Introduction
A major area of concern for sustaining the real gross domestic product (GDP) growth in India has been lack of adequate infrastructure, which can support the growth process. Realizing this, Government of India as well as the State Governments has ventured into making heavy investment in infrastructure especially from the First Five-Year Plan onwards. The major focus of infrastructural investment has been on irrigation, transportation, electric power, agricultural markets, etc between different regions as well as in terms of agricultural growth. On the verge of 12th Five Year Plan (will commence in 2012-13), it is necessary to look into the performances across the states as well as the country as a whole.
1. Understanding of Infrastructure
1.1 Definition and Categorization
Infrastructure is the services and utilities derived from the set of public works that normally has been produced and maintained by the public sector, even if it may be produced in the private sector. Water supply, electricity, sanitation, transportation, telecommunications, irrigation dams, regulated markets and banks are some of the examples of infrastructure for public consumption and use. The agricultural infrastructure includes all of the basic services, facilities, equipment, and institutions needed for the economic growth and efficient functioning of the food and fiber markets. As far as nature of infrastructure is concerned, there are different kinds of infrastructure such as economic infrastructure, social infrastructure, agricultural infrastructure, financial infrastructure, technological infrastructure etc. defined in broader terms. But this classification does not signify that each dominates at the cost of others, rather they are complementary to each other and are indispensable and connected part of economic development. Economic theory argues that benefits derived from all these kinds of infrastructure jointly are greater than that of the sum of benefits from each category of individual infrastructure. In other words, the net benefit of providing diverse kinds of essential infrastructure together tend to generate more amount of net benefits than that of providing a single infrastructural facility.
1.2 Importance of Infrastructure
The strong positive correlation between the level of infrastructure and the economic development has been a well-established fact in the concurrent economics literature. In Keynesian macroeconomic model, the income or the output in the economy originates from the level of investment made in the economy. It should be noted that out of all the four factors contributing to income of a nation namely, government expenditure, consumption expenditure, investment expenditure and net income from abroad, income from investment comes both from investment expenditure especially by private individuals as well as from government spending. In spite of the income in the Keynesian model refers to short-term income, usually measured on annual basis, the investment made also comprise long-term investment such as investment in basic infrastructural facilities. Since the model is based on the notion that there is a direct positive relationship between income and the investment, investment in infrastructure is economically reasonable.
2. Regional Disparity in Absolute and Relative Economic Terms
There are 29 states and 6 Union territories in the country (considering Delhi as a state). Disparities in various socio-economical factors can be observed among the states. Geographic location, natural resources, existing infrastructure, political environment as well as degree of economic reform are the rationale behind widely varied per capita SDP across states.
Table1.State Domestic Product at current price (New-series) (Rs. Cr.) |
State | Mar-07 | Mar-08 | Annual Growth | Per Capita (Rs.)(Adjusted for Inflation) |
Jammu & Kashmir | 29030 | 31793 | 9.52% | 20604 |
Himachal Pradesh | 22843 | 24800 | 8.57% | 38378 |
Punjab | 121209 | 144309 | 19.06% | 38859 |
Haryana | 130236 | 154231 | 18.42% | 48456 |
Uttar Pradesh | 309834 | 344346 | 11.14% | 14083 |
Rajasthan | 153344 | 176420 | 15.05% | 22350 |
Delhi | 125282 | 143911 | 14.87% | 65156 |
Uttarakhand | 31380 | 35592 | 13.42% | 28671 |
Bihar | 99579 | 114616 | 15.10% | 11416 |
Orissa | 95065 | 119066 | 25.25% | 22287 |
West Bengal | 264542 | 307895 | 16.39% | 27062 |
Assam | 64429 | 71625 | 11.17% | 18877 |
Meghalaya | 7330 | 8472 | 15.58% | 25349 |
Tripura | 10322 | 10821 | 4.84% | 24034 |
Mizoram | 2996 | 3305 | 10.33% | 23174 |
Manipur | 5403 | 5848 | 8.24% | 18347 |
Nagaland | 5978 | 6470 | 8.23% | 18490 |
Arunachal Pradesh | 3413 | 3888 | 13.93% | 25110 |
Sikkim | 2039 | 2298 | 12.72% | 29506 |
Jharkhand | 63229 | 69253 | 9.53% | 17956 |
Gujarat | 262723 | 306813 | 16.78% | 40004 |
Maharashtra | 508836 | 590995 | 16.15% | 40614 |
Goa | 15248 | 17215 | 12.89% | 70329 |
Madhya Pradesh | 133073 | 149840 | 12.60% | 16963 |
Chhattisgarh | 64706 | 79419 | 22.74% | 24522 |
Andhra Pradesh | 277286 | 326547 | 17.77% | 31533 |
Karnataka | 205852 | 238348 | 15.79% | 31305 |
Kerala | 145009 | 165722 | 14.28% | 39815 |
Tamil Nadu | 276917 | 304989 | 10.14% | 34417 |
Figure 1: Inflation Adjusted Per- Capita SDP across States (in Rs.) |
Before drawing any conclusion regarding current economic performance of the states, some factors needs to be taken care:
· Delhi and Goa are not comparable with other state (Because of their small size and political-economic importance, they do not represent the diversity of a state)
· Political instability, geographical barrier and consequently poor infrastructure affect SDP for north-east states and Jammu & Kashmir. In spite of this they are ahead of some central states in terms of year on year growth, though the overall production as well as per-capita is far less than national average
· “Growth States” like Punjab and Haryana continues to deliver superior performance, but growth has rather moderated for others like Maharashtra and Gujarat. Concurrent economic research argues that these two states are already achieved a certain scale of per-capita production with a considerable size of economy, and growth rate seems to be quiet impressive while comparing with states with small size and less matured economy
· Legacy of the so called BIMARU states (Bihar, Madhya Pradesh, Rajasthan and UP) as a consistent group of poor performers, continues with only exception- Rajasthan. Bihar and Uttar Pradesh and Madhya Pradesh performed very poorly, growing much more slowly than the average, but the other members of this group, Rajasthan have performed reasonably well.
· Regional disparity in absolute term can be observed by wide variation of per-capita output of states (Figure 1). But the more interesting finding is the degree of dispersion in growth rates increased very significantly in the recent years. The coefficient of variation of the growth rates increased from 0.15 in the period 1985-89 (before economic liberalization of India) to .31 in the current period 2006-09.
3. State Government Expenditure Pattern on Infrastructure Sector
State government expenditures on infrastructure can be categorized in to three main areas namely economic infrastructure services, social services and specific infrastructure projects pertaining to local improvement. A brief description of these categories follows:
Based on a paper on ‘Evaluating Investment on Basic Infrastructure’, B.E. Aigbokhan gives examples of economic infrastructure
Public Utilities | Power, Telecommunication, Piped water supply and piped gas, Sanitation and sewage, solid waste collection and disposal |
Public Works
| Roads, Major dam and canal works for irrigation and drainage, and other transport projects like urban and interurban railways, urban transport, seaports and waterways and airports |
Role in the Economy | It provides services that are part of the consumption bundle of residents; large-scale expenditures for public works increase aggregate demand and provide short-run stimulus to the economy; and it serves as an input into private sector production, thus boosting output and productivity. The provision of economic infrastructure can expand the productive capacity of the economy by increasing the quantity and quality of such infrastructure thereby accelerating the rate of economic growth and enhancing the pace of socio-economic development. |
Social infrastructures and their role as defined in the same paper:
Education | Education is a very important source of economic growth. Even though education may be a social investment, it is also an economic investment since it enhances the stock of human capital. |
Human resource development | Realistic and reliable indicator of modernization or development than any other single measure. It is one of the necessary conditions for all kinds of growth – social, political, cultural or economic |
Health | Health is one of the major determinants of labour productivity and efficiency. Public health measures include the improvement of environmental sanitation both in rural and urban areas, removal of stagnant and polluted water, slum clearance, better housing, clean water supply, better sewage facilities, control of communicable diseases, provision of medical and health services especially in maternal and child welfare, health education, family planning and above all, for the training of health and medical personnel |
State-wise specific infrastructure projects are actually categorized in to above two but funding of the projects does not purely come from government expenditure, rather it is executed on PPP (public-private partnership), BOT (build-operate-transfer) etc various models
Though the investment pattern can be broadly generalized into these categories, relative investment varies among states. The average distribution of expenditure in the year 2008 is approximately 17.43%, 27.14% and 49.50% respectively for the above mentioned areas and the trend is followed in subsequent year (Figure 2). In fact, a growing preference is implementing projects with a specific goal, rather than taking the general way of running long term programs. Where most of the developed states mostly adopting the project based approach and their expenditure often beyond planned limit, states from north- east and “BIMARU’ states are being failed to take the initiative (Figure 3).
Figure 2: All State government combined expenditure break-up for infrastructure sector |
Table2. State government expenditure on infrastructure sector in the year 2008 |
States | Total expenditure (Rs. Cr.) | Economic Factors | Social Factors | Specific Projects |
Jammu & Kashmir | 17045.82 | 20.05% | 17.58% | 38.27% |
Himachal Pradesh | 10613.78 | 18.69% | 27.09% | 67.31% |
Punjab | 26518.98 | 20.66% | 16.34% | 17.40% |
Haryana | 22079.43 | 28.18% | 25.99% | 56.09% |
Uttar Pradesh | 87304.42 | 13.79% | 26.44% | 15.16% |
Rajasthan | 37757.47 | 21.16% | 27.01% | 26.81% |
Delhi | 18159.63 | 3.48% | 28.76% | 38.49% |
Uttarakhand | 9974.61 | 14.65% | 28.36% | 51.07% |
Bihar | 31565.86 | 14.06% | 31.26% | 12.75% |
Orissa | 22844.33 | 16.32% | 28.09% | 18.55% |
West Bengal | 46644.08 | 11.91% | 28.86% | 53.34% |
Assam | 15150.3 | 18.84% | 32.72% | 11.06% |
Meghalaya | 2771.14 | 26.05% | 27.19% | 13.69% |
Tripura | 3835.11 | 12.37% | 24.61% | 6.20% |
Mizoram | 2559.15 | 22.12% | 27.23% | 8.91% |
Manipur | 3716.16 | 17.25% | 19.36% | 76.07% |
Nagaland | 3562.91 | 20.26% | 18.44% | 0.00% |
Arunachal Pradesh | 3068.13 | 30.41% | 23.03% | 4.70% |
Sikkim | 2819.62 | 11.37% | 15.54% | 134.38% |
Jharkhand | 18359.89 | 17.54% | 27.35% | 3.75% |
Gujarat | 42681.06 | 18.60% | 27.65% | 76.51% |
Maharashtra | 80240.29 | 16.50% | 33.37% | 85.72% |
Goa | 3559.18 | 28.38% | 26.14% | 10.29% |
Madhya Pradesh | 35265.68 | 18.54% | 23.10% | 27.86% |
Chhattisgarh | 15029.22 | 20.89% | 27.40% | 12.16% |
Andhra Pradesh | 74875.38 | 22.58% | 24.92% | 93.13% |
Karnataka | 48031.09 | 23.85% | 27.32% | 74.03% |
Kerala | 29044.99 | 10.30% | 27.59% | 117.64% |
Tamil Nadu | 55748.48 | 13.94% | 28.21% | 34.27% |
* Addition of percentage values may exceed or less than 100% as states have borrowed fund or un-utilized fund.
Figure 3: State government expenditure pattern on infrastructure sector for the year 2008 (in Rs. Cr.) |
4. Relationship between Economic Health and Industrial Activity of a State
Table2. Industrial Investment (All industries annually) |
State | 2007 (In cr) | % of GDP | 2008 (In cr) | % of GDP | Y-o-Y Growth |
Jammu & Kashmir | 2820.5 | 9.72% | 4047.52 | 12.73% | 43.50% |
Himachal Pradesh | 10875.92 | 47.61% | 24475.73 | 98.69% | 125.05% |
Punjab | 32324.58 | 26.67% | 39986.76 | 27.71% | 23.70% |
Haryana | 37038.62 | 28.44% | 47856.42 | 31.03% | 29.21% |
Uttar Pradesh | 70485.91 | 22.75% | 91591 | 26.60% | 29.94% |
Rajasthan | 28411.66 | 18.53% | 34302.71 | 19.44% | 20.73% |
Delhi | 6450.22 | 5.15% | 6966.88 | 4.84% | 8.01% |
Uttarakhand | 13405.6 | 42.72% | 18677.32 | 52.48% | 39.32% |
Bihar | 5533.1 | 5.56% | 5636.84 | 4.92% | 1.87% |
Orissa | 35871.08 | 37.73% | 52217.74 | 43.86% | 45.57% |
West Bengal | 43806.14 | 16.56% | 50801.8 | 16.50% | 15.97% |
Assam | 11795.26 | 18.31% | 13019.65 | 18.18% | 10.38% |
Meghalaya | 610.07 | 8.32% | 832.51 | 9.83% | 36.46% |
Tripura | 443.84 | 4.30% | 464.19 | 4.29% | 4.58% |
Mizoram |
|
| NA |
|
|
Manipur | 15.97 | 0.30% | 20.06 | 0.34% | 25.61% |
Nagaland | 73.57 | 1.23% | 69.53 | 1.07% | -5.49% |
Arunachal Pradesh |
|
| NA |
|
|
Sikkim |
|
| NA |
|
|
Jharkhand | 27131.67 | 42.91% | 29761.22 | 42.97% | 9.69% |
Gujarat | 185132.5 | 70.47% | 209558.4 | 68.30% | 13.19% |
Maharashtra | 192130.1 | 37.76% | 214767.5 | 36.34% | 11.78% |
Goa | 6676.39 | 43.78% | 7575.97 | 44.01% | 13.47% |
Madhya Pradesh | 31502.91 | 23.67% | 36431.68 | 24.31% | 15.65% |
Chhattisgarh | 26570.6 | 41.06% | 30862.15 | 38.86% | 16.15% |
Andhra Pradesh | 75464.49 | 27.22% | 95835.45 | 29.35% | 26.99% |
Karnataka | 70453.34 | 34.23% | 86223.98 | 36.18% | 22.38% |
Kerala | 14856.41 | 10.25% | 17075.9 | 10.30% | 14.94% |
Tamil Nadu | 115435.9 | 41.69% | 129523.1 | 42.47% | 12.20% |
From above data it can be concluded that almost every state are investing a certain % of their SDP for industry purpose, though the ratio of investment varies for different states. It can be concluded that growth in SDP certainly affects the industrial activity of a state in almost same way (the correlation coefficient of spending in industrial sector as a % of SDP over the two years being 0.902). Further analysis shows that both industrial investment and gross output growth have a positive correlation with SDP growth.
Figure 4: Industrial investment as a % of SDP is almost fixed in recent years, though they vary in absolute terms |
Now the question remains if change in SDP does have any impact on state government and private sector activities in infrastructure sector. The following table summarizes state-wise infrastructure activities under implementation (data is not available for some of the north east states)
Table 2. Infrastructure project investments under implementation (Rs. Cr) |
Intiative | Government |
| Private |
|
State | Mar-08 | Growth Over Previous Year | Mar-08 | Growth Over Previous Year |
Jammu & Kashmir | 5300 | -18.76% | 1116 | 100.21% |
Himachal Pradesh | 9951 | 39.28% | 17806 | 48.73% |
Punjab | 14447 | 213.09% | 26950 | 104.14% |
Haryana | 7881 | -36.37% | 197771 | 24.87% |
Uttar Pradesh | 39477 | 198.26% | 129227 | 195.56% |
Rajasthan | 16861 | 66.56% | 30364 | 148.09% |
Delhi | 7148 | 2.26% | 24636 | 19.84% |
Uttarakhand | 4865 | -4.50% | 10105 | -24.82% |
Bihar | 4028 | 0.07% | 661 | -33.51% |
Orissa | 5104 | 20.45% | 221302 | 26.30% |
West Bengal | 25206 | 1.32% | 124686 | 56.92% |
Assam | 1741 | 3.87% | 1043 | 14.43% |
Meghalaya | 600 | 58.19% | 1554 | 72.89% |
Tripura | 238 | 0.00% | 230 | 0.00% |
Mizoram | 228 | 0.00% | NA |
|
Manipur | 3227 | 14.15% | NA |
|
Nagaland | NA |
| NA |
|
Arunachal Pradesh | 106 | -26.56% | 900 | 0.00% |
Sikkim | 3078 | -18.77% | 3732 | -4.45% |
Jharkhand | 579 | -15.97% | 91595 | 7.51% |
Gujarat | 53978 | 65.30% | 178826 | 22.30% |
Maharashtra | 83268 | 21.06% | 172151 | 46.63% |
Goa | 366 | 0.00% | 910 | 378.95% |
Madhya Pradesh | 13097 | 33.31% | 79092 | 49.49% |
Chhattisgarh | 812 | -55.57% | 57187 | 86.13% |
Andhra Pradesh | 129563 | 85.80% | 138448 | 85.24% |
Karnataka | 32913 | -7.44% | 78967 | 10.92% |
Kerala | 29678 | -13.15% | 11886 | 67.04% |
Tamil Nadu | 29302 | 53.38% | 113102 | 89.75% |
The findings shows that the growth rate of combined investment of government and private entities is almost un-correlated with SDP growth rate (correlation factor being ~.05). This result can be mostly attributed to long term nature of projects where the benefits achieved from it spread across years after commencement of the project. Also some amount of investment goes for in terms of economic theory which stresses on more focus on ‘social’ infrastructure (subsidies, cap on outflow of funds) which is quite different from generic infrastructure in terms of various factors.
5. The Determinants of Growth in the States
The rate of investment is generally regarded as one of the most important factors explaining growth in any economy and it is therefore appropriate to consider whether inter-state differences in growth are associated with differences in the rate of investment in individual states. The growth rate of SDP would be explained in terms of the common explanatory variables traditionally used like the magnitude of investment in states, industrial activity and the factors of infrastructure index.
g= C +a* independent var. which is a linear equation where C and a constant
Several separate regression equations (g= C +a* independent variable where C is a constant and a is the intercept) which are to be estimated in which the dependent variable in each case was
g = growth of SDP, while the independent variables were
1. IPUB (cumulative expenditure in public sector projects as a ratio of SDP),
2. IPVT (cumulative expenditure in private sector projects as a ratio of SDP)
3. ITOT=IPUB+IPVT.
4. IGO (increase in gross output of all industries)
5. IINV (increase in gross investment in all industries)
7. V (percentage of villages electrified in the base year)
9. T (tele-density).
5.1 Investment Ratios at the State level
Three separate regression equations were estimated in which the dependent variable in each case was g = growth of SDP in 2006 to 2009, while the independent variables were IPUB, IPVT and ITOT which already defined above. The results are reported below
g= 0.152 - 0.06366 IPUB |
g = 0.137756 + 0.010789 IPVT |
g = 0.137876 +0.010141 ITOT |
No significant relationship can be found between the variation in growth across states and the variation in the public investment ratio while, the private investment ratio proves to be extremely considerable (coefficient has the expected positive sign). This variable explicate nearly one- sixth (16%) of the variation in growth for different states.
The above result does not imply that public investment is not important. There may be large errors in the data-set because of factors mentioned earlier (especially inclusion of future investment in unfinished projects is likely to introduce a larger error the more inadequately managed the investment programme). Incomplete projects due to lack of funding and delays may not fuel the growth as expected.
As private investment is subject to greater financial control the data error arising from a large number of unfinished and under-funded projects is likely to be much smaller. Because of efficient use of resource and time, private investment is more directly correlated with growth. It can be concluded that private investment matters and under-performing states needs to be focused to ensure private sector participation for development initiatives.
5.2 Industrial Activity
Considerable part of a states investment is devoted for industrial sector. Though private sector is dominant participant, it is supported by governments which provide the basic frame-work as well as investments. Two factors presented here are IGO (increase in gross output of all industries) and IINV (increase in gross investment in all industries)
g= 0.120971 + 0.061133 IGO |
g = 0.122652 + 0.012 IINV |
The above relationship re-establishes the fact that a state’s capability of representing itself as an attractive destination for investment and providing a business conductive environment would add to its economic growth.
5.3 Quality of Infrastructure
The CMIE has calculated a composite index of the relative infrastructure quality of different states based on 13 separate components. The individual components are : per capita electric power, percent of villages electrified, railway route length per 000 sq.km., surfaced road length per 000 sq.km., unsurfaced road length, handling capacity of major ports, gross irrigated area as % of cropped area, tele-density plus the following per lakh of population: bank branches, post offices, primary schools, hospital beds, and primary health centers. Each indicator is computed for each State relative to the all India average=100. The composite index is the weighted sum of individual indices. (Details: CMIE 1997)
As the composite index is not available for recent periods, some of the individual components are tested for the impact on growth in the states by estimating separate regression equations. The independent variables in this case are growth in % village electrification (V) and growth in tele-density (T)
g= 0.136157 + 0.096952 V |
g = 0.139103 + 0.39027 T |
The positive relationship between growth and the two infrastructure related parameter (village electrification and tele-density) broadly matches with expectations. Significance of these factors leis in their origin- government expenditure and consumption expenditure which are direct contributor to a state’s growth.
6. Conclusion
Statistical results have been achieved somewhat mixed result. They generate expected confirmation that change in the private investment ratios are positively and notably correlated with change in growth. They also give corroboration that certain factors of infrastructure are associated with variations in growth. They also recommend that public investment is not as certainly allied with growth as apparently expected. Although, all these results, including the lack of an important relationship in some cases, are subject to limitation of the data available (like absence of composite infrastructure index).