I
West Bengal:
Fiscal Decentralization to Rural Governments:
ANALYSIS AND REFORM OPTIONS
MAIN REPORT
February 28, 2007
Table of Contents
1. INTRODUCTION 1
2. THE SETTING FOR LOCAL GOVERNMENT FINANCE IN WEST BENGAL 3
Local Government Structure 3
Fiscal Autonomy 3
State Finance Commissions. 5
3. III. RURAL LOCAL GOVERNMENT FINANCES 8
Budget Shares 8
Expenditure Structure 9
Concentration by Population Size 12
Composition of Expenditures by Population Size Class 13
4. REVENUE STRUCTURE 15
Own Source Revenues 15
Grants and Transfers 17
Centrally Sponsored Schemes 18
Grants and Transfers: State Government 21
5. Analysis of the disparities in gram panchayat Finances 23
Expenditure Disparities 24
Explaining Expenditure Variations 26
Own Source Revenues 28
Explaining the Distribution Impact of Intergovernmental Transfers 31
6. FINANCIAL CONDITION 34
Do Many Gram Panchayats Have a Negative Recurrent Revenue Gap? 35
Do the Results For Surplus GPs Indicate an Inability to Absorb the Funds? 35
To What Extent Do “Deficit” Gram Panchayats Draw On Their Cash Balance Reserves to Cover the Cost of Delivering Services? 36
Do the Closing Balances Change Over Time, and How Do We Explain This? Are These Closing Balances “Too Large”? 37
What Determines Financial Condition? 37
7. THE FISCAL POSITION OF BLOCK AND DISTRICT LEVEL GOVERNMENTS 40
Expenditures 40
Own-Source Revenues 41
Intergovernmental Transfers 42
Financial Condition 43
Summary 44
8. State Government and FISCAL DECENTRALIZATION 45
State Taxation 46
Redirection of Existing Funds 46
The Granting of More Fiscal Discretion 47
9. Reform Options and Evaluation 49
Decide on an Optimal Tier for Local Self Government 49
Expenditure Assignment 53
Increased Own Source Revenue 57
Increased State Grants: Determining the Vertical Share 59
A Formula Approach. 63
Increased, Untied Grants: A Formula Distribution 63
10. FINANCING THE FISCAL DECENTRALIZATION PROGRAM 67
REFERENCES 125
INTRODUCTION
This report is about the fiscal performance of rural local governments in the state of West Bengal. Specifically, our goal is to develop a comprehensive fiscal information system for all rural local governments, and to use these data to evaluate the intergovernmental finance structure in the state. The work is of significant policy importance, given the need to develop programs to respond to the constitutional amendments mandating fiscal decentralization[1], and to support central and state government initiatives to use the PRI system as an important part of its poverty alleviation strategy. A more immediate need in West Bengal (and other states as well) is to support the work of the State Finance Commissions to better integrate rural local governments into the intergovernmental fiscal framework.
Many observers of fiscal federalism in India have pointed out that fiscal decentralization to the third tier has not progressed very far since the constitutional amendments of the early 1990’s. State governments have held on to budgetary control and State Finance Commission recommendations to strengthen local government finances have in large part been ignored. Underlying this state of affairs is the fact that neither the central nor state governments have data that allow them to accurately evaluate and monitor the fiscal performance of the Panchayat Raj Institutions (PRIs).
At present, there is no accurate, official record of the fiscal activities of PRI in West Bengal. The existing data base is not comparable across local government units, is not readily available in one place or in electronic form, is incomplete, and is not linked to amenity or demographic databases. Every time the Department of Rural Development in West Bengal (or the State Finance Commission) carries out an analysis of gram panchayat finances, it must resort to doing a special survey[2]. The results presented in this report, based on primary data for nearly all PRIs in West Bengal, give arguably the first-ever look at the overall picture of rural local government finances in the state. The situation as regards socio-economic data is somewhat better in that there is a 2001 census. But even here, census data are missing for a substantial number of gram panchayats and the so-called “amenity data” have not been aggregated into a usable data base[3]. This is because the base measurement unit of the census is the sub-village level and aggregation to the gram panchayat level has not been done properly in every case.
In this report, we use data from a newly developed fiscal information system to study the fiscal performance of PRIs in West Bengal. The general outline of the data base upon which this report is built, and the methodology used in collecting and organizing these data are included in Annex A.
The first three sections of this report describe the structure of rural local government finance in West Bengal. More specifically, we describe the expenditure responsibilities and financing powers of local governments, and carry out an empirical study of how they use these responsibilities and powers. In Section IV, we focus on own source revenue and grants and transfers to PRIs from the central and state level governments. In Section V, we study fiscal disparities among gram panchayats in West Bengal and model an explanation of these variations. The concern in Section VI is with fiscal balance among the gram panchayats, i.e., with the extent to which they run deficits on current account and the extent to which they carry significant balances. A parallel analysis for block and district level governments is the subject in Section VII. In Section VIII, we examine the pivotal role of the state government in determining whether fiscal decentralization will take place. In the final two sections of this report, we evaluate some options for reform and the cost implications of these reform packages. While this work does profile the fiscal activity of all three levels of PRI, the focus is on gram panchayats. This is because of the view in West Bengal (and in many other quarters) that gram panchayats are the best candidate for local self-government.
This study can be a significant compliment to the work of the Third State Finance Commission in West Bengal, which is due to report in 2007. An added benefit from this study, hopefully, is that it may lift the level of the discussion about PRI finances among political leaders, technical experts, private sector leaders and voters in the state. It might also be useful as a model for similar work being carried out in other states.
THE SETTING FOR LOCAL GOVERNMENT FINANCE IN WEST BENGAL
In terms of budget responsibilities and resources, each of the three levels of local government within the rural sector is assigned a set of expenditure responsibilities, revenue raising powers, and entitlements from the grant system. These assignments are made by the State government under the guidance of the Constitution and the Panchayat Act. The expenditure responsibilities of rural local governments are spelled out in some detail in Government of West Bengal (2005). PRI finances also are impacted by the recommendations of the State Finance Commission concerning the distribution of fiscal resources between the state government and the local governments[4]. Finally, there are direct, conditional transfers from the central government to the PRIs and these constitute the major revenue flow to the local bodies. The impact of these three influences is described below.
Local Government Structure
The PRI system in West Bengal consists of 18 districts (zilla), 341 blocks (panchayat samatis) and 3,324 gram panchayats, as described in Figure 1. The urban stream of local governments, which includes municipalities and city corporations, is separate from the rural stream. The rural and urban local governments operate under different enabling legislation, and each is allocated a specified share of the state government revenue sharing pool.
Perhaps as befits a state with more than 80 million people, the structure of rural local government is a hierarchical one. Local officials report up to the next highest level. Moreover, the flow of most intergovernmental transfers passes through the district and block levels before reaching the gram panchayats. Budget approval by PRIs, however, does not have to be sought from a higher tier of local government.
Fiscal Autonomy
The data presented in this report describe the pattern of spending and financing by rural local governments. But, data alone cannot reveal the degree of autonomy that local governments have in making fiscal decisions. There are elected local governments in West Bengal and each has the power to approve their budget. In fact, however, the degree of fiscal discretion that is underneath the making of these budgets is limited by expenditure mandates and by constraints on revenue-raising powers.
Local governments are given no powers to exceed their assigned complement of employees, nor do they have any power to determine the rate of pay of their employees. So, the wage bill of local governments is fixed from above.[5] In addition, there are expenditure mandates, e.g., the central schemes are conditional grants with narrowly prescribed expenditure targets.
The gram panchayats (GPs) are thought by some to be more like autonomous local governments than are districts or blocks. For decades, the idea of village government with some degree of autonomy has been discussed in India. Gandhi’s vision of village swaraj has influenced subsequent discussions of the need for local self-governance (Alok, p. 207). Moreover, there is provision for this in Article 40 of the Constitution. With the passage of the 73rd constitutional amendment, local governments were again recognized, and more explicit provision was made for planning and service delivery responsibility and for revenue raising powers. In most states, the gram panchayats have been given more fiscal autonomy than districts and blocks, including some independent power to levy certain taxes[6]. However, in West Bengal, this has led to only about 6 percent of GP expenditures being financed from local sources. On the side of expenditure composition, GPs play a role in project selection; hence to some extent they can be responsive to special needs in various locations within the gram panchayat. Otherwise, most of their expenditure budget is driven by mandates from higher level governments.
The blocks and districts have less fiscal discretion on the revenue side than do the gram panchayats, even though they sit higher in the local government hierarchy. They may raise revenues from fees and charges, and have the authority to set the rate for some of these charges, but they have no taxing power. They rely primarily on grants and transfers for their general purpose finances (only about 3 percent of their revenues are raised from own sources). Therefore, the size of the block and district budget is mostly determined by higher-level governments.
On the expenditure side, districts and blocks face the same restraints on their budget choices as do gram panchayats. The expenditure discretion that they do exercise is in the capital budget, and it relates mostly to project selection and implementation with respect to centrally sponsored schemes. With respect to State grants, only a small proportion is unconditional (untied). Most state grants and transfers in West Bengal are conditional and give local governments little room to rearrange the priorities laid down by the state government. Though governed by elected councils, the districts and blocks appear to function largely as spending agents of the state and central governments.
State Finance Commissions.
The State of West Bengal has received reports from two State Finance Commissions (SFC)[7]. The first SFC was constituted in 1994 and reported in 1995. The “period of recommendation” was 1996-2001. The second SFC was constituted in 2000 and made an interim report in 2001, with a period of recommendation of 2001-2006. The third SFC is now sitting with a report expected in 2007.
According to the West Bengal Panchayat Act and The Constitution, the charge of the SFC is far-reaching. Its report is to contain recommendations:
“…on the principles that should govern the distribution of state revenue between the state and the Panchayats and the allocation between the Panchayats, at all levels, of their respective shares of such proceeds. The Commission was also required to recommend the principle that should govern the distribution of the revenue resources between the state and the Municipalities and the allocation between the Municipalities of their respective shares. The Commission would also determine the taxes, duties, tolls and fees which could be raised by the Panchayats and the Municipalities. The Commission would also recommend measures needed to improve the financial position of the Panchayats and the Municipalities.”
In effect, the SFC is empowered to recommend a complete overhaul of the system of state and local government finance. Though there were numerous recommendations made by both West Bengal Commissions as regards intergovernmental finance, the focus has been heavily, if not exclusively, on the revenue side. This is similar to the approach that has been taken by State Finance Commissions in other states (Subrahmanyam, 2004), and it is consistent with the charge given to the SFCs in the constitutional amendments. Still, if the focus of the SFC is to be on ensuring adequate financing, a strongly implied responsibility is to determine optimal expenditure assignments. Otherwise, how could adequacy in “revenues” be determined?
Arguably, the most important proposal of the first two State Finance Commissions was for a vertical share of 16 percent of state taxes as a grant entitlement of local governments. Acceptance of this proposal would have led to a very significant increase in fiscal decentralization. It was also proposed that these grants be “untied”, i.e., that the recipient local governments be given the discretion to spend this money in any way they choose.
This primary recommendation of the Second SFC was not accepted by the state government[8]. Instead, they decided on a program where a fixed allocation would be made to a PRI revenue sharing pool each year, depending on the financial condition of the state. In fact, even this approach was not acted on by the State government in 2004 and 2005. In these two years, the State government did not distribute finance commission grants to the local bodies. In 2006, the vertical share was set at Rs 278 crore, which is about one-half the amount recommended. The sharing of this pool of funds among local governments, however, is done by formula, and in this regard, the recommendations of the SFC have been followed.
Other important recommendations of the State Finance Commission were in the area of own-source revenues of PRIs, where the need for a revenue increase and the need for more autonomy were seen to be important. The First SFC proposed to devolve entertainment tax revenues fully to local governments and to give rate setting powers to the local bodies. The Second SFC called for full devolution of entertainment tax revenues to local governments, but not for rate-setting powers. The State Government has chosen to hold the power to set rates but to transfer 90 percent of the revenues raised to local governments. Both State Finance Commissions argued for devolving the powers to set for the level of various charges. State government has not moved very far in this direction.
One could make the argument that the West Bengal State Finance Commissions have not been very successful[9]. Their major recommendation, that a general revenue sharing program with a 16 percent vertical share be established for local governments, was not accepted. There are many reasons for this, with the precarious fiscal position of the state government being the most common explanation. There were, perhaps, other shortcomings. A reasonable critique of the principal recommendation is that the 16 percent share was not justified by a hard analysis of the expenditure needs of the local governments. To date, neither of the SFCs nor the State Government has based their recommendations for a vertical share on expenditure needs. Oommen (2006) studied the outputs of five other State Finance Commissions and found that none estimated the vertical gap based on a hard analysis of expenditure needs. Correcting this problem is arguably the next important step that the SFCs should take to improve the acceptability of their recommendations.
Another critique of the SFC work in West Bengal (though this problem was out of their control) was that neither commission had access to a reliable data base of PRI finances, as has been developed here. The extent to which the absence of fiscal information constrained the work is well-described by the following quote from “Recommendations of the Second State Finance Commission” (p. 26):
“Data regarding resources of the different tiers of the Panchayats were not available at the State level. In view of this we circulated a questionnaire to all the Panchayats. Responses to this questionnaire were not uniform. Seven hundred and nineteen (719) out of 3362 gram panchayat sent replies but the data in respect of only 170 gram panchayat could be used. We also received information from 142 PSs out of a total of 341 while 10 out of 17 ZPs responded to our questionnaire. In spite of better administrative infrastructure available at the ZP level, it is difficult to understand why larger number of ZPs could not respond. We are aware of the inadequacy of the data and the problems of generalization from the same. While in respect of PSs and ZPs, the data could be taken to be fairly representative, in respect of gram panchayat this would at best give an indication of their state of finance.”
The combination of this absence of data and very limited staff resources made it difficult (impossible) for the SFC to fully evaluate the impacts of its proposed reforms.[10] Whether a better evaluation of impacts would have led to a different proposal, or to a different response from the state government, is something that we may only speculate about. The Third Finance Commission in West Bengal faces this same data constraint.
III. RURAL LOCAL GOVERNMENT FINANCES
The data base developed for this project is used here to investigate the fiscal importance of rural local governments in West Bengal, the structure of their expenditure outlays, and the sources of their finances. The goal is to develop a fiscal profile for different levels of rural local government, with special attention paid to the gram panchayats. Such information can be used by government to track rural local government finances in the state, and to evaluate reform options. It is an essential piece of evidence that heretofore has been missing from the policy analysis.
Budget Shares
The place to start this investigation of rural government finances is with an understanding of the relative importance of the PRIs in the state fiscal system. In Table 1 we show the fiscal shares of different levels of government in West Bengal. Note that 72 percent of the state population is resident in rural areas, but less than 17 percent of government expenditures are made by rural local governments[11]. The point to be taken from this comparison of population concentration and expenditure concentration is not that rural residents are being discriminated against by the fiscal system (the State government vertical programs may or may not emphasize rural benefits), but that rural local governments are quite small players in the state fiscal system, and they are much smaller players than are urban local governments. In total, expenditures by rural local governments are equivalent to less than one percent of state GDP. One could safely say that there is not much local self governance in rural areas of West Bengal.
The 17 percent share of expenditures managed through panchayats in West Bengal is not so far out of line with that in at least some other Indian states where data are reliable. Rao, et. al., (2004) estimate that about 20 percent of expenditures are channeled through panchayats in Karnataka, while Oommen, et. al. (2004) estimate the share at closer to 30 percent in Kerala.
West Bengal’s system of government finance is even more centralized on the financing side of the budget equation: 96 percent of all revenues raised are at the state government level. Rural local governments account for less than one percent of all own-source revenues raised. Even this small amount is an overstatement of their importance in revenue mobilization because local governments have limited discretion to determine the amount they will raise.
Another way to describe the small role of rural local governments in public financing is to note that local government expenditures are Rs 452 per person for urban residents as compared to Rs 138 per person for those who live in rural areas.[12] Voice in fiscal decisions at the community level is a benefit that would appear to be more important for urban voters than for rural voters.
We also may ask about the relative importance of the three tiers of PRI in terms of expenditures and own source revenues. From Table 1, we can see that the district governments account for about 45 percent of the spending of all PRIs[13]. More important is the finding that the gram panchayats in aggregate account for only about one-third of spending.[14] Thus about two-thirds of PRI expenditures are made by districts and blocks, who under the present structure, might be better thought of as spending agents of the state government. Under this interpretation, we may say that of all state and local government expenditures made in West Bengal in 2005, only about one-third was made by the level of government that that many would argue comes closest to approximating local self governance[15].
On the side of own source revenues, districts raise approximately the same share as the gram panchayats (who have access to both tax and non tax sources). The revenue raised by districts is a mixture of licenses, fees and charges such as fees to oversee tenders or the work of contractors, and revenues from district-owned enterprises. The block level raises very little own source revenue (Table 1).
Expenditure Structure
How do rural local governments spend their money, and how much variation is there across local governments? Interestingly, the budgets are dominated by spending for capital purposes at all three levels (Table 2). District governments report that 85 cents of every rupee spent is for capital purposes. The capital expenditure share in blocks and in gram panchayats is closer to 60 percent. In a sense, this is a correct representation of the expenditure pattern in that these reported capital expenditures are made to purchase or create assets with a longer life than that of the annual budget.[16] But, the percentages shown in Table 2 are surely an overstatement. Much of this expenditure carries the objective of job generation hence might be thought of as part of an income maintenance package and therefore as a current expenditure. Moreover, the assets created by these public works projects may be more akin to maintenance and repair than to new construction. Also suggesting the temporary nature of some of these projects is the fact that the use of machinery in the work is prohibited, as is the use of contractors (Government of India, 2006).
Some flavor of this capital expenditure activity in the PRI can be gained from the guidelines for the SGRY (employment generation) program. The SGRY specifies that the grant must be spent for the creation of durable assets, particularly those that would assist in drought-proofing such as soil and moisture conservation works, watershed development, promotion of traditional water resources, and afforestation, as well as construction of village infrastructure and link roads, primary school building dispensaries, veterinary hospitals, and marketing infrastructure (Government of India, 2006). While the assets created under this program may or may not be long-lived, they do seem to be more in the vein of development than consumption expenditures.
So, one can argue that rural local governments emphasize capital spending, but the numbers reported in Table 2 should be interpreted in the context given above.
A second thing to note about the pattern of rural local government expenditures is that there is specialization among the tiers of rural local governments in terms of functional assignment. As shown in Table 3, block governments are more involved in delivering social services through their budgets than are either districts or gram panchayats. Health, education, and welfare programs account for one-third of block-level budgets, by comparison to 10 percent or less for districts and gram panchayats. Block spending in the health area covers a range of responsibilities such as maintenance and upgrading of community health centers, supervision of primary curative services, implementation of immunization and safe drinking water programs, and monitoring and planning (Government of West Bengal, 2005). With respect to education, the blocks manage the mid-day meal program and with respect to welfare they are responsible for beneficiary selection for a number of programs. However, block level governments in West Bengal have been little involved in housing programs. And again, it should be emphasized that they have little discretion in deciding how to spend these funds.
The reported data (Table 3) show districts to spend primarily for housing, infrastructure, and employment generation (77 percent of total expenditures), a finding that seems reasonable for the level of government that can best handle service delivery responsibility when the benefit zone covers multiple blocks and gram panchayats. The budgetary expenditures of districts appear to be dominated by those programs financed as centrally and state sponsored schemes. This seems consistent with the idea that district governments are primarily spending arms of higher level governments.
The much smaller gram panchayat’s comparative advantage is in delivering services and implementing schemes where the benefit zone is local. For the most part, their expenditure assignments reflect this comparative advantage. Though there is some responsibility for education, e.g., implementing continuing education programs, the budgetary expenditures of gram panchayats are dominated by development programs (61 percent of total expenditures) that are mostly financed under the centrally sponsored schemes. Again, there is the issue of whether these are capital expenditures related to the creation of long-lived assets, or current expenditures to support an income maintenance program. Arguably the most noteworthy observation to make about gram panchayats is the 20 percent share of the budget devoted to administration and salaries (Table 4), compared to less than 3 percent for districts and blocks. This reflects some combination of the labor intensive nature of the services delivered by gram panchayats, the large amount of responsibility for management type activities, and apparently a high fixed cost associated with operating small local governments. This fixed cost effect is described in Box 1.
|Box 1 |
|The Fixed Cost of Rural Local Governments |
| |
|There is a fixed cost of local government that is independent of population size. All local governments have in common the need |
|for a secretary, bill collector, support for the local assembly, a basic level of physical faculties, etc. In fact the State of |
|West Bengal assigns the same number of posts for each GP, and determines the compensation rate for these posts. To the extent that|
|all posts are filled, salaries may be viewed as a fixed cost of local government, and do not vary much with the population size of |
|the local government. |
| |
|To test this hypothesis, we have pulled a sample of the 20 largest (population) and 20 smallest GPs. The average population for |
|the 20 largest GPs is over 10 times that of the 20 smallest. The calculations of the average fixed costs of each group are |
|reported in the table below. |
| |
|The overall level of administration expenses is higher in the larger GPs, but on a per capita basis, the fixed cost argument is |
|very apparent. The smaller GPs spend 4 times as much as the large GPs (per capita) on administration expense. The lower value for|
|the larger GPs reflects the ability to spread these costs over a larger resident population. |
| |
|In the case of salary expenditures, the total amounts are about the same, for large and for small GPs. The per capita amounts in |
|the smaller GPs, however, are about 15 times higher. |
| |
| |
|Table Box 1 |
|Fixed Cost Effects: For 20 Largest and Smallest GPs |
|(in Rs) |
| |
|20 Largest 20 Smallest |
|Administration Expenses Per GP 128,103 67,606 |
|Salary Expenses Per GP 347,798 375,377 |
|Administration Expenses Per Capita 6.8 27.7 |
|Salary Expenses Per Capita 10.3 146.0 |
| |
|Source: Source: PRI-West Bengal data base: The World Bank (see Annex A) |
Concentration by Population Size
An important question has to do with the concentration of expenditures among local governments with different population sizes. In particular, we are interested in the extent to which the expenditures of rural local governments in West Bengal are dominated by their larger members.
One might begin with the null hypothesis that the small gram panchayats have too little capacity to play a significant role in the rural local government fiscal system. If this is the case, one would expect that the per capita expenditures of smaller GPs would be lower. To test this, we examine the expenditure pattern for 2,959 gram panchayats, divided into four population size categories, and report the results in the bottom panel of Table 5.[17] The percent of spending by gram panchayats in each size class is then compared to the percent of population in that size class. These results (Columns 2 and 3) do not support the null hypothesis. They show that the smallest gram panchayats (under 15,000 in population) are more important in the local fiscal structure than their population share would suggest. The 849 gram panchayats in this size class account for only 18.6 percent of the rural population, but for 24 percent of the total spending by all gram panchayats. In all other population size classes, the share of population equals or exceeds the share of expenditures.
If more heavily populated local governments are more developed, and have the better capacity to deliver services, this is not the pattern that one would expect. In fact, the notion that more heavily populated GPs in West Bengal are more prosperous is not fully supported by the data. As may be seen from the matrix of simple correlation coefficients in Annex Table B-3, larger GPs tend to have significantly lower literacy rates, suggesting less wealth. However, they also have significantly lower proportions of SC/ST populations, smaller shares of female population, and lower percentages of marginal workers. These patterns suggest that more heavily populated gram panchayats have higher levels of income. Unfortunately, there are no income or product data available for GPs, so we cannot directly test for a relationship between each of these factors and the level of development of a GP.
Another explanation of the seemingly counter-intuitive result presented in Table 5 is that the transfers associated with centrally sponsored schemes are distributed away from more heavily populated gram panchayats, and this is the source of the negative relationship between population size and per capita expenditures. In fact, the data are consistent with this hypothesis in that the simple correlation between population size and per capita revenues from centrally sponsored schemes is negative and significant (Annex Table B-3).
Finally, we may attribute part of this result to an economies of size effect that leads smaller local governments to spend more in per capita terms. This is explained in Box 1.
In Column 4 of Table 5, we report the distribution of own source revenues raised, according to population size class. Our expectation is that larger population suggests agglomeration effects, such as regional markets or entertainment events, or more developed infrastructure. All of these suggest a greater capacity to levy taxes and assess user charges. Again, the result is surprising. The largest gram panchayats (over 25,000 in population) account for about 19 percent of the total population but for only about 15 percent of own source revenues raised. The fact that own source revenues are more concentrated among the gram panchayats with fewer than 25,000 in population suggests that either the more heavily populated gram panchayats are less developed than might be supposed, or that they do not make as much effort in revenue mobilization as do the smaller places.
We have repeated this analysis for blocks and districts, as shown in the top panels of Table 5. For the 288 blocks examined, the results are much the same as for gram panchayats. The smallest size class accounts for only about 22 percent of the population but over 29 percent of total spending. The largest block governments (those with populations above 250,000), by contrast, account for a greater share of population than of expenditures. And, as in the case of the gram panchayats, the largest blocks account for a small share of total own source (non-tax) revenues mobilized relative to their population. The hypothesis that larger populations lead to better capacity to spend and to raise revenues is not consistent with these statistical results.
For the 17 districts studied, the same pattern holds with respect to the concentration of expenditures (Table 5). The four districts with the smallest populations (less than 2.5 million) account for a disproportionately large share of expenditures. The reverse is observed for the four largest districts. This result is almost certainly due to the allocation formulae for centrally sponsored schemes. However, unlike the case of GPs and blocks, these four largest districts account for about 40 percent of the population but over 50 percent of own source revenues raised. In terms of user charges and license collections, and perhaps revenues generated from assets owned by these governments, larger districts would appear to have some comparative advantage and perhaps more willingness to make use of their revenue-raising powers.
Composition of Expenditures by Population Size Class
Is there much variation across gram panchayats with different populations in terms of the distribution of their expenditures by function? The issue of most interest here is whether the smaller local governments are forced to restrict their spending to more administrative functions, perhaps because they have a limited capacity to deliver services. The answer we get from the results reported in Table 6 is that there is a population bias in the functional distribution of gram panchayat spending. The share of capital expenditures in total expenditures (mostly for employment generation and low income housing assistance) rises with population size[18]. Two possible explanations for this pattern are that there are greater needs for housing in more heavily populated gram panchayats, and that funds available for housing and other infrastructure investment are allocated disproportionately to more heavily populated places. (These two possibilities are examined in more detail in the discussion below.) A third explanation is that the fixed costs of operating a local government force smaller gram panchayats to allocate a larger share of their budgets to administrative functions. In fact, the data in Table 6 show that the smaller gram panchayats do allocate a disproportionately large share of their budgets to administrative and salary expenditures.
The results for blocks, and particularly for districts, also show a dominance of capital expenditures in the budgets (Table 6). This pattern would be consistent with the view that districts are primarily involved in the implementation of central and state schemes, and are much less a local government than a spending agent of the state.
REVENUE STRUCTURE
“How do rural local governments finance their budgets? To what extent do they pay for services from own sources of revenues and to what extent do they pay from central and state grants and transfers?” About 6 percent of all revenue of gram panchayats is derived from own sources (Tables 7 and 8). This is less than the 20 percent estimated by Rao, et. al. (2004), for Karnataka for 2001, and the 17 percent estimated by Oommen et.al. (2004) for Kerala in 1999.
The share of revenues raised from own sources (including tax and non tax revenues) is less for smaller gram panchayats than for larger places (Table 7). From the data in this table, we can see a general pattern of gram panchayats of all sizes raising more revenue from non-tax fees and charges than from tax revenues. The dependence of blocks and districts on intergovernmental transfers is slightly higher than that of gram panchayats (Table 7). This is because districts and blocks have no taxing powers. These measurements underscore the finding that there is a very strong degree of revenue centralization in West Bengal state.
Own Source Revenues
The Constitution provides for gram panchayats to have the power to tax, i.e., to determine the effective rate at which certain bases will be charged. However, it is left to the state governments to determine which taxes a local government may levy, as well as the nature of the autonomy that local governments will have in determining their level of taxation. The broad-based taxes are denied panchayats, in all states, and this seems appropriate given their limited administrative capabilities. Otherwise, states differ in terms of the revenue sources they assign to local governments, and there is by now a long list of taxes that are locally administered in India. In their review of the practice in Kerala, Gujarat, and MP, Subrahmanyam and Annamalai (2004, p. 275-276) report 14 different categories of tax that are in use.
Rural local government taxes in most countries tend to be narrow-based and administratively difficult. But even so, they have the potential to significantly increase the level of revenues available to the local governments. By one estimate, rural local governments in West Bengal raise a per capita amount of own source revenue that is equivalent to about one-fourth the all-India average (Alok, 2006, Table 6.6). Based on this interstate comparison, it would seem that there is significant potential for additional revenue mobilization by local governments in West Bengal.
The term “own source revenue” requires some explanation in the case of rural local governments in West Bengal. The normal definition requires that local governments have the power to at least set the tax rate (Bahl and Linn, 1992, chapter 12; Bird, 1999). For the property taxes and the entertainment tax in West Bengal, the rate and base are prescribed by the State Government in the Panchayat Act. The gram panchayats have the power to set a property tax rate, but may not exceed the ceiling rate set by the state. Gram panchayats do have some discretion, however, in their administration of the property tax and in terms of setting the rates of certain non-tax fees and charges.
Property and Land Taxes. The gram panchayat level in India has been empowered in most states to levy a land and building tax. In theory, the base of the tax is the annual rental value of land and buildings.[19] In practice, the tax is levied on an area basis, or a housing unit basis, or on some other notional basis. At least one study in West Bengal reports a “backward” method where the amount of tax is determined first and then taxable property value is calculated as a residual (Pal and Adak, undated). It seems fair to say that the current practice is one where there is no valuation process by which some scientific method is used to estimate a market value. Neither is there a method to revalue properties in a systematic way. The local governments are responsible for keeping the tax rolls and for collections and enforcement.
In West Bengal, unlike in many other states, the tax base includes both agricultural and non-agricultural property. Properties with a value less than Rs 250 are exempt from tax. The maximum tax rates, set by the state government, are one percent for properties with an annual value less than Rs 1000 and two percent for properties with an annual value greater than Rs 1000. In addition, the gram panchayat may levy a property transfer tax on immovable property. The tax rate is 2 percent and the base is the selling price (consideration) in an arms length transaction.
We do not have data on property tax revenue. However, a reasonable guess is that most of the tax revenue reported for gram panchayats in West Bengal is property tax. Per capita total own source revenues for GPs is about Rs 8. Property tax performance is very weak.[20]
One might offer a number of explanations for this poor revenue performance. First, properties may be dramatically under assessed. We have no direct evidence on this but can report a widespread belief in West Bengal that valuation practices are very ad hoc. Second, collection rates can be very low. Pal and Adak (undated) estimated a ratio of collections to demand (assessed liability) of 26 percent in 2001. A recent SRD study (undated) made a similar estimate of the collection rate, based on data taken from a sample of gram panchayats[21]. Low collection rates may be traced to several factors:
• lax or inept administrative practices
• inadequate staffing and poorly trained staff
• residents do not see the value of paying taxes in terms of the services they receive from the GP, and therefore resist payment.
• GP leaders are hesitant to enforce the tax on the local elite.
Entertainment Tax. The entertainment tax is levied on admissions to various events. The Act defines entertainment as exhibitions, movies, performances, amusements, and games or sports to which persons are charged admission. The tax rate is 10 percent.
In West Bengal, the tax is levied and collected by the State government with 90 percent of the proceeds returned to local governments. The return is by formula: 80 percent to urban local bodies and 20 percent to rural local governments. Therefore, the entertainment tax is really an intergovernmental transfer, i.e., the tax rate and base are determined by the central government, collections are made by the central government, and the central government decides on how the proceeds will be divided among local governments.
The first SFC recommended turning this tax over to local governments, and giving them discretion to set the rates. The state government did not accept this proposal. The Second State Finance Commission did not call for full conversion to a local tax, but did hold to the recommendation that revenues be fully devolved. The State government has for the most part accepted the recommendation of the second SFC. It argues that an intergovernmental transfer is a better approach than a local entertainment tax because it (a) can reflect the superior ability of the state government to collect the tax, and (b) can allow rural local governments (whose residents may travel to urban entertainment events) to share in the revenue proceeds.
Grants and Transfers
About 94 percent of total revenues of the gram panchayats come from grants and transfers. The share for districts and blocks is even higher. The composition of these grants and transfers is described in Box 2, with revenue distributions for 2005 summarized in Tables 8 and 9.
|Box 2 |
|The Components of Intergovernmental Transfers |
| |
|1 State Government |
|Finance Commission Grants |
|Untied Grantsa |
|Salary Grants |
|Other Grants |
|BEUP |
|State Sponsored Schemes (Minideep, PROFLAL, other) |
| |
|2. Central Government |
|Finance Commission Grants |
|Centrally sponsored schemes (SGRY, IAY, NSAP, IMY, midday meal, SSA, other) |
|MPLAD, other |
| |
|a Untied grants include funds devolved to the Panchayats from the Government, the use of which is not restricted to any specific |
|purpose. In some GP statements, untied funds are termed as ‘Shartaheen Fund’. Untied funds include the following: (a) ‘Lump |
|grant’ which is a lump sum amount received by the panchayats from the Government and can be used by the panchayats for any |
|development purpose, (b) ‘Matching grants’ which are funds received from the Government to bridge any deficit faced by the |
|panchayats in meeting their expenses; matching grants are also termed as ‘Paripurak Anudan’ or ‘Sampurak Anudan’ in some |
|statements, (c) Other untied funds. |
Centrally Sponsored Schemes
The centrally sponsored schemes are by far the largest share of revenues, as may be seen in Table 8. About 75 percent of PRI transfers and 70 percent of PRI revenue is from the centrally sponsored schemes. Over two-thirds of this total for gram panchayats is accounted for by the IAY and SGRY schemes (Table 9). The share of centrally sponsored schemes for blocks and districts is even higher (in the range of 80-90 percent as indicated in Table 8), emphasizing again the agency role they play in implementing central government programs.
SGRY. The SGRY is an employment generation programme for rural areas that is targeted to benefit the poorest segment of the rural population (Government of India, 2006). The stated objectives of the program are to provide wage employment in rural areas and to create a durable social and economic infrastructure. The program is administered by the PRI, who have some discretion in deciding on the type and location of public works projects that will be carried out. There are limits on this discretion. Since this is a conditional grant, certain rules are prescribed on the use of these funds. Moreover, the action plan of each PRI must be approved by the next level up, e.g., gram by blocks, blocks by districts, etc.
The total funding for the programme for each year is decided on by the central government in the course of the normal budget process. There is no fixed formula defining the SGRY entitlement as a share of central taxes or of the central budget. In recent years (2003-2005) the national plus state allocation has been Rs 6000 crore plus 50 lakh tons of food grains. The entitlement (vertical share) for each state is decided upon by the central government, based on a formula that ranks states according to their share of the rural poor population in India.
The Central Government amount[22] for each state is paid directly to districts. This is done according to a formula that gives equal weight to the proportion of SC/ST population and to the inverse of production per agricultural worker. The Central Government prescribes how the revenues will be shared among PRI within a district: 20 percent to the district governments, 30 percent to the blocks and 50 percent to the gram panchayats. A matching requirement from the state government is mandated in the ratio of 75 percent central and 25 percent state. The state government uses the same formulae as the center in allocating its 25 percent share across rural local governments.
The districts make the allocations among blocks and among gram panchayats, but again according to formulae laid down by the Central Government. The 30 percent entitlement of blocks is distributed half by the proportion of SC/ST population and half by the proportion of rural population, with both variables measured relative to that of the district. The 50 percent share of gram panchayats is allocated by formula, subject to a minimum entitlement of Rs 25,000 per local government[23]. In fact, the gram panchayat share of SGRY can be even larger than is indicated by these formulas. This is because some district and block schemes are implemented at the GP level and the funds associated with these schemes pass through the GPs. We cannot identify these amounts separately.
The gram panchayat shares also can be smaller than these formulae suggest. This is because some GPs do not spend the funds fast enough to trigger the full release of the entitlement during the fiscal year.
Certainly the PRI have no discretion in determining the amount of their entitlement under SGRY. Nor do they have discretion to shift this money toward expenditures for other purposes. The discretion of gram panchayats in using this money is also limited by the requirement that it must be spent on infrastructure projects that employ unskilled labor, and that 50 percent of the funds be used for infrastructure development work in localities with a larger SC/ST population.
In theory, the PRI do have discretion in project selection. They are charged with developing an action plan that lays out the projects to be undertaken. (These plans must be approved by the next higher level of government). In practice, the discretion that PRI have in implementation may be very limited. One study argues, with respect to SGRY that “… the role of PRIs in planning and implementation is insignificant” (World Bank, 2005, p6). It is argued that line department officials take on a supervisory role and that central guidelines lead all key decisions about projects.
As may be seen in Table 9, SGRY transfers are a larger share of intergovernmental transfers in districts than in either blocks or gram panchayats. This is a surprising finding in that districts are supposed to retain only 20 percent of the total received, and the gram panchayat share is 50 percent.
IAY. The Indira Awaas Yojana (IAY) is a flagship scheme of the Ministry of Rural Development to provide houses to the poor in the rural areas (Government of India, 2006). The objective of the program is primarily to help construction/upgrading of dwelling units of members of Scheduled Castes/Scheduled Tribes, freed bonded laborers, others below the poverty line, and other needy groups[24] by providing them with financial assistance. The construction of the house is the sole responsibility of the beneficiary.
The IAY is a Centrally Sponsored Scheme funded on a cost-sharing basis between the Government of India and the State Governments, in the ratio of 75:25.
Central assistance under the Indira Awaas Yojana was originally allocated to the States/UTs on the basis of poverty ratio and housing shortage, with each of these variables being given equal weightage. Since 2005-2006, the weightage is 75 percent housing shortage and 25 percent poverty. The estimated poverty ratios prepared by the Planning Commission are used for this purpose, while housing shortage is determined on the basis of the most recent census data available. The proportions of rural SC/ST population (25 percent) and housing shortage (75 percent) in a district, relative to that of the State/UT, are the criteria for the allocation of the Indira Awaas Yojana funds within a State/UT. The numbers of houses to be constructed for each block and gram panchayat within a district are decided in the same way, but by the district government rather than by a strict formula. Once the block or gram panchayat is notified about the number of beneficiaries, it may decide on the specific beneficiaries, according to the guidelines of the program. Hence there is some discretion for the local government to decide on the distribution of benefits.
As may be seen in Table 9, IAY transfers are a larger share of intergovernmental transfers in gram panchayats than in districts. Block level governments in West Bengal were little involved in the IAY program in 2005. These results do not suggest a pattern in terms of the involvement of PRIs of different population sizes.
Other Central Schemes and Grants. There are a number of other types of central transfers to rural local governments. The “other schemes” category shown in Table 9 includes several assistance programs that are targeted on various sectors. Together, these amount to about 10 percent of total central transfers in the case of districts and blocks, and 7.5 percent in the case of gram panchayats.
The Member of Parliament Local Area Development Scheme (MPLAD) has the goal of enabling members of parliament to suggest and facilitate execution of development works based on local needs. The amount of MPLAD allocations are not trivial, especially by comparison to state government allocations to PRIs, as may be seen in Table 9. The funds go primarily to the block level.
The Twelfth Finance Commission grants, earmarked for operating costs of water and sanitation, account for a significant share of transfers. This award continues a tradition begun by the Eleventh State Finance Commission. The distribution among districts, blocks, and gram panchayats is shown in Table 9.
Grants and Transfers: State Government
The state government provides financial transfers to the PRIs through three types of programs: State grants, State sponsored schemes, and BEUP. These assistance programs, to the extent they carry conditions, allow the state government to influence the pattern of spending by the PRI. State government transfers are a relatively small 25 percent of gram panchayat revenues and an even smaller share for districts and blocks.[25]
State Grants. There are several state government transfers in the financing structure in West Bengal, but they take on most significance as a share of revenues in the case of gram panchayats (See Table 8)[26]. The State Finance Commission grant has the feature of being unconditional, hence it is in step with a decentralized fiscal strategy. It is this program that has drawn the attention of the two State Finance Commissions and led to the recommendation of a 16 percent vertical share. But, as may be seen in Table 10, the state government made no distributions under this program in 2004 and 2005. In 2006, the amount distributed was fixed at Rs 278 crore, and it is reported that the intent is to distribute this same amount in 2007.
The most important component of state grants is the salary grant. This is a cost reimbursement allocation to PRIs based on their number of approved posts. Since the state government approves posts, and sets pay grades, this transfer leaves the local governments with little discretion in terms of how the grant can be spent. The salary grant is equivalent in amount to nearly 80 percent of all state transfers received by gram panchayats and nearly 60 percent in the case of districts (Table 10).
Third, there are the so-called “untied grants”. The untied grants are a collection of unconditional grants (e.g., the lump sum grant, matching grants) that are of primary importance to district governments.
Finally, there are the BEUP grants made through state legislatures. As may be seen in Table 10, these grants (similar to the central MPLAD grants) are most important as methods of financing block level expenditures.
State Sponsored Schemes. In addition to the State Finance Commission and the salary grants, the State provides funding to the PRIs for various specific schemes. These schemes are targeted programs, for which the PRIs have little expenditure discretion. The schemes include:
• “Minideep”, which is an irrigation scheme to promote groundwater irrigation. The mini deep tubewells that are supported by the program are operated by electricity and all the operation and maintenance costs are borne by the State government.
• PROFLAL or Provident Fund for Landless Agricultural Laborers is a social security scheme for the landless agricultural laborers
The fiscal importance of the state intergovernmental transfers is described in Table 10. These constitute less than 3 percent of the total amount of state transfers received by gram panchayats.
Analysis of the disparities in gram panchayat Finances
There are significant variations in the socio-economic conditions existing in gram panchayats, blocks and districts. These underlying conditions are the basic determinants of expenditure needs, fiscal capacity, and the ability to attract central government transfers, and should help us explain fiscal disparities among local governments. Most empirical studies begin with per capita GDP as a standard for measuring variations in the capacity to finance services. In West Bengal, however, we have no data on per capita GDP below the district level. As an alternative, we might use the data available on socio economic condition to justify some proxy measures of poverty and economic development.
Various analyses in West Bengal have used four proxy measures of the concentration of poverty in gram panchayats: (a) the percent of population in scheduled castes and tribes, (b) the percent of the population female, (c) the percent of marginal workers, and (d) the rate of illiteracy.[27] In this study, we use population to measure size, and to measure the level of economic development, we use the literacy rate and the percent of employment in non-agricultural labor.
The variations across PRIs in these indicators are shown in Table 11. The mean values are reported in the first column of each panel, with the number of units reporting shown in parenthesis.[28] The next three columns show the range and relative variation in each indicator. For example, for the second row, we can see that for the 17 districts reporting, the average share of SC/ST in the total population is 32.1 percent. The lowest share is 13.3 percent and the highest is 55.6 percent, with a coefficient of variation of 37.2.[29]
Note from the minimum and maximum values in the table that the variation across gram panchayats is quite large in the case of some of these measures. For example, the literacy rate among gram panchayats ranges from a low of 12.5 percent to a high of 79.4 percent. Such variations may be telling for variations in fiscal performance. Literacy is likely to be associated with stronger economic development and therefore revenue mobilization. We expect that gram panchayats with low levels of literacy will obtain less own source revenue than those with higher literacy rates.[30] The disparities in literacy rates are also a reflection of expenditure need, which is likely to be much more acute in those gram panchayats with low levels of literacy[31]. This should be reflected in the flow of revenue from central schemes for poverty alleviation. The percent of marginal workers in the population also shows large disparities across gram panchayats.[32] While the average percent of marginal workers among GPs is 11 percent, in one GP, it is over 40 percent. In gram panchayats where there are larger proportions of marginal workers, there tends to be a significantly larger share of SC/ST population, a larger share of females in the population, and a lower literacy rate. The percent of marginal workers, then, seems a reasonable proxy for the backwardness of a gram panchayat, and an indicator of greater expenditure needs.
There also are substantial differences among districts in their level of economic well being. Note from Table 11 that the richest district has a per capita GDP that is roughly twice the level of the poorest district. We have developed an inter-correlation matrix for districts on these same measures for the 15 of 18 districts for which data are available. We find that in richer districts (measured by per capita gross product), there tends to be a significantly smaller share of SC/ST population, and a significantly higher literacy rate.
Expenditure Disparities
There are great disparities across local governments in West Bengal in the amounts they spend. An accounting of these disparities will give a baseline for determining the equalization job that the intergovernmental transfer system will be required to do.
District Aggregates. The disparity between the highest and lowest income districts in West Bengal is about 1.8 (Table 12). We examine whether rural local government expenditure disparities are as large by computing an aggregate per capita expenditure of district, block, and gram panchayats governments. The results, shown in Column (2) of Table 12 show a disparity of 3.1 between the highest and the lowest districts. Spending disparities are nearly twice as great as income disparities.
We examine the pattern of disparities in Figure 2 with aggregate per capita expenditures on the vertical axis. The pattern we observe suggests equalization. The four poorest provinces are among the highest spenders on a per capita basis and three of the four richest are among the lowest.
Gram Panchayats. To study the variation across gram panchayats, we have computed Table 13, which shows the overall variation in per capita total expenditures of gram panchayats. As above, we report mean values as well as variations.
Gram panchayats spend very little on a per capita basis, only about Rs 138 per person on average, i.e., US $3.14 per capita. The level of per capita expenditures fell from 113 rupees per person in 2003 to 102 in 2004 but then increased from 102 to 138 between 2004 and 2005. This continuing, very low level of expenditures suggests that gram panchayats are “under-assigned” expenditure responsibilities with the result that the services they do provide may not have much affect on the quality of life in the local government area. The result is that voters might not be very interested in getting involved to influence the level and structure of local government expenditures. In fact, some studies point to the non-functioning gram sabha as evidence of little citizen participation in budgeting decisions (Institute of Social Sciences, 2005). This is a major obstacle to realizing the local self-governance outcomes sought by the constitutional amendment. To address this problem, government could rethink the role of gram panchayats in delivering services, in the direction of giving them additional assignments of expenditure responsibility, as well as access to additional resources.
The large variation among gram panchayats in per capita spending level, in 2005, is shown by the frequency distribution in Figure 3. We first rank GPs from lowest to highest per capita expenditure (2005). We then create groups of per capita expenditures in 20 rupee increments (0 to 20, 20 to 40, 40 to 60, and so on) and fit each GP into their respective group. The second to last group is 480 to 500 rupees per person and the very last group is “more than 500 rupees.” The level of per capita expenditure is plotted on the X-axis and the cumulative frequency (number of GPs) is plotted on the right vertical axis, while the absolute frequency (actual number of GPs in an expenditure category) is plotted on the left vertical axis. For example, there are 591 GPs in the per capita expenditure group “80 to 100 rupees per person.”
Over 83 percent of all GPs spend 180 or less rupees per person. The distribution has a “long tail” meaning that there are a number of individual GPs that spend more than 180 rupees per person, but the level of spending for those GPs is not concentrated in any one expenditure group. The higher spending amounts range from 180 rupees to 4,515 rupees. In such cases, the services delivered are likely to be meaningful. Understanding the reasons for these wide disparities may be the key to developing a strategy to increase the fiscal importance of gram panchayats. We argue that these disparities are due either to the way in which grants and transfers are distributed, or to higher levels of own source revenues in some gram panchayats, or to an inadequate capacity to absorb expenditure responsibility on the part of some gram panchayats.
The distribution of per capita expenditures across population size classes, as shown in Table 13, is surprising. On average, the smallest gram panchayats spend more per person than do the more heavily populated gram panchayats[33]. As noted above, this could be a fixed cost effect, i.e., local governments must spend a certain amount to satisfy the basics of operating a local government and when this total is spread over a larger population, the per capita amount falls. But, the fact that 80 percent of gram panchayat spending is for capital and income maintenance purposes suggests that there are other explanations. Chief among these is the possibility that the formulae to allocate grant funding and other transfers may favor local governments that are less heavily populated.
We recalculate the relationship between per capita spending and population size, with fixed costs removed from the expenditure variable. Since the state government provides approximately the same salary grant for all gram panchayats, we might take salary expenditures as a measure of fixed costs (See also Box 1). We subtract salary grants received from the state government from total expenditures of gram panchayats, reproduce the calculations from Table 13, and report the results in Table 14. The pattern is much the same as reported in Table 13. The per capita expenditures of gram panchayats are higher for the less heavily populated local governments. This result, then, is due to more than the fixed cost effect. A hypothesis consistent with this finding is that there is a bias in the allocation of central and state transfers that favors gram panchayats with smaller populations.
Explaining Expenditure Variations
About 5 percent of the GPs report per capita expenditures that are very small—averaging 50 rupees per person. The top 5 percent of GPs (in terms of per capita spending) spend at least 2 ½ times that of the average GP. The very top of the distribution—those GPs in the top 1 percent of the distribution -- spend over 584 rupees per person. Understanding the determinants of this wide variation is a first important step toward developing a financing structure that will allow the provision of a minimum level of services in every gram panchayat.
As a first step, we calculate the simple correlation coefficients between selected fiscal variables and selected socio-economic variables. This simple correlation matrix is presented in Annex B (separately for districts, blocks, and gram panchayats). There are a number of significant covariates. In particular, we can see that per capita expenditures for gram panchayats are significantly higher where there are smaller populations, where there is a larger percent of SC/ST population, where the percent of marginal workers is larger, and where there is a greater share of agricultural population. Expenditure needs do seem to matter. These simple correlations suggest that the joint impact of these population characteristics on per capita expenditures is complicated, and involves more than first order correlations. Therefore, we use a multi-variable regression to explain inter-governmental differences in per capita expenditures.
We estimate OLS regressions separately for gram panchayats, blocks, and districts, where per capita total expenditures is the dependent variable, and the independent variables are justified as follows:
• Population size should be negatively related to per capita spending, because for smaller local governments, cet. par., the fixed cost effects will weigh heavily on budgets. Moreover, central scheme revenues may be allocated in disproportionate amount to local governments with a smaller population.
• The percent of SC/ST population should be positively related to per capita expenditures because this implies a heavier concentration of poor citizens who are more costly to serve. For this reason, greater amounts of CSS transfers will flow to local governments with heavier concentrations of SC/ST in the population and these grants will result in higher per capita expenditures.
• We do not have a prior on the marginal effect of variations in the literacy rate on per capita expenditures. The effect should be positive if literacy signals more willingness to pay on the part of residents and a greater capacity to deliver services on the part of government. If a greater rate of literacy equates with more poverty and therefore a greater inflow of transfers to support employment generation programs, a negative effect might be expected.
• The share of workers in the agricultural sector might indicate more need for services because services currently provided in the more remote areas may be more deficient and more costly to provide[34]. It also may be positively related to the level of per capita expenditures because of the likelihood that larger shares of agricultural workers indicate a more agrarian economy and more demand for employment generation programs. The simple correlations reported in Annex B suggest that where the agricultural share of employment is high in a gram panchayat, we can expect significantly less literacy, a greater percent of SC/ST population, and a larger percent of marginal workers.
• We have included a dummy variable to take account of district of location for blocks and gram panchayats, and a dummy variable to take account of block location in the gram panchayats analysis. This should pick up the impact of some qualitative factors such as location, political power, and different attitudes and levels of efficiency at the district and block levels. We expect that, all else being the same, there will be “district effects” and “block effects”. To construct the dummy variables, we have omitted Uttar Dinajur district and one randomly chosen block in each district. The remaining district and block coefficients should be interpreted as the “effect” of a particular district on the dependent variable, relative to the omitted district (block).
The results of this OLS analysis are presented in Table 15. About 81 percent of the variation in per capita expenditures among the 2,098 gram panchayats in the sample can be explained by these variables. Population size exerts the expected significant and negative size effect. The proxy measure for the concentration of poverty (SC/ST population) is significant in leading to higher levels of per capita expenditures. This is an expected result because higher proportions of SC/ST population draw in more intergovernmental transfers to address the greater expenditure needs. All else held constant, a ten percentage point higher share of SC/ST population may be associated with a 1.8 percent higher level of per capita spending by a gram panchayat[35]. The literacy rate exerts a positive marginal effect on spending. For any given level of population, SC/ST population, etc., a higher literacy rate leads to a higher level of expenditures. Better education leads to more demand for public resources and at the margin to a greater willingness to pay for services. We might think of this as the impact of a higher rate of economic development. A larger share in agricultural employment leads to significantly higher levels of per capita expenditures, as hypothesized.
Gram panchayats in all districts spend more than those in Uttar Dinajpur, even after account is taken of these explanatory variables. Seventy four of the 325 block dummy variables were significant (23 percent), indicating that there are important differences in spending levels within districts, even after we account for district effects and for the socioeconomic characteristics included in Table 15. Based on this, one might argue that there are important management and political factors to be considered in explaining inter-GP variations in per capita expenditures.
One might conclude from this analysis that expenditures are significantly higher in less populated and more backward GPs, suggesting that a considerable degree of equalization is built into the system. At the margin, however, higher rates of literacy are associated with higher levels of spending.
We repeat this analysis with the salary grant removed from the dependent variable. This should allow an estimate of determinants, independent of the fixed cost effects (See Box 1). The results, shown in Table 16, do not change the conclusions very much. Population size remains a dampening influence on per capita expenditures, though the elasticity is low compared to that reported in Table 15.
Own Source Revenues
Rural local governments in West Bengal raise very little revenue from own sources. The average for gram panchayats is only about Rs 8 in per capita. However, the variation is great. Some gram panchayats raise 20 to 30 times the average amount, while 200 GPs report raising no own source revenue—with 140 of those GPs in the two lowest population classes. This result is shown in Table 17 by population size class for districts, blocks, and gram panchayats. Interestingly, the average level of per capita own source revenue declines with population size for the gram panchayats[36].
We might turn to a more systematic approach to explain the considerable variation in per capita own source revenues across gram panchayats, i.e., to estimate an OLS regression of the determinants of per capita own source revenues. Our question is, “Why do some gram panchayats raise more own source revenues than do others?” The answer to this question may be important to helping formulate an incentive policy for stimulating revenue mobilization. The dependent variable in this analysis is per capita own source revenues, including tax and non-tax sources. The independent variables are included based on the following a priori reasoning:
• Population size should be positively related to per capita own source revenues because agglomerations of population suggest greater taxable capacity. With a larger population, there should be greater levels of economic activity, regional markets that would draw non-resident buyers and sellers to the GP, more commercial dwelling units to tax, and more services financed by user charges. On the other hand, if smaller GPs draw more intergovernmental transfers, this may dampen enthusiasm for revenue mobilization and a negative relationship might be expected.
• A larger percent of SC/ST population suggests a greater concentration of poor households, less taxable capacity, and a negative relationship with per capita own source revenues. This might be reinforced if the concentration of SC/ST population draws more transfers, and reduces the incentive to mobilize more revenues.
• A higher literacy rate suggests a greater taxable capacity and a positive relationship with the level of own source revenue. This hypothesis is based on the premise that more education leads to higher wages on the part of the local population, and arguably to a greater willingness to pay taxes.
• The percent of agricultural workers in the economy will signal more difficulty in tax collection and arguably a weaker taxable capacity. We expect a negative relationship with per capita own source revenue.
• District and block effects are included in the GP regression and district effects are included in the block regression.
The results of the analysis are reported in Table 18. About 55 percent of the variation in per capita revenues across 2,067 gram panchayats can be explained by this model. The literacy rate variable is significant and has the expected positive sign. This would appear to measure the positive marginal effect of economic development and voter awareness on the mobilization of own source revenues. The elasticity is relatively high, i.e., if the literacy rate is 10 percent higher, the level of own source revenue collections will be about 9 percent higher.
Greater percents of workers in the hard-to-tax agriculture sector do in fact dampen the level of own source revenues, as hypothesized. Neither of the poverty variables are significant determinants. The population effect is negative, i.e., there is no evidence of agglomeration effects on revenue mobilization. However, the “population effect” may have been obscured by the inclusion of the district and block dummy variables. There are a number of district effects with Bankura and Hugli reporting higher per capita own source revenues than the omitted district of Uttar Dinajpur (which is a relatively low income district). In the case of several other districts a negative effect is observed (See Table 18). Block effects are observed in about 17 percent of the cases, suggesting the importance of qualitative factors as discussed above.
Intergovernmental transfers play so large a role in financing rural local governments that they may have an impact on local revenue mobilization. Transfers may dampen the enthusiasm of local governments to be aggressive about collecting tax and non tax revenues. Alternatively, larger inflows of transfers might stimulate more local revenue mobilization, i.e., they might generate a kind of local match to accommodate the cost of larger government. To test this hypothesis, we repeat the regression analysis described above but add per capita total grants and transfers as an (exogenously determined) independent variable. The results (Table 19) show that for gram panchayats, per capita grants and transfers are positively and significantly related to own source revenues per capita. The latter results suggest that own source revenues and intergovernmental transfers do not substitute for one another but rather are complementary, i.e., the more grants received, the more own source revenue raised. The result is not so far-fetched. The cash payment inflow under the schemes and grants may well lead to increased tax and non-tax payments by beneficiaries and by those supplying inputs in the implementation of programs. Note that when we introduce intergovernmental transfers as an independent variable, neither the population nor the poverty variables are significant.
In summary, we might interpret this analysis as showing that per capita own source revenues in gram panchayats are higher where there is more literacy, where a smaller share of the population employed in the hard-to-tax agricultural sector, and where there is a greater inflow of transfers.
Measuring Tax Effort. One reason why this estimation of the determinants of revenue mobilization is important is that we might use these results to monitor the revenue mobilization efforts of gram panchayats. This would allow the State to identify low performing gram panchayats where additional training and other technical assistance is necessary to enhance collections. Or, an index of tax effort might be used in an intergovernmental transfer distribution formula to provide an incentive for better tax effort and a penalty for poor tax effort.
We may use the results generated above to develop an index of tax effort for gram panchayats. The idea is to identify those GPs that are raising own source revenues at a level above expectations and those that are performing below expectations. This is a good alternative to using the average per capita amount raised as the “expectations” for every gram panchayat. Fiscal capacities vary widely and some GPs should raise more revenues than others, even if they exert the same effort. To control for this, we use the following methodology:
• From the equation shown in Table 18, we estimate the “expected” level of own source revenues for each gram panchayat, based on the socio-economic characteristics of that gram panchayat. For example, for the first gram panchayat shown in Table 20 (Domahana), we would expect a per capita level of own revenues of Rs 4.47.
• The actual level of taxes divided by the estimated level is the index of tax effort. This is shown as “effort” in Table 20. For example, the first gram panchayat actually raises Rs 2.77 in per capita own source revenues, hence its effort index is 0.62.
• An effort index, for example of 0.62, indicates that Domahana gram panchayat is raising own source revenues at a rate that is 38 percent below expectations, based on a statewide comparison. By contrast, the gram panchayat of Oldabari exerts a tax effort that is 107 percent above expectations. The results for 10 of the more heavily populated gram panchayats shown in Table 20, indicate an above average effort in three cases.
Explaining the Distribution Impact of Intergovernmental Transfers
The “rules” for vertical and horizontal sharing of intergovernmental transfers is discussed at some length above. Now we turn to an analysis of the variations among local governments in the actual amounts of transfers received. In particular, we want to identify the “implicit formula” for the distribution of intergovernmental transfers across gram panchayats and across districts and blocks. That is, we examine the actual relationship between transfers distributed and measures of need such as the size of the SC/ST population, population size, etc. We are especially interested in whether there is any empirical evidence that this distribution is or is not equalizing.
To begin to answer this question, we have estimated an OLS regression with the major components of per capita transfers and grants as the dependent variables. We study the major components of the transfer system, because it seems to be the case that different programs carry different objectives and are structured in different ways. We would therefore expect the determinants of the amounts received by gram panchayats to vary from one grant type to another. In each case, the idea is to tease out an “implicit” grant formula, and in particular to see if per capita transfers are systematically allocated to favor poorer jurisdictions.
Centrally Sponsored Schemes. We might begin with an analysis of variations in the per capita amounts received from the two major centrally sponsored schemes: SGRY and IAY. In the first regression analysis, the dependent variable is per capita SGRY transfers. The explanatory variables include:
• The percent of SC/ST population, which is an indicator of the concentration of poor families. A positive association with per capita transfers would be consistent with equalization. We expect a positive association because of the poverty alleviation goal of the program and because SC/ST population is a factor that government includes in its distribution rules.
• The literacy rate is expected to have a negative effect on the level of per capita transfers received, because it is hypothesized that literacy is associated with a smaller concentration of below-poverty-line population, and therefore with a smaller inflow of transfers.
• Population size is introduced as a control variable. We expect a negative relationship with gram panchayats, in part, because there is a required minimum allocation of Rs 25000 to each GP.
• The percent of agricultural labor may indicate a larger rural sector and therefore more demand for employment generation programs.
• A district effect and a block effect. This might pick up some effects such as better program administration, more political skill in attracting transfers, etc.
The results for the SGRY scheme, presented in Table 21 show that the SC/ST variable has the expected positive sign and is a significant determinant in the case of gram panchayats. A one percent higher SC/ST population share, cet. par., is associated with a 0.38 percent higher level of per capita SGRY transfers received. This result is consistent with equalization. Gram panchayats with smaller populations also receive significantly more. The unexpected finding is that the literacy rate is significant and positive, suggesting a counter-equalizing influence in the distribution. The share of agricultural labor is not significant. There are 8 significant district effects, and 12 percent of the block dummies are significant, suggesting that other factors are at work in determining the level of per capita SGRY receipts. In total, we can explain about two-thirds of the variation in per capita SGRY receipts across gram panchayats.
We repeat this analysis for per capita IAY transfers, with the results shown in Table 22. The percent of SC/ST population has the expected positive sign and is significant. Per capita IAY transfers are also significantly higher in gram panchayats that have smaller populations, and a larger percent of agricultural labor.
We find that, at the margin, a higher literacy rate is associated with a greater level of receipts of IAY transfers. This runs counter to the backwardness hypothesis. About 65 percent of the variation in IAY transfers might be explained.
We carry out a similar analysis for total central schemes (Tables 23). The results are much the same as those found for the IAY per capita grants. In the case of GPs, 79 percent of the variation is explained in the regression. Smaller GPs and those with more backward populations (higher SC/ST) receive more central scheme funds per capita. However, there is again a counter intuitive result regarding the literacy rate.
State Grants and Schemes. In Table 24, we analyze total per capita state government transfers as a function of the same set of variables as reported in Table 22. The dependent variable is the per capita amount received from all state grants and schemes (Table 10). The goal here is to identify the determinants of per capita state aid, and to compare these results against those for central schemes.
The independent variables in this analysis are the same as in the centrally sponsored schemes. We are interested in the extent to which the distribution responds to backwardness (percent of SC/ST population), population size, the share of agricultural workers, and the literacy rate. A district and block effect are added to test for the possible influence of intangibles such as location, political influence, or a more efficient public administration.
The results of this analysis show that for gram panchayats, per capita state aid is distributed significantly more toward those with smaller populations and larger shares of agricultural employment (Table 24). The SC/ST, and literacy coefficients are not significant. We may compare these results for state aid with those for centrally sponsored schemes. In particular we might be interested in the question of whether state transfers or central transfers are more equalizing. As the SC/ST coefficient is not a significant determinant in the case of state transfers, we can conclude that the central schemes are more equalizing. That is, if a gram panchayat has a 10 percent greater concentration of SC/ST population (all else held constant) it does not receive a significantly greater amount of per capita state aid but it does receive about a 3 percent higher amount of per capita central scheme revenue.
Total Grants and Transfers. Finally, we use the per capita level of total state grants and transfers as the dependent variable. This includes both central schemes and state aid. The basic hypotheses are as above: per capita total grants and transfers should be positively related to the percent of SC/ST population, and to share of employment in agriculture, and negatively to the literacy rate, if the overall grant system features equalization.
The results presented for gram panchayats in Table 25 show that about 82 percent of the variation in per capita total transfers can be explained by this model. The percent of SC/ST population is significant and positive, suggesting equalization in the distribution of total grants and transfers. As noted above, this is due to the equalizing influence of central transfers. There would appear to be a bias in favor of GPs with a smaller population, and those with a larger share of employment in agriculture. These findings are also consistent with the equalization hypothesis. As in most of this analysis, these results show that the marginal impact of higher rates of literacy is positive.
FINANCIAL CONDITION
In this section, we examine the budgetary position of gram panchayats. We use a simple pro forma (presented in Box 3) to describe budgetary position and assess the magnitude of fiscal gaps, i.e., situations where annual revenues received (excluding opening balances) do not cover expenditures made. We then turn to the issue of opening balances. If these are adequate in amount to cover the recurrent fiscal gap, then the opening balance can be viewed as a pre-funding of the annual budget. In this case, the annual drawdown might be thought of as a recurrent revenue. In cases where opening balances are inadequate to close the annual fiscal gap, the fiscal health of local governments may be comprised. In studying this issue, we use data for three years (2003, 2004, and 2005).
|Box 3 |
|Pro Forma to Describe Budgetary Position |
| |
|Total Revenues |
|1a. Own Source |
|Tax Revenue (property tax, amusement tax, other) |
|Non-tax Revenue (sale of property, leases, donations, other) |
|1b. Intergovernmental Transfers |
|Untied Grants |
|Salary Grants |
|Other Grants |
|Finance Commission Grants |
|Union |
|State |
|Centrally sponsored schemes (SGRY, IAY, NSAP, IMY, midday meal, SSA, other) |
|State Sponsored Schemes (Minideep, PROFLAL, other) |
|Others (BEUP, MPLAD, other) |
| |
|Less: total expenditures |
|2a. Current |
|2b. Capital |
| |
|3. Equals: total annual surplus or deficit |
| |
|4. Equals: difference between opening and closing balance |
Based on this identity, we have calculated the indicators of financial condition that are summarized in Table 26. These indicators are very simple, but might be useful in profiling the financial condition of rural local governments in West Bengal. We draw on these data to raise (and answer) four questions.
Do Many Gram Panchayats Have a Negative Recurrent Revenue Gap?
In fact, about one-half the gram panchayats reporting incurred a deficit in 2005 (Table 26). There was not much change in this number over the 2003-2005 period. The deficits during this period were (on average) equivalent to about 13 percent of total revenues. The other half of gram panchayats reported a surplus that also averaged about 13 percent of total revenues. There would appear to be a great unevenness in the fiscal condition of gram panchayats, i.e., about half do not balance their current budgets and the other half do not spend all of their recurrent annual revenues. In other words, about half of GPs are able to add to their cash balances at the end of the fiscal year, and about half find it necessary to draw from their balances to meet the gap between recurrent expenditures and recurrent revenues available.
Do the Results For Surplus GPs Indicate an Inability to Absorb the Funds?
This is an especially important issue if a reform direction is to increase the flow of resources to GPs. In fact, there are serious capacity problems at the GP level which may indicate an inability to spend the money now available. An alternative explanation for the accumulation of balances is that the conditionality and bureaucratic processes associated with spending transfers from centrally sponsored schemes significantly limit the chances that a rural local government can move the money in the year in which it is received. Whatever the reason for this inability to absorb funds, it suggests the existence of financial surpluses alongside deficiencies in public service levels in some gram panchayats. We can note, however, that the same pattern of unspent balances was observed for gram panchayats in Kerala and Karnataka (Sethi, 2005).
There is another possible reason for the surpluses. The receipt of intergovernmental transfers late in the fiscal year makes it impossible to spend the money in the year when the funds are received. Many GPs allege this to be a serious problem. Some state officials see this timing issue as being overstated. The evidence presented here points to the timing of receipts being part of the problem in West Bengal. Oommen, et. al. (2004, p. 241-242), reach a similar conclusion in their study of Kerala.
“A rational transfer system should be predictable and ensure
an even flow throughout the fiscal period. This is especially important in view of the existing situation in which grant receipts are bunched at the end of the fiscal year, distorting the spending pattern and contributing to high closing/opening balances. At present, the income-expenditure pattern is so uneven that the fiscal balance fluctuates from a 200 percent deficit in August to a 40 percent surplus in March. Closing treasuries for business on working days or imposing oral or written instructions to restrict treasury transactions have exacerbated the problem. Resolving the problems of the state-local transfer system in Kerala and resolving the fiscal problems of the state government are, clearly, connected issues.”
The persistence of deficits is explored in Table 21a. During the 2003-2005 period, 199 GPs had deficits in all three years, but only a handful had deficits larger than their opening balances. This suggests that while some GPs are regularly in a deficit position, the size of the deficit relative to funds that are carried over is not large. About one-third of the GPs had at least 2 years of deficit and another one-third had one year of deficit. There does not appear to be any systematic relationship between the pattern of deficits and spending levels. For example, we cannot see a relationship between “years of deficit” (or surplus) and the average level of per capita expenditures for the GPs in this category (Table 27). More GPs had surplus in all three years (257) than had deficits in all three years. Failures in the area of financial indiscipline is not a widespread problem in West Bengal.
If the deficit and opening balance problem is one of timing, the surplus should remain about constant over a period of years (or should grow about in proportion to the distributable pool). Local governments would bank the money received at the end of the fiscal year, and then spend it down at the beginning of the next. Unless the flow of transfers was reduced, one would expect balances to remain at about the same level over time. This is the pattern we observe in West Bengal. Note from Table 26 that the size of closing balances relative to total expenditures has remained between 20 and 30 percent during this three year period. For those GPs running a surplus, the amount has stayed at about 12 to 14 percent of total revenues. For those running a deficit, the amount has ranged from 11.7 to 15 percent of total revenues. This analysis suggests that gram panchayats are “pre-funded” by higher level governments and carry balances that are sufficient for them to avoid year-end shortfalls.
To What Extent Do “Deficit” Gram Panchayats Draw On Their Cash Balance Reserves to Cover the Cost of Delivering Services?
The approximately 1,500 GPs that annually operate recurrent account deficits, do so in amount equivalent to around 11-15 percent of total recurrent revenue. As may be seen for the reported ratio of deficit to balances in Table 28, these GPs have the resources to balance their budgets.
We also can use these data to determine the extent to which opening balances are adequate to cover the recurrent fiscal shortfall. In all but a handful of gram panchayats, the balances are adequate. In most “deficit” GPs, the more accurate story would be that certain recurrent expenditures undertaken in any given year were financed from transfers received in the preceding year. From this analysis, we might conclude that financial discipline problems, such as borrowing or deferring creditors to balance the budget, are an issue for only a small number of gram panchayats in West Bengal. Dealing individually with these is a manageable task for the fiscal monitoring and evaluation unit of the State government.
Do the Closing Balances Change Over Time, and How Do We Explain This? Are These Closing Balances “Too Large”?
The closing balances did not change very much in aggregate over the 2003-2005 period. They stayed in a range between 22 and 28 percent of total expenditures. We might conclude from this, and from the analysis reported in Table 27, that, on average, the closing balances are more than adequate to cover the shortfalls that deficit GPs face. The question is whether these balances are too large and an indication that the gram panchayats are receiving more in transfers than they can absorb. Balances between 20 and 30 percent of expenditures do seem large in a state where services in rural areas are deficient and where the expenditures made by rural local governments are so meager.
Note from Table 26 that large balances are not the case in every GP. About 10 percent of all GPs closed their year with a balance lower than 5 percent of total expenditures.
What Determines Financial Condition?
The state government should be interested in whether financial condition varies among gram panchayats according to population size and concentration of poverty. Is there a way to use data on the socio-economic makeup of GPs to develop an early warning signal for fiscal distress? Or, might we use such data to classify GPs according to whether they are “high-risk”? Such quantitative measures can help the state determine where it might need to provide technical assistance in budget management, where it may need closer surveillance, and/or how it might need to adjust intergovernmental transfers to better fit the need for budget support. We might raise two questions in this research. The first is, “What are the factors that lead some gram panchayats to incur a deficit?” The second is, “What determines the size of the current account deficit?”
To analyze the propensity for GPs to be in deficit, we used a probit model, where we define a “deficit GP” according to our pro forma in Box 3. The dependent variable is (D=1) for deficit GPs and (D=0) for surplus GPs. We take two definitions of deficit GPs. First, using data from Table 21a, we define “chronic deficit” GPs as a GP that has a deficit for each year, 2003, 2004, and 2005. In the second case, we simply define a deficit GP as any GP that posted a deficit for 2005.
The coefficients in Table 29 are estimates of the probability of incurring a deficit. Our results show that the probability of choosing to run a current account deficit are different for chronic deficit GPs than for all GPs that posted a deficit in 2005. We hypothesize that a GP with a larger opening balance could “afford” to overspend against current revenues, and so we might expect to see a positive correlation between opening balance and the probability of a deficit. Interestingly, we see this for “regular” deficit GPs (third column) but not for “chronic deficit” GPs. In fact, for chronic deficit GPs, we observe an improbable relationship, that the probability of choosing a deficit is inversely related to the size of the opening balance. The expectation is that the deficit choice for the “chronic deficit” GPs would be driven more by underlying structural factors than by cash on hand. For example, the percent SC/ST population might reflect a harsher economic environment and therefore lead to higher deficits. We do observe this pattern for chronic deficit GPs. Also, we note that in “regular deficit” GPs, own source revenues per capita are associated with a smaller probability of deficit, which is an expected effect.
To answer the second question, we have estimated an OLS regression with the dependent variable expressed as the per capita deficit (excluding any use of cash balances). What we explain in this analysis is the variation in the size of the revenue/expenditure imbalance, across those gram panchayats that ran a deficit in 2005. “Surplus” GPs are excluded from this analysis. The independent variables and their justifications are:
• The per capita level of the opening balance. The hypothesis is that the larger the available opening balance, the more likely is a gram panchayat to incur a large current account deficit. Hence we expect a positive regression coefficient.[37]
• In estimating the relationship between the deficit and the opening balance, we control for both population size and the percent of SC/ST population, which we have shown above to be significant determinants of expenditure levels. A priori, we would expect more backward gram panchayats to face more budget pressures and to be more prone to run a deficit. To the extent that more backward places are less able to absorb funds, there is another rationale for expecting a positive relationship.
• The per capita level of centrally sponsored schemes is introduced as an explanatory variable. A positive coefficient would indicate that deficits are driven up by higher transfers because of overspending. A negative coefficient indicates that more scheme money dampens the deficit, a finding consistent with the story that more transfers encourage increased own source revenue mobilization.
• There may be a “district effect” on financial condition. Some districts may be more effective than others in tracking expenditure needs, training local officials, and passing resources to GPs where needs are greatest. To account for the district effect, we include a set of district dummy variables.
The results of the regression analysis (Table 30) confirm the null hypothesis. We do find the hypothesized positive relationship between the size of the opening balance and the size of the deficit, i.e., we find that gram panchayats that carry a larger opening balances run significantly larger deficits. This finding indirectly suggests that larger opening balances dampens the enthusiasm for higher levels of revenue mobilization. We also find some evidence of a district effect, i.e., the size of the deficit in Darjiling and Koch Bihar districts is significantly larger than in Uttar Dinapuri district. This finding confirms the belief that the management of fiscal affairs in some districts is significantly different than in others. The poverty variables are not significant determinants. About 55 percent of the variation is explained with this model.
THE FISCAL POSITION OF BLOCK AND DISTRICT LEVEL GOVERNMENTS
Block and district level governments are more in the nature of implementing agents of the state than they are local self-governments. Nevertheless, they manage about two-thirds of PRI spending. The focus in this report is on the gram panchayat level. However, to get a complete picture of PRI fiscal activity, it is also important to understand the structure of finances of blocks (panchayats samitis) and districts (zillas).
The richest district in West Bengal has about twice the level of per capita gross product as the poorest. They range in population size from 1.9 million to 9 million. The simple correlations in Annex Table B-2 show that higher income districts tend to have a significantly lower percent of SC/ST population and female population, and a higher literacy rate.
The variation in the population of blocks also is large, from under 70 thousand to over 400 thousand (Table 11). The simple correlations in Annex Table B-1 show that larger blocks have significantly greater shares of SC/ST and female population, and a larger percent of marginal workers. Larger blocks, apparently, are lagging in terms of economic development and have a larger concentration of poor females.
The question we raise here is whether these variations in socio-economic performance explain the different levels of fiscal activity.
Expenditures
On average, districts spend about 12 percent more on a per capita basis than do gram panchayats. Block level governments spend well less than either (Table 31). The variation in per capita spending across districts, however, is less than that across either blocks or gram panchayats (note the size of the coefficients of variation). The pattern found for gram panchayats, that smaller local governments spend more on a per capita basis than do more heavily populated local governments, also holds true for districts and blocks (Table 31).
We have carried out roughly the same analysis for districts and blocks as we did for gram panchayats, with regression results reported in Table 32. The results for districts are similar to those found for gram panchayats, as reported above. We use only two variables in the district equation: population size and percent of SC/ST population. About 63 percent of the per capita expenditure variation across 17 districts can be explained, with the percent of SC/ST population the dominant determinant. Population size has the expected negative coefficients, but is not significant at the .05 level.[38] What we can conclude from this is that per capita spending by district level governments is significantly higher in districts where there is a greater concentration of poverty. As in the case of gram panchayats, we might attribute this to the heavy weight attached to backwardness in the distribution formulae for the centrally sponsored schemes. What is interesting in these findings is that the percent of SC/ST population exerts a greater marginal effect on per capita expenditures in the case of districts than in the case of gram panchayats.
For the block level governments we can explain about 50 percent of the variation, with both population size (negative) and the percent of SC/ST population (positive) significant determinants. Note also that we find a significant “district effect”, with blocks located in Koch Behar, Gopiballarpur, and Purulia districts spending significantly more than those in Uttar Dinajur district. This suggests that some factors, unique to districts, are important in explaining why some blocks spend more than others.
We might summarize these findings on the determinants of rural local government expenditures in West Bengal with the following stylized conclusions:
• Larger block governments spend less on a per capita basis than do smaller block governments. There is no significant relationship between population size and spending by district governments[39].
• The greater the concentration of poor families, the higher will be per capita expenditures. This conclusion holds for all three levels of rural local government, and it suggests that the intergovernmental fiscal system is dominated by an equalization objective.
Own-Source Revenues
Districts and block governments have no taxing powers, but can raise own revenues from non tax sources. As may be seen in Table 33, the level of non-tax revenues raised by block governments is very small. The average is less than Rs 3 on a per capita basis and the largest amounts raised are less than Rs 40. The level of per capita own source (non tax) revenues declines with the population size of the block and the variation within each population size group is great. (Table 33).
With respect to districts, the pattern for per capita non tax revenues is more in line with what one would expect. The more heavily populated districts, where one would expect to see the greatest level of economic activity, show higher levels of per capita collections than do the smaller districts. On average, however, only about Rs 5 per capita is raised by district governments.
Since blocks and districts act as implementing agents of the central and state governments, this poor revenue performance suggests little commitment to cost recovery at any level.
There are variations in this generally low rate of revenue mobilization. We test the hypothesis that the variation can be explained by the level of economic development using an OLS regression analysis with per capita own source revenue as the dependent variable. We use the various measures of economic development and backwardness that are available, but cannot explain a significant amount of the variation for either blocks or districts (Tables 34 and 35). We conclude that there is a large random element in the pattern of variation in own source revenue per capita.
Intergovernmental Transfers
State and central transfers are distributed downward through the PRIs, first to districts, then to blocks, and finally to gram panchayats. The question we raise here is the extent to which central and state transfers are distributed in an equalizing way among these PRIs.
Centrally Sponsored Schemes. We can explain about 60 percent of the variation in per capita SGRY receipts for blocks and districts (Table 36). In the case of blocks, those units that are more heavily populated receive significantly less in employment generation grants. A higher share of SC/ST population draws more SGRY transfers per capita. At the margin, the literacy rate is associated with greater SGRY transfers per capita, which is a surprising result.
The results for districts, also reported in Table 36 are mostly in step with expectations. On a per capita basis, SGRY transfers are allocated in greater amounts to GPs with a heavier concentration of SC/ST population and a lower literacy rate. Oddly, however, we find that the marginal effect of per capita gross product on per capita SGRY is positive.
If we use the percent of SC/ST population as the basic measure of poverty, we can say that the SGRY scheme is driven by equalization at both the block and district level.
In the case of blocks, we can explain a significant percent of the variation in IAY transfers but cannot learn much about the determinants of the per capita distribution (Table 37). At the district level, we can explain about 60 percent of the variation (Table 37). The implicit distribution seems heavily weighted toward indicators of backwardness, i.e., percent of SC/ST population, and the illiteracy rate. Per capita IAY scheme amounts are transferred with a bias in favor of districts with a larger population. What we can say from this result is that the goal of the center -- to distribute housing scheme revenue toward pockets of poverty -- seems to work better at the district level than at the block level.
The next question is how this all plays out in terms of the per capita distribution of total central scheme revenues. For blocks, we can explain only about 35 percent of the variation. Both population size (negative) and SC/ST population (positive) are significant (Table 38). Overall, there is an equalizing feature in the system.
For districts, SC/ST population and the literacy rate variables are significant with directions of effect that are consistent with equalization. Again, however, we find that at the margin, higher income districts receive more in per capita central transfers. Over 80 percent of the variation can be explained.
State Grants and Schemes. The regression results for per capita state government transfers are reported in Table 39. For blocks, the variation would appear to be random, except for a number of significant district effects. The explanation for why some blocks receive more state government transfers may be driven more by political and management factors than by the makeup of the population. For districts, we see some conflicting equalization results. Literacy is positively correlated with per capita state transfers, but a larger female population is positively related to state grants and per capita GDP is negative.
Total Grants and Transfers. The last question is this all plays out in terms of the distribution of total transfers from higher level governments. The results for districts and blocks for per capita total transfers are shown in Table 40. The only significant determinant of inter-district variations in per capita grants and transfers is the share of SC/ST population, a result that is consistent with the equalization hypothesis. We find essentially the same result for blocks, but note the much greater equalizing effect in the case of districts. Overall, we find that the regression explains less of the variation for blocks (48 percent) and districts (61 percent) than for GPs.
Financial Condition
The fiscal balance problem does not appear to be restricted to gram panchayats. This is an unexpected finding since districts and blocks function more as spending agents of the state than as autonomous local governments. As reported in Table 41, most district governments closed the years 2003, 2004 and 2005 in a deficit position[40]. The size of the deficits, relative to total revenues of the district, were larger than in the case of gram panchayats, as were the closing balances. The story seems to be much the same as for the GP, i.e., districts carry large balances, presumably to pre-fund expenditures. We could find only one district with a closing balance as small as 5 percent of total expenditures.
The financial position of blocks showed a great deal of variation. About half incurred deficits, by our definition, and the amounts were in the range of 30 percent of revenues. However, blocks carried balances that were substantially greater than that for gram panchayats. The balances carried appear to be more than adequate to cover the deficits. In general, the size of the deficit chosen is directly related to the size of the opening balance that is carried into the fiscal year (Table 42). Again, the story seems to be one of using allocations from the previous year to fund expenditures.
Summary
Though districts and blocks are more spending agents of the state and central governments than local self-governments, they do exhibit variation in their spending and financing patterns. Together, they account for a considerably greater share of government expenditures than do gram panchayats.
The variations across the block and district levels show many of the same characteristics that were found for gram panchayats. Per capita spending is higher in blocks with smaller populations and in both blocks and districts where there is a heavier concentration of SC/ST population. These expenditures are financed primarily by intergovernmental transfers (97 percent) and there is no significant pattern of cost recovery through fees and charges.
Centrally sponsored schemes are distributed among districts and blocks on an equalizing basis, assuming that the percent of SC/ST population is an appropriate way to measure equalization. There is less of a pattern of equalization in the distribution of per capita state government assistance.
About half of all block level governments and nearly all districts show a shortfall between recurrent revenues and annual expenditures. These gaps appear to be easily covered by drawing on cash balances. As in the case of gram panchayats, the practice seems to be one of pre-funding the budgets by permitting districts and blocks to carry large balances.
State Government and FISCAL DECENTRALIZATION
From the above discussion, one can draw the conclusion that the fiscal system in West Bengal is heavily dominated by the state government. By itself the state accounts for 76 percent of direct expenditures, and raises 96 percent of all revenues. A recent analysis by Oommen (2006) estimates that the local government expenditure share in West Bengal is only about one-half of the national average.
It is also the case that the state government in West Bengal has chosen to limit the amount of fiscal discretion given to its local units, so by this measure we also can characterize West Bengal as a very centralized fiscal system:
• Gram panchayats have some power to tax, but the tax rates and the legal tax base are determined by the state government. Local governments have discretion mostly in terms of how they administer the tax.
• To a large extent, expenditures are dictated by the conditions associated with receipt of state and central grants and transfers. The untied amounts received by local governments are limited.
• The vertical share of local governments -- their “entitlement” -- is determined by the central and state governments, annually and in an ad hoc way. This limits possibilities for efficient fiscal planning by local governments.
How could the state begin to move this situation toward fiscal decentralization? The PRIs in West Bengal might be “upgraded” in two ways: (a) by increasing the size of their expenditure budgets, and (b) by giving them more discretion to make fiscal decisions. The first of these paths will be costly, if an enhancement in the scope and quality of public services is envisioned, and if a corresponding net increase in local government funding is given. The second would also imply new costs in the form of investments to upgrade the capacity of local governments and the transition costs necessary to get PRIs “on the learning curve”. The transition cost might include a short-term outlay to cover temporary service level shortfalls. One way or another, fiscal decentralization will imply a drain on the state budget.
The two avenues open to the state government to find the necessary resources to finance decentralization are: an increase in state government tax revenue, and a redirection of existing funds.
State Taxation
The state could enact a new tax or a general tax increase with revenues dedicated to the PRIs. For example, a specified amount could be dedicated to fund an increased amount of unconditional grants. Though not explicitly stated, something similar to this was implied by the SFC recommendation for a 16 percent share in the state taxes dedicated to revenue sharing with local governments.
Whether the resources necessary to finance fiscal decentralization can be found will depend in part on whether the economy of West Bengal has grown fast enough to generate the necessary surplus or fiscal space. Though West Bengal is a poor state in terms of average per capita GDP, it has grown well above the all-India rate over the past decade, thanks in large to robust growth in the agricultural sector (CMIE, 2006).
There also would seem to be room for a tax increase. West Bengal’s rate of revenue mobilization is low by comparison with other states, and has declined over the 1998-2004 period. A number of research studies have reached this conclusion (Government of India, 2004; Coondoo, et. al., 2005, The World Bank, 2005a). West Bengal’s relatively weak tax performance is longstanding (Jha, et. al., 1999).
One could also make the case that the West Bengal State Government is not presently in a good place to finance such an upgrading. The budget situation is still emerging from a significant imbalance. Over the past decade, West Bengal’s fiscal position was one of the weakest in the country (Rajmal, 2006; Purfield, 2004, Government of India, 2004). Though the fiscal deficit is down from its 9 percent level in 2000, even the projected 2007 deficit level of 5 percent of GDP presents a significant hurdle to overcome. Some significant and perhaps painful discretionary measures will need to be taken to reduce this deficit. As Rajmal (2006) has pointed out, the state government may have limited discretion to address the issue. Between 2002 and 2004, interest payments and pension payments together were equivalent in amount to about 70 percent of revenue receipts. Moreover, there are significant subsidy programs that are not easily cut back or withdrawn. Finally, there is the commitment to a large wage bill for state government employees and the possibility of another fiscal hit by the next pay commission.[41]
Redirection of Existing Funds
Redirection as a strategy would involve shifting resources from other programs toward the support of local governments. The issue here is less about funding new monies than it is about rearranging priorities.[42]
Redirection may be a very difficult strategy to implement. The budget speech of 2006-2007 (Government of West Bengal, 2006) makes the case that there are many other important and high priority claims on budgetary resources that will constrain any budget redirection:
• debt burden relief is a high priority,
• rural unemployment is a major issue to be addressed, and
• many social and physical infrastructure needs are pressing.
Fiscal decentralization certainly would address the last two items on this list. The
question at hand, however, is whether state government vertical programs would do a better job of service delivery. If so, redirection would not be a good strategy choice. Those who push hard for more decentralization will argue that some better balance between state and local government involvement will give a better result. There does not appear to be any hard evidence to support one position or the other.
Certainly the state government has not disowned the strategy of fiscal decentralization. The 2006-2007 budget speech underlines the need to strengthen panchayats, but no concrete, immediate plan is offered. An obvious choice is to redirect some of the expenditures made by state line agencies toward the gram panchayats. Though this “offloading” strategy would impose no revenue cost on the state, it would raise other questions such as the capacity of the local governments to absorb the additional responsibility and whether this offloading would be accompanied by restrictions as to how the money should be spent. Otherwise, per capita expenditures of the local governments would be increased but there might not be an improvement in service levels or even budgetary discretion.
The Granting of More Fiscal Discretion
Another part of the reform package to address fiscal decentralization could be to increase the spending and tax discretion of local governments, particularly gram panchayats. This may be done in two ways. First, the state government could “untie” its grants and schemes. This has already been done for the Rs 278 crore SFC grant. This model could be extended to the salary grant which at present is no more than a cost reimbursement to local governments for state-determined posts and compensation. An unconditional grant would simply award the funds to local governments on a formula basis and allow them to decide between salary and non salary expenditures. Under this scenario, a local government might decide to move funds from teachers (where salaries might be deemed too high) to health professionals (where they might be deemed too low). In fact, all state grants and schemes might be converted to an unconditional status. This strategy is considered in the next section of this report.
The unconditional grant route is not without risk. This strategy will impose a cost on the state, in terms of the direction over public investment that it will give up. It will carry a risk in that the money might not be spent “wisely” and the result may be deterioration in service levels and a loss in confidence on the part of taxpayers. If some gram panchayats fell into a pattern of fiscal indiscipline, it would be left to the state to cover this.
Reform Options and Evaluation
As the government of West Bengal moves toward the goals of better service delivery and more local self governance laid down in the Constitutional amendments, it will need to continuously rethink the structure of its intergovernmental fiscal system. The work of the Third State Finance Commission will be an appropriate opportunity to begin such a rethinking. In this regard, it is important to note that reform choices that would lead to a functioning third tier of government in West Bengal are not being held hostage by central laws and regulations. To the contrary, the Constitution strongly endorses fiscal decentralization. The wherewithal to implement changes in the system is clearly in the hands of the state government.
In the discussion below, we suggest and evaluate a number of reform directions that are in step with the intent in the Constitutional amendments. Some are consistent with ideas that have been offered by the first two State Finance Commissions, though in each case we take a different approach than did the SFC. Some are more far-reaching, and would require major structural changes. However, bringing some less feasible options to the table might be a useful way to enrich the debate about fiscal decentralization in West Bengal. Some other reform options hold promise but are not fully developed here because they involve changes in the method of financing urban local governments, which is a subject that this paper does not directly address.
We evaluate three general directions for reform: (a) a change in the structure of local government, (b) enhanced expenditure assignment and fiscal autonomy for gram panchayats, and (c) a revamped system of state government transfers.
Decide on an Optimal Tier for Local Self Government
The Constitutional amendments call for a third tier of government where voters can have both a voice in the decision about the quality of local public services that they will receive, and a responsibility for directly financing some of these services. While the intent is to involve the PRI as autonomous local governments there is no pronouncement in the amendments about the balance among the three tiers of PRI in terms of the degree of fiscal autonomy that they should be given. The costs and benefits of the various options should be weighed. The state government may retain the present hierarchical arrangement, or move the focus to gram panchayats (or to either of the other two levels). The principal instruments for shifting the emphasis from one level to the other are revenue assignment, expenditure assignment, and the distribution of intergovernmental transfers. All of these can be changed at the discretion of the state government. So, it falls to the state government to decide whether and how the roles and relative importance of the three levels of PRI ought to be changed.
The right structure of local government in West Bengal depends on the goals that government most wants to accomplish. In terms of capturing the economic efficiency benefits of decentralization (which requires moving government decisions closer to the people), the gram panchayat is the best candidate for autonomous local government. It is small enough to force elected leaders to pay attention to the preferences of voters, and this relatively small size gives the local population the sense that their vote will matter. In West Bengal, the average population size of the gram panchayat is 14,254 versus 181,000 for blocks and 4.4 million for districts. The gram panchayats in West Bengal are about three times larger than the all-India average, and are not small by world standards for local governments (See Box 4). Unlike the case in many Indian States, the gram panchayats in West Bengal may be small enough to move government close to the people but large enough to avoid some of the diseconomies of small size, and the efficiency losses due to spillover effects.
|Box 4 |
|Gram Panchayats in India |
| |
|The average population size of a gram panchayat in West Bengal is not small, either relative to that in other states in India or |
|relative to many other countries. See the comparison below. |
| |
|Average Population of Total Population |
|Local Governments (in millions)a |
| |
|All India (gram pachayats) 4,386 1028.6 |
|West Bengal State 14,254 80.2 |
|Karnataka 8,872 52.8 |
|Kerala 26,793 31.8 |
| |
|United Kingdom 126,128 59.7 |
| |
|Denmark 18,760 5.4 |
| |
|Poland 15,561 38.5 |
| |
|Finland 10,870 5.2 |
| |
|Spain 4,930 43.1 |
| |
|Hungary 3,242 10.1 |
| |
| |
|a Source: Non-India data from Fox and Gurley (2006). India results are author estimates based on data from various services. |
An argument that favors the choice of the gram panchayat as the best candidate for local government is that it is a longstanding choice of many analysts and decision makers. In fact, under the present system, the gram panchayats already have some fiscal independence. Budgets are approved by the elected local councils, rather than by a higher level government, and this is perhaps the most essential element of fiscal autonomy. GPs have some budget discretion on the expenditure side, but they do not have the power to hire, fire, or determine the compensation rates of their employees. Moreover, they are saddled with a significant number of budget mandates in that most of the intergovernmental transfers that they receive are conditional upon a particular use of the funds. Gram panchayats receive little by way of untied grants[43]. The gram panchayats also have some independent powers to raise revenues through taxation, as well as through user charges and fees. However, gram panchayats do not have discretion in setting the tax rate or determining the tax base. Such discretion will be important if the GP is to become a focal point for local self government. Districts and blocks are saddled with the same restrictions on the expenditure side of their budgets, and neither has taxing power. Some have argued that districts and blocks behave more like spending agents of the state than like autonomous local governments.
On balance, a strong case can be made on efficiency grounds for the gram panchayats as the principal unit of local government. However, economic efficiency is not the only criteria that may be used in choosing an optimal size local government, and other choice criteria may point to advantages of emphasizing the block or district level as an autonomous local government. Four advantages of larger local governments would seem particularly important.
First, both districts and blocks are large enough to capture the cost savings from economies of scale in the delivery of services. For many public services, gram panchayats may not be large enough to take advantage of size economies. This is especially the case for services that require large capital costs, because there is not an adequate population over which to spread these costs. To allow delivery of such services by gram panchayats, in such cases, might be to invite cost increases, and perhaps a lower quality of public services. However, the methods of service delivery for many types of rural service (e.g., water supply, sanitation) do not require the level of capital investment that is the case in urban areas.[44] Unfortunately, there is little evidence on size economies in the delivery of local public services in rural areas in LDCs and the results of studies for industrialized countries likely are not relevant[45]. Still, it seems reasonable to believe that consolidation to the block level would eliminate some duplication and reduce administrative costs.
Second, block and district governments have a larger benefit zone and therefore can internalize spillover effects from certain public services better than can gram panchayats. Examples are environmental and transportation services. This suggests that such services should be delivered by districts, blocks, or by the State government. There is an alternative to shifting assignment of such functions to a higher level government. A conditional grant could be given to gram panchayats to stimulate their spending on functions with spillover benefits. However, this can be an expensive way to deal with the externality issue. Moreover, there is the issue of estimating the expenditure response of a local government to a particular level of conditional grant funding, and the high cost of effectively monitoring local compliance with the conditions. So, for a number of important services, delivery by gram panchayats is not justified, even on efficiency grounds.
Third, many gram panchayats have not shown themselves to have good capacity to deliver services. Districts and blocks are larger, and likely could offer more specialization in work assignments, and might be able to recruit a more skilled managerial staff.
Fourth, there are 3,354 gram panchayats in West Bengal, and this is an unwieldy number to control from the state government level. Even in a decentralized government system, there is need for such controls. The necessary controls might involve, for example, audit, enforced accounting standards, civil service rules, grant distribution formulae, following up on compliance with mandates and tax limitations, etc. The 341 block level governments, or the present hierarchical arrangement, would seem a better choice for a workable structure of local government, when the span of control issue is considered.
There is no easy answer to this question. There has long been a debate about the optimal size government, and the debate has not led to the conclusion that any one population size is “best”. The optimal size government depends on what objective one wants to emphasize. If the spirit of the Constitutional amendments is read as calling for more emphasis on the economic efficiency objective of fiscal decentralization, the case is strong to upgrade the role of the gram panchayat and make it the primary unit of autonomous local government.
If strengthening the gram panchayat as an autonomous local government turns out to be the best choice for West Bengal, should the block and the district tiers of government take on a different role? There are two general approaches that might be taken in response to this question.
A first approach would be to create a unitary system with two levels (state government and gram panchayat) and formally designate districts and blocks as deconcentrated arms of the State administration. Under this scheme, gram panchayats would be the only sub-state government unit that represented local voters.
In some ways, this would not involve much change. Districts and blocks already act like agents of the state. On the other hand, if this is to be a restructuring, it suggests major changes in revenue and expenditure assignment, and in the degree of autonomy assigned to gram panchayats[46]. In particular, responsibility for some of the expenditures presently made by blocks and districts (about two-thirds of total PRI expenditures) would be either shifted downward to the gram panchayats, or in the case of services characterized by significant scale economies or externalities, would become deconcentrated state expenditures (vertical programs). The net impact of this approach to decentralization would be to heighten the fiscal importance of the gram panchayats relative to blocks and districts. In the case of services presently administered by blocks and districts, there is not much autonomy in any case, so this solution would likely lead to a net gain in welfare. In order to move toward this approach, the expenditure mapping presently in place (Government of West Bengal, 2005) would need to be redone with an increased emphasis on the gram panchayat level.
The main advantage of this approach is that it clarifies which PRIs are local governments and which are state and central government implementing agents. With the roles clarified, the stage would be set for an assignment of expenditure responsibility that the state government felt would best match its decentralization objectives.
A second approach is to leave things as they are, with three levels of PRI, and to assign functions to the up-levels according to factors such as service delivery capability, economies of scale and the possibility of spillover effects. Certainly this would be the least disruptive approach, and the expenditure mapping could be redone to enhance economic efficiency by assigning more “local benefit” functions to gram panchayats. The gram panchayats could be given increased autonomy in the areas of both taxation and expenditure delivery, much as proposed in the case of the unitary program above.
The main differences in these two approaches are that in the case of the present structure, gram panchayats will likely end up with less responsibility than under the unitary regime, and that a hierarchical arrangement among gram, block and district panchayats will remain in place. In short, there will continue to be less gram panchayat participation in service delivery. Another drawback is leaving in place the likelihood of overlapping service responsibility among three levels of PRI.
Expenditure Assignment
Expenditure assignment should be a priority reform concern for the State government and for the State Finance Commission. If gram panchayats are to play a meaningful role as local self governments, their expenditure responsibilities must be upgraded. In 2005, GP expenditures accounted for about one-third of the PRI total, about Rs 138 per capita ($US 3.13), and about 5.3 percent of all government expenditures. It is not likely that gram panchayats will deliver services that will matter greatly to the local quality of life when the amounts are so small. Nor is it likely that voters will get deeply involved in budget decisions when the amounts involved are so small. The situation is not much better for the other levels of PRI. Districts account for only about 7 percent of government spending in the state, and blocks for only about 3.6 percent. All together, the PRI manage about 17 percent of state and local government spending in West Bengal.
To move toward the type of fiscal decentralization envisioned in the Constitution, it will be necessary for the State government to ratchet up the spending of gram panchayats (or all PRIs) and to involve them more heavily in delivering services that matter deeply to their constituent populations. This might be done with a strategy that involves the state government taking three types of action (a) the assignment of increased expenditure responsibility and fiscal autonomy to the local governments, (b) assistance in developing an enhanced capacity of local governments to deliver these services, and (c) provision for higher levels of funding to enable delivery of these assigned responsibilities. The state government might look to the SFC for leadership in developing a strategy to achieve this objective.
Clarify and Upgrade Expenditure Responsibility. There is need for more clarity in the assignment of expenditure responsibilities. In theory, this is not an issue among local governments in West Bengal, because the state has done an extensive expenditure mapping (Government of West Bengal, 2005) that defines the sub-functional responsibilities of each level of PRI. The mapping contains a detailed and clear statement of how the state government believes that expenditure responsibilities ought to be assigned among the three tiers of PRI. As is so often the case, however, practice departs from theory and the actual division of responsibilities has lead to confusion and overlap.
The even bigger problem in West Bengal is the murkiness in the division of responsibilities between the state government and the local governments[47]. The Constitution defines a list of 29 objects of expenditure that may be either assigned to local governments or may be concurrent responsibilities with the State government. The State of West Bengal has chosen the concurrent route for all 29 functions, and this has led to three problems: (a) too limited an involvement of PRIs in service delivery, (b) some confusion as to whether the state or the local governments are responsible for certain services, and (c) an inability at the State level to rationally determine the amount of resources necessary for PRI to deliver assigned services at an adequate level.
The World Bank (2005) offers an interesting approach to resolving the expenditure assignment issue. The argument is that for each expenditure sector, there are five activities that are (better or worse) candidates for decentralization: policy and standards, planning, asset creation, operation, and monitoring and evaluation. In the case of schools, water, sanitation, and employment generation, they argue for assignment of operational responsibility to the gram panchayat level. This would include a transfer of functionaries to the control of the local government in order to increase the accountability of local officials.
Neither of the first two SFCs in West Bengal have taken on the issue of expenditure assignment in a comprehensive way. Both Commissions have argued to increase the share of untied grants in the State budget. While this would give PRIs more resources, and more autonomy, it would (presumably) leave in tact their expenditure responsibilities and their discretion in making decisions about how these funds should be used. The third SFC might consider addressing this larger issue directly, by considering the need to upgrade the expenditure assignments of local governments. The first step would be to determine for each of the 29 objects of expenditures, which sub-functions or sub-activities will be assigned exclusively to rural local governments. Then it would redo the mapping exercise to assign subfunctions of these expenditure categories to each of the three levels of PRI. Somehow, delivery would need to be monitored in order to ensure proper involvement by the PRI and to avoid duplication.
The second step would be to clarify the assignments that go with this classification of expenditure responsibilities by sub-activity. For example, if The World Bank (2005) model were to be followed, school operations and teachers would be shifted to gram panchayats, and water supply and sanitation in rural areas would become a gram panchayat function. Such changes would significantly upgrade the place of rural local governments in public service delivery.
The third step would be to define a target level of spending for GPs that would be great enough to stimulate voter interest and involvement in the process of budget making, and at the same time would enhance the quality of services available. The target level of spending would reflect both the minimum standards of service desired, and the fiscal limitations faced by the state government.
Fiscal Autonomy. The goal of enhanced local self governance requires more than just assigning new expenditure responsibilities to local governments. So long as the State of West Bengal (and the Central Government) continue to dictate how the money should be spent, local governments will not have the ability to adjust service delivery to match citizen preferences. As noted above, if the local population thinks of their elected local government as being little more than a spending agent of some higher level government, they will not hold their elected local council responsible for the quality of services delivered. Local governments must be given more autonomy to make budget decisions if local government officials are to be accountable to their constituents. Unless this happens, local voters/constituents will have little incentive to be involved.
There are a number of areas where increased autonomy might be given. First, those officials involved in the delivery of local public services could be assigned as local government employees. Their hiring, firing and the determination of their compensation levels can be made local government decisions. The power of this approach is illustrated by the case of education in Madhya Pradesh where teacher control was shifted to the local governments (The World Bank, 2006). The PRIs were given the power to hire and fire teachers (but not to determine wage rates). The result has been a remarkable improvement in the rate of teacher absenteeism and an expansion in the coverage of the school system.
Second, conditionalities could be removed on the distribution of state grants to local governments. These could become untied funds with expenditure made at the discretion of the local governments. Whenever this reform option is proposed (in nearly all countries), the criticism raised is that government funds will be diverted from what the upper levels of government consider the highest priority, and that corruption and waste will necessarily follow. The response to these observations is, first, a diversion of funds to projects with a heavier orientation toward local benefits will almost certainly happen. As local politicians and local voters learn about accountability, the budget will begin to show more “local choice” investments, and a better implementation of these projects. This is the essence of the fiscal decentralization story. In fact, the shift in the package of service delivered would be evidence that the fiscal decentralization strategy is working.
Unfortunately the corruption and waste story is also probably a valid one. Gram panchayat officials are not skilled in service delivery and local management. The books of account may not be kept well, staff may be untrained and there is probably little by way of skill in the area of tax administration. As local officials learn their new responsibilities, money may not be spent as wisely as if it were in more experienced hands. On the question of whether decentralization leads to more corruption, there is not yet a general agreement. In the scholarly research, Brueckner (1999) finds a direct relationship, but Fisman and Gatti (1999) find the opposite. They argue that corruption under decentralization can be lower if both revenue raising powers and expenditure responsibility are decentralized.
The spirit of the Constitutional amendments and of the recommendations of the State Finance Commissions is that of local self government. The implication here is that, in so far as is possible, grants should be unconditional and expenditure mandates should be removed. Therefore, the reform goal might be to move towards elimination of conditions associated with State government grants to GPs, in favor of unconditional grants with a defined vertical share[48]. Such a reform would be consistent with the recommendations of both the First and the Second State Finance Commissions in West Bengal. Both recommended a dramatic increase in untied grants to local governments. The state has not followed this recommendation and the present level of untied state grants is equivalent in amount to less than 2 percent of state government taxes.
Third, local governments could be given more independence in choosing their level of taxation, rather than have the tax rate and the tax base determined at the state level. This is an important part of the reform package. Local government officials could be made more accountable to their constituents if services were financed at least partially by taxation. In this regard, it would be important that the local government has the power to set at least the rate of a local tax. The state could set a minimum tax rate for GPs, but could leave open the ceiling rate. Under this arrangement, the local council will be more responsible to the local population for the quality of the service delivered.
Enhanced Capacity at the GP Level. It would be self-defeating to assign new responsibilities to GPs if they could not deliver these services in an effective way. And, every indication is that there are serious capacity problems at the local level. But not to assign more responsibility to the GP because their capacity is weak is to create a self-fulfilling prophesy. If GPs are not put on a learning curve as regards service delivery, they will never develop the capacity to absorb more responsibility.
The state could take a number of steps to improve the service delivery capacity of gram panchayats. Though this subject is beyond the scope of this work, a stylistic listing of some possibilities that have been offered elsewhere are below:
• In many gram panchayats, there is a need to increase the size of the gram panchayat staff and upgrade the quality of the staff.
• Panchayat secretaries often are not trained in the rules, procedures and statutory provisions of the panchayats. Short training courses should be provided (Subrahmanyam and Annamalai, 2004).
• GPs should be given authority to buy services from the private sector or contract with higher level governments in cases where they do not have adequate capacity to deliver services. Resource pooling by several gram panchayats for a specialized service might be considered. (World Bank, 2005).
• Automation in the case of more advanced GPs, should be encouraged, at least for record keeping purposes.
• Provision should be made for annual audits of local government books of account by external parties.
• Re-assessment for purposes of local property tax should be made by external valuers.
The first step to be taken here is to assess the need for training and staffing at the GP level. The goal would be to assess the capacity of GPs to assume new responsibilities and to design the technical assistance necessary to put this capacity in place. Second, a transition plan should be put in place whereby the new expenditure responsibility of gram panchayats would be passed to them when they are deemed ready. Until that time the services, and the finances that go with these services, would be delivered by blocks and districts. Third, a system to monitor and evaluate the performance of gram panchayats would be put in place.
Increased Own Source Revenue
Much has been made of the need for gram panchayats to increase their own source revenues (Rao and Singh, 2001). Success in this area will come from three kinds of initiative. First, some potentially productive tax bases must be assigned to gram panchayats, along with the power to set the tax rate[49]. There are many options for rural local government taxation that either are now used in West Bengal or are used in other states and might be considered in West Bengal. These include:
• Land and building tax. This is the mainstay of local taxation in rural India and in most countries. The needs in West Bengal are to remove any rate ceiling in favor of a policy of local governments setting their own rates, and state support for an upgrading of property tax administration.
• Property transfer tax. Local governments may levy a tax against the consideration in the transfer of property. In many countries around the world, this is an important source of local revenue. However, administration of a property transfer tax is beyond the reach of rural local governments. A better route is for the local government to be allowed to set a sur-rate against the state government stamp duty[50]. A sur-rate is preferable to a share of collections, because it forces the local government to make a tax choice and to be accountable to taxpayers for the expenditure of that money.
• Entertainment tax. In West Bengal, the entertainment tax is actually an intergovernmental transfer to local governments. The tax rate and base, and a sharing rate on collections with local governments, is set by the state government. Since most/all revenues are shared locally, the state government has little incentive for vigorous collection efforts. The entertainment tax might be a candidate for local taxation (or at least local rate setting). It is a local tax in some Indian states, e.g., Rajasthan, Karnataka, and MP (though rates are still set by the state).
• Professions tax. A tax on professions, trades, and employment is levied in several states. In at least Rajasthan, Assam, Punjab, and Bihar the tax is administered by the panchayats. This is a kind of rudimentary income tax that reaches those in rural areas with a greater ability to pay. Administration of the tax is difficult, especially for rural local governments.
• Land cess surcharge. State governments levy a cess against land for a variety of purposes. In some states, panchayats are allowed to levy a surcharge against these cesses, with the revenues returned on an origin basis. This approach to taxation is consistent with the accountability maxim of decentralization, so long as the panchayat sets the sur-rate.
Second, the capacity of states to better administer local taxes should be upgraded so that tax effort might be increased. With respect to the property tax, a number of steps should be taken:
• The state could develop a circular of guidelines on assessment and collections.
• The creation of an independent valuation authority should be considered. It should be staffed with trained values.
• GP Secretaries will be trained so as to develop basic valuation skills.
• Tax mapping, showing all properties and land uses in the local government area, should be completed.
The ability to improve the collection rate on other tax and non tax sources should be strengthened. In this regard, the staff support of the panchayat secretary could be upgraded. The collection of non tax revenues may have been pushed aside in order to comply with the ever increasing compliance issues associated with the schemes. With respect to the assignment of other taxes and more efficient collection of these, a number of possibilities for improvement have been suggested:
• More complete tax rolls for each levy (e.g., professions and trade tax, entertainment tax, land cess) should be compiled and annually updated.
• Enforcement should be more vigorous and proper sanctions should be applied. The names of delinquents might be publicly posted.
• Where permitted, surcharges on state government levies should be imposed. This allows the GP to bypass the entire administrative process.
• Where there is an organized sector, and where the GP is permitted to levy a tax on professions and trades, tax deductions at source should be allowed, as is done in Kerala and A.P.
Third, rural local governments might be given some significant incentives to upgrade their level of tax effort. This might be done in three ways. One is to put no restrictions on how the money can be spent. A second is to increase the taxing powers of gram panchayats either by assigning them additional taxes or removing any tax rate limits. The third approach is to reward tax effort through the system of transfers with a kind of incentive grant. The programme would work by matching local collections (or increases in local collections) with some amount of state grants. Such an approach has been tried in both Tamil Nadu and Goa (Subrahmanyam, 2004).
Increased State Grants: Determining the Vertical Share
Even if gram panchayats are assigned more responsibility, and even if this capacity is upgraded, it will come to naught unless adequate financing is provided. Increased own source revenues are an important element of the reform, but will at best be only a small part of the financing needs. If local governments are to provide a meaningful level of services, a significant increase in state grants must be provided. Moreover, the local governments must have some discretion over how these funds are spent; otherwise they will tilt toward being spending agents of the state rather than autonomous local governments.
Both the First and Second State Finance Commissions recommended an increase in state funding of local governments. The recommendation of the first SFC was to institute a program for rural and urban local bodies with a vertical share equivalent to 16 percent of State government taxes. At the time of this recommendation, and at present, there is no specified percent of State taxes that is guaranteed for revenue sharing with local governments. The vertical share is determined annually on an ad hoc basis. It can vary from year to year depending on the financial circumstances of the State Government.
A second dimension of grant policy is whether the additional funds will be conditional upon use for certain types of expenditures, as might be prescribed by the State, or whether they will be untied (unconditional) funds. The SFCs have recommended untied grants as a way of giving local governments more discretion in establishing spending priorities. The view here is that the general spirit of the State Finance Commission recommendations is correct. We propose and evaluate a reform package that is similar in intent to that of the SFC, but is structurally different.
We begin this analysis by establishing a target level of gram panchayat expenditures to be financed. Properly calculated, the target amount will depend on the expenditure assignment decided upon. It also will depend upon the minimum level of expenditures that is set by the state. As a matter of good policy, it is essential to assign expenditure responsibility and service level targets before determining the vertical share of transfers to be allocated[51]. This follows the well-traveled principle that “finance follows function”. The failure to follow this maxim might have been a problem with the model developed by the earlier State Finance Commissions[52]. The 16 percent proposal for the vertical share of all local governments appears to have been more of an arbitrary decision than one based on objective analysis.
It is not in the scope of work here to develop a new set of expenditure assignments or to develop a set of minimum expenditure requirements[53]. Rather, we simply assume a target level of per capita local government expenditures in order to demonstrate the impact of a new state grant system. We set an illustrative target for GP minimum per capita expenditures of Rs 414 (three times the current average level of per capita expenditures) and alternatively at Rs 276 (two times the current average level). We make the assumption that all of this increment above the present level of per capita expenditures (Rs 138) would come from state government grants and transfers to gram panchayats. We further assume there will be no reductions in central transfers. Note that this analysis is portable to different expenditure targets.
In this first example, we propose a minimum expenditure approach to revenue sharing where the vertical share for gram panchayats is based on a guaranteed minimum level of spending for each GP. This might be viewed as a transition to a more traditional formula-based system, as is described below[54]. The revenue sharing rules for the transition system -- which do not feature a formula based on socio-economic variables -- are as follows:
• Each gram panchayat will be brought up to a minimum per capita expenditure of Rs 414 (or, alternatively Rs 276 under the more modest target).
• Any gram panchayat with a present spending level that is higher than Rs 414 (Rs 276) will be held harmless at their present level. However, those GPs will not receive additional state grants.
The calculations for this hypothetical level of local government expenditures and its financing are shown in Table 43. Reaching the target minimum expenditure level of Rs 414 per capita would require that GP expenditures be higher than at present by Rs 15.8 billion (row 3 of column 1). The result is that the transfer from the state government would rise to over Rs 17 billion (row 5), or to an amount equivalent to about 10.6 percent of state government own source revenue collections (row 7). If the target was a less ambitious doubling of minimum per capita expenditures by GP, the vertical share would be 5.7 percent of state government tax collections (see the calculations in Column (2) of Table 43). In either case, the amounts are well above the present level (there was no distribution in 2005), but well below the 16 percent of state taxes recommended by the State Finance Commission.
Had this program been enacted at the higher level in 2005, the majority of GPs would have seen an increase in per capita total state grants of over 90 percent (Table 44). As may be seen in Table 25, 591 of the 3,074 gram panchayats in the sample would realize an increase in state aid of more than 95 percent. If the less ambitious minimum expenditure were used, most GPs would witness an increase in per capita state grants of 80 percent or more (See Box 5).
|Box 5 |
|Explanatory Note on Simulation Exercise |
| |
|This simulation is to show the impact of an unconditional state grant program, where the vertical share is equal to the target |
|amounts described in Table 24, and the horizontal shares are according to the formula described. The data used in the simulation |
|are for the year 2005. |
| |
|The counterfactual in this analysis is the amount of state government transfers distributed in 2005 as unconditional grants. Note |
|that the state did not distribute the State Finance Commission grant in 2005, hence the comparison here is against a very low |
|base.1 |
| |
|We can say, however, that the target level in this analysis implies a vertical share of Rs 1729 crores in 2005 under the high |
|scenario, and Rs 938 crores under the low scenario. The 2005 amounts for all state grants used in this baseline were equivalent to|
|Rs 147 cr in this baseline. Therefore, we are evaluating an increase of 1582 crore (791 in lower case) for gram panchayats in the |
|total grant pool. |
| |
|1The State did distribute the Finance commission grants in 2006, with a vertical share of Cr 278, but data describing the actual |
|distributions are outside the data base available here, which is for the years 2003-2005. |
With respect to the horizontal distribution, we ask if the proposed minimum expenditure system is more or less equalizing than the present system. The answer depends on how one defines equalization. Certainly the expenditures of most gram panchayats are dramatically increased under this approach. Moreover, the gap between the high spending GPs (who are held harmless under this scenario) and the low spending GPs is narrowed considerably. Many would see this as a favorable outcome and one that is consistent wit the idea of reducing disparities.
On the other hand, equalization might also be defined as developing a system that compensates GPs with low fiscal capacity or with high expenditure needs, so that they are on an equal footing with better situated local governments. Proponents of this vision of equalization might ask, for example, if the relative revenue shares of the more backward GPs greater or smaller than under the present system? If the latter, the minimum expenditure approach would not pass this version of the equalization test.
To compare the distribution effects of the present system with the minimum expenditure system, we have computed the simple correlations shown in Table 45. In column 1, we show the correlation between selected variables and the per capita distribution of the 2005 state aid system, and in column two with the proposed minimum expenditure system. If the percent of SC/ST population is the barometer for poverty, the proposed minimum expenditure system is no more equalizing than the present system. Neither shows a significant correlation with the percent of SC/ST population.
What we may conclude here is that a minimum guarantee program will eliminate low spending gram panchayats. However, this system will not favor poorer gram panchayats, over those that are less poor, with larger per capita allocations. Another disadvantage of the minimum expenditure approach is that it gives local governments no incentive for revenue mobilization.
A Formula Approach.
Increased, Untied Grants: A Formula Distribution
The analysis above describes a program with a guaranteed minimum allocation and with a hold harmless provision to protect any gram panchayat from losing revenues at the time of the introduction of the new system. Otherwise, it has not built-in features that would enable it to address specific issues, such as equalization or allocating funds more heavily to gram panchayats with a particular population make-up.
An alternative approach or perhaps the second step in the transition would be to adopt a new formula-based system but with the new vertical share maintained. In this section, we analyze the impact of one version of a formula distribution with the vertical share based on an entitlement of 5.7 percent of state government own source revenues. The question becomes one of settling on a formula that fits the goals of the state towards its rural local governments. The SFCs have suggested an objective formula, which is reported to have been mostly adopted by the State government for distribution under its present grant program. There are two ways in which the formula distribution among GPs might be improved over this system. First, it could be made simpler. Second, the revenue mobilization incentive might be made more effective.
There is no single “best” formula for distribution of a grant. The allocation formula chosen should be driven by the goals that the State government most wants to accomplish with its system of grants. There would seem to be three likely candidates for the appropriate goals:[55]
• ensuring a resource flow that would allow an adequate (minimum) level of local public services to be delivered,
• equalizing for differences in expenditure needs and fiscal capacity, and
• providing an incentive for revenue mobilization.
Moreover, the choice of a formula should also be influenced by acceptability at the local level, and by transparency. Both of these considerations would seem to argue for a less complex formula. Finally, any new formula must be politically acceptable, a consideration that will significantly constrain the policy choices.
Note that some of the goals outlined above reinforce one another, but others may conflict. For example, the goals of equalization and ensuring a minimum level of services in all GP areas probably are reinforcing. The revenue mobilization goal, however, may draw resources away from poorer jurisdictions and reduce the equalization emphasis of the formula. Likewise, the minimum service level objective may conflict with the goal of formula simplicity. Finally, any proposed change will produce winners and losers, even if only in relative terms, and therefore will have political opponents.
Deciding on a new formula is no easy matter. In the end, it will come down to weighing the balance between equalization and investing in GPs with greater immediate growth potential, and to the outcome of a political bargaining process that always plays a major role in formula determination. The State should begin with a clear statement of the objectives to be accomplished, and design a formula that best matches these objectives. Then it should move on to the art of political compromise. The casual search for formula variables based on data availability and guesswork about what they might mean, should be avoided.
There are many possible formula distributions that might be considered. The proposal we offer here is for purposes of illustration, but it does suggest how a new system might be developed. Developing such a formula involves four considerations.
Eligibility. If the GP is chosen as the primary unit of autonomous local government, State government grants in aid could be allocated directly to gram panchayats, bypassing the districts and blocks. Under this method, districts and blocks would be part of the vertical programs of the state. They might have responsibility for monitoring the performance of the gram panchayats, but they would not participate in the grant system as local governments. This is the approach we take in this example.
Vertical Sharing Pool. The vertical sharing pool would be established as 5.7 percent of State government own source revenues. Of this total amount of state grants, approximately 75 percent would be distributed by general formula, and 25 percent would be distributed from an incentive fund for local revenue mobilization. The state would commit to full distribution of the entitlement in a timely matter. All funds would be untied.
General Fund Distribution. The general fund (75 percent of the total) would be distributed by a formula with equal weights for two variables: population size and SC/ST population. The first element of this formula would recognize general expenditure needs while the second would recognize the special needs of more backward GPs and would add an equalization component. Data used to make this allocation would be drawn from the census. This approach is transparent, easy to understand, and is objective.
Revenue Mobilization Component. Of the vertical share for State grants (5.7 percent of State government own source revenue), 25 percent (1.44 percent of State government own source revenue) would be allocated to a fund that would be used as an incentive to encourage revenue mobilization by local governments. The distribution of the revenue mobilization sharing pool among GPs would be 50 percent according to the per capita amount of tax and non tax revenue collections in the preceding year, and 50 percent according to the increase over the preceding year.
Ideally, the distribution would be based on an index of tax effort, i.e., a measure that makes allowance for one GP having a greater capacity to tax than another. (Such an index is estimated and reported above.) But these indexes are difficult to use and to defend, so we resort here to a shorthand measure. The inclusion of per capita tax collections rewards those who make a greater effort, irrespective of their capacity to tax, and provides an incentive to maintain that effort. The inclusion of the increase in per capita tax collections rewards those GPs who respond to the incentive by raising their efforts at revenue mobilization.
Minimum Guarantee. A constraint would be placed on the distribution of this revenue-sharing pool. No gram panchayat would receive an amount less than Rs 276 per capita. This level would be taken to represent the guaranteed minimum level of support for per capita expenditures. If the minimum was not attained after distribution of the general pool and revenue mobilization components, the general fund pool would be reduced to ensure that the minimum per capita expenditure supported reached Rs 276. The maximum that any GP could receive is Rs 1500.
Simulation Results. We have simulated the distribution of the full system--general grant, revenue mobilization, and minimum expenditure for GPs --, with the results shown in Tables 46-48.
An important feature of this proposal is that there are no “losers” among the gram panchayats. No local government would receive less than it presently receives because the total vertical share is ratcheted up from 1 percent to 5.7 percent of State government own source revenue, and because a minimum guarantee is put in place.
The “fully phased in system” would give a different distributional result than the minimum expenditure approach simulated above in that it includes the general component, the revenue mobilization component and the minimum expenditure component. We have simulated the distribution according to this formula system across all gram panchayats for which we have data. Less than 2 percent of the GPs would receive an increase in per capita grants of less than 10 percent. About 80 percent of the GPs will see an increase in per capita state grants of 50 percent or more by comparison with the current system (Table 46). The per capita distribution of the general fund component is similar for small and large GPs (Table 47) but the revenue mobilization component provides more grants per capita to the smaller GPs. The implication here, that smaller gram panchayats have been more active in revenue mobilization, is surprising.
This formula system has several features that fit with the goal of stimulating the involvement of GPs in service delivery. First, the base of the proposed state transfer system would be more elastic, i.e., the vertical pool will automatically increase with tax collections. The growth in tax collections in recent years in West Bengal has been robust. Second, the new system would be relatively simple, with only a two factor formula and a guaranteed minimum expenditure level. It would give government the capacity to periodically upgrade the minimum per capita expenditure guarantee, or to increase the weight of the equalization component, in a simple way.
Third, the proposed system would have an equalizing component. We estimate the relationship between selected measures of equalization and the new grant and report the results in Table 48. The formula system does not favor gram panchayats with a higher proportion of SC/ST population, hence is no more equalizing than the present system. Both, however, favor less populated GPs. The literacy rate, which may be an indicator of relative wealth in a GP, is positively correlated with state government intergovernmental transfers under the current system but is unrelated under the proposed system. What we can conclude here is that it will probably take a significant movement away from the revenue mobilization incentive to develop a formula with a strong equalization component.
Finally, the proposed system has a revenue stimulation package that is large enough to provide a significant incentive. Based on the results of this simulation we show a wide disparity in the amounts received for achieving higher levels of revenue mobilization. On average, a Rs 10 per capita higher level of revenue mobilization is associated with a Rs 3 higher level of grants received.
There are major disadvantages to this proposal. First, about 3 percent of gram panchayats do not gain from this scheme compared with the present system, and there are wide variations in the increases received by various GPs. One would need to understand this pattern and any anomalies that might be hidden here. Second, we have all of the necessary data for only 2,098 gram panchayats, but any new grant system would have to cover all 3,324 of the gram panchayats.[56] Third, the census data that populate this formula are available only every ten years. Fourth, there is a question about whether some gram panchayats could absorb the very large increases in resources that they would see under this new system. Fifth, exclusion of blocks and districts from this program presupposes that the expenditure assignments of GPs are most in need of increased emphasis. Finally, no parallel program for upgrading the finances of urban local bodies is offered here.
FINANCING THE FISCAL DECENTRALIZATION PROGRAM
Where would the West Bengal State government find the additional funds to cover such a program? Based on 2005 levels, the gap to be financed is equivalent to about Rs 16 billion under the high scenario, and Rs 8 billion under the low scenario. There are several possibilities for raising these additional funds, six of which are discussed below:
The government could encourage (require) GPs to generate more own source revenue. If this strategy were successful, it could reduce the amount of state grants necessary to reach the target level of expenditures. However, the revenue potential of this option may not be very great. The average level of GP own source revenue is about Rs 8 per capita. If this were increased by 50 percent, the result would be an additional Rs 201 million. This would be equivalent to about 1.2 percent of the Rs 16 billion gap to be covered under the high scenario and 2.5 percent under the lower scenario. Certainly this does not cover a major share of the cost of this fiscal decentralization program, but it does significantly increase the PRI contribution to rural local government financing, and so is well in step with the goals of the constitutional amendments. A good argument can be made that this is an essential part of the reform program.
A second scenario is to assign additional taxing powers to urban local bodies, and shift a commensurate amount of the distributable grant pool from urban local governments to gram panchayats. In 2005, urban local bodies in West Bengal received Rs 698 million in state grants. If Rs 349 million (50 percent of this amount) was redirected to gram panchayats, it would cover about 1.6 percent of the Rs 16 billion required under the scenario of a threefold increase and 3 percent in the case of a twofold increase. Urban governments might make up for this Rs 349 million revenue reduction by increasing property and land taxes and the entertainment tax, if such powers for making tax increases were granted to them[57]. This reform is in the right policy direction in that it moves municipalities and municipal corporations toward local self governance, but does not go very far toward covering the necessary funding for PRI upgrading. Moreover, it could exacerbate the financing problems of urban local bodies, which are already acute, and would have significant political costs.[58]
The state government could increase its tax effort and earmark this additional amount to the GPs. If the State government increased taxes by one percent of GSP, it would raise an amount equivalent to 95 percent of the needed revenue for the high scenario case and nearly twice that needed for the low scenario case.[59]
Certainly there is tax space in West Bengal. Own source revenues in the State were about 4.26 percent of GSP in the 2000-2003 period, and this ratio has declined since the 1993-1996 period (Government of India, 2004). As the Twelfth Finance Commission reports (Government of India, 2004, p. 44), this ratio increased in most Indian states. The policy question to be considered here is whether fiscal decentralization would be a priority expenditure, even if tax effort were to be increased. West Bengal is one of the most heavily indebted states, and in the 2000-2003 period, over 35 percent of revenue receipts were allocated to interest payments.
Part of the necessary funding for a decentralization program could be covered by a reallocation of expenditure responsibility and revenue receipts to the gram panchayat level. For example, if 20 percent of district and block responsibilities were allocated to the gram panchayats, and if the supporting revenues followed this reallocation, the additional amounts would cover about 17 percent of the financing necessary for the high scenario program and 33 percent for the low scenario program. There would be no net cost to the state if this were done, but neither would there be an increase in the vertical share of the PRI sector. This would be simply a reallocation of expenditure responsibilities to gram panchayats. A good argument can be made that this is an essential part of the reform program.
There is a fine line between the offloading of expenditure responsibilities by a higher level government and the reassignment of expenditure responsibilities to lower level governments. In some countries, the offloading has come without funding and is a not too veiled shifting of the deficit.[60] What we propose here is a reassignment that would be accompanied by full funding, probably in the form of central or state transfers.
Funds could be directed away from state vertical programs to the untied grant pool for gram panchayats. This would imply that gram panchayats would assume responsibility for certain programs that are now delivered as state vertical programs. This strategy would not amount to a net increase in funding of local governments, or a drain on the state budget. Basically, it would be an offloading of expenditure responsibilities from the state to the local governments. However, it would shift the locus of expenditure responsibilities from the state government to the rural local governments, and in that sense would be consistent with a fiscal decentralization strategy. It would differ from the strategy outlined immediately above in that it would make the money available on an unconditional basis and the gram panchayats could move the expenditures toward what it considers higher priority areas.
In order to make an estimate of the extent to which this form of redirection would contribute to the Rs 16 billion target, it would be necessary first to do the detailed work on expenditure assignment. It seems clear, however, that a noticeable part of the gap could be covered in this fashion.
The government might find external assistance to support the state budget during the period of transition to a decentralized structure. There are a number of issues here. First, all gram panchayats will not be prepared to assume all responsibilities in the reform year. A period of training and other capacity building activities will be required. Even when responsibilities are decentralized, there is a possibility of service breakdowns in the “hand-off” years, therefore a contingency fund will need to be put in place. The contingency fund and the capacity building could be candidates for external support.
Second, the enhancement of the own source revenue capabilities of local governments will take time and technical assistance from the state level. It may take a period of years before the new, higher levels of revenue can be reached. External support might be sought to backfill during the transition.
Third, the redirection strategy cannot be accomplished quickly. This involves moving some functions and functionaries from the state, district, and block levels to the gram panchayat level. To minimize the chance of a service level breakdown, this redirection will need to be phased in, perhaps over a five-year period. Even then, a contingency fund may be required.
Fourth, it seems clear that some form of tax support will be required to finance the increase in state transfers implied by this program. Even if the government were to commit to this, it would take a period of years to reach the target. External financing could cover the gap in the interim.
Annex
Annex
Table A-1
Matrix of Simple Correlation Coefficients:
Blocks a
| |POP |SC/ST |FP |LR |MW |
|Population (POP) |--- | | | | |
|Percent of SC/ST Population |.0762* |--- | | | |
|(SC/ST) |(2142) | | | | |
|Percent of Female Population |.1328* |-.2221 |--- | | |
|(FP) |(2463) |(2142) | | | |
|Literacy Rate (LR) |.1333* |-.2052* |-.0330 |--- | |
| |(2456) |(2142) |(2456) | | |
|Percent of Marginal Workers |.2425* |0.1729* |.0906 |-.0950 |--- |
|(MW) |(2142) |(2142) |(2456) |(2456) | |
|Percent of Agricultural Labor|-0.020 |.2546* |.0321 |-.2876* |0.247* |
|(AL) |(2453) |(2139) |(2453) |(2453) |(2454) |
a>* denotes significance at .05 level. The number in parenthesis is sample size.
Table A-2
Matrix of Simple Correlation Coefficients:
Districts a
| |POP |SC/ST |FP |LR |
|Population (POP) |--- | | | |
|Percent of SC/ST Population |-0.4492 |--- | | |
|(SC/ST) |17 | | | |
|Percent of Female Population |-0.2826 |0.3316 |--- | |
|(FP) |17 |17 | | |
|Literacy Rate (LR) |0.3701 |-0.2750 |-0.2054 |--- |
| |17 |17 |17 | |
|Per Capita GSP |0.181 |-0.515* |-0.088 |0.832* |
| |15 |15 |15 |15 |
a>* denotes significance at .05 level. Number in parenthesis is sample size.
Annex Table A-3
Matrix of Simple Correlation Coefficients:
Gram Panchayats a
| |POP |SC/ST |FP |LR |MW |
|Population (POP) |--- | | | | |
|Percent of SC/ST Population |-0.0649* |--- | | | |
|(SC/ST) |2100 | | | | |
|Percent of Female Population |-0.1505* |-0.0320 |--- | | |
|(FP) |2409 |(2100) | | | |
|Literacy Rate (LR) |-0.1384* |-1969* |-.0330 |--- | |
| |2456 |(2100) |(2456) | | |
|Percent of Marginal Workers |-0.2408* |0.1658* |.0906 |-.0950 |--- |
|(MW) |2456 |2100 |(2456) |(2456) | |
|Percent of Agricultural Labor|-0.0287 |0.2503* |.0321 |-.2876* |0.247* |
|(AL) |2453 |2099 |(2453) |(2453) |(2454) |
a>* denotes significance at .05 level. number in parenthesis is sample size.
Figure 1
Government Structure in West Bengal
[pic]
a Percent of total population
b Not including 3 notified areas
Figure 2
Per Capita GDP and Per Capita PRI Expenditures:
By District
Figure 3
[pic]
Table 1
Distribution of Public Finances Among Levels of Government in West Bengal: 2005
| |Percent of Total Expenditure|Percent of Own Revenues |Percent of Populationa |Exhibit: Per Capita |
| | | | |Expenditures |
|State Government |75.8 |95.8 |100 |1218.2 |
| | | | | |
|Urban Local Governments|7.89 |3.7 |28.0 |452.5 |
| | | | | |
|Rural Local Governments|16.26 |0.5 |72.0 |138.4 |
| Of which Districts |45.0 |41.8 | |155.8 |
| Blocks |21.9 |14.2 | |94.8 |
| Gram Panchayat |33.1 |44.0 | |137.8 |
a Total population in Kolkata Metropolitan Area is 14.96 million in 2001; of which 88.4 percent is urban (Administrative Report of the Municipal Affairs Department, page 2).
Sources:
• Population: Census of India, available at:
• Expenditures:
o PRI-West Bengal data base, The World Bank (See Annex A): accounts for 94 percent (17 out of 18) of the districts, 84.4 percent (288 out of 341) of the blocks, and 87.7 percent (2,941 out of 3,354) of the gram panchayats.
o Urban – Administrative Report of Municipal Affairs Department, 2005, Government of West Bengal.
o State – Finance Department, Government of West Bengal, Budget Publications 2006-07 () total expenditure heads (revenue account) minus line 3604 compensation and assignments to Local Bodies and PRIs (page 14)
• Own Revenue:
o PRI- West Bengal data base, The World Bank (see Annex A)
o Urban – Administrative Report of Municipal Affairs Department, 2005, Government of West Bengal (pages 25 and 26).
o State - Finance Department, Government of West Bengal, Budget Publications 2006-07 (): tax revenue plus non tax revenue (pages 1 and 3)
Table 2
Capital and Current Expenditure Shares by PRI: 2005
| |Capital |Current |Total |
|Districts (N=17) |85.50 |14.50 |100 |
|Blocks (N=288) |62.41 |37.59 |100 |
|Gram Panchayats |63.16 |36.84 |100 |
|(N=3,016) | | | |
|Total |63.4 |36.6 |100 |
Source: PRI-West Bengal data base: The World Bank (See Annex A).
Table 3
Expenditure Shares by PRI Type: 2005
| |Education |Housing |Infrastructure |Employment Generation |
|Administration |0.5 |0.9 |0.6 |0.6 |
|Salary |2.2 |1.4 |19.2 |17.6 |
|All Other Expenses |97.3 |97.7 |80.2 |81.8 |
Source: PRI-West Bengal data base: The World Bank (See Annex A).
Table 5
Expenditures and Revenues of Districts, Blocks, and Gram Panchayats:
by Population Size Group: 2005
|Population Size |Number in sample |Percent of Total |Percent of Total |Percent of Total Own |
| | |Population |Expenditures |Source Revenue |
|Districts |
|Less than 2,500,000 |4 |11.8 |15.2 |6.8 |
|2,500,001-5,000,000 |9 |48.8 |56.1 |40.4 |
|Greater than 5,000,000 |4 |39.4 |28.6 |52.8 |
|Total |17 |100 |100 |100 |
|Blocks |
|Less than 150,000 |93 |21.5 |29.1 |27.0 |
|150,001-250,000 |156 |56.4 |53.1 |60.1 |
|Greater than 250,000 |39 |22.1 |17.8 |13.0 |
|Total |288 |100 |100 |100 |
|Gram Panchayats |
|Less than 15,000 |849 |18.6 |23.9 |20.9 |
|15,001-20,000 |1,075 |34.7 |34.8 |38.4 |
|20,000-25,000 |681 |28.1 |26.1 |25.7 |
|Greater than 25,000 |356 |18.7 |15.3 |15.1 |
|Total |2,961 |100 |100 |100 |
Source: PRI-West Bengal data base (See Annex A).
Table 6
Percent Distribution of Expenditures by Gram Panchayats:
by Population Size in 2005
|Population Size |Number in|
| |Sample |
|Less than 2,500,000 |4 |
|Less than 150,000 |93 |
|Less than 15,000 |849 |18.6 |
|Population Size |Percent of Total |OSR Tax as a |OSR Non-tax as a |Percent of Total Revenue |
| |revenue |Percent of Total |Percent of Total | |
| | |Revenue |Revenue | |
|Less than 2,500,000 |2.6 |0 |2.6 |97.4 |
|2,500,001-5,000,000 |3.2 |0 |3.2 |96.8 |
|Greater than 5,000,000|7.1 |0 |7.1 |93.0 |
|Total |4.0 |0 |4.0 |96.0 |
|Less than 150,000 |2.9 |0 |2.9 |97.1 |
|150,001-250,000 |3.1 |0 |3.1 |96.9 |
|Greater than 250,000 |2.5 |0 |2.5 |97.5 |
|Total |3.0 |0 |3.0 |97.1 |
|Less than 15,000 |5.4 |2.2 |3.2 |94.6 |
|15,001-20,000 |6.4 |2.8 |3.6 |93.6 |
|20,000-25,000 |6.1 |2.6 |3.5 |93.9 |
|Greater than 25,000 |6.2 |2.9 |3.3 |93.8 |
|Total |6.0 |2.6 |3.4 |94.0 |
a Unweighted means
Source: PRI-West Bengal data base: The World Bank (See Annex A).
Table 8
The Composition of Intergovernmental Transfers by Source: 2005a
|Population Size |Total Grants and |From Central Government |From State Government |
| |Transfers as a Percent of| | |
| |Revenue | | |
|Districts |94.3 |87.6 |6.7 |
|Blocks |96.0 |80.9 |15.6 |
|Gram Panchayats |93.8 |68.8 |24.9 |
|Total |94.0 |70.0 |24.0 |
a Unweighted means
b The data file contains a category of “other transfers.” This category includes “Other Continuing Education”, “transfers for the Village Education Committee”, and “Other development programs”. The file does not include these as separate data entries so they cannot be distributed between central and state transfers. They are therefore excluded from the entire analysis.
Source: PRI-West Bengal data set, World Bank (See Annex A)
Table 9
Percent Distribution of Central Transfers to Local Governments: 2005
| | |Schemes | | |
|Population Size |Total |SGRY |IAY |Other |Union Finance |MPLAD |
| | | | | |Commission | |
|Districts |
|Less than |100 |68.1 |21.3 |4.5 |4.9 |1.2 |
|2,500,000 | | | | | | |
|2,500,001-5,000,000|100 |48.1 |30.4 |12.3 |8.7 |0.6 |
|Greater than |100 |40.5 |19.2 |17.9 |21.2 |1.2 |
|5,000,000 | | | | | | |
|Average |100 |51.0 |25.6 |11.8 |10.7 |0.9 |
|Blocks |
|Less than 150,000 |100 |35.2 |0.9 |46.1 |13.0 |4.9 |
|150,001-250,000 |100 |36.9 |0.3 |46.3 |9.2 |7.3 |
|Greater than |100 |42.5 |0.0 |41.5 |12.4 |3.6 |
|250,000 | | | | | | |
|Average |100 |37.1 |0.5 |45.6 |10.9 |6.0 |
|Gram Panchayats |
|Less than 15,000 |100 |32.7 |40.4 |19.9 |6.8 |0.2 |
|15,001-20,000 |100 |32.9 |38.6 |20.4 |7.8 |0.3 |
|20,000-25,000 |100 |31.6 |40.9 |19.5 |7.8 |0.2 |
|Greater than 25,000|100 |31.2 |43.1 |18.3 |7.3 |0.02 |
|Average |100 |32.4 |40.2 |19.8 |7.5 |0.2 |
Source: PRI-West Bengal data set, World Bank (See Annex A)
Table 10
Percent Distribution of State Transfers to Local Governments: 2005
|Population Size |Total |Untied |Salary |State Finance |State Sponsored |BEUP |
| | | | |Commission |Schemes | |
|Districts |
|Less than |100 |27.4 |41.6 |0.0 |0.0 |15.3 |
|2,500,000 | | | | | | |
|2,500,001-5,000,000|100 |28.1 |61.1 |0.6 |0.5 |0.4 |
|Greater than |100 |13.1 |70.6 |0.0 |1.1 |1.2 |
|5,000,000 | | | | | | |
|Average |100 |24.4 |58.8 |0.3 |0.5 |4.1 |
|Blocks |
|Less than 150,000 |100 |1.3 |25.5 |0 |2.1 |46.0 |
|150,001-250,000 |100 |1.4 |20.7 |0 |1.8 |51.8 |
|Greater than |100 |3.7 |23.9 |0 |4.8 |44.0 |
|250,000 | | | | | | |
|Average |100 |1.7 |22.7 |0 |2.3 |48.9 |
|Gram Panchayats |
|Less than 15,000 |100 |0.8 |80.1 |0.2 |2.1 |1.3 |
|15,001-20,000 |100 |1.0 |78.8 |0.0 |2.6 |2.2 |
|20,000-25,000 |100 |0.9 |77.8 |0.01 |2.7 |2.4 |
|Greater than 25,000|100 |1.2 |77.4 |0.08 |1.9 |2.6 |
|Average |100 |0.9 |78.7 |0.07 |2.4 |2.0 |
Source: PRI-West Bengal data set, World Bank (See Annex A)
Table 11
Characteristics of Districts, Blocks, and Gram Panchayats: 2005
| |Districts |Blocks |Gram Panchayats |
|Indicator |Mean |Min |Max |
| |(N=17| | |
| |) | | |
| | |Gross State Product |For all levels of PRI |
|Uttar Dinajpur | |868.2 |419.49 | |
|Koch Bihar | |961.2 |725.88 | |
|Birbhum | |1028.4 |407.12 | |
|Purulia | |1036.1 |682.82 | |
|Murshidabad | |1073 |231.18 | |
|North Twenty Four |1094.1 |278.89 | |
|Dakshin Dinajpur | |1098.3 |430.48 | |
|Maldah | |1102.9 |273.18 | |
|Jalpaiguri | |1111.4 |676.64 | |
|Bankura | |1115.4 |403.63 | |
|South Twenty Four Parganas |1200.7 |292.26 | |
|Nadia | |1219.4 |255.98 | |
|Darjiling | |1449.2 |490.53 | |
|Hugli | |1472.2 |310.73 | |
|Haora | |1562.1 |231.7 | |
Note: The following districts are not included due to lack of gross state product data: Paschim Medinipur, Purba Medinipur, and Barddhaman
Table 13
Per Capita Expenditures by Population Size for Gram Panchayats: 2005
|Population Size |Per capita expendituresa |Minimum |Maximum |Coefficient of Variation |
| |(in Rs) | | | |
|Gram Panchayats |
|Less than 15,000 |183.6 |30.9 |1,423.3 |83.5 |
|15,001-20,000 |125.9 |19.3 |580.1 |59.8 |
|20,000-25,000 |117.1 |17.7 |538.2 |67.1 |
|Greater than 25,000 |102.8 |14.9 |373.1 |61.4 |
|Total N=2,961 |137.7 |14.9 |1,423.3 |78.2 |
a Unweighted mean
Source: PRI-West Bengal data set, World Bank (See Annex A)
Table 14
Per Capita Expenditures (Minus Salary Grant) by Population Size, 2005
|Population Size |Per capita expenditures |Minimum |Maximum |Coefficient of Variation |
| |excluding fixed costsa | | | |
| |(in Rs) | | | |
|Districts |
|Less than 2,500,000 |176.7 |103.9 |225.5 |29.2 |
|2,500,001-5,000,000 |169.7 |68.7 |288.3 |44.3 |
|Greater than 5,000,000 |103.7 |79.3 |116.7 |16.6 |
|Total N=17 |155.8 |68.7 |288.3 |42.0 |
|Blocks |
|Less than 150,000 |121.8 |14.6 |394.5 |62.7 |
|150,001-250,000 |83.0 |15.7 |349.6 |55.8 |
|Greater than 250,000 |70.4 |20.0 |178.3 |55.4 |
|Total N=288 |93.8 |14.6 |394.5 |64.2 |
|Gram Panchayats |
|Less than 15,000 |150.5 |11.0 |1,145.8 |92.0 |
|15,001-20,000 |105.2 |2.7 |559.4 |71.5 |
|20,000-25,000 |101.1 |5.7 |521.7 |77.5 |
|Greater than 25,000 |90.4 |7.3 |360.6 |69.4 |
|Total N=2,961 |115.4 |2.7 |1,145.8 |70.0 |
| |a Expenditures exclude reported |
| |salary grant. |
| |Source: PRI-West Bengal data set, |
| |World Bank (See Annex A) |
| | |
| | |
| | |
| | |
| |Table 15 |
| |OLS Estimation of the Determinants|
| |of Variations in Per Capita Total |
| |Expenditures |
| |of Gram Panchayats: 2005 |
| |(Log Per Capita Expenditures) |
| | |
| | |
| |Level of Government |
| | |
|Constant |9.96** |
| |(41.64) |
| | |
|Log Population |-0.432** |
| |(14.62) |
| | |
|Log Percent SC/ST |0.184** |
|Population |(13.7) |
| | |
|Log Literacy Rate |0.291** |
| |(5.50) |
| | |
|Log Percent of Agricultural |0.090** |
| |(7.81) |
|Labor | |
| | |
|R2 |0.81 |
|N |2,098 |
|a Coefficients on district and block dummy variables not reported. |
|* Significant at the 95% level or higher |
|** Significant at the 99% level or higher |
|Notes: |
|Significant District Effects: |
|Positive: Darjiling, Jalpaiguri, and Koch Bihar |
|Negative: Bankura, Birbhum, Haora, Pachim Medinipur, Purba Medinipur, Nadia, Purulia, North |
|Twenty-four Parganas, South Twenty-four Parganas, Dakshin Dinajpur |
| |
|The omitted district is Uttar Dinajpur. |
| |
|Seventy four of the 325 block dummy variables were significant (23 percent). This indicates |
|that they are important, indicating that there are differences in spending levels within |
|districts, even after we account for socio-economic characteristics included in Table 13. A |
|random block was omitted for each district. |
Table 16
OLS Estimation of the Determinants of Variations in Per Capita Total Expenditures (minus salary grants) of Gram Panchayats: 2005
(Log Per Capita Total Expenditures)
|Level of Government |Gram Panchayat |
| | |
|Constant |8.85** |
| |(30.63) |
| | |
| | |
|Population |-0.335** |
| |(13.22) |
| | |
| | |
|Percent SC/ST |0.240** |
|Population |(15.07) |
| | |
| | |
|Literacy Rate |0.282** |
| |(4.40) |
| | |
| | |
|Percent of Agricultural |0.042** |
| |(2.39) |
|Labor | |
| | |
| | |
|R2 |0.80 |
|N |2,079 |
|a Coefficients on district and block dummy variables not reported. |
|* Significant at the 95% level or higher |
|** Significant at the 99% level or higher |
| |
|Notes: |
|Significant District Effects: |
|Postive: : Darjiling, Jalpaiguri, and Koch Bihar |
|Negative: Bankura, Barddhaman, Birbhum, Haora, Hugli, Maldah, Paschim Medinipur, Purba |
|Medinipur, Nadia, Purulia, North Twenty Four Paraganas, South Twenty Four Parganas, and |
|Dakshim Dinajpur. |
| |
|The omitted district is Uttar Dinajpur. |
| |
|Sixty two of the 325 block dummy variables were significant (19 percent). This indicates that|
|they are important, indicating that there are differences in spending levels within districts,|
|even after we account for socio-economic characteristics included in Table 13a. A random |
|block was omitted for each district. |
.
Table 17
Per Capita Own Revenues for Gram Panchayats by Population Size: 2005
|Population Size |Per capita own source |Minimum |Maximum |Coefficient of Variation |
| |revenue (in Rs)a | | | |
|Gram Panchayats |
|Less than 15,000 |8.5 |0.0 |238.6 |146.0 |
|15,001-20,000 |8.0 |0.0 |190.2 |160.5 |
|20,000-25,000 |6.6 |0.02 |87.7 |116.5 |
|Greater than 25,000 |5.8 |0.05 |37.0 |101.0 |
|Total N=2,943 |7.6 |0.0 |238.6 |146.3 |
a 3 GPs report values of per capita own source revenues less than 0.001 and 4 report values greater than 100.
Source: PRI-West Bengal data set, World Bank (See Annex A)
Table 18
OLS Estimation of the Determinants of Variations in Per Capita Own Source Revenue of Gram Panchayats: 2005
(Log of dependent variable)
|Level of Government |Gram Panchayata |
| | |
|Constant |5.27** |
| |(6.28) |
| | |
|Log Population |-0.221** |
| |(2.97) |
| | |
|Log Percent SC/ST |0.090* |
|Population |(1.93) |
| | |
|Log Literacy Rate |0.924** |
| |(4.86) |
| | |
|Log Percent of Agricultural |-0.145** |
|Labor |(2.56) |
| | |
|R2 |0.55 |
|N |2,067 |
| | |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis.
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Bankura and Hugli
Negative effects: Birbhum, Darjiling, Haora, Purba Medinipur, Purulia
The omitted district is Uttar Dinajpur.
Significant Block Effects:
The block dummy variable is significant for 55 blocks—approximately 17 percent of the cases, split almost evenly between negative and positive coefficients. A random block was omitted for each district.
Table 19
OLS Estimation of the Determinants of Variations in Per Capita Own Source Revenue of Gram Panchayats: 2005
(Log of dependent variable)
|Level of Government |Gram Panchayata |
| | |
|Constant |2.091* |
| |(1.74) |
| | |
|Log Population |-0.080 |
| |(0.97) |
| | |
|Log Percent SC/ST |0.027 |
|Population |(0.54) |
| | |
|Log Literacy Rate |0.858** |
| |(4.50) |
| | |
|Log Percent of Agricultural |-0.164** |
|Labor |(3.15) |
| | |
|Log Per Capita Grants and Transfers |0.370* |
| |(3.70) |
|R2 |0.55 |
|N |2,067 |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive: Bankura, Barddhaman, Hugli
Negative: Birbham, Darjiling, Purba Medinipur, Purulia
The omitted district is Uttar Dinajpur.
Significant Block Effects:
The block dummy variable is significant in 22 percent of the cases (71 blocks). A random block was omitted for each district.
Table 20
Tax Effort, Gram Panchayats, 2005
|GP Name |Own Source revenue per capita |Estimated Own Source Revenue per|Tax Effort |
| | |capita | |
|Domahana |2.77 |4.47 |0.62 |
|Dutta Pulia |2.89 |4.25 |0.68 |
|Patharghata |15.03 |19.92 |0.75 |
|Haripur |2.12 |2.79 |0.76 |
|Chuprijhara |1.53 |1.83 |0.83 |
|Bansra |4.12 |4.77 |0.87 |
|Lalgarh |1.30 |1.46 |0.89 |
|Prusadpur |2.52 |2.22 |1.13 |
|Oldabari |8.49 |4.10 |2.07 |
|Kalia Chak |9.53 |2.39 |3.99 |
Source: Calculated from the PRI-West Bengal data base: The World Bank (see Annex A).
Table 21
OLS Estimation of the Determinants of Variations in Per Capita SGRY
of Gram Panchayats: 2005
(Log of dependent variable)
|Level of Government |Gram Panchayata |
| | |
|Constant |7.179** |
| |(14.96) |
| | |
| | |
|Log Population |-0.326** |
| |(7.59) |
| | |
| | |
|Log Percent SC/ST |0.377** |
|Population |(14.15) |
| | |
|Log Literacy Rate |0.264* |
| |(2.50) |
| | |
|Log Percent of Agricultural |0.029 |
|Labor |(1.31) |
| | |
|R2 |0.64 |
|N |2,066 |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Darjiling and Haora
Negative effects: Bankura, Barddhaman, Jalpaiguri, Koch Bihar, Paschim Medinipur, Nadia, North 24, South 24
The omitted district is Uttar Dinajpur.
Significant Block Effects:
The block dummy variable is significant for 38 blocks—approximately 12 percent of the cases. A random block was omitted for each district.
Table 22
OLS Estimation of the Determinants of Variations in Per Capita IAY
of Gram Panchayats: 2005
(Log of Dependent Variable)
|Level of Government |Gram Panchayat |
| | |
|Constant |-5.85** |
| |(10.61) |
|Log Population |-0.250** |
| |(5.07) |
|Log Percent SC/ST |0.322** |
|Population |(10.35) |
|Log Literacy Rate |0.285* |
| |(2.05) |
| | |
|Log Percent Agricultural Labor |0.132** |
| |(5.16) |
|R2 |0.65 |
|N |1,984 |
| | |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive: Darjiling, Jalpaiguru, Koch Bihar
Negative: Purulia
The omitted district is Uttar Dinajpur.
Significant Block Effects:
There are few significant block effects. Of 325 block dummies, only 10 were significant. A random block was omitted for each district.
Table 23
OLS Estimation of the Determinants of Variations in Per Capita Total Central Schemes
of Gram Panchayats: 2005
(Log of Dependent Variable)
|Level of Government |Gram Panchayata |
| | |
|Constant |8.405** |
| |(25.12) |
| | |
| | |
|Log Population |-0.287** |
| |(9.83) |
| | |
|Log Percent SC/ST |0.293** |
|Population |(15.87) |
| | |
|Log Literacy Rate |0.281** |
| |(3.85) |
| | |
|Log Percent Agricultural Labor |0.102** |
| |(6.67) |
| | |
| | |
|Log Percent Marginal Workers |-0.037* |
| |(1.79) |
|R2 |0.79 |
|N |2,097 |
| | |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Darjiling
Negative effects: Bankura, Barddhaman, Birbhum, Haora, Hugli, Maldah, alpaiguri, Koch Bihar, Paschim Medinipur, Pubra Medinipur, Nadia, North Twenty Four Parganas, South Twenty Four Parganas, Dakshin Dinajur
The omitted district is Uttar Dinajpur.
Significant Block Effects:
The block dummy variable is significant for only 12 blocks. A random block was omitted for each district.
Table 24
OLS Estimation of the Determinants of Variations in Per Capita State Transfers to Gram Panchayats: 2005
(Log of Dependent Variable)
|Level of Government |Gram Panchayata |
| | |
|Constant |11.46** |
| |(34.30) |
| | |
|Log Population |-0.820** |
| |(27.26) |
| | |
|Log Percent SC/ST |0.018 |
| |(0.93) |
| | |
|Log Literacy Rate |0.141* |
| |(1.76) |
| | |
|Log Percent Agricultural Labor |0.050** |
| |(3.42) |
| | |
|R2 |0.61 |
|N |2,022 |
| | |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Barddhaman and Hugli
Negative effects: Paschim Medinipur and South Twenty Four Parganas
The omitted district is Uttar Dinajpur.
Significant Block Effects:
The block dummy variable is significant for 58 of the block dummy variables—18 percent of all block effects. A random block was omitted for each district.
Table 25
OLS Estimation of the Determinants of Variations in Per Capita Total Grants and Transfers of Gram Panchayats: 2005
(Log of Dependent Variable)
| | |
|Level of Government |Gram Panchayata |
|Constant | |
| |9.21** |
| |(38.31) |
| | |
|Log Population |-0.452** |
| |(20.90) |
| | |
|Log Percent SC/ST |0.195** |
| |(14.30) |
| | |
|Log Literacy Rate |0.271** |
| |(4.72) |
| | |
|Log Percent Agricultural Labor |0.087** |
| |(7.93) |
|R2 |0.82 |
|N |2,022 |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Darjiling, Jalpaiaguri, Kock Bihar, Maldah, and Purulia
Negative effects: Bankura, Birbhum, Paschim Medinipur, and Nadia
The omitted district is Uttar Dinajpur.
Significant Block Effects:
Among the block effects, we find 71 significant coefficients—about 22 percent of the total block dummy variables. A random block was omitted for each district.
Table 26
Indicators of Financial Condition for Gram Panchayats: 2003-2005
| |2003 |2004 |2005 |
|Gram Panchayats |
|Number of GPs with an overall |1,494 |1,334 |1,501 |
|deficit (not including opening | | | |
|balance) | | | |
|Number of GPs with an overall |1,491 |1,703 |1,510 |
|surplus (not including opening | | | |
|balance) | | | |
|Total surplus (not including |12.0 |14.0 |13.0 |
|opening balance) as a percent of | | | |
|total revenue for surplus GPs | | | |
|Total Deficit (not including |15.0 |13.6 |11.5 |
|opening balance) as a percent of | | | |
|total revenue for deficit GPs | | | |
|Closing balance as a percent of |21.8 |28.3 |23.5 |
|total expenditures ALL | | | |
|Closing balance as a percent of |19.5 |26.1 |21.5 |
|grants and transfers ALL | | | |
|Number of GPs with closing balance |428 |242 |363 |
|equal -5 percent to +5 percent of | | | |
|total expenditures | | | |
|N |2,985 |3,038 |3,012 |
a Eliminating one outliers, this is 72.3 for closing balance and 83.4 for deficit/total revenue
Source: PRI-West Bengal data base, World Bank (See Annex A)
Table 27
Gram Panchayats with Chronic Current Account
Surplus or Deficit
| |Number |Number with Deficit Greater than Opening Balance |Average Per Capita Expenditures in |
| | | |2005 |
| | |2003 |2004 |2005 | |
|Deficit for all 3 |199 |5 |3 |4 |129.0 |
|Years | | | | | |
|Deficit for 2 Years |1,209 |31 |20 |17 |134.0 |
|Deficit for 1 Year |1,313 |23 |17 |7 |141.3 |
|Only | | | | | |
|Surplus for all 3 |257 | | | |97.7 |
|Years | | | | | |
|Surplus for 2 Years |1,313 | | | |141.3 |
|Surplus for 1 Year |1,209 | | | |134.0 |
|Only | | | | | |
Source: PRI-West Bengal data base, World Bank (See Annex A).
Table 28
Ratio of Current Account Deficit
to Opening Balance: 2005
Number of Gram Panchayats
More than 100 percent 27
50-100 percent 608
25-50 percent 483
0-25 percent 383
Source: PRI-West Bengal data base, World Bank (See Annex A)
Table 29
Probit Analysis
Gram Panchayat Deficits
|Variable |Chronic Deficit GPs (2005)a |Deficit GPs (2005) |
|Constant |-1.41** |-0.118* |
| |(13.61) |(1.85) |
|Opening Balance per capita |-0.011** |0.016** |
| |(3.73) |(11.82) |
|Percent SC/ST population |0.368* |-0.718** |
| |(1.69) |(4.45) |
|Own Source Revenue per capita |-0.006 |-0.011** |
| |(1.06) |(3.85) |
|N |2,098 |2,095 |
|Likelihood ratio |22.8 |184 |
a Chronic deficit GPs are defined as those with deficits for each year, 2003, 2004, and 2005 (199 GPs).
Source: PRI-West Bengal data base, World Bank (see Annex A).
Table 30
OLS Estimation of the Determinants of Variations in Per Capita Deficitsb
of Gram Panchayat Governments: 2005
(Log Dependent Variable)
|Level of Government |Gram Panchayata |
| | |
|Constant |-0.003 |
| |(0.01) |
| | |
|Log Population |-0.171 |
| |(1.17) |
| | |
|Log Percent SC/ST |0.129 |
|Population |(1.43) |
| | |
|Log Opening balance |1.51** |
| |(18.8) |
| | |
|Log Central Sponsored Schemes Per |-0.172* |
|Capita |(1.95) |
|R2 |0.55 |
|N |996 |
| | |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
b Deficits expressed as positive numbers.
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Darjiling and Koch Biharrddhaman and Hugli
Negative effects: Paschim Medinipur and South Twenty Four Parganas
The omitted district is Uttar Dinajpur.
Significant Block Effects:
The block dummy variable is significant for just 16 of the block dummy variables out of a total of 325 block dummy variables. A random block was omitted for each district.
Table 31
Per Capita Expenditures by Population Size for Districts and Blocks: 2005
|Population Size |Per capita expendituresa |Minimum |Maximum |Coefficient of Variation |
| |(in Rs) | | | |
|Districts |
|Less than 2,500,000 |176.7 |103.9 |225.5 |29.2 |
|2,500,001-5,000,000 |169.7 |68.7 |288.3 |44.3 |
|Greater than 5,000,000|103.7 |79.3 |116.7 |16.6 |
|Total N=17 |155.8 |68.7 |288.3 |42.0 |
|Blocks |
|Less than 150,000 |123.1 |14.7 |396.3 |62.7 |
|150,001-250,000 |84.0 |16.3 |349.9 |55.8 |
|Greater than 250,000 |71.1 |20.5 |177.0 |55.4 |
|Total N=288 |94.8 |14.7 |396.3 |64.2 |
a Unweighted mean
Source: PRI-West Bengal data set, World Bank (See Annex A).
Table 32
OLS Estimation of the Determinants of Variations in Per Capita Total Expenditures
of Districts and Blocks: 2005
(Log Per Capita Total Expenditures)
|Level of Government |Blocka |District |
| | | |
|Constant |8.07** |9.24** |
| |(7.52) |(3.96) |
| | | |
|Log Population |-0.309** |-0.227 |
| |(3.59) |(1.42) |
| | | |
|Log Percent SC/ST |0.158** |0.695** |
|Population |(2.81) |(3.73) |
| | | |
| | | |
|R2 |0.50 |0.63 |
|N |288 |17 |
|a Coefficients on district and block dummy variables not reported. | |
|* Significant at the 95% level or higher | |
|** Significant at the 99% level or higher | |
| | |
|Notes: For the block regression, positive, significant district effects are found for the | |
|following districts: Koch Bihar, Purulia, and Paschim Meninipur. | |
| | |
|The omitted district is Uttar Dinajpur. | |
Table 32a
OLS Estimation of the Determinants of Variations in Per Capita Total Expenditures (minus salary grants)
of Blocks and Districts: 2005
(Log Per Capita Total Expenditures)
|Level of Government |Blocka |District |
| | | |
|Constant |7.89** |9.13** |
| |(7.14) |(4.13) |
| | | |
|Log Population |-0.295** |-0.221 |
| |(3.32) |(1.41) |
| | | |
|Log Percent SC/ST |0.166** |0.722** |
|Population |(2.88) |(4.00) |
| | | |
| | | |
|R2 |0.48 |0.63 |
|N |288 |17 |
|a Coefficients on district and block dummy variables not reported | |
|* Significant at the 95% level or higher | |
|** Significant at the 99% level or higher | |
| | |
|Notes: For the block regression, positive, significant district effects are found for the | |
|following districts: Koch Bihar, Purulia, and Paschim Meninipur. | |
| | |
|The omitted district is Uttar Dinajpur. | |
Table 33
Per Capita Own Revenues for Districts and Blocks by Population Size: 2005
|Population Size |Per capita own source |Minimum |Maximum |Coefficient of Variation |
| |revenue (in Rs) | | | |
|Districts |
|Less than 2,500,000 |5.1 |0.62 |16.6 |150.1 |
|2,500,001-5,000,000 |4.6 |1.80 |8.1 |53.3 |
|Greater than 5,000,000 |7.2 |2.73 |15.0 |77.8 |
|Total N=17 |5.3 |0.62 |16.6 |86.0 |
|Blocks |
|Less than 150,000 |3.7 |0.1 |32.3 |165.2 |
|150,001-250,000 |2.7 |0.1 |39.8 |153.2 |
|Greater than 250,000 |1.5 |0.02 |6.1 |96.3 |
|Total N=288 |2.7 |0.02 |39.8 |160.0 |
Notes: 3 GPs report values of OSRPC less than 0.001 and 4 report values greater than 100.
Source: PRI-West Bengal data set, World Bank (See Annex A).
Table 34
OLS Estimation of the Determinants of Variations in Per Capita Own Source Revenue of Blocks: 2005
(Log of dependent variable)
|Level of Government |Blocka |
| | |
|Constant |1.33 |
| |(0.40) |
| | |
|Log Population |-0.116 |
| |(0.43) |
| | |
|Log Percent SC/ST |-0.102 |
| |(0.61) |
| | |
|R2 |0.12 |
|N |277 |
| | |
a Coefficients on district dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Barddhaman
The omitted district is Uttar Dinajpur.
Table 35
OLS Estimation of the Determinants of Variations in Per Capita Own Source Revenue of Districts and Blocks: 2005
(Log of dependent variable)
|Level of Government |Blocka |District |
| | | |
|Constant |-2.13 |-8.50 |
| |(0.60) |(1.02) |
| | | |
|Log Population |0.149 |0.396 |
| |(0.52) |(0.76) |
| | | |
|Log Percent SC/ST |-0.097 |-1.097* |
|Population |(0.54) |(1.79) |
| | | |
|Log Per Capita Grants and Transfers |0.339** |1.419* |
| | |(1.93) |
| |(3.61) | |
|R2 |0.14 |0.11 |
|N |277 |17 |
a Coefficients on district dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive: Barddhaman
The omitted district is Uttar Dinajpur.
Table 36
OLS Estimation of the Determinants of Variations in Per Capita SGRY
of Districts and Blocks: 2005
(Log of dependent variable)
|Level of Government |Blocka |District |
| | | |
|Constant |6.05** |-48.39* |
| | |(1.92) |
| |(17.28) | |
| | | |
|Log Population |-0.218** |-0.415 |
| |(6.44) |(0.81) |
| | | |
|Log Percent SC/ST |0.424** |2.37** |
|Population |(23.76) |(3.36) |
| | | |
|Log Literacy Rate |0.195* |-5.84** |
| |(2.06) |(3.07) |
| | | |
|Log Per Capita GSP | |6.14* |
| | |(2.81) |
|R2 |0.60 |0.69 |
|N |266 |15 |
| | | |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Bankura, Jalpaiguri, Koch Bihar, and Purulia
Negative effects: Murshidabad
The omitted district is Uttar Dinajpur.
Table 37
OLS Estimation of the Determinants of Variations in Per Capita IAY
Of Blocks and Districts: 2005
(Log of Dependent Variable)
|Level of Government |Blocka |District |
| | | |
|Constant |23.44 |-12.00 |
| |(1.05) | |
| | |(1.55) |
| | | |
|Log Population |-2.49 |0.839** |
| |(1.55) | |
| | |(2.39) |
| | | |
|Log Percent SC/ST |0.383 |2.07** |
|Population |(0.47) | |
| | |(4.26) |
| | | |
|Log Literacy Rate |-2.47 |-4.63** |
| |(0.65) | |
| | |(3.09) |
| | | |
|Log Per Capita GDP | |3.25** |
| | |(2.74) |
|R2 |0.40 |0.59 |
|N |229 |14 |
| | | |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive: Barddhaman
The omitted district is Uttar Dinajpur.
Table 38
OLS Estimation of the Determinants of Variations in Per Capita Total Central Schemes
of Districts and Blocks: 2005
(Log of Dependent Variable)
|Level of Government |Blocka |District |
| | | |
|Constant |10.118* |15.59** |
| |(4.76 |(3.14) |
| | | |
| | | |
|Log Population |-0.509** |0.069 |
| |(3.09) |(0.35) |
| | | |
| | | |
|Log Percent SC/ST |0.381** |1.564** |
|Population |(3.55) |(5.73) |
| | | |
| | | |
|Log Literacy Rate |-0.347 |-2.24** |
| |(0.76) |(3.07) |
| | | |
| | | |
|Log Per Capita GDP | |1.75* |
| | |(2.06) |
|R2 |0.35 |0.81 |
|N |288 |15 |
| | | |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Darjiling
The omitted district is Uttar Dinajpur.
Table 39
OLS Estimation of the Determinants of Variations in Per Capita State Transfers to Districts and Blocks: 2005
(Log of Dependent Variable)
|Level of Government |Blocka |District |
| | | |
|Constant |3.873 |14.36* |
| |(1.33) |(1.07) |
| | | |
|Log Population |-0.181 | |
| |(1.53) | |
| | | |
|Log Percent SC/ST |0.067 |-0.257 |
| |(0.87) |(0.92) |
| | | |
|Log Literacy Rate |0.189 |1.92* |
| |(0.57) |(2.39) |
| | | |
|Log Percent Female Population |-2.80 |35.96* |
| |(0.86) |(2.15) |
| | |-2.42* |
|Log Per Capita GSP | |(2.70) |
|R2 |0.27 |0.43 |
|N |288 |15 |
| | | |
a Coefficients on district and block dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Bankura, Barddhaman, Paschin Medinipur, and Purulia
The omitted district is Uttar Dinajpur.
Table 40
OLS Estimation of the Determinants of Variations in Per Capita Total Grants and Transfers of Districts and Blocks: 2005
(Log of Dependent Variable)
| | | |
|Level of Government |Blocka |District |
| | | |
|Constant |8.15** |7.508** |
| |(6.97) |(2.97) |
| | | |
|Log Population |-0.327** |-0.113 |
| |(3.46) |(0.65) |
| | | |
| | | |
|Log Percent SC/ST |0.177** |0.775** |
|Population |(2.98) |(3.92) |
| | | |
|Log Literacy Rate |-0.154 | |
| |(.56) | |
| | | |
|R2 |0.48 |0.61 |
|N |281 |15 |
a Coefficients on district dummy variables not reported; t-statistics in parenthesis
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Positive effects: Koch Bihar, Paschim Medinipur, and Purulia
The omitted district is Uttar Dinajpur.
Table 41
Indicators of Financial Condition for Districts and Blocks: 2003-2005
| |2003 |2004 |2005 |
|Districts |
|Number of districts with an overall|15 |13 |14 |
|deficit (not including opening | | | |
|balance) | | | |
|Number of districts with an overall|2 |5 |3 |
|surplus (not including opening | | | |
|balance) | | | |
|Total surplus (not including |11.6 |21.7 |13.4 |
|opening balance) as a percent of | | | |
|total revenue for surplus districts| | | |
|Total Deficit (not including |103.7a |36.7 |16.2 |
|opening balance) as a percent of | | | |
|total revenue for deficit districts| | | |
|Closing balance as a percent of |67.4 |74.9 |47.0 |
|total expenditures ALL | | | |
|Closing balance as a percent of |130.0a |83.9 |52.0 |
|grants and transfers ALL | | | |
|Number of districts with closing |1 |1 |1 |
|balance equal -5 percent to +5 | | | |
|percent of total expenditures | | | |
|N |17 |17 |17 |
|Blocks |
|Number of blocks with an overall |166 |192 |123 |
|deficit (not including opening | | | |
|balance) | | | |
|Number of blocks with an overall |110 |89 |155 |
|surplus (not including opening | | | |
|balance) | | | |
|Total surplus (not including |17.6 |15.3 |16.9 |
|opening balance) as a percent of | | | |
|total revenue for surplus blocks | | | |
|Total Deficit (not including |35.7 |37.4 |22.4 |
|opening balance) as a percent of | | | |
|total revenue for deficit blocks | | | |
|Closing balance as a percent of |76.2 |74.7 |69.3 |
|total expenditures ALL | | | |
|Closing balance as a percent of |80.8 |83.0 |66.6 |
|grants and transfers ALL | | | |
|Number of blocks with closing |1 |3 |1 |
|balance equal -5 percent to +5 | | | |
|percent of total expenditures | | | |
|N |276 |281 |278 |
a Eliminating one outliers, this is 72.3 for closing balance and 83.4 for deficit/total revenue
Source: PRI-West Bengal data base, World Bank (See Annex A).
Table 42
OLS Estimation of the Determinants of Variations in Per Capita Deficitsa
of Districts and Blocks: 2005
(Log Dependent Variable)
|Level of Government |Block |District |
| | | |
|Constant |-1.27 |12.90 |
| |(0.32) |(0.67) |
| | | |
|Log Population |0.100 |-0.801 |
| |(0.36) |(0.81) |
| | | |
|Log Percent SC/ST |0.398 |1.015 |
|Population |(1.37) |(0.77) |
| | | |
|Log Opening balance |0.567** |1.672* |
| |(2.97) |(1.88) |
| | | |
|Log Central Sponsored Schemes Per |0.120 |-0.922 |
|Capita |(1.38 |(0.71) |
|R2 |0.38 |0.18 |
|N |123 |13 |
| | | |
a Deficits expressed as positive numbers
* Significant at the 95% level or higher, ** Significant at the 99% level or higher
Notes:
Significant District Effects:
Negative effects: Jalpaiguri
The omitted district is Uttar Dinajpur.
Table 43
Reform Options: Alternative Expenditure Levels
(Amounts in Rs)
| |Three times current per capita |Two times current per capita |
| |expenditures |expenditures |
|1. Present spending levela |7,909,652,530 |7,909,652,530 |
|2. Proposed spending level |23,728,957,590 |15,819,305,060 |
|3. Increase |15,819,305,060 |7,909,652,530 |
|4. Present State Fundingb |1,451,315,982 |1,451,315,982 |
|5. Required Total State Funding |17,270,621,042 |9,360,968,512 |
|6. Required Increase |15,819,305,060 |7,909,652,530 |
|7. Required State Funding as a Percent of State Own|10.59% |5.74% |
|Revenue | | |
a Calculated for all gram panchayats system using the mean per capita expenditure for gram panchayats in the PRI-West Bengal data base, World Bank (see Annex A) times the total gram panchayat population (57,734,690). The data base contains data for 3,074 gram panchayats for 2005. This accounts for approximately 92 percent of gram panchayats by population base or by number of gram panchayats.
b Based on the amount of state sponsored schemes to gram panchayats and state grants to gram panchayats from the PRI-West Bengal data base, World Bank, increased by 8 percent to reflect the total of all state aid to all gram panchayats in West Bengal.
Table 44
Distribution of Per Capita Receipts from State Grants
Under A Minimum Expenditure Proposals
| | Number of Gram |Panchayats |
|Percent Gain in state aid as a share of |ThreeTimes Current |Two Times Current Per Capita Expenditures |
|current plus additional state aid |Per Capita Expenditures | |
|0-75 |249 |385 |
|75-80 |54 |221 |
|80-90 |604 |1,405 |
|90-93 |850 |568 |
|93-95 |726 |196 |
|Greater than 95 |591 |299 |
|Total number of GPs |3,074 |3,074 |
Source: PRI-West Bengal data base, World Bank (See Annex A).
Table 45
Selected Coefficients of Correlation
|Variable |Per Capita State Grants in 2005 |Per Capita Grants Under the Proposed |
| | |Minimum Expenditure System |
|Percent SC/ST population |0.065 |-0.004 |
|Literacy Rate |0.113** |0.039 |
|Percent agricultural workers |-0.003 |-0.132** |
|Percent marginal workers |0.183** |0.039 |
|Own source revenue per capita |0.133* |0.111* |
Source: PRI-West Bengal data set, World Bank (See Annex A).
* Significant at the 95% level, ** significant at the 99% level.
Table 46
Distribution of Per Capita Receipts from State Grants
Under A Formula Proposal
|Percent Increase in |Number of GPs |
|State Aid | |
|0-50 |456 |
|50-60 |595 |
|60-65 |335 |
|65-70 |308 |
|70-80 |332 |
|Greater than 80 |72 |
|Total number of GPs |2,098 |
Source: PRI-West Bengal data set, World Bank (See Annex A)
Table 47
Impacts of the General Fund and Revenue Mobilization Components
Under a Formula Proposal
|GP Population Size Class |Number of GPs |Mean Per Capita Amount Received |Mean Per Capita Amount Received |
| | |from General Fund |from Revenue Mobilization |
|0-15,000 |617 |112.2 |69.3 |
|15,000-20,000 |760 |104.6 |36.1 |
|20,000-25,000 |475 |105.4 |20.7 |
|Greater than 25,000 |246 |105.1 |13.7 |
|Total |2,098 |107.0 |40.0 |
Source: PRI-West Bengal data set, World Bank (See Annex A)
Table 48
Selected Coefficients of Correlation
|Variable |Per Capita State Grants (current system) |Per Capita Grants (proposed system |
| | |including general and revenue mobilization |
| | |components and 2X minimum expenditure |
| | |guarantee) |
|Percent SC/ST population |0.065 |-0.005 |
|Literacy Rate |0.113** |0.015 |
|Percent agricultural workers |-0.003 |-0.040* |
|Percent marginal workers |0.183** |0.081** |
|Own source revenue per capita |0.133* |0.412** |
|Population |-0.505** |-0.263** |
Source: PRI-West Bengal data set, World Bank (See Annex A).
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-----------------------
[1] Article 40 of the Constitution directs states to endow village panchayats with such powers as necessary to function as units of self government. This is reaffirmed in the 73rd amendment to the constitution (1992), which defines the governance of the PRIs, and calls for the assignment of expenditure responsibilities and taxing powers to them.
[2] See, for example, SRD (undated).
[3] The “amenity” data include measures of community infrastructure -- such as school capacity, miles of permanent roads, street lighting -- and measures of community development such as the presence of commercial banks or telecommunication services. For an example of how these data may be used, see the Karnataka and Kerala case studies in Sethi, ed. (2004).
[4] The State Finance Commissions are required to sit once in every five year period.
[5] An exception is that local governments may hire employees on a contract or a daily wage basis, without permission from up-level governments.
[6] This “discretion” is perhaps overstated. As is discussed below, the rates and bases of these local taxes are prescribed by the State government.
[7] The 73rd Amendment made provision for the appointment of the State Finance Commissions.
[8] The West Bengal State Second Finance Commission submitted their report to the government on February 6, 2002. The corresponding ‘Action Taken Report’ was filed by the State Government on 15th July 2005 before the State legislation.
[9] In fact, one could make the argument that very few of the SFCs have had a favorable impact on the finances of PRIs. A good review of the recommendations and results of the State Finance Commissions is in Subrahmanyam (2004). Also see Oommen (2006), and Rao and Singh (2006).
[10] The same problem has been emphasized in a number of other SFC reports. Subrahmanyam, 2004, notes (section 1.4.3) that “ Absence of district/microlevel data on panchayat finances on which the State-level data would be based could lead to the conclusion that the statistical particulars furnished by the States to the Central Finance Commission are nothing short of a kind of ‘guestimates’ ”.
[11] All population data in this report are drawn from the 2001 Census.
[12] These estimates of per capita expenditures in 2005 are based on 2005 fiscal data and 2001 population data, hence are an overestimate.
[13] Note that these samples are less than 100 percent coverage because of missing data for some districts, blocks, and gram panchayats. These missing units are small enough, however, that we do not believe that their inclusion would markedly change the results shown in Table 1.
[14] An interesting comparison is Karnataka where Rao, et. al. (2004), estimate that gram panchayats accounted for only about 5 percent of total PRI spending in 2003.
[15] An interesting comparison is Karnataka where Rao, et. al. (2004), estimate that gram panchayats accounted for only about 5 percent of total PRI spending in 2003.
[16] Capital expenses are defined in the data base as follows: “Any expenditure resulting in the creation of physical assets like land, buildings, machinery and equipment is regarded as capital expenditure. This includes centrally sponsored schemes, state sponsored schemes and other schemes/welfare programs which involve capital expenditure.” (See Annex A.)
[17] Of the 3,354 gram panchayats in West Bengal, fiscal data are reported in this study for 3,016. However, population data are available for only 2,973. Our maximum sample size, when using population data, is 86 percent of the total number of gram panchayats.
[18] A somewhat surprising result revealed in this table is that the expenditures on the housing programs (IAY) exceed the expenditures on employment generation programs (SGRY) for all population groupings of gram panchayats. Further investigation shows that this is not the case for 2003 nor for 2004 -- in both of those years, employment generation program expenditures are larger than housing program expenditures.
[19] Annual rental value is defined to be the equivalent of 6 percent of market value.
[20] Rao, et. al. (2004) reports about the same level for Karnataka.
[21] Rao, et. al. (2004), estimate a 69 percent collection rate in Karnataka in 2003, but noted that this is against a base that has not been revised in 30 years.
[22] Actually, only 95 percent of the full entitlement is allocated in this way. The Ministry retains 5 percent to allocate to areas of acute distress arising out of extraordinary seasonal conditions.
[23] After 2004, the allocation to each gram panchayat was made in proportion to their previous year’s allocation.
[24] The program benefits have been extended to the families of ex-servicemen killed in action, and to physically and mentally challenged persons.
[25] The state matching share for the CSS is not included in the state transfer category reported in Table 9.
[26] This is because salaries comprise an important share of the gram panchayats budget, and these are financed by the salary grant.
[27] See, for example, State Finance Commission (2002).
[28] All means are unweighted.
[29] The coefficient of variation is the standard deviation as a percent of the mean, hence it is a measure of relative variation. By this measure, for example, there is more variation across districts in the percent of SC/ST population than there is variation in the literacy rate.
[30] The simple correlation between the literacy rate and per capita own source revenue is positive and highly significant (see Annex B).
[31] The simple correlation between the literacy rate and the percent of SC/ST population is negative and highly significant (See Annex Table B-3).
[32] A ‘marginal worker’ is one who has not worked in the past six months.
[33] A regression analysis on gram panchayats in Kerala also found a significant negative relationship with population size (Oommen, et. al., 2004).
[34] Data on the share of workers in the agricultural sector are available for gram panchayats but not for districts or blocks.
[35] The alternate poverty measure, the percent of females in the population, was not significant, so was dropped from the regression.
[36] The simple correlation between population size and per capita own source revenue is negative, but not significant, as is shown in Annex B.
[37] The dependent variable, per capita deficit (measured in rupees) is expressed as a positive number.
[38] The analysis in Table 32 was repeated with the dependent variable expressed net of salary grants. The results were little different (See Table 32a).
[39] To test whether this is due solely to a fixed cost effect, we reduced the dependent variable by the size of the salary grant. There was very little change from the results (See Table 32).
[40] We use the pro forma in Box 3 to measure the deficit.
[41] One research report estimates that the next (sixth) pay commission has the potential to create more stress on state budgets than did the fifth pay commission. Crisil (2006) estimates an impact of as much as 3 percent of state GSP by 2011, an amount that is well above the 2.6 of the previous commission and above the 1 percent targeted by the Twelfth Finance commission.
[42] We do not consider the alternative of replacing centrally sponsored schemes with state assistance programs. For a discussion, see Rajamaram (2001).
[43] The general purpose grants that they receive -- untied grants and State Finance Commission grants -- accounted for less than one percent of their revenue in the years studied for this report.
[44] For a discussion of this aspect of service delivery by rural local governments in South Africa, see Schroeder (2003).
[45] For a review of the available evidence, see Fox and Gurley (2006).
[46] It also may suggest changes in the political structure that are beyond the reach of the state government.
[47] This vagueness in the assignment of expenditure responsibility is a problem throughout India. For a discussion, see Subrahmanyam and Annamaloi (2004, p. 223-224).
[48] The vertical sharing dimension of such a grant system is discussed in detail in Bahl and Wallace (2007).
[49] Analogous reforms should be put in place for user charges, licenses, and fees.
[50] See for example, the practice in Kerala as described in Subrahmanyam and Annamalai, 2004.
[51] For a discussion of the rationale for this sequencing, see Bahl and Martinez-Vazquez (2006).
[52] To be fair, it almost certainly was the case that neither SFC had the resources or the data to do this expenditure requirements analysis.
[53] Expenditure assignments for various tiers of PRI under the present system are laid out in detail in Government of West Bengal (2005).
[54] There are several reasons why a government might want to transition to a new formula system rather than do it in one “reform” year. The transition period gives the opportunity to set up a system of hold-harmless where no local government receives less than under the previous system, and none receives too large an increment. This minimizes the shock associated with the new system and gives some time for preparing to absorb the phase-in of the new system where the distributive shares will change.
[55] See also the discussion in Singh and Srnivasan (2006, p. 349).
[56] SC/ST population is the most limiting factor in terms of data availability.
[57] The revenue potential of urban local bodies in India is significant, and they are less prominent in public financing than is the case in many large countries. For a review of the fiscal performance and potential of selected urban local bodies, see World Bank (2004). For a discussion about organizing a fiscal package for urban local bodies, see Mathur (2001, Chapter 5).
[58] For a discussion of urban government financial condition in India, see Mathur (2006).
[59] This is based on data from the India Economic Survey, 2004-05 that lists West Bengal state domestic product at Rs173,674 crore (, Table 17).
[60] An interesting case is Russia, where there was a significant “offloading” of expenditure responsibilities by the federal government. These responsibilities included capital investment, social welfare, and price subsidies for social goods. The funding for the offloading was to be a combination of privatization and subnational government budgets (Martinez-Vazquez, Timofeev, and Boex, 2006, chapter 4).
-----------------------
• 3,324 Gram Panchayats
• 341 Samitis
• 6 Municipal corporations
• 117 Municipalitiesb
• 18 Districts
State Government
Urban (28)a
Rural (72)a
71483
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