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What Is Exclusive About 'Inclusive Growth'?

Inclusive growth is the new mantra of national and international agencies, but what does it mean and how does one measure inclusion or the lack of it? In contrast to policy documents that discuss inclusive growth in loose terms, this paper makes an attempt to define the concept and aims to develop measures of inclusion. Given the methodological inadequacies of verifying a broad-based growth process in terms of mean-based averages of income and absolute-norm based measures of deprivation, the study proposes order-based averages for verifying the presence of broad-based growth and extent of inclusion of the poor in terms of the consumer expenditure distribution. In addition, to facilitate verification and comparison of both inter- and intra-group inclusion in a plural society, normalised measures with reference to both mainstream/overall and subgroup averages are worked out. The tentative estimates indicate that the growth process between 1993-94 and 2004-05 bypassed the majority and was not inclusive. At the national level, the inclusion coefficient is higher for the rural sector than for the urban. The association between median consumption and the inclusion coefficient across states is weak, which would also imply that there is no cross-sectional evidence to believe that growth in India has been inclusive.

SPECIAL ARTICLEEconomic & Political Weekly EPW october 25, 200893What Is Exclusive About ‘Inclusive Growth’? M H SuryanarayanaInclusive growth is the new mantra of national andinternational agencies, but what does it mean and how does one measure inclusion or the lack of it? In contrast to policy documents that discuss inclusive growth in loose terms, this paper makes an attempt todefine the concept and aims to develop measures of inclusion. Given the methodological inadequacies of verifying a broad-based growth process in terms of mean-based averages of income and absolute-norm based measures of deprivation, the study proposes order-based averages for verifying the presence of broad-based growth and extent of inclusion of the poor in terms of the consumer expenditure distribution. In addition, to facilitate verification and comparison of both inter-and intra-group inclusion in a plural society, normalised measures with reference to both mainstream/overall and subgroup averages are worked out. The tentative estimates indicate that the growth process between 1993-94 and 2004-05 bypassed the majority and was not inclusive. At the national level, the inclusion coefficient is higher for the rural sector than for the urban. The association between median consumption and the inclusion coefficient across states is weak, which would also imply thatthere is no cross-sectional evidence to believe that growth in India has been inclusive.The Eleventh Five-Year Plan Strategy is ‘Towards Faster and More Inclusive Growth’. Though the Approach Paper [Gov-ernment of India (GoI) 2006] has not defined the concept of inclusive growth, the Economic Survey of 2007-2008 presents some estimates of outcome measures (without any evaluation) of inclusive growth in India between 1993-94 and 2004-05 [GoI 2008: 241-45]. A similar confusion exists in the international context too with institutions like the United Nations Development Pro-gramme (UNDP) and the World Bank harping on inclusive growth without a well-defined perspective. The UNDP is quite open when it admits: “UNDP’s Strategic Plan has a number of new terms. Chief among them is a previously not-so-much-talked-about term ‘inclusive growth’. So it is high time forUNDP to collectively understand and agree on this million dollar question – what is inclusive growth and how to achieve it?” [UNDP 2008: 1].Since it may not be possible to define a strategy without any understanding of the profile and magnitude of the problem, this paper proposes to define inclusion/exclusion with reference to an outcome scenario for broad-based growth as reflected in esti-mates of production, income, and consumption distribution. This should facilitate a sketch of occupational/social/regional profiles of the included/excluded and hence, appropriate policy design/strategy for the inclusion of the excluded in the mainstream/growth process. This study, therefore, makes an attempt to pro-vide a perspective, a measure of inclusion, and finally an evalua-tion (for illustration) based on the available estimates of con-sumption distribution for a recent year (2004-05) for India. This study is organised as follows: Section 1 provides a brief review based on the Eleventh Plan Approach Paper [GoI2006] and different versions of the concept of inclusive growth. Section 2 proposes a possible approach to outcome evaluation of inclusive growth followed by its application and empirical illustration in the Indian context in Section 3.1 Section 4 summarises the paper. 1 A Review of the ConceptThe Approach Paper of the Eleventh Plan states that the Plan pro-vides “an opportunity to restructure policies to achieve a new vision based on faster, more broad-based and inclusive growth. It is designed to reduce poverty and focus on bringing the various divides that continue to fragment our society” [GoI 2006: 1]. These are the broad objectives that successive five-year plans in India have sought to achieve in some form or the other right from the beginning. For that matter, the concept of inclusive growth has also already gained wide currency in several countries including India [Bolt 2004]. This is a revised and extended version of the paper presented in the plenary session of the Fourth National Conference on Finance & Economics organised by the ICFAI Business School, Bangalore, December 14-15, 2007. Thanks are due to Amit Bhaduri and Chandan Mukherjee for comments on an earlier version and to Ankush Aggrawal for computational assistance. The final revision was carried out in May 2008 while the author was visiting the Centre for International Cooperation and Development, University of Pavia, Italy.M H Suryanarayana ( is at the Indira Gandhi Institute of Development Research, Mumbai.
SPECIAL ARTICLEoctober 25, 2008 EPW Economic & Political Weekly94The government has sought to pursue a strategy without pro-viding even a working definition of it, not to speak of the nature and magnitude of the problem it seeks to address. It could be that the concept is too well known to bear any repetition. However, the available literature does not bear this out. Some important interpretations in the available literature are:y The World Bank has stated that inclusive economic growth can be achieved by “focusing on expanding the regional scope of eco-nomic growth, expanding access to assets and thriving markets and expanding equity in the opportunities for the next genera-tion of Indian citizens no matter who they are or where they live” [p xiv, World Bank 2006]. y Sen (2007) sets a necessary condition for inclusive growth in that the disparity in per worker income between agriculture and non-agriculture should not widen. y Besley et al (2007) use growth elasticity of poverty as measures to assess inclusiveness of the poor in the growth process. y The deputy chairman of the Planning Commission provides the following interpretations: (i) “Achieving a growth process inwhich people in different walks in life…feel that they too benefit significantly from the process” [Business Standard 2007], and(ii) “Poverty was one-dimensional, but lack of inclusion now is multidimensional and interlinked with regional and caste issues…The Plan is no longer about a model, it is now about pull-ing together a whole lot of forces and impulses... An Inclusive Strategy should provide for health, education and agriculture” [cited inSensex 2007].y Experts have started providing their own versions of inclusive growth. The prevailing confusion becomes apparent when experts propose their own definitions in term of combinations of a subset of operational strategies for “Opportunities, Empower-ment and Security” as recommended by the World Bank (2000). y TheUNDP defines inclusive growth by laying emphasis on the production and income side of the gross domestic product as “the process and the outcome where all groups of people have partici-pated in the organisation of growth and have benefited equitably from it. Thus inclusive growth represents an equation – with organisation on the left-hand side and benefits on the right-hand side” [UNDP 2008: 2].However, the government of India provides its own outcome presentation (but not evaluation) of inclusive growth in the Eco-nomic Survey of 2007-2008 under the sub-title ‘Poverty and Inclu-sive Growth’ [GoI 2008: 241-45]: (i) The survey does not define the concept of inclusive growth but distinguishes between con-sumption data sets based on different recall periods and examines their comparability. It only presents comparable estimates of pov-erty for rural India, urban India and all (rural-urban combined) India from alternative data sets. (ii) It does not define vulnerability or its source but states that “vulnerability is a relative term”. Vulnerability could be “gauged from the consumption patterns (in the absence of a better alternative)” (ibid: 243). A “higher” budget weight for food items is interpreted to indicate vulnerability. It is not clear how it is decided that there is no better alternative. The survey does not specify the norm used for deciding a higher budget weight and the source for vulnerability. (iii) It presents descriptive statistics on consumption patterns without interpreting them or drawing any inference (ibid: 243-44). (iv) It also provides esti-mates of compound annual growth rates of real consumption for different percentile groups of population in rural and urban India between 1993-94 and 2004-05. (v) It examines the rural and urban temporal changes in terms of mean-based averages, though they are not robust measures for skewed distributions, and (vi) It does not draw any inference or carry out any evaluation; nor does it make any policy recommendation.In other words, the issue raises both conceptual and metho-dological questions. How robust is a mean-based average as a measure of broad-based growth?2 Is there any better alternative? Given a better alternative measure, how does one measure inclusion? Therefore, it is important to define the concept and chart an approach to outcome evaluation at least from an ex postperspective.32 An Ex Post PerspectiveStudies generally verify growth performance or welfare improve-ment in terms of mean-based averages of income/consumption.4 Government of India (2008) too follows such an approach. It may not be appropriate to verify and assess broad-based growth in terms of mean-based averages for the reason already mentioned.5 Any outcome evaluation of inclusive growth, which is not even Table 1: Measures of Inclusion: A Singular Perspective (All India Rural and Urban Sectors Combined)Measure/Variable 1993-942004-05Per capita net national product (Rs at 1999/2000 prices) 12,207.00 19,325.00Monthly mean per capita consumption (Rs at 1993/94 prices) 325.18 373.67Monthly median per capita consumption (Rs at 1993/94 prices) 258.59 277.37Excess of mean over median per capita consumption (%) 25.75 34.72Elasticity of mean consumption with reference to mean income (η) -0.26Elasticity of median consumption with reference to mean consumption (ε) -0.49Inclusion coefficient (ψ) 0.750.74Coefficient of broad-based welfare(γ) 0.610.59Notes: (a) The NAS estimates of per capita net national product at 1999/2000 prices were derived using implicit deflators worked out using data in Table 1.1 [Government of India 2008: A-3]. (b) The NSS estimates of consumption at 1993/94 prices were worked out using price deflators implicit in the poverty lines published by the Planning Commission. (c) The estimates of elasticity of median consumption with respect to mean consumption (ε) (for the year 2004-05) for three different social groups for which data are available are as follows: 0.00 for the STs, 0.63 for the SCs and 0.48 for “Other Social Groups”, which includes the OBCs and the Others. (d) The percentage difference between mean and median with median as the base increased from 19 to 22 per cent for the STs, 17 to 23 per cent for the SCs and 27 to 37 per cent for Others. These estimates are not reported in the tables to conserve space but area available with the author. (e) For details on coefficient of broad based welfare(γ), refer footnote 9.Table 2: Descriptive Statistics: A Select Profile for All-India Consumption Distributions (Rural and Urban) 2004-05 Median Mean % Overestimation Disparity: % with Respect Bowley’s (Rs per capita per by Mean over to Average for the STs Coefficient of month at current prices) Median MedianMeanSkewness(bs)Rural All-India ST 366.50 426.20 16.29 0.00 0.00 0.22SC 406.30 474.70 16.83 110.86 111.38 0.20OBC 457.90 556.70 21.58 124.94 130.62 0.19Others 547.60 685.30 25.15 149.41 160.79 0.20Total population 455.80 558.80 22.60 --0.20Urban All-India ST 721.20 857.50 18.90 0.00 0.00 0.12SC 610.80 758.40 24.17 84.69 88.44 0.25OBC 685.70 870.90 27.01 95.08 101.56 0.25Others 992.80 1306.10 31.56 137.66 152.31 0.22Total population 792.20 1052.40 32.85 --0.25Source: Author’s estimates based on the NSS unit record data.
SPECIAL ARTICLEEconomic & Political Weekly EPW october 25, 200895defined in terms of input, output or outcome measures, is any-body’s guess. Negative covariance between mean-based averages of income/consumption and incidence of poverty, as generally done in empirical studies, cannot be taken as evidence of inclu-sion or lack of it. This is because time series estimates of absolute poverty, measured as the proportion of population living below the subsistence minimum, which is kept invariant, will provide little clue as to how far the status of the poor covaried with the growth process, however measured, of the economy.62.1 Concept and Measure As already noted, there is little by way of conceptual clarity and corresponding empirical evidence on verifying whether the observed growth process is broad-based and inclusive. For reasons cited in the preceding sections, we propose to make a departure from the existing studies.In an ideal set-up, we would prefer to characterise a broad- based growth process as one wherein there is all-round improve-ment as reflected in the three alternative perspectives of macro- economy, viz, production, income and expenditure. We propose to measure all-round improvement in terms of a robust order-based average like the median. We would prefer to define inclu-sion (participation) of the relatively deprived in such a growth process with reference to the order-based average of the outcome measure only, that is, assess their economic status with reference to a threshold, specified as a function of the median. By “inclusive growth”, we intend to convey the idea that the growth process under review or being proposed is such that it has benefited even those sections that are deprived of both physical and human asset endowments and hence, generally belong to the bottom rungs of income distribution and are incapable of partici-pating/benefiting from the growth process. Thus, the definition of the concept presupposes the identification of the set of deprived that cannot and hence, does not (i) participate effectively in the production process; (ii) benefit from it in terms of income gener-ated; and (iii) experience welfare improvements as measured by consumption. At the same time, in order to verify whether this deprived set has benefited/participated in the programme, it is important to ensure that the norm used for its identification is also related to some measure of economic performance so that categorical statements about their participation or otherwise in the process can be made. If so, an absolute norm for identification of the poor may not constitute an appropriate approach. Instead, it has to be the one relative to the average economic performance or level of the economy, which may be measured in terms of a rank-order based median to ensure robustness. Towards this end, we define the set of deprived as given by:θ = F(δξ.50) = ∫oδξ.50 f(x)dx …(1)where θ = incidence of the deprived.0<δ< 1 (We choose 0.6 as the value for δ following international con-vention for relative poverty)7; and ξ .50 such thatξ.50 1 ∞∫ f(x)dx = — = ∫ f(x)dx …(2)o 2 ξ.50F is the cumulative distribution function.f(x) is the density function of the variable concerned.Some important features and implications are as follows:* It is well known that θ lies in the open interval (0, 0.5). ¶(i)θ tends to 0 as the bottom half of the distribution getsconcentrated in the interval, “inclusion zone”, given by [δξ.50, ξ.50]; and ¶ (ii) It approaches 0.5 when its concentration is in the interval, what may be called the “exclusion zone”, given by [0,δξ.50].8* From a conceptual perspective, ¶Case (i) represents a situation wherein the growth process is inclusive with the poor participating in the growth process and hence, experience an improvement in their economic lot; and ¶Case (ii) emerges when the growth process is exclusive with little/negative participation by the poor such that there is a slide in their economic position.* Hence, whether the economic process under review is inclu-sive or exclusive could be defined and measured with reference to the concentration of the distribution in/out of the “inclusion zone” given by the interval [δξ.50, ξ.50], which should get reflected in variations inθ.* Given this conceptual framework, a “Coefficient of Inclusion or Poor Participation” may be defined by suitable normalisation with reference to its bounds as described below:2.1.1 Inclusion in a Singular SocietyThis section proposes an inclusive measure for the bottom half of the population in a singular society characterised by a single homogeneous social group.(i) We define an “Inclusive Coefficient” (IC) in terms of ‘ψ’ given by δξ.50ψ = 1 – 2∫ f(x)dx …(3) oTable 3: Percentiles of Consumption Distributions for Different Social Groups: All-India (Rural and Urban) (2004-05)(Rs per capita per month at current prices)Percentiles p50 p75 p95 p99Rural India ST 366.50503.34809.001301.33SC 406.33541.00900.331549.80OBC 457.88619.861119.002068.75Others 547.60760.001424.062799.13As % of corresponding percentile for the ST population ST 100100100100SC 110.87107.48111.29119.09OBC 124.93123.15138.32158.97Others 149.41150.99176.03215.10Urban India ST 721.201062.142014.882776.50SC 610.83900.831671.002905.42OBC 685.671006.751917.253365.40Others 992.83 1525.42 3130.13 6226.25As % of corresponding percentile for the ST population ST 100.00100100100SC 84.7084.8182.93104.64OBC 95.0794.7895.15121.21Others 137.66143.62155.35224.25Source: Author’s estimates based on the NSS unit record data.
SPECIAL ARTICLEoctober 25, 2008 EPW Economic & Political Weekly96where 0 < δ < 1 and ξ.50 such thatξ.50 1 ∞∫ f(x)dx = — = ∫ f(x)dxo 2 ξ.50where 0 < ψ < 1. In this study, we assign 0.6 as the value for δ. It has the following relevant properties:(a) When the “number of relatively poor” partici-pating and hence, benefiting from the mainstream economic process is nil,ψ will tend to the value 0; it will approach unity, as the set of beneficiary poor tends to exhaust the set of all relatively poor.(b) Any value greater than ½ for ψ, would indicate a situation where the proportion of the bottom half of the population falling in the inclusion zone or the mainstream is more than the proportion in the relative deprivation-zone, implying a scenario of inclusion. (c) Progressive improvement inψ and its positive covariance with median income/consumption would indicate inclusive growth; a constant ψ would imply perpetuation of status quo and a decline inψ with negative covariance with median income/consump-tion would be evidence of exclusion.(d) Being a rank-order based measure, it will reflect the deterioration/amelioration in the lot of the bottom half of the population satisfactorily. For the very same feature, it suffers from the limitation that the measure is not additive and hence, not decomposable.However, in the absence of comprehensive and related information on production (in particular) and income accounts, one would not be able to estimate and examine order-based averages and inclusion coefficients for these dimensions but only for house-hold consumption distribution. Hence, this paper pro-poses to cover at least the income dimension (for which information could be obtained from the National Accounts Statistics (NAS)) with reference to covariation between growth in income and consump-tion, and measure of inclusion in consumption. In other words, profiles of inclusion could be examined to some extent by examining mean-based estimate of average income and consumption, and order-based estimates of inclusion in consumption distribution. The relevant measures could be as follows: (i) Elasticity of mean consumption with reference to mean income (η), which would indicate, from an economic perspec-tive, whether growth in income is really broad-based and inclu-sive since if growth were concentrated at the top, even mean con-sumption would not increase at a corresponding rate and η would be less than unity. Elasticity of mean consumption with reference to mean income (η) =∂μc/μc , ∂μy/μywhere μc and μy stand for mean consumption and mean income respectively.(ii) Elasticity of median consumption with reference to mean consumption (ε) where(ε) = ∂ξ50/ξ50 . A value for ε > 1, would imply a scenario ∂μc/μcapproaching broad-based growth. This would further corrobo-rate the results on inclusive growth based on estimates of η; and(iii) Inclusion coefficient for consumption distribution (ψ).92.1.2 Inclusion in a Plural SocietyThis section provides a generalisation of the inclusion measure presented in the preceding section for a plural society for the following reasons:(i) Countries like India have a plural society, that is, a society consisting of different groups like the scheduled castes (SCs), scheduled tribes (STs), other backward classes (OBCs) and other social groups called “Others”.10 For historical reasons, in India these social groups differ with respect to mean as well as distri-bution of economic welfare, however measured. For instance, in Table 4: Estimates of Broad-Based Averages: Rural Sector 2004-05State Median Per Capita Consumption (Rs per 30 days) % Difference with Respect to Overall Median ST SCOBCOthersOverallST SCOBCOthersAndhra Pradesh 360.83 435.50 488.10 598.25 488.88 -26.19 -10.92 -0.16 22.37Assam 547.14478.33525.09497.67 514.716.30-7.07 2.02 -3.31Bihar 348.75320.86390.83467.58379.75-8.16-15.512.9223.13Chhattisgarh 310.00371.60367.16391.69345.33-10.237.616.3213.42Gujarat 422.71463.27481.64698.94508.67-16.90-8.93-5.3137.41Haryana 1087.50517.80636.11858.00673.7161.42-23.14-5.5827.35Jharkhand 351.03337.33399.83414.85378.50-7.26-10.885.649.60Karnataka 395.67371.25424.42464.00425.55-7.02-12.76-0.279.04Kerala 438.25584.32723.80890.15744.58-41.14-21.52-2.7919.55Madhya Pradesh 305.63 350.33 401.00 508.30 377.33 -19.00 -7.16 6.27 34.71Maharashtra 331.83384.65468.67539.72459.08-27.72-16.212.0917.57Orissa 250.07326.50366.33430.10335.25-25.41-2.619.2728.29Punjab 578.67552.13655.83902.06693.42-16.55-20.38-5.4230.09Rajasthan 434.92454.33548.29581.33515.14-15.57-11.806.4412.85Tamil Nadu 435.13 411.33 495.40 694.36 469.63 -7.35 -12.41 5.49 47.85Uttar Pradesh 421.67 385.75 440.33 513.79 437.00 -3.51 -11.73 0.76 17.57West Bengal 406.14 462.13 525.50 484.55 475.00 -14.50 -2.71 10.63 2.01All India 366.50 406.33 457.88 547.60 455.75 -19.58 -10.84 0.47 20.15Source: Author’s estimates based on the NSS unit record data.Table 5: Estimates of Broad-Based Averages: Urban Sector 2004-05State Median Per Capita Consumption (Rs per 30 days) % Difference with Respect to Overall Median ST SCOBCOthersOverallST SCOBCOthersAndhra Pradesh 520.50 647.63 700.25 883.31 748.35 -30.45 -13.46 -6.43 18.03Assam 759.00699.88786.25942.67899.40-15.61-22.18-12.584.81Bihar 392.45 376.58495.25824.29541.75-27.56-30.49 -8.58 52.15Chhattisgarh 712.75491.00523.031016.63698.252.08-29.68-25.0945.60Gujarat 751.88817.92671.801086.05932.88-19.40-12.32-27.9916.42Haryana 1198.56607.00677.501090.20871.4037.54-30.34-22.2525.11Karnataka 507.01595.58679.331009.36763.68-33.61-22.01-11.0532.17Kerala 2267.25 630.67 841.461303.42 903.12151.05-30.17-6.83 44.32Madhya Pradesh 607.10 461.43 534.60 875.00 641.90 -5.42 -28.11 -16.72 36.31Maharashtra 748.65729.96800.80981.07863.90-13.34-15.50-7.3013.56Orissa 425.50399.40541.38747.08579.50-26.57-31.08-6.5828.92Punjab 704.67678.25839.751221.80929.30-24.17-27.01-9.6431.48Rajasthan 848.86 525.00665.40935.33708.2119.86 -25.87 -6.04 32.07Tamil Nadu 1021.02 594.43 810.63 1554.03 819.37 24.61 -27.45 -1.07 89.66Uttar Pradesh 623.57 512.98 567.52 794.80 636.50 -2.03 -19.41 -10.84 24.87West Bengal 640.94 603.03 730.67 940.44 833.25 -23.08 -27.63 -12.31 12.86All India 721.20 610.83 685.67 992.83 792.17 -8.96 -22.89 -13.44 25.33Source: Author’s estimates based on the NSS unit record data.
SPECIAL ARTICLEEconomic & Political Weekly EPW october 25, 200897India SCs and STs constitute the socially vulnerable and economically backward classes. (ii) In pursuit of social welfare, governments pursue both mainstream economic policies and targeted welfare programmes to uplift the generally backward classes. (iii) But, for reasons like TypeI and TypeII errors, even the targeted pro-grammes do not end up providing for a general improvement of the back-ward social groups.11 As a result, there are situations when only a subsection of the backward communities get included in the mainstream/benefited from welfare programmes. (iv) There-fore, inclusion in a plural society has two dimensions: (a) inter-group and (b) intra-group. Inter-group dimen-sion could be examined with refer-ence to differences/disparities in median levels of income/consumption expenditure across social groups while the intra-group dimension could be examined in terms of inclusion coefficients (ICs) defined with respect to group-specific as well as overall median. Some details about these measures are:(1) Inter-group inclusion as measured by proximity of sub-group-specific median (ξS.50) to overall median (of the total/mainstream population, i e, all subgroups inclusive given by ξM.50).12 For a given δ such that (0 <δ < 1), there can be two situations: (a) Case (a)ξS.50 < δξM.50 implies exclusion of the subgroup, and (b) Case (b) ξS.50 ≥ δ ξM.50 would imply inclusion of the subgroup concerned.(2) Intra-group inclusion for any given social group ‘i’ could be measured with respect to either own median (ξS.50) providing a measure of ψiS (that is, IC-subgroup) or overall median (ξM.50) providing a measure of ψiM (that is, IC-mainstream). These two measures would (a) be distinct and different for situations when there is inter-group exclusion; and (b) converge with progressive inter-group inclusion: (a)IC-subgroup (ψiS) would measure the extent of inclusion of the bottom half of the subgroup under review in its own progress.(b) IC-mainstream (ψiM) would measure the extent of inclusion of the bottom half of the subgroup under review in the progress of the country/society as a whole. The limits for IC-mainstream (ψiM) are: ψiM = (-) 1 implies perfect exclusion of the subgroup, and ψiM = 1 implies perfect inclusion of the entire subgroup.(3) IC index in a Plural Society: The ratio (ωi) of IC-mainstream (ψiM) to IC-subgroup (ψiS) for a given social subgroup ‘i’ would provide a measure of its inclusion from an integrated perspective: ψiMωi = … (4) ψiSwhere ‘ψiM ’ = IC-mainstream is defined with respect to median of the total population (ξM.50), and ‘ψiS’ = IC-subgroup is defined with respect to median of the social group population (ξS.50).The conceptual limits for the IC index (ω) are:ω = (-) infinity implies perfect intra-and inter-exclusion, and ω = infinity implies perfect intra-exclusion and inter-inclusion of the entire subgroup.(4) For situations when ξS.50 < δξM.50, a comprehensive measure of inclusion for the entire (as against for the bot-tom half) social subgroup ‘i’ popula-tion in the mainstream would be indicated by the β-measure given by:βi = ½ (1 + ψiM) …(5)where 0≤βi≤ 1. The β-measure indicates the pro-portion of the subgroup population participating/included in the growth process as reflected in outcome measures like consumer expenditure distribution. Its limiting values will be zero and one; it will be zero when the entire social subgroup is excluded from the mainstream and unity, otherwise.3 EmpiricalIllustrationforIndiaThe following sections offer illustrations for India.3.1 A Uniform Perspective on the NationThis subsection provides estimates of elasticity measures for mean and median consumer expenditure between 1993-94 and 2004-05 and the coefficient of inclusion for consumer expendi-ture distribution in 2004-05 for India as a whole (rural and urban sectors combined). The estimates of income from the National Sample Survey (NsS) refer to the financial year and those for consumption are from the NSS corresponding to the agricultural year. In addition to the differences in period, other factors like concept, design and methods of estimation render their direct comparison difficult. Hence, these estimates are provided in Table 1 (p 94) largely for illustration: (i) Between 1993-94 and 2004-05, per capita income in India increased by 58.31 per cent. However, the corresponding increase in (mean) per capita consumer expenditure has not been equi-proportionate. It increased by 14.91 per cent implying an elasticity coefficient of 0.26. (ii) This limited increase in consumption was not broad based. Median consumption did not increase to the same extent; the extent of increase in median consumption (7.26 per cent) was less than half of that in mean consumption. The estimate of elasti-city of median consumption with respect to mean consumption, as a result, turned out to be 0.49, which is less than unity imply-ing that the country has not made much progress on realising the benefits of growth in terms of welfare distribution. This is reflected in estimates of mean relative to median consumption; Table 6: Inclusion Coefficient and the Median by Sector: Major StatesStates Inclusion Coefficient Median of Monthly Per Capita Expenditure RuralUrbanRuralUrbanAndhra Pradesh 0.79 0.71 488.88 748.35Assam 0.850.59514.71899.40Bihar 0.900.75379.75541.75Chattisgarh 0.830.53345.33698.25Gujarat 0.790.72508.67932.88Haryana 0.750.69673.71871.40Jharkhand 0.880.53378.50807.33Karnataka 0.910.67425.55763.68Kerala 0.700.63744.58903.12Madhya Pradesh 0.81 0.67 377.33 641.90Maharashtra 0.770.62459.08863.90Orissa 0.790.65335.25579.50Punjab 0.810.68693.42929.30Rajasthan 0.860.72515.14708.21Tamil Nadu 0.85 0.68 469.63 819.37Uttar Pradesh 0.84 0.69 437.00 636.50West Bengal 0.84 0.59 475.00 833.25All States 0.79 0.63 455.75 792.17Source: Author’s estimates based on the NSS unit record data.
SPECIAL ARTICLEoctober 25, 2008 EPW Economic & Political Weekly98the percentage difference with respect to median increased from 26 to 35 per cent, that is, by nine points between 1993-94 and 200-405; corresponding percentage point increase was three for the STs, six for the SCs and 10 for the Others.(iii) The coefficient of inclusion, however, is 0.74, which is greater than 0.5 implying thereby that the dominant fraction of the bottom half of the popula-tion falls in the inclusion zone as defined with respect to the median. Since the median itself has not kept pace with the mean, it would only imply that growth is not broad-based but limited to the top few. 3.2 Perspectives on the FederationThe following section presents estimates of measures of broad-based averages based on the latest available NSS data set on consumption distribution for the year 2004- LevelsGiven the framework described above, the question of broad-based growth for India, a plural society con-sisting of different social groups, could be examined in terms of social group specific as well overall (all social groups combined) median and the correspond-ingICs. For this purpose, the following social groups (for which data are available) are considered: STs, SCs, OBCs and Others. To begin with, the general levels of welfare across social groups in absolute as well as relative terms for all-India could be examined in terms of Tables 2 (p 94) to 3 (p 95) respectively. The salient features are:13y The consumer expenditure distributions for all the social groups as well as for the total population are posi-tively skewed in both rural and urban sectors (Table 2). y The profile for thickness of tails with reference to the 99th percentile, which is a measure of incidence of extreme values of the consumption distribution for the different social groups is as follows: thickness of tails for Others social group is higher than that for the OBCs, which is higher than that for theSCs; which in turn is higher than that for theSTs in both rural and urban all-India (Table 3). y It goes without saying that mean-based averages, under the influence of extreme values, would mislead regarding location. Accordingly, mean estimate exceeds themedian by a larger margin for the SCs than for the STs, for the OBCs than for the SCs, and for the Others than for the OBCs both in rural and urban sectors.14 This would imply that any comparison of levels of average welfare across social groups based on mean-based aver-ages would overstate the extent of inter-social-group disparities as shown in Table 2. Between rural and urban sectors, the rela-tive overestimation is higher in the urban than in the rural sector. Across states, contrary to the general perception, the percentage excess of mean over median is the highest for Kerala in both the rural (36 per cent) and the urban (43 per cent) sectors.15Therefore, the following discussion is based on median and related order-based statistics.(i) Rural Sector: As one would expect of the general levels of liv-ing in rural all-India, the average consumption levels, as repre-sented by the median, for the STs are lower than that of SCs which in turn are below that for theOBCs. Though the OBC median is less than that of the Others, it is about equal to the overall median for the total rural population. This pattern does not hold good uniformly across states (Table 4, p 96). For instance: (a) STs are better off than even the Others in Assam; (b)STs’ median con-sumption levels fall short of the corresponding overall median by Table 8: Inclusion Coefficients by Social Groups: Major States (Urban)States STs SCs OBCs Others IC-SIC-Mω IC-SIC-Mω IC-SIC-Mω IC-SIC-MωAndhra Pradesh ---0.85 0.57 0.68 0.81 0.74 0.92 0.63 0.77 1.23Assam 0.84 0.38 0.45 0.85 0.27 0.31 0.68 0.51 0.75 0.70 0.72 1.03Bihar ---0.91 0.25 0.27 0.87 0.78 0.90 0.54 0.86 1.60Chattisgarh 0.37 0.37 1.01 0.73 0.23 0.32 0.86 0.46 0.53 0.51 0.82 1.60Gujarat 0.71 0.52 0.73 0.75 0.64 0.86 0.90 0.49 0.55 0.70 0.85 1.22Haryana ---0.68 0.33 0.49 0.75 0.54 0.71 0.73 0.88 1.20Jharkhand 0.83 0.03 0.04 0.95 -0.05 -0.05 0.72 0.58 0.79 0.59 0.79 1.35Karnataka ---0.66 0.38 0.57 0.69 0.59 0.86 0.57 0.83 1.46Kerala ---0.81 0.36 0.44 0.63 0.57 0.89 0.60 0.86 1.45MadhyaPradesh 0.48 0.46 0.97 0.78 0.34 0.44 0.80 0.57 0.71 0.67 0.92 1.37Maharashtra ---0.58 0.45 0.77 0.68 0.62 0.91 0.57 0.68 1.20Orissa 0.72 0.38 0.53 0.74 0.34 0.46 0.70 0.59 0.85 0.56 0.83 1.49Punjab ---0.92 0.40 0.44 0.76 0.66 0.86 0.65 0.83 1.28Rajasthan ---0.86 0.44 0.52 0.77 0.71 0.92 0.58 0.89 1.52Tamil Nadu ---0.84 0.39 0.46 0.72 0.71 0.99 0.59 0.88 1.51Uttar Pradesh ---0.80 0.48 0.61 0.74 0.62 0.83 0.63 0.84 1.34West Bengal ---0.79 0.31 0.39 ---0.57 0.67 1.18All India 0.55 0.45 0.82 0.73 0.39 0.53 0.71 0.54 0.77 0.59 0.78 1.32IC estimates have not been reported for states where the corresponding population share of the social group concerned is less than 5 per cent.IC-S = IC-subgroup; IC-M=IC-mainstream .Source: Author’s estimates based on the NSS unit record data. Table 7: Inclusion Coefficients by Social Groups: Major States (Rural)States STs SCs OBCs Others IC-SIC-Mω IC-SIC-Mω IC-SIC-Mω IC-SIC-MωAndhra Pradesh 0.78 0.43 0.55 0.83 0.69 0.83 0.83 0.83 1.00 0.78 0.92 1.19Assam 0.90 0.94 1.04 0.88 0.81 0.92 0.84 0.87 1.04 0.87 0.82 0.95Bihar ---0.98 0.83 0.84 0.89 0.91 1.02 0.86 0.98 1.15Chhattisgarh 0.80 0.73 0.91 0.87 0.90 1.04 0.83 0.87 1.05 0.86 0.93 1.08Gujarat 0.74 0.58 0.78 0.89 0.80 0.89 0.86 0.80 0.93 0.77 0.97 1.26Haryana ---0.82 0.52 0.63 0.82 0.74 0.90 0.83 0.93 1.12Jharkhand 0.90 0.82 0.91 0.93 0.77 0.83 0.92 0.94 1.02 0.83 0.89 1.07Karnataka 0.97 0.95 0.98 0.97 0.84 0.87 0.90 0.90 1.00 0.93 0.96 1.04Kerala ---0.84 0.53 0.63 0.71 0.69 0.97 0.71 0.84 1.19MadhyaPradesh 0.90 0.65 0.72 0.80 0.75 0.93 0.84 0.88 1.05 0.85 0.95 1.13Maharashtra 0.85 0.43 0.51 0.82 0.64 0.78 0.84 0.86 1.02 0.76 0.86 1.14Orissa 0.86 0.50 0.58 0.81 0.78 0.97 0.83 0.90 1.09 0.85 0.95 1.12Punjab ---0.95 0.70 0.74 0.84 0.79 0.95 0.83 0.95 1.14Rajasthan 0.92 0.71 0.77 0.87 0.77 0.88 0.87 0.90 1.04 0.89 0.97 1.09Tamil Nadu ---0.89 0.81 0.90 0.81 0.86 1.06 0.49 0.78 1.59Uttar Pradesh ---0.89 0.76 0.85 0.83 0.84 1.01 0.80 0.91 1.14West Bengal 0.91 0.75 0.82 0.90 0.88 0.97 0.81 0.87 1.08 0.82 0.84 1.02All states 0.79 0.31 0.39 0.84 0.53 0.63 0.82 0.68 0.84 0.78 0.83 1.06IC estimates have not been reported for states where the corresponding population share of the social group concerned is less than 5 per cent.IC-S = IC-subgroup; IC-M=IC-mainstream.Source: Author’s estimates based on the NSS unit record data.
SPECIAL ARTICLEEconomic & Political Weekly EPW october 25, 200899more than 20 per cent (which is the average shortfall at the national level) in the states of Maharashtra and Orissa; and (c) TheOBCs are doing better than the Others in Assam and West Bengal. In other words, at least from an economic outcome per-spective,the profile across social groups is not uniform across states in thecountry.By our criterion, STs as a subgroup are excluded from the main-stream in rural Kerala. This may be because with a demographic share of less than 2 per cent, it is not empowered. (ii) Urban Sector: The ordinal ranking of SCs,OBCs and Others in terms of median is the same as that observed for the rural sector. However, the general levels of living of the STs are higher than that of bothSCs and OBCs.16 Unlike the rural scenario, OBCs in the urban sector have not caught up with the mainstream average and fall short of it by about 13 per cent. Across states, (a) SCs are worse off in a majority of states (Bihar, Chhattisgarh, Haryana, Jharkhand, Kerala, Madhya Pradesh, Orissa, Punjab, Rajasthan, Tamil Nadu and West Bengal), where the shortfall is greater than that in the national average. (b) OBCs also fall short of the mainstream across all states. To be noted are Chhattisgarh, Gujarat, Haryana, Jharkhand and Madhya Pradesh where the shortfall is greater than at the national level, and (c) SCs are an excluded subgroup in urban Jharkhand.3.2.2 A Uniform Perspective on the FederationSince the country has only begun its pursuit of (undefined) inclu-sive growth, we would not present any time series estimates of ICs and its evaluation. Instead we prefer to present estimates of ICs based on the latest available NSS data set on consumption dis-tribution for 2004-05 and interpret them.17 Table 6 (p 97) presents an aggregate profile by sector across states in India. The major features are: (i) IC at the national level is 0.79 for the rural sector and 0.63for the urban, which implies that the extent of inclusion is greater in the rural than in the urban sector at the all-India level. (ii) Across states, the extent of inclusion of the deprived in the rural growth process is one of the highest (greater than 90 per cent) in the states of Bihar and Karnataka, and the lowest in Kerala. (iii) As regards the urban sector, the IC is the highest in Biharand lowest in Chhattisgarh and Jharkhand (0.53). (iv) Consistent with the all-India profile, the estimates of IC are generally higher for the rural sec-tor than for the urban across states. (v) As regards the rural sectors of the BIMAROU states, the ICs are gener-ally as high as the all-India average. However, the extent of inclusion in the urban sectors of Chhattis-garh and Jharkhand is much less than the all-India average. (vi) There are interstate variations inICs both in rural and urban sector; the range is higher for the urban than for the rural sector. (vii) To examine whether the states with higher median also have rela-tively high inclusion, we estimate the rank correlation between the median monthly per capita consumer expenditure (MPCE) and the IC separately for each sector, which was found to be negative and insignificant for both rural ((-). 28) and the urban sector ((-).14). This indicates that both medianMPCE and the IC are weakly associated across states. In other words, states with higher medianMPCE need not have higher inclusion and vice versa. 3.2.3 A Plural Perspective on the FederationGiven the contemporary interest in disparities across social groups and the policy emphasis on inclusion of the socially dis-advantaged groups like theSCs and STs, it would be of interest to examine the extent of inclusion with respect to social group specific as well as overall averages. The corresponding estimates for the rural and urban sectors are presented in Tables 7 and 8 (p 98) respectively.In the rural sector (i) intra-group inclusion as defined with respect to the social group specific median (IC-subgroup) is high (more than 75 per cent) for all social groups in rural all-India. This would imply that more than three-fourths of the bottom half of the population fall outside the relative deprivation zone defined with respect to their own subgroup progress, (ii) How-ever, consistent with the profile of the median across social groups in rural all-India, the extent of inclusion with respect to the mainstream (total economy as a whole) – (IC-mainstream) is the highest for Others, followed byOBCs,SCs and STs respectively (Table 7). The IC with respect to the overall median (IC-main-stream) is just about one-third for the STs implying that just that much of the bottom half of the ST population in rural all-India enjoys levels of living in the neighbourhood of the mainstream population, (iii) The SCs are slightly better off in the sense that about half of the bottom half of their population is in the main-stream-inclusion zone (as defined by the mainstream average or IC-mainstream), (iv) However, this pattern does not hold good uniformly across states for the rural sector. For instance, IC-mainstream for the STs is more than 90 per cent and it is higher than those for theSCs and even the OBCs in the states of Assam and Karnataka; in Assam it is higher than that for the Others also, Table 9: Percentage Distribution of Population by Social Groups: States and All-India (2004-05)States Rural Urban ST SC OBC Others All ST SC OBC Others AllAndhra Pradesh 8.55 19.51 47.62 24.32 100.00 2.54 14.9 44.68 37.88 100.00Assam 18.90 9.60 17.46 53.76 100.00 7.2913.15 18.94 60.36 100.00Bihar 0.5723.0259.9416.32100.000.6710.957.6430.33100.00Chhattisgarh 35.24 14.56 44.76 5.45100.0016.79 12.36 40.530.35 100.00Gujarat 20.4711.2144.7123.62100.003.939.0928.858.18100.00Haryana 0.2728.0132.2039.52100.000.3218.524.9856.2100.00Jharkhand 29.89 13.02 45.75 11.35 100.009.63 12.22 41.17 36.98 100.00Karnataka 8.3720.26 38.84 32.52 100.002.7012.73 39.38 45.19 100.00Kerala 1.9211.19 59.39 27.51 100.000.488.28 62.88 28.36 100.00Madhya Pradesh 25.84 18.16 40.08 15.93 100.00 6.11 14.86 37.3 41.73 100.00Maharashtra 13.6014.8335.7435.83100.003.1117.2223.7955.88100.00Orissa 25.64 17.58 39.40 17.33 100.009.0013.69 30.53 46.78 100.00Punjab 0.3840.0721.4338.12100.000.5927.1518.1854.08100.00Rajasthan 16.0620.9646.6016.38100.002.5720.8237.6338.98100.00Tamil Nadu 0.54 27.06 70.54 1.86 100.00 0.64 14.52 74.74 10.09 100.00Uttar Pradesh 0.49 25.40 54.64 19.37 100.00 0.45 13.65 45.37 40.53 100.00West Bengal 8.18 28.92 7.05 55.79 100.00 1.40 20.11 4.63 73.83 100.00All India 10.57 20.92 42.75 25.71 100.00 2.92 15.64 35.6 45.81 100.00Source: Government of India (2007a: 36).
SPECIAL ARTICLEEconomic & Political Weekly EPW october 25, 2008101Notes 1 The empirical illustration is based on the National Sample Survey (NSS) 61st round estimates of household per capita consumer expenditure (unit record data) for 17 major states of the Indian Union. For this purpose, a major state is defined as one with a population of more than 20 million as per the 2001 Census. 2 A mean-based/least squares estimator of average is not a robust measure for a skewed distribution like that of household/personal income/consumption and can often mislead Mukherjee et al (1998). Hence, it would make sense to use order-based measures for welfare appraisals using data on household/personal income/consumption dis-tributions. However, there is no option other than a mean-based estimator for average value added/per capita domestic product. But it is important to be aware of the limitations of such estimators. For instance, Maharashtra is one of the richest states in terms of per capita state domestic product. This does not mean that there is broad-based growth and the State on an average is doing well. This is because high levels of income generated in the four largely urban districts of Mumbai, Thane, Nagpur and Pune together generate more than or about 50 per cent of the income in Maharashtra while districts like Gadchiroli and Osmanabad have a percentage share each of less than 1 per cent [Government of Maharashtra 2002]. 3 In other words, just as deprivation is defined with reference to outcome measures like income/ consumer expenditure, we propose to define inclusion/exclusion in terms of an outcome meas-ure. The framework is based on the author’s study on mainstreaming the National Poverty Reduc-tion Strategy into the National Development Plan of Botswana [Suryanarayana 2008]. 4 For instance, the entire series of studies on agri-cultural growth and its trickle down effects is based on estimates of mean-based averages of agricultural income or consumption distribution. In addition, verification of trickle down is carried out largely in terms of mean-based regression estimators without verifying their appropriate-ness for the sample under review. For a very informative illustration on how inappropriate application of mean-based regression would result in misleading signs and estimates, see the Chapter on approach in Mukherjee et al (1998). 5 See footnote No 2.6 In the Indian context, this minimum has been kept invariant for more than half a century in spite of improvements in infrastructure, techno-logy, health and sanitation facilities, which would involve a reduction in energy requirement. How-ever, academic as well as policy pursuits of deter-minants of poverty have overlooked such empiri-cal details. 7 This approach would do away with price indices associated with updating the poverty lines for exercises of the sort presented in Government of India (2008). 8 In the literature this is called the relative depriva-tion zone. 9 In a corresponding fashion, one could consider a coefficient of broad-based income generation and distribution ‘γ’ with reference to median income/consumption for welfare evaluations where (2–δ)ξ.50 γ = ∫ f (x)dx where f(x) is the income/ δξ.50 consumption density function andγ lies in the interval (0,1). In an ideal scenario on broad-based growth that is inclusive,ψ andγwould converge. To verify whether the growth process is broad-based one might consider adjusting the median by taking the product of median andγ.10 For that matter, one could consider different occupations/regions/sectors/states instead of social groups.11 When a targeted welfare programme fails to reach/benefit the intended beneficiaries, it is called a Type I error. A Type II error refers to a situation when the programme benefits the unin-tended beneficiaries [Cornia and Stewart 1993]. 12 The mainstream median (ξM.50) may be defined with reference to different combinations of the social groups including as well as excluding the subgroup under review depending upon the con-text. For illustration purpose, we have considered the median of the total population here.13 The share of ST population in the rural sector is less than 10 per cent in Andhra Pradesh, Bihar, Haryana, Karnataka, Kerala, Punjab, Tamil Nadu, Uttar Pradesh and West Bengal (Table 9, p 99). Its corresponding share in the urban sector is less than 10 per cent in the major states considered here, except Chhattisgarh (Table 9). This fact may be noted while comparing levels of living across social groups. Hence, estimates for this social group are not considered for discussion for the urban sector at the state level.14 Between 1993-94 and 2004-05, this difference favouring the mean increased more for the Others than for the SCs in the rural and urban sectors separately as well as combined.15 Of course, the profile across sates differs among social groups; estimates are available with the author.16 It may be noted that estimated population share of STs in urban all-India is 2.92 per cent.17 For conceptual difficulties in defining and esti-mating per capita income at the state level by sec-tors, this section does not present estimates of elasticities discussed in section 3.1.ReferencesBesley, Timothy, Robin Burgess and Berta Esteve- Volart (2007): ‘The Policy Origins of Growth and Poverty in India’ in Timothy Besley and Lousie J Cord(eds),Delivering on the Promise of Pro-Poor Growth, Palgrave Macmillan and the World Bank, New York, pp 59-78.Bolt, Richard (2004): ‘Accelerating Agriculture and Rural Development for Inclusive Growth: Policy Implications for Developing Asia’, ERD Policy Brief No 29, Asian Development Bank, Manila.Business Standard (2007): ‘Montek Singh on Indian Economy and Reforms’, Interview in theBusiness Standard, June 29.Cornia, Giovanni Andrea and Frances Stewart (1993): ‘Two Errors of Targeting’,Journal of International Development, Vol 5, No 5, pp 459-96.Government of India (1981): A Technical Note on the Sixth Plan of India (1980-85), Perspective Planning Division, Planning Commission, New Delhi.– (2006): ‘Towards Faster and More Inclusive Growth: An Approach to the 11th Five Year Plan’, Planning Commission, New Delhi.–(2007a): ‘Household Consumer Expenditure among Socio-Economic Groups: 2004-2005 NSS 61st Round (July 2004-June 2005)’, Report No 514 (61/1.0/7), National Sample Survey Orgnisation, Ministry of Planning and Programme Implemen-tation, New Delhi.– (2007b): ‘Poverty Estimates for 2004-05’, Press Information Bureau, New Delhi, India. – (2008): Economic Survey 2007-2008, Ministry of Finance, New Delhi.Government of Maharashtra (2002):Human Develop-ment Report Maharashtra 2002, Government of Maharashtra, Mumbai.Mukherjee, Chandan, Howard White and Marc Wuyts (1998):Econometrics and Data Analysis for Devel-oping Countries, Routledge, London.Sen, Abhijit (2007): ‘Presidential Address Delivered at the 66th Annual Conference of the Indian Journal of Agricultural Economics’,Indian Journal of Agricultural Economics, 62, No 1, pp 1-12.Sensex (2007): ‘The Plan with a Difference’, Sensex, Vol 1, No 4, pp 36-40.Suryanarayana, M H (2008): ‘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.United Nations Development Programme (2008): ‘A Million Dollar Question: What Is Inclusive Growth?’, Report prepared by Uyanga Gankhuyag from a learning event orgnaised by the UNDP Learning Resource Centre,Poverty Reduction News Update, Issue No 13, UNDP.World Bank (2000):World Development Report 2000/2001: Attacking Poverty, Oxford University Press, New York. – (2006): India Inclusive Growth and Service Deliv-ery: Building on India’s Success, Report No: 34580-IN, World Bank, Washington.Bihar and Karnataka, (ii) The profile across social groups con-veys a different message. There is intra-group inclusion at the level of each and every social group (that is, the proportion of the bottom half of the population in each subgroup participating in its own growth is more than half) in both rural and urban sectors at the national level. However, the extent of inclusion in the mainstream in rural all-India is the least (one-third) for the STs, followed by the SCs (one-half), OBCs (0.68) and the Others (0.83), (iii) This pattern does not hold good uniformly across states for the rural sector. For instance, IC-mainstream for the STs is more than 90 per cent and higher than those for the SCs and even the OBCs in the states of Assam and Karnataka, (iv) In a similar way, IC-mainstream for the OBCs is higher than that for Others in the states of Assam, Jharkhand, Tamil Nadu and West Bengal, and (v)Intra-group as well as mainstream inclusion is the same for theOBCs in most of the states. In the urban sector, (i) inclusion is the highest in Bihar (0.75) and lowest in Chhattisgarh and Jharkhand (0.53), (ii) As regards the urban profile across social groups, intra-group inclusion is the highest for the SCs, followed by theOBCs, Others andSTs at the all-India level, (iii) IC-mainstream is lower in the urban sector than in the rural for the SCs and OBCs. In other words, these two social groups do not seem to have really caught up with the Others in the urbanisation process of economic development, and (iv)STs as a social subgroup have a very low IC-mainstream in Assam, Chhattisgarh, Jharkhand and Orissa.

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