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Intra-State Economic Disparities: Karnataka and Maharashtra

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.

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
study on intra-state economic disparities for a national finance commission calls for a well-defined perspective on the concept, measure and unit of analysis. The issues that would call for some clarification are as follows.

  • (i) What does the term “economic” refer to? Does one measure it with reference to input, output, outcome, or final impact? What would be the appropriate indicator?
  • (ii) What is the policy relevant issue: Disparity? Inequality? Or both?
  • (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

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    june 27, 2009 vol xliv nos 26 & 27

    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
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    Table 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.

  • (i) The incidence of rural poverty declined between 1973-74 and 2004-05. The percentage point reduction was higher in Karnataka (34) than at the all-India level (28). The number of poor also declined between these two years. The decline was more pronounced in rural Karnataka (42%) than in rural India as a whole (15%). The estimated rural poverty for 2004-05 was 21% in Karnataka as against 28% for all India. The rural headcount ratio has always been less in Karnataka than in the country as a whole.7
  • (ii) Urban poverty has declined since 1973-74 in both Karnataka and all-India but with the difference that there was an increase in the former between 1983 and 1987-88. The reduction in urban poverty between 1973-74 and 2004-05 was less in Karnataka (19 percentage point) than in all-India (24 percentage point). However, the decline in poverty ratios was not sufficient to neutralise the growth in urban population; hence, the number of u rban poor increased in Karnataka and India as a whole. The percentage increase in the number of urban poor was more in Karnataka (52%) than in all-India (34%). U rban poverty in 2004-05 was 33% in Karnataka as against 26% in the country as
  • 218

    ● Region 2: Inland East: Chickmagalur, Hassan, Kodagu and Shimoga.

  • Region 3: Inland South: Bengaluru (Rural), Bengaluru ( Urban), Chamarajanagar, Kolar, Mandya, Mysore and Tumkur.
  • Region 4: Inland North: Bagalkot, Belgaum, Bellary, Bidar, B ijapur, Chitradurga, Davanagere, Dharwad, Gadag, Gulbarga, Haveri, Koppal and Raichur. The salient features are as follows.
  • (i) Rural Karnataka
  • (1) For the state as a whole, rural median consumption increased but less proportionately than the mean. Inequality remained virtually the same though poverty declined. Both broad-base and inclusion coefficients increased by more than 10 percentage points. However, the region-wise profile tells a different story.
  • (2) Coastal and Ghats followed by Inland East had levels of consumption higher than the state average and incidence of poverty lower than the state average in the two years. By 2004-05, Inland South, where the increase in nominal mean and median consumption was the highest, also caught up with the mainstream; but the increase was pronounced in the 99th percentile.
  • (3) There was a general improvement in all the parameters only in Inland East and Inland South.
  • (4) The Coastal and Ghats experience is notable for the following. Though most prosperous in terms of per capita consumption, mean elasticity of median consumption (0.74) was the least across regions. Broad-base and inclusion coefficients declined quite perceptibly. Increase in consumption was concentrated at the top: the richest decile group enjoyed 34% of the total consumption in 2004-05. The consumption share of the poorest decile group was the lowest across regions. Poverty and inequality increased only in this region. Growth virtually bypassed the relatively deprived.
  • (5) The percentage increase in both mean and median consumption was the same and the least in the backward Inland North. P overty was the highest across regions. Inclusion and broad-base measures improved. The broad-base measure was the highest across regions in 2004-05. Given the low levels of median consumption, this could be because of broad-based backwardness.
  • 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
  • (1) The percentage increase in consumption was greater in the urban than in the rural sector but mean elasticity of median was less than that in the rural sector by more than 10 points. Both broad-base and inclusion coefficients were less for the urban than for the rural sector. Inequality increased; however, poverty declined. The broad-base measure declined and inclusion coefficient increased (both slightly).
  • (2) Coastal and Ghats was the most prosperous region in terms of both mean and order-based averages in 1993-94. But the increase in consumption was the lowest; mean elasticity of median was also the lowest. Both broad-base and inclusion coefficients declined by about 20 percentage points. Inequality increased by about 15 percentage points; poverty increased to 43%. In sum, the growth process was regressive in the urban sector also.
  • (3) By 2004-05, Inland South (Bengaluru belt) exceeded Coastal and Ghats in terms of both mean and order-based averages. Consumption increase was the highest but was not broad-based: the 99 percentile more than trebled but the mean elasticity of median
  • 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.

  • (1) Coastal region: Greater Mumbai, Suburban Mumbai, Thane, Raigarh, Ratnagiri and Sindhudurg.
  • (2) Inland Western: Ahmednagar, Pune, Satara, Sangli, Solhapur and Kolhapur.
  • (3) Inland Northern: Nandurbar, Nasik, Dhule and Jhalgaon.
  • (4) Inland Central: Auragnabad, Parbhani, Bid, Latur, Nanded, Osmanabad, Jalna and Hingoli.
  • (5) Inland Eastern: Buldhana, Akola, Washim, Amravati, Yavatmal, Wardha and Nagpur
  • (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.

  • (2) The Coastal and Inland Western regions had mean and median levels of per capita consumption higher than the state estimate, and incidence of poverty lower than it. The increase in consumption was the lowest in the Coastal region and highest in I nland Western. The increase was not broad-based in both; mean elasticity of median was less in the former than in the latter. Poverty increased in the Coastal region but decreased in Inland Western; inequality increased somewhat in the Coastal region. The broad-base and inclusion measures remained the same in the Coastal region but improved in Inland Western.
  • (3) The relative levels of consumption were less than state averages and poverty quite pronounced in Inland Northern, Inland Centre, Inland Eastern, and Eastern. More than two-fifths of the rural population was deprived in Inland Centre and Eastern, and more than one-third in Inland Northern and Inland Eastern in 2004-05. Nominal consumption increase was the second highest in Inland Eastern but the mean elasticity of median was less than one. Mean elasticity was the lowest for Eastern. Inequality declined only in Inland Centre. The broad-base and inclusion measures increased in Inland Centre but declined in the other regions.
  • (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.

  • (2) In the urban sector, only the Coastal region was better off in comparison with the state average and the rest of Maharashtra. The increase in mean consumption was about the same as that in the state mean but the increase in median was much less. The mean elasticity of median was the lowest for the Coastal region. Inequality increased perceptibly and poverty slightly; and the broad-base and inclusion measures remained the same.
  • (3) Urban deprivation, as measured by relative levels of consumption and poverty, was quite pronounced in the remaining five regions. Nominal consumption increase was the highest in Inland Northern (mean) and in Inland Eastern (median). Increase in consumption was the lowest in Inland Centre where poverty increased despite having the highest mean elasticity. Poverty declined in the remaining regions. Poverty was among more than two-thirds of the urban population in Inland Centre, about half in Inland Northern and Inland Eastern, and more than one-third in Inland Western and Eastern. Barring Inland Western and Inland Centre, inequality increased in the remaining regions. The broad-base and inclusion measures increased in Inland Centre but declined in the majority of the regions.
  • 4.2.3 District-wise Profile
  • (1) Estimates of rural poverty at the district level could only be made for the year 1993-94 because of data availability constraints (Suryanarayana 2008d). The estimates show that rural poverty had virtually been eliminated in the prosperous district of Raigad (4.94%), followed by Kolhapur (6.97%) and Thane (8.29%). Rural poverty was the maximum in Dhule (45.5%), which also ranked the lowest in terms of per capita district domestic product.
  • (2) The incidence of urban poverty was the lowest in the district of Gadchiroli (6.11%), followed by Mumbai (7.84%). More than two-thirds of the urban population lived in deprivation in the u rban sectors of Ahmednagar (68.06%), Akola (71.39%) and Buldhana (74.09%); the estimate for 1993-94 was 31% for urban Maharashtra.
  • (3) Combined estimates for the districts as a whole indicate that the incidence of poverty was the least in Mumbai (7.84%) and highest in Dhule (49%), with the average for the state being 28.40%. There is a significant negative correlation between the ranks of the districts in terms of per capita domestic product and the incidence of poverty.8 This would call for concerted efforts at balanced regional development in Maharashtra.
  • 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.

  • (2001a): Census of India 2001: Maharashtra Population Data, Directorate of Census Operations, Mumbai, Maharashtra.
  • (2001b): Poverty Estimates for 1999-2000, Press Information Bureau, New Delhi.
  • (2007): Poverty Estimates for 2004-05, Press Information Bureau, New Delhi.
  • Government of Karnataka (1999): Human Development in Karnataka 1999, Planning Department, Bengaluru.

  • (2002): Economic Survey 2001-2002, Planning, Statistics and Science and Technology Department, Bengaluru.
  • (2006): Karnataka: Human Development Report 2005, Planning and Statistics 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.

  • (2008a): Mainstreaming Poverty Reduction into the National Development Plan of Botswana: An Approach, sponsored by the United Nations Development Programme, Ministry of Finance and Planning, Government of Botswana, Gaborone.
  • (2008b): “What Is Exclusive About ‘Inclusive Growth’?” Economic & Political Weekly, Vol 43, No 43, 91-101.
  • (2008c): Eleventh Five Year Plan on Food Security: Estimates and Interpretations, paper presented at the “International Conference on Health and D evelopment: Issues, Strategies and Options”
  • o rganised by the Department of Applied Economics, Kannur University, Thalassery, 22-23 October 2008.
  • (2008d): Intra-state Economic Disparities: Karnataka & Maharashtra: A Report, Prepared for the 13th Finance Commission, Government of India, New Delhi.
  • Economic & Political Weekly

    EPW
    june 27, 2009 vol xliv nos 26 & 27

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