INTER AND INTRA STATE DISPARITIES Intra-State Economic Disparities: Karnataka and Maharashtra
M H Suryanarayana
This study addresses issues related to definition, dimension, and measure of economic disparities from the perspective of the finance commission. It illustrates concepts and measures within the Kuznets framework for Karnataka and Maharashtra. Though the two states are better off than the nation as a whole in terms of mean-based estimates of average income, they have pronounced inter-regional disparities, interpersonal inequalities and intra-regional deprivations. Broad-based and inclusion measures are generally higher in poor backward regions and vice versa, implying broad-based backwardness and inclusion in deprivation. Such a scenario sets limits on the potential for resource mobilisation and makes a case for investment strategies that promote broad-based inclusive growth across all regions at the state level.
The author would like to thank Vinod Vyasulu for his comments on a previous version of this paper.
M H Suryanarayana (surya@igidr.ac.in) is at the Indira Gandhi Institute of Development Research, Mumbai.
1 Introduction
A
(iii) What is the level of analysis: Macro? Micro? Sectoral (primary, secondary and tertiary)? Regional (rural/urban)?
(iv) What is the unit of analysis: Production? Household? P erson?
Since the finance commission is entrusted with the task of a llocation of fiscal resources among the states from the centre, its concern for intra-state economic disparities, however measured, could be because of its implications for resource mobilisation at the state level or for its adverse welfare consequences or for both. It could be either, and one option would be to address the different issues, to the extent possible, in an integrated framework.
Studies on regional imbalances in development generally use combinations of input, output, outcome and final impact indicators, each of which differ with respect to time, resource and welfare. Interpreting such estimators is difficult, if not impossible. Given the perspectives on resource mobilisation and welfare consequences, it would make sense to examine disparities in three different dimensions of an economy – production, income and expenditure. Since comprehensive up to date information is not generally available on production, this study proposes to examine economic disparities with reference to final outcome measures like income generation and consumption distribution.1 While the former focuses on the size of income generated, the latter captures the distributional, and hence, welfare, dimensions. Therefore, one approach could be to use Kuznets framework (Kuznets 1955). Kuznets examined the extent of economic i nequality and its major determinants in an inter-temporal context. He observed and explained that an inverted-U relation b etween income inequality and per capita income runs in terms of changes in (i) rural-urban disparities in per capita income;
(ii) rural- urban intra-sectoral inequalities in income distri bution; and (iii) sectoral (primary, secondary and tertiary) allocation of the workforce and origin of income.
Kuznets’ hypothesis pertains to the secular behaviour of i ncome distribution in the course of economic development based on time series information for developed countries or a
Economic & Political Weekly
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c ross section of countries spread over a wide range of income. However, the extent of per capita income growth in India has been quite limited during the past five decades of planned development. There have been substantial changes in the sectoral distribution of income (net domestic product) with a decline in the share of the primary sector and a matching increase in the shares of the secondary and tertiary sectors. Sectoral allocation of the workforce, on the other hand, has remained virtually unchanged; the primary sector continues be a source of livelihood for the m ajority of population across states as well as the country as a whole. As a result, sectoral disparities in income per capita have increased and India finds herself in the first phase of the inverted-U hypothesis, that is, in an era of growing income inequality. This profile generally holds good across states but for differences experienced due to historical, institutional and policy interventions towards growth in states like Karnataka and Maharashtra; and progressive redistribution in states like Kerala.
It is not the intention of this study to verify Kuznets’ hypothesis or any part thereof.2 Instead, it seeks to provide a snapshot of the extent of economic disparities and inequalities in the states of Karnataka and Maharashtra using the same framework. Karnataka is above the median in terms of per capita income across major states and the national average in growth performance, while Maharashtra is noted for its second highest level of per c apita income and second best growth performance in terms of annual growth rates of per capita income across states in India (Ahluwalia 2000, GoK 2004, Suryanarayana 2008d).
The study is organised as follows. Section 2 explains measures of economic disparities, which this study seeks to estimate and examine empirically. The subsequent two sections present results on the extent of economic disparities, inequalities and deprivation in Karnataka and Maharashtra. The final section sums up the paper.
2 Economic Disparities: Measures
Generally studies measure levels of disparities in development in terms of mean-based averages of income and inequalities in terms of the Gini ratio. But a mean-based average is not a robust measure for skewed distributions like those of income. Hence, besides some conventional measures, given the emphasis of the 11th Five-Year Plan on inclusive broad-based growth, this study examines the extent of broad-based-ness and the extent of inclusion of the poorer sections in the mainstream in terms of the f ollowing order-based measures (Surynarayana 2008a, b).
● Coefficient of broad-based income distribution ‘γ’ with r eference to the median is given by
(2–δ)ξ50
γ = ∫ f (x)dx where f (x) is the income density function
δξ 50
and γ lies in the interval (0,1).
ξ.50 ∞
1
Where 0 < δ< 1 and ξ.50 such that ∫ f (x)dx = —= ∫ f (x)dx
2
0
ξ.50
and 0 < ψ < 1. In this study, we assign 0.6 as the value for δ. The measure ‘γ’ provides an estimate of the proportion of the population lying within an absolute range of a fraction (0.4) of
216 the median from itself. It lies in the interval (0,1). The higher the value for ‘γ’, the greater is the broad-based-ness of the income distribution process.
δξ .50
● Inclusive Coefficient (IC) is defined as ψ = 1–2 ∫ f (x)dx
where f (x) is the density function of the variable concerned, 0 < δ< 1 and ξ.50 is the median and 0< ψ< 1. In this study, we assign 0.6 as the value for δ. A higher value for ψ indicates greater extent of inclusion of the relatively deprived in the mainstream as measured by the median.
● Mean elasticity of median (ε) where ∂ξ.50/ξ50
(ε) = and μ and ξ.50 stand for mean and median, ∂μ/μ
respectively, of the economic variable under review. A value for ε> 1 would imply a broad-based scenario in its growth and d istribution process.
Given these measures, the following two sections report on economic disparities in the states of Karnataka and Maharashtra, respectively.
3 Karnataka
With a geographical area of 1,92,000 sq km, Karnataka is the eighth largest state in India. For administrative purposes, the state is divided into 27 districts. Karnataka had a population of 53 million in 2001. It is predominantly rural; 66% of the population lives in rural areas. About 71% of its workforce is engaged in agricultural and allied activities, which generate 29% of the net state domestic product (NSDP). The industrial sector in Karnataka a ccounts for 23% of the NSDP (GoK 2002). Inter-regional disparities in income exist due to uneven resource endowments as well as inadequate investment (Suryanarayana 2008d).
3.1 Net State Domestic Product
The following sections discuss the level, structure and trend of the NSDP and the regional dimension in net district domestic product (NDDP) in Karnataka.
3.1.1 Level, Structure and Trend
Karnataka had a per capita NSDP of Rs 27,000 against Rs 25,956 for all India in 2005-06 (GoM 2008). The state, like the nation, was predominantly agricultural with the primary sector contributing 60% of the NSDP (at 1980-81 prices) in 1960-61. This share declined to 43% in 1980-81 and to 25.6% in 2001-02. Between these years, the share of the secondary sector increased from 15.2% to 23% and 26% and that of the tertiary sector from 24.8% to 34% and 48%, respectively (GoK 2006). Estimates of growth performance by sectors and by successive five-year plan periods show that the non-agricultural sectors have generally played a greater role in Karnataka than in India as a whole (Suryanarayana 2008d). However, as with all India, there were only marginal changes in the sectoral distribution of the workforce. Even in 1991, 66.7% of the workforce depended on the primary sector while 13.9% depended on the secondary and 19.4% on the tertiary sector (GoK 1999). In other words, the relative product per
june 27, 2009 vol xliv nos 26 & 27
Industry Primary Secondary Tertiary Total Per Capita NSDP
disparity in per capita net domestic
Year Rs crore Annual Rs crore Annual Rs crore Annual Rs crore Annual Rs Per Annual Growth Rate (%) Growth Rate (%) Growth Rate (%) Growth Rate (%) Annum Growth Rate (%) product, as measured by the Gini
1993-94 14,089 -8,876 -14,017 -36,982 -7,838 -ratio, was 25.49%.
1994-95 13,996 -0.66 9,594 8.09 15,327 9.35 38,917 5.23 8,097 3.30 (ii) Bidar, with a per capita NDDP
1995-96 14,281 2.04 9,828 2.44 16,866 10.04 40,974 5.29 8,368 3.35 of Rs 13,118, is the poorest district. 1996-97 14,979 4.89 10,767 9.55 18,990 12.59 44,737 9.18 8,990 7.44
With a population share of 2.84%,
1997-98 14,588 -2.61 12,054 11.95 20,875 9.93 47,517 6.21 9,416 4.73
it accounted for only 1.56% of the
1998-99 16,250 11.39 14,560 20.79 23,151 10.90 53,961 13.56 10,549 12.04
total NSDP. Urban Bengaluru, the
1999-2000 17,825 9.69 13,255 -8.96 25,463 9.99 56,543 4.78 10,912 3.44
richest district, had a per capita
2000-01 20,078 12.64 13,702 3.37 28,352 11.35 62,132 9.88 11,854 8.63
NDDP of Rs 55,484, which is more
2001-02 17,039 -15.14 15,414 12.49 30,618 7.99 63,071 1.51 11,857 0.03
than four times that in Bidar.
2002-03 15,693 -7.90 16,584 7.59 33,488 9.37 65,765 4.27 12,212 2.99
(iii) Bidar, together with Rai
2003-04 13,375 -14.77 18,269 10.16 37,259 11.26 68,904 4.77 12,634 3.46 2004-05 QE 15,464 15.62 19,068 4.37 41,766 12.10 76,298 10.73 13,820 9.39 chur, Chamarajanagara, Bijapur,
Average growth Haveri, Tumkur and Chitradurga, (% per annum) -0.85 7.20 10.43 6.81 5.29
constituted the poorest quarter
QE = Quick estimates. Source: Based on GoK 2006 and a couple of previous issues. with a share of 21.73% in the state
population and 13.45% in the NSDP. worker has declined in the primary sector and increased in (iv) Gulbarga, Mandya, Kolar, Hassan, Gadag, Bagalkote and the secondary and tertiary sectors in Karnataka.3 This would Belgaum fell in the lower middle quarter. This quarter accounted i mply increases in inter-sectoral disparities and, given intra-for 30.26% of the state population but only 21% of the NSDP. sectoral distributions, in the extent of overall inequality in (v) Koppal, Davanagere, Uttara Kannada, Shimoga, Dharwad i ncome distribution. and Mysore, constituted the upper middle quarter. Their
Karnataka’s economy grew at the rate of 4.8% per annum during income share at 16.75% was a little less than their population the 1980s, that is, at a rate less than the all-India average of 5.4%. share of 19.35%. However, its growth rate picked up
in the 1990s; the average annual Table 3.2: Net District Domestic Product: Karnataka (2004-05) (At current prices)
Rank District NDDP Distribution (%) Per Capita Population NSDP Share Comment
growth rate of NSDP between
NDDP Share 1993-94 and 2001-02 was 6.6% and Primary Secondary Tertiary Total Rs per annum (%) (%)
| exceeded the all-India average of | 1 | Bidar | 21.91 | 16.21 | 61.88 | 100.00 | 13,118 | 2.84 | 1.56 | |
|---|---|---|---|---|---|---|---|---|---|---|
| 6.2% (GoK 2004; 238). The latest | 2 | Raichur | 30.96 | 14.25 | 54.80 | 100.00 | 14,121 | 3.16 | 1.87 | |
| available estimates show that be | 3 | Chamarajanagara | 37.36 | 12.90 | 49.74 | 100.00 | 14,329 | 1.83 | 1.10 | Poorest |
| tween 1993-94 and 2004-05, the | 4 | Bijapur | 31.12 | 17.11 | 51.77 | 100.00 | 14,452 | 3.42 | 2.07 | quarter |
| economy as a whole grew at 6.81% per annum. The average growth rate of per capita income has been commendable at 5.29% per annum | 5 6 7 89 | Haveri Tumkur Chitradurga Gulbarga Mandya | 26.95 31.18 33.83 26.60 37.02 | 22.70 18.79 14.74 19.86 17.66 | 50.36 50.02 51.43 53.54 45.32 | 100.00 100.00 100.00 100.00 100.00 | 15,541 15,549 15,619 15,795 15,910 | 2.72 4.89 2.87 5.92 3.34 | 1.77 3.19 1.88 3.92 2.23 | |
| ( Table 3.1). During this period, the | 10 | Kolar | 32.70 | 16.59 | 50.71 | 100.00 | 16,481 | 4.80 | 3.32 | Lower |
| industry and service sectors grew at 7.20% and 10.43%, respectively | 1112 | Hassan Gadag | 33.43 23.18 | 12.87 14.84 | 53.70 61.98 | 100.00 100.00 | 16,492 16,705 | 3.26 1.84 | 2.25 1.29 | middle quarter |
| (Table 3.1). The primary sector, due | 13 | Bagalkote | 33.09 | 19.75 | 47.16 | 100.00 | 16,766 | 3.13 | 2.20 | |
| to factors like drought, was virtually | 14 | Belgaum | 28.14 | 23.45 | 48.42 | 100.00 | 17,554 | 7.97 | 5.87 | |
| stagnant with a growth rate of | 15 | Koppal | 24.78 | 30.35 | 44.87 | 100.00 | 18,416 | 2.26 | 1.75 | |
| 0.85% per a nnum. Consistent with the relative dominance of these | 1617 | Davanagere Uttara Kannada | 32.01 23.11 | 14.96 21.69 | 53.03 55.20 | 100.00 100.00 | 19,184 19,277 | 3.39 2.56 | 2.73 2.07 | Upper middle |
| s ectors, r egional disparities persist with a dverse welfare consequences in terms of income inequalities and | 18192021 | Shimoga Dharwad Mysore Bengaluru (R) | 29.80 7.70 22.74 25.92 | 16.57 23.61 25.92 21.37 | 53.63 68.70 51.35 52.71 | 100.00 100.00 100.00 100.00 | 20,196 21,674 22,996 24,805 | 3.11 3.04 5.00 3.56 | 2.63 2.76 4.82 3.70 | quarter |
| deprivation. | 22 | Udupi | 22.66 | 21.04 | 56.30 | 100.00 | 25,041 | 2.10 | 2.21 | |
| 3.1.2 Regional Dimension | 23 24 | Chickmagalur Bellary | 49.7929.05 | 8.47 24.41 | 41.75 46.55 | 100.00 100.00 | 26,699 27,808 | 2.163.84 | 2.42 4.47 | Richest quarter |
| Unlike its southern neighbour, Kerala, | 25 | Kodagu | 48.23 | 7.25 | 44.53 | 100.00 | 34,551 | 1.04 | 1.50 | |
| Karnataka is marked by high regional | 26 | Dakshina Kannada | 14.00 | 29.10 | 56.90 | 100.00 | 37,462 | 3.59 | 5.64 | |
| disparities in per capita NDDP.4 The | 27 | Bengaluru (U) | 1.78 | 31.21 | 67.01 | 100.00 | 55,484 | 12.37 | 28.78 | |
| estimates for 2004-05 bring out the following features (Table 3.2). | Karnataka 20.33 23.32 Gini ratio (%)=25.49 Source: Based on /des.kar.nic.in/mainpage.asp?option=5. | 56.35 | 100.00 | 23,848 | 100 | 100.00 | ||||
| Economic & Political Weekly | june 27, 2009 | vol xliv nos 26 & 27 | 217 |
EPWTable 3.3: Per Capita Consumption Distribution: Broad-Base and Inclusive Measures Rural Karnataka a whole. Unlike the rural scenario,
Region Mean Median 99 Percentile Head Poverty Gap Squared Gini Ratio Inclusion Broad-base
the incidence of urban poverty in
Count ratio Ratio Poverty Gap Coefficient Coefficient Rs per month at current prices
(%) Karnataka has always been higher
than that at the national level.
Coastal and Ghats 368.9 300.65 1,255.20 8.96 1.31 0.30 28.03 84.40 68.0
Inland East 299.21 259.28 852.55 14.55 2.59 0.89 23.89 87.20 72.0
3.2.2 Regional profile
Inland South 264.45 229.72 797.88 29.59 5.79 1.79 25.66 82.30 67.0
This section is based on the National
Inland North 247.12 212.8 782.39 37.88 8.31 2.71 26.58 79.00 66.00
Sample Survey (NSS) unit record data
Total 269.38 232.88 826.26 30.11 6.27 2.01 26.99 78.00 66.50
from the central sample on consump-Coastal and Ghats 695.39 501.58 2,487.70 20.26 3.04 0.75 38.37 73.90 61.30 tion distribution at current prices for
(88.50) (66.83)
the 55th (1993-94) and 61st (2004-05)
Inland East 569.36 482.23 1,623.50 5.1 0.55 0.07 23.19 96.00 75.90
(90.29) (85.99) rounds (Tables 3.3 and Table 3.4,
Inland South 534.68 447.40 2,513.00 15.15 1.72 0.35 25.43 93.50 76.70p 219). The NSS regions for Karnataka
(102.19) (94.76)
are classified as follows.
Inland North 444.71 384.63 1,227.71 27.35 4.00 0.90 22.97 93.30 79.60
(79.96) (80.74) ● Region 1: Coastal and Ghats:
Total 508.46 425.55 1,666.13 20.67 2.86 0.64 26.64 91.10 76.00 Dakshina Kannada, Udupi and
(88.75) (82.73)
U ttara Kannada.
Figures in brackets in all tables stand for % increase with reference to the corresponding estimates for 1993-94.
(vi) The richest quarter consisted of Bengaluru (Rural), Udupi, Chickmagalur, Bellary, Kodagu, Dakshina Kannada and Bengaluru (Urban). This subset of districts enjoyed an income share (48.72%) which was almost double its population share (28.66%). Bengaluru (Urban) and Dakshina Kannada dominate this group, with a share of 16% in the state population but 34% in the NSDP.
(vii) The city of Bengaluru alone contributed 29% of the NSDP. In a per capita-NDDP-ordered distribution of districts, Bengaluru (Urban) was an extreme outlier5 and Dakshina Kannada was an outlier.6
3.2 Deprivation
We discuss below the extent of deprivation at the state, regional and district levels for Karnataka.
3.2.1 Macro Profile
Karnataka has generally done better in reducing deprivation visà-vis the all-India profile. The findings based on official estimates of headcount measure of poverty by sectors for Karnataka and all India (GoI 1993, 2001b, 2007) are as follows.
218
● Region 2: Inland East: Chickmagalur, Hassan, Kodagu and Shimoga.
(i) Rural Karnataka
june 27, 2009 vol xliv nos 26 & 27
Count ratio Ratio Poverty Gap Coefficient Coefficient
(%) about 13 percentage points.
Rs per month at current prices
1993-94 (2) The extent of reduction was
Coastal and Ghats 571.93 500.33 2,204.83 15.51 2.99 0.94 30.11 68.90 62.20
quite uneven across districts. The
Inland East 418.34 366.53 1,208.17 37.14 9.31 3.16 27.84 63.90 56.50
percentage point reduction was
Inland South 476.88 409.43 1,475.50 28.79 6.64 2.1 29.44 66.00 56.40
maximum in the district of Ben-
Inland North 336.53 267.88 1,266.62 57.46 18.65 7.81 31.87 71.10 56.60
galuru Rural (32.9), followed by
Total 423.14 351.22 1,451.09 39.9 11.36 4.37 31.89 65.30 54.30
Dakshina Kannada (26.7), Bellary
2004-05
Coastal and Ghats 1,141.46 702.5 3,980.38 42.87 12.02 4.07 45.62 50.50 40.30 (25.7), Chickmagalur (22.6), Ben
(99.58) (40.41)
galuru Urban (21.7) and Shimoga
Inland East 934.64 816.70 2,607.67 28.96 5.34 0.3 27.47 75.10 63.50
(21.5). Poverty increased in the dis
(123.42) (122.82)
Inland South 1,274.86 1,004.75 4,914.17 14.07 2.71 0.84 33.35 71.70 54.20 tricts of Bijapur (2.6 point) and Rai
(167.33) (145.40)
chur (21.2 point).
Inland North 697.96 541.25 2,313.50 57.04 17.01 6.71 32.4 80.00 62.40
(3) The association between dis
(107.40) (102.05)
Total 1,033.20 763.68 4,062.00 32.61 8.73 3.25 36.85 66.70 51.80 trict-wise estimates of poverty and
(144.17) (117.43)
per capita domestic product was
Figures in brackets in all tables stand for % increase with reference to the corresponding estimates for 1993-94.
(ii) Urban Karnataka
positive and significant in 1993-94 and 2004-05. Spearman rank order correlation coefficients are statistically significant at (-) 0.60 and (-) 0.77, respectively. There is some evidence of poverty alleviation by the growth process in Karnataka.
(4) A region-wise profile of poverty shows that deprivation was concentrated largely in northern Karnataka. The divisions of Gulbarga and Belgaum accounted for about 40% of the state’s population but nearly 60% of the poor in Karnataka. In contrast, Mysore division accounted for 26% of the state’s population, but only 14% of its poor.
4 Maharashtra
Maharashtra has a geographical area of 3,07,713 sq km. It is the third largest state in India and is divided into 35 districts. As per the 2001 census, Maharashtra has a population of 96.8 million, that is, 9.42% of the total Indian population. This is the second largest among all states and union territories in India (GoI 2001a). Its urban sector has a state population share of 42.40%, which is the second highest across states. About two-thirds of
was less than one (0.87). Inclusion Table 4.1: Growth (%) in State Domestic Product by Sector, Maharashtra: New Millennium
| improved | but | the | broad-base | Sector | 2000-01 | 2001-02 | 2002-03 | 2003-04 | 2004-05 | 2005-06 | 2006-07 | Average |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| m easure declined somewhat; and i nequality increased. (4) Both the broad-base and inclusion measures increased only in | AgricultureForestry and logging Fishing Mining and quarrying | (-) 4.84 (-) 7.09 (-) 5.22 6.23 | 7.53 1.31 4.23 4.66 | 3.02 (-) 4.14 (-) 3.44 6.76 | 11.23 (-) 2.64 3.05 9.42 | (-)6.70 (-) 11.65 (-)7.78 7.22 | 9.38 0.07 7.23 5.86 | Growth Rate 9.09 3.88 12.87 (-) 1.86 0.25 (-) 0.37 0.13 5.72 | ||||
| Inland East and Inland North. In- | Sub Total: Primary sector | (-) 4.50 | 7.07 | 2.75 | 10.46 | (-) 6.26 | 8.87 | 8.59 | 3.66 | |||
| land North had the lowest average | Registered Manufacturing | (-) 20.38 | (-) 7.28 | 13.10 | 14.24 | 10.75 | 8.56 | 12.81 | 3.75 | |||
| consumption and more than half | Unregistered manufacturing | 7.68 | (-) 3.24 | 6.88 | 5.33 | 7.85 | 4.83 | 9.87 | 5.52 | |||
| the population was deprived even | Construction | (-) 12.17 | 11.32 | (-) 0.06 | 7.93 | 2.82 | 18.27 | 21.01 | 6.48 | |||
| in 2003-04. | Electricity, gas and water supply | 16.98 | (-) 20.05 | 20.50 | 3.80 | 12.86 | 12.23 | 3.53 | 6.30 | |||
| Sub Total: Secondary sector | (-) 11.21 | (-) 3.44 | 8.98 | 10.10 | 8.52 | 10.21 | 13.42 | 4.87 | ||||
| 3.2.3 | District-wise profile | Transport by other means and storage, communications, trade, hotels and restaurants | 3.96 | 4.18 | 7.21 | 8.38 | 16.81 | 9.19 | 11.98 | 8.74 | ||
| Comparable estimates of poverty at | Banking and insurance, real estate, ownership | |||||||||||
| the district level for the years 1993-94 and 1999-2000 bring out the following (Suryanarayana 2008d). (1) Poverty declined in the state | of dwellings public administration and other services Sub Total: Tertiary sector Net State Domestic Product Per Capita NSDP (Rs) | (-) 0.35 1.31 (-) 3.07 (-) 4.86 | 6.01 5.28 3.46 1.60 | 7.36 7.30 6.86 5.31 | 2.93 5.07 7.18 5.49 | 10.16 12.85 8.37 6.69 | 9.64 9.46 9.55 7.87 | 6.26 8.64 9.79 8.15 | 5.94 7.08 5.93 4.23 | |||
| (rural and urban sectors combined) | Source: Based on GoM 2008. | |||||||||||
| Economic & Political Weekly | june 27, 2009 | vol xliv nos 26 & 27 | 219 |
EPW| Table 4.2 Net District Domestic Product: Maharashtra (2006-07) (At current prices) | in 1960, the state per capita NSDP | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Rank | District | NDDP Distribution (%) | Per Capita NDDP | Population Share | NSDP Share | Comment | grew at 4.73% till 1999-2000 (Sury- | ||||||
| Primary | Secondary | Tertiary | Total | Rs per annum | (%) | (%) | anarayana 2008d). Per capita NSDP | ||||||
| 1 | Washim | 36.32 | 8.17 | 55.50 | 100.00 | 20,774.24 | 1.03 | 0.52 | increased by about 150% between | ||||
| 2 | Nanded | 22.19 | 14.29 | 63.53 | 100.00 | 21,089.44 | 2.92 | 1.49 | 1960-61 | and | 1999-2000. | This | |
| 3 | Buldhana | 26.63 | 12.98 | 60.39 | 100.00 | 21,188.39 | 2.26 | 1.16 | meant a growth rate of 2.43% per | ||||
| 4 5 6 78 | Latur Hingoli Gadchiroli Jalna Osmanabad | 23.90 36.69 41.36 31.90 31.74 | 15.09 8.24 10.21 13.03 11.55 | 61.01 55.06 48.43 55.06 56.71 | 100.00 100.00 100.00 100.00 100.00 | 21,997.71 22,667.15 23,126.1 23,436.47 23,760.09 | 2.11 1.00 0.97 1.63 1.50 | 1.12 0.55 0.54 0.92 0.86 | Poorest quarter | annum in SDP per capita. The growth experience during the new millennium has been impressive: per capita net SDP in | |||
| 9 | Amravati | 20.71 | 14.37 | 64.92 | 100.00 | 24,858.06 | 2.67 | 1.61 | creased by 34% between 1999-2000 | ||||
| 10 | Parbhani | 32.50 | 11.95 | 55.55 | 100.00 | 24,859.8 | 1.56 | 0.94 | and 2006-07 at an average annual | ||||
| 11 | Dhule | 18.51 | 18.97 | 62.52 | 100.00 | 25,521.9 | 1.74 | 1.07 | growth rate of 4.23% (Table 4.1, | ||||
| 12 | Beed | 34.29 | 10.90 | 54.81 | 100.00 | 26,017.69 | 2.18 | 1.37 | p 219). The primary sector, in spite | ||||
| 1314 | Yavatmal Gondia | 32.39 16.55 | 12.15 22.52 | 55.46 60.94 | 100.00 100.00 | 26,456.02 27,115.36 | 2.48 1.21 | 1.59 0.79 | Lower middle quarter | of its declining share in output, continues to be the major source of | |||
| 15 | Akola | 24.72 | 17.10 | 58.19 | 100.00 | 28,287.2 | 1.68 | 1.15 | livelihood. While its share of in | ||||
| 16 | Nandurbar | 41.96 | 6.77 | 51.27 | 100.00 | 28,516.6 | 1.32 | 0.91 | come declined from 42.14% to | ||||
| 17 | Wardha | 22.84 | 18.78 | 58.38 | 100.00 | 30,529.01 | 1.26 | 0.93 | 22.88% | between | 1960-61 | and | |
| 1819202122 | Bhandara Jalgaon Ratnagiri Sindhudurg Sangli | 23.99 26.00 14.71 23.43 22.83 | 22.25 20.47 26.54 17.36 16.22 | 53.76 53.52 58.76 59.21 60.95 | 100.00 100.00 100.00 100.00 100.00 | 31,254.48 32,072.49 32,945.75 33,099.16 35,200.78 | 1.15 3.76 1.70 0.87 2.63 | 0.87 2.91 1.36 0.70 2.24 | Upper middle quarter | 1990-91, its share of the workforce declined from 72.07% to 61.51%. In other words, the percentage point decline in the workforce share is | |||
| 23 | Ahmednagar | 28.68 | 17.08 | 54.24 | 100.00 | 35,251.73 | 4.09 | 3.49 | less than that in the output share of | ||||
| 24 | Aurangabad | 16.08 | 38.14 | 45.78 | 100.00 | 35,844.98 | 2.98 | 2.58 | the primary sector. The secondary | ||||
| 25 | Solapur | 26.94 | 16.73 | 56.33 | 100.00 | 36,186.47 | 3.94 | 3.45 | sector has increased its share of | ||||
| 26 | Chandrapur | 29.91 | 18.05 | 52.04 | 100.00 | 36,793.8 | 2.12 | 1.89 | output as well as workforce. Within | ||||
| 27 | Satara | 24.94 | 20.01 | 55.04 | 100.00 | 37,398.48 | 2.83 | 2.56 | the secondary sector, the manufac | ||||
| 28 29303132 | Kolhapur Nagpur Nashik Raigad Thane | 18.47 12.72 24.17 8.18 3.37 | 21.86 28.95 29.22 48.12 30.56 | 59.67 58.34 46.61 43.69 66.07 | 100.00 100.00 100.00 100.00 100.00 | 43,448.49 44,597.75 46,064.22 47,647.85 58,224.04 | 3.60 4.28 5.14 2.24 8.61 | 3.78 4.62 5.73 2.59 12.13 | Richest quarter | turing sector has played a major role in providing factory employment. On an average, it accounts for 92% of the total daily factory | |||
| 33 | Pune | 9.59 | 37.45 | 52.95 | 100.00 | 60,375.43 | 7.57 | 11.05 | employment (1.23 million). This | ||||
| 34 | Mumbai* | 1.41 | 28.64 | 69.95 | 100.00 | 65,361.1 | 12.98 | 20.53 | i nvolves a wide spectrum of sectors | ||||
| Maharashtra | 14.95 | 25.85 | 59.20 | 100.00 | 41,331.11 | 100.00 | 100.00 | falling under the consumer goods |
Gini ratio (%) = 20.62. Source: Based on GoM 2008.
the workforce is dependent on agriculture as a source of livelihood, resulting in low levels of per capita income in rural areas. Growth options have had to be exercised largely on the non- agricultural front. Maharashtra’s record in this respect has been mixed. The secondary and tertiary sectors have been instrumental in the growth process but not so with regard to absorption of the growing workforce. This has called for conscious public p olicies to alleviate unemployment and poverty, in particular in the rural sector.
4.1 Net State Domestic Product
The following sections discuss the level, structure and trend of the NSDP and the regional dimension in NDDP in Maharashtra.
4.1.1 Level, Structure and Trend
By the income measure, Maharashtra emerges as the second richest among the major states in India. In 2005-06, per capita state domestic product was Rs 36,090 which is about 40% more than the all-India average of Rs 25,956 (GoM 2008). Since its creation
220
industry, intermediate goods indus
try and capital goods industry which account for 37.5%, 29.2% and 25.4% of total factory employment, respectively (GoM 2001; 30). The tertiary sector increased its share of the workforce by about 7 percentage points. As a result, disparities in relative product per worker in the three sectors have increased over time. While the relative product per worker in the primary sector declined from 0.58 to 0.37, that is by about 36%, during 1960-61 to 1990-91, those of the secondary and tertiary sectors have declined by less than 6% (Suryanarayana 2008d). The relative sectoral product per worker of the primary sector is about one-fourth those of the secondary and tertiary sectors. Such inter-sectoral disparities in growth performance have implications for the regional distribution of income and poverty. This question is examined in the following sections.
4.1.2 Regional Dimension
An important feature of planned economic development is its balanced spread across regions. The estimates of district-wise i ncome and its composition for 2006-07 bring out the following features (Table 4.2).
june 27, 2009 vol xliv nos 26 & 27
| Table 4.3: Per Capita Consumption Distribution: Broad-Base and Inclusive Measures Rural Maharashtra (i) Inter-district disparity (Gini |
|---|
| Region Mean Median 99 Percentile Head Poverty Gap Squared Gini Ratio Inclusion Broad-Base ratio) in per capita income gener- |
| Count Ratio Ratio Poverty Gap Coefficient Coefficient |
| ated was 20.62% in 2006-07. |
| Rs per month at current prices (%) |
| 1993-94 (ii) Washim, with a per capita NDDP |
| Coastal 361.92 300.06 1,481.15 15.22 2.50 0.64 29.38 77.70 64.30 of Rs 20,774, is the poorest district. Its |
| Inland Western 298.47 257.33 936.16 24.92 5.00 1.62 26.93 79.50 67.90 |
| per capita NDDP was Rs 17,537 in |
| Inland Northern 232.76 200.52 657.83 47.30 10.92 3.64 26.01 83.80 70.80 |
| 2005-06 and was about the same as |
| Inland Central 262.20 195.75 1,354.94 49.80 15.91 6.89 38.50 63.20 54.00 |
| the first quartile for per capita NSDP |
| Inland Eastern 230.99 198.40 840.67 49.11 11.49 3.70 26.35 85.80 70.30 |
| across major states in India. Mumbai, |
| Eastern 229.88 195.52 669.60 49.30 10.66 3.40 24.88 90.70 72.00 |
| the richest district, had a per capita |
| Total 272.66 225.41 989.96 37.91 9.28 3.35 30.67 75.90 63.90 |
| 2004-05 NDDP of Rs 65,361, which is more |
| Coastal 608.95 481.81 2,352.67 26.03 5.71 1.88 32.09 77.00 63.00than three times that in Washim. |
| (68.26) (60.57) |
| (iii) The districts of Washim, |
| Inland Western 687.28 572.00 2,358.80 9.54 1.24 0.27 27.67 86.90 69.60 |
| (130.27) (122.28) Nanded, Buldhana, Latur, Hingoli, |
| Inland Northern 490.89 413.05 1,362.98 37.90 8.73 3.05 28.50 80.60 66.60Gadchiroli, Jalna, Osmanabad, and |
| (110.90) (105.99) |
| Amravati form the poorest quarter. |
| Inland Central 499.68 383.85 3,471.03 42.64 9.72 3.05 32.77 84.10 67.90 |
| (90.57) (96.09) They accounted for just 8.8% of the |
| Inland Eastern 526.13 433.33 1,844.27 33.45 6.14 1.62 28.24 83.80 67.30 total income generated in the state |
| (127.77) (118.41) |
| despite having a proportionately |
| Eastern 496.52 377.00 1,968.00 47.05 12.03 4.41 34.26 81.10 64.00 |
| (115.99) (92.82) larger share in population (16.1%). |
| (iv) Parbhani, Dhule, Beed, Yavat-Total 567.84 459.075 2,150.37 29.57 6.31 1.99 31.20 77.10 63.60 |
| (108.26) (103.66) |
| mal, Giondia, Akola, Nandurbar, and |
| Wardha belonged to the lower mid- |
| Table 4.4: Per Capita Consumption Distribution: Broad-Base and Inclusive Measures Urban Maharashtra |
| dle quarter. Together they contrib-Region Mean Median 99 Percentile Head Poverty Gap Squared Gini Ratio Inclusion Broad-Base |
| uted just 8.75% to the total NSDP. Count Ratio Ratio Poverty Gap Coefficient Coefficient |
| Rs per month at current prices (%) |
| (v) Bhandara, Jalgaon, Ratnagiri, |
| 1993-94 |
| Sindhudurg, Sangli, Ahmednagar, Coastal 676.59 566.38 2,214.46 12.46 2.37 0.68 30.43 71.70 60.00 |
| Aurangabad, and Solapur constituted | Inland Western | 487.92 | 369.26 | 1,838.50 | 40.17 | 9.90 | 3.61 | 34.08 | 76.30 | 58.90 |
|---|---|---|---|---|---|---|---|---|---|---|
| the upper middle quarter. Their share | Inland Northern | 363.39 | 303.76 | 1,335.95 | 58.49 | 16.87 | 6.72 | 29.78 | 75.00 | 64.20 |
| in NSDP was 17.6% but their share in | Inland Central | 385.94 | 273.5 | 2,390.35 | 61.54 | 23.04 | 11.14 | 40.61 | 58.80 | 48.20 |
| population was higher at 21.1%. | Inland Eastern | 375.87 | 282.95 | 1,356.93 | 59.04 | 20.02 | 8.71 | 35.4 | 69.90 | 56.50 |
| Eastern | 388.93 | 325.11 | 930.73 | 52.73 | 12.38 | 4.33 | 26.71 | 84.40 | 63.80 | |
| (vi) The richest quarter consisted | ||||||||||
| Total | 529.8 | 411.43 | 2,011.22 | 34.99 | 10.14 | 4.16 | 35.75 | 63.00 | 50.30 | |
| of Chandrapur, Satara, Kolhapur, | ||||||||||
| 2004-05 | ||||||||||
| Nagpur, Nashik, Raigad, Thane, | Coastal | 1461.35 | 1087.9 | 6,642.99 | 14.51 | 2.74 | 0.78 | 36 | 72.40 | 58.30 |
| Pune and Mumbai. With a popula | (115.99) | (92.08) | ||||||||
| Inland Western | 994.97 | 797.00 | 3,511.83 | 36.81 | 8.92 | 3.02 | 32.74 | 68.60 | 56.80 | |
| tion share of 49%, they contributed | ||||||||||
| (103.92) | (115.84) | |||||||||
| about 65% of the total NSDP. | Inland Northern | 921.04 | 682.79 | 3,397.75 | 48.17 | 15.30 | 6.54 | 36.26 | 69.40 | 51.10 |
| (vii) Thus, a striking character of | (153.46) | (124.78) | ||||||||
| Inland Central | 667.60 | 496.42 | 2,561.57 | 66.17 | 25.03 | 11.19 | 34.02 | 74.10 | 55.80 | |
| economic development in Mahar | ||||||||||
| (72.98) | (81.51) | |||||||||
| ashtra is the wide disparity in income | Inland Eastern | 909.40 | 699.42 | 3,528.75 | 46.88 | 14.74 | 5.96 | 37.11 | 62.60 | 53.60 |
| across districts. Mumbai accounted | (141.95) | (147.19) |
| for about 21% of the NSDP followed by Thane (12%), Pune (11%) and | Eastern Total | 882.48 (126.90) 1148.25 | 741.13 (127.96) 863.90 | 2,698.27 5,223.32 | 35.77 32.1 | 10.53 9.13 | 4.27 3.56 | 29.02 37.77 | 69.50 62.00 | 58.90 50.90 |
| Nashik (6%). In other words, these | (116.73) | (109.97) | ||||||||
| four urban districts alone accounted | ||||||||||
| for about 50% of the NSDP in Maharashtra. | a bsorption, one finds that the incidence of deprivation is quite |
(viii) Mumbai, together with Pune and Thane, constitute the high in Maharashtra. The official estimates of poverty bring out subset of outliers in an income-based, rank-ordered profile of dis-the following (GoI 1993, 2001b, 2007). tricts in Maharashtra. The incidence of rural poverty declined by the same percent
age points (28) between 1973-74 and 2004-05 in both Maharashtra
4.2 Deprivation and India as a whole. The reduction in the number of rural poor We discuss below the extent of deprivation at the state, regional was more in Maharashtra (19%) than in India as a whole (15%). and district levels for Maharashtra. About 30% of the rural population in Maharashtra and 28% in
India were below the poverty line as per official estimates.
4.2.1 Macro Profile The percentage point reduction in urban poverty between 1973-74 Consistent with poor resource endowment and limited labour and 2004-05 was less in Maharashtra (11) than in the country (24).
Economic & Political Weekly EPW june 27, 2009 vol xliv nos 26 & 27 221
The decline in poverty ratios could not neutralise the growth in urban population; hence, the number of the poor increased in urban Maharashtra and urban India as a whole. The increase in the number of u rban poor was more in Maharashtra (95%) than in all India (34%). Urban poverty in Maharashtra was less than the national average till 1993-94. In 2004-05, it was 32% against the all India estimate of 26%.
4.2.2 Regional profile
This section provides a regional profile of deprivation based on the NSS unit record data at current prices for the 55th (1993-94) and 61st (2004-05) rounds (Tables 4.3 and 4.4, p 221). The NSS regions are classified as follows.
(6) Eastern: Bhandara, Gadchiroli, Chandrapur and Gondiya.
(i) Rural Maharashtra
(1) The proportionate increase in mean per capita consumption was more than that in the corresponding median for the state. Inequality remained virtually the same but poverty declined. Both broad-base and inclusion coefficients for Maharashtra were much less than those for Karnataka and remained the same between 1993-94 and 2004
05. But region-wise profiles differ in Maharashtra also.
(ii) Urban Maharashtra
(1) In the state as a whole, urban consumption increased more than that in the rural sector but its mean elasticity of median was marginally less. Both broad-base and inclusion coefficients were less for the urban than for the rural sector and remained the same b etween the two years. Poverty declined and inequality increased somewhat.
4.2.3 District-wise Profile
5 Conclusions
This study has addressed issues related to definition, dimension, and measure of economic disparities from the perspective of the national finance commission. Given the commission’s concerns on resource mobilisation and equity, the paper focuses on the outcome dimension as reflected in estimates of income generation and distribution. Consistent with the current emphasis on broad-based i nclusive growth, the study proposes measures of broad-based i ncome distribution; and inclusion. Finally, it illustrates concepts and measures within the Kuznets framework, that is, in terms of inter- and intra-sectoral dimensions at the state/regional levels for Karnataka and Maharashtra. Some salient findings are as follows.
june 27, 2009 vol xliv nos 26 & 27
Karnataka falls just above the median in a rank-ordered profile of Indian states in terms of per capita income. Its growth performance since the mid-1990s has been above the average for the country. The secondary and tertiary sectors have done better than the primary sector in the growth process. The differential growth performance across these three sectors, depending on their relative dominance, has a cumulative impact on the level of income across districts. Accordingly, Karnataka is marked by regional imbalances. The city of Bengaluru alone accounts for 29% of the state income; it enjoys a per capita income four times greater than that in the poorest district, Bidar. Northern Karnataka is relatively backward in economic as well as non-economic dimensions and there is a concentration of deprivation. Karnataka has generally done better in terms of reducing rural deprivation vis-à-vis all India. Unlike the rural scenario, the incidence of urban poverty in Karnataka has a lways been higher than that at the national level. Recent growth profiles in consumption differ between sectors across regions. Both the rural and urban sectors in the prosperous Coastal and Ghats stand out for narrow-based growth, and excluding the relatively deprived, poverty has increased substantially. The broad-base and inclusion coefficients generally improved in the rural and urban sectors of the other regions. The extent of inclusion was less in u rban than in rural Karnataka. The north continues to be inclusive in backwardness and lag behind the rest in its growth profile. In sum, the growth observed in Karnataka seems to be neither broadbased nor inclusive across regions or persons.
Maharashtra is one of the most industrialised and urbanised states in India. It ranked second in terms of per capita NSDP and also growth performance during the 1990s. Growth, though significant, is confined largely to the non-agricultural sectors located in urban districts like Mumbai and Thane. This has sharpened inter-district disparities. The four urban districts of Mumbai, Thane, Pune and
Notes References
Nashik account for half of the state income; the other half is shared by the remaining 31 districts, where deprivation is quite pronounced. Rural poverty in Maharashtra was generally higher than the national average. Urban poverty was less than the national average till the mid-1980s but has crossed it since then. As regards regional profiles, in the rural sector, the Coastal region and Inland Western are better off than the state average in terms of levels of living as well as extent of deprivation. Deprivation was quite pronounced in the remaining four regions of rural Maharashtra. Almost half of the rural population was deprived in the Inland Central and Eastern regions. The increase in rural consumption was broad-based and inclusive only in the Inland Western and Inland Central regions. These two measures declined or remained the same in the remaining regions. There was a general decline in both the broad-base and inclusion measures in the majority of regions in urban Maharashtra. These two measures registered perceptible improvement in only urban Inland Central. Deprivation was generally higher in those districts which are economically backward in terms of per capita domestic product. Needless to say, this calls for concerted efforts at balanced regional development in Maharashtra.
The two case studies provide empirical evidence to show that though mean-based estimates of average income reveal the two states to be relatively better off than the nation as a whole, both of them are marked by pronounced inter-regional disparities, interpersonal inequalities and intra-regional deprivations. Broad-base and inclusion measures are generally higher in poor backward regions and vice versa, implying broad-based backwardness and inclusion in deprivation. Such a scenario sets limits on the potential for resource mobilisation and makes a case for investment strategies that promote broad-based inclusive growth across all regions at the state level. Therefore it becomes imperative to define some limits on intra-state disparities and canons for resource mobilisation.
– (2008): Economic Survey of Maharashtra 2007-08,
1 Further, “the most common ... meaning of economic in relation to regional economic disparities is per capita income” (Cameron 1981; 502).
2 Verification of trends in the extent of inequality in income/consumption distribution would not be possible for reasons cited in Suryanarayana 2000.
3 Relative product per worker of a given sector is obtained as the ratio of its share in total value added to its share in the total workforce.
4 For methodological details on estimation of state domestic product, see Nayyar et al (2003).
5 This limit for defining an extreme outlier, given by upper quartile plus three times the inter-quartile range, worked out to be Rs 48,483 for the year 2004-05.
6 This lower limit for defining just an outlier, given by the upper quartile plus one and a half times the inter quartile range, was Rs 36,192 for the same year.
7 Estimates of incidence of calorie deficiency based on the same data sets, on the contrary, show an increase in nutritional deprivation. This could be because of the application of outdated subsistence norms in a context of structural and technological changes in the economy calling for reduced energy expenditure (see Suryanarayana 2008c).
8 The rank correlation is -0.58, which is statistically significant for a one-tail test at 1% level of s ignificance.
Ahluwalia, M S (2000): “Economic Performance of States in Post-Reforms Period”, Economic & Political Weekly, Vol XXXV, No 19, 1637-48.
Cameron, David M (1981): “Regional Economic Disparities: The Challenge of Federalism and Public Policy”, Canadian Public Policy, Vol 7, No 4, 500-05.
Government of India (1993): Report of the Expert Group on Estimation of Proportion and Number of Poor, Perspective Planning Division, Planning Commission, New Delhi.
Government of Karnataka (1999): Human Development in Karnataka 1999, Planning Department, Bengaluru.
Government of Maharashtra (2001): Economic Survey of Maharashtra 2000-2001, Directorate of Econo mics and Statistics, Planning Department, Mumbai.
Directorate of Economics and Statistics, Planning Department, Mumbai.
Kuznets, Simon (1955): “Economic Growth and Income Inequality”, The American Economic Review, Vol 45, No 1, 1-28.
Nayyar, Rohini, Meenakshi Rajiv and Vinod Vyasulu (2003): Estimating District Income in India (New Delhi: Macmillan).
Suryanarayana, M H (2000): “How Real is the Secular Decline in Rural Poverty?” Economic & Political Weekly, Vol XXXV, No 25, 2129-39.
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