Indian Banking Industry Competitiveness and Market Structure

Indian Banking Industry Competitiveness and Market Structure Introduction After 1991 crisis, Indias liberalisation journey was multi-faceted. One of the major areas of liberalization was the banking sector which was highly regulated and controlled by government. Most importantly for banking industry, as per the M. Narasimhan committee recommendations, the liberalization came in the right areas namely interest rate, reduction of reserve requirements, entry deregulation, credit policies and prudential supervision. Incase of interest rates, they could now be determined by the banks based on their cost of funds rather then government fixing them for banks. The administered regime for interest rate came to an end except for interest rate on savings account. The reduction of reserve requirement for banks made huge capital available for banks which could be deployed in the business. The entry of new players was de-regulated. The government empowered the Reserve Bank of India to issue licenses to the new players, if they met the set criteria jointly set by RBI and Finance Ministry. The credit rationing was completely done away with. Although there is still credit rationing for priority sector, the banks are free to deploy their capital on the sectors which they feel profitable. Excessive supervision regime came to an end. The Reserve Bank of India made several changes in prudential supervision and gave autonomy to banks in their day-to-day operation. The total asset size of Indian Banking industry is over US$ 270 billion. The total deposit amount is US$ 200 billion. Its branch network is one of the largest in the world with more than 66,000 branches and over 17,000 ATM spread across the country. The bank assets are expected to grow at 13.4% CAGR and it is predicted that India could become the 3rd largest banking hub in the world by 2040. Currently India has 80 Scheduled commercial banks out of which 28 are public sector banks, 24 private banks and 28 foreign banks (Annual Report, RBI). As Indian economy is growing at an average rate of over 7% since a decade, more and more foreign banks are thinking to foray into the Indian market. As per McKinseys report on Indian Banking (2010), total loans-to-percentage of GDP, could grow from its current level of around 30% to ~45% in years to come. Such huge opportunities also  prompts several questions: Who is/ are the dominant players in the market? What is/are their share in the banking industry? What is the market structure of Indian banking industry; is it a monopoly or a perfect competition? Objectives and Motivation: The objective of this dissertation is to understand the Indian banking industry, its composition (nationalised banks, private bank and foreign banks) and knowing the players of the industry. Further the study will find out how much concentrated the Indian banking industry is and provide knowledge regarding top 3 as well as top 5 major banks. Such a concentration ratio would give a fair idea of how decision of the top players as an implication on the other industry players. The study will include the determination of the market structure of Indian banking industry. Its imperative to know whether the industry is a perfect competition, a monopoly or a monopolistic competition. This would lead to understanding of the cohesive behaviour of the market players. My motivation for choosing this topic came from the complexity of the Indian banking industry. The number of players, entry of new players, consolidation among the existing players, ever-changing economic scenario of India etc and its impact on the banking industry always fascinated me to do a study on the Indian Banking industry. I also feel that such study would be useful not only for the policymakers within the central bank and the government but also for the existing players, the potential entrants and for other stakeholders of the banking industry. Literature Review As per the neoclassical theory, the spectrum of market structure can be defined by the number of firms and size of those firms in the market [Goddard, Molyneux Wilson (2001)]. Various numerical measures of concentration have been used by empirical researchers in order to find the concentration of industry players. But at the same time, there is no single perfect measure for concentration [Goddard, Molyneux Wilson (2001)]. Nevertheless all these measure are subject to the idiosyncracies and limitation; they usually tend to correlate highly with each other [Curry and George (1983); Scherer and Ross (1990)]. Hall and Tideman (1967) have provided the desirable properties which are required for these measures of concentration to be acceptable. Concentration measures like k-bank concentration ratio, Herfindahl-Hirschman index (HHI) are extensively used to measure the banking sector performance as a function of market structure [Barth et al., 2004, Beck at el, 2006)]. k-bank concentration ratio For measuring the concentration of firms, the most frequently used ratio is k-bank concentration ratio (Bikker 2004). The reason this ratio is so frequently used is because of its simplicity and limited data requirement. The index gives equal emphasis to the k leading banks, but neglects the many small banks in the market. It is a one dimensional measure ranging between zero and unity [Al-Muharrami S.,Matthews k., Khabari Y (2006)]. In a review of 73 US Structure-Conduct-Performance studies in banking from 1961 to 1991, in 37 studies the k-bank deposit concentration measure was used (Molyneux et al. 1996) Herfindahl Hirschman Index (HHI) HHI is another benchmark measure for measuring the bank concentration and gives more weight to larger banks. It was developed by A.O.Hirschman. It expands to all the banks in the system, thereby avoiding the arbitrary cut offs [Alegria, C and Schaeck K (2006)]. Bikker (2004) highlights the importance of HHI in the theoretical research. In practice, the HHI plays a pivotal role in the US for the approval of bank mergers where the post mergers market HHI cannot exceed 0.18 and that the change in the index should be less than 0.02 (Cetorelli, 1999). This index is also used to measure the bank concentration in Arab GCC banking system [Al-Muharrami S.,Matthews k., Khabari Y (2006)] and in measuring the competition and market structure in the Saudi Arabia [Al-Muharrami (2009)] Panzer and Rosse H statistics The measure of market structure helps in determining whether the market enjoys perfect competition, monopoly or monopolistic competition. This is also known measuring the monopoly power hypothesis. It means that in more concentrated markets the bigger players tend to be collusive and try to dominate the market. Also their actions have considerable impact on the other market players. There are several models for determining the market structure. The models are divided into two parts: 1) Structural Models and 2) Non Structural Models. This study will employ the non-structural model approach suggested by Rosse and Panzer (1977) and Panzer and Rosse (1982, 1987), popularly known as the H-statistics. It is widely used in determining the competitive structure of the banking industry in various countries. In the banking industry, there is extensive use of Rosse and Panzer method and has got a wide practical applicability. In his study on New York banks, Shaffer (1982) had observed that banks had monopolistic competition. Similar study for Canadian banks by Nathan and Neave (1989) found a perfect competition for 1982 but monopolistic competition for 1983-84. Japan revealed perfect competition [Molyneux et al (1996)]. Molyneux et al. (1994) also tested the P-R statistics for French, German, Italian, Spanish and British banks for the period of 1986-1989 in order to determine the competitive conditions of major European countries. Methodology The study involves the use of k-bank concentration ratio and HHI ratio for gauging the competition and Panzer and Rosse for determining the monopoly power of the players of Indian Banking industry. These ratios have been extensively used in the different studies mentioned above. K-bank concentration ratio measures the market share of the top k-firms in the industry. The equation is n CRn = à ¢Ã‹â€ Ã¢â‚¬ËœSi i=1 Where Si is the market share of the i-th firm when firms are ranked in descending order of the market share. Market share is measured in terms of sales, assets or number of employees. Commonly used values of n include 3, 4, 5 or 8. The researchers have also found that there is high correlation between concentration ratios defined using alternative values of n [Bailey and Boyle (1971)]. The advantage of k-bank concentration ratio is that it is easily measurable; one needs to know only the total size of the industry and the individual sizes of firms. But it lacks in taking the size distribution of remaining firms. In this study, the market share would be measured on the basis of the loan size (assets) and the deposit size (liability) of the banks. The value of n would be 3 and 5 i.e. CR3 and CR5. HHI uses information about all points in the firm size distribution. It is defined as the sum of the squares of the markets share of all firms: N HHI = à ¢Ã‹â€ Ã¢â‚¬ËœSi2 i=1 Where Si is the market shares of the firm i and N is the total number of firms in the industry. In the calculation of HHI, the larger firms get a heavier weightage than their smaller counterparts which reflects their relative importance in the market. This study uses P-R h-statistics, a non-structural model, measuring competition and emphasizes the analysis of the competitive conduct of banks without explicit information about the structure of the market. The P-R determines the competitive behaviour of banks on the basis of the comparative static properties of reduced-form revenue equation based on cross-section data [Panzer and Rosse (1987)]. The equation is Ln(TREV) = ÃŽÂ ±0 + ÃŽÂ ±1 ln PL + ÃŽÂ ±2 ln PK + ÃŽÂ ±3 ln PF + ÃŽÂ ±4 ln RISKASS + ÃŽÂ ±5 ln ASSET + ÃŽÂ ±6 ln BR The variables are defined as follows: TREV : the ratio of total revenue to total assets PL : ratio of personnel expense to employees PK : ratio of capital expense to fixed assets PF : ratio of annual interest expense to total loanable funds RISKASS : ratio of provisions to total assets ASSET : bank total assets BR : ratio of number of branches to total number of branches in the country. The H-statistic value is the sum of factor price elasticity: PL, PK and PF. The value H à ¢Ã¢â‚¬ °Ã‚ ¤ 0 implies monopoly equilibrium. A value of 0 Data The data for all the calculations of k-bank concentration ratio, HHI and P-R H-statistics will be obtained from Orbis database. Further, the data would also be taken from the Reserve Bank of India(RBI)s profile of banks 2004-2005 2008-2009. Incase any data is not available from the two main sources (Orbis and RBI), the data would be extracted from financial statements of banks, from their websites and from reports published on the Indian Stock exchanges namely Bombay Stock Exchange (BSE) and National Stock Exchange (NSE). The sample period covers 2002-2008. Conclusion The conclusion would include the interpretation of the results obtained by usage of E-view and MS- Excel software. In summation, the study would help in knowing the concentration ratio through k-bank ratio as well as HHI and help in understanding the monopoly power of large banks in India. Such a study would be helpful to determine the cohesive behaviour of the players of industry and how their decision would affect the entire industry as well as the Indian economy. With a lots consolidation happening in the industry, such a study would help in understanding the shifts in the concentration and market powers if any. Last but not the least; an attempt would be made to give some recommendations based on the results.