reforms (namely, (i) fiscal reforms, (ii) financial reforms, and (iii) private investment liberalization) on banks efficiency. Their results revealed a positive association between the efficiency of the bank and the level of competition, but a negative association between bank efficiency and the presence of foreign bank, which came as a result of the increasing costs that associated to the introduction of new banking technology by foreign banks. As for the effect of different economic reforms on banks efficiency; their results revealed that fiscal deficits negatively affect bank efficiency; and that bank efficiency improved after reforms, especially for foreign banks. Sufian and Habibullah (2010) empirically investigated the effect of economic freedom on Malaysian banks performance during the period of 1999 2007 by using profitability ratios as a measurement tool. Their results revealed that banks profitability increased as the level of business freedom increased, as banks were able to start a business with minimum government intervention and had the ability to freely select the activities they are going to undertake. Sufian and Habibullah (2011) used DEA to investigate the efficiency of the Chinese banking sector, and found that inefficiency stems largely from scale rather than pure technical. They also examined the effect of economic freedom level on bank efficiency, their results revealed that business freedom and monetary freedom have a positive effect on bank efficiency, while financial freedom has a negative effect.

Bank Efficiency and Economic Freedom: Case of Jordanian Banking System 447 Chortareas et.al (2013) used DEA to measure the efficiency of a large sample of commercial banks operating in the European Union member states between the years 2001 and 2009, then study the effect of economic freedom on banks efficiency. Their results showed that banks benefits from the higher level of financial freedom and that banks efficiency is maintained to a higher extent in countries with free political systems and higher quality governance. In view of the foregoing review, this study aims at examining the efficiency of Jordanian non- Islamic banks listed at Amman Stock Exchange (ASE) by utilizing the Data Envelopment Analysis approach (DEA). Further, OLS regression will be applied to investigative the impact of economic freedom level on the calculated bank efficiency. Accordingly, this study seeks to answer the following questions: 1. To what extent are Jordanian banks efficient in terms of using resources and inputs? 2. To what extent are Jordanian banks efficiency levels linked to the economic freedom level? 3. Research Methodology 3.1 Sample Selection and Variable Definition The sample consists of all non-islamic banks listed in Amman Stock Exchange (ASE), they were 13 commercial banks listed in table (1), and the required data was collected for the period 2005-2015. The DEA used to assess the efficiency of the 13 commercial banks Listed in ASE, this approach was applied on banks for the first time by Sherman and Gold (1985). Table 1: Selected Banks NO BANK'S NAME SYMBOL LISTED SHARES 1 JORDAN KUWAIT BANK JOKB 100,000,000 2 JORDAN COMMERCIAL BANK JCBK 112,875,000 3 ARAB JORDAN INVESTMENT BANK AJIB 150,000,000 4 BANK AL ETIHAD UBSI 125,000,000 5 ARAB BANKING CORPORATION /(JORDAN) ABCO 110,000,000 6 INVEST BANK INVB 100,000,000 7 CAPITAL BANK OF JORDAN EXFB 200,000,000 8 SOCIETE GENERALE DE BANQUE - JORDANIE SGBJ 100,000,000 9 CAIRO AMMAN BANK CABK 180,000,000 10 BANK OF JORDAN BOJX 200,000,000 11 JORDAN AHLI BANK AHLI 175,000,000 12 ARAB BANK ARBK 640,800,000 13 THE HOUSING BANK FOR TRADE AND FINANCE THBK 252,000,000 The most important aim of using the DEA technique is to settle which banks are operating on their efficient frontier and which banks are not. This means if the bank s input-output pattern lies on the DEA frontier, so bank is considered as efficient, and inefficient if it lies inside the frontier (Ragsdale, 2007). In this study the intermediation approach has been applied in order to define inputs and outputs of our sample of banks (Khankhoje & Sathye, 2008), Erasmus and Makina (2014). This approach take into account that banks as primarily intermediaries channeling funds between savers and borrows (surplus and deficit units). Table 2 represents inputs and outputs for each bank covering the period 2005 to 2015 were obtained from ASE web site 4. 4 http://www.ase.com.jo/en/library-and-publications.

448 Asma a Al-Amarneh and Hadeel Yaseen Table 2: Inputs and Outputs variables under the Intermediation Approach Total Deposit Fixed Assets Shareholders Equity Employee Expenses Non-Interest Expenses Inputs Total Loans Non-Interest Income Outputs The statistics for input and output variables for all selected banks were presented in table (3). The figures show that average amount of deposits held by the 13 commercial banks was (2478.241) million JDs, while the average amount of loans provided to borrowers was (1468.464) million JDs, indicating that commercial banks hold excess liquidity that can be invested. Concerning the noninterest revenues and expenses the average non-interest revenues was (12.97) million JDs while the non-interest expenses was (25.63) million JDs, indicating that on average commercial banks in Jordan pay non-interest expenses more than receive. Table 3: Statistics for inputs and outputs variables for all banks during the period 2005-2015 (figures in million JDs) Output Variables Input Variables Loans Non Interest Employee Non Interest Fixed Deposit Equity Income Cost Expenses Assets Mean 1468.464 12.97412 2478.241 483.4076 29.98691 25.63755 41.77719 Median 665.9721 5.442888 1087.128 194.6991 14.47187 9.854877 24.19810 Maximum 11264.98 118.0440 19492.22 3955.414 209.8430 412.2390 220.7750 Minimum 84.56372 0.323171 113.0699 21.97460 2.082952 1.663432 1.473055 Std. Dev. 2523.702 22.12112 4274.801 909.0760 45.07664 53.75877 51.26213 Observations 143 143 143 143 143 143 143 When analyzing the input and output variables for each bank alone the results presented in tables 4 and 5 respectively. The ARBK holds the largest average amount of deposit (16,548.30) million JDs and the average amount of loans provided was (9843.713) million JDs, also this bank receives the highest non-interest income (79.016) million JDs and pays on average the highest Non-interest expenses (189.8340) million JDs. Table 4: Input variables statistic for each bank Total Deposit Shareholders equity Employee Cost Non Interest Expenses Fixed Assets Bank Code Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. JOKB 1601.383 412.0087 305.7848 109.7704 18.92431 3.673303 11.87672 4.583664 13.99697 4.166836 JCBK 627.6786 288.5396 96.74478 20.82615 8.099323 2.628920 6.604736 2.298456 14.60996 8.570438 AJIB 773.3855 366.7411 128.9910 43.83911 7.839227 3.636460 6.489700 2.919832 25.10221 18.22539 UBSI 541.8808 188.2057 106.0174 33.43044 9.198678 2.128888 5.859546 1.006477 10.18917 0.993527 ABCO 515.6431 52.84317 110.2462 31.37661 6.353447 3.174860 4.232177 1.887069 17.91732 8.396260 INVB 320.1105 257.0920 69.07620 40.19377 3.581919 0.939556 3.131244 0.766566 10.50339 10.11639 EXFB 1450.032 253.5076 232.7727 82.38226 22.69128 5.050517 15.30364 3.819420 31.13629 9.621067 SGBJ 1702.042 263.4458 241.6834 46.58599 31.92575 5.041806 19.29621 3.904952 55.05755 4.464880 CABK 1108.028 456.8496 216.6896 60.42131 11.29518 5.940772 7.102443 3.859374 21.33693 10.63109 BOJX 876.2743 367.8058 208.2407 49.25865 10.98619 4.359409 9.911110 4.184409 20.52308 8.517090 AHLI 1405.943 346.9476 209.9521 60.31630 29.10539 6.786832 16.97111 4.684305 31.13467 5.362316 ARBK 16548.30 2018.968 3489.983 590.4688 175.6893 23.25475 189.8340 87.20491 192.6741 17.57230 THBK 4746.430 1275.950 868.1173 173.9974 18.92431 14.66903 36.67554 11.08317 98.92183 35.74309 All 2478.241 4274.801 483.4076 909.0760 8.099323 45.07664 25.63755 53.75877 41.77719 51.26213 Source: Descriptive data for the inputs using EViews software In the other hand; the INVB hold the lowest amount of Deposits (320.1105) million JDs and provide the lowest amount of loans (185.271), and receives the lowest non-interest income (1.309) million JDs and pays the lowest non-interest expenses (3.13) million JDs.

Bank Efficiency and Economic Freedom: Case of Jordanian Banking System 449 Table 5: Output variables statistic for each bank Total Loans Non Interest Income Bank Code Mean Std. Dev. Mean Std. Dev. JOKB 1176.952 209.6669 14.44476 5.656638 JCBK 395.5537 120.6004 5.038850 4.992802 AJIB 361.6241 193.0171 1.856732 1.489282 UBSI 358.7036 117.8717 5.997817 2.280849 ABCO 338.2764 95.08724 2.235354 1.715727 INVB 185.2714 103.8746 1.309368 0.320215 EXFB 895.2412 191.9432 5.618896 2.152804 SGBJ 993.3530 255.9835 10.85899 5.379541 CABK 757.1193 315.6813 1.424994 1.115840 BOJX 624.1150 145.6459 5.919698 3.898032 AHLI 795.7566 240.3260 5.880204 1.652546 ARBK 9843.713 1378.325 79.01609 29.43637 THBK 2364.356 601.4139 29.06182 4.554421 All 1468.464 2523.702 12.97412 22.12112 Source: Descriptive data for the outputs using EViews software. 3.2 Model Specification This study used the standard DEA approach and the efficiency of bank I is described as: Efficiency of bank i = The weighted sum of bank i s outputs divided by the weighted sum of bank i s inputs. Assuming N DMUs, 13 banks each with n inputs and m outputs. The DEA relative efficiency score of bank i is attained by resolving the next linear programming model: Maximize = i=1,2, m j=1,2,.n S=1,2, 13 (1) Subject to the following: 1 u i >0, v j >0 Where: E = the efficiency score; = the ith output produced by the sth bank; = the jth input used by the sth bank; = weight of output; = weight of input; =the input j utilized by the rth DMU; and =the output i produced by the rth DMU 4. Impirical Results Using the DEAP Version 2.1 computer program for Data Envelopment Analysis we apply Input orientated, Variable Return to Scale (VRS), Multi-stage DEA to assess the efficiency of the selected banks. The input oriented approach used to assess the amount of inputs that can be reduced without shifting the produced outputs, while the VRS used because the imperfect competition constrains on finance, etc. that may cause a bank as decision making unit (DMU) to be not operating at optimal scale. The Multi-Stage DEA approach conducted to identify the efficient projected point. The result of this analysis presented in the following tables. Table (6) presents the technical efficiency of the selected banks under the Constant Return to Scale (CRS) and the Variable return to Scale Assumptions and Scale Efficiency calculated by: CRS-TE / VRS-TE.

450 Asma a Al-Amarneh and Hadeel Yaseen Table 6: Technical Efficiency and Scale Efficiency Bank Code Technical Efficiency CRS- TE VRS -TE Scale Efficiency JOKB 1.000 1.000 1.000 JCBK 1.000 1.000 1.000 AJIB 0.734 0.826 0.889 Increased Return to Scale UBSI 1.000 1.000 1.000 ABCO 0.893 1.000 0.893 Increased Return to Scale INVB 0.808 1.000 0.808 Increased Return to Scale EXFB 0.952 0.965 0.987 Decrease Return to Scale SGBJ 1.000 1.000 1.000 CABK 1.000 1.000 1.000 BOJX 0.969 1.000 0.969 Increased Return to Scale AHLI 0.928 0.944 0.983 Decrease Return to Scale ARBK 0.851 1.000 0.851 Decrease Return to Scale THBK 1.000 1.000 1.000 Mean 0.934 0.980 0.952 Source: output from the DEAP computer program version 2.1 The technical efficiency results under the CRS show that: JOKB, JCBK, UBSI, SGBJ, CABK and THBK were fully efficient (technical and scale), while AJIB and ABCO, INVB, EXFB, BOJX, AHLI and ARBK banks were inefficient DMUs. The CRS assumption is only appropriate when all DMU s are operating at an optimal scale, which is too restrictive in reality. Imperfect competition, constrains in finance, etc. may cause a DMU to be not operating at optimal scale, and that will result in measures of technical efficiency (TE) which are confounded by Scale Efficiency (SE). A subtle modification of the CRS model allows us to compute efficiency under variable returns to scale (VRS) and disentangle technical efficiency from scale efficiency. Table (6) shows that under the VRS model the TE for all banks is higher than TE estimated under the CRS and all banks are fully efficient except the AJIB, EXFB and AHLI banks, this technical efficiency is free from the scale efficiency effect. It is worth to note that some banks have scale inefficiency due to increasing return to scale (AJIB, ABCO, INVB, and BOJX). Increasing return to scale or shrinking the costs attributes to the fact that all factors of production are increased (inputs), outputs also increase at a higher rate. This indicates when all inputs are doubled, outputs will also increase at faster rate than double. This increase is due to many reasons like division external economies of scale. On the other hand, some banks have scale inefficiency due to decreasing (diminishing) return to scale (EXFB, AHLI and ARBK). The shrinking of returns or rising costs raise because of the production situation, this means when all factors of production are increased in a given proportion, outputs surge in a smaller amount. The main reason is that internal and external economies are less than internal and external diseconomies. The overall efficiency level (total Economic Efficiency or Total Cost Efficiency) is founded by: Total Economic efficiency= Technical Efficiency Scale Efficiency, or EE = TE SE Table (7) summarizes the efficiency level of our banks under the VRS. The figures show that only (6) banks have a full efficiency level while the other banks were not fully efficient due to scale inefficiency. Table 7: Efficiency Summary Bank Technical Efficiency Scale Efficiency Economic (Overall) Code (TE-VRS) (SE-CRS) Efficiency (EE) Efficiency Level JOKB 1.000 1.000 1.000 Full JCBK 1.000 1.000 1.000 Full AJIB 0.826 0.889 0.734 inefficient

Bank Efficiency and Economic Freedom: Case of Jordanian Banking System 451 Bank Technical Efficiency Scale Efficiency Economic (Overall) Code (TE-VRS) (SE-CRS) Efficiency (EE) Efficiency Level UBSI 1.000 1.000 1.000 Full ABCO 1.000 0.893 0.893 inefficient INVB 1.000 0.808 0.808 inefficient EXFB 0.965 0.987 0.952 inefficient SGBJ 1.000 1.000 1.000 Full CABK 1.000 1.000 1.000 Full BOJX 1.000 0.969 0.969 inefficient AHLI 0.944 0.983 0.928 inefficient ARBK 1.000 0.851 0.851 inefficient THBK 1.000 1.000 1.000 Full Mean 0.980 0.952 0.934 Source: output from the DEAP computer program version 2.1 The average overall efficiency level for the Jordanian banks is (0.934) which implies a gap of 0.17 (17%) from the full efficiency level. According to the Data Envelopment Analysis (DEA); full efficient banks with TE I (Input orientated technical efficiency) value of 1.0 lies on the DEA efficient frontier and their peers are themselves. Table (8) presents each bank peers and the peer weights. For example AJIB bank has TE I of (0.826) which means that AJIB bank should be able to reduce the consumption of all inputs by (17.4%) without reducing output. Also, AJIB bank has three peer banks: CABK, JCBK and INVB with peer weights of (0.196, 0.304, 0,499) respectively. This implies that these peers of AJIB bank define where the relevant part of the frontier is and hence define the efficient production for AJIB bank. Table 8: Summary of peers for each bank Bank Code Bank peers peer weights JOKB JOKB 1.00 JCBK JCBK 1.00 AJIB CABK, JCBK, INVB 0.196, 0.304, 0,499 UBSI UBSI 1.00 ABCO ABCO 1.00 INVB INVB 1.00 EXFB EXFB, JOKB, SGBJ, JCBK 0.344, 0.387, 0.270 SGBJ SGBJ 1.00 CABK CABK 1.00 BOJX BOJX 1.00 AHLI AHLI, JCBK, JOKB, SGBJ 0.401, 0.230, 0.369. ARBK ARBK 1.00 THBK THBK 1.00 Source: output from the DEAP computer program version 2.1 For deep analysis TE, SE and EE were estimated for each bank during the period from 2005 to 2015. The overall efficiency levels for each bank were presented in table 8. Table 8: Technical, Scale and Overall Efficiencies for each Bank during 2005-2015 Bank's 2005 2006 2007 2008 Code TE SE EE TE SE EE TE SE EE TE SE EE JOKB 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.541 0.541 1.000 1.000 1.000 JCBK 0.874 0.954 0.834 0.850 0.928 0.789 0.968 0.998 0.966 1.000 1.000 1.000 AJIB 0.772 0.601 0.464 1.000 1.000 1.000 0.722 0.896 0.647 0.705 0.985 0.694

452 Asma a Al-Amarneh and Hadeel Yaseen UBSI 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 ABCO 1.000 0.886 0.886 0.989 0.810 0.801 1.000 1.000 1.000 1.000 1.000 1.000 INVB 1.000 0.854 0.854 1.000 0.870 0.870 1.000 1.000 1.000 1.000 1.000 1.000 EXFB 0.710 0.994 0.706 0.944 0.984 0.929 1.000 1.000 1.000 1.000 1.000 1.000 SGBJ 0.744 0.779 0.580 0.678 0.974 0.660 1.000 0.925 0.925 1.000 0.960 0.960 CABK 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 BOJX 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 AHLI 0.582 0.995 0.579 0.740 0.973 0.720 0.878 0.947 0.831 0.929 0.977 0.908 ARBK 1.000 1.000 1.000 1.000 1.000 1.000 0.545 0.987 0.538 1.000 0.917 0.917 THBK 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.874 0.874 Bank's 2009 2010 2011 2012 Code TE SE EE TE SE EE TE SE EE TE SE EE JOKB 1.000 0.810 0.810 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 JCBK 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 AJIB 0.746 0.989 0.738 0.839 0.839 0.704 0.892 0.864 0.771 0.934 0.889 0.830 UBSI 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 ABCO 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 INVB 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.752 0.752 1.000 0.797 0.797 EXFB 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.856 0.856 1.000 0.871 0.871 SGBJ 1.000 1.000 1.000 1.000 0.642 0.642 1.000 0.981 0.981 1.000 0.918 0.918 CABK 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 BOJX 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.976 0.976 0.878 0.991 0.870 AHLI 1.000 1.000 1.000 1.000 0.995 0.995 1.000 0.961 0.961 1.000 0.362 0.362 ARBK 0.586 0.606 0.355 0.199 0.862 0.172 0.172 0.886 0.152 1.000 0.286 0.286 THBK 1.000 1.000 1.000 1.000 0.972 0.972 1.000 0.746 0.746 1.000 0.646 0.646 Bank's 2013 2014 2015 Code TE SE EE TE SE EE TE SE EE JOKB 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 JCBK 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 AJIB 0.819 0.984 0.806 1.000 1.000 1.000 1.000 0.954 0.954 UBSI 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 ABCO 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 INVB 1.000 0.979 0.979 1.000 1.000 1.000 1.000 1.000 1.000 EXFB 0.856 0.395 0.338 1.000 0.433 0.433 1.000 0.536 0.536 SGBJ 1.000 1.000 1.000 1.000 0.847 0.847 1.000 0.795 0.795 CABK 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 BOJX 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 AHLI 1.000 0.928 0.928 0.960 0.214 0.205 0.963 0.504 0.485 ARBK 0.404 0.755 0.305 0.132 0.982 0.130 0.122 1.000 0.122 THBK 1.000 0.841 0.841 1.000 0.869 0.869 1.000 0.520 0.520 Source: output from the DEAP computer program version 2.1 The geometric average growth rate was calculated for each type of efficiency for all selected banks. Figures 5 show that four banks (JOKB, UBSI, CABK, and BOJX) keep a stable level of TE, SE and EE during 2005-2015, the AHLI bank show the highest growth in technical efficiency (5.16%) as a result of high decrease in scale efficiency (-6.58%) during the study period, while the ARBK show the highest decrease in technical efficiency (-18.97%) as a result of increase in scale efficiency (13.09%). To examine the effect of the world financial crises on Jordanian bank s efficiency, an in-depth examination of efficiency levels for the years 2007, 2008 and 2009 was made. The figures show that before the financial crises the mean technical, scale and economic efficiencies of the selected banks were (0.932, 0.946, 0.881) respectively, while the year after the financial crises the figures were (0.949, 0.978, 0.916) indicating an improvement in all types of efficiency levels. 4.2 Bank Efficiency and Economic Freedom The next step in our research is to test the linkage between the efficiency levels on Jordanian banks and the economic freedom index, which obtained from by the Heritage Foundation during the period 2005-2015. The Economic Freedom (EcoF) vector can be define as follows; EcoF i = (Business i, Corruption i, Monetary i, Financial i, Govspend i, Freedom i) (2) 5 Calculation made by the other but not shown here.

Bank Efficiency and Economic Freedom: Case of Jordanian Banking System 453 The Economic Freedom (EcoF) include the following variables from Heritage Foundation: Business freedom; a measure of the ability to establish and run a business freely. Corruption freedom; the distortion by individuals, the higher level of corruption, the lower economic freedom. Monetary freedom; a measure of price stability. Financial freedom; a measure of banking efficiency. Government Spending, the high level of government spending indicating the level of government contribution in the economy. Economic freedom or Freedom index; the aggregate measure of overall economic freedom. Turning to the variables explaining economic freedom, the results uncovered a significant relationship with banking efficiency of Jordanian banks, a regression has estimated efficiency scores on economic freedom indexes. The results exhibit a strong relationship between efficiency level and business freedom, monetary, financial freedom, government spending, freedom index, fiscal policies and investment. All estimated coefficients indicating a significant relationship except freedom from corruption. Table 9: Regression analysis Economic Freedom Efficiency (EE) Technical Efficiency (TE) EE/TE BUSINESS 0.000353** -9.85E-05-0.001269*** CORRUPTION 0.000430 0.000224 0.001556** MONETARY -0.006167*** 0.001288*** -0.004343*** FINANCIAL -0.003819*** -0.013554*** 0.009494*** GOVSPEND -0.005789*** -0.000216-0.003192*** FREEDOM -0.007051*** -0.000297-0.013020*** FISCAL -0.004642*** 0.000945*** -0.007195*** INV -0.000778*** -0.000432*** -0.001429*** Conclusion This research examines the relationship between economic freedom and bank s efficiency by taking a sample of 13 Jordanian banks over the period 2005 2015. We first produce Efficiency scores which were obtained by using the Data Envelopment Analysis (DEA) methodology, then we regress the efficiency score on economic freedom indexes while controlling the bank's profitability, which was measured through the ROE and the logarithm of total assets. The results revealed that the variables capturing business freedom, monetary freedom and financial freedom are associated with improved banks efficiency, indicating a clear relationship between the financial counterparts of economic freedom indexes and the bank efficiency measures exist. Hence, our results suggest that the excessive government intervention in banking activities adversely impacts the efficiency of the banking sector. References [1] Al-Faraj, T., Alidi, A., and Bu-Bshait, K. (1993). Evaluation of bank branches by means of data envelopment analysis. International Journal of Operations and Production Management, 13, 45 52. [2] Al-Faraj, T., Bu-Bshait, K., and Al-Muhammad, W. (2006). Evaluating the efficiency of Saudi commercial banks using data envelopment analysis. International Journal of Financial Services Management, 1(4), 466-477. [3] AlKhathlan, K., Abdul Malik, S. (2010). Are Saudi Banks Efficient? Evidence Using Data Envelopment Analysis (DEA). International Journal of Economics and Finance. 2(2); May 2010. [4] Ajlouni,Moh'd, Hmedat,Mohammad and Hmedat,Waleed.(2011).The Relative Efficiency of Jordanian Banks and its Determinants Using Data Envelopment Analysis. Journal of Applied Finance & Banking, vol.1, no.3, 2011, 33-58.

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