Chapter - V BANK EFFICIENCY IN NORTH EAST INDIA: DATA ENVELOPEMENT ANALYSIS

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1 Chapter - V BANK EFFICIENCY IN NORTH EAST INDIA: DATA ENVELOPEMENT ANALYSIS I. Conceptual Background Introduction A variety of studies on bank efficiency has enriched the banking literature over the years. Review of literature reveals that there has been a substantial change in the method of analysis. What constitutes efficiency or inefficiency in such type of analysis is an important issue for consideration. There exists no second view that cost remains an important consideration for any business decision. Managerial success of any entity depends on how well the firm minimises costs and maximises revenue. Economists over the years have developed several concepts of cost. Which cost concept is most relevant for its analysis depends on the situation in which the firm is operating. This is because relevant costs to be considered differ from one situation to another depending on the problem faced by the managers. Hence it becomes imperative to understand different cost concepts before analysing efficiency of banks in North East India. The following section is predominantly designed to have a prior understanding of some such concepts Bank Efficiency Since the beginning of 20 th century, studies on bank efficiency has gained popularity and a matter of great significance. Efficiency measures are indicators of success by which the performance of individual banks and banking industry as a whole is gauged (Mokhtar, Abdullah & Alttabshi, 2006). The efficiency level or the scores of banks enable the stakeholders to apprehend the ability of individual banks to adapt better to a different operating environment. More specifically such studies allow investigation into the success and loopholes of reform measures e.g., deregulation, mergers and acquisition etc. Further, it is also indicative of managerial effectiveness in converting inputs into outputs. In nutshell, efficiency generally refers to the ability of productive units to convert inputs into outputs as can be seen from Fig

2 Fig Input-Output Analysis Environmental Factors INPUTS Firms transform inputs into outputs OUTPUTS Source: Mokhtar, H., Abdullah, N. and Alttabshi, S. (2006) Cost Efficiency Performance of a bank is often linked with the extent to which the resources are utilised to generate revenue. It is explained by the ratio of output to input where a larger value is indicative of superior performance. Cost efficiency is the most conventional concept of efficiency pursued in studies of bank performance. The cost efficiency analysis helps to assess the relative performance of the bank as against the best practice bank in managing the operating costs of producing the same output under the same condition. Empirical measurement of productive efficiency is first made by Farrell (1957). He defines the cost efficiency and decomposes it into its technical and allocative components. Efficiency relate to how well a bank employs its resources relative to the existing production possibilities frontier or relative to current best practice bank; how a bank simultaneously minimises cost and maximises revenue based on an existing level of production technology. However, what constitutes efficiency is dependent on the economic objective (maximisation of output or profit, minimisation of costs, etc) pursued by the producer (Sinha & Chatterjee, 2005). Efficiency is defined as the success with which an organisation uses its resources to produce outputs i.e., the degree to which the observed use of resources to produce outputs of a given quality matches the optimal use of resources to produce outputs of a given quality (Bhagavath, 2006). Thus, efficiency implies comparison of actual Output or Input to optimal Output or Input. Efficiency Actual Output Input Optimal Output Input

3 Cost efficiency is also expressed as the maximum that the bank can reduce its costs while still producing the same amount and combination of goods and services. The potential cost savings is termed as cost inefficiency often referred to as X-inefficiency. A deterioration of the bank s relative cost efficiency indicates its increasing vulnerability. Cost efficiency measures the possible reduction in costs that can be achieved if a bank is technically and allocatively efficient. It is the ratio of minimum cost to observed cost. Hence the overall (cost) efficiency (OE) is the product of Allocative Efficiency (AE) and Technical Efficiency (TE) indicated as follows: OE TE X AE Technical Efficiency In the last decade of the 20 th century, the focus of bank efficiency measurement is shifted to X-efficiencies, that is, the ability of management to control costs and generate revenues. X-efficiency comprises technical and allocative efficiencies. The technical efficiency of a firm refers to its success/failure in transforming its inputs into outputs. A firm is said to exhibit TE if it is able to reduce the variable inputs to produce the same level of output. The bank is then operating on the efficient frontier. A bank s level of technical efficiency is ascertained in relation to an estimated best practice firm. The Overall Technical Efficiency (OTE) of a firm is decomposed into Pure Technical Efficiency (PTE) and Scale Technical Efficiency (STE). Pure Technical inefficiency results from using more inputs than necessary. Such inefficiency arises due to factors such as managerial errors arising from inertia and ignorance, poor quality of inputs etc (Kumbhakar & Sarkar, 2004). Scale inefficiency exists if the bank does not operate at constant return to scale Allocative Efficiency A bank enjoys allocative efficiency if it is properly choosing the right mix of inputs given the input price. AE refers to the ability of Decision Making Units (DMUs) to use inputs in optimal proportions, given their respective prices and production technology. It relates to the optimal combination of inputs and outputs at a given price. The objective of producers entails the production of given outputs at minimum cost or utilisation of given inputs to maximise the revenue, or the allocation of inputs and outputs to maximise profit.

4 Input Oriented Efficiency Input oriented measure addresses the question of by how much can input quantities be proportionally reduced without changing the output quantities produced. The concept of cost efficiency constituting TE and AE is illustrated with the help of the Fig : According to the diagram the firm uses two inputs x 1 and x 2 to produce one output y. Knowledge of the unit isoquant of the fully efficient firm is represented by SS'. It shows all possible combinations of inputs to produce an output if the firm is perfectly efficient. Slope AA' represents the budget line or the Input-price ratio line. This represents various combinations of inputs that require the same level of expenditure. If we measure efficiency of a firm operating at point P, corresponding to which a defined set of inputs to produce a unit of output exists, two types of inefficiencies prevails viz., Technical Inefficiency and Allocative Inefficiency. The firm is technically inefficient at point P because by moving to point Q it produces the same output with fewer inputs. The firm s level of technical inefficiency is represented as OQ/OP which is equal to one minus QP/OP. The firm is allocatively inefficient at point P because, by moving to point Q' production costs are reduced. The firm s level of allocative inefficiency is measured as OR/OQ. Thus by operating at point P both technical inefficiency and allocative inefficiency exist. If the firm

5 moves to point Q, it becomes technically efficient but allocatively inefficient. Similarly by operating at point R, the firm remains allocatively efficient but technically inefficient. Thus, to be perfectly efficient, the firm should operate at point Q' where the input-price line is tangent to the isoquant SS'. Technical Efficiency OQ OP OR OQ TE X AE X All the three measures of efficiency viz., cost, allocative and technical are bounded by zero and one Output Oriented Efficiency Output oriented measure of cost efficiency addresses the question as to by how much can output quantities be proportionally expanded without altering the input quantities used. The three measures of efficiency are examined with the help of Fig In the given diagram, production frontier under Decreasing Returns to Scale (DRTS) is represented by f x where the firm is assumed to have used only one input to produce one output. The technical inefficiency of a firm operating at point P is represented by CP/CD as opposed to AB/AP under input oriented measure of TE. It is to be noted that output and input oriented measures give the same result of TE only under Constant Return to Scale

6 (CRTS) as depicted in the Fig Technical inefficiency at point P is represented by CP/CD which is equal to AB/AP. The above model is extended to measure output oriented TE of a firm producing two outputs using one input. In Fig , curve ZZ' represents the unit production possibility curve. Firm at point A is technically inefficient as by moving to point B, output is increased without requiring extra inputs. Technical inefficiency of a firm at point A is represented by OA/OB. Similarly if the firm s isorevenue line is drawn, allocative efficiency is ascertained. In the figure, DD' represents the isorevenue line. Thus the firm s level of allocative inefficiency at point A is OB/OC.

7 Thus under output oriented measure, Economic Efficiency OA X OB Box : Efficiency Categorisation COST EFFICIENCY OB OC INPUT ORIENTED OUTPUT ORIENTED TECHNICAL EFFICIENCY ALLOCATIVE EFFICIENCY PURE TE SCALE TE PROFIT EFFICIENCY REVENUE EFFICIENCY

8 Input and Output Indicators As discussed above efficiency of any productive unit is judged on the basis of the relationship between inputs and outputs. But there is lack of consensus amongst researchers as to what constitutes input and output for a bank. Two main approaches are found in literature in this regard. (i) Production Approach; and (ii) Intermediation Approach Production Approach Production approach defines the bank activity as production of services and views the banks to be using physical inputs e.g., Labour and Capital to provide deposit and loan account. Berger & Humphery (1992) refer this as the value added approach. Under this approach it is the number of accounts of various types that are taken as measures of output produced by the use of capital and labour. Input Labor Capital Output Deposits Advances Intermediation Approach Under the intermediation approach, a bank is treated as a producer of intermediation services as it receives funds from depositors and invests at different risk and maturity profile, by using labour and capital. But banks also produce services for which specific charges are levied. Thus money value of loans and non-interest income are taken as outputs while inputs are taken as labour and capital. Input Labor Capital Output Loan Non Interest Income Colwell & Davis (1992) present the varied approaches to the selection of inputs and outputs, study of productivity, selection of methodology etc in the study of banks efficiency. In their study they point out three approaches to the selection of input and output viz., the national accounts approach, intermediation approach and production approach. Under the national accounts approach, the Value Added approach is followed, where the value added by the

9 different sectors of the economy in terms of profits and income is considered. Here they view that this measure is not free from flaws as profits exclude interest receipts and such exclusions leads to not only understatement of a firm s profit but also of GDP contribution from the sector. They further point out that under production approach the banks are considered to be the producers of loans and deposits using labour and capital. Hence output is measured by the number of accounts or services produced by the use of inputs i.e. labour and capital. As against this they highlight the intermediation approach where the banks are considered to be the inter-mediators of financial services and therefore the value of loans and investments are treated as outputs while labour and capital form the inputs. Deposits according to them are taken either as inputs or outputs. Box : Input and Output Indicators of Banks Input Indicator Deposits, Borrowings, Fixed Assets, Loan, Number of Employees, Number of Bank Branches, Equity, Physical Capital Output Indicator Net Interest Income, Advances, Investments, Net Interest Margin, Interest Spread II. Data Envelopment Analysis Introduction Though ratio analysis is popularly used to evaluate the financial performance of any business entity but it provides relatively insignificant amount of information when we consider the effects of economies of scale, identification of benchmarking policies, and estimation of overall performance measures of firms. Besides there is no absolute definition as to what constitutes a correct/most appropriate ratio. Further, ratio analysis fails to set targets to enable a unit to become more profitable. It is also unable to reflect by how much an individual branch should increase or decrease its inputs or outputs to be at par with the best performing unit. These problems are handled efficiently by the DEA. DEA takes simultaneous account of all resources and outputs in assessing performance while ratio analysis takes into account only one resource to one output at a time. DEA basically addresses those problems which are not taken care of through ratio analysis e.g., how well

10 we are doing relative to others doing the same thing as we do? What do we need to improve? Who are the best- in-class performers for the purpose of benchmarking? However, the two methods are complementary to each other if both are adopted. Ratios do provide useful information on the performance of a unit on specific aspects and can support the communication of DEA results to non-specialists when the two methods agree on performance. Efficiency analysis of the sample branches is undertaken in the present study through DEA. Analysis is made after computation of cost, technical and allocative efficiency scores as computed under DEA. The efficiency scores are estimated employing the DEA software (viz., DEAP Version 2.1 developed by Professor Tim Coelli of the Centre for Efficiency and Productivity Analysis, University of New England, Australia). As already mentioned in the methodology the DEA identifies three types of efficiencies, namely technical, allocative and cost efficiency. These efficiencies are computed by taking all the outputs and inputs together and also against each output indicators separately to test the sensitivity of the results. Since DEA does not permit efficiency calculations taking time series data, year-wise analysis is presented in the following paragraphs. In the present study we have adopted three models to compute the DEA scores and to assess the relative efficiency/inefficiency level of the bank branches. The first model (Model I) takes all the inputs viz., deposits and labour (number of employees) and all the outputs viz., Advances, Interest Income and Non-Interest Income. In order to check the sensitivity of the results of DEA the resultant efficiency scores are again computed taking one output at a time. Thus the Model II, Model III and Model IV take Advances, Interest-Income and Non- Interest Income as output measures respectively: Box : Models of Input and Output Model Output (s) Inputs Model I Advances, Interest Income and Non-Interest Income Deposits and Number of Employees Model II Advances Deposits and Number of Employees Model III Non-Interest Income Deposits and Number of Employees Model IV Interest Income Deposits and Number of Employees

11 5.2.2 Mean Efficiency Scores Year-wise mean efficiency scores for all the bank branches are presented in Table Data reveal that majority of the branches are technically more efficient. In almost all the years the mean TE score is the highest which ranges from 35 to 54 per cent. In case of AE score, it ranges from 4 to 58 per cent. With respect to CE score the mean value ranges from 3 to 27 per cent. The table also reflects that TE score on an average estimated at 44 per cent is the highest followed by AE score estimated at 28 per cent and further followed by cost efficiency score at 14 per cent. The mean efficiency scores of small branches reveal that they are technically more efficient as compared to other branches though a decline is noticed in the TE score from 74 per cent in 2005 to 64 per cent in 2006 and further to 54 per cent in With respect to allocative efficiency scores, decline is noticed in all the years from a peak of 80 per cent in 2004 to 35 per cent in 2005 and further to 13 per cent in A slight improvement is noticed in the year 2007 where the mean AE score increases from 13 per cent in 2006 to 18 per cent in A highly unsatisfactory position is reflected by the Cost efficiency scores. This figure is less than 47 per cent in almost all the years. In short, small branches are found to be technically more efficient where the grand mean of TE is estimated at 59 per cent followed by AE and CE at 40 and 25 per cent respectively. The mean Technical, Allocative and Cost efficiency scores of medium branches indicate that the branches are allocatively better. Further analysis reflects that TE scores in general display a downward trend from 77 per cent in 2004 to 58 per cent in 2005, again from 59 per cent in 2006 to 51 per cent in 2007 while AE scores in general exhibit an upward trend from 73 per cent in 2004 to 91 per cent in 2005 again from 50 per cent in 2006 to 86 per cent in Year 2004 and 2006 earmarked the year of decline in AE scores. Cost efficiency scores show downward trend from 65 per cent in 2003 to 60 per cent in 2004 to 54 per cent in 2005 and further to 30 per cent in 2006 but followed by an increase in 2007 at 42 per cent. The grand mean of AE score is estimated at 79 per cent which is the highest followed by TE at 64 per cent. The grand mean of CE score is estimated at 50 per cent.

12 The Mean efficiency scores of large bank branches too reveal that they are technically more efficient. There is improvement in the mean TE scores during the initial years of study period from 51 per cent in 2003 to 70 per cent in 2004 while decline is noticed in 2005 and 2007 from 70 per cent in 2004 to 66 per cent in 2005 and from 68 per cent in 2006 to 43 per cent in Allocative efficiency scores show improvement in all the years except for the year 2006 where a decline is observed. Cost efficiency scores are indicative of declining trend in almost all the years. The large bank branches in general are found to be technically more efficient. The grand mean is calculated at 60 per cent, 50 per cent and 31 per cent for TE, AE and CE respectively.

13 Table : Estimated Mean Efficiency Scores of Bank Branches Year Score All Branches Small Branches Medium Branches Large Branches TE AE CE TE AE CE TE AE CE TE AE CE Mean Maximum Minimum SD Mean Maximum Minimum SD Mean Maximum Minimum SD Mean Maximum Minimum SD Mean Maximum Minimum SD Grand Mean Note: SD- Standard Deviation

14 If we analyse the grand mean as depicted in Table , it reveals that in general the small and large branches are technically more efficient while the medium branches are allocatively more efficient. Table also indicates that branches generally are highly cost inefficient. Amongst all the branch type medium branches display a relatively superior performance with the mean Technical, Allocative and Cost efficiency scores of 63 per cent, 79 per cent and 50 per cent respectively which is the highest amongst all the branches Efficiency Range of Bank Branches Graphical presentation of distribution of bank branches is made according to their level of efficiencies over the period from to The findings indicate that majority of the bank branches are in the range of per cent level of efficiency as per all the types of efficiency. Cost efficiency scores indicate highest concentration of branches in the range of per cent in all the years. However TE scores indicate a relatively lower concentration of bank branches in this range. Fig : Distribution of Bank Branches in Efficiency Range, efficiency range number of brances te ae ce efficiency range Fig : Distribution of Bank Branches in Efficiency Range, efficiency range number of branches te ae ce efficiency range Fig : Distribution of Bank Branches in Efficiency Range,

15 efficiency range number of branches efficiency range te ae ce Fig : Distribution of Bank Branches in Efficiency Range, efficiency range num ber of branches efficiency range te ae ce Fig : Distribution of Bank Branches in Efficiency Range, efficiency range number of branches efficiency range te ae ce

16 The sensitivity of the results of the DEA scores is further tested by analysing individual output separately. Taking all the branches together and employing Advances as the output indicator in the model it is seen from the Table that the mean TE scores exhibit an increasing trend in the initial years from 20 per cent in 2003 to 30 per cent in 2005 but it declines subsequently to 25 per cent in 2006 and further to 17 per cent in The Mean AE scores exhibit a declining trend throughput the study period from 22 per cent in 2003 to 3 per cent in In 2007, it increases to 25 per cent. The cost efficiency scores are more or less stable and are indicative of a very poor state of affairs which is less than 14 per cent in all the years. In short, with Advances as output indicator the branches are found to be technically more efficient. With Advances as output indicator, large and medium branches are found to be allocatively more efficient whereas small branches are found to be technically more efficient (Table ). For the large branches, the AE score is highest as against TE and CE scores in three out of five years. The mean TE scores in case of large branches are more or less within 30 to 36 per cent. The mean AE scores are highly fluctuating and ranging from 5 to 84 per cent. The CE scores in all the years are very low ranging from 4 to 29 per cent. In case of medium branches also the AE scores are more than TE scores in three out of five years. The TE scores in this case ranges from 14 to 42 per cent whereas the AE scores range from 12 to 83 per cent. The CE score is lowest in all the years ranging from 7 to 35 per cent. But in case of small bank branches the mean TE score is higher than AE score in four out of five years. Like in large and medium branches, the CE scores are far lower as compared to TE and AE scores in small branches ranging from 8 to 27 per cent. The mean TE scores with Interest Income as the output indicator shows a declining trend from 31 per cent in 2004 to 14 per cent in 2005 and further from 26 per cent in 2006 to 11 per cent in 2007 (Table ). The Mean AE scores reveal deterioration over the study period from 76 per cent in 2004 to 10 per cent in 2005 and further to 3 per cent in 2006, though in 2007 it increases to 41 per cent. The CE scores also exhibit a declining trend over the study period. In general the branches are found to be allocatively more efficient with the output indicator. Medium and large branches are found to be allocatively more efficient whereas small branches are found to be technically more efficient with this output indicator.

17 Table reveals that with Non-Interest Income as the Output indicator mean AE scores are highest in almost all the years. The CE scores are the lowest in all the years. The TE scores show a declining trend from 11 per cent in 2003 to 2 per cent in 2004 and from 31 per cent in 2005 to 21 per cent in 2006 and further to 2 per cent in 2007 but the AE scores display an increasing trend from 41 per cent in 2003 to 78 per cent in 2004 and from 5 per cent in 2006 to 88 per cent in The mean CE scores show a declining trend throughout the study period. In short with Non-Interest Income as output indicator the branches are found to be allocatively more efficient. Table further reveals that branches of all type are allocatively better.

18 Table : Estimated Mean Efficiency Scores for Bank Branches (Output Indicator = Advances) Year Score All Branches Small Branches Medium Branches Large Branches TE AE CE TE AE CE TE AE CE TE AE CE Mean Max Min SD Mean Max Min SD Mean Max Min SD Mean Max Min SD Mean Max Min SD Grand Mean Note: Max. Maximum, Min Minimum, SD Standard Deviation

19 Table : Estimated Mean Efficiency Scores for Bank Branches (Output Indicator = Interest Income) Year Score All Branches Small Branches Medium Branches Large Branches TE AE CE TE AE CE TE AE CE TE AE CE Mean Max Min SD Mean Max Min SD Mean Max Min SD Mean Max Min SD Mean Max Min SD Grand Mean Note: Max. Maximum, Min Minimum, SD Standard Deviation

20 Year Table : Estimated Mean Efficiency Scores for Bank Branches (Output Indicator = Non-Interest Income) All Branches Small Branches Medium Branches Large Branches Score TE AE CE TE AE CE TE AE CE TE AE CE Mean Max Min SD Mean Max Min SD Mean Max Min SD Mean Max Min SD Mean Max Min SD Grand Mean Note: Max. Maximum, Min Minimum, SD Standard Deviation

21 Table : Grand Mean Efficiency Scores with different Output Indicators ( ) Output Indicator Technical Efficiency Allocative Efficiency Cost Efficiency Mean Mean Mean All output Advances Interest Income Non-Interest Income From the above analysis it is inferred that the branches under study are highly inefficient as per all the measures of efficiency. The mean CE scores of the branches in all the years are considerably lower as per all the output measures, indicating a highly unsatisfactory state of business. The branches reflect higher mean TE score with all the output together as well as with advances taken as output individually. On the other hand the branches show a higher mean AE score with Interest Income and non-interest income as output indicator. Table Ranking of Branches based on Efficiency Scores Model Branch Type TE AE CE All Branches I II III Model I Large Branches I II III Medium Branches II I III Small Branches I II III All Branches I II III Model II Large Branches II I III Medium Branches II I III Small Branches I II III All Branches II I III Model III Large Branches II I III Medium Branches II I III Small Branches I II III All Branches II I III Model IV Large Branches II I III Medium Branches II I III Small Branches II I III

22 5.2.4 Branch wise Efficiency Analysis Analysis in previous paragraphs concentrated on efficiency scores of the branches classified on the basis of their size as large, medium and small. The present section provides an insight into the state of efficiency with respect to the three types of efficiencies i.e. cost, technical and allocative amongst individual branches which will facilitate the identification of the best performing and worst performing branches irrespective of their size. This will further help in identifying the most efficient banks. The branches are accordingly classified into four categories viz., best performing branches, moderately better performing branches, weakly performing branches and worst performing branches. Table : Classification of Bank Branches based on Performance Br. Code TE Br. Code AE Br. Code CE Best Performing Branches Relatively Better Performing Branches Weakly Performing Branches Worst Performing Branches

23 Table shows the distribution of bank branches under the three measures of efficiency. Our analysis in this regard indicates that some branches are efficient as per TE, some others as per AE and still some others as per CE. But there are only few branches which are efficient under all the measures of efficiency. Likewise there exist some branches which are highly inefficient in all the three measures. The table exhibits five branches each under best, relatively better, weakly performing and worst performing category. Even the best performing bank branches display a low mean efficiency score which varies from 54 to 62 per cent for TE, 35 to 37 per cent for AE and 17 to 20 per cent for CE. Table : Percentage of Efficient Bank Branches Name of the Bank Percentage of Efficient Branches according to TE AE CE Bank of India Allahabad Bank Union Bank United Bank of India Punjab National Bank Central Bank of India Table above clearly indicates that six out of ten selected banks fall in the efficient category. It further reveals that Union Bank at Bongaigaon, Assam, Allahabad Bank at Machkhowa, Assam, CBI at Barabazar, Shillong in Meghalaya and PNB at Zoo Road, Assam are the best performing branches under all the measures of efficiency. Whereas UCO Bank at (1) Shillong in Meghalaya, (2) Imphal in Manipur, (3) Aizwal in Mizoram, (4) Karimganj in Assam, and (5) Agartala in Tripura and Vijaya Bank at Laitumkhrah in Shillong are the worst performing branches under all the three measures.

24 Table : Important Statistics Relating to Best and Worst Performing Branches Branch Code Aggregate Aggregate Interest Non-Interest No. of Deposits Credit Income Income Employees Best Performing Bank Branches Worst Performing Bank Branches III. Productivity Improvement 5.3 Total Factor Productivity In the last two decades, the literature on productivity growth measurement has been extended from the standard calculations of TFP employing production function framework towards more refined decomposition methods. To overcome the shortcomings of growth accounting approach and to identify the components of productivity change, techniques have been developed that are based on the decomposition of TFP index. A method of measuring productivity with growing popularity is the use of Malmquist Index. Three different indices are frequently used to evaluate technological changes: the Fischer Model, Tornqvist Model and Malmquist Index (1953). The Malmquist index has several features, which makes it an attractive approach. First, it is a TFP index. Second, it can be constructed using distance functions which are primal measures based only on input and output quantities rather than on price. Third, the index can be decomposed into technical efficiency change and technological change. Efficiency change can further be decomposed into pure efficiency change and scale components. As efficiency and technical changes are analogous to the notions of technological innovation and adoption respectively, the dynamics of the recent growth observed in the manufacturing sector of the Indian economy can be appreciated

25 better. Finally, assumptions do not need to be made with regard to objectives of firms or regions in terms of, say, cost minimisation or profit maximisation objectives, which could be inappropriate in certain situations. Measuring technical efficiency is an attempt to quantify how well the inputs are converted into outputs by the production process. However, used in isolation, technical efficiency can be a misleading measure of productivity for an organisation or industry where major environmental changes are under way, e.g., deregulation or technological change. Another source of productivity improvement that should be studied is technological progress. Technological progress represents shift of the efficient frontier due to technological innovation, and it should be distinguished from gains in technical efficiency represented by units moving toward the frontier. Hence a study in the nature of total factor productivity is essential to discover the efficacy of a concern to convert inputs into outputs as well as technological improvement Malmquist Index In the present section we have analysed Malmquist Index in order to identify the growth in factor productivity. Since our study is concerned with efficiency measurement placing due importance to input and output, measurement of productivity is considered desirable. Since 2003 is the reference year, the Malmquist TFPCH index and its components takes an initial score of for Hence, any score higher (lower) than in subsequent years indicates an improvement (declination) in the relevant measure. It is also worth mentioning that favourable efficiency change (effch) is interpreted as evidence of catching up to the frontier, while favourable technological change (techch) is interpreted as innovation Table shows an average decline of 2 per cent in the total factor productivity over the study period. The tfpch is found mainly due to a decline in effch index whereas a growth in techch of 0.8 per cent is observed. The decomposition of effch index into pech and sech components indicates that effch decline is mainly due to scale inefficiency where a decline of 2 per cent is noticed though a decline of 0.9 per cent is also identified in case of pech. In almost all the years, techch index shows a growth higher than effch.

26 Table : Malmquist Index Summary of Annual Means for All Branch Type with All Output Indicators Year effch Techch pech sech tfpch 2 nd rd th th Average (GM) Note: effch = technical efficiency change; techch = technology change; pech = pure technical efficiency change; sech = scale efficiency change; and tfpch = total factor productivity change. With advances as output indicator, the MP index reflects mean productivity progress over the study period of 21.7 per cent (Table ). With respect to year 2003, productivity growth of 18 per cent is observed in 2004 and Further growth of 46.6 per cent in TFP is observed in The year 2007 shows a fall to 7 per cent in TFP. The decline in 2007 is due to effch regress of 41.6 per cent. Overall the TFP progress is attributable more due to techch progress. Further decomposition of effch index into pech and sech components suggests that the dominant source of tfpch is sech rather than pech. That is a progress in tfp in case of sample bank branches which is more due to scale efficiency rather than managerial efficiency, implying that the bank branches are relatively inefficient in controlling costs but able to operate at the right scale. With Interest income as output indicator a tfpch of 18 per cent on an average is noticed. Here too tfpch is more due to techch. The decomposition of effch into pech and sech indicate scale inefficiency rather pech. With Non-Interest Income also techch progress of 83 per cent is found to be responsible for a tfp progress despite regress in effch index of 41 per cent on an average. Decomposition of effch reflects that the main source of effch regress is due to managerial inefficiency in controlling costs.

27 Year Table : Malmquist Index Summary of Annual Means effch Techch pech sech tfpch Output Indicator: Advances 2 nd rd th th GM Output Indicator: Interest income 2 nd rd th th GM Output Indicator: Non-Interest income 2 nd rd th th GM Note: effch = technical efficiency change; techch = technology change; pech = pure technical efficiency change; sech = scale efficiency change; and tfpch = total factor productivity change, GM- Geometric Mean.. The MPI in case of small branches show a tfpch progress of 0.5, 17.3 and 16.8 per cent with NII, Interest income and advances as output indicator respectively (Tables , and ). In case of NII and advances as output indicator, it is observed that there is an effch regress of 41 and 9 per cent respectively. However, on the contrary taking Interest income as output indicator techch index fall of 1 per cent is observed. In all these cases scale efficiency is found to be more dominating over effch index. In case of medium branches, a tfpch progress of 4, 17.8 and 21.9 per cent are observed with NII, Interest income and advances as output indicator respectively (Tables , and ). In case of NII and advances a fall in the effch index is observed and computed at 41.1 and 9.4 per cent

28 respectively where the major source of effch regress is found to be pech regress. In case of large bank branches, a tfpch of 8.6, 20.9 and 9.9 per cent is observed with respect to NII, interest income and advances as output indicator respectively. With NII, an effch regress of 9.8 per cent is noticed. While with interest income and advances as output indicator effch is found to be more dominant towards TFP growth. In case of large bank branches with NII as output indicator decomposition of effch index into pech and sech, a fall in both these indices is observed at 9.5 per cent and 0.3 per cent respectively. Year Table : Malmquist Index Summary of Annual Means (Output Indicator = Non Interest Income) effch Techch pech sech tfpch Small Branches 2 nd rd th th GM Medium Branches 2 nd rd th th GM Large Branches 2 nd rd th th GM Note: effch = technical efficiency change; techch = technology change; pech = pure technical efficiency change; sech = scale efficiency change; and tfpch = total factor productivity change, GM- Geometric Mean..

29 Year Table : Malmquist Index Summary of Annual Means (Output Indicator = Interest Income) effch Techch pech sech tfpch Small Branches 2 nd rd th th GM Medium Branches 2 nd rd th th GM Large Branches 2 nd rd th th GM Note: effch = technical efficiency change; techch = technology change; pech = pure technical efficiency change; sech = scale efficiency change; and tfpch = total factor productivity change, GM- Geometric Mean..

30 Table : Malmquist Index Summary of Annual Means (Output Indicator = Advances) Year effch techch pech sech tfpch Small Branches 2 nd rd th th GM Medium Branches 2 nd rd th th GM Large Branches 2 nd rd th th GM Note: effch = technical efficiency change; techch = technology change; pech = pure technical efficiency change; sech = scale efficiency change; and tfpch = total factor productivity change, GM- Geometric Mean..

31 Table : Distribution of Branches in Productivity Range based on Mean MTFP Index Score Productivity Range No. of Branch Code (tfpch score) Branches , ,3,5,6,8,9,10,11,12,13,1517,18,19,20 21,24,25,2627,28,29,30,32,34,35,37, 38,39,44,46,47,49,50,52,53,54,57, 47 58,59.60,61,62,63,64,65, ,7,22,23,31,33,45, 8,55,56,69, ,14,16,41,42,51,66,68, , Table shows productivity improvement in case of 23 sample bank branches. Among these branches, two branches viz., PNB at Fancy Bazar, Assam and CBI at Garikhana, Shillong account for highest growth in TFP. The majority of the bank branches display a productivity fall and majority of the branches show a TFP decline which ranges from 20 per cent to 99 per cent as the tfpch index concentrates mostly in the range of 80 to 100. Branch Nos. 40 and 43, namely, Allahabad Bank in Assam at Machkhowa and Hahimbazar show a major fall in the total factor productivity. Comparison of the efficiency scores of the best performing bank branches indicates that best performing branches do not necessarily exhibit a productivity growth. But majority of the efficient branches display productivity improvement. Similarly worst performance of the bank branches are not necessarily linked to fall in productivity. But majority of the inefficient/worst performing bank branches exhibit a productivity decline. This is further revealed in Table Thus analysis in the present chapter gives a mixed result. It is found that the branches are highly cost inefficient where the aggregate CE score stands at just 14 per cent. It is also found that allocative inefficiency is more responsible towards overall cost inefficiency. This is further supported by the fact that the AE score is just 28 per cent as against TE score of 44 per cent. Comparison across the branch type also brings out a mixed outcome where the large and small branches are found relatively better in terms of TE as compared to AE whereas for the medium branches TE score is below the AE score

32 indicating that technical inefficiency is a major source of overall cost inefficiency. Above results are then focussed for sensitivity test by taking one-one output at a time and the resulting efficiency scores are then analysed. It is found that the branches are again highly cost inefficient. Taking Advances as the output indicator the cost efficiency score is just 6 per cent where the allocative inefficiency is more responsible for such a high level of cost inefficiency. The AE score is much lower than TE score estimated at 15 per cent and 23 per cent respectively on an average. With interest income and non-interest income taken as the output indicator the results indicate high cost inefficiency at 8 per cent and 11 per cent respectively but in this case technical inefficiency is a major source of cost inefficiency. A comparison across the branches on the basis of the three different output indicators reveals that large and medium branches are allocatively better with advances and interest income as the output indicator whereas the small bank branches are technically better with these two output indicators. With non-interest income as output indicator all the bank branches are found to be allocatively better. Analysis further suggests that majority of the branches fall in the highest inefficiency range ( per cent) as per all the measures of efficiency except for TE where majority are in the range of The results of Malmquist productivity analysis for productivity improvement suggest productivity decline in general for all the branches with all output indicators. However with all the output taken separately and classified for each branch type, productivity improvement over the study period is identified and productivity change is more attributable to the technological efficiency change (techch) than technical efficiency change (effch). This suggests that technology (e.g. increasing number of ATMs, e-accounts, credit cards, etc) has proved to be successful in raising level of efficiency of bank branches in north eastern states.