Volume 3 ISSN 0975-0746
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Volume 3 ISSN 0975-0746 Volume 3 (2010-2011) Published in December 2013 ISSN 0975-0746
BUSINESS PERSPECTIVES
JOURNAL OF THE DEPARTMENT OF COMMERCE UNIVERSITY OF KALYANI
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Volume 3 ISSN 0975-0746
BUSINESS PERSPECTIVES
Volume 3 (2010-2011) Published in December 2013
Editors Professor Sunil Kumar Gandhi Professor Subhas Chandra Sarkar
Associate Editors Dr. Debangsu Das Dr. Subhamoy Das Dr. Pradip Kumar Smanta Dr. Amalendu Bhunia Dr. Biswambhar Mandal
Managing Editor Dr. Amalendu Bhunia
Advisors to the Editorial Board (in Alphabetic Order)
Prof. Amit Kr. Mallik, formerly of University of Burdwan Prof. Amitava Sarkar, Director, IISWBM, West Bengal University of Technology Prof. Arindam Gupta, Vidyasagar University Prof. Arun Kr. Basu, University of Calcutta Prof. Bhabatosh Banerjee, formerly of University of Calcutta Prof. H. K. Singh, Banaras Hindu University Prof. Jaydeb Sarkhel, University of Burdwan Prof. Kalyan Kumar Roy, I.I.S.W.B.M Prof. Kartik Ch. Pal, Vidyasagar University Prof. Pralay Kanti Haldar, Tripura University Prof. Ranjan Kr. Bal, Utkal University Prof. Uttam Kumar Dutta, West Bengal State University
Editorial Assistant : Sri Soumya Ganguly
Views and opinions expressed or implied in this Journal are those of the authors, and the Editorial Board of the Department of Commerce, University of Kalyani is not responsible for the same.
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Volume 3
ISSN 0975-0746 Volume 3 (2010 – 2011) Published in December 2013 ISSN 0975-0746
EDITORIAL
It gives me great pleasure to state that we have, through our integrated effort, been able to bring out the third issue of the BUSINESS PERSPECTIVES. Meanwhile we have obtained the ISSN code (0975-0746) for our journal from the appropriate authority. The allotment of such a number in the shortest possible time has encouraged us to maintain the quality of our journal. We are thankful to the said authority for this.
We had received a large number of articles and the number of articles approved for publication by our reviewers out of those is also a substantial one. However, due to space constraint we could not accommodate each and every of those articles. The inconvenience caused is regretted. We hope to incorporate those articles in the coming issues.
I take this opportunity to invite our esteemed readers, scholars and friends to please go through the articles & send their comments and also to send their research articles for publication in the future issues of this journal. In bringing out this issue, the co-operation extended by all the faculty members of our department is thankfully acknowledged. We also acknowledge the co-operation extended by the printing solution provider, Print&Press, without whose active help we could not have published the journal in time.
Amalendu Bhunia Kalyani Managing Editor December, 2013
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Volume 3 ISSN 0975-0746 BUSINESS PERSPECTIVES
Volume 3 (2010-2011) December 2013
CONTENT
Page No. Profitability and its Internal Determinants: A Study of Indian 9 Banks J.K. Das & S.N. Bhattacharya
Governance in NGOs: A Study of Selected NGOs in Northern 26 West Bengal B. Bagchi & D.R. Dandapat
Financial Performance Analysis: A Comparative Study on the 36 Selected Cement Companies in India S. C. Sarkar
An Analysis of the Development of Corporate Governance in 45 India S. Das
A brief history of Powerloom industry in West Bengal: A study 53 U. Paul & D.N. Konar
Growth Performance-A Comparative Study between SBI and 66 ICICI Bank A. Bhunia & P. Saha
Right to Education Act: Perspective & Challenges 77 B. Mandal
NGO Governance-A Study in West Bengal 85 S. Pakira
Profitability Analysis – A Case Study of Public Sector General 99 Insurance Companies in India M. Bhattacharya
Mismanaged Industrialization concerning Man-Made Disaster in 110 Bhopal Gas Tragedy S. Chakraborty
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Volume 3 ISSN 0975-0746 PROFITABILITY AND ITS INTERNAL DETERMINANTS : A STUDY OF INDIAN BANKS
J K Das Associate Professor, Department of Commerce, University of Calcutta, West Bengal & S. N. Bhattacharya Faculty in Finance, RGIIM, Shillong
Abstract
The paper analyses the importance of fee based income vis-à-vis fund based income and explores the internal determinants of the above two sources of income. For the purpose, this paper uses aggregate bank level data from 1998 to 2009. Several factors like risk, operating cost, size and technology change are examined empirically to find out the significance of these factors in bringing about a variation in the income structure of the bank. Results show that the relative contribution of non-interest revenue streams grows rapidly with bullish capital market. The paper concludes that banks should try to reach to optimum level through experimenting different combination of technology use and human resource for profit maximizing. There is enough room for diversification for the state run banks to focus on revenue generation from the fee based services to improve non-interest margin. The size of the bank is not positively significant in improving profitability position of Indian banks.
Keywords: Fee based income, fund based income, net interest margin, non-interest revenue.
1. Introduction India has witnessed phenomenal transformation in the banking sector in the last two decades. Banking today has been redefined and re-engineered with entry of new generation banks, changes in the process, methods and techniques of banking, introduction of new products and services, collaboration between banking and insurance companies, improvement in service quality, increased focus on retail banking and branchless banking, change in customer expectations, outsourcing of resources (human and non-human), volatility in interest rates, increase in non-interest and fee based income, corporate governance and business transformation, mergers, acquisitions and consolidations. Restructuring of the banking system in India became apparent from 1990‘s and was planned to encourage competition in the banking sector, mobilize savings and lead to a more efficient allocation of resources. Traditionally, banks were involved in accepting deposits from public at a lower rate and issuing loans at a higher rate and thereby making profit on interest margin. Banking sector reforms aimed at liberalization of interest rates and credit allocation, introduction of new indirect monetary policy, strengthening prudential regulation, opening the financial sector to foreign financial institutions and promotion of the capital market. Liberalisation of services sector and reforms in the banking sector allowed the banks to transcend their normal business operation and venture into activities like investment banking, leasing, merchant banking, factoring, hire purchase, micro financing, derivative trading and mutual 9 | Business Perspectives
Volume 3 ISSN 0975-0746 funds etc., through separate subsidiaries. The Indian banking industry was quick to realise the growth potential of the financial service industry and begun focussing more on non-traditional activities that generate fee income, service charges, trading revenue, and other types of non-interest income. Enhanced profitability and operational efficiency became essential for survival and growth of any bank, including the government-owned public sector banks. The entry of new generation private sector banks, which were equipped with the latest technology on par with the foreign banks operating in India, had given another dimension to the industry competition. The public sector banks like Punjab National Bank, Bank of Baroda, Canara Bank etc., were aggressively looking for branch expansions beyond the national boundaries. In order to gain in size, maximize economies of scale and scope by providing single platform for various financial services and to focus more sharply on competitive strengths, mergers and acquisitions were undertaken in the Indian banking sector on large scales. In response to the increased competition from Scheduled Commercial Banks (SCBs), Kotak Mahindra, a non-banking financial company (NBFC) has been converted into a scheduled commercial bank, Ashok Leyland Finance has merged with IndusInd Bank, Centurion Bank of Punjab Limited has been taken over by HDFC Bank. ICICI Bank acquired Investitsionno-Kreditny Bank in Russia and Bank of Rajasthan has merged with ICICI Bank very recently. These are just a few examples signifying the transformation in the banking sector. The strong customer base and wide reach of the banking houses were considered as potential distribution channels by the service sector. The government also identified the banking channel a convenient mode for collection of taxes and duties. Since liberalisation, Indian banks have adopted universal banking structures (in different forms and degrees) as a strategic response to increased competition in both domestic as well as global market. Through diversification banks tried to eliminate the unevenness of geographical reach, bring about product-process innovation, exploit economies of scale and scope, bring in advanced technology and diversify risk along with mobilization of additional capital. It helped commercial banks to earn fee income from investment banking, merchant banking, insurance agency, securities brokerage, and other non- traditional financial services and improve income structure. Advancements in technology in banking circle allowed them to provide facilities like ‗core banking solutions‘, ‗real time gross settlement‘, mobile banking, e banking, etc. It has widened the scope of fee based income for the banks. Therefore modern banking houses are coming out with innovative products and services to boost up revenue from fee based income. In line with this, performance in terms of profitability through both fund based and fee based sources have become important for Indian banks. Therefore the need to identify the determinants of bank performance in the Indian as well as other country context has gained importance. Researchers have tried to analyze bank performance based on external and internal variables in various country contexts (Gizyeki, 2001). External variables include rate of economic growth, industry-wide developments, inflation, money supply, economies of scale and scope, dynamics of bank competition, global presence of financial conglomerates, disintermediation in banking activities and other macroeconomic factors; while bank specific internal
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Volume 3 ISSN 0975-0746 variables are nature of ownership, risk reduction motive, cost of production, low cost of capital, technology upgradation, size, quality of assets, interest spread, business diversification, productivity and growth parameters. Ali-Yrkko (2002) viewed that banks diversify for synergy (or economic) motive, managerial motive, value maximization motive, increased market power motive, capital strength and risk diversification motives etc. With the implementation of Basel II norms, the banks are focussing more on their risk adjusted returns. Therefore, risk adjusted measures of banks have become more meaningful measures of bank performance. This implies that apart from the level of profits or earnings, the source of profit or income is also of importance as different activities of the banks are associated with different types of risk levels. In this paper an attempt has been made to analyze the importance of fee based income vis-à-vis fund based income and also investigate the significance of internal determinants for diversification of banks in India. For the purpose, this paper uses aggregate bank level data from 1998 to 2009. Several internal determinants like risk, operating cost, size and technology change etc., motivating banks to diversify are examined empirically to find out significance of these factors for bringing variation in the income structure of the bank.
2. Literature Review Diversification has been one of the most frequently researched areas in strategic management literature and to some extent in finance. Many studies have been conducted on factors influencing performance of banks. The internal determinants originate from the financial report of the bank concerned and are often termed as micro or bank-specific determinants of profitability. The external determinants are those forces that reflect the economic environment which conditions the operation and performance of financial institutions. The typical internal determinants employed are variables, such as size and capital [Akhavein et al., (1997); Demirguc-Kunt and Maksimovic, (1998); Haslem, (1968); Bourke, (1989); Molyneux and Thornton, (1992); Bikker and Hu, (2002)]. The literature provides mixed evidence on the impact of liquidity on profitability. Molyneux and Thornton (1992) found a significant negative relationship between the level of liquidity and profitability. Bourke (1989) in contrast, reports an opposite result. Some of the other internal determinants found in the literature are funds source management and funds use management (Haslem, 1968), capital and liquidity ratios, the credit-deposit ratio and loan loss expenses [Short, (1979); Bell and Murphy, (1969); Kwast and Rose (1982)]. Bourke (1989) and Molyneux and Thornton (1992) find that better-quality management and profitability go hand in hand. Miller and Noulas (1997) found a negative impact of credit risk on profitability. Athanasoglou et al. (2005) provides an explanation of the above result suggesting higher exposure to high-risk loans by the financial Institutions results in accumulation of unpaid loans and these loan losses produce lower returns to many commercial banks. Bennaceur and Goaied (2008) examined factors affecting profitability for the period 1980-2000 and suggested that capital and overhead expenses are positively related to profitability level. Kosmidou (2008) findings suggest that the more profitable banks have higher level of capital and lower cost to income ratio.
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Volume 3 ISSN 0975-0746 Studies in Indian context include analysis of the impact of ownership on bank efficiency and performance since reforms [Sarkar et al., (1998); Arun and Turner, (2002); Ram Mohan, (2002); De, (2003); Das et al., (2005); Mohan, (2005)]. The business diversification impact on bank performance in the Indian context has not been the main focus of their research. De (2003) found business diversification variable irrelevant in determining the bank performance. Ram Mohan (2003) used risk-adjusted return comparison to compare bank performance across ownership groups and concludes that there is no statistical difference between the performance of public sector and private sector banks. Report on Trend and Progress of Banking in India (2004-05) by RBI shows that in a rising interest rate scenario, two key financial performance parameters – interest income and non-interest income respond differently. The data show that the share of non-interest income in banks‘ total income has increased continuously from 10.7% in 1993-94 to 21.5% in 2003-04 but declined to 18% in 2004-05. Venkatesan (2007) viewed that the net interest margin has come down over the last one decade with increased competition in the banking industry. He viewed that banks will look for fee based income to fill the gap in interest income.
3. Data and Methodology The data used in the study were extracted from published documents of Reserve Bank of India, Capitaline database and the reports on trends and progress in banking sector in India. The banks which were part of BSE BANKEX index in March 2009 were selected for the study. The period of study is from 1998 to 2009 for the regression and from 1995 to 2009 for the graphical analysis. Graphical analysis was done on 18 banks and regression analysis was done on 13 banks due to non availability of required data. Four bank-characteristic indicators are used as internal determinants of profitability viz. performance. To analyze the significance of four internal determinants (explanatory variables) of profitability namely risk, cost of operation, size and technological change, the multiple regression has been used. Regression Coefficient and t values have been calculated for four explanatory variables by taking the Net Interest Margin (NIM) and Non-Interest Margin (NOM) as dependent variable. These are defined as the ratio of NII (net interest income) and NOI (non-interest income) to total funds, respectively. RISK is defined as ratio of return on assets of the bank in a year to average return on assets in banking sector. Return on assets is the ratio of profit after tax to total assets. The ratio of operating expenses to total funds (OETF) is used to provide information on variation in bank costs over the banking system. It reflects employment related costs including the total amount of wages and salaries. Operating expenses is expected to have a negative impact on performance because efficient banks are expected to operate at lower costs. The size of the bank is also included as an independent variable to account for size related economies and diseconomies of scale and is measured as log of capital employed (ln_Capital_Emplo). As fee income rises in importance, it correlates to rising use of electronic and other non-traditional means of product delivery. It signifies a changing mix between traditional and non-traditional business. The impact of this changing mix is captured by the ratio of Non-Interest Income/Net Interest Income (NONI-NETI) (Arora and Kaur, 2009). To identify factors across
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Volume 3 ISSN 0975-0746 the banking industry that is driving NIM and NOM and also to know if certain factors are significant determinants for profitability and diversification in banks, the following two equations are used in the analysis:
NIM0 1 OETF+ 2 NONINETI+ 3 RISK 4 ln_Capital_Emplo+e ... (1)
NOM0 1 OETF+ 2 NONINETI+ 3 RISK 4 ln_Capital_Emplo+v ... (2)
Where ii's and ' s ( i 0,1,2,3,4) are constants and e and v are the error terms.
4. Data Analysis and Findings 4.1. Graphical analysis A graphical analysis of two ratios, namely (1) Net Interest Income / Total Funds (%) and (2) Non-Interest Income / Total Funds (%) was done for 18 banks for the period 1995 to 2009 and is presented in Figure 1 along with a graphical representation of non interest income to interest income ratio.
Figure 1: Graphical Analysis for the period 1995-2009. AXIS BANK
BANK OF BARODA
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Volume 3 ISSN 0975-0746 BANK OF INDIA
BANK OF MAHARA STRA
BANK OF RAJAST HAN
CANARA BANK
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Volume 3 ISSN 0975-0746 FEDERA L BANK
HDFC BANK
ICICI BANK
IDBI BANK
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Volume 3 ISSN 0975-0746 INDU- SIND BANK
INDIAN OVERSE AS BANK
KARNA- TAKA BANK
KOTAK MAHIN- DRA BANK
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Volume 3 ISSN 0975-0746 ORIE- NTAL BANK OF COMM- ERCE
PUNJAB NATIO- NAL BANK
STATE BANK OF INDIA
UNION BANK
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Volume 3 ISSN 0975-0746 In 17 cases out of 18 we find that ratio of Net Interest Income to Total Funds (%) is much higher than the ratio of Non-Interest Income to Total Funds (%). The average of Net Interest Income to Total Funds (%) for the period is higher than average of Non-Interest Income to Total Funds (%) with ICICI Bank being the sole exception (Table 1). In fact all the government undertaking banks included in our study like Bank of Baroda, Bank of India, Bank of Maharashtra, Canara Bank, IDBI Bank, Indian Overseas Bank, Oriental Bank of Commerce, Punjab National Bank, State Bank of India and Union Bank have much higher Net Interest Income to Total Funds (%) compared to Non-Interest Income to Total Funds (%) clearly indicating enough diversification scope for the state run banks to focus on revenue generation from these fee based services. The ratios of Non-Interest Income to Net Interest Income for state run banks are all less than 1 indicating that the proportion of revenue generation from fee based activities of these banks is much lower in comparison to revenue generation from their traditional business activities. IDBI bank is the sole public sector bank that has Non-Interest Income to Net Interest Income ratio above one for most of the period between 2000 and 2009. The relatively high ratio of non- interest income to net interest income reflects the efforts of IDBI Bank to reduce its dependence on just the loan book for revenue growth. Almost all the banks under study have shown that ratio of non-interest income to net interest income has peaked in between the study period. FII investment inflows in Indian equity market surged during the study period till 2007-08 which led BSE SENSEX reach higher peaks. The bullish trend in capital market along with decline in interest rate spreads in India lured the Indian banks to take the advantage of bullish capital market in order to increase its customer base and improve revenue generation through higher fee based income. This probably led the non-interest income to net interest income ratio to peak in between the study period. This is an indication of the growing effectiveness of the bank's deliberate strategy of diversifying its revenue streams while delivering a wider range of products to serve the increasingly complex requirements of its client base. However, this ratio has tended to oscillate in line with the buoyancy in capital market conditions. When capital market conditions are favourable, the relative contribution of non- interest revenue streams grows rapidly. The opposite tends to be the case when capital markets are flagging.
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Table 1: Average and Coefficient of Variation of Net Interest Margin and Non Interest Margin Net Interest Income / Total Non Interest Income / Total Funds Funds Banks Coefficient of Coefficient of Average Average variation variation AXIS Bank 2.233333 3.941395 1.952 2.995726 Bank of Baroda 3.114 7.618331 1.488 4.677426 Bank of India 2.796 12.2178 1.503333 4.431633 Bank of 3.130667 7.097462 1.207333 4.032078 Maharashtra Bank of Rajasthan 2.784667 4.917433 1.526667 3.400082 Canara Bank 2.986 6.448417 1.590667 4.868435 Federal Bank 2.834 4.571856 1.678667 4.630241 HDFC Bank 3.660667 3.073429 1.656 2.646939 ICICI 2.241333 2.519171 2.313333 3.813164 IDBI Bank 1.352 1.17475 1.050667 2.812385127 IndusInd Bank 2.283333 3.080128 2.071333 3.057168 Indian Overseas 2.844667 4.170673 1.366 4.38753 Bank Karnataka Bank 2.850667 3.365235 1.770667 2.768043 Kotak Mahindra 7.506 2.257987 2.922667 1.950958 Bank Oriental Bank of 3.318667 4.619914 1.232667 4.047454 Commerce PNB 3.478 13.17424 1.502 5.315602 SBI 3.018 9.356502 1.678 6.489657 Union Bank 3.19 8.977786 1.180667 2.083645
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Volume 3 ISSN 0975-0746 4.2 Regression Analysis for Net Interest Margin The details of the results are shown in Table 2 below.
Table: 2 Regression Result for Net Interest Margin (Net Interest income to Total Fund : Dependent variable) Banks Coefficients ln_Capital_E Constant OETF NONINETI RISK mplo R2 F-statistic AXIS Bank 1.47615 0.786106 -0.609802 0.750766 - 0.0961979 25.3153 (2.130) (2.247) ( -4.808) (2.215) (-0.852) [p-value = [ 0.07066*] [0.05947 *] [0.00195 ***] [0.06236 *] [0.42242] 0.93534 0.00029***]
Bank of 0.796057 0.970709 - 0.435928 0.432685 - 0.0182712 3.606398 Baroda (0.1585) (1.475) (-0.4341) (0.6500) ( --3.537) [p-value = 0.673288 [0.8786] [0.1838] [0.6773] [0.5365] [0.0095 ***] 0.06691*]
Bank of 4.67923 0.375134 - 1.04562 0.708360 -0.247834 12.8353 India (2.177) (2.295 ) (-3.823 ) (6.473) (-1.585) [p-value = [0.06597 *] [0.05539 *] [0.00652***] [0.00034***] [0.15688] 0.88002 0.0024***]
Bank of 14.1078 - 0.578355 -0.624817 0.401235 - 1.08988 5.09059 Rajasthan (3.548 ) (-1.893 ) (-1.176 ) ( 4.485 ) (-3.084) [p-value = [0.00937 [0.1005 *] [0.27790] [0.00285***] [0.01772 **] 0.74417 0.0305**] ***]
Canara 6.34830 0.598725 - 1.83457 0.648793 - 0.382440 4.69368 Bank ( 0.884) ( 0.943) ( -2.534) ( 2.287) (-0.765) [p-value = [0.40605] [0.37711] [0.03899 **] [0.05603 *] [0.46941] 0.72842 0.0371**]
HDFC Bank 0.332536 1.27677 -2.17404 0.833118 - 0.0000015 124.067 ( 1.375) ( 8.343) ( -6.212) ( 4.648 ) ( -0.879) [p-value < [0.21165] [0.00007***] [0.00044***] [0.0023 ***] [0.40878] 0.98609 0.00001***]
ICICI Bank 2.88402 0.841735 - 0.524719 0.00077 - 0.175974 13.5072 ( 5.615) ( 3.106) ( -2.590) ( 0.002 ) ( -3.653) [p-value = [0.00080 [0.01717 **] [0.03596 **] [0.99869] [0.00814 ***] 0.88530 0.00209***] ***]
IndusInd 3.99867 0.176642 - 0.591825 0.700569 - 0.243087 37.6411 Bank ( 4.715) (1.427 ) (-3.689 ) ( 9.697) ( -2.417) [p-value = [0.00217 [0.19652] [0.00777 ***] [0.0003 ***] [0.04632 **] 0.95557 0.00008***] ***]
Indian -2.54373 1.23111 0.452749 1.16933 0.111803 13.3709 Overseas ( -0.640) ( 3.574) ( 0.441) ( 4.982 ) ( 0.368) [p-value = Bank [0.54258] [0.00904 ***] [0.67233] [0.00160 ***] [0.72379] 0.88427 0.00216***]
Karnataka 6.28484 - 0.267337 - 0.984672 1.33653 - 0.460588 15.2997 Bank (1.727) ( -0.391) ( -4.781) (3.266 ) (-1.545) [p-value = [0.12780] [0.70768] [0.00201 ***] [0.01375 **] [0.16614] 0.89736 0.00143***]
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Volume 3 ISSN 0975-0746 Oriental 8.98774 0.513710 - 3.36403 0.964073 - 0.896094 65.9302 Bank of ( 2.014) ( 0.789) ( -5.497 ) ( 8.556) (-2.902) [p-value = Commerce [0.08392 *] [0.45579] [0.00091 ***] [0.00006***] [0.02294 **] 0.97414 0.00001***]
Punjab 2.89189 0.0954346 1.18905 0.290751 0.00767262 0.665910 National ( 0.6104) (0.2023) (0.6503) (0.6754) (0.02325) [p-value = Bank [0.5609 ] [0.8454] [0.5362] [0.5211] [0.9821] 0.275635 0.6356]
State Bank 3.52683 0.695032 - 1.76252 1.16751 -0.181562 6.96774 of India ( 1.188) ( 2.655 ) (-2.552) ( 3.634) (-1.012) [p-value = [0.27354] [0.03271 **] [0.03797 **] [0.00836 ***] [0.34505] 0.79926 0.0138**]
*, **, *** represents significance at 10%, 5% and 1% level respectively. ( ) represents t values and [ ] represents the p- values.
The model performs reasonably well as indicated by R square values and the F statistic values. The coefficient of OETF is significantly different from zero in 7 cases out of 13 banks under study. The coefficient of OETF is found significant for AXIS Bank, Bank of India and Bank of Rajasthan at 10% level, for ICICI Bank and SBI at 5% level and for Indian Overseas Bank and HDFC Bank at 1% level respectively. The coefficient of the ratio of Non-Interest Income/Net Interest Income (NONINETI) is found significant for ICICI Bank, Canara Bank and for State Bank of India at 5% level of significance and for AXIS Bank, Bank of India, HDFC Bank, IndusInd Bank, Karnataka Bank and Oriental Bank of Commerce at 1% level of significance respectively. The coefficient of measure of Risk (RISK) is found significant for AXIS Bank and Canara Bank at 10% level of significance, for Karnataka Bank at 5% level of significance and for Bank of India, Bank of Rajasthan, HDFC Bank, IndusInd Bank, Indian Overseas Bank, Oriental Bank of Commerce and State Bank of India at 1% level respectively. The coefficient of measure of size (ln_Capital_Emplo) is found significant for Bank of Rajasthan, IndusInd Bank and Oriental Bank of Commerce at 5% level of significance and for ICICI Bank and Bank of Baroda at 1% level of significance respectively. The constant is found significant for AXIS Bank, Oriental Bank of Commerce and Bank of India at 10% level, for Bank of Rajasthan, ICICI Bank and IndusInd Bank at 1% level of significance.
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Volume 3 ISSN 0975-0746 4.3 Regression Analysis for Non-Interest Margin The details of the result are shown in Table 3.
Table: 3 Regression Result for Non Interest Margin
Non Interest Income / Total Funds: Dependent variable Banks Coefficients
ln_Capital_ 2 Constant OETF NONINETI RISK R F-statistic Emplo AXIS Bank 0.452591 0.668396 1.03732 1.25792 - 0.211624 14.59597 (0.5220 ) (1.527) (6.537) ( 2.966) ( -2.847) [p-value= [0.6178] [0.1706] [0.0003***] [0.0209 **] [0.0216 **] 0.892940 0.00165***]
Bank of -1.43875 0.536271 2.80715 0.281790 0.00353339 27.61146 Baroda ( -0.5208) (2.397 ) ( 5.084 ) ( 0.7698 ) ( 0.02141) [p-value= [0.6185 ] [0.0477 [0.0014 ***] [0.4666] [0.9835] 0.940398 0.00022***] ** ]
Bank of 1.00307 0.206764 2.15425 0.400308 -0.131072 0.986517 128.0476 India ( 0.6977) (1.892 ) ( 11.78 ) (5.470) ( -1.254) [p-value= [0.5079 ] [0.1005 *] [7.21e-06 ***] [0.0009 ***] [0.2502 ] 1.27e-06***]
Bank of 6.44757 -0.350776 2.33386 0.236144 - 0.6078 33 23.39449 Rajasthan ( 2.487 ) ( -1.743) (6.739) ( 4.048) ( -2.638) [p-value = [0.0418 [0.1249] [0.0003 ***] [0.0049 ***] [0.0335 **] 0.930402 0.00038***] **]
Canara 2.30883 0.338684 1.69074 0.445578 - 0.246152 20.69793 Bank ( 0.5472) ( 0.9078) (3.975) ( 2.674) ( -0.8378) [p-value = [0.6013 ] [0.3941] [0.0054 ***] [0.0318 **] [0.4298] 0.922042 0.00056***]
HDFC Bank -2.29147 0.559499 2.60120 0.686519 0.0310458 138.5710 ( -2.570) ( 10.76) ( 11.05) (2.993 ) (0.5233) [p-value= [0.0370 **] [1.32e-05 [1.10e-05 ***] [0.0201 **] [0.6169] 0.987529 9.65e-07***] ***]
ICICI Bank 0.585990 0.512276 0.831064 0.880950 - 0.122615 15.28662 ( 0.9549) (1.582 ) (3.433) ( 1.611) (-2.130) [p-value= [0.3714] [0.1576] [0.010 ***] [0.1512] [0.0706 *] 0.897280 0.00144***]
IndusInd 3.17551 0.349923 1.61528 0.666622 - 0.419016 45.35400 Bank ( 2.772 ) ( 2.094 ) (7.454) ( 6.832 ) ( -3.084) [p-value= [0.0276 [0.0746 *] [0.0001 ***] [0.0002 ***] [0.0177 **] 0.962848 0.00004***] **]
Indian -1.36500 0.476 199 3.22131 0.529997 - 0.0383810 12.67835 Overseas ( -0.6227) ( 2.507 ) ( 5.693) (4.095) ( -0.2291) [p-value= Bank [0.5532] [0.0406 [0.0007 ***] [0.0046 ***] [0.8254] 0.878711 0.00253***] **]
Karnataka 2.19116 -0.255570 1.46553 0.575164 - 0.196136 62.28122 Bank ( 0.8967) (-0.5562) ( 10.60) ( 2.093) (-0.9802) [p-value= [0.3996] [0.5954] [1.46e-05 ***] [0.0746 *] [0.3597] 0.972670 0.00002***]
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Volume 3 ISSN 0975-0746 Oriental 2.00464 0.337009 5.01762 0.491735 -0.385866 34.99010 Bank of ( 0.6189 ) ( 0.7136) (11.30) (6.013) ( -1.722) [p-value= Commerce [0.5556 ] [0.4986] [9.51e-06 ***] [0.0005 ***] [0.1288 ] 0.952368 0.00010***]
Punjab -0.290056 0.0246395 4.13344 0.127260 0.00534560 12.42218 National ( -0.1340) ( 0.1143) ( 4.947 ) ( 0.6469) (0.03545) [p-value= Bank [0.8972] [0.9122] [0.0017 ***] [0.5383] [0.9727] 0.876519 0.00269***]
State Bank 0.828524 0.380953 1.88411 0.691351 - 0.138592 48.47458 of India ( 0.6095) (3.178) (5.959) ( 4.699 ) ( -2.328) [p-value= [0.5614] [0.0155 [0.0006 ***] [0.0022 ***] [0.0528 *] 0.965157 0.00003***] **] *, **, *** represents significance at 10%, 5% and 1% level respectively. ( ) represents t values and [ ] represents the p- values
The model performs reasonably well as indicated by R square values and the F statistic values. The coefficient of OETF is significantly different from zero in 6 cases out of 13 banks under study. The coefficient of OETF is found significant for IndusInd Bank and Bank of India at 10% level of significance, for Bank of Baroda, Indian Overseas Bank and State Bank of India at 5% level of significance and for HDFC Bank at 1% level. The coefficient of the ratio of Non-Interest Income/Net Interest Income (NONINETI) is found significant for all the 13 banks under study at 1% level of significance. The coefficient of measure of Risk (RISK) is found significant for Karnataka Bank at 10% level, for HDFC Bank, AXIS Bank and Canara Bank at 5% level of significance and for Bank of India, Bank of Rajasthan, IndusInd Bank, State Bank of India, Oriental Bank of Commerce and Indian Overseas Bank at 1% level respectively. The coefficient of measure of size (ln_Capital_Emplo) is found significant for ICICI Bank and State Bank of India at 10% level of significance and for IndusInd Bank, Bank of Rajasthan and AXIS Bank at 5% level of significance respectively.
5. Conclusion There are positive and significant coefficients on the overhead to total fund ratio variable (OETF) in the net interest margin and non-interest margin equations. Positive and significant coefficients on the overhead suggest that a non negligible percentage of a bank‘s overhead costs are passed on to its depositors and lenders (in terms of lower deposit rates and/or higher lending rates). It indicates that the strategy of use of technology substituted for labour is to be reconsidered and bank should go for new recruitment of more skilled and professionally qualified human resource. Also in the era of fast changing technologies, more use of technology substituting human resource may adversely affect the profitability in future due to obsolescence of today‘s technology. Banks should try to reach to optimum level through experimenting different combination of technology use and human resource for profit maximizing. This positive relationship should also mean that a more motivated
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Volume 3 ISSN 0975-0746 staff (well paid) is favourable to the profitability of the banking industry as the major component of overhead is salaries and wages. The coefficients of the ratio of Non-Interest Income / Net Interest Income (NONINETI) in the NOM equation are all positive and significant but are mostly negative and significant in the NIM equation. It clearly indicates that the changing mix between traditional and non-traditional business have been instrumental in increasing non-interest income of the banks. However, the same has corroded the net interest margin which has been the major source of income especially for the government control banks. Therefore, use of technology substituting human resource may adversely affect the profitability in future. Risk, measured by the coefficient of the bank‘s return (ROA) to the average return on assets in banking sector is positive in all equations and mostly significant. Higher risk implies the greater NIM and NOM. This is in agreement with finance theory where higher returns (profits) are associated with higher risks. Many researchers find that little cost saving can be achieved by increasing the size of the banking firm (Berger et al., 1987) and others report significant scale economies for banks whose asset size extends well into the billion range (Shaffer, 1985 and many others). The size variable (ln_Capital_Emplo) has mostly negative and significant coefficients on both the equations. This suggests that large size banks tend to lower margins and is consistent with models that emphasize the negative role of size arising from scale inefficiencies. Overall, we may conclude that Banks should try to reach to optimum level through experimenting different combination of technology use and human resource for profit maximizing. There are enough room for diversifications for the state run banks to focus on revenue generation from the fee based services to improve non-interest margin. The size of the bank is not positively significant in improving profitability position of Indian Banks.
References 1. Akhavein, J. D., Berger, A. N. and Humphrey, D. B. (1997). ―The effects of megamergers on efficiency and prices: Evidence from a bank profit function‖, Review of Industrial Organization. vol.12, pp. 95-139. 2. Ali-Yrkkö, J. (2002). ―Mergers and Acquisitions – Reasons and Results‖, Discussion Papers No 792, Etla - The Research Institute of the Finnish Economy, Helsinki. (http://www.etla.fi/wp-content/uploads/2012/09/dp792.pdf) 3. Arora, S. and Kaur, S. (2009). ―Internal Determinants for Diversification in Banks in India an Empirical Analysis‖, International Research Journal of Finance and Economics, vol. 24, pp. 177-185 4. Arun,T G. and Turner, J. D. (2002). ―Public Sector Banks in India: Rationale and Prerequisites for Reform‖, Annals of Public and Co-operative Economics, vol. 73(1), pp. 89-109. 5. Athanasoglou, P.P., Brissimis, S.N. and Delis, M.D. (2005). ―Bank-specific industry- specific and macroeconomics determinants of bank profitability‖, Bank of Greece Working Paper 25. (http://mpra.ub.uni- muenchen.de/32026/1/MPRA_paper_ 32026.pdf) 6. Bell, W. F. and Murphy, N. B. (1969). ―Impact of market structure on the price of a commercial banking service‖, Review of Economics and Statistics, vol. 51,pp. 210- 13.
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Volume 3 ISSN 0975-0746 7. Bennaceur, S. and Goaied, M. (2008). ―Determinants of Commercial Bank Interest Margin and Profitability: Evidence from Tunisia‖, Frontiers in Finance and Economics, vol. 5(1), pp. 432-56. 8. Berger A., Hanweck, D. and Humphrey, D. (1987). ―Competitive viability in banking: Scale, scope and product mix economies‖, Journal of Monetary Economics, vol.20, pp. 501-20. 9. Bikker, J.A. and Hu, H. (2002). ―Cyclical Patterns in Profits, Provisioning and Lending of Banks and Procyclicality of the New Basle Capital Requirements‖, BNL Quarterly Review, vol. 221, pp. 143-175. 10. Bourke, P. (1989). ―Concentration and other determinants of bank profitability in Europe, North America and Australia‖, Journal of Banking and Finance, vol. 13, pp. 65-79. 11. Das, A., Nag, A. and Ray ,S. C. (2005). ―Liberalisation, Ownership and Efficiency in Indian Banking – A Non-parametric Analysis‖, Economic and Political Weekly, March 19, pp.1190-1197. 12. De, B. (2003). ―Ownership Effects on Bank Performance: A Panel Study of Indian Banks‖, Presented at the Fifth Annual Conference on Money and Finance in the Indian Economy at IGIDR 2003. (http://www.igidr.ac.in/money/mfc_5/bikram.pdf) 13. Demirguc-Kunt, A. and Maksimovic, V. (1998). ―Law, finance and firm growth‖, Journal of Finance, vol. 53(6), pp. 2107-2137. 14. Gizyeki M. (2001). ―The Effect of Macroeconomic Conditions on Banks' Risk and Profitability‖. Discussion Paper, Reserve Bank of Australia. (http://www.rba.gov.au/ publications/rdp/2001/pdf/rdp2001-06.pdf) 15. Haslem, J.A. (1968). ―A Statistical Analysis of the Relative Profitability of Commercial Banks‖, Journal of Finance, vol. 23(1), pp.167-176. 16. Kosmidou, K. (2008). ―The Determinants of Banks' Profits in Greece during the period of EU Financial Integration‖, Management Finance, vol. 34(3), pp. 146-159. 17. Kwast, M. L. and Rose, J. T. (1982). ―Pricing, operating efficiency, and profitability among large commercial banks‖, Journal of Banking and Finance, vol.6, pp. 233-254. 18. Miller, S. and Noulas, A. (1997). ―Portfolio Mix and Large-Bank Profitability in the USA‖, Applied Economics, vol. 29, pp. 505-512. 19. Mohan, R. (2005). ―Financial Sector Reforms in India – Policies and Performance Analysis, Economic and Political Weekly, vol. 40(12), pp. 1106-1119. 20. Molyneux, P. and Thornton, J. (1992). ―The determinants of European bank profitability‖, Journal of Banking and Finance, vol. 16, pp. 1173-1178. 21. Ram Mohan, T. T. (2002). ―Deregulation and performance of public sector banks‖, Economic and Political Weekly, vol. 37 (5), pp. 393-397. 22. Ram Mohan, T. T. (2003). ―Long-run Performance of Public and Private Sector Bank Stocks‖, Economic and Political Weekly, February 22, pp.785-788. 23. Sarkar, J., Sarkar, S. and Bhaumik, S. K. (1998). ―Does Ownership always Matter? Evidence from the Indian Banking Industry‖, Journal of Comparative Economics, vol. 26, pp. 262-281. 24. Shaffer, S. (1985). ―Competition, economies of scale, and diversity of firm sizes‖, Applied Economics, vol.17, pp. 467-76. 25. Short, B.K. (1979). ―The Relation between Commercial Bank Profit Rates and Banking Concentration in Canada, Western Europe and Japan‖, Journal of Banking and Finance, vol. 3, pp. 209-219. 26. Venkatesan, S. (2007). ―Banking Industry Vision 2010‖, IBA Bulletin,vol.2(1),pp.33-37.
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Volume 3 ISSN 0975-0746 GOVERNANCE IN NGOS: A STUDY OF SELECTED NGOS IN NORTHERN WEST BENGAL
Bhaskar Bagchi Assistant Professor, Department of Commerce, Alipurduar College, West Bengal & Dhrubaranjan Dandapat Professor, Department of Commerce, University of Calcutta, West Bengal
Abstract
Although NGOs raise billions of dollars each year, there is no accepted benchmark for evaluating the effectiveness of NGOs in their stated missions. NGOs are not subject to the standards of budgetary and governance oversight that apply to listed companies or government officials in democratic States. The distinguishing feature of NGOs is that donors do not benefit directly from their contributions, with the benefit accruing instead to third parties targeted by the organizations or to society as a whole. As a result, NGOs have traditionally been accorded the presumptions of moral authority, altruism and absence of conflicts of interest. However, the NGO sector is now being viewed as an area where same type of governance standards may be applicable as to that of the corporate sector. The credibility of an organization can be enhanced by adherence to the principles and practices of good governance. This paper examines how good governance practices are being followed by the NGOs operating in the districts of northern West Bengal, and offer some suggestions for improvement of the present scenario.
Keywords: NGOs, governance, accountability assurance, North Bengal, Z-test.
1. Introduction In India over the past quarter–century, there has been a rapid growth, in the number of NGOs involved in the developmental works, in the number of people working for NGOs, and in the amount of money which flows into the hands of voluntary agencies. Perhaps the highest growth has been in the number of new grass-root organizations referred to as ‗groups‘ and sometimes as peoples organizations, (Human Development Report, 2004) which have grown up locally – some extending no further than one or two villages. There are limits to the ‗road across‘ from corporate and regulatory governance to NGO governance, because NGOs have their own special features. Their role as voluntary organizations distinguishes them from the government sector and their not-for-profit status distinguishes them from business. In a highly competitive, globalized and digitized operating environment combined with reduced donor flight and a myriad of questions by governments & other stakeholders on accountability, transparency, value addition, legitimacy and overall credibility of the NGOs, good governance has emerged not only as a tool to enhance professionalism but, more importantly, to ensure that NGO interventions are effective, sustainable, efficient and positively perceived by all stakeholders. For the NGOs to deliver services effectively, the importance of good governance has to be emphasized.
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Volume 3 ISSN 0975-0746 In spite of such importance, NGO governance has received relatively little attention from researchers that holds significant promise as an important area of research. Hence, an attempt has been made to throw some light on this issue with the help of a primary survey conducted among selected NGOs operating in the Northern West Bengal. This paper specifically aims at: analyse and develop an understanding of the term NGO governance; examine empirically how far the NGOs that are operating in Northern West Bengal, have adopted good governance principles; identify the lapses, if any, in the performance of the NGOs in this regard; and put forward some suggestions for improvement of the existing scenario. In view of the above objectives, the paper is organized as follows. The next section discusses the fundamental concept of the NGO governance and the principles of good governance. Section 3 sets down the methodology comprising sample size and distribution, questionnaire designed for the study, period of study and statistical tools used for analysis. Section 4 delineates the hypothesis that has been framed for this study and section 5 deals with analysis and findings of the study. Concluding remarks and suggestions are presented in section 6.
2. NGO Governance In the public sector, good governance is based on a system of checks and balances between the different branches of government (legislative, executive, judicial). It is understood to include a process of regular consultation between governmental authorities and the general public, so that citizens can hold authorities accountable to their trust and ensure their interests are served (Vibert, 2006). A non-profit organization exercises good governance when it has an internal system of checks and balances in order to ensure that the public interest is served. Good NGO governance is based on how power is distributed amongst the organizational entities, i.e. management of the governing body. This arrangement helps restrain and moderate the control of any one person or group, ensure the organization‘s resources are well managed and safeguard the NGO‘s public-service orientation (Vibert, 2006). NGO governance is an emerging term which describes a framework covering both the corporate governance and the business governance aspects of an organization. Achieving a panacea of good corporate governance that is linked strategically with performance management will enable NGOs to focus on the key drivers that move their organizations forward. This is both a challenge and an opportunity (PAIB, 2002).
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Fig.1: The NGO Governance Framework (PAIB, 2002).
The above diagram is much similar to that of Enterprise Governance Framework (PAIB, 2002, www.ifac.org). The figure above illustrates the reach of NGO Governance. It constitutes the entire accountability framework of an organization. In general, the conformance dimension takes an historic view while the performance dimension is forward looking. The lines show that, although the conformance feeds directly to accountability and the performance to resource utilization, the conformance can also feed to resource utilization while the performance can feed to assurance (ibid). The conformance dimension sits on the left hand side of the illustration which seems highly appropriate given that this is the side of the brain that governs our logical, orderly and analytical functions while right brain thinking tends to be intuitive, holistic and creative (ibid). Governance – the manner in which power is exercised in the management of organizational resources in order to achieve the organizational mission – is of critical importance for NGOs. Good governance is essential for order and equality, efficient delivery of goods and services, accountability in the use of power, protection of human rights and freedom, and maintenance of an organizational framework within which each person can contribute fully towards finding innovative solutions to common problems.
3. Methodology The study is primarily empirical in nature. In order to get first-hand information on the good governance practices of NGOs in the 7 districts of northern West Bengal we have conducted field survey through a structured questionnaire to extract the necessary data for analysis. 55 NGOs (about 15% of the total population) were selected on stratified random sampling basis out of the 28 | Business Perspectives
Volume 3 ISSN 0975-0746 listed 366 NGOs (DAINET, 2000) operating in these 7 districts of West Bengal. In order to reduce biasness of the responses and to establish the measurement reliability and validity of the survey instrument we decided to conduct the survey in two phases. Accordingly, the first draft of questionnaire was sent to NGO leaders of selected 55 NGOs via e-mail and speed post out of which 9 questionnaires had to be cancelled due to incomplete responses. The process was repeated after a span of 3 months amongst 46 NGOs to see whether there are any variances in their answers with that of their earlier responses. It has been found that responses of 5 NGOs differ with that of their previous responses while the answers of 41 NGOs remain unaltered. Thus the final sample is 41. However, these 41 NGOs spread up in all the 7 districts of northern West Bengal as their focused area of operation. The description of the sample is given in Table 1.
Table 1: District wise Representation of the Sample NGOs Districts Number of Total Number Percentage of Sample of NGOs Sample NGOs NGOs Jalpaiguri 6 57 10.53 Coochbehar 5 41 12.20 Darjeeling 7 68 10.30 Dinajpur(North) 5 35 14.29 Dinajpur(South) 5 33 15.15 Malda 7 87 8.05 Murshidabad 6 45 13.33 Total 41 366 11.20
Source: Field Survey
3.1 Design of Questionnaire: The questionnaire developed for the study is based on five basic parameters as indicated below: o Accountability to funding agencies, stakeholders, legal authority, employees and beneficiaries. The governing body of an organization should be ready to account for the use of resources and for its actions. o Effectiveness and efficiency in the use of resources and in getting results. o Integrity and fairness in all its dealings and operations, hence governance that is honest, faithful and diligent. o Responsibility, hence leadership that is capable, responsible, representative and conscious of its obligations. o Transparency and open leadership with accurate and timely disclosure of information relating to activities of an organization.
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Volume 3 ISSN 0975-0746 Based on the above parameters the questionnaire was framed to know whether the NGOs: Question 1: sustain well-organized, proficient and transparent administration to meet well defined objectives; Question 2: are governed with integrity, probity and transparency; Question 3: are managed by responsible leaders who are capable, responsible, representative and conscious of their obligations; Question 4: are effective and efficient in the use of resources and in getting results; Question 5: are ready to account for the use of resources and for their actions; Question 6: comply with legal and regulatory requirements; Question 7: adopt policies based on the principles of democracy; Question 8: make timely disclosure of information relating to activities of an organization; Question 9: make timely financial disclosure to cover sources and uses of funds, assets and liabilities; Question 10: apply proper and relevant Accounting Standards that are being applicable to NGOs; Question 11: ensure that internal financial controls are in place and working; Question 12: ensure that the organization‘s accounts are regularly audited; Question 13: ensure that the audit reports are produced and distributed; Question 14: make clear description of duties and responsibilities of NGO staff; Question 15: are accountable to funding agencies, stakeholders, legal authority, employees and beneficiaries; Question 16: recognize and protect stakeholders‘ interests; and Question 17: keep minutes of all meetings of the governing bodies.
3.2 Period of Study: The Field study was conducted during the year 2008-2009. 3.3 Statistical Tools used for analysis: The objective of our study as stated earlier was to examine the governance practices of NGOs that are operating in the districts of northern West Bengal. For this purpose data collected through questionnaire have been duly processed, tabulated and analyzed using Test of Proportion (z Test). This statistical test reveals how far the hypotheses is tenable in the light of the information provided by the respondents.
4. Hypothesis: We have framed null hypotheses (Ho) and alternative hypotheses (H1) as follows: HO : Around 50% (fifty percent) of the selected NGOs are carrying out good governance practices.
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H1 : (a) More than 50% (fifty percent) of the selected NGOs are carrying out good governance practices. [+ve result will indicate (a) is true], and (b) Less than 50% (fifty percent) of the selected NGOs are carrying out good governance practices. [-ve result will indicate (b) is true]. The test statistic:
Where P = observed value
And Ho: = 0.50 against H1(a) : > 0.50 and H1(b) : < 0.50
For testing significance at 5% level, the null hypotheses Ho is rejected when the value of z is either greater than 1.645 or less than - 1.645. If z > 1.645 then H1(a) is true and if z < -1.645 then H1(b) is true. Following the methodology mentioned above, z values have been calculated against each of the 17 questions for all the 7 districts of northern West Bengal. The results and its implications are briefly stated in table 2 where the term ‗Accepted‘ indicates that about 50% of the selected NGOs are carrying out good governance practices and ‗Rejected‘ implies that either more than 50% of the selected NGOs are carrying out good governance practices (for positive results) or less than 50% of the selected NGOs are carrying out good governance practices (for negative results).
5. Analysis and Findings of the study Based on the analysis of questionnaires collected from the NGOs and results in table 2 (see annexure), we summarize below the findings of the study. I.An important feature is that leaders of all 41 NGOs under the study feel that their organization sustain well-organized,capable and transparent administration to meet well-defined objectives; govern organization with integrity, honesty and transparency; are managed by competent, responsible and conscious leaders; use organization’s resources effectively and efficiently; conforms to the legal and regulatory requirements; ensure that the organizations accounts are regularly audited; are accountable to funding agencies, stakeholders, legal authority, employees and beneficiaries; recognize and protect stakeholders’ interests and maintain minutes of all its meetings. It has been observed that preparation and distribution of audit report is ensured by only 4 NGOs (9.76%). II.In the district of Coochbehar, null hypotheses (Ho) [i.e. around 50% of the selected NGOs are carrying out good governance practices] is accepted in 6 cases, the highest acceptance of null hypotheses among all the 7districts in northern West Bengal followed by Jalpaiguri and Dinajpur (North). Alternatively in the districts of Darjeeling and Murshidabad, the null hypotheses is accepted in 2 cases each followed by the district of Malda. In the districts of Darjeeling, Malda and Murshidabad, alternative hypotheses H1(a) [i.e. more than 50% of the 31 | Business Perspectives
Volume 3 ISSN 0975-0746 selected NGOs are carrying out good governance practices] is true for 11 cases which is higher than the rest of the districts. But at the same time it may be noted that in the district of Darjeeling, and Murshidabad alternative hypotheses H1(b) [i.e. less than 50% of the selected NGOs are carrying out good governance practices] is true for 4 cases which is also the highest figure in its category. On the other hand in the districts of Jalpaiguri and Coochbehar H1(a) is found to be tenable for 10 cases and 9 cases respectively and H1(b) is true for 2 cases each. So it may be concluded that the NGOs operating in Jalpaiguri are the best performers and the NGOs of other 6 districts demonstrates mixed performances as far as ‘carrying out good governance practices’ is concerned. III.It is also evident from the study that the Board of 28 (68.29%) NGOs are ready to account for the use of resources in getting results; 22 (53.66%) NGOs adopt policy based on the principles of democracy; 25 (60.97%) NGOs make timely disclosure of information relating to activities of an organization; 8 (19.51%) NGOs make timely financial disclosure to cover sources and uses of funds, assets and liabilities but none of the NGOs reveal proper and relevant Accounting Standards that are being followed by the NGOs. The study also reveals that only 5 (12.19%) NGOs make clear description of duties and responsibilities of NGO staff.
6. Conclusion and Suggestions A number of selected NGOs in the study have ignored the importance of timely disclosure of information relating to activities of their organizations and timely financial disclosure for performance of goal. Therefore, as the role of NGOs in solving problems of human rights, poverty, environment, and peace- building is increasing, there is a need for enhanced governance and accountability in all sectors. Governance has become an issue of world-wide importance. The efficiency and accountability of organizations are matter of both public and private interests. With a significant increase in the number of NGOs, funding agencies, beneficiaries and other collaborators have identified governance as a key issue in organizational effectiveness and efficiency. In our study, it has been found that while the Boards of modern democratic NGOs are assumed to be more people friendly and have in place reliable arrangements for receiving and redressing people‘s grievances, in actual practice access to such mechanisms tend to be available to some small empowered sections of people only. The vast numbers of illiterate and underpowered people living at the margins of the society still suffer in silence. Ideologically the democratic NGOs are expected to have foolproof arrangements for not only redressing people‘s grievances but also for directly involving people in specific decision making including developmental planning. However in practice seldom by the NGOs acquire the attitude to work through mechanisms that enable ordinary people to influence policy of the organizations. This situation is likely to change. As the movement of good governance is gaining recognition, this weakness in policy making process is sought to be remedied through innovative ways of bringing about people‘s participation in
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Volume 3 ISSN 0975-0746 policy formulation on the one hand and implementation on the other. One of the ways of involving people in both the aspects of policy is through public hearing. Now, based on the findings of the study, the following suggestions are offered for improvement of the governance in NGOs. There should be instructions handbook / manual for governing bodies of NGOs. The handbook would address roles and functions of Boards, values, philosophy, vision and mission, procedures for Board operations, criteria for Board appointments, principles of good governance and evaluation mechanism. Long-term strategic plans are required for NGO development. Emphasis should be laid on NGO leadership, with a focus on senior management and Boards, which will help create an enabling environment thus enhancing proactive leadership development. The Boards of NGOs should include an equal number of men and women, people of different ages, young and dynamic professionals, experienced social workers and representatives of the target groups of the NGOs. It is desirable to have some board members with expertise in personnel management, finance and law. NGO Boards should review and assess their own performance and establish oversight committee to oversee effective operation of the Boards. The governance of NGOs should cover both conformance dimension as well as performance dimensions. In other words, it should consider the whole picture of the organization to ensure that strategic goals are aligned and good management is achieved. While the conformance dimension takes an historic view, the performance dimension is forward looking. Strategic plans, financial plans, performance measurement, control systems and stakeholders satisfaction are under the coverage of performance dimensions. It is important the regulatory body should strengthen the accounting and reporting practices as well as ensure compliance of audit standards. Audit quality control process must ensure that the audit effectiveness is raised. The performance of projects, activities or operations of the NGOs should conform to the purpose of the grant, manner in which it should be utilized and the time frame, etc. It is recommended that the donors and funding agencies should critically examine the effectiveness of the NGOs in utilization of resources and in achieving results through Performance Audit. For better transparency and accountability to the target groups as well as to the society at large, it is suggested that the NGOs should publish their accounts in a newspaper or they should put their financial statements on their websites. It is evident from the study that governance and leadership of NGOs need to be strengthened for greater efficiency, effectiveness and impact. Programmes of capacity building aimed at sustainability of NGOs should be created and institutionalized. NGOs need to create and sustain
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Volume 3 ISSN 0975-0746 partnerships with governments and other organizations working in various fields and share their experiences, best practices and expertise. Existence of a positive and enabling environment is required for raising awareness among NGOs for effective governance and sustainability of NGOs,. Leaders need to create a culture of ownership and shared values with the staff and facilitate an empowering culture within an organization.
References: 1. Centre for African Family Studies, A Situation Analysis of NGO Governance and Leadership in Eastern, Southern, Central and Western Africa, November, (2001). 2. Batten, J. R. (2006), NGOs and Good Governance, Capacity Building for the Not-for- Profit Sector in East Africa, Poverty Eradication Network. 3. Burwell, B. and Mankins, M. C. (2002), Improving Corporate Governance from the Inside, Marakon Associates. 4. CIMA, IFAC (2004), Enterprise Governance: Getting the Balance Right. 5. Gupta, S. P. (2001), Statistical Methods, Sultan Chand, New Delhi. 6. Levin, R. I. (1979), Statistics for Management, Prentice Hall of India, New Delhi. 7. Vibert, F. (2006), International NGOs: An International Code of Conduct. An Approach Paper, European Policy Forum. 8. Websites: o www.cimaglobal.com o www.cafs.org o www.icnl.org o www.ifac.org o www.oecd.org o www.penkenya.org
ANNEXURE Table 2: District wise Acceptance/Rejection of null hypothesis using Z values (standard normal) Sl no Jalpaiguri Coochbehar Darjeeling Dinajpur(North) questions 1 Rejected(positive) Rejected(positive) Rejected(positive) Rejected(positive) 2 Rejected(positive) Rejected(positive) Rejected(positive) Rejected(positive) 3 Rejected(positive) Rejected(positive) Rejected(positive) Rejected(positive) 4 Rejected(positive) Rejected(positive) Rejected(positive) Rejected(positive) 5 Rejected(positive) Accepted Rejected(positive) Accepted 6 Rejected(positive) Rejected(positive) Rejected(positive) Rejected(positive) 7 Accepted Accepted Accepted Accepted 8 Accepted Accepted Rejected(positive) Accepted 9 Accepted Accepted Rejected(negative) Rejected(negative) 10 Rejected(negative) Rejected(negative) Rejected(negative) Rejected(negative) 11 Accepted Accepted Accepted Accepted 12 Rejected(positive) Rejected(positive) Rejected(positive) Rejected(positive) 13 Rejected(negative) Rejected(negative) Rejected(negative) Rejected(negative) 14 Accepted Accepted Rejected(negative) Accepted 15 Rejected(positive) Rejected(positive) Rejected(positive) Rejected(positive) 16 Rejected(positive) Rejected(positive) Rejected(positive) Rejected(positive) 17 Rejected(positive) Rejected(positive) Rejected(positive) Rejected(positive)
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Volume 3 ISSN 0975-0746 Table 2 (Contd.) Districtwise Acceptance/Rejection of null hypothesis using Z values (standard normal) Sl no Dinajpur (South) Malda Murshidabad questions 1 Rejected(positive) Rejected(positive) Rejected(positive) 2 Rejected(positive) Rejected(positive) Rejected(positive) 3 Rejected(positive) Rejected(positive) Rejected(positive) 4 Rejected(positive) Rejected(positive) Rejected(positive) 5 Accepted Rejected(positive) Rejected(positive) 6 Rejected(positive) Rejected(positive) Rejected(positive) 7 Accepted Accepted Accepted 8 Accepted Rejected(positive) Accepted 9 Rejected(negative) Rejected(negative) Rejected(negative) 10 Rejected(negative) Rejected(negative) Rejected(negative) 11 Rejected(positive) Accepted Rejected(positive) 12 Rejected(positive) Rejected(positive) Rejected(positive) 13 Rejected(negative) Rejected(negative) Rejected(negative) 14 Accepted Accepted Rejected(negative) 15 Rejected(positive) Rejected(positive) Rejected(positive) 16 Rejected(positive) Rejected(positive) Rejected(positive) 17 Rejected(positive) Rejected(positive) Rejected(positive) Source: Field Survey, Results computed. Note: Ho is rejected when the value of Z is either greater than 1.645 or less than - 1.645
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Volume 3 ISSN 0975-0746 FINANCIAL PERFORMANCE ANALYSIS: A COMPARATIVE STUDY ON THE SELECTED CEMENT COMPANIES IN INDIA
Subhas Chandra Sarkar Professor, Department of Commerce, University of Kalyani
Abstract
In this paper an attempt has been made to make a comparative financial performance analysis between public sector and private sector cement companies in India. With a view to making the analysis fruitful, both accounting and sophisticated statistical tools have been adopted. The study reveals that financial performance of Private Sector Cement Company is comparatively ahead with that of Public Sector Cement Company. This pinpoints that management of various financial aspects of Public Sector Cement Company be given appropriate emphasis to make it competitive.
Key Words: Liquidity indicators, financial performance, overall profitability, asymmetrical distribution, symmetrical distribution.
1. Introduction India is the second largest cement producer after China in the world. Cement is the backbone for sustainable development of any country throughout the world. Cement, among others, is highly essential item for the purpose of development of infrastructure especially for the construction of buildings, bridges, reservoirs, water tanks, dams, canals etc. Cement is one of the core industries which plays a vital role in the growth and development of a nation. The cement industry in India has been expanding significantly because of increasing infrastructural activities and demand from housing sector. Keeping in view with the technological world, the Indian cement industry has transformed itself into a more advanced one. At present, the Indian cement industry comprise of 137 large and 365 mini cement plants. The Indian cement industry has great future growth potential. It is evident from the fact that the per capita consumption of cement in India is much less as compared to the world average. In 2011, per capita cement consumption was around 150 kg as compared to the per capita world average of over 350 kg, which shows vast potential for growth. The corresponding figure is 660 kg per capita in China, 631 kg per capita in Japan and 447 kg per capita in France. The sector-wise demand for cement in India: housing—67%, infrastructure—13%, commercial construction—11% and industrial sector—9%.
2. Objective The objective of the paper is to make a comparative analysis on the financial performance of the two selected cement companies in India. To fulfill the objective, the under-noted issues are required to be emphasized: (i) To assess the individual impact of some selected liquidity indicators on the profitability. (ii) To measure the joint impact of liquidity indicators on the profitability. 36 | Business Perspectives
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3. Methodology Data have been collected from different websites. To analyze data, both accounting and statistical tools have been adopted. In accounting tool, various accounting ratios have been adopted. In case of statistical tool, descriptive statistics, multiple correlations and multiple regressions have been used. SPSS package has been used in finding the result of statistical tool. Two cement companies one from public sector and other one from private sector have been conveniently chosen. A time frame of six years from 2007 to 2012 has been covered. In measuring the financial performance, nine accounting ratios, such as, current ratio (CR), quick ratio (QR), cash to current liability ratio (CCLR), debt equity ratio (DER), interest coverage ratio (ICR), stock turnover ratio (STR), debtors turnover ratio (DTR), creditors turnover ratio (CTR) and return on capital employed ratio (ROCE) have been adopted. ROCE has been considered as dependent variable while other accounting ratios have been taken as independent variables for finding the coefficient of multiple correlations and regressions. All accounting ratios except ROCE are termed as liquidity indicators.
4. Analysis and Interpretations In this section, an attempt has been made to make comparative financial performance of the two selected cement companies in India with a view to observing the magnitude of differences that may arise in course of analysis. The analysis and interpretations are given separately in two sections that follow.
4.1 Madras Cement Ltd. (MCL)—Public Sector Company It is evident from Table-1 that ICR has shown extremely high level of fluctuation (89.96%) followed by ROCE, CCLR, STR, DER, DTR, CR, CTR and QR over the years under review. The higher is fluctuation in profit, the higher is the perception of risk associated with ICR. ROCE has also shown a fluctuation of 61.34% which is significantly high. This high fluctuation indicates inconsistency in ROCE to a large extent over the years under consideration. Table-1 discloses that none of the distribution of the values of the variable within the individual liquidity indicators is symmetrical since the values of variable are not equidistant from their mean, i.e., skewed. Distribution of the values of the variable relating to five liquidity indicators, such as, CCLR, ICR, DTR, CTR and ROCE has shown positively asymmetrical distribution. On the contrary, distribution of the values of the variable relating to remaining four liquidity indicators, such as, CR, QR, DER and STR has shown negatively asymmetrical distribution. With a view to observing the level of peakedness of the values of the variable near the average, kurtosis may be looked into. A very high level of concentration near the average of the values of the variable relating to CCLR is found and the distribution is said to be Lepto-Kurtic. On the other hand, type of concentration of the values of the variable relating to CR, QR, DER, ICR, STR, DTR, CTR and ROCE is observed and all the distributions are said to be Play- Kurtic as revealed by Table-1.
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Volume 3 ISSN 0975-0746 Table-2 shows that the coefficient of correlation between CR & ROCE comes to (-)0.458. This indicates that there is a moderate degree of negative association between the variables of two liquidity indicators which is statistically not significant at 5% level. Secondly, the coefficient of correlation between QR and ROCE arrives at (-)0.751. It indicates there is a moderately high degree of negative association between the variables of two liquidity indicators that is statistically not significant at 5% level. Thirdly, the coefficient of correlation between CCLR and ROCE is 0.763. This indicates that there is moderately high degree of positive association between the variables of two liquidity indicators which is statistically not significant at 5% level. Fourthly, there is a moderate degree of negative association between DER and ROCE as the coefficient of correlation between the variables of two liquidity indicators comes to (-)0.450 which is statistically not significant at 5% level. Table-1: Descriptive Statistics (MCL) N Minim Maxi- Mean S. D. C.V. Skewnes Kurtos -um mum (%) s is CR 6 0.25 0.39 0.332 0.058 17.6 -0.748 -1.676 QR 6 0.73 1.19 0.9933 0.156 15.74 -0.765 1.486 CCL 6 0.07 0.16 8.57E- 0.036 42.37 2.333 5.526 02 DER 6 1.02 1.98 1.5535 0.337 21.67 -0.634 0.233 ICR 6 2.8 21.52 8.2817 7.45 89.96 1.483 1.238 STR 6 39.91 70.27 57.2797 13.49 23.55 -0.562 -1.976 DTR 6 16.57 29.07 22.924 4.927 21.49 0.045 -1.583 CTR 6 8.17 13.41 10.3547 1.724 16.65 1.043 2.465 ROC 6 4.9 26.4 13.5167 8.291 61.34 0.869 -0.766 E Table-2: Simple Correlation Statistics (MCL) CR QR CCL DER ICR STR DTR CTR ROCE CR 1.000 QR 0.321 1.000 0.535 . CCLR 0.032 -0.837 1.000
0.952 .038* . DER -0.533 0.476 -0.715 1.000 0.277 0.339 0.11 . ICR -0.264 -0.809 0.848 -0.629 1.000
0.613 0.051 .033* 0.181 .
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Volume 3 ISSN 0975-0746 STR -0.662 -0.511 0.55 0.095 0.618 1.000
0.152 0.301 0.258 0.858 0.191 . DTR -0.888 -0.286 0.169 0.423 0.351 0.881 1.000
.018* 0.582 0.75 0.403 0.495 .02* . CTR -0.185 -0.723 0.917 -0.549 0.838 0.748 0.468 1.000
0.726 0.105 .010** 0.259 .037* 0.087 0.35 . ROCE -0.458 -0.751 0.763 -0.45 0.968 0.755 0.564 0.844 1.000 0.361 0.085 0.078 0.371 .001** 0.083 0.244 .034* . ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
Fifthly, the coefficient of correlation between ICR and ROCE is 0.968. It discloses that there perfectly high degree of positive association between the variables of two liquidity indicators which is statistically significant at 1% level. Sixthly, a moderately high degree of positive association between STR and ROCE is found and coefficient of correlation comes to 0.755 that statistically not significant at 5% level. Seventhly, there is a little better than moderate degree of association between DTR and ROCE and the value of coefficient of correlation is 0.564 which is statistically not significant at 5% level. Eighthly, a moderately high degree of positive association between CTR and ROCE is observed as the value of coefficient of correlation arrives at 0.844 that is statistically significant at 5% level.
Joint impact of liquidity indicators on profitability: Table-3 discloses that the multiple correlation coefficient between ROCE, dependent variable and QR, CCLR, DER and ICR, independent variables considered together is found to be (-)0.4315. This indicates that the profitability is negatively influenced by QR, CCLR, DER and ICR moderately. Again, it is evident from the value of R2 that 98.4397% of the variation in ROCE is accounted for by the joint variation in CR, QR, CCLR, DER and ICR.
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Volume 3 ISSN 0975-0746 Table-3: Multiple Regression Analysis (MCL) Coefficie Std. t-ratio p-value VIF nt Error const -15.0675 24.6833 -0.6104 0.6511
QR 6.71527 14.6787 0.4575 0.72685 1.98301 CCLR 2.46558 79.0632 0.0312 0.98015 2.00247 DER 6.66588 4.82235 1.3823 0.3987 1.73248
ICR 1.36997 0.285153 4.8043 0.13064 1.93652
R-squared 0.984397 Adjusted 0.921986 R- squared R(Multiple) -0.431463 Durbin- 2.251885 Watson S.E. of 2.315638 a Dependent Variable: ROCE regression b Predictors: (Constant), ICR, CCLR, DER, QR
Table-3 shows that the strength of association between ROCE, dependent variable and all the independent variables taken together with a view to showing joint impact on overall profitability. It is observed that an increase in QR by one unit leads to increase in ROCE by 6.7152 units which is statistically not significant at 5 % level as the value of p>0.05. Similarly, for one unit increase in CCLR, DER and ICR, the profitability of the company increases by 2.4656 units, 6.6658 units and 1.3610 units respectively and the they are statistically not significant at 5% level because p-values for all the three independent variables are greater than 0.05. Again, there is no multicollinearity among the four independent variables, such as, QR, CCLR, DER and ICR as their values of VIF is about 2. However, multicollinearity exists among the other independent variables, such as, CR, STR, DTR and CTR. Multicollinearity indicates that independent variables, such as, CR, STR, DTR and CTR are highly inter-related each other, that is why they are removed from the final table after making several trials in the SPSS. Durbin-Watson (DW) statistic indicates serial correlation of error terms/unexplained variables. When DW statistic (1≥DW≤4) exceeds the limit, then it is regarded as error terms which are serially correlated. Here, D-W statistic has been between 1 and 4, so we can easily understand that the residuals are not dependent, i.e., unexplained variables are independent.
4.2 Associated Cement Companies Ltd. (ACL)—Private Sector Company Table-4 discloses that CTR has shown significantly high level of fluctuation (61.42%) followed by DER, CCLR, ROCE, QR, ICR, DTR, CR and STR over the years under consideration. The higher is fluctuation in CTR, the higher is the perception of risk associated in respect of payment to suppliers of goods and services. ROCE has also shown a fluctuation of 34.24% which is
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Volume 3 ISSN 0975-0746 moderate. This moderate fluctuation indicates inconsistency in ROCE over the years under review. Table-4 discloses that the concentration of the values of the variable within the individual liquidity indicators shows asymmetry because the values of variable are not equidistant from their mean. Distribution of the values of the variable relating to six liquidity indicators, such as, CCLR, ICR, STR, DTR, CTR and ROCE has shown positively asymmetrical distribution. On the contrary, distribution of the values of the variables relating to remaining three accounting ratios, such as, CR, QR and DER has shown negatively asymmetrical distribution. It is evident from Table-4 that an extremely high level of peakedness of the values of variable of CTR near the average is observed and the distribution is said to be Lepto-Kurtic as the value of 2>3. Again, a very high level of concentration of the values of variable of DER near the average is noticed and the distribution is to be regarded as Lepto-Kurtic since the value of 2>3. On the contrary, level of concentration of the values of variable in respect of CR, QR, CCLR, ICR, STR, DTR and ROCE is to be mentioned as Play-Kurtic since all the values of 2<3. Table-5 depicts that the coefficient of correlation between CR and ROCE arrives at 0.467. This indicates a moderate degree of positive association between the variables of two liquidity indicators that is statistically not significant at 5% level. Secondly, the coefficient of correlation between QR and ROCE comes to 0.433. It also indicates a moderate degree of positive association between the variables of two liquidity indicators which is statistically not significant at 5% level. Thirdly, the coefficient of correlation between CCLR and ROCE is 0.33. This indicates a degree of positive association between the variables of two liquidity indicators which is statistically not significant at 5% level. Fourthly, there is a little better than moderate degree of positive association between DER and ROCE as the coefficient of correlation between the variables of two liquidity indicators comes to 0.529 which is statistically not significant at 5% level. Fifthly, the coefficient of correlation between ICR and ROCE is 0.758. It discloses that there is a high degree of positive association between the variables of two liquidity indicators which is statistically significant at 10% level. Sixthly, a high degree of positive association between STR and ROCE is found and coefficient of correlation comes to 0.763 that statistically significant at 10% level. Seventhly, there is a high degree of negative association between DTR and ROCE and the value of coefficient of correlation is (-)0.622 which is statistically not significant at 5% level. Eighthly, there is a high degree of negative association between CTR and ROCE and the value of coefficient of correlation arrives at (-)0.604 that is statistically not significant at 5% level.
Joint impact of liquidity indicators on profitability: Table-6 discloses that the multiple correlation coefficients between dependent variable, ROCE and independent variables, such as, QR, CCLR, DER and ICR taken together come to 0.815. This asserts that the profitability is highly and positively influenced by QR, CCLR, DER and ICR highly. Again, it is evident from the value of R2 that 66.50% of the variation in ROCE is accounted for by the joint variation in QR, CCLR, DER and ICR.
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Volume 3 ISSN 0975-0746 Table-6 shows that the strength of association between dependent variable, ROCE and all the independent variables, such as, QR, CCLR, DER and ICR taken together in order to assess the joint impact on overall profitability. It is observed that an increase in QR by one unit causes increase in ROCE by 131.123 units which is statistically not significant at 5 % level as the value of p>0.05. Similarly, for one unit increase in CCLR, DER and ICR, the profitability of the company decreases by 2.4656 units, increases by 274.309 units and decreases by 0.35 units respectively and the they are statistically not significant at 5% level because for all the three independent variables values of p>0.05. Again, there are no multi-co-linearity among the four independent variables, such as, QR, CCLR, DER and ICR as their values of VIF≤2. However, there is a presence of multi-co-linearity among the other independent variables, such as, CR, STR, DTR and CTR. Multi-co-linearity confirms that independent variables, such as, CR, STR, DTR and CTR are highly inter-related each other. That is why they are omitted from the final table after making several trials in the SPSS. Durbin-Watson (DW) statistic indicates serial correlation of error terms/unexplained variables. When DW statistic (1≥DW≤4) exceeds the limit, then it is regarded as error terms which are serially correlated.
5. Findings Findings are summarized below: (i) Fluctuation in liquidity indicators is higher in public limited company (MCL) than private limited company (ACCL). This indicates better consistency in the management of liquidity indicators in ACCL than MCL. (ii) Out of the distribution of the values of the variable of eight liquidity indicators, an equal numbers of distribution are positively and negatively asymmetrical in case of MCL. On the contrary, five and three distributions are positively and negatively asymmetrical respectively in case of ACCL. Therefore, none of the distribution of the liquidity indicators is symmetrical for both the companies. (iii) In case of MCL, one distribution has shown extremely high level of concentration while two distributions have shown such level of concentration in case of ACCL. (iv) High degree of positive association between CCLR & ROCE, between ICR & ROCE, between STR & ROCE and between CTR & ROCE is observed in case of MCL. Conversely, more or less same degree of positive association is found between ICR & ROCE and between STR & ROCE. (v) The coefficient of multiple regressions is moderately negative in case of MCL. On the other hand, such coefficient is almost perfectly positive in case of ACCL. (vi) Multi-co-linearity exists within the four liquidity indicators, such as, CR, STR, DTR and CTR for both companies under the study. As such, they are removed from the final table. (vii) Financial performance in terms of liquidity indicators as measured by coefficient of variation, simple correlation and multiple regressions is better in ACCL than MCL.
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Volume 3 ISSN 0975-0746 Table-4: Descriptive Statistics of ACC Ltd N Minimum Maxi- Mean Std. C.V (%) Skewness Kurtosis mum Deviation CR 6 .51 .92 .7500 .1637 -.462 -1.501 QR 6 .29 .61 .4570 .1367 -.112 -2.627 CCL 6 .21 .53 .3477 .1238 .341 -1.403 R DER 6 .02 .10 7.33E-02 2.73E-02 -1.631 3.157 ICR 6 9.89 20.43 14.8055 4.1934 .166 -1.922 STR 6 37.24 40.63 38.7638 1.3738 .235 -2.137 DTR 6 27.10 48.94 34.8967 9.2990 .996 -1.264 CTR 6 2.19 7.63 3.4550 2.1222 2.113 4.500 ROC 6 13.90 34.40 22.3833 7.6648 .626 -.577 E
Table-5: Simple Correlations of ACC Ltd QR CCLR DER ICR STR DTR CTR ROCE CR QR 1.000 CCLR .941 1.000 DER .241 .397 1.000 ICR .464 .404 .761 1.000 STR .442 .292 .567 .962 1.000 DTR .033 -.025 -.873 -.726 -.618 1.000 CTR -.204 -.365 -.960 -.656 -.461 .889 1.000 ROCE .433 .330 .529 .758 .763 -.622 -.604 1.000 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
Table-6: Multiple Regression Coefficients of ACC Ltd Unstandardized t Prob. Coefficients Model B Std. Error VIF 1 (Constant) -5.522 22.415 -.246 .846 QR 131.123 263.185 .498 .706 1.664 CCLR -135.030 279.085 -.484 .713 1.567 DER 274.309 669.223 .410 .752 1.979 ICR -.350 4.112 -.085 .946 1.087 Adjusted S.E=9.9 2 Durbin- R=0.815 R =0.665 R Square=- 3 Watson=2.97 0.677 a Dependent Variable: ROCE b Predictors: (Constant), ICR, CCLR, DER, QR
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Volume 3 ISSN 0975-0746 References: 1. Invest India Report (2013). Sector overview, http://www.investindia.gov.in/?q=cement-sector 2. http://www.equitymaster.com/research-it/sector-info/cement/Cement-Sector- Analysis-Report.asp
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Volume 3 ISSN 0975-0746 AN ANALYSIS OF THE DEVELOPMENT OF CORPORATE GOVERNANCE IN INDIA
Subhamoy Das Associate Professor, Department of Commerce, University of Kalyani, West Bengal
Abstract The present corporate governance system in India has come through an evolutionary process. Its genesis in India can be traced back to the managing agency system which had played a humongous role in the field of corporate scenario in India as a pioneering system. This was followed by the Business House model, the bedrock for which was first laid out in the famous Bombay Plan. Its move towards the present Anglo-American model is owed largely to the lack of success in the previous interventionist models. But doubtless the experience gathered from the earlier models has provided a great underpinning to the model in currency. With these in the backdrop, this paper seeks to analyse the development of corporate governance system in India that will pave the way toward a further study of corporate governance systems in different countries.
Keywords: Corporate governance, India, managing agency model, business house model, anglo-american model.
JEL Classification : G34; L98; N15
Background A historical analysis of the development of corporate governance shows that there has had been three models of corporate governance in India: i) The managing agency model of the colonial period; ii) The business house model that emerged after independence; and iii) The Anglo-American model adopted around 1991 and continuing till date. Presented hereinafter are the analyses of the models.
Managing Agency Model In India modern corporation emerged out of the ‗managing agency system‘. It is generally regarded that the managing agency system was a European innovation in India. The terms ‗managing agents‘ and ‗managing agencies‘ were used to designate individuals and business firms (partnerships or private companies) that entered into a legal contract with joint stock companies to manage the affairs of the latter. The system of managing agency was so extraordinary that it is very difficult to find a parallel system in the economic history of any other country. ―The pioneering and promoting of industry in India reveal some distinct and almost unique features which differ from those of company promotion in other countries and are almost without parallel in any part of the world.‖ (Lokanathan, 1935, p.13). As business enterprises, managing agencies served three basic functions. (a) They started or promoted new companies. Typically, a businessman or a group of businessmen would float a company with their own capital. After it became successful, they would then sell off most or all of its shareholdings, but still retain control over the company 45 | Business Perspectives
Volume 3 ISSN 0975-0746 through the managing agency contract. (b) Managing agencies were often asked to manage existing companies. In such cases, managing agencies were sought because of their managerial expertise, as demonstrated by their track records. (c) They provided important financial functions. Their ability to attract new investors, to secure bank loans, etc. made managing agencies attractive to joint stock companies especially at a time when the credit system and capital markets were still in their infancy. In India, since the middle of the 19th century came the modern era of business with the passing of the Companies Act, 1850. The managing agency houses since then started organising joint stock companies for operating business on a large scale. ―After the Act of 1850 they turned to this new form of organisation which soon became the principal mechanism for large-scale business.‖ (Sengupta, 1975, p.3) Statistics show that a substantial number of 505 joint stock companies reported to be in existence in 1882 had been formed by the managing agencies (Nigam, 1957, p.2). Data relating to the year 1951-52, when the managing agency system was at its last stage, was furnished by Mr. C. D. Deshmukh, the then Finance Minister, during the Parliamentary debate on the Companies Bill, showing that 1340 managing agencies had contributed to the paid-up capital of 1720 companies managed by them, a total amount of Rs.292 million, which worked out at 13.6% of the total paid-up capital of the companies. The contribution of managing agencies was 23.9% of all loans and advances from various sources. (NCAER, 1959, pp.67-68) A key feature of the managing agency model related to control. The managing agency was a novel development in that it shifted the locus of corporate power and corporate control from the level of the individual joint stock company to what was, in effect, a parent or apex company, viz., the managing agency. In effect, these functioned like holding companies. Managing agencies would float companies, and their imprimatur sufficed to ensure massive over- subscription of shares. Given excess demand, most of these companies could split shareholdings into small enough allotments to ensure that nobody — barring the managing agency — had sufficiently large stocks to ensure their presence in the board of directors. Thus, dispersed ownership allowed managing agencies to retain corporate control with relatively low equity ownership (Goswami, 2000). Another characteristic of the system relating to control is that most Indian managing agencies were founded as partnerships among members of a single family. This nexus between the managing agencies and the business families established the structural basis for the family-controlled conglomerates that have dominated the Indian economy since independence. A second key characteristic of the model involved profit generation. In the managing agency model, the source of profit did not lie in innovations or gains in productivity but rather was related to inflation, intermediation and trade on the basis of market imperfections and market incompleteness. Thus, profits were ―earned‖ primarily through the generation of artificial scarcities and the inflationary effect of these scarcities. Profits also emanated from price fluctuations caused by wars, famines and similar causes. (Sarkar, 1983, pp. 171-172 and 406-407)
Business House Model
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Volume 3 ISSN 0975-0746 After independence, the new Indian government adopted an interventionist approach to development designed to accelerate the rate of industrialisation and growth in the country. The basics of these strategies were first articulated in the famous Bombay Plan of 1944[1] (Thakurdas, et al, 1945) and later formalised in the Industries (Development and Regulation) Act (IDRA) of 1951 and the Industrial Policy Resolution of 1956. The key vehicle for implementing the strategy was to be the Five-Year Plan, while the basic measures of the new model were laid out in the IDRA of 1951. These included: the requirement that all scheduled industries register with the government; the requirement that a licence be procured for the start-up of new undertakings, the expansion of productive capacity and the manufacture of new products; the right of the government to investigate undertakings, require changes (in cases of mismanagement or management not in the national interest) and, in the event of non-compliance, to take over management control; the right of the government to regulate the price, supply and distribution of products produced by certain designated industries. The objectives of this set of regulations, which obviously went far beyond the cost/profit considerations that guide the new ventures in liberal economies, were intended to promote economic growth and employment through support for both large (private and public sector) industrial corporations and small and medium sized businesses. In practice, it created a set of institutional barriers to entry for smaller firms resulting in a systematic weakening of competitions, and became fraught with rent-seeking abuses by political/bureaucratic elites and influence-pedalling by business elites. Christened the ―licence-permit raj‖ by its various detractors, over time this system came to be regarded as the embodiment of the inefficiencies of the model (Mukherjee Reed, 2002, pp.249- 268). The IDRA continued for four decades before being dismantled in June, 1991. The Business House model of corporate governance can be evaluated in terms of corporate growth, rights of minority shareholders and employment. The growth of assets that occurred in the interventionist era, especially since 1970, was concentrated at the upper crust of the corporate economy. Between 1970 and 1985, for example, their assets rose from an index base of 100 to 749 (Sharma, 1989, p.202). While large companies were able to grow rather robustly during the interventionist period, this does not mean that the minority shareholders benefited proportionally. Effective control through inter-corporate investment, interlocking directorates, etc. enabled business families to distribute the benefits in accordance with their own interest and insulated them from any ―voice‖ through formal channels like Annual General Meetings, shareholders‘ resolutions, etc. The increase in employment generation was quite modest in comparison to the accumulation of physical capital, and slowed over time. In an excellent in-depth study on corporate governance models in India, Ananya Mukherjee Reed and Darryl Reed have stated that the defining characteristic of the formal mechanism of control in the Business House model was the superseding of the managing agency contract by an elected Board of Directors. The basis of this switch was laid down in the Companies Act, 1956. 47 | Business Perspectives
Volume 3 ISSN 0975-0746 The Act also contained provisions concerning a number of other areas which, in principle, served to protect shareholder interest and bring the system more in line with the spirit of the traditional Anglo-American model. While similar to Anglo- American model in some of its characteristics, the Business House model also distinguished itself in several ways. One area of difference was that the Companies Act subjected many more corporate decisions to government approval. The second major difference with the Anglo-American model involved the institution of the ‗Nominee Director‘, which enabled banks and other financial institutions to demand of companies the right to nominate a director to represent their interests on the Board. (Mukherjee Reed and Reed, 2004).
Anglo-American Model If we go to the core of the difference between the Anglo-American model and the models followed in countries like Germany, France and the like, we shall see that the Anglo-American model pursues the interests of the shareholders whereas the latter pursues the interests of all the stakeholders, i.e., employees, customers and shareholders. Historically Anglo-American models of corporate governance have been characterised by: (1) a single-tier board structure which gives almost exclusive primacy to shareholder interest (e.g. the board is elected exclusively by shareholders, shareholders have strong rights grounded in company law); (2) a dominant role for financial markets (both as the major source for investment funds and as a disciplinary mechanism to address the agency problem); (3) a correspondingly weak role for banks (which typically provide a small proportion of investment funds, cannot hold shares, do not have nominee directors, etc.); and (4) little or no industrial policy involving firms cooperating with government agencies (and labour bodies) (Reed, 2002, pp.223-247). There are several reasons for developing countries, especially India, for favouring an Anglo-American model. For India, there are strong historical ties to the Anglo-American model (e.g., its company law is firmly rooted in British company law) that make further movement in this direction appear natural to some. Another possible factor is that the lack of success in the previous interventionist models has served to discredit elements commonly associated with other models. It is also the case that, insofar as the previous interventionist model bred uncompetitive firms, strong financial markets present themselves as an important tool for promoting more competitive domestic firms. What is indisputable, however, is the fact that key domestic (business and political) factors have presented past failures as a justification for liberalisation and a move towards an Anglo-American model. Business interests generally tend to favour the Anglo-American model and have been outspoken in opposing the adoption of any other models of governance, especially models that provide a role for stakeholder involvement (e.g., employees), like the Rheinal model (Confederation of Indian Industry, 1998). Another reason for the move to an Anglo-American model has to do with debt and the influence of international financial institutions. The fiscal crisis of 1991 and the consequent need to approach international financial institutions, most prominently the IMF, led the government of India to move towards the introduction of programmes of radical economic liberalisation. As a condition of renegotiating loans, international
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Volume 3 ISSN 0975-0746 financial bodies imposed these structural adjustment programmes on India. These programmes included a variety of features that has a close association with the Anglo-American model of governance. Moreover, the neo-liberal character of globalisation serves to promote an Anglo-American model of corporate governance. In the neo-liberal environment, where domestic firms have to increasingly raise funds in equity markets and states are seeking to induce foreign investment – foreign portfolio investment to finance domestic firms and foreign direct investment to generate employment and stimulate key sectors of the economy – shareholder interests have to be given priority. This necessitates a liberalisation of the capital market. In effect, the Anglo-American model of corporate governance is a logical micro level complement of the macro neo-liberal global economy. Development economists like Amartya Sen argue that (Sen, 1998) proponents of economic liberalisation (who generally advocate Anglo-American corporate governance reforms as well), make a fundamental mistake by assuming that the freeing up of economic opportunities for business necessarily involves funding cuts and a reduced presence by government in other activities, viz., the provision of social welfare programmes. To the contrary, governments in developing economies have a key role to play. Because of the relatively low costs of health and education programmes in these countries, a tremendous impact can be made without affecting the efforts to stimulate economic recovery. Indeed, such efforts provide the necessary basis for long-term growth and development. India can be considered to be in the ‗post-transition regime‘ with a well- defined and stable corporate governance structure and where the management of enterprises is through due process defined by corporate law (Aoki, 1995). The SEBI, as an independent quasi-judicial, regulatory body, regulates the stock exchanges. Corporate governance requirements in India are largely based on recommendations of the Cadbury and Higgs Reports [2] [3] and the Sarbanes- Oxley Act [4]. SEBI has been proactive in keeping India‘s corporate governance rules and regulations in line with best practices around the world (Som, 2006, pp. 4153-4160). Driven by a desire to make Indian business more competitive and respected on the world stage, the Confederation of Indian Industries (CII) published a voluntary Code of Corporate Governance in 1998—one of the first major codes in Asia. SEBI followed, in 1999, by appointing the Kumar Mangalam Birla Committee to recommend improvements to the corporate governance framework. In 2002, SEBI updated its listing requirements with Clause 49.[5] SEBI again revised Clause 49 in late 2004 on the recommendations of the Narayana Murthy Committee on Corporate Governance, with the revisions coming into effect on 1 January, 2006 to incorporate some best practices laid out in the Sarbanes-Oxley Act. SEBI has also issued regulations relating to the acquisition of significant shareholdings, takeovers, share buybacks and insider trading. Bankruptcy and anti-competitive laws are also in place. Other recent developments in the arena of corporate governance in India, inter alia, include the following: (i) the Institute of Chartered Accountants of India (ICAI) has formed a committee to create a roadmap for the convergence of Indian accounting standards with International Financial Reporting Standards by end-2008;. (ii) SEBI formed a Committee on Disclosures and Accounting Standards in late 2006
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Volume 3 ISSN 0975-0746 to advise on disclosure requirements for listed companies and to facilitate the implementation of ICAI accounting standards as they relate to the capital markets; (iii) A code of corporate governance is being developed for public-sector enterprises (both listed and unlisted); (iv) On 10 July, 2007, SEBI issued an amendment to Clause 41 of the listing agreement, which deals with quarterly reporting. SEBI has now made it optional for companies to present an either unaudited or audited quarterly result and year to date financial results to the Stock Exchange within one month from the end of each quarter. If the option is for an unaudited result, then the results will be subject to a limited review, and the report will have to be submitted to the Stock Exchange two months from the end of the quarter.
Conclusion The paper has taken an initial step in analysing the backdrop and position of India in respect of corporate governance and its different models. The paper has attempted to provide a broad evaluation of the corporate governance scenario keeping in view the models thereof. Comparing corporate governance in different models can be done from a number of perspectives. Comparisons can overlap with contrasts. The framework addressed here reviews the characteristics of different models. Models are derived from both reality and perception and portray ‗ideal types‘, i.e., they correspond to how things should be according to prevailing ideologies or principles, but not necessarily according to reality in every case. Inevitably, there are variations and distortions. Further studies can be extended to other economies to provide an exhaustive comparison of corporate governance systems in different countries.
Endnotes: 1. ‗Bombay Plan‘ is a memorandum of proposals for the development of the post- independence economy of India. It was authored by a group of leading Indian industrialists and technocrats (Jehangir Ratanji Dadabhoy Tata, Ghanshyam Das Birla, Ardeshir Dalal, Lala Shriram, Kasturbhai Lalbhai, Ardeshir Darabshaw Shroff, Purushottamdas Thakurdas and John Mathai). The Plan went through two editions: the first was published in January 1944. This first edition became ‗Part I‘ of the second edition, published in two tiny pamphlet-sized volumes in 1945 by Penguin under the editorship of Purushottamdas Thakurdas as A Brief Memorandum Outlining a Plan of Economic Development for India. It was meant as a fifteen year investment plan for India. The aim of the Bombay Plan was to attain in fifteen years time, ‗a general standard of living which would leave a reasonable margin over the minimum requirements of human life.‘ (The ‗Bombay Plan‘ for India‘s Economic Development, Bombay, The Commercial Printing Press, 1944, p.7). The strategy of the government's first three five year plans after independence was very similar to that of the Bombay Plan. [See, for example, Krishna (2005), Kudaisya (2003)] 2. The Cadbury Report, titled Financial Aspects of Corporate Governance and published in 1992, was issued by the Committee on the Financial Aspects of Corporate Governance chaired by Sir Adrian Cadbury. The committee was set up in May 1991 in response to concerns about the perceived level of low confidence both in financial reporting and the ability of auditors to provide safeguards, particularly in light of the BCCI and Maxwell cases. The recommendations of the report were enshrined in a Code of Best Practice on corporate governance. 3. In the wake of the Enron scandal, the UK Government asked Derek Higgs – an experienced corporate financier and non-executive director – to look at the role and effectiveness of non-executive directors in Britain. This was part of the Government‘s 50 | Business Perspectives
Volume 3 ISSN 0975-0746 response to the (mainly US) corporate scandals which had rocked the global economy – the non-executive director having a vital role in monitoring and controlling executive excess, incompetence and fraud. Review of the Role and Effectiveness of Non-Executive Directors (or the ‗Higgs review‘) was the resultant report published on 20 January 2003. It reviewed the role and effectiveness of non-executive directors and of the audit committee, aiming at improving and strengthening the existing Combined Code on Corporate Governance. 4. The Sarbanes–Oxley Act of 2002, aka the ‗Public Company Accounting Reform and Investor Protection Act‘ (in the Senate) and ‗Corporate and Auditing Accountability and Responsibility Act‘ (in the House) and commonly called SOX is a Federal Act passed by U.S. Congress in 2002 to protect investors from the possibility of fraudulent accounting activities by corporations. The Sarbanes-Oxley Act mandated strict reforms to improve financial disclosures from corporations and prevent accounting fraud. The Sarbanes-Oxley Act was passed in the wake of a myriad of corporate scandals. What these scandals had in common was skewed reporting of selected financial transactions. For instance, companies such as Enron, WorldCom and Tyco covered up or misrepresented a variety of questionable transactions, resulting in huge losses to stakeholders and a crisis in investor confidence. The Act was drafted by Senator Paul Sarbanes and Representative Michael Oxley. The intent of the Sarbanes-Oxley Act is to protect investors by improving the accuracy and reliability of corporate disclosures made pursuant to the securities laws, and for other purposes. The Sarbanes-Oxley Act created new standards for corporate accountability as well as new penalties for acts of wrongdoing. It changes how corporate boards and executives must interact with each other and with corporate auditors. It holds the CEOs and CFOs accountable for the accuracy of financial statements. The Act specifies new financial reporting responsibilities, including adherence to new internal controls and procedures designed to ensure the validity of their financial records. It requires all financial reports to include an internal control report. This is designed to show that not only are the company‘s financial data accurate, but the company has confidence in them because adequate controls are in place to safeguard financial data. 5. In addition to mandatory requirements, Clause 49 provides a list of non- mandatory requirements, which promotes governance practices such as creating a board level remuneration committee, training for board members, conducting board member evaluations and establishing whistle blower mechanism.
References: 1. Aoki, Masahiko (1995). ‗Controlling Insider Control: Issues of Corporate Governance in Transition Economies‘ in Masahiko Aoki and Hyung–Ki Kim (eds.), Corporate Governance in Transitional Economies : Insider Control and the Role of Banks, EDI, World Bank. 2. Confederation of Indian Industry (1998). Desirable Corporate Governance – A Code, Confederation of Indian Industry, Delhi. 3. Goswami, Omkar (2000). ‗The Tide Rises, Gradually: Corporate Governance in India‘, paper for presentation at the Informal Workshop held on 3-4 April 2000 at OECD Headquarters, Paris. 4. Krishna, Ananth V. (2005), ‗Globalization and Communalism: Locating Political Discourse in the Context of Liberalization‘, in Ram Puniyani (ed) Religion, Power and Violence: Expression of Politics in Contemporary Times, New Delhi: Sage, pp. 44-67. 5. Kudaisya, Medha M. (2003), The Life and Times of G. D. Birla, Oxford University Press, New Delhi, 2003. 6. Lokanathan, P.S. (1935). Industrial Organization in India, George Allen & Unwin Ltd., London.
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Volume 3 ISSN 0975-0746 7. Mukherjee Reed, Ananya (2002). ‗Corporate Governance Reforms in India‘, Journal of Business Ethics, 3. 8. Mukherjee Reed, Ananya and Darryl Reed (2004). ‗Corporate Governance in India: Three Historical Models and Their Development Impact‘, in Darryl Reed and Sanjoy Mukherjee (eds.), Corporate Governance, Economic Reforms, and Development: The Indian Experience, Oxford University Press, New Delhi, pp. 25-63. 9. National Council for Applied Economic Research (NCAER) (1959). The Managing Agency System, Asia Publishing House, Bombay. 10. Nigam, R.K. (1957). Managing Agencies in India, Govt.of India, Ministry of Commerce & Industry, Deptt. of Company Law Administration. 11. Reed, Darryl (2002). ‗Corporate Governance Reforms in Developing Countries‘, Journal of Business Ethics, 3. 12. Sarkar, S. (1983). Modern India, Macmillan India, New Delhi. 13. Sen, Amartya (1998). ‗Theory and Practice of Development‘, in I. J. Ahluwalia and I. M. D. Little (eds.), India’s Economic Reforms and Development : Essays for Manmohan Singh, Oxford University Press, Oxford. 14. Sengupta, N.K. (1975). Changing Patterns of Corporate Management, VikasPublishing House Pvt. Ltd., Delhi. 15. Sharma, M. K. (1989). Business Environment in India, Commonwealth Publishers, New Delhi. 16. Som, Lalita S. (2006). ‗Corporate Governance Codes in India‘, Economic and Political Weekly, 30 September. 17. Thakurdas, Purushottamdas, ed. (1945). A Brief Memorandum Outlining a Plan of Economic Development for India (2 vols.), London: Penguin.
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Volume 3 ISSN 0975-0746 A BRIEF HISTORY OF POWERLOOM INDUSTRY IN WEST BENGAL: A STUDY
Uttam Paul Assistant Professor, Sreegopal Banerjee College, Bagati, Mogra, Hooghly, West Bengal & D. N. Konar Professor, Depertment of Commerce, Kalyani University, West Bengal
Abstract One of the most essential commodities of civilized human beings is the cloth and it comes from the textile industry. The textile industry in India has been classified into three sectors: pre-weaving i.e. spinning, weaving and post-weaving i.e. finishing. The powerloom industry is a weaving sector and an important segment of the decentralized cotton textile industry in India. Powerloom industry weaves grey cotton by power-operated machines or looms and works into a fabric with the help of warp in the form of beam and weft directly through bobbins. Beams come from processing mills and weft yarn from spinning mills. Spinning mills produce only yarn / thread as raw materials to the powerloom industries. Processing mills prepare warp in the form of beam and the powerloom industry used the beams for weaving the projected cloths. So it is clear that the powerloom industries are functioning the middle level work in the cloth production. According to the demand of time, powerloom industry in West Bengal has been classified as organized sector and small scale unorganized sector. These looms mostly produce course / medium count dhuti, saree, markin, long cloth, tikkin cloth etc. Some of these looms also produce polyester blended fabrics. This sector is one of the most important segments of the textile industry in terms of fabric production and employment generation. It provides employment to 48.60 lakh persons and contributes 62 % to total cloth production in the country. The government of West Bengal believes that handloom and powerlooms economies can and should harmoniously co-exist since both have distinct markets, focus areas and space for future growth. It shall be the policy of the government to encourage a liberal yet harmonious.
Keywords: Powerloom industry, handloom sectors, West Bengal, descriptive statistics, trend value.
Introduction: One of the most essential commodities of civilized human being is the cloth and it comes from the textile industry. Textile and their products constitute the second largest industry in the world, just ranking below the food products. Textile Industry in India has classified in to three sectors: pre-weaving i.e. spinning, weaving and post-weaving i.e. finishing. In this sense, the power loom industry is a weaving sector and the important segment of the decentralized cotton textile industry of our country. Power loom industry is the industry, which, in general, weaves gray cotton by power-operated machine or loom. Such looms work into a fabric with the help of warp in the form of beam and weft directly through bobbins.
Review of literature: There is no authentic and huge number of literatures about this area but some literatures are there, which are helpful for the study and research 53 | Business Perspectives
Volume 3 ISSN 0975-0746 purposes, some such references are Book India 2006 a reference annual compiled and edited by research, reference and training division, Ministry of Information and Broadcasting, Govt. of India. West Bengal Human Development Report, Development and Planning Dept; Govt. of India, first published in may 2004, India Year Book 2004, Institute of Applied Manpower Research, Textile Souvenir-1981-82, Textile Souvenir-1984, 1986, Yojana-Dhanadhanye- June & July-2007, Tex Vision-2008, The Kolkata Gazette-2008, Govt. of West Bengal, Encyclopedia of Textile, ―Tantu O Rang‖- A book of Textile Technology – basu, T.N., Majumder, Dipak, ―The issue of small versus large in the Indian Textile Industry‖, Govt. of West Bengal: Report of the Power loom Enquiry committee- 1967, Schemes and Initiatives for the Development of the Textile Industry, Govt. of India,West Bengal Economy- present, past and future-basu, kalipada,etc.
Methodology and sources of data: Most of the data which have been used in the present study are primary and some are, of course, secondary. The economic parameters have been analyzed with the help of the statistical tools like mean, median, mode, standard deviation (SD), correlation coefficient (r) etc. as the situation demands. Primary data are collected through convenient sample survey. One basic limitation of the study is the lack of availability of sufficient data. I have tried my level best to make the data as current and accurate as possible.
Objectives: The following are the objectives of the study: i. To discuss the revolution of small scale powerloom industry in West Bengal; ii. To evaluate the growth pattern of small scale powerlooms in West Bengal; iii. To highlight the production of these industries in West Bengal as well as cost of production; iv. To suggest some line of actions that may be necessary for an overall improvement this sector, and v. Making concluding remarks.
Sampling pattern: The small scale powerlooms in West Bengal are seen mainly in 11 districts.These are Nadia, Burdwan, Hooghly, North 24 Parganas, South 24 Parganas, Howrah, Midnapur (E+W), Uttar Dinajpur and Purulia. I have visited all the districts in West Bengal where small scale powerlooms have been installed and surveyed at randam 500 workers in 72 powerloom factories where about 800 powerlooms have been installed. This data are collected through convenient sample survey.
Powerloom: Edmund Cartwright of England invented the powerloom and the comber frame in 1774. In 1785 he received his second set of patents for his further inventions on the powerloom. At this time he brought out the warp –stop motions on a loom.
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Volume 3 ISSN 0975-0746 As per the Cotton Textiles (Control) Order 1948, ―Powerloom‖ means a loom which is worked by power as defined in Section 2 (g) of the Factories Act. 1984.
Powerlooms in use: 1) Plain loom; 2) Box loom; 3) Dobby loom; 4) Double Cylinder; 5) Jacquard loom; 6) Leno or Doup loom; 7) Lappet loom; 8) Swivel or Clip- Spot loom; 9) Pile fabric looms; 10) Indian type loom.
Weaving Process: A simplified explanation of the weaving process involves the following steps: 1. The warp yarn is wound on a beam. All the threads are arranged parallel to each other. Often they are sized to give them strength. 2. From the warp beam the threads are led over a whip roll, under and over the lease rods, through the eyes of the needles, and then through the splits or points of the reed. This makes it possible to manipulate the various warp threads according to a pre-arranged design plan. 3. As the warp yarns are manipulated, they are separated into two layers, creating an opening called ‗shed‘. Through this shed a shuttle carries the filling yarn. 4. After the filling yarn has passed through the shed, it is beaten into the place by the reed which has a to - and- fro action. 5. As the fabric is woven it is wound around a cloth roller.
Powerloom Industry: Powerloom industries are the industries, which, in general, weave grey cotton by power-operated machines or looms. Such looms work into a fabric with the help of warp in the form of beam and weft directly through bobbins. Beams come from processing mills and weft yarn from spinning mills. Spinning mills produce only yarn / thread as raw materials to the powerloom industries. Such threads are stretched out lengthwise in a loom to be crossed by a woof (weft). This comes through the processing mills and from processing mills the warps in the form of beams are used in the powerloom industries just to weave the projected clothes. These clothes after calendaring through processing mills take the form of finished goods of such industries. It is quite clear that the powerloom industries function in the middle level of work to produce a cloth in its finished form.
Revolution of Small Scale Powerloom Industry in West Bengal: There is no authentic record to indicate the first introduction of powerloom in our country but there is evidence for the existence of powerloom in
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Volume 3 ISSN 0975-0746 India during the Second World War. The powerloom industry started its productions in the early part of the last century when some handloom weavers set up small factories with second hand non-automatic looms sold-off by the mills. But the rapid growth of the powerloom industry in India is really a post- 1950 phenomenon. The Small-Scale Powerloom Industry in West Bengal (SSPIWB) has been traced to the initiative taken by the handloom weavers to switch over to powerlooms. In 1948, Mr. Brojagopal Basak, the owner of Ranaghat Textile Mills, first set up 4 (four) powerlooms under the separate name of ― Tantushilpa Pratishtan‖ at Ranaghat, Nadia and another pioneer Mr. Atul Paul, the proprietor of United Spinning and Weaving Mills had installed 5 (five) powerlooms at Ranaghat, Nadia in 1950. Initially, these powerlooms were run by power from diesel generators. The availability of power from 1954 led to the expansion of power looms in decentralized sector in near by centers of Nadia district. When the oldest handloom industry in the country plunged into a tremendous crisis in 1952, the Government of India appointed a Textile Enquiry Committee with Shri Nityananda Kanungo as chairman to look into the affairs of the mills, and both handlooms and powerlooms in India. This committee made certain recommendations with regard to the three sectors of the textile industry. The Kanungo Committee also laid down the scheme for conversion of handlooms into powerlooms as the powerlooms were found to be more profitable in comparison with handlooms. In West Bengal, this industry has an especial importance. After independence a large number of Bengalee refugees from former East Pakistan come over to West Bengal and settled here. Dr. Bidhan Chandra Roy, the then honorable Chief Minister of West Bengal, formulated a number of schemes for economic rehabilitation of the refugees. Revitalization and extension of powerloom industry was one of these schemes chalked out for the economically uprooted people coming from east while East Pakistan (now Bangladesh). The Refugee Relief and Rehabilitation Department, Govt. of India, issued permits for the installation of units of four powerlooms to these persons only on the recommendation of the Government of West Bengal for the purpose of their economic rehabilitation. These permits were issued on such condition that the refugee workers were to be employed in the country. Under this scheme, 4000 powerlooms were installed in West Bengal. Meanwhile, the Government of India took a policy of bringing these establishments into co-operative sector. The Kanungo Committee indicated in the report that in the long run these co- operative societies would be gradual shrinkage of employment in the handloom sector. For maintaining the level of employment, the Kanungo Committee considered that the handlooms should be replaced by powerlooms ultimately and accordingly recommended small-scale powerloom industry to avoid the crisis that facing the handloom industry. Again, the committee also proposed certain specific measures of financial assistance. There after, about 1600 powerlooms in West Bengal come into existence under the co-operative sector in 1960-61 and these 1600 powerlooms were controlled by 100 co-operative societies each considering of 16 power- looms. Government of West Bengal tried to develop these societies with grants and low interest banking loans.
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Volume 3 ISSN 0975-0746 In 1963, the Government of India again appointed a committee under the chairmanship of Shri Ashoke Mehta to enquire into the affairs of the powerloom industry which had already come in to existence. The Mehta Committee observed that the policy with regard to setting up the powerlooms in clustered area as per recommendation of the Kanungo Committee did not meet with full success due to insufficient financial assistance provided for working capital, imposition of condition for installing powerloom in rural areas with a population of less than 30000, absence of facilities for preparatory, processing and finishing arrangement in rural areas and absence of arrangement to ensure distribution of financial benefits amongst all members of the co-operative societies. Thus the co-operative movement in powerloom sector of West Bengal failed to flourish. As a result, in 1988, only about 33 co-operative societies were working and in the year 2005-06 there were 40 power loom co-operatives but out of which only 18 co-operative societies were active in production with the help of ‗agent financer‘. Agent financer is a class of traders who have required amount of capital, business experience, control on marketing channel and entrepreneurship, but with out production apparatus, i.e. powerlooms in this case. They come forward with their resources and entered into an agreement with the societies, perhaps not in writing anywhere, that they would supply sized beams and get fabrics woven in the factories of the societies. In return, the societies are being paid certain amount as remuneration. Under the Refugee Relief and Rehabilitation Scheme, the Central Government established different loom shades throughout India in the name of Rehabilitation Industries Corporation (RIC). In West Bengal, only two shades – one at Taherpur, Nadia and another at Bonhooghly, Baranagar, Kolkata set up consisting 75 powerlooms. All the powerlooms under RIC were installed in 1968 but were closed soon after the year 1974. From the year 1972 and onward, the Government of India nationalized totally 14 composite sick mills as National Textile Corporation (NTC) for West Bengal jurisdiction. These composite mills consisted nearly of 10,000 powerlooms. At present, most of them are closed. These sick composite mills and co-operative societies sold their scrapped looms at a minimum price. Besides, a few number of scrapped looms from other states, e.g. Gujrat, Maharastra, Bihar etc. entered in to West Bengal as small-scale sector. Mainly the handloom weavers of West Bengal got the chance of conversion of their handlooms into power looms at a minimum cost. In this way the small scale power loom industry in West Bengal came in to existence.
Role and Importance of Powerloom Industry: In textile industry, West Bengal was the pioneer in India. The first cotton mill named Fort Gloster Mills was set up in 1818 at Howrah, West Bengal– presently known as Bowreah Cotton Mills Co. Ltd. The first jute mill was set up at Rishra in Hooghly district of West Bengal in 1855 and the first cotton hosiery Oriental Hosiery Ltd. was established in 1833 at Khidirpur, Kolkata and the Belting and String Industry was also first established in West Bengal. Thus the spinning mill, weaving mill, jute mill etc. were first established in West Bengal and once the state reached a stage of first bench level in cotton textile industry in India. The powerloom industry also took a place of its own in the Indian textile
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Volume 3 ISSN 0975-0746 market. But unfortunately, due to some constraints the power loom industry in West Bengal had lost its prime position in the textile industry in India. When competition was not so tough, the powerloom industry of West Bengal had a ready market in Bihar, Madhya Pradesh, Assam etc. It can not be gainsaid that these days Maharastra, Tamil Nadu, Bihar and Orissa have captured the present market of textile industry almost every year. However, the produced articles of the powerloom industry of West Bengal, particularly dhuties, sarees, lungies, chadar, bed sheet, marking etc. were used by the rich as well as poor families as they were comparatively cheap. The number of the registered unemployed in our country is more than the total number of population in Australia or Ethiopia or Burma. If a queue (for every metre) is formed by those unemployed, its length would be 8,750 kilometres (of which 1250 kilometres is allotted for West Bengal) and the queue length is increasing by one kilometer per hour or in every second at least one is enrolling his / her name in the registered book of unemployment in our country. In fact, the total number of the unemployed is more or less 2.3 times the registered unemployed. At present; West Bengal ranks the remarkable position in the number of the unemployed. Under such alarming condition of unemployment in West Bengal, the powerloom industry offers gainful employment to thousands of people either as purely workers, or as purely owners or both in capacity. Moreover, the powerloom industry contributes a lot of revenues to the Government exchequer by way of Central Excise on cloth, Income Tax, Sales Tax etc. It also helps to earn some foreign exchange by exporting a few quantity of export quality of output.
Growth Pattern of Small Scale Powerlooms in West Bengal: Powerloom is the machine of weaving a cloth. In India, as a whole, the powerloom sector among other sectors has been producing most cloth till today. But in West Bengal, production of cloth by handloom scores top position, powerlooms scores second position and mills scores third position. At present, there are about 6089 powerlooms in West Bengal and 40 powerlooms co- operatives, out of which only 18 co-operatives are working, only 658 powerlooms are working under co-operatives society. During the year 2005-06, annual production of this sector is estimated to be 152.90 million metres. These looms mostly produce course / medium count dhuti, saree, markin, long cloth, tikkin cloth etc. Some of these looms also produce polyester blended fabrics. Most of these looms are running on job work basis for pan city of working capital and adequate marketing facilities.As per the statement of Economic Review 2006-07, Govt. of West Bengal, there are about 6089 Powerlooms in West Bengal during the year 2005-2006. But only 4876 Powerlooms are working at present in West Bengal, out of which 658 Powerlooms are working under co-operatives society. So, 1213 powerlooms are either out of order or have been closed by the weavers. (Source: Economic Review 2006-07, Govt. of West Bengal.)
Ownership Pattern of Small Scale Powerlooms in West Bengal: It has been mentioned earlier that small-scale power looms in West Bengal had been first installed by Mr. Broja Gopal Basak at Ranaghat, Nadia. It was the individual proprietary entrepreneurship installation. In the later time, it
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Volume 3 ISSN 0975-0746 had not been in the grip of only proprietary ownership. So, now we would like to discuss the ownership pattern of power looms in the Small Scale Sector of West Bengal.
Table 1: Ownership Pattern of Small Scale Powerlooms in West Bengal Ownership No. of Powerlooms Percentage (%) Proprietary 734 91.75% Partnership 16 2.00 % Co-operative 50 6.25% Total 800 100.00 Source: Field Investigation
The Table 1 reveals that out of 800 Powerlooms, 91.75% i.e. 734 powerlooms are in proprietary entrepreneurship, only 2% i.e. 16 powerlooms are in partnership and 6.25% i.e. 50 powerlooms are in the hands of co-operative societies. In case of individual ownership, if a owner have more than 4 or 5 units, he or she tactfully transferred ownership to some other person may be spouses or close relatives for ignoring large pattern of ownership setup, worker‘s movements regarding wages etc. In the case of partnership firms, whether these firms are registered as such or not have not been disclosed by the firm owners. But most of the co-operative societies are converted in to worker‘s co-operatives at present though these had been set up by the owner‘s co-operatives societies.
Age distribution of Looms: As a general rule, there is a negative relationship between the production and the age of the looms, or they move in the opposite direction i.e. as the age of a powerloom increases the productivity of that powerloom decreases. So every loom has to be properly lubricated and cleaned and a significant amount is to be spent every year for maintenance of looms. Consequently, the selling prices of products increase due to the increasing cost of production and hence, it has a negative effect on marketing. Data in Table 2 show the age distribution of the looms set up in the small scale sector in West Bengal.
Table 2: Age Distribution of Powerlooms in West Bengal Age (in year) No. of Looms Percentage (%) Up to 5 8 1.00 5-10 20 2.50 10-15 68 8.50 15-20 104 13.00 20-30 184 23.00 30-40 328 41.00 Above 40 88 11.00 Total 800 100.00 Source: Field Investigation as on the year 2006-07
It is observed from Table 2 that out of 800 powerlooms, 328 looms (41%) are 30 to 40 years old and only 8 (1%) looms were set up in the last 5 years. As 59 | Business Perspectives
Volume 3 ISSN 0975-0746 per field study, it is learnt from the respondents that they prefer to purchase discarded looms at a minimum cost from the secondary sources, mainly sick composite mills, co-operative societies, brokers of second-hand machines and after major overhauling, they installed these looms in their own shades. The loom owners admit that the looms require significant maintenance charges every year and frequent breakdown of machines is a regular phenomenon. It is fact that due to high prices of new looms and non-availability of funds they cannot purchase looms of the latest technology (the price being more or less 2.5 to 4 lakh). In the office of the Deputy Directorate of the Powerloom Servicing centre, the Govt. of India at Millpara, Ranaghat, Nadia, there are three powerlooms of the latest technology, lying for specimen purpose and sometimes used for special training to the weavers.
Year- wise total production in Powerloom sector in west Bengal:
Table 3 - Year- wise total production in SSPIWB Quantity Quantity (in Million Metres/ Year Year (In Million Metres) * in Million Sq. Metres. 1981-82 190.00 1994-95 160.00 1982-83 190.00 1995-96 172.00 1983-84 190.00 1996-97 76.72 * 1984-85 192.00 1997-98 77.99 * 1985-86 190.00 1998-99 78.05 * 1986-87 192.00 1999-00 78.18 * 1987-88 194.00 2000-01 77.74 * 1988-89 194.00 2001-02 78.72 * 1989-90 196.00 2002-03 79.75 * 1990-91 144.00 2003-04 80.07 * 1991-92 150.00 2004-05 80.18 * 1992-93 155.00 2005-06 80.87 * 1993-94 159.00 2006-07 81.18 * Source: Data for 1981-90 – West Bengal State Annual Plan Different Issues, Govt. of West Bengal.,Data for 1991-96 – Office records, Deputy Directorate, Powerloom,6 Church Lane, Kolkata-1 (Now changes the address),Data for 1996-2007- Office records of Deputy Directorate of Handloom and ,Textile, Govt. of West Bengal, Powerloom Sector C – Block (4th Floor), New Secretariat Building, No. 1 K.S Roy Street, Kolkata * Note: - Data of production for the year 1981 to 1996 are in unit million metres. But the data for the year 1997 to 2007 are in unit million square metres.
The Table-3 shows that from the year 1981-82 to 1995-96 it is observed that the highest quantity of production of 196 million metres was achieved in 1989-90 when the number of powerlooms in decentralized sector was 3941 (Table-2.6) and the lowest quantity of production of 144 million metres was achieved in 1990-91 when the number of powerlooms was 5030. Again, in the year 1996-97 to 2006-07 it is found that the production of cloths in SSPIWB gradually increased from the year 1996-97 to the year 1999-2000, but in the year 2000-01 it slightly decreased as compared to the previous year . Again, from the year 2001-02 the production increased, but not sufficient for the smooth running of the industry. 60 | Business Perspectives
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Table: 4 - Year- wise total production in SSPIWB and Exponential Trend value (From the year1981-82 to 1995-96) Year Quantity (In Million Metres) Trend Value 1981-82 190.00 140.28 1982-83 190.00 137.91 1983-84 190.00 135.58 1984-85 192.00 133.29 1985-86 190.00 131.04 1986-87 192.00 128.83 1987-88 194.00 126.65 1988-89 194.00 124.51 1989-90 196.00 122.41 1990-91 144.00 120.34 1991-92 150.00 118.30 1992-93 155.00 116.31 1993-94 159.00 114.26 1994-95 160.00 112.41 1995-96 172.00 110.51 Note: Exponential Trend value calculated by the method of Least Squares.
Table: 5- Year- wise total production in SSPIWB and Exponential Trend value (From the year 1996-97 to 2006-07): Year Quantity (in million metres) Trend Value 1996-97 76.72 73.84 1997-98 77.99 74.85 1998-99 78.05 75.88 1999-2000 78.18 76.91 2000-01 77.74 77.97 2001-02 78.72 79.03 2002-03 79.75 80.11 2003-04 80.07 81.21 2004-05 80.18 82.32 2005-06 80.87 83.45 2006-07 81.18 84.59 Note: Exponential Trend value calculated by the method of Least Squares.
Line Diagram showing combined Exponential Trend of production (From the year 1981-82 to 2006-07)
Line Diagram The Line Diagram on the basis of annual production data shows broadly three phases- gradual rising, sharp falling, and again gradual rising. From the
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Volume 3 ISSN 0975-0746 year 1981-82, the annual production more or less had risen up to the year 1989- 90 and suddenly it had fallen in the next year 1990-91. Again, it rose from the year 1991-92 up to 1999-2000. In the year 2000-01 the annual production had fallen, but from the y ear 2001-02 it had risen up to the year 2006-07. It is to be noted that the quantity of production during 1981-84 remained the same and it fluctuated in other years. Another point is that if we consider 1989-90 as the base year when the quantity of production was 196 million metres (maximum) by 3941 power- looms, then it should be proportional to other year. But the actual quantities of production of other years did not reach up to the mark. The disparity in quantities of production in other years probably happened due to the idleness of so many powerlooms. The causes of idleness, according to the powerloom owners in small scale sectors were short supply of raw materials, lack of market, havoc power cut and so on. So we can conclude that the graphical representation of trend values in the Diagram clearly shows that from the year 1981-82 to 1995-96 there is a declining trend of production, but from the year 1996-97 to 2006-07 it is an increasing trend of production of cloths in SSPIWB.
Weaving Cost: The weaving cost relating to an agent financer and a loom owner (whether independent or pick party) are different. The weaving cost of an agent financer is determined by the pre- determined rates which vary according to the type of fabrics, variety of cloth, pick at which the cloth would be woven, the carrying charge and even the bargaining capacity of the agent financer and the pick party (loom owner). If the agent financer wishes to have woven cloth from ‘Ranaghat’, the pick rate at the current price is Rs.23.50 for 9 yards 27 inches long dhuti. Thus, the weaving cost at the current price of the product is Rs. (23.50 x 40 /100) = Rs. 9.40 per pair. Again the pick rate at the base period for the same product is Rs.19.50. Then the weaving cost to the agent financer for the product is Rs. (19.50 x 40 / 100) = Rs. 7.80. But the calculation of the weaving cost to powerloom owners is too much complicated. This requires considering all the elements related to weaving cloths as a whole. For this purpose, we assume the following: 1) The power loom owner has eight power looms under a single shed. 2) All the looms work in three shifts per day 3) Each loom is operated during the month for the same product. 4) One operator (weaver) operates two looms at the same working hours. 5) A jobber looks after all the power looms under the shed. 6) One winder winds all the bobbins required by the looms during the shift. 7) The motors attached with the looms are operated by electricity (power) supplied from a single meter box. Under the same set of assumptions, the monthly weaving cost has been calculated.
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Volume 3 ISSN 0975-0746 Table: 6: Weaving Cost per month to a power loom owner: (For 8 looms and 3 shifts per day) At current At Base period Particulars period (Rs.) (Rs.) 1) Weavers‘ Wages 11,275.00 10,044.00 2) Jobbers‘ Wages 2,200.00 1,900.00 3) Winders‘ Wages 1,575.00 1,325.00 4) Drawer & Reachers‘ Wages 320.00 240.00 5) Checkers‘ wages 210.00 180.00 6) Electrician & Carpenters‘ wages 150.00 125.00 7) Power & Electricity 4,300.00 3000.00 8) Stores 3,100.00 2,200.00 9) Depreciation of Looms, Rent / 300.00 300.00 Depreciation of Factory building Total 23,430.00 19,314.00 Source: Primary data (considering 12 factories where we have seen the production of said product and each particular 1 to 9 has been taken as average).
Table: 7: Cost Sheet for a month : (Out put = 3116 Pairs Per Month) Item of Cost Agent Financer Independent Owner Pick Parties Base Current Current Base Current Base period (Rs.) Period (Rs.) period (Rs.) Period (Rs.) period (Rs.) Period (Rs.)
1) Material 1,77,019.96 1,87,645.96 1,77,019.96 1,87,645.52 2) Pre- weaving 14,863.32 10,282.80 14,863.32 10,282.80 cost 3) Weaving 29,290.40 24,304.80 23,430.00 19,314.00 23,430.00 19,314.00 cost 4) Post- 22,840.28 19,256.88 22,840.28 19,256.88 weaving cost 5) Admt. 1,850.00 * 1,700.00 * 2,400.00 2,150.00 1,140.00 900.00 Cost Cost of 2,45,863.96 2,43,190.00 2,40,553.56 2,38,649.20 24,570.00 20,214.00 Production 6) Selling& 6,232.00 4,985.60 6,232.00 4,985.60 Dis. cost 7) Other 1,445.00 * 1,650.00 *** 4,212.00 3,702.00 2,976.00 2,572.00 Costs Cost of 2,53,745.96 2,50,997.55 2,47,336.80 27,546.00 22,786.00 Sales 2,49,620.60 Note: * Assuming lower than Independent Owner because of economy in large sized production. ** Excluding part of Annual Bonus. 63 | Business Perspectives
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Comparative cost of processed fabrics in relation to Mill and Handloom sectors: Table: 8: Comparative Cost of processed Fabrics in relation to mill and handloom sector Sl. No. Cotton Fabrics Mill Powerloom Handloom 1 Drill 100 95 96 2 Sheeting 100 93 96 3 Long Cloth 100 93 98 4 Shirting 100 94 110 5 Dhoti 100 91 108 6 Mill 100 89 103 7 Cambric 100 95 120 8 Poplin 100 93 105 9 Suiting 100 94 95 Source: K. Rang Nathan. Et.al. ―Sectoral Cost of Production‖ in ATIRA, Rehabilitation of the Textile Industry, Ahmedabad 1985.
The comparative costs of processed fabrics in relation to mill sector exhibit clearly that the sorts of cloth, especially cotton fabrics, are essential for the existence of the poorer section of our society.
Conclusion: West Bengal has a very small powerloom base with barely 6089 powerlooms (2005-2006) (All India 18.36 lakh) operating in small clusters in the district of Nadia, Howrah, Kolkata and North 24 Parganas and producing around 81.18 million sq. mtrs of cloth (All India 30,254 million sq. mtrs). Most powerlooms in West Bengal are technologically outdated needing modernization of varying degree. The sectoral vision for powerlooms in the state would be to take the active powerloom number in West Bengal to 20,000 and enhance the powerloom output by at least 300% to reach 180 million meters by 2014. To achieve the sectoral vision, the government shall facilitate setting up of three powerloom parks in public-private partnership with comprehensive common support infrastructure, including common facilities for fabric dyeing, processing and finishing. In order to facilitate modernization of powerlooms including induction of shuttle less and airjet and waterjet looms, Government shall encourage entrepreneurs to avail assistance under Technology Up gradation Fund Scheme (TUFS) and other similar schemes. Government shall also encourage increased use of manmade/ synthetic fibers on powerlooms in the State as synthetic fibre manufacturing is taking deeper roots in the State. The government of West Bengal believes that handloom and powerlooms economies can and should harmoniously co-exist since both have distinct markets, focus areas and space for future growth. It shall be the policy of the government to encourage a liberal yet harmonious.
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Volume 3 ISSN 0975-0746 References: 1. Awachat, Anil ―The warp and the weft‖ – I & II, Economic and Political Weekly, Vol. XXIII No. 34. August 20, 1988 and Vol. XXIII No.35, August 27, 1988. A Sameeksha Trust Publication. 2. Balogh, Thomas. (1987) ‗Economics of Poverty‘, MacMillan, New York, 1966. 3. Bandapadhay, B. (2004 ‗Karbar Niyantraner Ruporekha,’ Rabindra Library, Kolkata. 4. Bedi Jatinder, S. (2002) ‗Economic Reforms and Textile Industry: Performance and Prospects, Commonwealth, New Delhi. 5. Datt, Ruddar and Sundharam (1981) ‗K.P.M. Indian Economy‘, S. Chand & Company Ltd., New Delhi. 6. Das, N.G. (1984) ‗Statistical Methods‘, M. Das & Company, Kolkata, 1984. 7. Gupta, K. Shashi. Sharma, R.K. (2005) ‗Management Accounting, Principles and Practice‘, Kalyani Publishers, New Delhi. 8. Guho, S.P. & Roy, P.K. (2005) ‗Entrepreneurship Development and Business Communication simplified‘, New Deys Publishers, Kolkata. 9. Konar, D.N, (2004) ‗The scenario of population growth in India‘, Akansha Publishing House, New Delhi. 10. Michael, V.P. (1984),’Industrial Relations in India and Workers Involvement in Management‘ Himalaya Publishing House, Mumbai. 11. Ramaswamy, E.A. (1988) ‗Worker Consciousness and Trade Union response‘, O.U.P, New Delhi. 12. Singh, U.B. (1973) ‗Wage Patterns, Mobility and Savings of Workers in India: A Study of Kanpur Textile Industry, Lalvani Publishing House, Mumbai. 13. http//www.cotti.in 14. http//www.tradeindia.com 15. http// www.pdexcil.org
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Volume 3 ISSN 0975-0746 GROWTH PERFORMANCE-A COMPARATIVE STUDY BETWEEN SBI AND ICICI BANK
Amalendu Bhunia Associate Professor, Department of Commerce, University of Kalyani, West Bengal & Prasanta Saha Assistant Professor, Department of Commerce, Puras Kanpur Mahavidhyalaya, Howrah, West Bengal
Abstract The paper contrasts the growth performance of SBI and ICICI for the period from 2003 to 2012 using secondary data with the application of descriptive methods of statistical analysis including multiple regressions. In view of the fact that the growth of the banking sector (deposits mobilization, advances deployment, bank branches, interest and non- interest margin, operating expenses and net profits) is straightforwardly connected to the economy but it is estimated to have slow down remarkably because of ongoing crisis in Europe and economic slow down in the United States. Descriptive statistics shows that the growth of ICICI bank is more satisfactory than SBI under the study except deposit mobilization and operating expenses and multiple regression test results indicate that the growth of profits rely on bank branches, interest and non-interest margin in case of both the banks under the study.
Keywords: Growth performance, banks, SBI, ICICI, descriptive statistics, multiple regressions
1. Introduction Generally, growth is an increase, as in size, number, value or expansion of an organisation. Growth of a banking business means an increase in the business over a period of time in the areas of deposits, advances, bank branches, interest and non-interest margin, operating expenses, and net profits etc. of the current year in comparison to previous year (Pathak, 2011). Nonetheless, growth analysis of a bank is a technique of intriguing models on distinct intervals as well as determining the development patterns. Gupta and Sikarwar (2013) argued that growth can be studied from diverse angles similar to sales, net profit, reserve and surplus, earning per share, internal growth & sustainable growth and so on. The recital of the Indian economy is one of the strongest drivers for the banking industry‘s growth and vice versa and the average GDP growth of 8.1 per cent expected over 2011–16 will smooth the progress of the growth of the banking sector (IBEF, 2011). The growth of the banking sector is directly associated to the economy than possibly that of any other sector. The growth of the Indian economy is expected to have decelerated notably from 8.39 percent in the year 2011-12 to 6.88 percent in the year 2012-13 because of ongoing crisis in Europe and economic decelerate in the United States disturbing foreign investments coming into India, policy paralysis considering the government‘s lethargy on diverse policy issues and reforms, fiscal deficit, high inflation leading to high interest rate and rupee depreciation that additionally weakens the current 66 | Business Perspectives
Volume 3 ISSN 0975-0746 account deficit (KPMG report, 2013, p.3). However, the Indian banks observed a mixed trend in their profitability in 2012-13. Despite the fact that the average pre- tax profit of the banks increased by 16.46 percent, the private sector banks significantly outperformed their public sector counterparts (28.38 percent vs. 9.85 percent). In this way, the net interest margin for most of the banks declined apart from SBI and ICICI bank because of higher cost of bulk deposits and a slowdown in the credit growth (KPMG report, 2013, p.6). Keeping in view of this, the present research work examines and evaluated the growth of SBI and ICICI bank as a factor accountable for these banks play an important role in mobilizing the financial savings and deployment of those to the sectors of production.
2. Literature Review Panda and Lall (1991) had identified certain factors which influence the profitability improvement of banks to the great extent. They argued that branch expansion is one of those factors which can impact on profitability. Rammohan and Ray (2004) concluded that with regard to the revenue maximizing efficiency, public sector banks are significantly better than private banks but they found no significant difference between public and foreign banks on this parameter. Kumar (2006) observed that the bank nationalization in India marked a paradigm shift in the focus of banking as it was intended to shift the focus from class banking to mass banking and efforts are also being made internationally to study causes of financial inclusion and designing strategies to ensure financial inclusion of the poor disadvantaged. He argued that the banks also need to redesign their business strategies to incorporate specific plans to promote financial inclusion of low income group treating it both a business opportunity as well as a corporate social responsibilities and financial inclusion can emerge as commercial profitable business. Manoj (2010) argued that enhanced profitability and efficiency has become vital for survival and growth of the banks in the era of globalization and significantly affected by asset quality, capital adequacy and liquidity of the banks. Ghosh (2010) examines the interplay between credit growth bank soundness and financial fragility in Indian banks. The soundness of banks is measured by their distance to default. Loan growth is often directly associated with soundness but an extension could weaken bank soundness. Anjum and Deepika (2012) made a comparative study of the profitability of the Indian Banking Sector and the impact of technological investment on the profitability of the Public and Private Sector Banks. They argued that Indian Banking Industry in technological advancement is still in gestation phase and RBI has to take various steps so that the Public Sector Banks (Nationalized and SBI & its Associates) becomes able to manage their profitability by striking the balance between technological Investments (Expenditures) and Incomes. Ayyappan and Sakthivadivel (2012) found that compound growth rate of the private sector banks is comparatively higher than that of the public sector banks. The banks were grouped into two categories: i.e., Public Sector Banks Group (22 banks) and Private Banks Group (15 banks). Their study predicted that at the current rate of growth the private sector banks can pose a challenge in the market place and may even overtake the public sector banks in the longer period of time. The study does not provide any idea regarding the growth of any individual or
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Volume 3 ISSN 0975-0746 frontline public and private sector commercial banks but the growth picture at macro level. A significant number of studies on performance of banks have already been undertaken. Though profitability and efficiency of the banks have become most fascinating area for study but with the view of growth in economy, the importance of growth in banking sector cannot be ignored. The comparative analysis of growth performance among SBI and frontline new private sector commercial banks as well as growth performance before and after the world economic crisis of 2008 at bank level is an area which has not yet explored. The present study will try to analyze and compare the growth of the largest public sector SBI and the new private sector bank ICICI.
3. Materials and Methods 3.1 Sources of data The study is based on secondary data obtained from annual reports of the particular banks. In addition, the facts, figures and findings sophisticated in related past studies and the government publications are as well used to complement the secondary data.
3.2 Research design Since growth of a banking business means an increase in the business over a period of time in the areas of deposits, advances, bank branches, interest and non-interest margin, operating expenses, and net profits etc. of the current year in comparison to previous year. So we have measured growth rate encircling the absolute information using the sample period extents from 2003 to 2012; nevertheless, there are 9 observations. Eviews 7.0 package program and SPSS have been utilized for coordinating the data and carrying out of statistics and econometric analyses.
3.3 Variable used In the present study, deposits mobilization, advances deployment, number of branches, net interest margin, non-interest margin, operating expenses and net profits have been used to measure the growth performance. Net profits (also treated as profitability indicator) are taken as dependent variable and six main factors that affect the growth performance have been taken as independent variable for the present study.
3.4 Tools used In the course of analysis in the present study, descriptive statistics, correlation statistics and multiple regression statistics have been used. The uses of all these tools at different places have been made in the light of requirement of analysis.
3.5 Hypothesis taken H0: There are no significant differences subsist in growth performance between SBI and ICICI over the period under study. H1: There are significant differences subsist in growth performance between SBI and ICICI over the period under study.
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Volume 3 ISSN 0975-0746 4. Empirical Results and Analysis 4.1 Descriptive statistics Descriptive statistics shows that mean value of ICICI bank in terms of growth indicators are more satisfactory than SBI under the study except deposit mobilization and operating expenses which indicates that growth performance is very pleasing in case of private sector bank than public sector bank in India during the period under study. But in the case of management of growth performance in the area of deposit mobilization, advances deployment, net interest margin and operating expenses, C.V. of SBI is better than ICICI because lower variability is seen in case of SBI. Again, in case of expansion of branches, non-interest income and net profits, lower variability is seen in case of ICICI bank. This is an indication of satisfactory management of growth performance. Median, Skewness, Kurtosis, J-B statistics with probability authenticates that none of the variables are normally distributed, which is shown in tables 1 & 2.
Table-1: Descriptive Statistics on Various Growth Rates of SBI Deposits Number Net Non- Advances Operating Net Mobiliza- of Interest Interest Deployment Expenses Profits tion Branches Margin Income Mean 15.407 22.844 5.127 18.304 12.267 14.415 17.439 Median 14.597 23.547 3.073 13.406 5.722 13.272 16.939 Maximum 38.085 30.169 12.366 37.408 45.956 29.843 48.176 Minimum 3.541 14.646 0.132 -3.406 -9.309 0.839 -9.836 Std. Dev. 10.272 6.569 4.924 12.483 20.060 8.793 20.389 C.V. (%) 66.67 28.76 96.04 68.20 163.53 61.00 116.92 Skewness 1.177 -0.165 0.286 -0.032 0.396 0.283 0.276 Kurtosis 3.723 1.324 1.344 2.373 1.807 2.448 1.688 Jarque-Bera 2.275 1.094 1.150 0.149 0.769 0.235 0.760 Probability 0.321 0.579 0.563 0.928 0.681 0.889 0.684 Observations 9 9 9 9 9 9 9
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Volume 3 ISSN 0975-0746 Table-2: Descriptive Statistics on Various Growth Rates of ICICI Deposits Number Net Non- Advances Operating Net Mobiliza- of Interest Interest Deployment Expenses Profits tion Branches Margin Income Mean 22.865 21.032 23.212 26.844 18.564 18.278 21.332 Median 13.253 17.268 19.829 19.045 12.859 21.876 25.505 Maximum 65.382 59.907 67.152 65.856 55.756 51.589 35.726 Minimum -10.671 -16.996 0.000 -3.015 -13.699 -16.824 -9.611 Std. Dev. 26.315 23.639 21.301 22.268 26.086 21.885 14.201 C.V. (%) 115.09 112.40 91.77 82.95 140.52 119.73 66.57 Skewness 0.208 0.093 1.109 0.469 0.227 -0.420 -1.257 Kurtosis 1.759 2.351 3.074 2.096 1.613 2.366 3.555 Jarque-Bera 0.642 0.171 1.847 0.636 0.799 0.415 2.485 Probability 0.725 0.918 0.397 0.728 0.671 0.813 0.289 Observations 9 9 9 9 9 9 9
4.2 Correlation Statistics Correlation statistics in tables 3 & 4 identify that deposit mobilization, number of branches, net interest margin and non-interest income are positively correlated with net profits and advances deployment as well as operating expenses are negatively related with net profits in case of SBI during the period under study. Correlation test result is unbelievably powerful in case of ICICI bank than SBI. However it does not talk about the grounds and shock. In order to make out an unequivocal delineation of the shock, it is obligatory to execute multiple regression tests between the selected variables.
Table-3: Correlation Statistics on Various Growth Rates of SBI Deposits Number Net Non- Advances Operating Net Mobiliza- of Interest Interest Deployment Expenses Profits tion Branches Margin Income Deposits 1.000 Mobilization Advances 0.417 1.000 Deployment Number of 0.684 -0.002 1.000 Branches Net Interest 0.188 -0.320 0.284 1.000 Margin Non-Interest 0.536 -0.025 0.611 -0.072 1.000 Income Operating 0.034 -0.292 0.469 0.230 0.525 1.000 Expenses Net Profit 0.507 -0.045 0.247 0.116 0.344 -0.105 1.000 *Correlation is significant at 1%, 5% and 10% level of significance.
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Volume 3 ISSN 0975-0746 Table-4: Correlation Statistics on Various Growth Rates of ICICI Deposits Number Net Non- Advances Operating Net Mobiliza- of Interest Interest Deployment Expenses Profits tion Branches Margin Income Deposits 1.000 Mobilization Advances 0.910 1.000 Deployment Number of -0.343 -0.010 1.000 Branches Net Interest 0.942 0.926 -0.407 1.000 Margin Non-Interest 0.595 0.438 -0.034 0.451 1.000 Income Operating 0.916 0.921 -0.069 0.839 0.701 1.000 Expenses Net Profit 0.564 0.514 0.252 0.311 0.712 0.740 1.000 *Correlation is significant at 1%, 5% and 10% level of significance.
4.3 Multiple Regression Test Results With the intention of observe the association between the dependent variable net profits (NP) and six independent variables of deposits mobilization (DM), advances deployment (AD), number of branches (NB), net interest margin (NIM), non-interest income (NII) and operating expenses (OP) have been used to measure the growth performance of SBI and ICICI bank. So as to test the impact of six selected independent variables on the net profits during the study period the regression model used in this analysis is NP = α + ß1 DM + ß2 AD + ß3 NB + ß4 NIM + ß5 NII+ ß6 OP + µt. With the aim of determine the reliability of the regression results, Durbin- Watson statistics has been used. The rule of thumb is that the observed D-W statistic should be between 1 and 4 for the dependability of the regression results and the absence of serial correlation. In order to examine the multicollinearity between the independent variables, variance inflation factor (VIF) has been used. According to modern statistics if the VIF of a variable does not exceed 2, it may be said that there are no multicollinearity problem with other independent variables. First of all, six independent variables of deposits mobilization (DM), advances deployment (AD), number of branches (NB), net interest margin (NIM), non-interest income (NII) and operating expenses (OE) have been taken as independent variables and net profits (NP) has been used as dependent variable. Using these six independent variables as the determinants of NP it has found that six variables are correlated with each other.
4.3.1 SBI It is also observed that insignificant association is found with a very high standard error for all the runs of the regression model. In order to reduce the multicollinearity problem and to obtain reliable results, next step of regressions under enter method with five variables (after removing DM) linear regression analyses run on the SPSS are performed. For each function constructed, the
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Volume 3 ISSN 0975-0746 model fit has been assessed on how strong is the function, how well it associates and checking the VIF and tolerance for predictive accuracy for the company as well and the ultimate results of SBI are reported in table 5.
Table- 5: Multiple Regression Test Results of SBI Unstandardized Model t Sig. Collinearity Statistics Coefficients Std. 1 B Tolerance VIF Error (Constant) 27.82 50.92 0.546 0.62 AD -0.36 1.66 -0.214 0.84 0.80 1.25 NB 0.28 2.83 0.101 0.93 0.49 2.00 IM 0.37 .94 0.395 0.72 0.70 1.43 NII 0.61 .71 0.853 0.46 0.47 2.00 OE -1.24 1.44 -0.863 0.45 0.60 1.68 R Adjusted R R=0.56 Square= Square= F=0.31 Durbin-Watson=2.40 0.31 -0.84 a. Predictors: (Constant), OE, IM, AD, NB, NII b. Dependent Variable: NP
It is observed from the table that one unit increase in AD, NP of the bank decreased by 0.36 units. However, when NB increased by 1 unit, NP of the bank increased by 0.28 units. Again for one unit increase in IM and NII, the NP the bank increased by 0.37 and 061 units respectively. It is evident from the table that when OE increased by one unit, the NP of the bank decreased by 1.24 units. The multiple correlation coefficient (R) between the NP and the independent variables taken together is 0.56. It may be said that NP was significantly influenced by its independent variables. R2 defines to what extent the variation in the response is explained by the regression. From the table it is observed that the value of R2 is 31%, which means 31% of the variation is explained by the regression. Adjusted R2 (-0.84) indicates the co-efficient of determination which is negatively associated in the regression equation. The value of F is 0.31, which examines the significance of all the variables collectively in regression function. The observed R2 and F statistics may thus be sufficient to draw an inference in the favour of goodness of the regression model to fit into the present task of identifying the factors influencing the NP of the banks during the study period. The value of the D-W statistics is 2.40, which also strongly advocate in favour of the dependability of the results. VIF measures the multicollinearity problem, which is the inverse of tolerance value. Based on the value of VIF in tables, there is very low multicollinearity among the variables because VIF is near about 2.
4.3.2 ICICI It is also observed that insignificant association is found with a very high standard error for all the runs of the regression model. In order to reduce the multicollinearity problem and to obtain reliable results, numerous regressions under enter method (after removing DM, AD and OE) linear run on the SPSS are 72 | Business Perspectives
Volume 3 ISSN 0975-0746 performed. For each function constructed, the model fit has been assessed on how strong is the function, how well it associates and checking the VIF and tolerance for predictive accuracy for the company as well and the ultimate results of SBI are reported in table 6.
Table- 6: Multiple Regression Test Results of ICICI Unstandardized Model t Sig. Collinearity Statistics Coefficients Std. 1 B Tolerance VIF Error (Constant 6.89 9.31 0.74 .49 ) NB 0.23 .21 1.07 .33 .81 1.24 NIM 0.10 .23 0.43 .68 .64 1.56 NII 0.36 .18 2.03 .10 .77 1.30 R Square=0.60 Durbin- Adjusted R R=0.77 F=2.49 Watson= Square=0.36 1.03 a Predictors: (Constant), NII, NB, NIM b Dependent Variable: NP
It is observed from the table that one unit increase in NB, NP of the bank increased by 0.36 units. Nevertheless, when NIM increased by 1 unit, NP of the bank increased by 0.10 units. Again for one unit increase in NII, the NP the bank increased by 0.36 units. The multiple correlation coefficient (R) between the NP and the independent variables taken together is 0.77. It may be said that NP was significantly influenced by its independent variables. R2 defines to what extent the variation in the response is explained by the regression. From the table it is observed that the value of R2 is 60%, which means 60% of the variation is explained by the regression. Adjusted R2 (0.36) indicates the co-efficient of determination which is negatively associated in the regression equation. The value of F is 2.49, which examines the significance of all the variables collectively in regression function. The observed R2 and F statistics may thus be sufficient to draw an inference in the favour of goodness of the regression model to fit into the present task of identifying the factors influencing the NP of the banks during the study period. The value of the D-W statistics is 1.03, which also strongly advocate in favour of the dependability of the results. VIF measures the multicollinearity problem, which is the inverse of tolerance value. Based on the value of VIF in tables, there is very low multicollinearity among the variables because VIF is less than 2.
4.3.3 Test of hypothesis A hypothesis is a supposition to be tested. The statistical testing of hypothesis is the significant method in statistical inference. Hypothesis tests are far and wide used in business and industry for making decisions. The following are the hypothesis framed and tested using test of significance at 5% level of significance.
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H0: There are no significant differences subsist in growth performance between SBI and ICICI over the period under study. H1: There are significant differences subsist in growth performance between SBI and ICICI over the period under study.
t- test Results 95% Confidence Test Value = 0 Interval of the Difference Sig. (2- Mean t df Lower Upper tailed) Difference SBI 2.57 8 0.033 17.44 1.77 33.11 ICICI 4.51 8 0.002 21.33 10.42 32.25 The calculated value of t is more than the significant value, hence null hypotheses is not accepted, as supported in, (Bhunia, 2011).
5. Conclusions The present study investigates and compares the growth performance of SBI and ICICI for the period from 2003-2012 using descriptive statistics, correlation statistics and multiple regression statistics. The empirical results of descriptive statistics illustrate that the growth of ICICI bank is more satisfactory than SBI under the study except deposit mobilization and operating expenses which indicates that growth performance is very pleasing in case of private sector bank than public sector bank in India during the period under study. But in the case of management of growth performance, C.V. of SBI is better than ICICI because lower variability is seen in case of SBI. Skewness, Kurtosis, J-B statistics with probability authenticates that none of the variables are normally distributed. Correlation statistics justify that deposit mobilization, number of branches, net interest margin and non-interest income are positively correlated with net profits and advances deployment as well as operating expenses are negatively related with net profits in case of SBI during the period under study. Correlation test result is unbelievably powerful in case of ICICI bank than SBI. However it does not talk about the grounds and shock. Again, multiple regression test results exemplifies that the growth of net profits meagerly hinge on the growth indicators and it relies on bank branches, interest and non-interest margin in case of both the banks under the study. It also indicates that the net profits of SBI rely on deposit mobilization and advances deployment. This study is not free from certain limitations. We have considered only 10 years period for the study and based on only seven growth indicators. We could not consider the growth of sales, reserve and surplus, earning per share, internal growth & sustainable growth in the present study. This will be our future research work.
References 1. Anjum and Deepika (2012). Technological Implementation-Path of Growth: A Comparative Study of Public and Private Sector Banks, Asia Pacific Journal of Marketing and Management Review, 1(1), 24-39. 2. Ayyappan and Sakthivadivel (2012). Growth and Trend Analysis of Key Profitability Factors in Indian Scheduled Commercial Banks, Journal of Research, 1(9), 49-58.
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Volume 3 ISSN 0975-0746 3. Bharati V. Pathak (2011). The Indian Financial System: Market, Institution and Services, 3e, Pearson, New Delhi. 4. Bhunia and Khan (2011). A Study of Managing Liquidity, Journal of Management Research (USA), 3(2): E8, 1-21. 5. Ghosh Saibal (2010). Credit Growth, Bank Soundness and Financial Fragility, Evidence from Indian Banking Sector, Munich Personal RePEc Archive, MPRA Paper No. 24715. 6. Gupta, R and Sikarwar, N.S (2013). A Comparative Study of Growth Analysis of Punjab National Bank of India and HDFC Bank Limited, International Journal of Application or Innovation in Engineering & Management, 2(2), 60-67. 7. IBEF (2013). The Indian Banking Sector: Recent Developments, Growth and Prospects, taking online from www.ibef.org. 8. KPMG (2013). Indian banks: Performance benchmarking report, http://www.kpmg.com/IN/en/IssuesAndInsights/ArticlesPublications/Documents/perfor mance-benchmarking-report-12-new.pdf. 9. Kumar T. S. (2006), Leveraging Technology Foreign Banks Financial Inclusion, Bankers Conference Proceedings (Nov.): 44-152. 10. Manoj P. K. (2010), Determinants of Profitability and Efficiency of Old Private Sector Banks in India with Focus on the Banks in Kerala State, International Research Journal of Finance and Economics, 47, 7-20. 11. Panda J. and Lall G.S. (1991), ―A Critical Appraisal on the Profitability of Commercial Banks,‖ Indian Journal of Banking and Finance, Vol.5, No.2, pp. 40-44. 12. Ram Mohan T.T. and Ray S.C (2004), ‗Productivity Growth and Efficiency in Indian Banking: A Comparison of Public, Private, and Foreign Banks‘, University of Connecticut, Economics Working Papers No. 2004-27.
Appendix
Table 1: Various Growth related Data of SBI & ICICI (Rs. in crore) Deposits Advances Number of Year Net Interest Margin Mobilization Deployment Branches ICICI ICICI ICICI ICICI SBI SBI SBI SBI Bank Bank Bank Bank 2002-03 296123 48169 137758 53279 9081 -- 9977.56 1424.06 2003-04 318619 68109 157934 62096 9093 469 11186.32 1878.79 2004-05 367048 99819 202374 91405 9156 562 13944.62 2839.01 2005-06 380046 165083 261801 146163 9247 614 15589.13 4708.68 2006-07 435521 230510 337336 195866 9314 755 15058.20 6635.79 2007-08 537404 244431 416768 225616 10270 1262 17021.23 7304.10 2008-09 742073 218348 542503 218311 11540 1419 20873.14 8366.61 2009-10 804116 202017 631914 181206 12638 1707 23671.44 8114.36 2010-11 933933 225602 756719 216366 13698 2529 32526.40 9016.90 2011-12 1043647 255500 867579 253728 14119 2752 43291.08 10734.16 Source: Annual Accounts of the respective Banks.
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Volume 3 ISSN 0975-0746 Table 2: Various Growth related Data of SBI & ICICI (Rs. in crore) Year Non-Interest Income Operating Expenses Net Profits ICICI SBI SBI ICICI Bank SBI ICICI Bank Bank 2002-03 5740.26 1967.77 7942.42 2011.69 3105.00 1206.18 2003-04 7612.46 3064.92 9254.32 2571.23 3681.00 1637.10 2004-05 7119.90 3416.14 10074.16 3299.15 4304.52 2005.20 2005-06 7435.20 4983.14 11725.10 5001.15 4406.68 2540.07 2006-07 6765.26 5929.17 11823.51 6690.56 4541.31 3110.22 2007-08 8694.93 8810.76 12608.60 8154.18 6729.12 4157.73 2008-09 12690.79 7603.73 15648.70 7045.11 9121.23 3758.13 2009-10 14968.15 7477.65 20318.68 5859.83 9166.05 4024.98 2010-11 15824.59 6647.89 23015.43 6617.25 8264.52 5151.38 2011-12 14351.45 7502.76 26068.99 7850.44 11707.29 6465.26 Source: Annual Accounts of the respective Banks. Table-3: Various Growth Rates (%) of SBI Deposits Number Net Non- Advances Operating Net Mobiliza- of Interest Interest Deployment Expenses Profits tion Branches Margin Income 2003-04 7.597 14.646 0.132 12.115 32.615 16.518 18.551 2004-05 15.2 28.138 0.693 24.658 -6.470 8.859 16.939 2005-06 3.541 29.365 0.994 11.793 4.428 16.388 2.373 2006-07 14.597 28.852 0.725 -3.406 -9.010 0.839 3.055 2007-08 23.393 23.547 10.264 13.036 28.523 6.640 48.176 2008-09 38.085 30.169 12.366 22.630 45.956 24.111 35.549 2009-10 8.361 16.481 9.515 13.406 17.945 29.843 0.491 2010-11 16.144 19.750 8.387 37.408 5.722 13.272 -9.836 2011-12 11.748 14.650 3.073 33.095 -9.309 13.267 41.657 Source: Author‘s own calculation. Table-4: Various Growth Rates (%) of ICICI Number Net Non- Deposits Advances Operating Net of Interest Interest Mobilization Deployment Expenses Profits Branches Margin Income 2003-04 41.396 16.549 - 31.932 55.756 27.814 35.726 2004-05 46.558 47.2 19.829 51.108 11.459 28.310 22.485 2005-06 65.382 59.907 9.253 65.856 45.870 51.589 26.674 2006-07 39.633 34.005 22.964 40.927 18.985 33.780 22.446 2007-08 6.039 15.189 67.152 10.071 48.600 21.876 33.680 2008-09 -10.671 -3.238 12.441 14.547 -13.699 -13.601 -9.611 2009-10 -7.479 -16.996 20.296 -3.015 -1.658 -16.824 7.101 2010-11 11.675 19.403 48.155 11.123 -11.097 12.926 27.985 2011-12 13.253 17.268 8.818 19.045 12.859 18.636 25.505 Source: Author‘s own calculation
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Volume 3 ISSN 0975-0746 RIGHT TO EDUCATION ACT : PERSPECTIVE & CHALLENGES
Biswambhar Mandal Assistant Professor, Dept. of Commerce, University of Kalyani, West Bengal
Abstract
The present study explores the outlook as well as confronts of Right to Education Act, 2009. In other words, this study observes the anomalies in terms of financial and social effect of the said act. This act is very crucial for strengthening the education infrastructure and fixes the quality education. At the same time, it is very much important to remove the gap among social, regional and gender bias. The primary findings of the study is that there is a gap exist among social, regional and gender biasness in India. It is suggested that proper educational planning, financial planning, social awareness can reduce the problems.
Keywords: Right to Education Act, India, outlook, confronts, regional imbalances, quality education.
1. Introduction Education is the most important driving force for the progress and development of a nation. The ‗right to education‘ of every Indian child was a dream of Gopal Krishan Gokhle, an eminent freedom fighter of India. More than a hundred years ago, he urged the Imperial Legislative Assembly to confer such a right on Indian children. That very old dream of Gokhle has come to an end in India with the enactment of the Right of Children to Free and Compulsory Education (hereinafter called RTE Act) Act 2009. This Act is the first legislation in the world that puts the responsibility of ensuring enrollment, attendance and completion on the government. The Act makes education a fundamental right of every child between the ages of 6 and 14 and specifies minimum norms in elementary schools. It means that the government will be responsible for providing education to every child up to the eighth standard, free of cost, irrespective of class and gender.
2. Historical Context of RTE Act 2.1. Constitutional Provision Article 45 of the Indian Constitution (one of the Directive Principles) provided that ―the State shall endeavour to provide within a period of 10 years from the commencement of the Constitution, free and compulsory education to all children until they complete the age of 14 years.‖ This Directive Principle remained as such without implementation till 2002. The 86th amendment of the Constitution of India in 2002 made education a fundamental right by transferring this provision to Article 21A. This amendment includes the following changes through three important inclusions of Article 21A, Article 45 and Article 51A. Article 21A states that, ―The state shall provide free and compulsory education to all children of the age of 6-14 years, in such a manner as the state may, by law determine.‖
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Volume 3 ISSN 0975-0746 Article 45 states that, ―The state shall endeavour to provide early childhood care and education for all children until they complete the age of six years‖. A new clause ‗K‘ has been added to Article 51A through which a duty of every citizen (who is a parent or guardian) was fixed. The clause states that every citizen (who is a parent or guardian) has to provide opportunities for education to his child or, as the case may be ward, between the age of 6 and 14 years.
2.2. Allocation in the Five year Plans If we look at the plan allocations, we find that in the first five year plan allocation was 7.8%., but in subsequent plans gradually it dwindled. To increase plan allocation, making basic education a fundamental right was a bold decision. After Constitution amendment in 2002, the plan allocations started increasing. From 11th plan the allocation touched double digit.
Table: Financing of Education in Five-year Plans Five Year Plan Allocation of Funds to Education of the Total Plan Outlay First (1951-56) 7.8% Second (1956-61) 5.8% Third (1961-66) 6.9% Fourth (1969-74) 5.8% Fifth (1974-79) 3.3% Sixth (1980-85) 2.7% Seventh (1985-90) 3.1% Eighth (1992-97) 4.5% Ninth (1997-02) 4.3% Tenth (2002-07) 7.68% Eleventh (2007-12) 11.17% Twelfth (2012-17) 12.71% * Source: Various Five-year plan Documents, GOI. * Proposed Amount.
2.3. Emphasis in National Policies on Education In the National Policy of Education 1968, the Central Government committed towards elementary education. This was further emphasized in the National Policy on Education1986. In the review of the Policy in 1990 (by a Committee under the chairmanship of Acharya Ramamurti), it was recommended to include Right to Education as a fundamental right in the Constitution, on the basis of which The Programme of Action (POA), 1992 was formulated. ―The National Educational Policies have reiterated the Constitutional directive. The National Policy on Education, 1986, provided that ‗free and compulsory education of satisfactory quality shall be provided to all children upto the age of 14 years before we enter the 21st century.‘ The Programme of Action (POA), 1992 outlined various strategies for achieving the goal.‖ (Mandal, Ajit & Mete, Dr. Jayanta , 2012).
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Volume 3 ISSN 0975-0746 2.4. Other Initiatives by the Government Apart from these, the following initiatives were taken and developed by the government, which can be called as foundation stones of fundamental right to education:
Operation Blackboard (1987) This programme aimed to improve the human and physical facilities available in primary schools.
Restructuring and reorganization of teacher education (1987) It aimed to create a resource for the continuous upgrading of teachers‘ knowledge and competence.
National Literacy Mission (1988) The aim of NLM was to eradicate illiteracy in the country by imparting functional literacy to non-literates. Thus, National Literacy Mission was established not only to make everybody just self reliant in the three Rs — reading, writing and arithmetic — but also to make them aware of the development issues affecting the society. The target group of NLM is people between the age of 15 and 35. (www.wikipedia.org)
Minimum Level of Learning (1991) This programme laid down levels of achievement at various stages and therefore it sought to revise textbooks.
District Primary Education Programme (DPEP) (1993) The aim of this programme was to provide access to children to primary education through formal primary schools or its equivalent through alternatives. This programme emphasized decentralized planning and management, improved teaching and learning materials, and school effectiveness.
National Programme for Nutritional Support to Primary Education (1995) This programme provided for a cooked meal daily for children in class I to class IV of all government, government aided, and local authority schools.
Mid-Day Meal Scheme (1995) This scheme was launched in 1995 to increase enrolment, retention and participation of children in primary schools through improving their nutritional status.
Sarva Shikha Abhijan (SSA) (2001) It is a flagship centrally sponsored scheme for universalization of elementary education. The programme focuses specially on girls and children with challenged social or financial backgrounds. This programme aims at: (a) strengthening school infrastructure. (b) providing teachers and to build their capacities through training. (c) providing quality education. (d) promoting community participation in primary education. (e) making bridge social, regional and gender gaps in literacy and primary education. 79 | Business Perspectives
Volume 3 ISSN 0975-0746 (f) focusing on girl‘s education and children with special needs. (g) providing computer education.
Impact of Literacy Programmes on Literacy Rate Presently India has the second largest population in world. At the same time India has one-third of the world‘s illiterate population. Let us look at the literacy rate in India from the year 1951 to the year 2011 as shown in the following Table.
Table: Literacy Rate in India Census Year % Literate in 7+ population Male-female Male Female Overall gap 1951 27.2 8.9 18.3 18.3 1961 40.4 15.4 28.3 25.0 1971 46.0 22.0 34.4 24.0 1981 56.4 29.8 43.6 26.6 1991 64.1 39.3 52.2 24.8 2001 75.3 53.7 64.8 21.6 2011 82.1 65.5 74.0 16.7 Source: Census of India (2011)
It is shown from above table that up to 1981 census in India male literacy level has reached 56.4%, while female literacy has touched 29.8% and overall literacy has touched 43.6%. The difference between male and female literacy level is 26.6%. Up to 1991 census in India male literacy level has reached 64.1%, while female literacy has touched 39.3% and overall literacy has touched 52.2%. The difference between male and female literacy level is 24.8%. If we look at the 2001 census figures, the male literacy level has reached 75.3%, while female literacy has touched 53.7% and overall literacy has touched 64.8%. The difference between male and female literacy level is 21.6%. If we look at the 2011 figures, the male literacy level has reached 82.1%, while female literacy has touched 65.5% and overall literacy has touched 74%. The difference between male and female literacy level is 16.7%. It is seen that the difference between male and female literacy level in India is decreasing. It‘s worth mentioning, however, that in the period between 2001 and 2011, the increase in male literacy was just 6.14%, whereas it was 12.1% between 1991 and 2001. Similarly, in the period between 2001 and 2011, the increase in female literacy was just 11.46%, whereas it was 14.8% between 1991 and 2001. India has witnessed remarkable progress in spread of literacy. Compared to just 18.3 % of India‘s population recorded as literate in the first Census after independence, according to the 2001 Census, that proportion has gone up to 64.8%, and according to the 2011 Census, that proportion has gone up to 74%. The achievement among males has been from 27.2% to 82.1% and achievement among females has been from 8.9% to 65.5% in the 60 years. From less than one in ten women counted as literate in 1951, in 2011 two out of three women are enumerated as literate. 80 | Business Perspectives
Volume 3 ISSN 0975-0746 3. Implementation and Overview of RTE Act A key feature of RTE is that it emphasises quality as an integral aspect of the child‘s right to be educated. Part-V of the RTE Act lays down specific terms under which the quality of elementary education is to be ensured. These include a comfortable teacher-student ratio, curriculum reform and improvement in evaluation methods. 1. It provides that children have a right to free and compulsory education till completion of elementary education in a neighbourhood school. It provides for neighbourhood schools within reach, with no school refusing admission to any child. 2. It makes provisions for a non-admitted child to be admitted to an age appropriate class. 3. It provides that no admitted child shall be held back, expelled, or required to pass a board examination until completion of elementary education. 4. For children in 6-14 age groups the Act prohibits physical punishment and mental harassment, screening procedures for admission, capitation fees, private tuition by teachers, running of schools without recognition. 5. It requires all private schools to reserve 25% of seats to children from poor families (to be reimbursed by the state as part of the public-private partnership plan). 6. The Act makes it mandatory for every child between the ages of 6-14 to be provided for education by the state. 7. A new concept of ‗neighbourhood schools‘ has been introduced. This would imply that the state government and local authorities will establish primary schools within distance of one km of the neighbourhood. In case of children for class VI to VIII, the school should be within a distance of three km of the neighbourhood. 8. Unaided and private schools shall ensure that children from weaker sections and disadvantaged groups shall not be segregated from the other children in the classrooms. 9. No teacher shall be deployed for any non-educational purpose. 10. The Act prescribed minimum number of working days for teachers in an academic year as follows. 200 working days (for class I-V) 220 working days (for class VI-VIII). 11. The Act prescribed minimum 45 teaching including preparation hours per week for teachers. 12. In addition to above, the schools need to have certain minimum facilities and have to maintain norms and standards as prescribed in the Act. The schools have to ensure proper infrastructure, which includes a playground, library, adequate number of classrooms, toilets, barrier free access for physically challenged children and drinking water facilities within three years.
4. Anomalies in the Act The RTE Act does have some confusions or some sort of uncertainty or loopholes which may create challenges at the time of implementation. We shall discuss some of such cases.
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Volume 3 ISSN 0975-0746 Definition of ‘child’ The United Nations Convention on Rights of the Child (UNCRC) defines any individual below 18 years of age as a child. India is a signatory to that convention. The Juvenile Justice Act in our country considers persons below 14 years of age to be children. But as per Section 2c of the RTE Act 2009, ‗‗Child means a male or female child of the age of six to fourteen years.‖ (Right to Education Act, 2009, p.2.) Such differences in definitions of child may create complications on the part of implementation of the RTE Act.
Establishment of Neighbourhood School The question of establishing a neighbourhood school where there is none within three years of commencement of the Act is a case in point. The Act does not clarify the area or limits for establishment of a neighbourhood school, leaving this to be decided by the government at a later date through rules that it may deem fit to alter. The neighbourhood school concept was not specifically defined and was left vague.
Eligibility of a Teacher Eligibility of teachers would be based on minimum qualifications as laid down by an academic authority. The act allows for unqualified teachers to continue for five years after the act comes into effect, on grounds of lack of availability of trained teachers. We cannot ensure quality without reasonably good infrastructure, sufficient numbers of trained and adequately compensated teachers, other amenities and teaching aids.
School Management Committees Sec 21(l) of the RTE Act states that, a school ―shall constitute a School Managing Committee consisting of the elected representatives of the local authority, parents or guardians of children admitted in such school and teachers; Provided that at least three-fourth of members of such committee shall be parents or guardians; Provided further that proportionate representation shall be given to the parents or guardians of children belonging to disadvantaged group and weaker section. Provided also that fifty per cent of Members of such committee shall be women.‖ (Right to Education Act, 2009, p.7.) The School Management Committees (SMCs) are assumed to ensure enrolment and continued attendance of all children from the neighbourhood of the school. But these obligations remain only on paper as we continue to see children either begging on the roads or involved in child labour. Lack of awareness about the Act, inability to meet the distance criteria and difficulty in obtaining necessary certificates from government authorities could be some of the reasons for the poor response.
Age appropriate classrooms Section 4 of the Act states that ―where a child above six years of age has not been admitted in any school or though admitted, could not complete his or her elementary education, then, he or she shall be admitted in a class appropriate to his or her age.
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Volume 3 ISSN 0975-0746 Provided that where a child is directly admitted in a class appropriate to his or her age, then, he or she shall, in order to be at par with others, have a right to receive special training, in such manner, and within such time-limits, as may be prescribed. …‖. (Right to Education Act, 2009, p.3) It has been mentioned in the Act that the programmes of special training will be determined by the Head teacher of the school. In many cases the Head teachers are not aware of what this special training is and what constitutes this training. In such a situation when they are not even aware of the special training, expecting them to know who will impart the training, where and how will be needless.
Exclusion of un-aided schools Quality monitoring is attainable only in a culture of accountability. To ensure this, the Act requires that all schools, except those that are unaided, constitute school management committees. It is not clear why unaided schools are left out of the purview of accountability.
Financial Responsibility There is no clarity on who will take the lead in financing the implementation of the Act.
Capitation Fees Sec. 2(b) of the RTE Act defines the term ‗capitation fee‘. It means any kind of donation or contribution or payment other than the fee notified by the school. It seems from the definition that the Act permits the private schools to charge capitation fee under the mask of ‗fees notified by the school‘.
Mental Harassment In the Act, the term ‗mental harassment‘ is left without a clear definition. This provision could be misused against teachers.
Children with Disability The Act is silent on the rights of children with disability.
5. Challenges in Implementing the Act To realize the goals of the RTE Act is a huge challenge. Some of the important challenges in implementing the Act are: Shortage of trained teachers Who will train the teachers? Who will orient the existing cadre of teachers Lack of infrastructure in schools. Requirement of additional schools. Finance. Early Marriage Migration of people for sustenance. Lack in the sincerity of approach by the stakeholders. Instead of improving teachers‘ working conditions and training, many states have opted for cosmetic solutions.
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Volume 3 ISSN 0975-0746 6. Concluding Observations The Act is a landmark initiative of the government of India. It is a progressive piece of legislation that aims to take education to the masses and fill the gaps in the social system. It has some loopholes, yet this Act has the capacity to deliver the long-standing commitment of providing basic and quality education to all. There are some challenges in the course of implementation of the Act. It requires some modifications and proper financial planning. However, it has the capacity to face the challenges and reduce the anomalies. The success will depend on the participation of people at large.
References 1. Various Five-year plan Documents, Government of India. 2. Mandal, Ajit & Mete, Dr. Jayanta (2012), Right to Education- An Appraisal, Kurukshetra, Vol. 60, No. 11, Ministry of Rural Development, September 2012, p.11. 3. www.wikipedia.org 4. www.censusindia.gov.in 5. Ministry of Human Resource Development (2009), Right to Education Act, 2009, Dept. of Elementary Education and Literacy, Govt. of India, New Delhi.
Other Related Readings 1. S C Agarwal and Vishal Awrawal (2012), RTE Act: Some Reflections in the light of Supreme Court Decision, University News, 50(49), Dec.3-9, p. 8-13, 21. 2. Anil Kumar Biswas (2012), Decentralisation of elementary education in India, Kurukshetra, Vol. 60, No. 11, Ministry of Rural Development, September, p.3-7. 3. Praveen Jha, Pooja Parvati (2010), Right to education Act 2009: Critical Gaps and Challenges, Economic & Political Weekly, March 27, Vol XLV No 13, p. 20-23 4. T.K. Rajalakshmi (2012), Postcards from the margins, Frontline, May 18, p. 36-38. 5. www.pib.nic.in/newsite/PrintRelease.aspx 6. Ojha Seema S. (2013), Implementing Right to Education: Issues and Challenges, Research Journal of Educational Sciences, Vol. 1(2), 1-7, May, p. 1-7. 7. Ajit Mandal & Jayanata Mete (2012), Right to Education Act, 2009: Opportunities and Challenges in the 21st Century, Proceedings on UGC sponsored National Seminar on ‗Education in the 21st Century‘, Org. by Shimurali Sachinandan College of Education, 13-14 March, 2012. 8. Ashok Hando(2010), The Right to Education now a Fundamental Right, Kurukshetra, Ministry of Rural Development, Vol. 58, No. 11, September, p.19-20. 9. Krishna Kumar (2011), Why RTE remains a moral dream, The Hindu, May 21, 2011.
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Volume 3 ISSN 0975-0746 NGO GOVERNANCE-A STUDY IN WEST BENGAL
Sanjib Kumar Pakira Assistant Professor, Department of Commerce, Maharaja Manindra Chandra College
Abstract Over the past three decades, there has been an exponential growth in the number of non- governmental organizations (NGOs), operating across the entire spectrum of development activities in the world, and West Bengal is no exception. The rapid growth in the number, influence and effectiveness of NGOs in recent years has produced greater demands for NGO accountability and governance. These demands – which originate from several spheres, including government, the private sector, academia, and the general public – necessitate assurance that NGOs are responding to the needs and expectations of their many stakeholders and fulfilling their varying missions and objectives. Despite the growing number of NGOs playing vital role in a number of areas, there has been an absence of a reasonable framework to ensure the accountabilities to good governance. However, this paper discusses the practice followed by the surveyed NGOs to see the trends of NGO accountability for establishing good governance in West Bengal.
Key words: NGOs, Governance, Accountability, Fund, Society, Environmental advocacy.
1. Introduction Success of an enterprise depends on how effectively and efficiently the financial resources are put to use by it. Indeed, NGOs are no exception to this proverb. A non-governmental organization (NGO) is an organization that is not part of a government and was not founded by states. NGOs are therefore typically independent of governments. The term is generally restricted to social, cultural, legal, and environmental advocacy groups having goals that are primarily noncommercial (Venkatesha S.Sampa, 2010). NGOs are usually non- profit making organizations which secure at least a portion of their funding from private sources. With NGOs receiving grants from various donor organizations, it is their duty to maintain financial discipline and ensure transparency in dealings. Over the past quarter century, there has been a rapid growth in the number of NGOs involved in the developmental works. An NGO is a legal entity and has in its possession funds of its members and also the property belonging to the members in its name which is used for achieving the objectives for which the NGO has been formed. Like any other corporate body, the funds of the NGOs are managed by a group of individuals who are accountable for these funds to other members of the society. To have proper accountability, it is important to have good governance for the NGOs. To achieve this, it is important for NGOs to maintain regular books of accounts and to have them audited. The importance of NGO governance is rising in this state and thus, opens a vast field for research and enquiry about it. Therefore, an attempt has been made in this paper to examine and evaluate the NGO governance in West Bengal.
1.1 Concept of NGO- Governance The English word ―governance‖ comes from the Latin word meaning ―to steer, guide, or direct.‖ The term generally refers to the way in which power is 85 | Business Perspectives
Volume 3 ISSN 0975-0746 assumed, conveyed, and exercised within a society or an organization. According to Western political theorists, ―good governance‖ is a sharing of decision-making authority so that power and resources don‘t accumulate in the hands of a single individual or group. Good governance is input to the growth and sustainability of nongovernmental organizations (NGOs). ―Effective NGO Governance,‖ presents methods and techniques for planning and implementing actions to improve an organization‘s governance. An NGO‘s sustainability—its ability to serve its clients over the long term— depends largely on the quality of the organization‘s governance (Marilyn Wyatt, 2010).
1.2 Effective and standard NGO Governance Governance standards of organisations are recognized as significant in maintaining the transparency and accountability on the whole. This is as true for the NGOs as for the corporates and the government. The governance standards play a significant role in creating operational efficiencies of NGOs (Marilyn Wyatt, 2010). To be aware of effective NGO governance in West Bengal, we encounter first at a typical governance structure of an NGO with a high level of capacity. A clear picture of effective governance makes it easier to plan actions that move an NGO in the direction of better governance. NGOs are directed and controlled by a governing body, or a board of directors. In most countries, the board has a legal, moral, and fiduciary responsibility for the organization An NGO with a high level of governance capacity should have a board which is the principal governing body and the board makes all decisions collectively. The board has a chair and the board is distinct from the staff. All individual board members have specific duties. The board governs and the staff manages. Good governance involves the separation of governance and management (Module 5: Effective NGO Governance).
1.3 Problems of Governance in the NGO Sector The corporate world in general, and also the government sector, has in recent years increasingly acknowledged the emphasis on the corporate governance and the regulatory frameworks that have emerged. But while the corporate sector in India and elsewhere has somewhat succeeded in institutionalizing effective governance policies and regulations, the NGO sector is yet to reach anywhere near that level. The changing social environment has added to the exposure of the voluntary sector to various risks, particularly those operating in extremely remote or underdeveloped regions in West Bengal (where the need and the role of the NGOs are most significant). In particular, the NGO sector has become helpless to the vested interests of partial political interests, organised crime and extremist organizations in such regions. The Indian government has been blacklisting several NGOs for primarily fund misappropriation and relationships with extremist groups. In 2003, India‘s home ministry blacklisted more than 800 NGOs only in the north-eastern region of the country for links with extremist groups. This is dragging down the NGO sector from performing the role that it must play for the overall growth of the nation and its economy (Module 5: Effective NGO Governance).
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Volume 3 ISSN 0975-0746 2. Review of Literature A brief review of the different pains of research in this field is attempted in the following paragraphs. Garain‘s (1993) study made an effort to develop an instrument for measuring organizational efficiency of NGO. The study was conducted in West Bengal. Having followed a systematic and exhaustive process, he identified eight dimensions and twenty-eight items. The instrument was consistent with the concept of Organizational Effectiveness used in the study. Sachchidananda et al. (1994) completed a study on 'Tribal Development and Voluntary Action' to review the activities of the Badlao Foundation in some districts of the 'Santhal Pargana Division' in Bihar. This organization has been working for more than ten years in the field of tribal development with support from the state government, central government and international donor agencies. Its main center of attention is on women's development, economic upgradation and additional service for education as well as health. The study made an attempt to offer a number of suggestions to improve the condition and to modernize the work so that it becomes effective and fruitful. Kapoor (1995) conducted a research project on "Women and Welfare—A Study of Voluntary Agencies" in Punjab. The study explored the changing nature and dimensions of voluntary action towards women welfare by understanding the working of four voluntary agencies—Association for Social Health in India, Bharatiya Grameen Manila Samiti, Nari Niketan, and Sewa Sadan—along with their subsidiary units. The study brought out the points of strength and weakness of voluntary agencies and suggested ways to tackle the new challenges, in view of the changing roles and increasing needs of women. Bhattacharjee (1996) completed a study on "NGO Approaches to Health and Development in India: Strategies and Sustainability." He observed that, an NGO will have to make long-term commitments to the community in order to achieve significant and sustainable results. To do so, it has to depend upon government, donors and internal resources. Abdul-Rahman, A. and Goddard, A. (1998) initiated a study on ―An Interpretive Inquiry of Accounting Practices in Religious Organisations. The study of accounting practices was rooted in two religious organisations in Malaysia. The research was an attempt to study accounting practices in a cultural setting. The study also makes a contribution towards the need for accounting research to become more explanatory of accounting as social practice and is developed by observation. This is achieved by developing grounded theory from the data and is in accordance with recent calls for case studies in accounting research to be more concerned with producing social theories of accounting practice. Forbes (1998) conducted an extensive 20-year review of empirical studies in NGOs that addressed the concept of effectiveness. Forbes included quantitative archival data, such as financial reports and operational statements, as measures of effectiveness. He concluded that effectiveness in not for-profit settings is a complex concept that was not only difficult to measure but also required a multidimensional approach and consideration of multiple constituents. Seshagiri (1999) observed that neither too much nor too should less importance be given to the non-governmental organizations. NGOs are
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Volume 3 ISSN 0975-0746 undoubtedly significant as vital gap fillers and conduits between the governing and governed bodies. She concluded that the NGO phenomenon is an indication of organisational improvement to respond to irregular market trends and an affirmation of the irreducible autonomy of individuals and communities, against an active state. Alnoor Ebrahim‘s (2003) study on ―Accountability in Practice: Mechanisms for NGOs‖ examines how accountability is practiced by nongovernmental organizations. Five broad mechanisms are reviewed: reports and disclosure statements, performance assessments and evaluations, participation, self- regulation, and social audits. Each mechanism, distinguished as either a ―tool‖ or a ―process,‖ is analyzed along three dimensions of accountability: upward– downward, internal–external, and functional–strategic. It is observed that accountability in practice has emphasized ―upward‖ and ―external‖ accountability to donors while ―downward‖ and ―internal‖ mechanisms remain comparatively underdeveloped. Moreover, NGOs and fund providers have focused primarily on short-term ―functional‖ accountability responses at the expense of longer-term ―strategic‖ processes necessary for lasting social and political change. The conclusive sum of this retrospective review of the relevant literatures produce till date on the offered subject reveals wide room for the validity and originates of this work and reflects some decisive evidences that affirm its viability, as may be marked here it. Nor has any previous research measured the NGO governance as well as NGO accountability for establishing good governance in West Bengal at a time. No study has incorporated in this fashion before the present work.
2.1 Objectives of the study The main objective of the present work is to observe the trends of NGO accountability for establishing good governance in West Bengal. More specifically, it seeks to dwell upon mainly the following issues: (1) To assess the role of NGOs regarding governance in West Bengal; (2) To suggest the best possible ways for improvement of the role of NGOs regarding governance; Many more similar issues can be raised. However, the ultimate purpose will be to make the study focused in the line of main objective.
2.2 Hypothesis To test the hypothesis, the present study pursued to test the following: Null hypothesis (H0) is that around 50% (fifty percent) of the selected NGOs follow the norms of good governance in West Bengal. Alternative hypothesis (H1) is that (a) More than 50% (fifty percent) of the selected NGOs follow the norms of good governance (+ve result indicates (a) is true) and (b) less than 50% (fifty percent) of the selected NGOs follow the norms of good governance (-ve result indicates (b) is true).
3. Methodology An appropriate methodology has been pursued to carry out the present research work. It encompasses the Universe of the Study, Sampling Structure and Method, sample size, data source and tools used. 88 | Business Perspectives
Volume 3 ISSN 0975-0746 3.1 Universe of the Study The location of the study was West Bengal as recognized by the Planning Commission as the ―Socio-economically Backward in India‖ (Wikipedia). The state West Bengal was selected so that findings from this preliminary study may be used to design a more in-depth study on a larger scale. This research work was thus restricted to all the districts of West Bengal. West Bengal and the characteristics of all the districts in West Bengal are not different. There were 100150 NGOs registered under the Information of Society Registration Office in West Bengal as on 31.03.2009. It was also informed from the same office that 30150 NGOs were just existed only in papers, 70000 NGOs were operated in papers but it was clear from the field survey that only 34500 registered NGOS really operated in West Bengal.
3.2 Sampling Structure and Method After finalizing the registered NGOs really operated in the field, it has been collected from the field survey that 8625 registered NGOs have audited and published their annual reports regularly. From the audited and published NGOs, we have taken 20 per cent for each district in West Bengal for sampling purposes.
3.3 Sample Design Out of 34500, total 8625 NGOs who audited and published their annual reports regularly are taken as the population for the study. From the 8625 NGOs we have selected 1725 NGOs (20 per cent of the population). The simple random sampling without replacement (SRSWOR) method has been used on these 1725 NGOs. 640 NGOs were rejected through sampling and the remaining 1085 NGOs were then approached to supply annual reports for ten years starting from 2000-01 to 2009-10. Out of 1085 NGOs, 346 NGOs responded very negatively and they are not willing to supply any data and reports (NWSDR). Annual reports and data are not available (DNA) for 10 years in case of 427 NGOs. Only 312 NGOs responded favorably and annual reports and data are available for 10 years in case of only 312 NGOs. Thus, sample size stood at 312 NGOs. However, these 312 NGOs spread up in all the districts of West Bengal as their focused area of operation. The description of the sample is given in table-1
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Volume 3 ISSN 0975-0746 Table-1: District-wise representation of the sample NGOs Number of Total % of DNA for sample NGOs Districts selected Rejected NWSDR sample ten years based on NGOs NGOs SRSWOR 24-parganas 82 51 74 61 22.76 (N and S) Bankura 268 28 15 7 9.46 Birbhum 87 74 18 22 14 16.09 Burdwan 52 23 11 10 8 15.38 Coochbehar 41 17 9 8 7 17.07 Darjeeling 68 23 29 12 4 5.88 Dinajpur 33 7 17 4 5 15.15 (N and S) Hooghly 36 17 5 6 8 22.22 Howrah 138 24 8 79 27 19.57 Jalpaiguri 71 18 6 35 12 16.90 Kolkata 536 256 93 90 97 18.10 Malda 87 43 15 18 11 12.64 Medinipur 140 38 27 39 36 25.71 (E and W) Murshidabad 13 4 3 4 2 15.38 Nadia 48 23 15 2 8 16.67 Purulia 33 8 11 9 5 15.15 Total 1725 640 346 427 312 18.09 Source: Field Survey (2010-11)
3.4 Data Source The study is based on primary data for the period from 2001 to 2010.Primary data were collected through structured questionnaire (Appendix-1) and unstructured interview schedules with NGO leaders, members, beneficiaries, secretaries, presidents and accountants of selected NGOs under study. The primary data was supplemented by field survey as well as discussion with NGO officials.
3.5 Period of the Study The study relates to the period of a first decade of the New Century, starting from 2000-01 and ending on 2009-10.
3.6 Tools Used For the purpose of examining the accounting and reporting practices of NGOs operating in West Bengal, data collected through questionnaire have been duly processed, tabulated and analyzed using chi square test and z test (Test of proportion). These statistical tests reveal how far the hypothesis is justifiable in the light of the information provided by the respondents.
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Volume 3 ISSN 0975-0746 4. Empirical Results and Analysis For the purpose of examining the governance practices of NGOs operating in West Bengal, data collected through questionnaire have been duly processed, tabulated and analyzed using chi square test and z test (Test of proportion). These statistical tests reveal how far the hypothesis is justifiable in the light of the information provided by the respondents.
4.1 Analysis based on Selected NGOs as a whole Table-2 represents the output of the questionnaire that was administered to the selected 312 NGOs. The test statistic Where, O = Observed value, E = Expected value which is assumed to be fifty percent. The observed value of the Chi-Square () distribution is 1314.97
Table-2: Analysis of the output of the questionnaire as a whole Question Question Yes No Yes No No No 1 306 6 9 53 259 2 312 0 10 266 46 3 312 0 11 312 0 4 91 221 12 191 121 5 221 91 13 47 265 6 129 183 14 312 0 7 183 129 15 259 53 8 88 224 16 312 0
All 312 NGOs admitted that they have both internal auditor and statutory auditor and among 312 NGOs, only 6 NGOs (1.92%) get their accounts audited continuously after thee months or six months throughout the year and the remaining 306 NGOs (98.08 %) audit their accounts only after finalization of accounts at the end of the financial year.91 NGOs (29.17%) have a single-tier governance structure i.e. trustees are the final reference point of decision making and the remaining 221 NGOs (70.83%) have a dual tier governance structure i.e. the board is constituted by another larger body called general body. 129 NGOs (41.35%) have closely held governance structure i.e. these NGOs have a board of less than 7 members and a general body of less than 12 members for a long period of time and 183 NGOs (58.65%) have a broad based governance structure having more than7 members in the board and a general body of more than 12 members for a long period of time. Among 312 NGOs only 88 NGOs (28.21%) have trustees or board members who are permanent in nature and 53 NGOs (16.99%) have a board consisting of two or more close relatives. All 312 NGOs admitted that their board is independent enough to recruit control and govern the CEO or Chairman and there is an ideal and clear distinction between the role and functions of the board and managerial staff. 266 NGOs (85.26%) have a clear distinction between executive leadership and legislative leadership. The gender balance in general body and board members of 191 NGOs (61.22%) 91 | Business Perspectives
Volume 3 ISSN 0975-0746 are equitable i.e. more than 25 % either women or men in general body or board. Among 312 NGOs, only 47 NGOs (15.06%) are there in West Bengal where more than 40 % of the board members draw salaries. 259 NGOs (83.01%) have clearly defined policy for recruitment, election, selection of trustees or board members and the board members of all 312 NGOs retire and be re-elected on the basis of rotation. The observed value of Chi-Square () distribution has been compared with the table value (26.30 at 5% level of significance with 16 degrees of freedom). The null hypothesis is rejected as observed value is higher than table value.
Analysis based on District-wise selected NGOs Table 3 provides the district- wise result of the questionnaire which is given below:
Table-3: District-wise analysis of the output of the questionnaire Districts 24-pgs Bankura Birbhum Burdwan Cooch- Darjeeling Dinajpore Hooghly
(N & S) behar (N &S)
Q. Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No No 1 61 0 7 0 14 0 8 0 7 0 4 0 5 0 8 0 2 61 0 7 0 14 0 8 0 7 0 4 0 5 0 8 0 3 61 0 7 0 14 0 8 0 7 0 4 0 5 0 8 0 4 13 48 2 5 5 9 3 5 2 5 3 1 2 3 3 5 5 48 13 5 2 9 5 5 3 5 2 1 3 3 2 5 3 6 21 40 4 3 4 10 3 5 2 5 2 2 3 2 4 4 7 40 21 3 4 10 4 5 3 5 2 2 2 2 3 4 4 8 19 42 2 5 3 11 3 5 0 7 0 4 2 3 2 6 9 3 58 2 5 1 13 2 6 2 5 1 3 1 4 3 5 10 53 8 4 3 12 2 5 3 4 3 4 0 0 5 6 2 11 61 0 7 0 14 0 8 0 7 0 4 0 5 0 8 0 12 38 23 5 2 8 6 3 5 3 4 0 4 3 2 5 3 13 9 52 3 4 3 11 4 4 2 5 1 3 1 4 3 5 14 61 0 7 0 14 0 8 0 7 0 4 0 5 0 8 0 15 52 9 7 0 11 3 8 0 7 0 4 0 5 0 8 0 16 61 0 7 0 14 0 8 0 7 0 4 0 5 0 8 0
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Table-3:District-wise analysis of the output of the questionnaire Districts Howrah Jalpaiguri Kolkata Malda Medini- Murshida Nadia Purulia pore bad (E &W)
Q. Ye Yes No Yes No Yes No Yes No Yes No Yes No Yes No No No s 1 27 0 12 0 91 6 11 0 36 0 2 0 8 0 5 0 2 27 0 12 0 97 0 11 0 36 0 2 0 8 0 5 0 3 27 0 12 0 97 0 11 0 36 0 2 0 8 0 5 0 4 5 22 3 9 22 75 3 8 15 21 2 0 6 2 2 3 5 22 5 9 3 75 22 8 3 21 15 0 2 2 6 3 2 6 13 14 5 7 38 59 5 6 19 17 2 0 2 6 2 3 7 14 13 7 5 59 38 6 5 17 19 0 2 6 2 3 2 8 11 16 4 8 26 71 3 8 10 26 0 2 2 6 1 4 9 8 19 3 9 6 91 4 7 7 29 2 0 5 3 3 2 10 20 7 12 0 92 5 11 0 35 1 0 2 8 0 0 5 11 27 0 12 0 97 0 11 0 36 0 2 0 8 0 5 0 12 16 11 9 3 63 34 9 2 19 17 0 2 7 1 3 2 13 4 23 1 11 7 90 1 10 2 34 0 2 3 5 3 2 14 27 0 12 0 97 0 11 0 36 0 2 0 8 0 5 0 15 18 9 12 0 78 19 11 0 23 13 2 0 8 0 5 0 16 27 0 12 0 97 0 11 0 36 0 2 0 8 0 5 0
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Volume 3 ISSN 0975-0746 Table–4: District wise Acceptance/ Rejection of Null Hypothesis using Chi square test Districts Observed value Remarks 24parganas (North and 286.89 Rejected South) Bankura 28 Rejected Birbhum 61.43 Rejected Burdwan 30.75 Rejected Coochbehar 32 Rejected Darjeeling 22 Accepted Dinajpur(North and South) 22.4 Accepted Hooghly 31.25 Rejected Howrah 106.22 Rejected Jalpaiguri 59.17 Rejected Kolkata 457.73 Rejected Malda 53.82 Rejected Medinipur (East and West) 151.11 Rejected Murshidabad 16 Accepted Nadia 39.75 Rejected Purulia 21.6 Accepted
From Table 4, we get the district wise result of the Chi- Square test where, in every district the null hypothesis is rejected except the district of Darjeeling, Dinajpur(North and South), Murshidabad and purulia. In these districts the null hypothesis is accepted because the table value (26.30 at 5% level of significance with 16 degrees of freedom) is higher than the observed value.
Selected NGOs based on questionnaire The test static Observed value (P) – expected value (μ) Z = ------S.E. Or, Sample means (P) -- population means (μ) ------S.E. P – μ Or, Z = ------μ n For testing significance at 5% level, the null hypothesis H0 is rejected when the value of z is either greater than 1.645 or less than -1.645. If Z > 1.645 then H1 (a) is true and if Z< -1.645 then H1 (b) is true. Following the methodology mentioned above, z values have been calculated against each
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Volume 3 ISSN 0975-0746 of the 16 questions for all the districts of West Bengal. The results and its implications are briefly explained in table 5.
Table 5 Acceptance/Rejection of Null Hypothesis using Z values Districts Q. 24parganas Dinajpore Cooch- Darjee- NO (North & Bankura Birbhum Burdwan (North & Hooghly behar ling South) South) 1 -17.47 -17.64 -17.62 -17.64 -17.64 -17.65 -17.65 -17.64 2 -17.47 -17.64 -17.62 -17.64 -17.64 -17.65 -17.65 -17.64 3 -17.47 -17.64 -17.62 -17.64 -17.64 -17.65 -17.65 -17.64 4 -17.62 -17.66 -17.65 -17.65 -17.66 -17.65 -17.66 -17.65 5 -17.51 -17.65 -17.64 -17.65 -17.65 -17.66 -17.65 -17.65 6 -17.60 -17.65 -17.65 -17.65 -17.66 -17.66 -17.65 -17.65 7 -17.54 -17.65 -17.63 -17.65 -17.65 -17.66 -17.66 -17.65 8 -17.60 -17.66 -17.65 -17.65 -17.66 -17.66 -17.66 -17.66 9 -17.65 -17.66 -17.66 -17.66 -17.66 -17.66 -17.66 -17.65 10 -17.49 -17.65 -17.63 -17.65 -17.65 -17.65 -17.66 -17.64 11 -17.47 -17.64 -17.62 -17.64 -17.64 -17.65 -17.65 -17.64 12 -17.54 -17.65 -17.64 -17.65 -17.65 -17.66 -17.65 -17.65 13 -17.64 -17.65 -17.65 -17.65 -17.66 -17.66 -17.66 -17.65 14 -17.47 -17.64 -17.62 -17.64 -17.64 -17.65 -17.65 -17.64 15 -17.50 -17.64 -17.63 -17.64 -17.64 -17.65 -17.65 -17.64 16 -17.47 -17.64 -17.62 -17.64 -17.64 -17.65 -17.65 -17.64
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Volume 3 ISSN 0975-0746 Table 5 Acceptance/Rejection of Null Hypothesis using Z values
Districts Q. 24parganas Dinajpore Cooch- Darjee- NO (North & Bankura Birbhum Burdwan (North Hooghly behar ling South) &South) 1 -17.58 -17.63 -17.37 -17.63 -17.55 -17.66 -17.64 -17.65 2 -17.58 -17.63 -17.35 -17.63 -17.55 -17.66 -17.64 -17.65 3 -17.58 -17.63 -17.35 -17.63 -17.55 -17.66 -17.64 -17.65 4 -17.65 -17.65 -17.59 -17.65 -17.62 -17.66 -17.64 -17.66 5 -17.59 -17.64 -17.42 -17.64 -17.60 -17.66 -17.66 -17.65 6 -17.62 -17.65 -17.54 -17.65 -17.60 -17.66 -17.66 -17.66 7 -17.62 -17.64 -17.47 -17.64 -17.61 -17.66 -17.64 -17.65 8 -17.63 -17.65 -17.58 -17.65 -17.63 -17.66 -17.66 -17.66 9 -17.64 -17.65 -17.64 -17.65 -17.64 -17.66 -17.65 -17.65 10 -17.60 -17.63 -17.37 -17.63 -17.55 -17.66 -17.64 -17.66 11 -17.58 -17.63 -17.35 -17.63 -17.55 -17.66 -17.64 -17.65 12 -17.61 -17.64 -17.46 -17.64 -17.60 -17.66 -17.64 -17.65 13 -17.65 -17.66 -17.64 -17.66 -17.66 -17.66 -17.65 -17.65 14 -17.58 -17.63 -17.35 -17.63 -17.55 -17.66 -17.64 -17.65 15 -17.61 -17.63 -17.41 -17.63 -17.59 -17.66 -17.64 -17.65 16 -17.58 -17.63 -17.35 -17.63 -17.55 -17.66 -17.64 -17.65
Based on the analysis of questionnaire collected from NGOs of different districts we summarize the result of z values in table 5. The null hypothesis is rejected in all cases as Z < -1.645.
Suggestions and recommendations 1. All NGOs should not have single-tier governance structure where trustees are the final reference point of decision making but NGOs should have a dual tier governance structure where the board is constituted by another larger body called general body. 2. All NGOs are recommended to have a broad based governance structure having more than7 members in the board and a general body of more than 12 members for a long period of time. NGOs should not have closely held governance structure. 3. All NGOs are recommended that they should not have trustees or board members who are permanent in nature and a board consisting of two or more close relatives. 4. All NGOs are suggested that their board should be independent enough to recruit control and govern the CEO or Chairman and there should
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Volume 3 ISSN 0975-0746 have an ideal and clear distinction between the role and functions of the board and managerial staff. 5. All NGOs are suggested to have a clear distinction between executive leadership and legislative leadership. 6. The gender balance in general body and board members of NGOs should be equitable i.e. more than 25 % either women or men in general body or board. 7. More than 40 % of the board members should not draw salaries. Not more than 2-3 employees should be board members with voting rights or at any point the employees‘ participation should not exceed 40% of the board members. If two or more employees are on the board then they should not be relatives. 8. All NGOs are recommended to have a clearly defined policy for recruitment, election, selection of trustees or board members and the board members of all NGOs should retire and be re-elected on the basis of rotation. 9. The induction of new trustees should be through an open process providing the opportunity of being elected /selected to a wider group of stakeholders. The process should include use of methodologies such as advertising for new trustees through various medium. 10. The board should meet once at least in every quarter. An annual report on the financial or other contributions of the board members should be prepared to assess the stakes and ownership of the board members. 11. The board should appoint the statutory auditor and the internal auditor. Both the auditors should directly report to the board. The board should determine and approve the annual budget and allocations. The board should determine and approve the bank accounts to be operated and the signatories thereof
Selected References: 1. Venkatesha S. Sampa. (2010), Sampada Foundation, Sampa Saalu Kannada Magazine (RNI No. KARKAN/2008/29456). 2. Marilyn Wyatt, (2010) ―Access, Accountability and Advocacy: The Future of Nonprofit Governance is Now‖, no date 3. Adapted from An NGO Training Guide for Peace Corps Volunteers, Module 5: Effective NGO Governance, pages 148, no date. 4 4. Garain, S. (1993), ―Towards a Measure of Organizational Effectiveness for Non Governmental Organizations‖,The Indian Journal of Social Work, Vol.LIV, No, pp.251- 270. 5. Sachchidananda et al., (1994), ―Tribal Development and Voluntary Action‖, Inter-India Publications: New Delhi 6. Kapoor, U. (1995), "Women and Welfare—A Study of Voluntary Agencies", Indus Publishing Company: New Delhi 7. Bhattacharjee, S.(1996), "NGO Approaches to Health and Development in India: Strategies and Sustainability." M.A. Dissertation, Prins Leopold Instituutvoor Tropische Geneeskunde : Belgium. 8. Abdul-Rahman, A. and Goddard, A.1998, ―An Interpretive Inquiry of Accounting Practices in Religious Organisations‖. Journal of Financial Accountability and Management, Vol.-14, Issue-3, pp-183-201.
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Volume 3 ISSN 0975-0746 9. Forbes, D. 1998, ―Measuring the Unmeasurable: Empirical Studies of Nonprofit Organization Effectiveness from 1977 to 1997‖, Nonprofit and Voluntary Sector ,Quarterly 27, no. 2,pp-183-202. 10. Seshagiri,S. (1999), ―Role of the Indian State and Ngos in Public Health‖, M. Phil Dissertation. Centre for political Studies, Jawaharlal Nehru University, New Delhi (Unpublished). 11. Ebrahim, A. 2003, ―Accountability in Practice: Mechanisms for NGOs‖, World Development, Vol.31, Issue : 5, pp-813-829.
Appendix
1. Does your NGO have regular audits? Yes: __ No ------2. Does your NGO have any internal auditor? Yes ------No ------3. Is your account audited by statutory auditor? Yes ------No ------4. Does your NGO have a single tier governance structure i.e. trustees are the final reference point of decision making? Yes ------No ------5. Does your NGO have a dual tier governance structure i.e. where the board is constituted by another larger body called general body? Yes ------No ------6. Whether the governance structure is closely held? Yes ------No ------7. Whether the governance structure is broad based? Yes ------No ------8. Does the NGO have trustees or board members who are permanent in nature? Yes ------No ------9. Whether the board of the society is having two or more close relatives? Yes ------No ------10. Is there a clear distinction between executive leadership and legislative leadership? Yes ------No ------11. Is the board independent enough to recruit, control and govern the CEO or chairman? Yes ------No ------12. Is the gender balance in general body and board members equitable? Yes ------No ------13. Does more than 40 % of the board member draw salaries? Yes ------No ------14. Is there an ideal and clear distinction between the role and functions of the board and managerial staff? Yes ------No ------15. Is there any clear defined policy for recruitment, election, selection of trustees or board members? Yes ------No ------16. Do the board members retire and be re-elected on the basis of rotation? Yes ------No ------
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Volume 3 ISSN 0975-0746 PROFITABILITY ANALYSIS – A CASE STUDY OF PUBLIC SECTOR GENERAL INSURANCE COMPANIES IN INDIA
Mahasweta Bhattacharya Assistant Professor, Department of Commerce, Santipur College
Abstract This paper investigated the profitability position of the general insurance companies of India. Insurance services are now being integrated into wider financial industry and the insurance sector plays an important role in service based economy of India. This study is based on secondary data obtained from the Annual Reports of the respective companies and in the course of analysis, descriptive statistics, correlation statistics and multiple regression test have been designed. Descriptive statistics indicates that profitability position is not satisfactory and correlation is fantastically strongly associated with gross profit and commission. Multiple correlation test results show that the relationships are existed between profitability and investment income.
Keywords: Profitability indicators, public sector, general insurance company, India, multiple regression analysis.
Introduction Insurance industry acts as a crucial role in the economic growth of an economy. A strong insurance market covers approach for well-organized resource allocation in the course of transfer of risk and enlistment of savings. The general insurance industry was nationalized in 1972. However, the General Insurance Corporation was set up as a holding company with four subsidiaries of New India, Oriental, United India and National Insurance Companies. It was implicit that the companies would struggle with one another in the market; nonetheless, the same could not take place then although was achievable merely after 29 years (Rao, 2000). The historical point of view of the general insurance companies expose that the speedy development of insurance companies since nationalization had specified augment to a number of difficulties connected to the reflection, operational effectiveness, productivity and the quality of portfolio of the scheme all together and there have been constant grievances concerning decline in customer service (Rohit & Manjit, 2009). But because of reform policy the insurance diffusion increased below 1 per cent in the case of GIC that is far away from life insurance on account of poor profitability performance (IRDA, 2011-12). The critical reply explicitly obligatory from the accessible public insurers is obvious that they must stay behind aggressive by doing things improved as well as quicker and by ensuring cost usefulness with performance. Huge number of proposals has been taken by these public sector companies to fight with private sector companies. But still the public sector companies need to reconsider their present status after having modified their move toward and attitude in the post- reform period. Today, in this liberalized world, to facilitate maintain them, the insurance companies have to ensure quality products at a competitive price. Companies can lower the price of the product by reducing the cost. Their continued existence depends upon their performance in profitability, productivity, efficiency and service quality (ICRA, 2008). However, the present study is an
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Volume 3 ISSN 0975-0746 attempt to examine the profitability of the non-life public sector insurance companies over a period of eight years.
Literature review Deloittie and Touche (2004) examined the profitability as well as efficacy of the federal Multi Peril Crop Insurance (MPCI) programme using secondary data on both the MPCI business, and the property and casualty insurance business for the period from 1992 to 2002. The empirical results designated that the MPCI line of business does not possess risk return advantages relative to the P & C business because of net losses. Dhanda (2004) appraised the performance of non-life insurance companies based on both primary and secondary data for the period from 1957 to 1990. It was create that the growth of individual business had not been very consistent during the period from 1957 to 1990. The share of individual business remained more than 50 per cent in total business. The profitability analysis showed that more than 60 per cent of total income was received by way of premium income and the remaining income was earned by investing funds. Hoyt and Powell (2006) observed the financial performance of medical liability insurer by using economic combined ratio and the return on equity for the period from 1996 to 2004. The study establishes that there was no proof that medical liability insurers had been earning excessive returns or that they were over-capitalized. The study wrapped up that there was no evidence that medical malpractice insurance was overpriced. Mahmoud (2008) assessed the financial performance of insurance companies in Egypt based on the data consisted of three public sector and three private sector non-life companies for the period from 1992-93 to 2005-06 using 25 ratios to measure the efficiency and financial performance with the application of factor analysis for data reduction. The study establish that the mean of efficiency of financial performance do not vary notably under the study. Public sector belongings correspond to 66.7 per cent of the low-efficiency clusters of financial performance, while private sector cases comprise 47.6 per cent of high- efficiency clusters for financial performance. Consequently, there is a relationship between the fuzzy classification of the insurance company's financial performance efficiency and its ownership type The above review points out that while a large number of studies have been conducted on non-life insurance sector at the international level but a few studies have been conducted on the profitability analysis of the general insurance sector in Indian public sector general insurance companies. No proper study has been conducted to assess the profitability of the public sector general insurance companies in India. Therefore, there exists a research gap and this study titled, ―Profitability Analysis – A Case Study of Public Sector General Insurance Companies in India‟ is an attempt to fill this gap.
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Volume 3 ISSN 0975-0746 Objectives of the study The specific objectives of the study are as follows: 1. To evaluate the profitability of Public Sector General Insurance companies under the study; 2. To make suggestions to improve the profitability of the General Insurance Industry in India.
Research methodology The study is based on secondary data. Most of the facts and figures originate from extensive research of an array of publicly available data in the form of annual reports, books, reports etc. Secondary data have been collected from the relevant Annual Reports, Statistical Handbooks of GIC of India and various news bulletins of the IRDA. The Annual Reports of Insurance Regulatory and Development Authority (IRDA) and other related literature available both as hard copy and on the web-journals/reports have also been consulted. This study covers all the four public sector non-life insurance companies engaged in general business (i.e. other than the two specialized insurance companies) in India. Table 1 below, discloses the name of the four companies: i. Table – 1: Name of the four public sector non-life insurance companies No. Name of the Companies 1 National Insurance Company Limited (NICL) 2 New India Assurance Company (NIACL) 3 Oriental Insurance Company Ltd (OICL) 4 United India Insurance Company Limited (UIICL)
The study is based on population rather than on samples. The study covers a period of 8 years from 2000-01 to 2007-08. The data so collected were analyses with the help of appropriate statistical tools SPSS to get the result of Correlation co-efficient and multiple regressions. The dependent variable is defined as the profitability of the sample companies. The independent variable is interpreted as Gross Premium, Net Premium, Claim, Commission, and Income from Investment. Regression technique deals with the procedure of determining an equation for estimation. Now the variable to be estimated is called the dependent variable, while the variable acts as a basis of estimation is known as independent variable. In a simple regression there is only one independent variable. For two or more independent variables and one dependent variable, we find multiple regressions. Object of regression analysis is to estimate the dependent variable from known values of independent variable and to obtain a measure of the error involved in using the regression line for estimation.
Present status of non-life insurance industry in India The outline of insurance business has been changing across the globe with the progress of time and the ripple effect of the same is seen in the Indian market as well. Insurance sector is of vital importance for economic growth of any country. The origin of insurance business has been developed from the concept of safeguarding the interests of people from uncertainty by providing 101 | Business Perspectives
Volume 3 ISSN 0975-0746 certainty of payment at a given contingency. General or non-life insurance provides much-needed protection against unforeseen events such as accidents, illness, fire, burglary etc. Unlike life insurance, general insurance is not meant for returns but is protection against contingencies. In India insurance business has had a chequered past. The growth and development of general insurance in India started in 19th century. In 1850, Triton Insurance Co. Ltd., the first general insurance company was established in India by British but in 1907 first Indian general insurance company named Indian Mercantile Insurance Co. Ltd. was established. Prior to nationalization of insurance sector, the insurance market in India had a much diluted presence. The entire general insurance business was nationalised in the year 1972 and General Insurance Corporation (GIC) was formed with four fully owned subsidiary companies having sole power to operate general insurance business. These four companies, National Insurance Company Ltd., The New India Assurance Co. Ltd., The Oriental Insurance Co. Ltd. and United India Insurance Co. Ltd functioned under government control for almost three decades. Towards the end of 20th Century the Government of India accepted the concept of liberalization and adopted the policy of open market economy. As a result many private players both domestic and foreign commenced insurance business in India since 2000, which ended the monopoly of the PSUs. This led to a serious debate about the pros and cons of liberalization. Malhotra Committee on Reforms in the Insurance Sector favoured mixed arrangement of public and private sector insurance companies. Therefore, India adopted the latter alternative viz. to generate competition without dismantling the public sector. As we have taken four public sector non-life insurance sector for our study, following four tables, No.2 to 5 illustrate the absolute figures along with growth rate of Gross Premium, Net Premium, Claim Settled, Commission Paid, Investment Income of four public sector non-life insurance companies for the period starting from 2000-01 to 2007-08 :
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Volume 3 ISSN 0975-0746 ii. Table – 2: National Insurance Company Limited (NICL) (Rs. In Lakh) Year 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 Gross 211788 243941 286987 339997 381065 353634 382712 402197 Premium Growth (%) 15.18 17.65 18.47 12.08 -7.20 8.22 5.09 Net Premium 170471 181698 196596 238781 266414 276317 276757 301853 Growth (%) 6.59 8.20 21.46 11.57 3.72 0.16 9.07 Claim 146163 172510 161966 210990 226350 283033 239422 283884 Growth (%) 18.03 -6.11 30.27 7.28 25.04 -15.41 18.57 Commission -181 -1031 4534 7173 7749 14055 11405 20389 Growth (%) 469.61 -539.77 58.20 8.03 81.38 -18.85 78.77 U/W Result -24789 -46252 -30155 -52683 -53705 -109032 -54617 -92190 Growth (%) 86.58 -34.80 74.71 1.94 103.02 -49.91 68.79 Investment 40329 43978 48587 66268 68517 100976 105480 118092 Income Growth (%) 9.05 10.48 36.39 3.39 47.37 4.46 11.96 PBT 8938 -9395 13943 7301 14121 -5964 45583 17206 Growth (%) -205.11 -248.41 -47.64 93.41 -142.23 -864.30 -62.25 Source: Annual Reports of National Insurance Co. Ltd.2000-2008
iii. Table – 3: New India Assurance Company (NIACL) Year 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 Gross 304117 419806 481279 492147 510316 567554 593678 615197 Premium Growth (%) 38.04 14.64 2.26 3.69 11.22 4.60 3.62 Net Premium 257646 285887 329716 358946 376717 412099 453511 481143 Growth (%) 10.96 15.33 8.87 4.95 9.39 10.05 6.09 Claim 227973 255514 269951 271358 290498 363201 364361 417748 Growth (%) 12.08 5.65 0.52 7.05 25.03 0.32 14.65 Commission 480 7982 19314 21362 33188 37628 39089 45924 Growth (%) 1562.92 141.97 10.60 55.36 13.38 3.88 17.49 U/W Result -45325 -55392 -48608 -68910 -68425 -119419 -65198 -84439 Growth (%) 22.21 -12.25 41.77 -0.70 74.53 -45.40 29.51 Investment 79585 85716 88100 126679 149253 208294 225507 234619 Income Growth (%) 7.70 2.78 43.79 17.82 39.56 8.26 4.04 PBT 23884 20820 31282 64789 79788 85557 161393 152146 Growth (%) -12.83 50.25 107.11 23.15 7.23 88.64 -5.73 Source: Annual Reports of New India Assurance Co. Ltd.2000-2008
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Volume 3 ISSN 0975-0746 iv. Table – 4: Oriental Insurance Company (OICL) Year 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 Gross 219967 249864 286815 289974 309055 360977 402078 390022 Premium Growth (%) 13.59 14.79 1.10 6.58 16.80 11.39 -3.00 Net Premium 168387 182072 185577 197246 212317 235584 269077 287623 Growth (%) 8.13 1.93 6.29 7.64 10.96 14.22 6.89 Claim 150206 182791 146655 158765 190838 206474 235886 260222 Growth (%) 21.69 -19.77 8.26 20.20 8.19 14.24 10.32 Commission -4520 -2337 -1211 2890 8457 10340 9962 13135 Growth (%) -48.30 -48.18 -338.65 192.63 22.27 -3.66 31.85 U/W Result -27600 -59316 -25077 -46288 -61139 -66306 -52194 -68095 Growth (%) 114.91 -57.72 84.58 32.08 8.45 -21.28 30.47 Investment 39571 43762 48200 94313 108219 111751 116010 114315 Income Growth (%) 10.59 10.14 95.67 14.74 3.26 3.81 -1.46 PBT 7513 -23486 17589 45433 47170 33419 62964 44235 Growth (%) -412.60 -174.89 158.30 3.82 -29.15 88.41 -29.75 Source: Annual Reports of Oriental Insurance Co. Ltd.2000-2008
v. Table – 5: United India Insurance Company (UICL) Year 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 Gross 244109 278148 296963 306347 294446 315478 349877 373956 Premium Growth (%) 13.94 6.76 3.16 -3.88 7.14 10.90 6.88 Net Premium 182204 197280 210938 213663 216265 219433 237324 270209 Growth (%) 8.27 6.92 1.29 1.22 1.46 8.15 13.86 Claim 177693 178081 190546 184217 199853 204277 214206 250628 Growth (%) 0.22 7.00 -3.32 8.49 2.21 4.86 17.00 Commission -5618 -1753 -1931 885 1999 6398 6776 13661 Growth (%) -68.80 10.15 -145.83 125.88 220.06 5.91 101.61 U/W Result -42124 -45308 -39916 -53967 -74669 -88907 -73104 -85335 Growth (%) 7.56 -11.90 35.20 38.36 19.07 -17.77 16.73 Investment 48564 62431 67100 94560 107029 140042 131426 157725 Income Growth (%) 28.55 7.48 40.92 13.19 30.84 -6.15 20.01 PBT 907 15669 21416 39339 31830 45274 52034 65814 Growth (%) 1627.56 36.68 83.69 -19.09 42.24 14.93 26.48 Source: Annual Reports of United India Insurance Co. Ltd.2000-2008
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Volume 3 ISSN 0975-0746 Descriptive statistics as whole Descriptive statistics include measures of central tendency such as mean, measures of variability such as the coefficient of variation and measures of distribution, such as skewness and kurtosis that indicate how much a distribution varies from a normal distribution. Descriptive statistics shows that mean and C.V. in terms of growth indicators are not satisfactory than industry average under the study in case of all the indicators during the period under study. This is an indication of unsatisfactory growth management performance. Skewness, Kurtosis authenticates that none of the variables are normally distributed, which is shown in table 6.
Table-6: Descriptive Statistics as a whole GP NP CLAIM COMM U/W INVINC PBT Mean 9.0611 7.9871 8.6629 71.425 22.812 18.523 6.8260 Std. 2.0189 1.5109 2.4779 127.19 10.746 1.0193 196.91 Deviation C.V. (%) 22.30 18.90 28.64 178.06 47.13 5.51 2736.6 Skewness -.710 -1.221 -1.160 1.729 .426 .049 .465 Kurtosis .303 1.611 2.204 3.245 -2.849 -5.576 .570 Minimum 6.41 5.88 5.21 -27.43 12.46 17.59 -211.90 Maximum 11.15 9.38 11.10 257.94 35.76 19.54 258.93 N 4 4 4 4 4 4 Industry Average GP NP CLAIM COMM U/W INVINC PBT Mean 17.145 13.667 13.892 94.003 30.054 31.251 41.234 Std. 5.156 3.024 4.123 97.655 46.222 4.025 208.21 Deviation C.V. (%) Skewness -1.112 -2.036 -2.243 1.856 0.867 .056 0.859 Kurtosis 0.423 1.682 1.974 3.087 -2.114 -4.234 0.682
Correlation statistics Pearson‘s correlation analysis is used to see the strength and direction of the relationship between major components of revenue, expenses and profitability. Table 7 displays Pearson correlation coefficients and significance values. Pearson correlation coefficients assume the data are normally distributed. It is a measure of linear association between two variables. If the significance level or probability is less than 0.05, then the correlation is significant and the two variables are linearly related. If the significance level is moderately large or more than 0.50 then the correlation is not significant and the two variables are not linearly related.
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Volume 3 ISSN 0975-0746 Table- 7: Correlation Test Results GP NP CLAIM COMM U/W INVINC PBT GP 1 NP .545 1 .206 CLAIM -.189 .571 1 .685 .180 COMM -.184 -.014 .533 1 .694 .976 .218 UW -.353 .293 .945(**) .667 1 .437 .524 .001 .102 INVINC -.465 .262 .696 .100 .659 1 .294 .570 .083 .832 .107 PBT .046 .665 .699 .080 .539 .286 1 .921 .103 .081 .864 .212 .534 ** Correlation is significant at the 0.01 level (2-tailed). Note: The p-value is given in addition
Correlation test result is unbelievably powerful in case of gross profit and commission. However it does not talk about the justification of the relationship. To facilitate suggest an unambiguous explanation of the alarm; it is mandatory to carry out multiple regression tests between the selected variables.
Multiple regression test results Multiple correlations and multiple regression analysis of four insurance companies have been tabulated in Table 8.
vi. Table – 8: Multiple Regression Test Results Model B Std. Error t value Significance VIF Constant -552.45 972.170 -0.568 0.671 Inv Income -15.813 4.785 -3.304 0.187 1.088 U/W 49.668 50.450 -0.985 0.505 1.088 R = 0.968, R2 = 0.937, Adj. R2 = 0.812, Std. Error Of the estimate = 8.3898, F=7.478, Durbin-Watson statistic=1.973 a. Predictors: (Constant), investment income, u/w b. Dependent Variable: PBT
The strength of the relationship between the dependent variable, PBT and all the independent variables taken together and the impact of these independent variables on the profitability are given in Table 8. After numerous run in the SPSS, GP, NP, claim and commission have been removed from the model because of solving the multi-collinearity problems. It was observed from the above that an increase in investment income by one unit; the PBT decreased by 15.813 units that were statistically insignificant at
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Volume 3 ISSN 0975-0746 5 per cent level. Again, when U/W increased by one unit, PBT increased by 49.668 units which were statistically insignificant at 5 per cent level. The Multiple correlation coefficient between the dependent variable PBT and the independent variables Gross Premium, Net Premium, Claim, Commission and Investment Income taken together was 0.968. It indicates that the profitability was highly responded by its Gross Premium, Net Premium, Claim, Commission and Investment Income. It is also evident from the value of R2 that 93.7 per cent of variation in PBT was accounted by the joint variation in Gross Premium, Net Premium, Claim, Commission and Investment Income that indicates the model robust the data well. Adjusted R2 (81.2 per cent) indicates that the co-efficient of determination which is positively associated in the regression equation. The value of F is 7.478, which examines the significance of all the variables collectively in regression function. The value of the D-W statistics is 1.973, which also strongly advocate in favour of the dependability of the results. VIF measures the multi-collinearity problem, which is the inverse of tolerance value. Based on the value of VIF in tables, there is no multi-collinearity among the variables because VIF is less than 2.
Conclusions Main findings of the study Mean and C.V. in terms of growth indicators are not satisfactory in comparison with industry average under the study in case of all the indicators during the period under study. This is an indication of unsatisfactory growth management performance. Skewness and Kurtosis also indicate that none of the variables are normally distributed. On the basis of the above study if we consider the growth rate of Gross and Net Premium of all public sector non-life insurance companies, they did not show steady trend. As regards underwriting profit we observed that the four public sector non-life companies experienced more under writing losses during the study period because of high amount of claim settled and positive commission incurred. PBT of all public sector non life insurance companies fluctuated widely throughout the course of study. It was observed from the multiple regression that an increase in investment income by one unit; the PBT decreased by 15.813 units that were statistically insignificant at 5 per cent level. Again, when U/W increased by one unit, PBT increased by 49.668 units which were statistically insignificant at 5 per cent level. There is powerful Correlation in case of gross profit and commission. The Multiple correlation coefficient between the dependent variable PBT and the independent variables Gross Premium, Net Premium, Claim, Commission and Investment indicates that the profitability was highly responded by its Gross Premium, Net Premium, Claim, Commission and Investment Income.
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Volume 3 ISSN 0975-0746 Policy implications In view of the findings of our study mentioned, we put forward the following set of suggestions for improvement of the performance of general insurance business in India 1. Due to huge amount of claim, underwriting loss is also huge for all the companies. Claims are uncontrollable on the part of the companies. Therefore the insurance companies should manage the investments portfolio in more professional way, so that underwriting losses are covered with sufficient safety margin. 2. Another way of improving profitability of the companies is to control operating expenses. All the companies should concentrate on this point. 3. Since new players are coming with new innovative products and ideas so public general insurance companies have to change their business strategies for the benefit of their future course of business. 4. To survive in future indigenous non-life insurance companies have to modify their business strategies considering the business role of the private players. 5. Insurance business is the business of mutual trust and faith. So, to maintain the good financial performance public players have to maintain good customer relationship and honest customer service. Otherwise the main ideology of the insurance will be lost.
Limitations of the study This study obviously has some limitations. These are as follows: 1. All the numerical figures or the financial parameters, based on which the calculations were made and the inferences are drawn, had been on the basis of information obtained from secondary sources. 2. In our study we have considered only four public sector non-life insurance companies in India and this might not be true representation of the population. 3. The study covers a period of only eight years from 2000-2001 to 2007- 2008.
Scope for future research At present many academicians as well as researchers have focused their attention to this particular area. Still there are so many areas in this field where further research work could be undertaken. Few such areas are: 1. Comparative analysis of Indian Insurance Sector with the Insurance Sector of SAARC countries. 2. Comparative studies on Marketing Strategy between Indian Public Sector Unit and Private Sector units. 3. Customers‘ perception regarding Public and Private non-life Insurance products. 4. Analysis of customer satisfaction taking customers from both public and private non-life insurance companies.
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Volume 3 ISSN 0975-0746 References 1. Kaur, N and Kapoor, R (2007). Profitability Analysis of Public Sector Banks in India, Indian Management Studies Journal, 11, 167-181. Rohit, K., & Manjit, S. (2009). Emerging Trends in Financial Performance of General Insurance Industry in India. Indian management Studies Journal, 13, 31-44. 2. Insurance Regulatory and Development Authority (IRDA). (2011-12). Report on non- life insurance. New Delhi: Government of India. 3. Rao, T. S. (2000). The Indian insurance industry: The road ahead. Journal of Insurance Chronicle, 1(3), 31. 4. Moody's ICRA Global (2008), "Indian General Insurance Industry Outlook: Major Changes Expected as Deregulation Continues" April. http://www.icra.in/Files/Articles/Insurance-ICRAMoody's -200704.pdf accessed on Aug.10, 2009. Deloittie; and Touche, L. (2004), "Federal Crop Insurance Program: Profitability and Effectiveness Analysis", National Crop Insurance Services in, 2-23. 5. Dhanda, R.L. (2004), "Divisional Performance Evaluation of LIC Business in North Zone", Finance India, Vol. XVIII, No. 1, pp. 229-233. Hoyt, R.E.; and Powell, L.S. (2006), "Assessing Financial Performance in Medical Professional Liability Insurance", Journal of Insurance Regulation, 3-13. Mahmoud, O. (2008), "A Multivariate Model for Predicting the Efficiency of Financial Performance for Property and Liability Egyptian Insurance Companies", Casulty Actuarial Society, 53-78.
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Volume 3 ISSN 0975-0746 MISMANAGED INDUSTRIALIZATION CONCERNING MAN-MADE DISASTER IN BHOPAL GAS TRAGEDY
Suvankar Chakraborty Research Scholar, Department of Commerce, University of Kalyani
1. Introduction A disaster is an incidence that causes damage, ecological disorder, loss of human life or weakening of health and health services on a scale sufficient to warrant an extraordinary response from outside the affected community or area. Rapid industrialization and new technologies have produced new hazards. The harshness and frequency of technological emergencies have increased. With explosion of nuclear power and chemical plants over the last few decades, disasters on the scale of Chernobyl or Bhopal cannot be ruled out (Kulkarni, 2013, p.1). The risks of accidental chemical liberates go up as a number of new risky matters are produced. First, production, transport, and use of flammable, explosive or toxic chemicals have grown significantly in both developing and developed countries. Second, greater and more centralized productions have increased the quantities of chemicals manufactured and the distances across which they are transported throughout the country. Third, in India, population growth nearer to chemical plants and along transportation routes has meant that there are larger communities in great number at high risk following a chemical accident. In India, we have 2,000,000 registered industries, of which more than 5000 are chemical industries (Investopedia, 2012). Consequently, it is obligatory for us to have a disaster management plan and the awareness to turn away any loss of life, human suffering, and economic losses like the frightening event that occurred in Bhopal. Political stability and political will is most needed to force such initiatives in any country (Kulkarni, 2013, p.2). Disaster refers to the serious disruption of the functioning of society, causing widespread human, material or environmental losses, which exceed the ability of the affected communities to cope using their own resources justifying external assistance. In other words a disaster occurs when an extreme event exceeds a community‘s ability to cope with the event. It may be natural and man-made. Bhopal Gas tragedy –a man- mad disaster was one of the world's worst industrial catastrophes. It is often stated that the lack of property rights causes excessive damage to the environment. Because environmental impacts tend to be external in nature there are no monetary transactions compensating for the gains or losses in welfare. With no market mechanism in operation agents take environmental impacts into consideration only if regulated by law or action taken by those affected (Anderson, 1990). Keeping in view of this, this paper observes the experience on Bhopal Gas tragedy and greater awareness of community about the relevance of pre and post disaster management so as to face the crisis situation
2. About Bhopal The capital of Madhya Pradesh, Bhopal is situated on the beautiful Malwa Plateau, the city of lakes Bhopal is about 625 metre high from Mean Sea Level spreading over 285 square kms. Today‘s Bhopal was habituated by Parmar King Bhoj who founded the city in 11th Century and named it Bhopal. As 110 | Business Perspectives
Volume 3 ISSN 0975-0746 a result of constant efforts of former president Dr. Shankar Dayal Sharma, Bhopal became the state capital of Madhya Pradesh in November, 1956. After it became a capital place, Bhopal started growing fast .The Union Carbide India Limited (UCIL), the giant 70 acre pesticide plant was built in 1969 to produce the pesticide Sevin (Union Carbide Corporation (UCC)‘s brand name for carbaryl) using methyl isocyanate (MIC) as an intermediate consumption. Union Carbide Corporation (UCC) owned 50.99 shares in the Bhopal plant .Unfortunately because of the past reputation of UCC, the concerned Government Department including Directorate General of Technical Development(DGTD) and State and Central Level pollution control authorities were not much vigilant about the product-mix otherwise the unit could not be located so close to Bhopal Railway and City Centre.
3. What happened during the night of December 2-3, 1984? During the night of December 2–3, 1984, water entered a tank containing 42 tons of MIC. The resulting exothermic reaction increased the temperature inside the tank to over 200 °C (392 °F) and raised the pressure. The tank vented releasing toxic gases into the atmosphere. The gases were blown by northwesterly winds over Bhopal. The 1984 gas leak in Bhopal was a terrible tragedy that understandably continues to evoke strong emotions even 28 years later. On 3rd December, 1984 just past midnight, an operator in the factory observed something very unusual, he immediately alerted his senior supervisor. The internal alarm rang. Workers rushed to tank E610 and found that the situation was already out of control. The huge tank measuring 40 feet by 8 feet containing the lethal 42 tonnes of liquid MIC had reached a temperature of over 200ºC which need to be kept at a temperature close to 0ºC and therefore it was evident that MIC would turn from liquid to gas and escape from the tank. Soon the tank started vibrating violently that the reinforcement cracked and due to the built up of huge pressure the safety valve opened and the gas escaped into a 70 feet pipeline leading into the vent gas scrubber. Normally, this would not have been dangerous as a flow of caustic soda solution into the scrubber was expected to detoxify the MIC, producing harmless by-products, but unfortunately that night the scrubber was not functioning as it was shut-down because of maintenance, flare tower was designed to burn off gas if escaped, but a connecting pipe had been removed for maintenance. Five point safety systems failed in UCIL on the night of accident because of the following reasons: (i) MIC had to be stored at a temperature close to 0ºC. But the refrigeration system had been closed down as part of a cost-saving measure. Therefore, when the temperature started rising in tank E610, nothing could be done. (ii) A spare empty tank had to be kept empty in order to divert any excess MIC into it which could have reduced the volume of poisonous MIC escaping into the air. But in the panic, nobody thought of opening the valve in order to allow the MIC into the empty tank, E619. (iii) The tank with MIC was attached by one of its pipes at a 30 metre high flare tower, the chimney, where a pilot flame was always kept burning and in case of leak, the flame would burn off all the toxic gas before it could reach the
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Volume 3 ISSN 0975-0746 atmosphere. But unfortunately one of the pipes connecting the scrubber to the flare tower had become corroded and had been removed for replacement. Therefore, the flare tower was disconnected and the pilot flame extinguished. (iv) The other escape route for the gas was through the vent gas scrubber. Normally, caustic soda solution would be released into it to scrub the poison from the gas, neutralizing it into non-toxic substances before letting it out into the atmosphere. But the vent gas scrubber had been turned off and as a result the poisonous gas escaped into the atmosphere. (v) At around 1 a.m. the workers of the plant tried their level best to operate the water curtain on the gas as it escaped, thinking that water would absorb the gas before it is dispersed into the atmosphere. But it was designed to shoot water up to a height of 12 to 15 metres in the air whereas the MIC gas already crossed the height of 33 metres. It was a comedy of errors which forced the poor people of Bhopal like Babu Khan, Mohan Singh, Jiten Koli, Rekha Gaolat, Abdul Aziz, Sona Bai and the list goes on, into the valley of death. It was a scenario straight out of a horror story. It was a cold night. Most people were indoors, asleep. Within two hours past midnight the entire old Bhopal within a radius of eight to ten kilometres were engulfed by the circular chamber of deadly MIC gas. Mohan Singh, the resident of Chhola , just opposite to UCIL plant narrated the scene to me. He said old men using walking sticks, ladies in petticoats and half burqas, children shrieking with their mothers huddled and clinging on to them, formed a massive crowd, some of them got into trucks, tempos, autorickshaws and more affluent escaped in their own vehicles and reached safely to distant places but most of them were coughing and spitting, some even bleeding from mouth, many fainted and even lay dead under the gas effect. He saw in the morning of December,3, 1984 (Monday), at around 8 a.m. a large number of cattle and other animals lying dead, not far from human corpses. The official estimate of the number who died that night is given as 2,000 but unofficially over 8,000 people died in two days‘ time and total death due to the gas disaster crossed 25,000, in some cases the doctors forgot to issue death certificates, which later proved to be a major legal problem for the family of the victims. . Over 1,600 animals died which posed a serious threat of epidemics. They were buried in a one acre plot with the help of 10 bulldozers. There was shock and confusion all around. No one knew what exactly had happened. According to him till 10 a.m. organized official relief measures even at crowed hospitals was eventually non-existent. Police was rarely seen anywhere. Army personnel were, however, doing a commendable job. Doctors and very few nurses on night duty were working hard at Hamidia and other hospitals and reinforcement of nursing personnel started at about 8 a.m. when students of Medical College and junior doctors took charge of the situation. Hamidia Hospital, one of the largest in Bhopal had to handle over 25,000 cases that night which was much beyond their limit. In the gas tragedy the most affected areas apart from Chhola and Jaya Prakash Nagar, are Teela Jamalpur,Nishat Pura, Kechi, P & T Colony, Sindhi Colony, Ibraheempura, Shantinagar, Pir Gate, and Green Park.
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Volume 3 ISSN 0975-0746 4. What happened after the deadly night of December 2-3, 1984? On December 3, Monday, 1984: All offices and educational institutions have been closed down. Chief Minister, Arjun Singh has ordered a judicial inquiry into the tragedy. Four persons responsible for the management and operation of the factory including the Works Manager, J. Mukund, have been arrested under the chief Minister‘s instructions. On December 4, Tuesday, 1984: A relief work picked up as the then Prime Minister Rajiv Gandhi came to Bhopal to assess the magnitude of disaster. Mr Gandhi said he would look into the matter of location of plants like Union Carbide‘s Bhopal Unit in the vicinity of towns and action would be taken after full consideration of all issues. Chief Minister Arjun Singh who was present said the Government was going to demand compensation from the proprietors of the pesticides factory. Cremations and burials were intensified late Tuesday evening as medical experts were reported to have opined that any more delay would cause large scale decompositions leading to terrible pollution hazards. December 5, 1984: In the early hours of Wednesday morning a large number of graves were kept ready for the dead to be brought in the Bara Bagh graveyard near Bhopal Talkies, the same story was seen in the graveyards near Bharat Talkies, Chhola and Ibraheemganj. December 7, 1984: Warren Anderson the Chairman of UCC at the time of Bhopal Gas disaster landed in Delhi on Friday, to personally investigate the disaster. The Delhi police arrested him at the airport on charges of criminal and corporate negligence, leading to culpable homicide. He was detained for six hours in the UCIL guesthouse and then released on a bail of Rs. 25,000. A Union Carbide corporate jet took him back safely to his country. Since then, he never appeared before court. December 12, 1984: the immediate problem after the disaster was how to neutralize the 15 tonnes of MIC that remained in the other tank, E611. On 12th December, Chief Minister, Arjun Singh announced the launch of Operation Faith. It was to take place on 16th December. December 16, 1984: A number of suggestions were given regarding getting rid of the 15 tonnes of MIC but finally it was decided that the MIC would be neutralized by converting it into the pesticide Sevin. The operation Faith was successfully completed. February, 1985: Indian government files claim for $ 3.3 billion from Union Carbide in a US court. 1986: US District Court judge transfers all Bhopal litigation to India. December 1987: CBI files charge sheet against Warren Anderson and other accused, including UCC (USA), Union Carbide (Eastern) Hong Kong, and UCIL. Summons served on Anderson and UCC on charges of culpable homicide. February 1989: CJM, Bhopal, issues non-bailable warrant of arrest against Warren Anderson for repeatedly ignoring summons. February 1989: Indian government and Union Carbide strike an out-of- court deal and compensation of $ 470 million is given by Union Carbide. February – March 1989: Public protest against the unjust settlement followed by filing of a number of review and writ petitions against the settlement in the Supreme Court by the Bhopal Gas Peedith Mahila Udyog Sangatan
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Volume 3 ISSN 0975-0746 (BGPMUS), the Bhopal Gas Peedith Sangarsh Sahayog Samiti (BGPSSS) and other concerned groups. October 3, 1991: The Supreme Court revokes criminal immunity to the firm and its officials. November 11, 1991: Criminal cases against all accused revived in the chief judicial magistrate‘s court at Bhopal. 1992: Part of $ 470 million is disbursed by the government among Bhopal gas victims. February 1992: Anderson declared fugitive by law for ignoring court summons. November 1994: Despite numerous petitions by survivors‘ groups, the Supreme Court allows Union Carbide to sell stake in UCIL to McLeod Russell (India) Ltd of Calcutta. September 1996: Supreme Court dilutes charges against Indian officials of Union Carbide India Limited - subsidiary, majority owned by Union Carbide Corporation [UCC] – partly on grounds that culpability lies with UCC. August 1999: Union Carbide announces merger with USbased Dow Chemicals. November 1999: Several victims and survivors‘ organisations file an action suit against Union Carbide and its former CEO, Warren Anderson, in federal court of New York, charging Carbide with violating international human rights law, environmental law, and international criminal law. February 2001: Union Carbide refuses to take responsibility for UCIL‘s liabilities in India. January 2002: A study by Srishti and Toxics Links finds lead and mercury in breast milk of nursing mothers in communities near the plant. June 2002: Bhopal gas tragedy survivors launch a protest in New Delhi when they hear the Indian government plans to drop charges against Anderson. August 2002: Charges of culpable homicide are maintained against Anderson by Indian court, which demands his extradition to stand trial. Meanwhile, a British newspaper reports that Anderson is in New York after US authorities say they are unable to locate him. October 2002: Protests to clean up former UCIL factory site in Bhopal that activists say contains thousands of tonnes of toxic waste. May 2003: The Indian government formally conveys its request for extradition of Anderson to the US. March 2004: A US court says it could order Dow Chemicals to clean soil and ground water in the abandoned factory site if the Indian government provides a no objection certificate. The Indian government forwards the certificate to the United States. June 2004: The US rejects India‘s request for extradition of Anderson saying the request does not ―meet requirements of certain provisions‖ of the bilateral extradition treaty. July 19, 2004: India‘s Supreme Court orders the Central Bank to pay out more than 15 billion rupees, part of the original $ 470 million received as compensation kept in the account since 1992. October 25, 2004: Bhopal gas victims protest the failure of the government to pay victim‘s compensation.
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Volume 3 ISSN 0975-0746 October 26, 2004: India‘s Supreme Court sets deadline of November 15 to pay out the rest of $ 470 million paid by Union Carbide as compensation. June 7, 2010: All eight accused, including the then Chairman of Union Carbide Keshub Mahindra, in the Bhopal Gas disaster case convicted by a court. June 27, 2012: US Federal Court on 27 June 2012 absolved Union Carbide Corporation and its former chairman Warren Anderson of the Bhopal gas tragedy case. Activists and victims of the Bhopal Gas tragedy case, who were fighting for justice, received a major blow when a US court held that neither Union Carbide nor its former chairman Warren Anderson were liable for environmental remediation or pollution-related claims at the firm‘s former chemical plant in Bhopal.
5. Conclusions Over the centuries there have been many natural disasters or ―acts of God‖ that have stolen human lives and left destruction and havoc for the survivors. Even the man made disaster like Bhopal Gas Tragedy can cause havoc due to mere negligence. Some of the fortunate survivors like Mohan Singh , Bahia Lal, Rekha Gaolat, Jiten Koli…who happened to be in the valley of horror and death on the night of December, 2-3 , 1984, and who reside in the Chhola, J.P. Nagar, just opposite of UCIL gas plant. Institutions under the Council of Scientific and Industrial Research (CSIR) and the Indian Council of Medical Research(ICMR) , which initially took an active interest in unraveling all the ramifications of the disaster, have failed to live up to their potential in this regard. The brazen manner in which the ICMR discontinued all medical research relating to the disaster as early as 1994 speaks volumes about the indifference of the premier health research institution in the country towards the health needs of the gas victims. In 2010 , the organizations fighting for the cause of the victims succeeded in forcing the ICMR to reopen its Bhopal centre, now named the National Institute for Research in Environmental Health(NIREH) . But NIREH is also not fulfilling its commitment. As a result more than five lakh survivors of the disaster continue to remain helpless at the mercy of death. Justice continues to elude the victims of the disaster even after 28 years and little has been done to monitor the health status of victims like Babu Khan who reside just opposite of UCIL at J.P. Nagar, House No. 310. He can neither eat nor drink; he is given saline – water whenever their family can manage. There are may more like Babu Khan within the radius of 3-4 Kilometers from UCIL. About 5,00,000 people still suffer from chronic disease consequential to gas exposure. In a report published on October, 8, 2003, by the reputed journal of American Medical Association (JAMA), it is said that children born to women of Bhopal gas victims are now 19 years old showing physical irregularities. But my observation from the survey made during the field visit is that the woman of Bhopal Gas victims giving birth to children after the gas tragedy is not showing any irregularities. It is generally children above 3 years who came out on the night of disaster on the roads with their parents without any protection and awareness were worst affected but those who stayed back at home and were able to cover their faces were less affected.
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Volume 3 ISSN 0975-0746 Pre- Disaster Management UCC claimed that Bhopal plant was designed and engineered in the same way as its sister plant at West Virginia. This is far from truth, because West Virginia plant had computerized monitoring system which was not used in the Bhopal plant. Operators in the plant should have been cautioned beforehand regarding serious consequences in case MIC came into contact with water. In fact during the night of December 2–3, 1984, water entered a tank containing 42 tons of MIC. The temperature inside the tank increased to over 200 °C (392 °F) and raised the pressure. The tank vented releasing toxic gases into the atmosphere. The gases were blown by northwesterly winds over Bhopal.
Post- Disaster Management From UCC’s perspective If the pre disaster management failed miserably post disaster management turned out to be a total failure. The failure may be summarized as follows: It failed to identify its crisis. It had no disaster management plan. It adopted a ‗bunker mentality‘. From India’s perspective Company Law Board (CLB) introduced a series of new rules and regulations. It was emphasized that in case of a mishap not only promoter Director but also other Directors will be held responsible. Only Rs. 25,000 was given as compensation to the gas victims. Very little medical help is being provided till date. Infrastructure has not been developed to provide medical help to the gas victims and most of them are helpless, no one is there to stand by their side. It can be said that Bhopal Gas Tragedy has been an eye-opener to the entire process Industry and stress was laid on reviewing SHE (Safety, Health and Environment) facilities. Large and medium scale units have implemented ISO- 9000 standards as Total Quality Management tools and ISO 14000 as Environment Management System Standards. To conclude it may be commented that even with best Total Quality Management a Fortune 500 Company like UCC may end up with a real misfortune unless due weightage is given to the critical issues like ―Holistic and Integrated Disaster Management.‖ The response from the men of administration was very poor. Some times they failed to honour their appointment. In few cases they did not answer for different reasons. As per rehabilitation policy of Government, Government should give Job opportunities to the Gas Victims who are within the age limit of 18-40 years under special reservation policy and those above 40 years should be provided unemployment and special relief allowances. Proper medical help should be provided to them instead of leaving them at the mercy of death. The Study can help the policy makers to frame the effective policies of the Government so far as the displacement and rehabilitation of the Bhopal Gas Victims are concerned.
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Volume 3 ISSN 0975-0746 Reference 1. Anderson, T (1990). Government Failure - The Cause of Global Environmental Mismanagement, taken online from www.ifn.se/eng/publications. 2. Jaeryl Covington and David M. Simpson (2006). An Overview of Disaster Preparedness Literature: Building Blocks for an Applied Bay Area Template ,Working Paper series. 3. Kulkarni, G.K (2013). Disaster Management-Issues for action, Indian J Occup Environ Med [serial online] 2005 [cited 2013 Nov 23]. Available from http://www.ijoem.com/text.asp?/16740. 4. Prakash , I (1994). Disaster Mangement, Rashtra Prahari Publishers, Sahibabad, Ghaziabad, India. 5. Mandal, G.S (1993). Natural Disaster Reduction, Reliance Publishing House, New Delhi. 6. Shaw Rajib and Krishnamurthy R.R (2001). Disaster Management –Global Challenges and Local Solutions, Serial Publication House, New Delhi. 7. Report of Government of India (2009). Ministry of Home Affairs, National Disaster Management Division, New Delhi. 8. http://www.apu.ac.uk/geography 9. www.bhopal.net/march
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