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(NABARD), with corpus from the commercial
A Critical Analysis of the RIDF
banks. The fund was initially developed to provide resources for the projects that remained unfinished due to want of re-Meenakshi Rajeev sources, but later extended to new
This article critically examines the use of the Rural Infrastructure Development Fund by different states and finds that a number of aspects need to be improved to ensure proper utilisation and to reduce intra-rural disparity in India.
This work was done as a part of a project at the ADRT Centre of the Institute for Social and Economic Change, Bangalore. The author is grateful for support of the centre. Many thanks to R S Deshpande for his support and useful discussions.
Meenakshi Rajeev (meenakshi@isec.ac.in) is at the Institute for Social and Economic Change, Bangalore.
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I
1 Introduction
In India, while the importance of rural infrastructure has been well recognised, adequate measures to improve the same are not forthcoming. Amongst many other constraints, the poor financial health of the states is one of the major causes for the state of affairs we observe today. Recognising this fact, the union budget of 1995-96 announced a funding provision for the states to improve the status of rural infrastructure. This provision has created through the Rural Infrastructure Development Fund (RIDF) under National Bank for Agriculture and Rural Development projects as well. RIDF-I was launched in 1995-96 with an initial corpus of Rs 2,000 crore through contributions both from public and private sector banks. Except for a brief break, this funding scheme has been continuing till today. Twelve years after its inception, it is useful to have a critical review of RIDF, which may help us to identify and work on its shortcomings in the coming years. This paper highlights a few selected areas that need attention.
2 Utilisation of Funds
As mentioned above, one of the major objectives of RIDF is to provide funds for unfinished projects so as to achieve speedy completion.
2.1 Status of RIDF Projects
Norms of loans under RIDF show that the normal phasing (for completion of a project) was two years for RIDF-I which was extended later to three years for subsequent tranches. A critical examination of the status of the projects (Table 1, p 28), reveals that even after 10 years some projects have remained incomplete. About 6,000 projects taken up from RIDF-I to RIDF-V have remained incomplete till
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date. If projects taken up under RIDF itself remain incomplete, perhaps due to a state’s inability to borrow funds under the given terms and conditions, then the genuine cases, administrative delays should be kept strictly under control.
2.2 Funds for Local Institutions
It was decided in 1999 that RIDF can be given to local level institutions like the panchayati raj institution (PRI) or prominent self-help groups (SHGs) of the locality, while the respective state government remains the guarantor of the loan taken. One of the main objectives of making funds available to local level institutions is to ensure efficient utilisation. Since local governments themselves are stakeholders, one may expect funds to be employed according to the local needs. During the first year (1999-2000) one observes as high as 17 per cent of funds diverted to local level institutions. However, over time this share shows considerable decline, even in absolute levels (Table 2, p 29). From about Rs 500 crore in 2001-02, funds diverted to PRIs declined to about Rs 50 crore in the next two years. The percentage share indeed has declined to a level which can be termed “negligible”.
It has been observed by a number of authors that state level functionaries are often hesitant to hand over the financial and functional powers to local governments [Mathur 2003]. In case of RIDF also we observe a similar tendency. The question that arises is, are funds deployed according to the local needs or as per the decision of the state departments at the apex level? In such circumstances need and allocation pattern may not match. To attain optimal use of limited resources such possibilities need to be avoided.
3 Funds and Infrastructure
A strong positive correlation between rural poverty and deficiency of infrastructure is a well-established phenomenon. For example, a National Council for Applied Economic Research’s (NCAER) India Rural Infrastructure Report clearly demonstrates that with different infrastructure deficiency indices, rural poverty rates are positively correlated. In other words, the higher the deficiency of infrastructure in a region, the higher is the poverty rate and
Table 1: Number of Incomplete Projects
RIDF No of Incomplete Projects
I 234
II 600
III 366
| IV | 1,004 |
| V | 3,666 |
| VI | 6,261 |
| VII | 16,049 |
| VIII | 14,118 |
| IX | 19,091 |
| X | 60,015 |
| Total | 1,21,404 |
Source: NABARD.
very purpose of introducing such a scheme is defeated.
Time overrun often occurs due to lack of adequate funds to complete projects as a result of cost escalation. Our discussions with state government officials reveal that administration delays in releasing funds to the relevant implementing departments lead to cost escalation and thereafter a
vicious circle sets in. Sometimes delays are unavoidable due to problems such as acquisition of lands for construction of roads. While the problem of cost escalation needs to be considered favourably for sanctioning additional support in the
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Infrastructure like irrigation facilities can reduce overall cost of irrigation and rural roads aid further by enhancing connectivity whereby offering better marketing possibilities. If we accept this line of argument, we can then examine whether regions with higher levels of rural poverty get better allocation of funds for infrastructure development.
3.1 Rural Poverty
Rural poverty rates for different states of India show considerable disparities. As discussed earlier, if we assume that poverty and lack of good infrastructure are positively related then we can consider these rates as indirect indicators of the in adequacy of rural infrastructure or, conversely, improvement of infrastructure in comparatively poorer regions can help in reduction of rural poverty and income inequality across rural regions. Against this background, we should expect the poorer regions to receive higher allocations of funds. Also under such conditions it is essential to ask whether the states with higher poverty rates use more funds for rural development under RIDF.
We have considered the states in terms of RIDF loans sanctioned per hectare of rural area1 and rural poverty rates. Out of a total of 28 states, the top 14 are placed in the category “high” (H) and the bottom 14 are in the category “low” (L). A comparison of the poverty rates and flow of funds across states is presented in Table 3.
Concentration of states around the offdiagonal in Table 3 clearly reveals that the states with lower poverty rates are also those which made higher demands for resources under RIDF. On the contrary, states with higher rural poverty rates are
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minimal users of RIDF for rural infrastructure developments.
In fact, if we look at the correlation between the total flow of RIDF funds (per rural area) and rural poverty rates, we observe a significant negative correlation (-0.365, significant at 6 per cent level). In other words, the higher the rates of rural poverty (indicating greater need for infrastructure) the lower are the flow of funds.2 Since RIDF is a demand driven scheme, this may be due to the fact that the poorer states have less of an ability to borrow and thus though there is a need, this desire is not backed by adequate purchasing power and, hence, requirements have not transformed into demand.3
After looking at this general indicator and its relation with the total flow of funds we next move on to the sector specific allocations.
3.2 Irrigation Facilities
Creation of irrigation facilities and construction of rural roads for better connectivity are two major activities taken up through RIDF. To begin with, however, the fund was created mainly for the provision of irrigation facilities. If we examine the state-wise irrigation potential created through RIDF projects per hectare of net sown area, we observe Haryana is the major benefactor, followed by West Bengal and Uttar Pradesh [see NABARD Reports and Rajeev 2006].
The percentage of gross irrigated area to gross sown area (GSA)4 provides an indicator of adequacy of irrigation facilities in a state.5 Though the need for irrigation facilities may differ across states, due to lack of appropriate data to assess this we use the above indicators as proxy for adequacy. Thus if we infer that the lower the percentage of irrigated area, the higher would be the necessity of irrigation facility in the region, we can then come up with classification of the states as before. More precisely, taking this indicator into consideration, we have classified the top 50 per cent of the states as those with high adequacy and the bottom 50 per cent as those with low adequacy.
The classification of states shows concentration around the diagonal (Table 4) while ideally it should have been around the off-diagonal. Thus states with inadequate infrastructure also have a lower allocation of resources and thereby lower levels of creation of infrastructure facility. The correlation also shows a significant positive values (0.48). Thus, states with higher proportions of irrigated area also had higher allocations of funds under RIDF for the same.
3.3 Funding for Rural Roads
The first RIDF concentrated mainly on providing minor irrigation facilities. Thereafter rural roads and bridges were incorporated under the purview of the RIDF, which now constitute the highest share in terms of allocation of funds across sectors. However, as expected, the flow of funds and hence creation of road potential through RIDF is not uniform across
Table 2: Sanction of Funds to Local Level Institutions
Funds Sanctioned
Year Amounts For Percentage (Rs Crore) RBI/SHG/NGO PRI/SHG/NGO
1999-00 3504.41 608.53 17
2000-01 4539.05 736.11 16
2001-02 4792.52 567.7 12
2002-03 6039.62 533.22
2003-04 5599 43.2 0.7
2004-05 8282.75 54.28 0.7
Total 42948.51 2543.04 6
Source: Computed using NABARD data.
Table 3: Classification of States with Respect to Poverty Rates and Total Loan Flow (Per Hectare)
Rural Poverty Rate
L (Low) H (High)
L (Low) J ammu and Kashmir, Madhya Pradesh, Manipur, Rajasthan Meghalaya, Mizoram, Nagaland, Sikkim, Tripura, Arunachal Pradesh, Assam, Bihar, Jharkhand,
H (High) Goa, Punjab, Orissa, Tripura
Himachal Pradesh,
Haryana, Kerala,
Andhra Pradesh,
Gujarat, Karnataka,
Maharashtra, Tamil Nadu,
Uttar Pradesh, West Bengal
Source : Compiled by author using NABARD data and Jha ( 2002).
Table 4: Classification of States with Respect to Irrigation Potential Created (under RIDF) per Hectare of Net Sown Area and Percentage of Gross Area Irrigated*
(average of percentages taken over the period of RIDF)
| Gross Area Irrigated/GSA | ||
|---|---|---|
| L (Low) | H (High) | |
| L (Low) | Arunachal Pradesh, Tamil Nadu, Rajasthan Meghalaya, Sikkim Gujarat, Bihar, Karnataka, Mizoram Nagaland Maharashtra, Madhya Pradesh Irrigation Potential Created/NSA | |
| H (High) | Kerala, Assam, Tripura Himachal Pradesh, Goa | Orissa, Punjab, Manipur Andhra Pradesh, Jammu and Kashmir, Uttar Pradesh, West Bengal, Haryana |
*These figures are average over the period of RIDF and are taken from www.indiastat.com.
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regions. In comparative terms, Tamil Nadu and Karnataka have created maximum road facilities through RIDF and some of the other similarly placed states are Maharashtra, Kerala, Goa and Punjab.
If we look at the percentage of villages connected by roads (see Appendix,p 31) as of 1996-97 (the beginning of RIDF) we observe that Goa, Karnataka, Tamil Nadu, Punjab, Haryana, Gujarat and Andhra Pradesh were some of the well-connected states. On the other hand, Madhya Pradesh, Bihar and even West Bengal had less than 50 per cent villages connected. As argued above, while demand for rural roads is difficult to estimate, adequacy of the same may be proxied by the percentage of villages yet to be connected by roads. Ideally, one would expect more funds to flow to the states where even 50 per cent of the villages are not connected by roads. Though the quality/conditions of the roads may not be satisfactory even in the highly connected states, the situation is expected to be even worse for the poorly connected ones.
After examining these numbers the next question that arises is, whether or not the flow of funds is greater towards states with relatively inadequate connectivity. As before if one classifies the states according to the percentage of villages yet to be connected by roads vis-a-vis the allocation of funds (under RIDF) similar picture as that of irrigation repeats. Calculation of correlation between the inadequacy indices and potential of roads created through RIDF funds shows that correlation has negative sign (-0.234, however the coefficient is insignificant). Thus we observe that funds are indeed going to the comparatively better off states than the ones that are most needy. In fact, even when we examine in absolute terms, some of these needy states are using very little assistance from RIDF to improve their rural infrastructure.
4 Conclusions
In the face of increasing competition from private sector banks, including foreign banks, public sector banks are beginning to change their strategies. They are trying to trim operating expenses, by cutting down the wage bill by using retrenchment under the voluntary retirement scheme.
They are also seeking to reduce costs by limiting branch expansion and reducing the number of bank branches. The latter, which affects the rural areas first, is expected to reduce access to credit in rural areas that were served through the postnationalisation branch expansion drive. Given this background, inclusion of funds directed towards development of rural infrastructure under priority sector lending through schemes like RIDF is a move in the right direction. Infrastructure facilities, being public goods, benefit both the rich and the poor, and directly affect the rural masses. Furthermore, infrastructure projects also generate employment, especially for the poor.
RIDF projects in particular are usually well monitored and several NABARD surveys show that the satisfaction levels of the users of these services are quite high.6 In other words there is proper use of allocated resources. In fact a Road Users Satisfaction Survey carried out in Karnataka at the behest of the World Bank shows that awareness of NABARD schemes is very high amongst users and people demand
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that projects be implemented by the organisation [NABARD 2004].
However, attention needs to be paid to certain aspects. For example, projects showed considerable time overruns due to several reasons. According to NABARD [Morris and Morris 2003] the implementing departments (of governments) were not adequately funded by the state governments. Our discussions with the implementing departments reveal that problems in the completion of projects due to cost escalation arise because of administrative delays as well. Preference is therefore given to improve rural infrastructure through central government schemes like the Prime Minister’s Gram Sadak Yojana. Lack of transparency among the key functionaries also lead to delays in completion of the projects [Morris 2003]. Further, land acquisition sometimes creates problem in the completion of road as well as irrigation projects. Such delays often result in cost escalation and thereafter a vicious circle sets in. While delays due to bureaucratic procedures should be mini mised, unavoidable delays should be considered and appropriate funding should be provided to complete the projects in such cases. Unless the problem of completion of projects in time is tackled by both the borrower and the lender through a combined effort, rural infrastructure development will suffer.
Focused Allocation of Funds
Secondly, according to the new norms of RIDF, funds can be allocated to the local level governments as well. It can be expected that given a certain amount of independence, the lower tier of government can come up with more need based project concepts. Our analysis of national level already existing data reveals that states with comparatively poor rural infrastructure are also poor users of the fund. To put it more strongly, we observe that at best there is no relation between inadequacy of infrastructure facilities and allocation of funds. This is not only true in an aggregate sense but also holds good sectorwise. Therefore, more focused allocation of resources to the most adversely placed regions is necessary. Only then will such schemes succeed in reducing intrarural disparity.
One may, however, argue that RIDF is a demand driven funding facility. A state government with poor infrastructure facility may not come forward to take loans under RIDF and therefore such disparities may be unavoidable. However, in such cases it is necessary to persuade some such states to use the funding facility for improving the condition of the rural population.7 More importantly, by analysing data on allocation of funds across districts within the state of Karnataka we observe exactly similar trends [Rajeev 2006]. No doubt when we reflect on the district or lower level allocations within a state, the question of allocation becomes more appropriate. In other words, if a state has already decided to borrow a particular amount, the issue of how its distribution has been planned across regions and whether it will reduce the inequality becomes critical. As mentioned above we do not observe such consideration even at the district level allocations within a state. Thus, the question of need based allocation of funds is required to be considered seriously if one wishes to reduce intra-rural disparity.
Notes
References
Ahmed, Raisuddin and Mahabub Hossain (1990): Devlopment Impact of Rural Infrastructure in Bangladesh, Research Report 83, International Food Research Institute, Washington DC.
Binswanegar, Hans P, S R Khandekar and M R Rousenzweig (1989): ‘How Infrastructure and Financial Institutions Affect Agriculture Output and Investment in India’, Policy Planning and Research Working Paper No 163, World Bank, Washington DC.
Centre for Monitoring Indian Economy, Economic Intelligence Services Report, Different Issues, Mumbai.
Fan, S and P Hanzell (2001): ‘Returns to Public Investment in Less Favoured Areas of India and China’, American Journal of Agriculture Economics, 83(5).
Government of Andhra Pradesh (2000): ‘Strategy Paper on Poverty Eradication in Andhra Pradesh’, available at http://www.aponline.gov.in/quick% 20links/strategy % 20papers/strategy_paper_ poverty_eradication.html.
Government of India (1995): Union Budget.
Government of Karnataka, Karnataka at a Glance, Different Issues.
Jha, Raghbendra (2002): ‘Rural Poverty in India: Structure, Determinants and Suggestions for Policy Reform’, ASARC Working Papers 2002-07, Australian National University, Australia South Asia Research Centre.
Mathur, M P (2003): ‘Panchayat Raj Institutions and the State Finance Commission: A Report’ in Sebastian Morris (ed), India Infrastructure Report, op cit.
Morris, A A and S Morris (2003): ‘Rural Infrastructure Development Fund: A Review’ in S Morris (ed), India Infrastructure Report, op cit.
Morris, Sebastian (ed) (2003): India Infrastructure Report: Public Expenditure Allocation and Accountability, 3i Network, Oxford University Press, New Delhi.
National Bank for Agriculture and Rural Devlopment, Annual Reports, (various issues), NABARD, Mumbai.
– (2004): Implementation of RIDF Projects in Karnataka: A Review Report, NABARD, Karnataka. National Council for Applied Economic Research (2006): India Rural Infrastructure Report, New Delhi.
Rajaraman, Indira (2003): ‘Interstate Variations in Utilisation of the Rural Infrastructure Development Fund’, Working Paper No E/235/2003, Institute of Economic Growth, New Delhi.
Rajeev, Meenakshi (2006): ‘Rural Infrastructure Deve lopment: Role of RIDF’, Project Report No Eco/ADRT 77, Institute for Social and Economic Change, Bangalore.
Reserve Bank of India (1999): Fiscal Deficit: A Study of Budgets.
– Statistical Tables Relating to Banks in India, different issues, RBI, Mumbai.
Vos, Rob, L Taylor, R P D Barros (2002): Economic Liberalisation, Distribution and Poverty: Latin America in the 1990s, UNDP, Edward Elgar Publishing, UK.
Appendix: Percentage of Villages Yet to be Connected by Roads (1996-97)
data shows that the share of funds allocated to this lower tier of government is decreasing over time. While implementing department may carry forward the work, local stakeholders need to be involved in making a choice of a infrastructure facility required for the region. Only then can the limited resources be utilised in a most optimal manner.
Coming to the question of allocation of given resources amongst different rural areas, more careful consideration is required. In fact, the above analysis of
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1 “Rural population” can also be used as a normalising factor, and has been also used in the main report. However, “rural area” appears to be a more appropriate factor for normalisation given the kind of infrastructure services involved. This has also been done in Rajaraman (2003).
2 Even if we normalised the loan figures by rural area or rural population, negative relation prevails even though level of significance declines.
3 We revisit this issue in the concluding section. 4 Data taken from www.indiastat.com. See also Karnataka at a Glance.
5 Calculations have also been done using net cropped area and we arrive at qualitatively similar results. 6 NABARD, Implementation of RIDF projects in
Karnataka: A Review, 2004.
7 Our discussions with the RBI officials in Karnataka reveal that such an attempt was taken in case of Karnataka.
| Madhya Pradesh* | 71.61 | Maharashtra | 29.23 |
| Arunachal Pradesh | 59.44 | Assam | 25.44 |
| Himachal Pradesh | 55.13 | Sikkim | 20.53 |
| Meghalaya | 54.67 | Mizoram | 16.69 |
| Manipur | 54.04 | Andhra Pradesh | 14.12 |
| Bihar* | 52.16 | Nagaland | 11.17 |
| West Bengal | 51.33 | Gujarat | 5.67 |
| Orissa | 50.86 | Punjab | 2.73 |
| Uttar Pradesh* | 49.59 | Haryana | 1.2 |
| Tripura | 49.07 | Kerala | 0.75 |
| Tamil Nadu | 48.82 | Karnataka | 0.38 |
| Rajasthan | 47.97 | Goa | 0.27 |
| Jammu and Kashmir | 34.19 | ||
| * Erstwhile, now two states. | |||
| Source: Economic Intelligence Services, CMIE, 1997. | |||
| 31 |
