Islamic Banking Competitiveness in Indonesia

Transcription

1. ISLAMIC BANKING COMPETITIVENESS IN INDONESIA Helma Malini ¹ Universitas Tanjungpura, Indonesia Alifah Nurrahmani Putri² Universitas Tanjungpura, Indonesia ABSTRACT Financial integration in the ASEAN Economic community (AEC) by 2020 forces Islamic banks in Indonesia to be more competitive and have market power domestically and internationally to ensure business sustainability and increase assets rapidly in order to boost market share of Islamic banking in Indonesia. Islamic bank market competitiveness and power will determine the returns, investment, asset and trust in Islamic banks. The study uses data from 10 Islamic banks in Indonesia. The result confirmed that Islamic banking in Indonesia is characterized by the monopolize industry. JEL : E58, E59 Keywords : Islamic Banks, Market Structure, Bank Competition, Indonesia. 1. INTRODUCTION The Islamic Banking industry grows based on the basis of beliefs in religion supported by the implementation of the risk sharing concept depending on a number of pre-requisites such as transparency and accountability, good governance, contacts enforcement, effective monitoring, well-structured economic institutions, and efficient financial markets (Ying et al., 2016). Islamic banking industry has become a supporter of economic growth and an important part of the national financial industry. In Asia, the growth of Islamic banking is represented by two countries, namely Indonesia and Malaysia. The two country becomes hubs for the Shariah Industry in Asia and become a reference in relation to the latest Shariah developments, particularly Islamic banking in ASEAN (Peni & Vähämaa, 2012) According to (Hopt & Von Hippel, 2010), financial integration of ASEAN should fulfill these three frameworks, which are equal access, equal treatment and equal environment. These factors will be able to achieve if market where Islamic bank competing are competitive and diversely concentrate. Islamic banking in Indonesia is expected to achieve the qualification standard of qualified ASEAN bank (QAB) in the hope to compete with other Islamic banking. However, Indonesia Islamic banking industryhas to strengthen their competitiveness within International banking environment in order to handle the impact of diverse market concentration. This paper investigates the impact of structural changes due to the improvement of Islamic banking rules particularly on the competitiveness level of Islamic bank Industry. Competitiveness levels lead Islamic banking to concentrate on diverse market. Lipczynski (2005) stated that market concentration has implication toward level of competitiveness of company in a market or industry. While, Islamic banking industry diverse due to business environment complexity (Al-Muharrami & Matthews, 2009). The analysis of competitiveness level and market power Islamic bank in Indonesia is expected to provide map of assessment for a better business environment and to support ASEAN financial integration in 2020. Therefore, this study examined market concentration with the objective to find level of competitiveness among Islamic bank in Indonesia and assessing market power of Islamic banking in that countries. This research is very important to conduct since it will provide special treatment for Islamic bank in one side and realize the core concepts of Islamic banking regulation 241
2. 242 and asses the level of competitiveness and market concentration in order to achieve financial integration in term of fairness , transparency, protection for Islamic banking environment. 2. LITERATURE REVIEW (Malini, 2016) in their research about competitive condition and market power of Islamic and Commercial Conventional Banks in Indonesia between 2006 and 2013 suggested that the banking markets of Indonesia cannot be characterized by the bipolar cases of either perfect competition or monopoly. That is, banks earned their revenues operating under conditions of monopolistic competition in that period. However, research conducted by (Malini & Putri, 2020) about market power and efficiency of Islamic Banking and Conventional Banking in Indonesia in the period of January 2009 to December 2016 showed that SCP (Structure-Conduct-Performance) hypothesis is closely applied to Islamic and conventional banks because market concentration significantly influences profitability. RMP(Relative Market Power) hypothesis is also closely applied to Islamic and conventional banking, this indicates Indonesian banking has market power in determining prices and this condition makes the profit higher. Moreover, (Peni & Vähämaa, 2012) measured the competitiveness of Islamic Banking in Indonesian dual banking system from 2003 to 2005 and found that Islamic banking is relatively more efficient than conventional banking. This means that Islamic banks are competitive enough to compete with conventional banks. Islamic banking is technically more efficient, but less scale efficient than conventional banking. 3. METHODS 3.1. Data Collection Islamic banking in Indonesia is an industry that has undergone structural changes due to the dual banking system and the liberalization process. In Indonesia, conventional banks also offer Shariah units lead to a clustered Islamic banking industry. At the end of 2019, there are 14 Islamic banks in Indonesia. The identification of problems in this study are (1) What is the condition of the competition Islamic banks in Indonesia during the 2015-2019 period? and, (2) What is the market power of Islamic banks in Indonesia during the 2015-2019 period? Thus, selection of banks as sample on the basis of the relevance of these banks as bank institutions that provide products with close substitutes within research period where number of samples in this study were 10 Islamic banks in Indonesia. Data obtained from annual reports of each bank in Indonesia during the study period, taken from the bank's official website and combined with data obtained from Bank Indonesia, as the financial authority service. Table 1 . List of Islamic banks in Indonesia (2019) No Name of Bank 1 Bank Muamalat 2 Bank Syariah Mandiri 3 Bank Mega Syariah
3. 243 4 Bank BRI Syariah 5 Bank Syariah Bukopin 6 Bank BNi Syariah 7 Bank BCA Syariah 8 Bank Panin Syariah 9 Maybank Syariah Indonesia 3 .2. 3.2.1. Methodologies Concentration measure Since the purpose of study is to evaluate market concentration measures, hence absolute and relative measures will be calculated based on the weighting scheme as shown in Table 1. The weighting scheme of anumber of concentration ratios discussed in this study is based on Marfels as stated by. They are as follows: Table 2. Features of Concentration Measure ConcentrationMeasure ConcentrationFormula Ratio Range TypicalFeatures Concentration ratio of n bank n 0 <CRn= 1 Only takes large banks into account 1/n = HHI= 1 Considers all banks; sensitive to entry of new CRn =∑si i=1 HHI N HHI =∑si2 i=1 entropy N banks 0 = EH =log n EH = −∑silnsi i=1 Relative entropy R = EH/ln N Based on expected information content of a distribution 0 <R = 1 Based on expected information content of a distribution Hannan and Kay (HK) N Index HK(α) = ∑ siα 1/s = HK =n Sensitive to size distribution; a< 1 stresses the
4. 244 i =1 influence of small banks and a> 1 stresses the influence banks Comprehensive Industrial Concentration (CCI) N 0 <CCI =1 CCI = s1 +∑ si2 + (1−si) Index 0 Addresses relative dispersion and absolute 0 <G= 1 Accounts all banks in the market, shows Inequality in distribution. variance Logarithms of the VL = (1––N)∑Ni=1[loge(si) s–]2 (vL) Numbers (Ne) Ne for HK Ne entropy equivalents large Magnitude. i=1 G= 1 − 2∫1L(X)d(X) Gini Index of the Shows inequality in the distribution. NE HK(a) = (N∑i=1si)2 /(1a) An inverse measure of concentration, show N NE Entropy = eEH Equal-sized of firms in an industry. The methodology is based on set of measures of the competition and market power. The first measure is a set of concentration ratios (CR) and HHI index. The second measurements are the PR-H statistic and the Lerner index based on econometric estimations with the aim of evaluating the structure of market and measuring its power in term of price setting. This research implements two steps to study the Islamic banks market power competitiveness in Indonesia. The first is to measure the competition of Islamic bank and identify the market power using PR-H statistic and the Lerner index. 3.2.2. The Herfindahl-Hirschman Index The HHI is another traditional measure of the competition and the concentration of the market conceived by (Rhoades, 1993) Since 1982, theUS Department of Justice has based its merger guidelines on this index. It is thenwidely applied to estimate the level of competition of a market and its structure: where Si2 is the market shares of the company i and n is the number of companies. This indicator is calculated by adding the squares of the market shares of every banking the market or a country and it varies between zero (situation of pure and perfect competition) and 10,000 (1002: monopoly
5. 245 position ). The higher the value of the indication, the more concentrated the market, and the weaker is the competition between the agents. The aim of the market is therefore to establish a monopoly position and increase market power. Declination indicates the opposite. According to the current U.S. screening guidelines, if the HHI is less than 1,000, the banking industry is considered a competitive market, a somewhat concentrated market if the HHI is between 1,000 and 1,800, and a very concentrated market if the HHI is more than 1,800. If the post-merger market HHI is less than 1,800 points and the pre-merger index increase is less than 200 points, the merger is considered to have no anti-competitive effects and is accepted by the regulators. 3.2.3. Panzar and Rosse (PR) Model A test developed by (Panzar & Rosse, 1987) examined whether the behavior at company level is consistent with either the model of perfect competition, the model of monopolistic competition or the model of monopoly. This test is based on an empirical study of the price variation impacts of the inputs on the company’s income. It is obtained by the sum of the price elasticity of the inputs (Hstatistics). The H-statistic is estimated from the reduced form of the bank revenue equation as the sum of the elasticity of the bank's total revenue in relation to the bank's input prices. H-Statistics vary between 0 and 1, with less than 0 being monopoly, less than 1 being monopolistic competition and 1 being perfect competition. Table 3. Interpretation of the Rosse-Panzar H-Statistic Estimated H statistic H=0 Competitive Environment test Equilibrium test Monopoly equilibrium H < 0 Disequilibrium Perfect colluding oligopoly H = 0 Equilibrium Conjectural variations short-run oligopoly 0<H<1 Monopolistic competition free entry equilibrium H=1 Perfect Competition Natural Monopoly in a perfectly contestable market Sales maximizing firms subject to break even constraint Source: Panzar&Rosse, 1987; Nathan & Neave, 1989; Shaffer, 1982; and Molyneux et al 1996 The following log-linear revenue equationwhich is a variation of the Panzar and Rosse (1987) methodology:
6. 246 ln TRit = a + ß1 lnW1it+ ß2ln W2it + ß3ln W3it + ß4 lnZ1it+ ß5lnZ2it+ 6lnZ3it + eit (1) The dependent variable TR itindicates total revenues measured by the ratio of interest and non-interest revenues to total assets, following Nathan and Neave (1989). Equation (1) includes three input prices: W1 is a proxy for input price of deposits. It is the ratio of total interest expenses to total deposits and money market funding. W2 is a proxy for input price of equipment and other fixed capital. It is the ratio of other operating expenses over total assets. W3 is proxy for input price of labor. It is the ratio of personnel expenses over total assets. The analysis includes other bank-specific control variables to capture bank-specific effects; three control variables are included in the equation (3). Z1 represents the ratio of net loans to total assets to capture the risk component, Z2 stands for total assets to account for possible scale economies, and Z3 denotes the ratio of equity to total assets to capture the impact of capitalization; eit is a random disturbance term. The subscripts’ and t refer to bank ioperating at time t. It consistent with (Panzar & Rosse, 1987), the application of the PR framework to banking requires three assumptions. First, banks are single product firms that produce interest revenues using labor,capital, and deposits as inputs (De Bandt and Davis, 2000); second, higher factorprices do not correlate with higher revenues generated by higher quality services; and third, banks are profit-maximizing firms with normally shaped cost and revenue functions (Gelos and Roldos, 2004). More importantly, banks should be observed from a long-run equilibrium perspective, for which this study tests using the following equation: ln ROA = a + 1lnW1it + 2 ln W2it+ 3 ln W3it + 4lnZ1it + 5 lnZ2it+ 6lnZ3it +eit (2) where ROAitis the ratio of pre-tax profits to total assets that measures a bank’s return on assets. The subscript i denotes bank i, and the subscript t denotes year t. All the variables in the righthand side of the equation are similar to the variables in equation (3). The equilibrium statistic, E, is the sum of input price elasticity’s, i.e. E = 1+2+3. The interpretation of this statistic is as follows: a value of E significantly different from zero implies that the market is not in equilibrium because in the long-term, the variation of the yields on assets does not relate to the variation of the prices of the inputs. However, in the presence of positive values of the PR-H statistics. Shaffer (2004) underlines that the rejection of the test of equilibrium does not distort the inferences based on the results of the estimation of this indicator. 3.2.4. The Lerner index and the Power of Pricing The market power can be considered as the capacity to sell products over the marginal cost. The Lerner index is one of the most popular and the oldest indexes of market power. It is a direct measure of competition through the distance between the price and the marginal cost. The Lerner index (LI) is computed using the formula as follows:
7. 247 where P is the price of banking outputs and MC is the marginal cost . Following the approach in Berger et al. (2008), we proxy bank output by using Total assets, P is calculated as total bank revenues over assets, and MC is calculated by taking the derivative from a translog cost function shown in equation (3): Where TC is the total operating plus financial costs; TA (i.e. Total assets) is a measure of bank production. W1, W2, and W3 are the same input prices used in equations (1) and (2) and defined above. Finally, idenote banks and t denotes years, α denotes bank-level fixed effects and ε is an error term. The estimated cost function coefficients are then used for the calculation of marginal costs. Indeed, given that the marginal cost is the derivative of the total cost to output (here total assets), it can be derived that the derivative of the total cost logarithm to the output logarithm is the ratio of marginal cost to total cost multiplied by output. As a result, the marginal cost is equal to the product of the derivative of the logarithm of the total cost to output multiplied by the ratio of the total cost to output). The Lerner index is generally between 0 and 1. Lerner index = 0, mean a perfectly competitive behavior and the firm has no market power.The Lerner index close to 1: shows the weakness of competition at the price level and that the firm exercises market power thanks to a higher mark-up. An increase in prices or a decrease in the marginal cost of the company are two elements which can explain the increase of the index. However, it can register negative values which can be explained as a consequence of a very strong competition obliging the firms to propose a price lower than the marginal cost, or they can correspond to the period of introduction on the market which is characterized by a very high rate of charges. 4. RESULTS AND DISCUSSION Table 4. Summary Statistics Variable Mean Std. Dev Total Revenue (TR) 1.0786 78.4321 Total Cost (TC) 1.1750 50.8800 Output (q) 17.7800 789.240 Total Assets (Z2) -23.6600 13.4000 Return On Assets (ROA) 1.29320 66.3451 Return On Equity (ROE) -1.89712 5.23403
8. 248 Price of Deposits (W1) 8.6890 3.7654 Price of Capital (W2) 14.6055 8.57324 Price of Labor (W3) 14.8930 3.55500 Loans Ratio (Z1) 18.1281 100.000 Capital Ratio (Z3) 10.7166 0.00000 Efficiency (TDTA) 1.4638 12.1174 Capitalization (EQTA) -0.2426 3.81701 Variables total revenue (TR), total cost (TC), output (q), and total assets (Z2)are expressed in million Indonesian Rupiah. Table 5 presents a statistical summary of the variables used in the empirical analysis. Mean and standard deviations for the dependent variable, totals income (TR), and return on assets (ROA) remained stable throughout the sample point. In terms of return on equity, the average mean of ROE is highly contributing to the performances of Islamic banks. ROA contributing to risk exposure of Islamic banks in Indonesia since one of the considerations for investor to invest in Islamic banking is sense of security that translates into capital stability. Efficiency mean in Indonesia is (1.4638) contradicts with Indonesia standard deviation at (12.1174). This translates as the average cost-to-income comparison of Islamic banks has varied greatly. When Islamic banks can optimize the use of its assets, which primarily consist of customers saving, efficiency can be achieved. Table 5. Trends in Absolute Measure of Concentration in Indonesia Islamic Banking Industry Year/Measures 2015 2016 2017 2018 2019 No. of Banks 10 10 10 10 10 CR(%) 2 0.80 0.80 0.85 0.80 0.73 CR(%)3 0.97 0.93 0.90 0.90 0.80 CR(%)4 0.49 0.48 0.44 0.33 0.29 CR(%)5 0.45 0.84 0.90 0.80 0.78 CR8 (%) 0.51 0.53 0.39 0.42 0.45 Entropy 1.60 1.43 1.23 1.40 1.33 Re 0.22 0.43 0.33 0.33 0.45 CCI 0.03 0.07 0.01 0.09 0,01 CR
9. 249 HK (1.5) 0.12 0.18 0.17 0.20 0.25 HK(2) 0.19 0.17 0.18 0.19 0.18 HK(2.5) 0.18 0.16 0.19 0.20 0.21 HK (1.5) 6 7 8 9 7 HK(2) 5 7 6 4 7 HK (2.5) 8 7 9 2 7 entropy 11 14 17 16 18 NE Notes: CR = concentration ratio, HHI = HerfindahlHirshman index, RE = relative entropy, HK = Hannah and Kay index, NE = number of equivalent.Source: Calculated by authors Table shows the market concentration in Islamic banking in Indonesia. The decline in total assets shows an increase in the number of banks in Islamic bank in Indonesia and Malaysia. In terms of market concentration, Islamic banking in Indonesia can be classified as Monopoly market because of the dual banking system, so there is still a dependency between Islamic banks and their conventional units which are still integrated. In addition, over the last five years the Indonesian Islamic banking has largely focused on Monopoly market because the three major Islamic banks have the ownership of assets: BCA Syariah, BNI Syariah and BRI Syariah where those are still integrated with their conventional parent banks which facilitate their subsidiary to access their banking networks, systems and infrastructure (Al-Muharrami et al 2005). Table 6. Market Concentration of the Indonesian Banking System Over the Period 2006-2013 HHI Number of Banks Year Assets Deposit Loan 2015 10 0.3576 0.02024 0.01723 2016 10 0.1183 0.01278 0.02272 2017 10 0.3233 0.00872 0.01691 2018 10 0.1238 0.01100 0.01967 2019 10 0.1396 0.01416 0.01751
10. 250 Referring to market concentration it is found that HHI total assets showed a declining trend during the study period in both Indonesia and Malaysia . During the 2015-2019 period Islamic banking in Indonesia was concentrated in a medium distribution where HHI exceeds 1000 and less than 1800 where markets with the above HHI value results are considered to be included in the market characterization of monopoly or weak oligopoly competition (Widyastuti and Armanto, 2013). This is consistent with the study by Natadipurba (2004) on Malaysia and studies on other developing countries that find H-statistics between zero and one and monopolistic competition (Al-Muharrami et al., 2006; Perera et al.,2006). The weak monopoly and oligopoly competition market for Islamic banking in Indonesia is characterized by rapid growth in 2008 to 2013. Meanwhile after that year the period of development of Islamic banks was stagnant after 2014. The slowdown in 2015 triggered the fall in Islamic banking assets as compared with conventional banks. Concentration of market ownership strength, however, when selecting Islamic banks in Indonesia with a "survival of the fittest" framework where banks with ownership of assets, networks, and systems as they derive from traditional banks can better dominate the market (Shaw, 2006). Table 7. Equilibrium test: Fixed Effect Estimation Result of Islamic and Conventional Banks Islamic Banks in Indonesia coef. t-stat Price of Deposit (lnw1) -0.0196 -0.2283 Price of Capital (lnw2) -0.0213 -0.3616 Price of Labor (lnw3) -0.0031 -0.3893 Loans Ratio (lnz1) -0.0035 -0.2333 Total Assets (lnz2) 0.0163 -0.0931 Capital Ratio (lnz3) 0.0509 -0.0904 Constant -0.0081 -0.133 R2 0.0109 -0.1666 E-statistic 0.0251 -0.0588 Wald test (F-test) for E=0 0.0322 -0.1621 Observations Table 8. Competitive structure for Islamic Banks in Indonesia and Malaysia Islamic Banks in Indonesia coef. t-stat Price of Deposit (lnw1) 0.0332656 0.65272 Price of Capital (lnw2) -0.0233915 0.70715 Price of Labor (lnw3) 0.0312119 0.81377 Loans Ratio (lnz1) 0.0112227 0.54915
11. 251 Total Assets (lnz2) -0.0313121 0.34657 Capital Ratio (lnz3) -0.0233192 0.04165 Constant 0.0120816 0.88043 R2 0.0454851 0.65290 H-statistic 0.56939 Wald test (F-test) for H=0 0.0480856 0.00289 Wald test (F-test) for H=1 -0.0196 -0.2283 From above results, it appears that the Islamic market in Indonesia is more monopolistic. Where deregulation on market structure influenced the most toward market composition. Islamic bank in Indonesia also explaining about the capabilities of each bank to asses profit by becoming efficient not only in term of operationalization but also in term of delivering their product to the customer. Furthermore, Islamic bank in Indonesia also showed that there is dynamics development toward Islamic bank market. Islamic banking always try to win the competition by updating their system, facility and services to customer (Liu et al., 2012). 5. CONCLUSION The level of competitiveness and market concentration of Islamic banking Industry in Indonesia confirm that Indonesia Islamic bank is under monopolistic competition. Being in Monopoly market leads to certain benefit where Monopolies in banking can drive growth. This happens because monopolistic banks have an immediate benefit to allocate the majority of their assets to more profitable investment projects. On the contrary, deposit rates at banks operating on the monopolistic market are reducing the interest of depositors in saving; meaning savings to banks are reduced. In terms of liquidity, Indonesian Islamic banks are less competitive with the conventional bank in Indonesia. The reason is due to the transformation of banking landscape in Indonesia and the implementation of dual banking system. In addition, due to moderated concentrate Islamic bank in Indonesia, Islamic bank in Indonesia is hugely influenced by conventional bank. REFERENCES Al-Muharrami, S., & Matthews, K. (2009). Market power versus efficient-structure in Arab GCC banking. Applied Financial Economics, 19(18), 1487–1496. Hopt, K. J., & Von Hippel, T. (2010). Comparative corporate governance of non-profit organizations. Cambridge University Press. Liu, H., Molyneux, P., & Nguyen, L. H. (2012). Competition and risk in South East Asian commercial banking. Applied Economics, 44(28), 3627–3644. Malini, H. (2016). Indonesia Shari’ah compliance stock index responses toward macroprudential and monetary policy of Indonesian central bank. In Macroprudential regulation and policy for the Islamic financial Industry (pp. 213–227). Springer. Malini, H., & Putri, A. N. (2020). Competitiveness and Market Concentration of Islamic Banking Industry: A Comparison Study between Indonesia and Malaysia. SRIWIJAYA INTERNATIONAL JOURNAL OF DYNAMIC ECONOMICS AND BUSINESS, 4(3), 175– 190.
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