What ails primary credit cooperatives in India?: a state level analysis.
Globally, the cooperative sector is making impressive strides. The share of cooperative banks in the banking sector increased from 9% in the mid-1990s to 14% in the year 2004 in 29 major advanced and emerging economies that are members of the OECD (Hesse and Cihak, 2008). The 300 largest cooperatives in the world attained a turnover of US$963 billion in 2004, equivalent to the GDP of Canada, the ninth largest economy in the world (Garry, 2007). Though India is one of the 28 nations where cooperatives are between 50 and 100 years old, no Indian cooperative features among the top hundred in the world (ICA, 2007). (1) Indian credit cooperative banks also fare poorly compared with their commercial peers. Compared with non-performing assets (NPAs) of 3.3 % for commercial banks in India in 2006, credit cooperatives reported overdues as high as 32.48%, which shows their poor financial performance. This paper attempts to explore the possible reasons for the poor financial performance of the rural credit cooperatives in India and suggests measures for improvement.
THE SCOPE OF THE STUDY
Rural cooperatives in India have a complex structure, with institutions specializing in short-term or long-term credits. The cooperatives providing short-term credit have a three-tier structure. Typically, in a state, the primary agricultural credit societies (PACSs) form the lowest tier of the short-term structure. They are affiliated with district central cooperative banks (DCCBs), which in turn are affiliated with state cooperative banks (SCBs). Thus, while PACS form the base, the DCCBs and SCBs occupy the middle and apex position to provide short-term credit within each state. The SCBs, DCCBs and PACS form a vertical chain where the upper tier acts as a balancing centre of funds for the lower tier. (2) The rural cooperatives mostly provide crop and other working capital loans to farmers and rural artisans primarily for short periods. The structure of rural credit cooperatives is not uniform across the states. (3) Some states have a unitary structure where SCBs operate through their own branches, whereas others have the three-tier structure. This study examines the financial performance of PACS for the period of 1997-2005.
The study is organised into six sections. Section I provides a brief review of the evolution of the rural cooperatives and PACS. Section II sets out some hypotheses concerning the performance of PACS based on the discussion in the previous section and in the light of existing literature. Section III discusses certain stylised facts relating to the functioning and performance of PACS in India along with interstate variations. The methodology of the empirical analysis and factors that influence the performance of cooperatives is discussed in section IV. Section V discusses these results, and conclusions based on the empirical results are presented in section VI.
EVOLUTION OF COOPERATIVES
With more than 100,000 outlets and a membership base of 120 million, cooperatives in India make up one of the largest rural financial systems in the world (GoI, 2007). They occupy an important place in India's financial edifice as they play a key role in the multi-agency framework for rural credit delivery. (4) They also dominate finance to rural areas both in terms of the number of clients and their accessibility to the small and marginal farmers and other poorer segments of the population. The short-term cooperative credit system has 50 % more agricultural credit accounts than do the commercial banks and regional rural banks (RRBs) put together. Notwithstanding these impressive achievements, the financial health of credit cooperatives in India has been a matter of perennial concern.
Cooperatives were institutionalised in India through the enactment of the India Cooperatives Act in 1904. The purpose was to help the distressed farming community in a situation where the reach of the banking system was too narrow and the peasantry was overdependent on village moneylenders. The government supported the cooperatives in the initial stages by supplying finance and active guidance to the sector. The current three-tier structure is based on provisions of the Cooperative Reforms Act of 1912. The next landmark for cooperatives was enactment of the Cooperative Reforms Act of 1919, which classified cooperation as a state subject and transferred legislative control over cooperatives from the central government to state governments.
The growth of cooperatives was modest until independence when there was a paradigm shift in the government's approach to cooperatives. Based on the recommendations of the All India Rural Credit Survey (AIRCS) Committee, the Government came to view cooperatives as vehicles of development for rural India. (5) Accordingly, state partnership with all levels of cooperatives emerged in the mid-1950s in the form of share capital contributions and provision of technical, managerial and financial assistance. With government involvement, cooperatives came to be perceived as agencies of the state rather than as autonomous bodies. This government policy of deliberate expansion of cooperatives led to their politicisation and the entrenchment of vested interests in their management. To curb these vested interests, cooperative legislation in the states' incorporated stringent and restrictive provisions that increased government interference in the cooperatives (GoI, 2000, 2001, 2004). The character of the cooperatives changed from member centric to state centric in the subsequent decades.
The 1990s witnessed attempts at freeing the cooperative sector from government control and restoring its democratic character. The Mutually Aided Cooperative Societies Act adopted by the Andhra Pradesh government in 1995 marked a significant step towards reforms. Following the example of Andhra Pradesh, eight other states have passed similar legislation. (6) Later, the Vaidyanathan Committee (GoI, 2004) suggested a systematic overhaul of the cooperatives. (7) The Committee's recommendations include withdrawal of the equity contribution by state governments from credit cooperatives, promotion of thrift along with the prevalent 'borrower-driven' approach, removing legal anomalies and improving the quality of internal control systems, human resources, housekeeping and audit in the cooperatives (GoI, 2004). The Vaidyanathan Committee suggested an action plan with substantial financial assistance for refurbishing the cooperative credit system in India. The states are in different stages of implementation of the recommendations of this Committee. However, there has been substantial dilution of the Committee's recommendation at the implementation stage. (8) Given the dilution of the original recommendation (see Appendix), the efficacy of the revival package is doubtful.
LITERATURE ON DETERMINANTS OF PERFORMANCE
Performance indicator of PACS
Describing performance requires the use of an appropriate indicator. There is a number of possible candidates to describe the performance of a cooperative. The first one is profit. The PACS at an aggregate level incurred losses in 2005-2006 as only 42% of them reported profits of Rs 7.19 billion, which was outweighed by losses of Rs 19.20 billion suffered by the remaining cooperatives. In the spatial dimension, financial performance of PACS can be gauged from the proportion of profit-making PACS in a state. Seen in this way, performance shows marked variations across the states. For instance, compared with only 16% in Tripura, 79% of the PACS were earning profits in Haryana during the 4-year period of 2002-2005. The performance of the PACS can also be measured in terms of their viability. Any functioning entity that is viable should not only he making profits but should also be able to muster the resources, such as infrastructure, technology, skilled manpower and so on to continue making profits in the foreseeable future.
It is also possible to conceptualise viability without an immediate reference to profitability. A PACS that is not profitable but that does meet some threshold norms on business size, client base or some non-financial prerequisites, such as having its own office, a full-time secretary and so on could become financially viable in due course. In fact, many attempts at the policy level to set viability norms for of the PACS have adopted this line of reasoning. Official viability norms, however, have changed over time. For instance, while GoI (2000) defines viability in terms of a threshold business size, GoI (2001) defines those PACSs as viable that have reported profits consecutively for 2 years. The changing viability norms suggest another measure; the ability of a PACS to recycle funds reflected through recovery performance could be considered a good indictor of performance. Recovery of loans to some extent would also reflect whether the members of the society appreciate the 'principles of cooperation', ceteris paribus.
Determinants of performance
Equity partnership by the government is unique to credit cooperatives in India. Notwithstanding state involvement and guidance, the financial performance of cooperatives has been unsatisfactory. This raises concerns about government intervention in the working of the cooperatives and whether such intervention is desirable. Government involvement degenerated into government interference and destroyed the democratic and member-driven character of the cooperatives (GoI, 2000, 2004). However, there has been little empirical validation of the problems associated with government intervention. We consider government involvement in the PACS as one of the determinants of their performance.
The literature on credit cooperatives recognises size as an important determinant of performance. The size of a credit union can be seen either in terms of its total assets or its membership size. The prevalent practice in the literature on credit unions is to consider assets as the indicator of size (Amburgey and Dacin, 1993 and Barton et al., 1994). Membership base, along with assets, as an indictor of size has been explored by some studies (Goddard et al., 2002, Ward and McKillop, 2005a, Ward and McKillop, 2005b and Goddard and Wilson, 2005). Ward and McKillop (2005b) and Goddard and Wilson (2005) report higher growth and better financial performance for credit cooperatives with many members for the United States and the United Kingdom. Indian cooperatives have an average membership size comparable to that of the United Kingdom. However, the scale of operation of credit cooperatives both in the United Kingdom and the United States is much greater than that of Indian ones. Cooperatives in many European nations have assumed conglomerate status by adopting cooperative networks, which provide diversified financial services and adopt a commercial ethos (Fonteyne, 2007; Gutierrez, 2008). Indian credit cooperatives at the village level, on the other hand, are seen as means of meeting the credit needs of the poor who have been excluded from the commercial banking system. PACS in India are not just another category of financial institution with certain specified characteristics that competes and strives to attain the scale of operation matching commercial banks. (9) Rather, the PACS try to reduce the dependence of the rural poor on informal and unorganised sources to meet their credit needs and to inculcate prudent credit habits. (10) They also specialise in meeting the multi-purpose needs of the poor, which may range from short-term consumption loans to medium-term investment loans. As the rural credit cooperatives strive to ameliorate the conditions of the poor by meeting their credit needs, their average loan size is small. Government ownership of cooperatives coupled with periodic loan waivers creates a moral hazard problem. In a cooperative, it is the peer pressure to pay back loans that determines their success. Peer pressure is best attained when the group is cohesive and cohesion perhaps is better in small groups. Hence, large size may be desirable for economies of scale in cooperatives, but very large member size may not be ideal for the PACS.
The literature on the impact of a common bond on cooperative's performance provides additional perspective on the size of credit cooperatives in India. Performance of a credit union depends on the strength of common bond among members (Ward and McKillop, 2005b). Studies find a favourable impact of occupation-based commonality on the performance of credit unions, as commonality of occupation suggests tighter bonds and reduces operating costs (Ward and McKillop, 2005b). As village level credit cooperatives in India lend to members belonging to different occupational categories, a better way to ensure the success of cooperatives is by having members exert moral pressure on each other. In the absence of a common bond of occupation, a smaller member size promotes cohesiveness of the cooperatives and fosters peer pressure. The importance of member size can also be appreciated from the success of self-help groups (SHGs) in India, which are essentially groups of 20-40 micro entrepreneurs having homogenous social and economic backgrounds who function on the cooperative principle of mutual help. (11) The success of SHGs is attributed to peer pressure to ensure proper end-use of credit and timely repayment. (12) In fact, peer pressure has been recognised as an effective substitute for collateral (RBI, 2000). The ideal size suggested for PACS to ensure peer pressure is between 90 and 100 members, on the basis of the German experience (13) (GoI, 1915). Over the years, the average member size of credit cooperatives in India has steadily risen (Table 1). Keeping in view the above discussion, we study member size of PACS as another determinant of their performance.
The literature on Indian cooperatives is predominantly narrative. Whatever little empirical work concerning cooperatives is available is based on case studies (Kulandaiswamy and Murugesan, 2004 and Chalam and Prasad, 2007). These case studies employ ratio analysis on the balance sheet of the selected PACS to comment on their performance. This study attempts to build an empirical model to draw inferences about the performance of PACS across the states. Before we discuss the empirical model, what follows is a discussion on certain stylised facts on performance of PACS in India in section III.
STYLISED FACTS ON PERFORMANCE AND PROGRESS IN BUSINESS INDICATORS
Indicators, such as deposit mobilization, borrowing and working capital of PACS have grown at roughly 15% per annum between 1950 and 1951 and 2005 and 2006. The loans advanced by PACS have always exceeded their deposits as they borrow heavily from the higher tiers to meet the credit needs of their members. The PACS, however, have fared poorly in their management of the deployed funds. In the 55-year period under scrutiny, loans per member grew at 7.8% per annum, but overdue loans grew at a still higher rate at 8.4% per annum. Seen in terms of borrowing members, the situation looks much more critical. While loans advanced per borrowing member have increased 42-fold, the overdues per borrower increased 69-fold per borrowing between 1960 and 1961 and 2005 and 2006. The high proportion of overdue loans has adversely affected PACS profits. Further, changing viability norms have led to frequent restructuring of PACS through liquidation and amalgamation. As such, the number of PACS has fluctuated considerably. The number of PACS peaked at more than 200,000 primary societies in 1960-1961, but their number had halved by 2005-2006 (Table 1). Not withstanding their frequent restructuring, the membership growth of PACS has been impressive. The total member of PACS, which was 4.4 million in 1950-1951, has grown 28-fold in the last 55 years with an annual growth of 6.3%. PACS, which used to cover only 1.2% of the population of the country in the year 1950-1951, embrace more than 11 per cent of an increasing population in the year 2005-2006.
The average membership size across the states varied within a large range of 182 for Jammu and Kashmir to 5,591 for Kerala for the 2002-2005 period. Between 1997 and 2001 and 2002 and 2005 periods, the average membership increased for 14 and declined for 10 states.
The 10 states that experienced a decline in average membership size was as high as 1844 during 2002-2005. With such large number of members, it is perhaps the case that peer pressure has weakened among members of the primary society, which was so vital for their success in the initial design of cooperatives. The change in character of the PACS from unlimited liability to the present limited liability of the members on account of the government's contribution to the share capital might have a role to play in weakening peer pressure. On an all India basis, government's contribution to share capital was only 12 %, but across states, it varied from as low as 3 % to 80 % (Table 2). It is generally observed that PACS in states with very high proportion of government equity also have low recovery rates. However, a relatively low contribution from government is not necessarily associated with very high recovery rates. This is because recovery depends on other factors, such as sourcing of funds, effective monitoring of deployed funds and so on.
Sourcing of funds is also important as it determines the cost effectiveness of the operations of a PACS. In addition to the share capital contribution by members and the government, deposits and borrowings are the two other major sources of working capital for the PACS. At the all India level, deposits and borrowings accounted for 28% and 52%, respectively, of the working capital of the PACS for the 2002-2005 period. Though borrowings accounted for a larger proportion of the working capital than did deposits for the majority of the states, their relative contributions also exhibited wide interstate variations. For 10 out of the 23 states under study, deposits contributed less than 10 percent of the working capital during 2002-2005 (Table 2). Borrowings, however, contributed more than 50 % of the working capital for 13 states. Overall, deposits contributed to a larger proportion relative to borrowings in the working capital for states having relatively higher average membership size in their PACSs.
It is possible that deposits have two opposite implications for recovery. First, as a less expensive source of funding, a relatively larger contribution from deposits enables PACS to lend at relatively low rates so that chances of recovery are better. On the other hand, non-borrowing depositors lack voting rights in a PACS. Hence, a relatively larger proportion of deposits from such depositors may adversely impact recovery by lowering accountability in the management of funds. The proportion of borrowing members has declined from 50% in 1997-2001 to 43% in the period 2002-2005. The proportion of borrowing members in PACS is quite low for many states, and it is more than 50% only in six states. The impact of deposits on recovery performance would be the net effect of these two opposing forces. Unlike deposits, borrowings are a costlier source of funds, which the PACS obtain from the upper-tier DCCBs. However, borrowed funds bring with them greater accountability. As borrowings in general are associated with restrictive covenants and need to be repaid, there is a built-in accountability. Hence, one would expect that the PACS will be more judicious in the deployment of funds raised through borrowings and hence a higher proportion of borrowings is likely to affect recovery positively. A higher proportion of borrowings nonetheless constrains the ability of PACS to lend at the most competitive rates, which might impact their recovery performance. Again, it is the net impact of these two opposing forces that will determine the impact of borrowings on recovery performance of the PACS.
Although resource mobilisation is important, ultimately it is the judicious use of the available funds that determines the success of a PACS. The loan portfolio of the PACS broadly consists of 'agricultural', 'non-agricultural' and 'other' loans. Agricultural loans can be further categorised into loans for crop production, investment in agriculture and for activities allied to agriculture, such as diary farming, mixed farming and so on. Non-agricultural loans cater to the credit needs of some segments of the so-called priority sectors, such as small road transporters, small-scale industries, small business, rural housing and so on. (14) The other loans are a composite category including personal loans and loans-against-deposits. On an all India basis, agricultural loans accounted for two-thirds of the entire loan portfolio of PACS as on March 2006. Next in order of importance was the 'other loans', which accounted for 20 percent of the loan portfolio, and the balance 13 % went to non-agricultural category. The mix of the loan portfolio of the PACS has undergone distinct changes in the majority of the states between 1997 and 2001 and 2002 and 2005. Different loans have varying elements of risks associated with them. Although crop loans are exposed to the vagaries of nature, recovery of 'other loans' depends on the proper assessment of the earning capacity of the borrower. Further, the PACS themselves should be in a better position to monitor certain categories of loans. As the management of the loan portfolio is important, it would be interesting to see the impact of the loan mix recovery performance of the PACS.
Having discussed some of the factors that have an impact on the performance of the PACS, we now try to decipher their impact through parametric estimation.
METHODOLOGY AND DATA
As discussed earlier, recovery performance is used as an indicator of the health of the PACS. To ascertain whether government's involvement is really detrimental to the recovery performance of the PACS, we consider government's contribution to the capital as an explanatory variable. To study the impact of growing member size of the cooperatives on their recovery performance, we use average member size of cooperatives as another explanatory variable in the model.
As far as the business of the PACS is concerned, they lend funds obtained from deposits and borrowings from higher tiers of the cooperative credit system to their members. Cooperatives obtain deposits from their members and also from the general public. However, the PACS restrict membership with full voting rights only to borrowers, and non-borrowing depositors are treated as nominal members without voting rights. The Vaidyanathan Committee observed that such practice is not only inconsistent with cooperative principles and democratic functioning but also logically inconsistent, as fund providers have no say in the management of their own money. To assess whether denial of voting rights to the non-member depositors has a bearing on the performance of the PACS, we consider share of deposits in the working capital as another explanatory variable.
Borrowed funds are obtained from the middle-tier DCCBs, and the PACS are accountable for their use. As the share of borrowed funds rises as a proportion of working capital, PACSs have to be more vigilant about the use of the funds, and that should positively influence their recovery efforts. Thus, we consider the share of borrowings in working capital as another explanatory variable. To consider the impact of the loan mix of PACS on their recovery performance, we consider the proportion of non-agricultural loan to agricultural loan as another variable. We have used growth in the state domestic product (SDP) as a conditioning variable. It is quite possible that past recovery performance has a bearing on current recovery performance. Therefore, the lagged value of recovery is also considered. To ascertain the impact of the various factors on the recovery performance of the PACS, panel data regression models have been used. Equation (1) describes the specification of the model.
[Recovery.sub.i,t] = [[eta].sub.0][Recovery.sub.t-1] + [[eta].sub.1][AVGMEM.sub.i,t] + [[eta].sub.2][GOVCAP.sub.i,t] + [[eta].sub.3][DEPTOBOR.sub.i,t] + [[eta].sub.4][LONAGRI.sub.i,t] + [[eta].sub.5][SDP.sub.i,t] + [[epsilon].sub.i,t] (1)
where, [[eta].sub.0], [[eta].sub.1], [[eta].sub.2], [[eta].sub.3], [[eta].sub.4] [[eta].sub.5] and are parameters to be estimated and the subscripts t (=9) and i (= 19) refer to the year and cross section (state), respectively; Recovery=proprtion of outstanding loans, which could be collected by the PACS on the due date; AVGMEM = average members per society in state i; GOVCAP = share of government capital as a proportion of working capital; DEPTOBOR = deposits of the PACS as a proportion of its borrowings; LONAGRI = non-agricultural loans as a proportion of agricultural loans; GSDP = growth in SDP; [[epsilon].sub.i,t] = error term that is assumed to be i.i.d.
All the variables under study are expressed in percentage terms except the AVGMEM variable, which is expressed as numbers. Equation (1) is a dynamic panel data model. We adopt an instrumental variable procedure, with different lags of the dependent variable used as instruments. The Arellano and Bover (1995) approach is adopted as it generates the most efficient estimates. While using lagged dependent variables as instruments, overall instrument validity is examined using a Sargan test of over-identifying restrictions.
The data are obtained from the National Federation of State Cooperative Banks (NAFSCOB), the agency that collects and collates information on PACSs functioning across the country. The study is based on 19 states for which consistent information was available for all the variables for the study period, which covers the period 1997-2005.
Estimation of the model (1) provides coefficient estimates that are statistically significant (Table 3). The dynamic panel data estimation reveals that past year's performance had a significant impact for the current year for both categories of states. (15) The p-value of the Sargan test indicates that the estimated model does not suffer from mis-specification. Now, we discuss the results from this extended model. First, as has been surmised by a number of studies (GoI, 2000, 2004), government's contribution to the share capital of PACS is found to be detrimental to their recovery performance.
Second, as membership size grows in the PACS, it is detrimental for the recovery. This result is important because the issue of optimal member size was not discussed by most of the committees and commissions that had inquired into the problems of PACS. Although the MacLagan Committee in the year 1915 had stressed the desirability of smaller size cooperatives, the preference after independence has been for bigger size cooperatives in the interest of viability. This is a classic case of missing the forest for the trees. In its zeal to promote cooperatives, the government ignored some basic principles of cooperatives that are key to their success. Cooperative since their inception were conceptualised as a small and neatly firm group of people where the moral pressure that the members exert on each other rather than their material means is key to their success. Peer pressure ensures recovery and recycling of funds and contributes to the success of cooperatives. The proposition noted earlier that peer pressure is diluted as membership size grows is borne by the empirical results. As such, the early advocates of cooperatives favoured small size cooperatives. This basic principle of cooperation was turned upside down in the post-independence era in India. Cooperatives were seen as a panacea for all the ills of the rural India. Government found in the cooperatives a mechanism to reach out to the rural poor without having any regard for the fundamental factors that contributed to their success.
Third, as deposits as a proportion of borrowings rise, recovery is adversely affected. This is perhaps because non-borrowing depositors do not have adequate representation in the functioning of a PACS. Management accountability in a PACS is compromised to the extent that funds are sourced from the non-borrowing members. The Vaidyanathan Committee also pointed out this problem. Unlike for deposits, PACSs are accountable to the higher tiers for the funds borrowed from them. When deposits rise in proportion to borrowings, recovery is adversely affected. Fourth, as far as loan mix is concerned, a rise in the non-agricultural loan as a proportion of agricultural loan adversely affects recovery performance. Handling non-agricultural loan requires special skills that the PACS perhaps lack.
This study made an attempt to decipher the factors that contribute to the recovery performance of the PACS. Unlike the extant literature on Indian cooperatives, which is primarily narrative and in some instances based on case studies, this study was a model based attempt to examine the performance of cooperatives.
The results indicate that, as the PACSs have drifted from some of the core principles of cooperation, their recovery performance has suffered. As membership size has grown over the years in case of the PACS, their recovery rate has fallen. Thus, there is a need to re-examine the issue of optimal member size of the PACS. This is a neglected aspect in the present-day literature on cooperatives, but merits attention from all stakeholders. Government's contribution to the share capital is also found to be detrimental to the recovery performance. Government's contribution in share capital not only allows for government influence, it may create moral hazard in lending because of the possibility of a government bailout in case of difficulty. In view of the empirical findings, there is a need to reconsider the latest amendment in the Vaidyanthan Committee's recommendation to permit 25 % government equity contribution in PACS. The attempt should be either to completely dislodge government equity in the PACS or not to consider the PACS as cooperatives but to accept them as quasi-government ventures for which performance parameters need to be revisited. The study also found that as deposits grow in proportion to borrowings, the recovery performance is adversely affected. This is perhaps because non-borrowing members do not have a voting right in the PACS.
See Table A1.
Table A1: Vaidyanathan Committee: Revised eligibility criteria for revival package Institutions Original criteria Revised criteria PACSs (1) Gross interest margin Loan recovery of at Least should be [greater than 30% of the demand as on or equal to] 50% of 30 June 2004. State operating expenses government will be under obligation to determine the future set up of ineligible PACSs with recovery level of < 30%. (2) Recovery should be The quantum of financial [greater than or equal assistance will be to] 50% of demand determined through Special Audit of Accounts of PACS, DCCB and OSCB as on 31 March 2004. Government of India may consider relaxing the eligibility norm for PACS/DCCBs for northeastern states, scheduled areas and Tribal Districts. DCCBs Positive net worth and All DCCBs are eligible. those with negative net worth with deposit erosion of <25% SCBs Positive net worth and All SCBs are eligible. those with negative net worth with deposit erosion of < 25%
The author is grateful to Shri Tushar Kanti Panda, Chief General Manager, Orissa State Cooperative Bank for very useful discussion and thought provoking comments on the paper.
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(1) Indian cooperatives also fare poorly in terms of revenue or contribution to GDP among the countries in the Global 300 Project of the International Cooperative Alliance (ICA).
(2) As a number of PACS are affiliated to one DCCB, the latter absorb funds of those PACS that have surplus funds and lend to those PACSs that are in need of funds. In this way, the DCCBs were supposed to act as a balancing centre of funds for the primary credit societies.
(3) India is made up of administrative units known as 'states'. Geographical contiguity is the basis for classification of regions, which comprise of a number of states. Each state has its own political system and a democratically elected government. The village level PACS in the states are under dual control. They are governed by the legal prescriptions of the concerned state in matters relating to their constitution and governance and also by some statutory financial regulator for their banking activities.
(4) The multi-agency framework in India consists of commercial banks, regional rural banks (RRBs) and cooperative banks.
(5) The All India Rural Credit Survey committee (AIRCS) was appointed to take stock of rural finances in 1951. The committee submitted its report in the year 1954.
(6) These states are Bihar, Chhattisgarh, Jammu and Kashmir, Jharkhand, Karnataka, Madhya Pradesh, Orissa and Uttaranchal.
(7) The Vaidyanathan Committee had the mandate to recommend an implementable action plan for reviving rural cooperative banking institutions.
(8) There has been certain amount of dilution in the stipulations laid down by the Vaidyanathan Committee in the Memorandum of Understandings (MoUs) that are signed by the cooperative banks with National Bank of Agriculture and Rural Development (NABARD), the state government and the central government. The states are eligible for financial assistance only after they sign the MoUs.
(9) The cooperative sectors' loans are around 3.5 % of those of commercial banks in India. To get a comparative perspective, the Italian cooperative banking sector account for about 30 % of both the loans and deposits of the Italian banking system (Gutierrez, 2008).
(10) Unorganised and informal sources include village moneylenders, friends and relatives.
(11) A self-help group (SHG) is a registered or unregistered group of micro entrepreneurs having homogenous social and economic backgrounds. They voluntarily contribute small amounts regularly to build a common fund and meet their emergency needs on mutual help basis. The group members use collective wisdom and peer pressure to ensure proper end-use of credit and its timely repayment, http://www.rbi.org.in/scripts/FAQView.aspx?Id = 7
(12) Out of 290 reporting banks, 73 % of banks had more than 80 % recovery rate on loans given to SHGs as on 31 March 2007.
(13) This was suggested by the Lord MacLagan Committee on Cooperation in the year 1915.
(14) In India, the government defines a composite category of activities as the priority sector. It is obligatory for the financial institutions to allocate a specific percentage of their total loan portfolio to the priority sector. Loans to agriculture, small, medium and micro enterprises, rural housing and so on are considered as part of lending to the priority sector.
(15) This in a way testifies the appropriateness of employing the extended dynamic model for estimation.
BISWA SWARUP MISRA
Room No. 251, Administrative Building, Xavier Institute of Management, Xavier Square, Bhubaneswar, Orissa, India 751013. E-mail: email@example.com
Table 1: Progress of PACS in the post-independence era (million Rs) Year 1950-1951 1960-1961 1970-1971 1980-1981 Number 105 212 161 94 Members 4,408 17,041 30,963 57,653 Owned funds 172.6 755.7 2,653.1 7,579.5 Deposits 44.8 145.0 694.0 2,913.4 Borrowings 192.1 1,795.9 6,751.9 29,574.2 Working capital 409.6 3,099.2 11,534.6 40,360.3 Loans advanced 229.0 2,027.0 5,778.8 17,694.1 Loans outstanding 291.3 2,180.0 7,844.8 24,506.4 Overdue 64.1 440.0 3,220.0 10,862.0 Average member 42.0 80.4 192.3 613.3 per society Proportion of NA 53.00 37.00 32.40 borrowing members Year 1990-1991 2000-2001 2005-2006 Number 83 99 106 Members 80,115 99,918 125,197 Owned funds 16,420.3 55,937.5 92,920.1 Deposits 13,489.7 134,810.7 125,611.9 Borrowings 77,785.9 258,896.6 410,176.0 Working capital 118,719.2 538,674.7 733,866.7 Loans advanced 46,788.5 256,983.1 429,195.9 Loans outstanding 68,772.3 345,223.3 517,789.9 Overdue 31,393.4 100,378.8 154,762.3 Average member 966.4 1,011.3 1,176.8 per society Proportion of 32.87 46.57 36.80 borrowing members Note: Numbers and Members are in '000 (in thousands). Source: NAFSCOB for data for the period 1990-1991 and onwards. Data for previous years are taken from IN DIASTAT. Table 2: Key drivers of recovery performance State Recovery Average members 1997- 2002- 1997- 2002- 2001 2005 2001 2005 Andaman Nicobar Island 62 47 130 238 Andhra Pradesh 57 50 2,177 3,926 Arunachal Pradesh 9 4 581 581 Bihar 19 30 893 895 Goa 71 48 884 1,012 Gujarat 64 55 292 549 Haryana 75 75 1,026 1,079 Himachal Pradesh 58 61 498 473 Jammu and Kashmir 27 23 361 182 Karnataka 64 54 1,133 1,185 Kerala 79 77 5,933 5,591 Madhya Pradesh 51 55 1,301 1,293 Maharastra 57 55 511 456 Meghalaya 24 14 985 702 Mizoram 20 12 81 619 Orissa 64 79 2,621 4,565 Pondicherry 50 72 2,408 1,371 Punjab 84 86 513 521 Rajasthan 69 71 895 939 Tamil Nadu 63 63 1,848 1,730 Tripura 10 8 2,683 1,492 Uttar Pradesh 57 57 317 527 West Bengal 21 38 472 819 India 65 64 954 1,141 State Government's Share of contribution deposits in share in working capital capital 1997- 2002- 1997- 2002- 2001 2005 2001 2005 Andaman Nicobar Island 28 25 12 20 Andhra Pradesh 4 3 4 12 Arunachal Pradesh 76 75 0 0 Bihar 60 48 4 9 Goa 43 31 21 36 Gujarat 3 3 4 4 Haryana 15 9 3 6 Himachal Pradesh 35 31 55 66 Jammu and Kashmir 47 51 2 1 Karnataka 22 17 20 24 Kerala 11 11 72 85 Madhya Pradesh 27 24 7 11 Maharastra 2 1 4 5 Meghalaya 49 51 8 7 Mizoram 76 13 3 10 Orissa 32 22 31 48 Pondicherry 59 63 32 62 Punjab 11 5 12 16 Rajasthan 26 21 4 5 Tamil Nadu 14 13 40 37 Tripura 64 79 1 1 Uttar Pradesh 22 22 6 7 West Bengal 25 30 30 25 India 14 12 24 28 State Share of Share of borrowings agricultural in working loan in capital total loan 1997- 2002- 1997- 2002- 2001 2005 2001 2005 Andaman Nicobar Island 39 24 73 100 Andhra Pradesh 67 86 45 57 Arunachal Pradesh 25 25 100 100 Bihar 84 89 99 74 Goa 36 27 50 48 Gujarat 64 69 55 92 Haryana 67 59 85 86 Himachal Pradesh 17 12 91 76 Jammu and Kashmir 60 71 92 62 Karnataka 62 56 73 60 Kerala 16 15 31 35 Madhya Pradesh 52 74 71 77 Maharastra 69 72 82 61 Meghalaya 51 56 57 94 Mizoram 12 24 8 58 Orissa 42 29 63 48 Pondicherry 37 22 52 45 Punjab 67 68 94 89 Rajasthan 58 69 42 85 Tamil Nadu 49 39 39 43 Tripura 53 50 98 71 Uttar Pradesh 77 75 0 25 West Bengal 19 35 84 70 India 52 52 56 59 State Share of Share of non-agricultural other loans loan in in total Loan total loan 1997- 2002- 1997- 2002- 2001 2005 2001 2005 Andaman Nicobar Island 27 0 0 0 Andhra Pradesh 6 4 50 39 Arunachal Pradesh 0 0 0 0 Bihar 0 0 1 26 Goa 43 48 7 4 Gujarat 1 2 44 6 Haryana 14 13 1 1 Himachal Pradesh 9 0 0 24 Jammu and Kashmir 6 3 2 36 Karnataka 13 11 14 30 Kerala 27 39 42 27 Madhya Pradesh 9 6 20 17 Maharastra 8 10 10 29 Meghalaya 22 1 21 4 Mizoram 3 4 89 38 Orissa 2 2 35 50 Pondicherry 14 31 34 24 Punjab 4 4 2 7 Rajasthan 1 2 57 13 Tamil Nadu 38 34 23 23 Tripura 2 6 0 24 Uttar Pradesh 0 0 100 75 West Bengal 11 11 5 20 India 13 15 31 26 Source: NAFSCOB. Table 3: Dynamic panel data (GMM) estim ation results Independent variables Coefficient t-value Recovery (-1) 0.424 23.512 AVGMEM -0.012 -5.545 GOVCAP -1.796 -5.513 DEPTO BOR -0.035 -8.318 LONONAGRI -0.032 -4.319 GSDP 0.113 1.562 P-value of Sargan test 0.855
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|Author:||Misra, Biswa Swarup|
|Publication:||Comparative Economic Studies|
|Date:||Sep 1, 2009|
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