我們首先需要承認的是，一個有效的金融部門可以促進整體經濟發展這種觀點可以最早追溯到20世紀初，熊彼特（1911）提出了財政短缺是一種嚴重的發展障礙這個經濟發展理論。由于資本的機會成本主要產生于那些落后的，或者所謂的發展中經濟體中，再加上不發達的金融市場，這種必要性在以上的情況下尤為明顯（Smith，1998）。資金從儲蓄者向借款人的有效流通使得資源得到最有效的配置。金融體系越是如此的產生資源并且配置，它對生產力和經濟增長的貢獻就越大（麥金農1973）。此外，低效率的金融流通附有資金，這可能會導致不良資產配置不當的更大可能性（Barman，2007）。

 

A need recognition of an efficient financial sector to promote overall economic development can be traced all the way back to the early 20th century when Schumpeter (1911) argued in Theory of Economic Development that scarcity of finance is a serious obstacle to development. This necessity is more obvious in the case of backward or so-called developing economies because the opportunity cost of capital is more in them, coupled with underdeveloped financial markets (Smith, 1998). Efficient intermediation of funds from savers to borrowers enables the allocation of resources to their most productive uses. The more efficient a financial system is in such resource generation and in its allocation, the greater its contribution to productivity and economic growth (McKinnon 1973). Further, inefficiency in financial intermediation carries with it the possibility of misallocation of funds, which could result in more non-performing assets (Barman, 2007).

 

Financial intermediaries such as banks are major players in any financial market, and their overall performance is therefore an important determinant of the performance of the financial sector concerned, in particular, and that of the overall economy, in general. Thus, one of the major areas of macro economy that has been the subject of focused attention is the efficiency and soundness of the financial sector. Within the broad scope of the financial sector, a stable and efficient banking system has become the area of attention for research throughout the world. Examining banking performance has been a common practice among banking and finance researchers for a number of years.

 

The main reason for continued interest in this area of research is the ever-changing banking business environment throughout the world. Many countries that adopted financial deregulation policies are now experiencing competitive banking practices. Over time, the banking systems in many developing economies performed poorly, and researchers are diagnosing the problems that are in place. However, the experience with deregulation in the banking sector has been mixed in nature.

 

Productivity and Efficiency#p#分頁標題#e#

 

Production is an act of transforming inputs into outputs. Because the objective of production is to create value through transformation, outputs are, in general, desirable outcomes. Hence, more output is better. At the same time, inputs are valuable resources with alternative uses. Unspent quantity of any input can be used for producing more of the same output or to produce a different output. The twin objectives of efficient resource utilization by a firm are (a) to produce as much output as possible from a specific quantity of input and, at the same time, (b) to produce a specific quantity of output using as little input as possible.

 

Two concepts commonly used to characterize a firm's resource utilization performance are (i) productivity and (ii) efficiency. These two concepts are often treated as equivalent in the sense that if firm A is more productive than firm B then it is generally believed that firm A must also be more efficient. This is not always true, however. Although closely related, they are fundamentally different concepts. For one thing, productivity is a descriptive measure of performance. Efficiency, on the other hand, is a normative measure. While useful as a relative measure of performance, productivity (whether partial or total) has two major limitations. First, in general the unit of measurement of the aggregate input is undefined. Second, a comparison of productivities of two different practices does not tell us anything about how many outputs a particular practice should be able to produce from its actual inputs. A more appropriate measure of the performance of a practice can be obtained by comparing actual output with the maximum level of output producible from its observed bundle of inputs and this leads to the concept of efficiency.

 

Economic Measures of Efficiency

 

Efficiency: Modern efficiency measurement begins with Farell (1957) who drew upon the work of Debreu (1951) and Koopmans (1951) to define a simple measure of firm efficiency which could account for multiple inputs. Farell (1957) proposed that efficiency of a firm consists of two components, namely, technical efficiency (TE) - the ability of a firm to produce existing level of output with the minimum inputs (input-oriented), or to produce maximal output from a given set of inputs (output-oriented); and allocative efficiency (AE) - the ability of a firm to use the inputs in optimal proportions, given their respective prices. Allocative efficiency relates to prices, while technical efficiency relates to quantities (Barros and Mascarennas, 2005). Thus, cost inefficiency incorporates both allocative inefficiency from failing to react optimally to relative prices of inputs and technical inefficiency from employing too much of the inputs to produce a certain output bundle (Gjirja, 2004). In banking efficiency literature, the term cost efficiency is being used interchangeably with economic efficiency, X-efficiency and overall efficiency. In fact, the relationship between CE, TE, and AE is expressed as: CE= TE X AE.#p#分頁標題#e#

 

In measuring input-oriented technical efficiency, all inputs are treated equally and the objective is to reduce all inputs by the same proportion to the extent possible. Thus, once any one input becomes binding no further possible reduction in any other input is considered. But when input prices are available, reducing the more costly input assumes a greater priority than reducing the less costly ones. In this case, efficiency lies in producing the target output bundle y0 at the minimum cost. Suppose that the input price vector faced by the firm is w. Then its actual cost is C0= w'x0. The minimum cost of producing the target output is C (w, y0) = min w'x: (x, y0) ∈T, where x0 is input bundle and T is the state of technology. With reference to the estimated production possibility set, the minimum cost is obtained as C* = min w'x. The cost efficiency of the firm is then measured as γ = C*/ C0.

 

Revenue efficiency: In the measurement of output-oriented efficiency, the objective is to achieve the maximum rate of increase that would be feasible for all outputs. But, as in the case of inputs, some outputs are more valuable than others. When output prices are available, a firm attains efficiency by producing the output bundle that results in the highest revenue at the applicable output prices. Thus, the criterion of efficiency in this case is revenue maximisation. Assume that the output price vector faced by the firm is p. Then the revenue from its observed output bundle would be R0 =p'y0. The maximum attainable revenue, on the other hand, will be R( p, x0) = max p'y : (x0, y) ∈T. Thus, in an empirical application, the maximum revenue achievable from the input bundle x0 is R* = max p'y. The revenue efficiency of the firm is measured as ρ=R*/R0

 

Profit efficiency: In all of the oriented models, either inputs or outputs were treated as exogenously given. For a commercial firm, however, both inputs and outputs will be choice variables and the only constraint would be the feasibility of the input-output bundle chosen. For such a firm, the criterion of efficiency is profit maximisation. At input and output prices w and p, respectively, the actual profit of the firm producing the output bundle y0 from the input bundle x0 is Π0= p'y0 – w'x0. The maximum profit feasible for the firm is Π (w, p) = max p'y – w'x : (x, y) ∈T. In any empirical application, the maximum profit may be obtained as Π* = max p'y – w'x. The profit efficiency of the firm is measured as δ= Π*/ Π0

 

Total Factor Productivity Growth

 

The growth in productivity, which is also known as total factor productivity growth (TFPG), is the difference between the actual growth of output and the growth due to a composite of all factor inputs. It measures the overall efficiency with which products are produced and thus enable the economy to generate a larger output from the same available resources. Hence, it is an important source of sustainable long-term economic growth.#p#分頁標題#e#

 

TFPG = Technical efficiency change × Technology progress

 

(Catching up effect) (Frontier effect)

 

Technical Efficiency Change (EFFCH): Also known as the catching up effect, is the change in the efficiency score over the time period t and t+1. EFFCH is decomposed further into pure efficiency change (PECH) and scale efficiency change (SECH). Pure technical efficiency change suggests that there will be a learning process adopted by the manufacturing industries and scale efficiency indicates whether the firm/bank can increase its productivity by becoming larger. The positive value of the scale efficiency suggests that the manufacturing sector has succeeded in taking advantage of the growth in size of the sector. Technology Change: also known as technology progress or frontier effect is the change in the efficiency score by adopting the different state of technology for the time period t and t+1

 

Indian banking sector

 

The Reserve Bank of India (RBI) is the central bank of the country that regulates the operations of other banks, manages money supply and discharges other numerous responsibilities that are usually associated with a central bank. The banking system in India comprises commercial and cooperative banks, of which the former accounts for more than 90 percent of the assets of the banking system. Within the category of commercial banks, there are two types of the banks:

 

(1) Schedule commercial banks (i.e. which are listed in Schedule II of the RBI Act, 1934); and

 

(2) Non-scheduled commercial banks.

 

Depending upon the pattern of ownership, scheduled commercial banks can be classified into three types:

 

(1) PSBs which include:

 

State Bank of India (SBI) and its associate banks;

 

Nationalized banks (NB); and

 

Other PSBs.

 

(2) Private sector banks consists of private domestic banks (which can further be classified as old private banks that are in business prior to 1995, and de novo private banks that were established after 1995) and foreign banks.

 

(3) Others comprising regional rural banks (RRBs) and local area banks.

 

Conceptual Framework

 

The research work will focus on the banking industry in India. The banking industry in India has been influenced by the deregulation of the financial services sector, development in information and communication technologies and globalisation of financial services industries. The deregulation process, which began in 1991, is aimed at making structural changes in the financial services industries to enhance competition. Structural changes in the overall financial services sector have affected the banking industry greatly. The entry of foreign banks, as well as an expansion of branch networks in both privately-owned and state-owned banks, appeared to have increased the degree of competition in the market. Further, globalisation of the sector, together with developments in information and communication technology, has improved the quality and quantity of products and services which are offered by banks.#p#分頁標題#e#

 

On the other hand, the changes in overall economic policies have improved microeconomic variables which may be directly or indirectly related to bank performance. Therefore, this study predicts that the recorded changes in the financial services industry may have affected overall bank performance through improved efficiency, productivity gains and structural changes in the banking market which enhanced the degree of competition. Based on this background, the study identifies four research issues.

 

Whether deregulation of the financial services sector has affected efficiency and productivity gains in the banking industry in India.

 

Whether inefficiency in the banking industry in India is determined by a set of microeconomic and macroeconomic variables.

 

Rationale of Study

 

Efficiency and productivity gains of the banks, as well as market structure of the banking industry, have been regarded as crucial areas in contemporary public policy concerned with a country’s economic development. Empirical analysis of efficiency, productivity change, and determining the determinants of efficiency are vital requirement for further policy changes.

 

Accordingly, studies in these areas are important as improvements in efficiency and productivity gains in financial institutions are a vital requirement for providing a more efficient system of asset allocation in the financial services sector. Since India has a bank-led financial services sector, efficiency and productivity gains in firms in the banking industry are more important for providing supportive financial infrastructure for economic development. Improvements in efficiency and productivity gains may reduce the cost of intermediation, which directly affects the intermediation margin in the market.

 

Literature Review

 

Considerable work of research takes place on efficiency and productivity of Indian banks as well as others related various issues and reforms by academicians, researchers and institutions like Reserve Bank of India (RBI) etc. The literature concerning to bank efficiency in India shows that good number of studies has assessed the impact of transition from regulation to competition on the efficiency and productivity of banks. The most of literature on the effect of deregulation and liberalization on Indian banking industry portraits a positive impact of deregulatory policies on the efficiency and productivity of Indian banks.

 

Satyanarayana (1996) presented a model for measuring the productivity of banking industry in India. The opinion of the model was based on the ‘market share concept’ i.e. the market share should be taken in percentages instead of absolute terms so that comparison of one bank to the other bank can be done easily. Model was applied to compare the efficiency of various groups of banks from 1969 to 1994. Ramamoorthy (1997) measured the productivity of Indian commercial banks for the period 1991 to 1996 using business per employee as the measure of productivity. The study concluded that measuring productivity as the business per employee did not truly represent the business in all its facets both from quantitative and qualitative angles. Bhattacharya et al. (1997) in his study divulged that deregulation has led to the improvement in the overall performance of Indian commercial banks. Das (1997) utilized non-parametric frontier methodology to derive efficiency measures for 65 major banks using the cross-section data for the year 1995. The results indicated that Indian banks, in general, were more technically efficient than allocatively efficient.#p#分頁標題#e#

 

Saha and Ravishankar (2000) estimated productivity of twenty five public sector Indian Commercial Banks for the period 1992 to 1994 using intermediate approach for about input and output variables. The results indicated that the public sector banks had improved their efficiency scores over the year 1992 to 1995. Das (2000) analyzed the technical and allocative efficiency of 27 PSBs using the cross-section data for the year 1998. It has been found that PSBs had the scope of producing 1.23 times as much output from the same inputs. The results further indicated that banks belonging to State Bank of India group are, in general, more efficient than the nationalized banks. The study provided a negative relationship between non-performing assets and efficiency, and size and efficiency.

 

Das (2000) examined the interrelationship among risk, capital and productivity change of the public sector banks in India. It was concluded that higher productivity led to a decrease in credit risk; it has a positive influence on bank capitalization also. The positive effect of productivity on capital is attributed to regulatory especially for pressure banks having fall short of capital adequacy standards. Mukherjee et al. (2002) made an attempt to explore technical efficiency and benchmark the performance of 68 commercial banks using data envelopment analysis (DEA). It has been observed that in India, public banks are more efficient than both private and foreign banks and the performance of public banks improved over the study period.

 

Krishnasamy (2003) used both DEA and Malmquist total factor productivity index (MPI) to evaluate bank efficiency and productivity changes in Malaysia over the period 2000-2001. The results indicated that total MPI increased in all the bans studied. The growth of productivity in banks was attributed to technological change rather than TE change. Sathye (2003) examined the technical efficiency of Indian banking sector using the cross-section data for the year 1997-1998. The technique of DEA has been applied for obtaining efficiency scores for 94 banks. Two models have been constructed to show how efficiency scores vary with change in the inputs and outputs. The study showed that the mean efficiency score of Indian banks compares well with the world mean efficiency score and the efficiency of private sector commercial banks as a group was, paradoxically lower than that of PSBs and foreign banks. The study recommends that the existing policy of reducing non-performing assets and rationalization of staff and branches may be continued to obtain efficiency gains and make the Indian banks internationally competitive.

 

Kumbhakar and Sarkar (2003) concluded that a significant TFP growth has not been observed in Indian banking sector during the deregulatory regime. Further, public sector banks have not responded well to the deregulatory measures. Galagedera and Edirisuriya (2005) observed that deregulation has brought no significant growth in the productivity of Indian banks. Sensarma (2005) pointed out that profit efficiency of Indian banks has shown a declining trend during the period of deregulation. Ram Mohan and Ray (2004) found an improvement in the revenue efficiency of Indian banks. Also, they noticed convergence in performance between public and private sector banks in the post-reform era. Shanmugam and Das (2004) observed that during the deregulation period, the Indian banking industry showed a progress in terms of efficiency of raising noninterest income, investments and credits.#p#分頁標題#e#

 

Ataullah et al. (2004) reported that overall technical efficiency of the banking industry of India and Pakistan improved following the financial liberalization. Das et al. (2005) the efficiency of Indian banks, in general, and of bigger banks, in particular, has improved during the post-reform period. The study observed that Indian banks are not much differentiated in terms of input- or output-oriented technical efficiency and cost efficiency. However, they differ sharply in respect of revenue and profit efficiencies. Bank size, ownership, and being listed on the stock exchange are some of the factors that have a positive impact on average profit efficiency, and to some extent, revenue efficiency scores. Finally, the median efficiency scores of Indian banks, in general, and of bigger banks, in particular, have improved during the post-reform period. The findings of the study of Mahesh and Rajeev (2006) are completely similar to that of Shanmugam and Das (2004). Das and Ghosh (2006) found that the period after liberalization did not witness any significant increase in number of efficient banks and some banks have high degree of inefficiency during the period of liberalization.

 

Sanjeev (2006) studied efficiency of private, public, and foreign banks operating in India during the period 1997-2001 using data envelopment analysis. He also studied if any relationship can be established between the efficiency and non-performing assets in the banks. He found that the there is an increase in the efficiency in the post-reform period, and that non-performing assets and efficiency are negatively related. Sensarma (2006) noted that deregulation in Indian banking industry (especially public sector banks) achieved the aim of reduction in intermediation costs and improving TFP. Das and Ghosh (2006) found that the period after liberalization did not witness any significant increase in number of efficient banks and some banks have high degree of inefficiency during the period of liberalization. On comparing the effect of deregulation on the productivity growth of banks in Indian sub-continent (including India, Pakistan and Bangladesh) Jaffry et al. (2007) concluded that technical efficiency both increases and converges across the Indian sub-continent in response to reform. Zhao et al. (2007) noted that, after an initial adjustment phase, the Indian banking industry experienced sustained productivity growth, driven mainly by technological progress.

 

Sahoo et al. (2007), and Sahoo and Tone (2009) observed that the government reform process constituted in the banking industry has had a favourable effect on the performance of the Indian banking industry. Ramamoothy (2007) attempted to examine the performance of banks in countries of Gulf Cooperation Council. The performance of 55 banks operating in the countries of Gulf Cooperation Council was evaluated by using Data Envelopment analysis (DEA) and Malmquist productivity Index (MPI). Mahesh and Bhide (2008) found that deregulation has a significant positive impact on the cost and profit efficiencies of commercial banks. Das and Ghosh (2009) concluded that the liberalization of the banking sector in India has generally produced positive results in terms of improving the cost and profit efficiencies of banks. Kumar and Gulati (2009) appraised the efficiency, effectiveness, and performance of 27 public sector banks (PSBs) operating in India by using a two-stage performance evaluation model and the results revealed that high efficiency does not stand for high effectiveness in the Indian PSB industry. A positive and strong correlation between effectiveness and performance measures has been noted. Further, on the efficiency front, State Bank of Travancore appears as an ideal benchmark, while State Bank of Bikaner and Jaipur, and State Bank of Mysore emerge as ideal benchmarks on the effectiveness front.#p#分頁標題#e#

 

Kumar (2010) analysed the trends of cost efficiency and its components across Indian public sector banks (PSBs) during the post-deregulation period spanning from 1992/93 to 2007/08 and concluded that deregulation has had a positive impact on the cost efficiency levels of Indian public sector banking industry over the period of study. Further, technical efficiency of Indian public sector banking industry followed an upward trend, while allocative efficiency followed a path of deceleration. Kaur & Kaur (2010) examined the cost efficiency of Indian commercial banks by using a non-parametric Data Envelopment Analysis Technique. The findings of the study suggested that over the entire study period average cost efficiency of public sector banks found to be 73.4 per cent while for private sector banks it is 76.3 per cent and to some extent merger programme has been successful in Indian banking sector. Das (2010) intended to analyze the performance of the Indian banking sector after the initiation of financial liberalization and also aims to measure the cost efficiency of the Indian banking sector during the post reform period. The study found, after deregulation, the concentration has declined which resulted in increasing competition. The share of private and foreign banks in banking asset, deposit and credit has gone up. The profitability of all bank groups has gone up, but the foreign banks are more profitable. Amir and Abbas (2010) used Hicks-Moorsteen TFP index developed by O——Donnell (2008, 2009, 2010c) to analyse efficiency and productivity changes in banking system and the results obtained showed that the Iranian banking industry has been inefficient over the period of study.

 

Thus, wide literature is available on the banking efficiency, change in the productivity over the period, analysis of determinants that affect the efficiency of banks in India, but there is less number of literatures available on efficiency and productivity of banks that focus on the longer time period to evaluate. Along with this, there are no such studies that have focused on the decomposition of efficiency and productivity in more elaborative terms rather than only focusing on efficiency change, scale efficiency, pure technical efficiency and technology change in India. Thus, this study will try to focus on more elaborative way to evaluate the efficiency of banking industry in India and bridge the gap with the existing literature.

 

Proposed/ Tentative Objectives of the Research

 

1. To determine the efficiency of commercial banks in India

 

2. To investigate the banks’ efficiency and productivity improvements gained during the period of study by focusing on efficiency and productivity gains as a primary method for creating a more economical and efficient banking industry in India.

 

3. To investigate determinants of efficiency of banks in India and their significance.#p#分頁標題#e#

 

Research Methodology

 

The study will include data collected from the statistical tables provided by the Reserve Bank of India. The banks will be divided into four different ownership groups’ namely State bank of India group, other nationalized banks, private banks (new and old private banks) and foreign banks for the period of 1995 to 2010.

 

Various approaches used to evaluate efficiency

 

Literature suggests that there are different approaches that have been employed in evaluating the efficiency of a financial institution defined as its ability to convert its resources into financial performances. These methods differ in the assumption in the term of (a) functional form of the best practice frontier (parametric when a functional form is considered and non-parametric when no functional form is considered), (b) consideration of error terms, (c) probability distribution of random error terms if it is considered. These are broadly classified into three approaches:

 

Accounting approach

 

Within the banking industry, cost efficiency is often measured by using a cost to income ratio (Isik & Hassan, 2002). For profitability, the measurements that are used include return on assets (ROA), return on equity (ROE) and capital asset ratio, liquidity ratios and ratios measuring credit risk (Yeh, 1996; Maudos et al., 2002). Whilst these ratios are widely used to measure efficiency they have certain limitations. Yeh (1996) highlighted the disadvantages of financial ratios as being that they are only meaningful when used with a suitable benchmark, which may be difficult to establish. Secondly, each performance measure is calculated using only a subset of data available to a firm. Therefore, there is need for a more flexible way of expressing a bank’s financial position.

 

Parametric: There are three main parametric approaches to the estimation of best practice frontier as: i) Stochastic frontier approach (SFA): Also known as economic frontier approach, it specifies a functional form for the cost, profit relationship among the input, output and the environmental factors. Mester (1997) used SFA to analyse the efficiency of US banks ii) Distribution free approach: It also specifies a functional form for the frontier, but separates inefficiency from the random error. It makes no assumption regarding the specific distribution of inefficiency or random error and assumes that efficiency of each bank is stable over time with random error averaging out to zero over time. Berger and Humphery (1992) and Berger and Mester (1997) uses DFA to study the efficiency of US banks. iii) Thick frontier approach: This approach imposes no distributional assumptions on either the inefficiencies or the random error. De Young (1997) has used this method for studying the efficiency of US banks. Non-parametric: The main non-parametric approaches are data envelopment analysis (DEA) and free disposal hull (FDH). i) DEA: DEA employs mathematical programming to construct a best practice frontier from the observed data and to measure efficiency relative to the constructed frontier. The DEA does not require output or output prices for identifying the best practice frontier. The best practice frontier is identified as piece-wise linear combination that connects the set of best practice observations, given the specifications of inputs and outputs. The outcome is to produce a convex production frontier for output oriented DEA and concave production frontier for input oriented DEA (Berger and Humphrey, 1997). As a consequence, DEA efficiency score for a decision making unit (DMU) is not defined by an absolute standard but is defined relative to other forms.DEA generates a within sample efficiency score between 0 and 1 with 1 being the most efficient. ii) FDH: Under FDH approach, the assumption of convexity is dropped and it is expected to allow for a better approximation of observed data and generate larger efficiency estimates than DEA. However, a significant advantage of DEA is that it does not superimpose a particular functional form on the data in determining the most efficient decision making units and so captures the interplay between inputs and outputs of different dimensions. Thus any of these above approach can be use in the present study to evaluate the efficiency of banks in India#p#分頁標題#e#

 

In computing the efficiency scores, the most challenging task that always encounters is to select the relevant inputs and outputs for modeling banks behaviour. In the literature on banking efficiency, there are mainly two approaches for selecting the inputs and outputs for a bank: i) the production approach, also called the service provision or value added approach; and ii) the intermediation approach, also called the asset approach (Humphrey 1985). Both these approaches apply the traditional microeconomic theory of the firm to banking and differ only in the specification of banking activities. Under the production approach, financial institutions are considered to be producer of loans and deposit accounts for their customers. This approach is more suitable for measuring efficiencies of bank branches as customer- level transactions are carries out at the branch level where the branch managers have little control on the overall decision making regarding the funding and investment decision of bank. In the alternative, intermediation approach, financial institutions are considered to be intermediaries between the saver and the investor where the outputs is considered in terms of value of loans rather than the number of loan accounts, and the inputs are measured by the various cost of labour, capital, deposits, and other resources .