losZ{k.kSARVEKSHANA

st91 IssueVol. XXVII No. 1 & 2

(July 2007)

Journal of

National Sample Survey Organisation

National Sample Survey OrganisationMinistry of Statistics & Programme Implementation

Government of IndiaNew Delhi

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Vol. XXVII

No.1&2

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SARVEKSHANA91st Issue

Vol. XXVII No. 1 & 2

Journal of

National Sample Survey Organisation

National Sample Survey OrganisationMinistry of Statistics & Programme Implementation

Government of IndiaNew Delhi

Printed at Bengal Offset Works, New Delhi

Journal of National Sample Survey Organisation

Editorial Advisory BoardProf. Dipankar Coondoo (Chairman)Prof. T.J. RaoProf. Ravi Srivastava, Centre for the Study of Regioinal Development, Jawahar Lal Nehru University,New Delhi.Dr. Manoj Panda, Indira Gandhi Institute of Development Research, A.K. Vaidhya Marg, Goregaon(East),Mumbai-400065.Shri S.K. Sinha, Director General & Chief Executive Officer, NSSO, Sardar Patel Bhavan, Sansad Marg,New Delhi-110001.Deputy Director General, Survey Design & Research Division, NSSO, 164, G.L.T. Road, MahalanobisBhavan, Kolkata.Deputy Director General, Coordination & Publication Division, NSSO, Sardar Patel Bhavan, Sansad Marg,New Delhi-110001 (Managing Editor)

Editorial Secretariat - Coordination and Publication Division, National Sample Survey Organisation,Sardar Patel Bhavan, New Delhi-110001.Mr. Ramkripal, DirectorMr. Bhupinder Kumar, S.S.O.Mr. S.A. Beg, J.I.

Frequency and Subscription‘Sarvekshana’ is published twice a year

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Manuscript Submission‘Sarvekshana’ is aimed at encouraging research and analysis of NSS data to bring about a deeper understanding ofsocio-economic development of the country. For details about manuscript submission refer to back of cover page.

Opinions expressed in 'Sravekshana' are those of the authors and not necessarily reflect the views or policies of theNSSO or the Government of India. NSSO is not responsible for the accuracy of the data and information included inthe technical papers nor does it accept any consequence for their use. Material in 'Sarvekshana' may be freely quotedwith appropriate acknowledgement and a copy of the publication sent to the Managing Editor.

Suggestions for improvement of the Journal may be addressed to:

The Managing Editor, Sarvekshana,Coordination and Publication DivisionNational Sample Survey OrganisationSardar Patel Bhawan, Sansad Marg, New Delhi.

SarvekshanaVol. XXVII No 1 & 2Issue No. 91

CONTENTS

PART – I : TECHNICAL PAPERS

Page1. IV Estimation of Engel Elasticities from Indian Household Budget Data 1-16

(Suchismita Bose (Ghose) and Nikhilesh Bhattacharya)

2. Disparities of living in rural India 17-20

(Tushar kanti Mitra, Tushar Kanti Ghara, Gouranga Sinha)

3. NSS Experience on the Pilot Survey on Non-Profit Institutions Serving Households 21-51

(G. C. Manna)

PART – II : SUMMARY AND MAJOR FINDINGS OF SURVEYS

4. An Integrated Summary of NSS 58th Round (July 2002 - December 2002) 54-90on "Disabled Persons in India"

(R N Pandey and A L Chatterjee)

5. An Integrated Summary of NSS 58th Round (July 2002 - December 2002) 91-110on "Village Facilities"

(Siladitya Chaudhuri)

6. An Integrated Summary of NSS 58th Round (July 2002 - December 2002) 111-129on "Condition of Urban Slums"

(Tapas Kumar Sanyal & Nilanjana Roy)

PART – III : HINDI SECTION

Hindi Section fg- 1 & fg- 13

PART - I

TECHNICAL PAPERS

SARVEKSHANA 1

IV Estimation of Engel Elasticities from Indian Household Budget Data*

Suchismita Bose (Ghose) Nikhilesh Bhattacharya

Abstract

This study experiments with Instrumental Variables (IV)estimation of engel elasticities of items like clothing, fromIndian National Sample Survey (NSSO) household budgetdata, in order to eliminate the effects of seasonal andother fluctuations affecting data collected for a shortreference period. Such data generally relate to a movingreference period of `30 days' preceding the date ofinterview (also referred to as the last month referenceperiod). The result being that seasonal and other short-run fluctuations thus get superimposed on the truevariation across households exaggerating the inequalityin the size distribution of population by per capita totalconsumer expenditure, the widely used measure of levelof living as well as other poverty measures. Further theuse of such a reference period introduces errors inobservation in both the regressor and the regressandleading to biased estimates in the standard method of engelcurve estimation. This problem has been largely ignoredin the econometric literature. In this paper the problem istreated in an errors-in-variables (EIV) framework.However, the standard techniques of dealing with the EIVproblem offer no easy solution in this case, especiallybecause the errors in the regressor and the regressandare correlated. The possibilities of Instrumental Variable(IV) estimation have been tried out. Instruments werechosen from item groups whose consumption is relativelyless affected by seasonal and short-run factors. Thoughthe choice among the IV's is not very clear, different IV'sgive a range of estimates which may cover the true

elasticity and which appear to be better than theconventional WLS estimates based on last month data.(JEL : C20,C21)

Correspondence to :Suchismita BoseICRA LtdA10&11, FMC Fortuna234/3A A.J.C. Bose RoadCalcutta--700 020 India phone: (91)(33)22406617fax : (91)(33)2247 0728email : suchismita_bose@hotmail.com

1. Introduction

The main motivation of the present study is to estimatethe engel elasticities of clothing and some other items ofconsumption, after eliminating the possible effects ofseasonality and other short-run fluctuations, from IndianNational Sample Survey (NSS) household budget datarelating to the `last month' reference period.

For its enquiries on household consumer expenditure, theNSS Organization generally employs a moving referenceperiod of `last 30 days' preceding the date of interview(`last month') and staggers the interviews evenly over thesurvey period, usually one year. Different householdsthus furnish information for different periods of 30 daysand this introduces seasonality and other short-run factorsinto the data for any particular household. While theaverage consumption over sample households gives a fairapproximation to annual levels of consumption, seasonal

* This paper is part of the Ph.D Thesis by Suchismita Ghose prepared under the supervision of Prof. N. Bhattacharya, at the IndianStatistical Institute. Thanks are due to the authorities of the NSS Organisation, Govt. of India, for permitting the use of updated tapescontaining NSS 38th round consumer expenditure data supplied to the Indian Statistical Institute, Calcutta. The authors are grateful toProfessor Angus Deaton for a major suggestion regarding the choice of IV. Helpful suggestions of Professor D. Coondoo, Dr.N. Sarkar andDr. M. Pal are gratefully acknowledged.

SARVEKSHANA2

and other short-run fluctuations get super-imposed on thetrue variation across households possibly distorting theengel curves, particularly for items like clothing whichare considerably affected by seasonality and othertransitory factors.

Friedman (1957) brought out the distortions thattransitory components of income and consumption mayproduce in empirical estimates of the consumptionfunction. As is well-known, Friedman treated thesetransitory components as errors-in-variables in a standardtwo-variable linear regression model (Malinvaud, 1972,chap 4; Johnston, 1963, chap.6, pp. 148-149).

Accounting periods shorter than one year are discussedin the literature on poverty and economic inequality, andit is recognized that income or consumption for shortperiods are unreliable indices of economic status(Atkinson, 1975, Chap.3; Deaton, 1994, pp. 25-27). Thedegree of inequality is exaggerated if such accountingperiods are used. Even one year may be rather short formeasurement of income inequality, because individualhouseholds are influenced by economic cycles and life-cycle factors.

While scientific information is by no means plentiful,household consumption is known to be strongly seasonalin India, mainly due to the influence of agriculture andthe cropping seasons on household incomes and prices1.Many poor households pass through lean periods withgreat difficulty and find much-needed relief in harvestingand post harvest months. Rural households tend to spendmore on food, clothing, footwear etc in post-harvestmonths which often overlap with months when many ofthe festivals and wedding ceremonies are held. Evenmedical treatment may be postponed till the householdhas some cash income. Expenditure on education showsseasonal variation because school fees tend to be paid inthe early months of the academic year.

That engel relations estimated from household budget datamay yield under-estimates of elasticities because of errorsof measurement in the determining variable was notedby Prais and Houthakker(1955, pp. 62-63) and theproblem was later dealt with by Liviatan (1961), Cramer(1969) and Deaton (1994). All these authors examinedthe matter in the light of various errors-in-variables (EIV)models. Clearly, when estimating engel relations fromhousehold budget data it is desirable to use annual incomeor total consumption expenditure as the determiningvariable rather than income or total expenditure from anyshorter time period (Deaton, 1994, pp. 25-27).

Unfortunately in India, as in many other LDC's, householdbudget data have to be collected by the interview method,because, quite often, households do not keep accounts ordiaries, and receipts from shops/vendors are generallynot available. The questionnaires are therefore filled upon the basis of responses of households based on theircapacity for recalling past events. Faced with such asituation, the Indian NSS employs a moving referenceperiod of last 30 days preceding the date of interview forcollecting household consumption data. For any particularsample household the data relate to a randomly chosenperiod of 30 consecutive days ending on one of the 365days of the survey year. Therefore, approximatelyspeaking, if the unobserved annual total of consumptionexpenditure ÷ (365/30) represents the true value ofconsumption, the reported value relating to the past 30days can be taken as equal to the true value ± an error ofobservation whose expected value is nearly zero2 .

Deaton (1994, pp. 79-80) (see also Prais and Houthakker,1955, pp. 62-63) deals with the crucial question : what

1 Although not strictly relevant here, one may note that many officialCPI numbers in India use varying weightages of items of the "fruitsand vegetables" group in different seasons of the year (LabourBureau,Govt.of India, 1972).

2 As mentioned by Deaton (op. cit, pp. 25-27), many countries uselast week or last month as reference period for food and some othergroups of items but longer reference periods like last year (365days) for more expensive and rarely purchased items like durables.Problems of seasonality are not fully eliminated by this. This wasdone in the recent rounds of the Indian NSS, which employed bothlast month and last year reference periods for several item groups.Note that the statement made in the last sentence of the foregoingparagraph remains approximately correct if one combines data fordifferent reference periods to estimate the annual total ofconsumption expenditure for any individual household.

SARVEKSHANA 3

happens if the errors in the determining and dependentvariables are correlated? This is often a real problem. Thus,unusually high expenditure on medical care during the lastmonth will raise total consumer expenditure also. Deatonpresents the following results for the general multivariatecase where the correctly measured variables satisfy

y =Xβ + u (1.1)

The OLS parameter estimates have the probability limitgiven by

plim β = ( M + Ω )-1 Mβ + (M + Ω )-1 γ (1.2)

where M is the moment matrix of the true x’s, Ω is thecovariance matrix of the measurement errors in the x’s,and γ is the vector of covariances between themeasurement errors in the x’s and the measurement errorin y. The second term of Eqn. (1.2) captures any additionalbias from a correlation between measurement errors in

the dependent and independent variables.

In recent rounds the NSS also collected additional dataon consumption expenditure for ‘the last 365 days’ (lastyear) preceding the date of interview for five item-groups: clothing, footwear, durables, medical care and education.Analysis of NSS data by Ghose and Bhattacharya(1994, 1995) showed that weighted least squares (WLS)estimates of engel elasticities for some of these itemsdecline dramatically when available ‘last year’ data forthese items are used in place of corresponding ‘last month’data. When item consumption relates to ‘last month’ thedetermining variable is total consumer expenditure duringthe same month; but when item consumption relates to‘last year’ the determining variable is total consumerexpenditure during the last month on food and other itemsplus 30/365 times total consumer expenditure on the fiveitems mentioned above. Actually, in the first case, theregression is of per capita item consumption on per capitatotal household consumption expenditure i.e., PCE (‘lastmonth’) and in the second case the regressor is PCE (‘lastyear’). The true engel elasticity may be defined as theelasticity which would be obtained from the relation

between ‘permanent’ components of item consumptionand total income/consumption per capita. The elasticityderived from last year data would only be anapproximation to this, if errors in observation are not toolarge.

From estimates based on a retabulation of all-India NSS38th round (Jan.—Dec. 1983) household budget data theelasticity of clothing was found to be around 2.1 when‘last month’ data is used for all items of the budget, but itdrops to about 1.0-1.1 when annual data for clothingand other four items is used. Similarly, for footwear, theelasticity changes from 1.9-2.1 to about 1.4 for rural Indiaand from 1.7-1.9 to 1.2-1.3 for urban India. The elasticityfor durables drops from 2.75 for rural India and 2.6-3.3for urban India to 2.1-2.2 when annual data is used.Similar changes are noticed for expenditure elasticitiesfor medical care and education3. Separate analyses for13 major states of India yielded results which corroboratedthe main findings of the all-India analysis (vide Ghoseand Bhattacharya, 1995). These results highlight the needfor special methods of estimating engel elasticities frombudget data relating to short reference periods like ‘lastmonth’ or ‘last week’. The standard techniques of dealingwith the EIV problem offer no easy solutions in this case,especially because the two errors are correlated.Instrumental variable (IV) estimation suggested byLiviatan (1961) is a possibility. This study explores thepossibility of IV estimation by using differentcombinations of item expenditures, excluding those itemsfor which seasonality is pronounced, as instruments.

Section 2 describes briefly the data analysed and themethodology adopted for this study. Sections 3, 4 and 5present the important findings of the study. Section 3compares the estimates of engel elasticities based ondifferent IV estimators. Section 4 makes a comparative

^

3 It was also found that that measures of inequality, like the LorenzRatio and shares (in total consumption) of different fractile groups,get distorted due to the effect of the reference period (Ghose, 1998).The Lorenz Curves based on last year data were shown to beinterior to that based on last month data and the decline in theLorenz ratio is statistically significant when last year data is used,for both rural and urban India.

SARVEKSHANA4

study of these estimates in respect of the divergencebetween half-sample estimates of these elasticities.Section 5 examines the correlation between the chosenIVs and some estimates of the errors in the variables.Section 6 concludes the paper with some observations.

2. Material Analysed and Methodology

The present study is based on a retabulation of NSS 38thround (Jan.—Dec. 1983) ungrouped (household level)data by using the computer tapes provided to ISI,Calcutta, by the NSSO, Govt. of India. The main findingsof the 38th round enquiry were released through NSSReport No.332 (National Sample Survey Organisation,Govt. of India, 1986).

The enquiry covered practically the whole of India,including both rural and urban sectors. A probabilitysample of households was drawn for the enquiry. Thesampling design adopted was stratified two-stage withprovision for two replicates or independent andinterpenetrating half-samples. Data were collected by theinterview method and information was collected from eachsample household for a period of ‘last 30 days’ precedingthe date of interview. The item groups considered for thepresent study are clothing, footwear, durable goods,medical care and education. As stated earlier, both lastmonth and last year data were collected for these fiveitems.

Consumption included consumption out of purchase incash or in credit, out of home-grown produce, out ofreceipts in exchange of goods and services and out ofgifts, loans and free collections. Non-monetizedconsumption was imputed at producer’s/ local retailprices. The imputed rental of owner-occupied houses orof free/ subsidized quarters provided by employers wasexcluded from the data on consumption expenditure. Formany item groups including food the value of consumptionis derived by aggregating the monetary value of goodsactually consumed during the reference period. Forclothing and footwear, consumption is defined as valueof articles brought into first use. For durable goods,consumption is equated to expenditure on purchase or

acquisition. The simple formulation of the Engel relationwhere total consumer expenditure is taken as the soledetermining variable is known to be seriously inadequatefor durables, as the cost of acquisition may be spreadover several years like the flow of benefits derived fromthe assets. All expenditure figures are in Indian rupees,abbreviated Rs.

NSS data for 13 states, namely, Andhra Pradesh, Bihar,Gujarat, Karnataka, Kerala, Madhya Pradesh,Maharashtra, Orissa, Punjab, Rajasthan, Tamil Nadu,Uttar Pradesh and West Bengal, are analyzed hereseparately for the rural and urban sectors. All-Indiaresults presented are in fact overall results for these 13states combined. The sample size for each state-sectorcombination is given in col.2 of Tables 1.1 and 1.2 of thenext section.

In this study the following three-parameter Working-Lesertype Engel equation was estimated by the IV method :

Here x is per capita total consumer expenditure on allitems and y is per capita expenditure on the selecteditem, for a sample household. This was found to be oneof the best-fitting forms for Indian NSS 38th round budgetdata (vide Ghose and Bhattacharya, 1994)4.

To fit the Working-Leser function by IV method, (2.1)above was recast as

to avoid the regressand y/x. If one uses vy

ux

x

y

++

= , there isa mix-up of the errors in variables v and u in x and y,

(2.1)

4 The LLI form x

xyγβα ++= lnln which was also a best-fitting

form was avoided in view of the occurrence of zero itemexpenditures for a few households in the sample.

(2.2)

ln

xx

x

y γβα ++=

lnxxxy βαγ ++=

SARVEKSHANA 5

respectively, and the model moves far from the simplelinear EIV model analyzed in econometric literature. Sinceour focus is on the bias of the estimates, we ignore theproblems of heteroscedasticity that may be generated dueto this reformulation of the Working-Leser function.

Note also that when we state that we used a pair of IV’s(Z

1, Z

2), we really used Z

1 and Z

2ln Z

2 as the instruments

for the estimation.

The IV estimation was done using the 2SLS estimationprocedure with SHAZAM (see Judge, Griffiths et. al.,1988, Chs. 14-15). The 2SLS estimator is given by

β2SLS = [X´Z(Z´Z)–1Z´X]–1X´Z(Z´Z)–1Z´y (2.3)

and Var (β2SLS ) = σ2 [X´Z(Z´Z)–1 Z´X]–1 (2.4)

with σ2 = u´ u / (n–k) = (y – Xβ2SLS )´(y– Xβ2SLS

)/ (n–k) (2.5)

(2.3) above is the same as the IV estimator if the numberof instruments is equal to the number of explanatoryvariables, as is the case in this study.

Since the sampling design adopted by the NSSO is acomplex one, direct estimation of standard errors isdifficult. However, the fact that the sample was dividedinto some independent replicates (two interpenetratingsub-samples) of the same basic design makes the

estimation of standard errors fairly easy (Cochran, 1977).

If the combined sample consists of 2 replicates orinterpenetrating subsamples and the estimates of anyparameter

θ

obtained from the 2 replicates are given by

1θ

and 2θ , then the combined sample estimate of is givenby

2

)ˆˆ(ˆ 21 θθθ

+=

and the variance of θ can be estimated as

4

)ˆˆ()ˆ(ˆ 21 θθ

θ−

=V

^

^

^ ^ ^ ^ ^

The estimated standard error of θ is :

2

|ˆˆ| 21ˆ

θθθθ

−=S

Five variables have been tried as IVs from those itemgroups or subgroups of the household budget whoseconsumption is believed to be relatively less affected byseasonal and short run factors, which is why only lastmonth data were collected for them. These are :

c : per capita expenditure on cereals;

c+o : per capita total expenditure on all itemsexcluding expenditure on the five seasonalitems, namely, clothing, footwear, durablegoods, medical care and education; so c+oincludes expenditure on food, pan, tobacco,intoxicants, fuel and light, housing and certaingroups of miscellaneous items5;

o : per capita total expenditure on all items minusexpenditure on cereals and on five seasonalitems mentioned above;

f : per capita expenditure on food;

c+o-f : per capita expenditure on non-food itemsexcluding the five seasonal items.

5 This IV was suggested by Professor Angus Deaton in a personalcommunication to the authors.

SARVEKSHANA6

........................................................................

Cereals (c)

Food otherthan cereals

non-food (non-seasonal) items

five seasonal items (clothing e.t.c)

[

Food (f)

(o)

The variables may be explained with the help of adiagram, which shows how different items are clubbedtogether, according to the way the NSS data is structured:

The variables c,o and f should be clear from the above. c+ o – f = non-food items excluding the five seasonal items.Various pairs of these five basic instruments have beenused to estimate the model. Most of the pairs of IVs wereformed by taking the same IV twice, like c+o, c+o. Fourextra pairs of IVs were formed taking (i) c and o togetheras c,o and o,c and (ii) f, and c+o-f in that order andreversed.

3. Results I : Comparisons of different estimatesof Engel elasticity

The results are presented in this and the next two sections.This section presents some of the statewise Engelelasticities based on different IV estimators and also theall-India rural and urban elasticities, for the five itemsconsidered. These elasticities are then compared on thebasis of closeness of the different estimates to theconventional WLS estimates based on last month and lastyear data. We also examine the distances between thevarious pairs of estimates.

Cols. 5-13 of Tables 1.1 and 1.2 present the differentIVestimates of engel elasticities for clothing for the ruraland urban sectors of the 13 states. They also show theconventional estimates of elasticities from last month andlast year data (vide cols. 3-4) obtained by the usual WLSmethod6. Similar results have been obtained for each ofthe other four seasonal items considered namely, footwear,durable goods, medical care and education, but these havenot been presented for reasons of space.

6 Standard errors or t-ratios could be shown in a routine manner for the 2SLS/IV estimates, however, they are open to serious criticismbecause NSS data are not obtained by simple random sampling, but were collected through a complex sampling design involvingstratification, multistage selection etc. The only safe approach to the estimation of sampling error is to obtain half-samplewise estimatesand study their divergence. This was not routinely done, considering the enormity of the task, particularly since broad conclusions can bedrawn by noting the general pattern of so many statewise estimates.

Table 1.1 : Estimates of engel elasticities of clothing, for 13 major states, obtained by different methods:Rural sector

WLS based on IV estimates based on last month data

States no.of sample last month last year c+o, c+o o,o c,c c,o o,c f,f c+o-f, c+o-f f,c+o-f c+o-f,fhhs.

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

Andhra Pradesh 5419 2.08 1.22 1.45 1.50 1.40 1.47 1.48 1.45 1.42 1.35 1.38Bihar 7879 2.09 0.93 1.65 1.92 1.36 1.22 1.11 1.63 1.42 1.21 1.31Gujarat 2477 2.35 1.25 1.75 1.78 0.93 1.55 1.58 1.74 1.55 1.74 1.64Karnataka 3263 2.06 1.09 1.26 1.37 1.06 0.79 4.03 1.25 1.13 1.55 1.03Kerala 3009 1.98 1.28 1.73 1.70 1.87 1.90 1.94 1.73 1.81 1.78 1.81Madhya Pradesh 5719 1.98 0.90 1.75 2.02 1.01 0.98 1.94 1.75 1.28 1.43 1.01Maharashtra 5517 1.91 0.89 1.21 1.32 0.92 0.84 0.72 1.22 1.00 2.01 6.82Orissa 3052 1.86 0.94 1.13 1.38 0.67 1.05 1.06 1.09 0.91 1.09 1.06Punjab 2095 2.03 1.01 1.16 1.04 1.56 1.49 1.39 1.14 1.53 1.39 1.51Rajasthan 3530 1.76 0.84 1.26 1.31 0.88 0.55 0.18 1.27 1.06 0.63 0.91Tamil Nadu 4540 1.86 1.24 2.17 2.41 1.70 2.34 2.43 2.38 0.39 5.28 4.24Uttar Pradesh 10517 1.94 0.94 1.33 1.46 0.93 0.39 1.51 1.32 1.12 1.63 0.73West Bengal 4996 1.96 1.13 1.38 1.41 1.41 1.38 1.40 1.50 1.20 1.13 1.09

SARVEKSHANA 7

Table 1.2 : Estimates of engel elasticities of clothing, for 13 major states, obtained by different methods:Urban sector

WLS based on IV estimates based on last month data

States no.of sample last month last year c+o, c+o o,o c,c c,o o,c f,f c+o-f, c+o-f f,c+o-f c+o-f,fhhs.

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

Andhra Pradesh 2494 1.93 1.34 0.89 0.84 0.92 0.66 0.10 1.01 0.63 0.00 0.26Bihar 1992 1.96 1.09 1.15 1.13 0.50 1.21 1.24 1.11 1.07 0.87 1.04Gujarat 1663 2.33 1.13 1.66 1.60 2.59 1.15 0.82 1.70 1.70 1.13 1.41Karnataka 2097 1.98 1.12 2.45 2.16 3.24 0.59 5.01 2.53 2.89 2.21 2.43Kerala 1225 2.05 1.27 1.64 1.69 1.66 1.51 1.51 1.62 1.66 1.61 1.61Madhya Pradesh 2376 1.94 1.03 1.60 1.69 0.68 1.78 1.95 1.66 1.07 1.40 1.98Maharashtra 4797 1.70 0.89 1.11 1.08 1.37 1.19 1.30 1.14 1.16 1.21 1.22Orissa 824 1.99 1.09 1.36 1.30 1.56 1.32 1.29 1.36 1.54 1.64 1.32Punjab 1557 1.88 0.95 1.24 1.23 1.34 1.04 1.08 1.34 1.00 1.35 0.86Rajasthan 1579 1.74 0.96 1.13 1.19 0.45 1.12 1.12 1.15 0.71 1.11 1.17Tamil Nadu 3499 1.98 1.20 0.79 0.48 1.52 1.75 1.68 0.87 1.12 1.08 1.11Uttar Pradesh 4180 1.91 1.08 1.32 1.35 0.93 1.23 1.30 1.33 1.11 1.23 1.21West Bengal 3138 1.87 1.06 1.19 1.22 1.04 1.16 1.20 1.18 1.06 1.19 1.17

Table 2.1: Algebraic and absolute sums over13 states of differences between IV estimates of elasticities(Zi) and conventional WLS estimates from last year data (Z) : rural sector

itemstype of estimate clothing footwear durables medical care education sum of row

ranks

(1) (2) (3) (4) (5) (6) (7)

Σ(Zi-Z)

WLS last month 12.20 (10) 6.71 (8) 10.13 (10) 4.56 (8) 4.15 (6) 42

last year 0.00 0.00 0.00 0.00 0.00

IVs c+o,c+o 5.57 (4) 2.22 (5) -1.35 (2) -1.36 (4) -0.63 (2) 17

o,o 6.96 (6) 4.35 (7) -1.63 (3) 0.11 (1) 0.95 (3) 20

c,c 2.04 (1) -2.38 (6) -9.55 (8) -6.83 (9) -5.43 (8) 32

c,o 2.28 (3) -7.23 (10) -3.79 (5) -8.92 (10) -10.38 (10) 38

o,c 7.11 (7) 0.16 (1) 2.00 (4) 1.16 (2) 2.53 (5) 19

f,f 5.81 (5) 2.06 (4) -1.16 (1) -1.32 (3) -0.06 (1) 14

c+o-f,c+o- 2.16 (2) -0.41 (2) -5.99 (7) -4.43 (7) -4.93 (7) 25

f,c+o-f 8.56 (8) -1.30 (3) 5.62 (6) -2.56 (5) 1.32 (4) 26

c+o-f,f 10.88 (9) 6.73 (9) 9.76 (9) -3.83 (6) -7.62 (9) 42

Σ|Zi-Z|

WLS last month 12.20 (10) 6.71 (6) 10.13 (4) 4.56 (5) 4.23 (1) 26

last year 0.00 0.00 0.00 0.00 0.00

IVs c+o,c+o 5.57 (4) 4.10 (2) 8.95 (1) 1.86 (1) 6.65 (3) 11

o,o 6.96 (6) 6.33 (5) 8.97 (2) 2.11 (3) 6.67 (4) 20

c,c 3.30 (1) 6.28 (4) 11.15 (5) 7.03 (6) 8.99 (6) 22

c,o 4.66 (3) 10.41 (9) 20.13 (7) 8.92 (7) 15.66 (9) 35

o,c 8.77 (7) 8.90 (8) 26.46 (9) 12.20 (8) 17.25 (10) 42

f,f 5.81 (5) 3.70 (1) 8.98 (3) 1.88 (2) 6.12 (2) 13

c+o-f,c+o-f 3.92 (2) 5.45 (3) 11.23 (6) 4.45 (4) 8.75 (5) 20

f,c+o-f 8.98 (8) 7.20 (7) 24.04 (8) 13.14 (9) 15.62 (8) 40

c+o-f,f 11.50 (9) 17.33 (10) 31.64 (10) 14.97 (10) 15.50 (7) 46

SARVEKSHANA8

Table 2.2: Algebraic and absolute sums over13 states of differences between IV estimates of elasticities(Zi) and conventional WLS estimates from last year data (Z) : urban sector

itemstype of estimate clothing footwear durables medical care education sum of row

ranks

(1) (2) (3) (4) (5) (6) (7)

Σ(Zi-Z)

WLS last month 11.05 (10) 4.72 (6) 7.29 (10) 2.96 (4) 1.40 (3) 33

last year 0.00 0.00 0.00 0.00 0.00

IVs c+o,c+o 3.32 (6) -2.75 (3) -5.80 (7) -4.62 (7) -0.97 (2) 25

o,o 2.75 (5) -3.03 (4) -6.40 (8) -3.94 (6) -0.24 (1) 24

c,c 3.59 (7) -10.84 (10) -4.78 (3) -7.38 (10) -8.67 (10) 40

c,o 1.50 (1) -6.24 (9) -3.07 (2) -3.48 (5) -4.70 (6) 23

o,c 5.39 (9) -1.56 (2) -5.16 (6) 1.47 (2) -6.97 (8) 27

f,f 3.79 (8) -0.77 (1) -5.03 (5) -4.95 (8) -1.67 (4) 26

c+o-f,c+o-f 2.51 (3) -6.22 (8) -8.81 (9) -5.99 (9) -7.81 (9) 38

f,c+o-f 1.82 (2) -5.12 (7) -1.54 (1) 0.21 (1) -5.53 (7) 18

c+o-f,f 2.58 (4) 3.18 (5) -4.92 (4) -2.65 (3) -3.64 (5) 21

Σ|Zi-Z|

WLS last month 11.05 (10) 5.82 (1) 7.41 (1) 3.66 (1) 2.70 (1) 14

last year 0.00 0.00 0.00 0.00 0.00

IVs c+o,c+o 5.04 (3) 6.31 (2) 8.46 (4) 6.06 (5) 5.87 (2) 16

o,o 5.19 (6) 6.83 (4) 8.00 (2) 5.68 (3) 7.34 (6) 21

c,c 7.67 (8) 14.84 (10) 19.40 (10) 8.96 (9) 12.13 (10) 47

c,o 3.93 (1) 7.66 (6) 11.73 (7) 5.92 (4) 8.54 (8) 26

o,c 8.49 (9) 10.90 (9) 14.62 (8) 9.31 (10) 8.09 (7) 43

f,f 5.11 (4) 6.69 (3) 8.25 (3) 6.13 (6) 6.69 (4) 20

c+o-f,c+o-f 4.63 (2) 9.04 (8) 14.95 (9) 7.27 (7) 9.59 (9) 35

f,c+o-f 5.18 (5) 8.60 (7) 10.78 (5) 7.51 (8) 7.19 (5) 30

c+o-f,f 5.20 (7) 7.04 (5) 11.38 (6) 4.57 (2) 5.88 (3) 23

Tables 2.1 and 2.2 give the results of a comparison of thestatewise elasticities from the IV method with thecorresponding conventional WLS estimates based on lastyear data. The upper half of each table shows the algebraicsum (Σ(Z

i - Z)) of differences between the last year

estimates (Z) and each selected IV estimate (Zi), the sum

extending over the 13 states for each item, separately forrural and urban sectors. The lower half of the tablepresents the corresponding sum of absolute differences(Σ|Z

i-Z|). The different estimates have then been ranked—

the ranks are shown in brackets — according to theircloseness to last year estimates, separately for each itemand sector. Finally, col.7 of either table gives the sum ofthese ranks over the five items considered for each of theestimators — it therefore indicates which of the IVestimates may be the best for estimating elasticities forall of the five seasonal items taken together.

Col.(7) of Table 2.1 shows that for the rural sector foodexpenditure gives the best pair of instruments (f,f) whenjudged by Σ(Z

i-Z), and this is followed by the pair (c+o,

c+o). Judging by Σ|Zi-Z|, (c+o, c+o) is the best pair

followed by (f,f) for the rural sector. Table 2.2, col. (7)shows that (c+o, c+o)and (f,f), in that order, are the bestinstruments for the urban sector also in terms of Σ|Z

i-Z|.

By the criterion Σ(Zi-Z), however, for the urban sector,

(f,c+o-f) is the best followed by (c+o-f,f). These rankingsgive the overall picture considering the five items togetherand judging by closeness to last year based estimates.

If one looks at individual items, instruments based onc+o or f do not appear to be the best for many item-sector combinations, especially for the urban sector, andalso for clothing in either sector if one takes the ‘lastyear’ estimate as the criterion.

SARVEKSHANA 9

Interestingly, the conventional WLS estimate based onlast month data appears to be closer to last year basedestimates than any IV estimate judging by sums Σ|Z

i-Z|

for several items, especially in the urban sector. But thesums (Z

i-Z) give a very different picture — last month

estimates tend to be relatively far from last year basedestimates on this criteria. The sums Σ(Z

i-Z) would be

better indicators of systematic biases, if any, of differentestimates, compared to the last year estimate.

Table 3 presents as an example, a summary picture ofthe distances between different pairs of statewise estimatesfor clothing for the rural sector. The upper half of thetable shows the algebraic sum of differences between eachpair of estimates Σ(Z

i-Z), the sum being over the 13 states.

The lower half of the table shows the corresponding sum

of absolute differences Σ|Zi-Z|. Table 3 and analogous

tables (not shown) for other item-sector combinationsgenerally show that IV estimates (c+o, c+o) are closeto IV estimates (f,f) and (o,o), which is quiteunderstandable.

Table 4 presents the all-India rural and urban elasticitiesfor the five items under consideration calculated as aweighted average of 12 statewise elasticities using the1981 census population of each state (sector) as its weight.Here Tamil Nadu has been excluded from the 13 statesoriginally considered since it appears that the correlationbetween IVs and the seasonal disturbances areexceptionally high for Tamil Nadu due to the existenceof a few outliers in the data, which were detected at thelast stage.

Table 3: Pairwise comparisons of statewise elasticities for clothing, obtained by different methods :rural sector.

WLS type of IV estimate

type of estimate last month last year c+o,c+o o,o c,c c,o o,c f,f c+o-f,c+o-f f,c+o-f c+o-f,f

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Σ(Zi-Z)

last month 0.00

last year -12.20 0.00

c+o,c+o -6.63 5.57 0.00

o,o -5.24 6.96 1.39 0.00

c,c -10.16 2.04 -3.53 -4.92 0.00

c,o -9.92 2.28 -3.29 -4.68 0.24 0.00

o,c -5.09 7.11 1.54 0.15 5.07 4.83 0.00

f,f -6.39 5.81 0.24 -1.15 3.77 3.53 -1.30 0.00

c+o-f,c+o-f -10.04 2.16 -3.41 -4.80 0.12 -0.12 -4.95 -3.65 0.00

f,c+o-f -3.64 8.56 2.99 1.60 6.52 6.28 1.43 2.75 6.40 0.00

c+o-f,f -1.32 10.88 5.31 3.92 8.84 8.60 3.77 5.07 8.72 2.32 0.00

Σ|Zi-Z|

last month 0.00

last year 12.20 0.00

c+o,c+o 7.25 5.57 0.00

o,o 6.42 6.96 1.69 0.00

c,c 10.16 3.30 4.67 6.30 0.00

c,o 10.88 4.66 4.65 5.96 3.24 0.00

o,c 10.17 8.77 6.24 6.49 7.73 6.21 0.00

f,f 7.43 5.81 0.46 1.59 4.89 4.59 6.10 0.00

c+o-f,c+o-f 10.04 3.92 4.31 6.00 3.34 4.70 8.17 4.59 0.00

f,c+o-f 10.68 8.98 6.57 7.08 8.50 7.46 8.55 6.45 8.30 0.00

c+o-f,f 15.90 11.50 10.91 11.90 10.30 9.54 14.27 10.75 11.10 8.42 0.00

SARVEKSHANA10

Table 4: Weighted mean* of 12** statewise elasticities obtained by different methods :rural and urban.

WLS IV estimates based on last month data

sector item last month last year c+o,c+o o,o c,c c,o o,c f,f c+o-f,c+o-f f,c+o-f c+o-f,f

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

rural clothing 2.00 1.01 1.43 1.54 1.12 1.01 1.47 1.43 1.26 1.45 1.77

footwear 1.78 1.22 1.30 1.47 0.82 0.23 1.16 1.29 1.01 1.11 1.85

durables 2.77 2.05 1.76 1.74 1.49 1.14 2.27 1.79 1.48 3.04 2.50

medicalcare 1.62 1.27 1.14 1.27 0.66 0.37 1.77 1.14 0.86 1.65 0.96

education 1.73 1.39 1.31 1.47 0.80 0.00 1.64 1.36 0.86 1.86 0.32

urban clothing 1.91 1.06 1.36 1.34 1.36 1.13 1.46 1.39 1.26 1.19 1.29

footwear 1.74 1.25 1.24 1.26 0.65 1.06 1.33 1.38 1.06 1.07 1.22

durables 2.67 1.99 1.53 1.48 1.83 1.84 1.48 1.59 1.43 1.77 1.54

medical care 1.34 1.11 0.81 0.86 0.56 0.85 1.23 0.77 0.75 1.14 0.92

education 1.62 1.60 1.26 1.27 0.88 1.36 0.93 1.19 0.89 1.06 1.16

*Statewise 1981 cencus populations were used as weights.

**Tamil nadu was excluded for reasons mentioned in the text.

The estimates presented in Table 4 should be much lessaffected by sampling errors than the statewise estimates,and should therefore reveal relative biases, if any, of thedifferent estimates of elasticities.

Taking the last year estimates in col.(4), as the criterion,one finds that IV estimates (c+o, c+o) or (f,f) these arequite close, especially for the rural sector — are, on theaverage, nearly equal to the last year estimates for severalof the ten item-sector combinations. But there are fairlylarge discrepancies for other combinations like clothingfor rural sector and all but footwear for urban sector.The instruments (c,o) and (f,c+o-f) seem to be better formany items in the urban sector.

4. Results II : Divergence between half-sampleestimates

This section presents the results, mainly, of thecomparison of divergences between half-sample estimatesof engel elasticities for the different choices of instruments.

For each statewise engel elasticity estimated by IVmethod, the standard error was estimated from thedivergence between the two half sample estimates of thesame elasticity. Tables 5.1 and 5.2 first present (see sub-table (a)) the median of these statewise standard errorsseparately for each IV estimate, and also for each itemand sector. Next, in sub-tables (b) in both the tables, wepresent the median rank of each IV estimate by themagnitude of standard error. Finally, sub-tables (c) inTables 5.1 and 5.2 show the standard deviations of thestatewise engel elasticities estimated by different IVtechniques. For reasons stated earlier, the estimates forTamil Nadu were excluded from such calculations. Thissub-table does not relate to sampling errors, strictlyspeaking. But since the true values of the statewiseelasticities are unlikely to be really different, the standarddeviation of statewise elasticities should reflect thesampling variability of the statewise estimates. For therural sector, judging by median ranks in sub-table (b) ofTable 5.1, IV’s (c+o, c+o) and (f,f) seem to give the moststable estimates followed by (o,o).

SARVEKSHANA 11

However, the medians of standard errors in sub-table (a)show that (f,f) may have a slight edge over (c+o,c+o) inpoint of sampling error. The picture is somewhat differentfor the urban sector — see sub-tables (a) and (b) of Table5.2. Four choices of instruments — (c+o,c+o), (f,f),(o,o) and (c+o-f,c+o-f) tend to give the best estimates(with the smallest half-sample divergence); the choice(o,c) may also be good in a few cases.

The standard deviations in the sub-tables (c) broadlycorroborate the above. The instruments (c+o-f,c+o-f) alsoseem to be good for the rural sector for some items. Butfor the urban sector, the same instruments (c+o-f,c+o-f)seem to be relatively poor when compared to (c+o, c+o),(f,f) and (o,o). The choice (c,o) seems to be good forseveral items.

Table 5.1 : Comaparisons of sampling variability of statewise elasticities obtained by different methodsof IV estimation: rural sector.

Instrumental variables used

item c+o,c+o o,o c,c c,o o,c f,f c+o-f,c+o-f f,c+o-f c+o-f,f

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

(a) Median of statewise standard errors based on divergence between halfsample estimates

clothing 0.095 0.190 0.140 0.225 0.520 0.075 0.150 0.350 0.315

footwear 0.110 0.100 0.235 0.225 0.420 0.110 0.175 0.215 0.370

durables 0.400 0.330 0.395 0.550 0.685 0.320 0.555 0.935 0.885

medical care 0.075 0.120 0.255 0.250 0.680 0.065 0.090 0.540 0.230

education 0.310 0.335 0.185 0.345 0.940 0.235 0.305 0.775 0.535

(b) Median rank of each IV estimate by standard errors

clothing 3 6 4 6 8 4 4 7 6

footwear 3.5 3 5 6 8 3.5 6 7 6

durables 3 3 5 7 7 2 5 7 6

medical care 3 4 6 7 7 3 3 8 6

education 4 4.5 3 5 7 4 4 9 7

(c) s.d of elasticities for different states excluding Tamil Nadu

clothing 0.23 0.27 0.33 0.43 0.89 0.23 0.25 0.35 1.58

footwear 0.45 0.59 0.59 0.98 0.97 0.45 0.39 0.69 3.08

durables 0.62 0.49 1.13 1.34 1.95 0.63 0.98 2.45 4.72

medical care 0.26 0.31 0.51 0.73 1.53 0.26 0.3 1.59 1.96

education 0.74 0.76 1.05 1.81 1.78 0.72 0.91 1.66 1.73

SARVEKSHANA12

Table 5.2 : Comaparisons of sampling variability of statewise elasticities obtained by differentmethods of IV estimation : urban sector.

Instrumental variables used

item c+o,c+o o,o c,c c,o o,c f,f c+o-f,c+o-f f,c+o-f c+o-f,f

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

(a) Median of statewise standard errors based on divergence between halfsample estimates

clothing 0.150 0.170 0.435 0.245 0.155 0.150 0.295 0.195 0.250

footwear 0.195 0.190 0.555 0.240 0.141 0.200 0.170 0.180 0.210

durables 0.410 0.365 0.830 0.515 0.435 0.430 0.460 0.695 0.580

medical care 0.205 0.220 0.355 0.310 0.310 0.215 0.210 0.430 0.375

education 0.175 0.150 0.700 0.415 0.270 0.200 0.190 0.305 0.460

(b) Median rank of each IV estimate by standard errors

clothing 4 4 8 6 6 5 6 2 6

footwear 6 5 7 5 3 5 4 4 5

durables 3 3 8 5 5 5 5 7 6

medical care 4 5 7.5 6 7 4 3 5 4

education 4 3 7 6 7 3.5 3 5 6

(c) s.d of elasticities for different states excluding Tamil Nadu

clothing 0.39 0.34 0.80 0.31 1.14 0.40 0.58 0.50 0.52

footwear 0.39 0.35 1.10 0.45 1.17 0.43 0.60 0.67 0.53

durables 0.70 0.62 2.03 1.26 1.64 0.71 1.21 1.19 1.07

medical care 0.42 0.41 0.69 0.37 1.31 0.44 0.50 1.05 0.37

education 0.19 0.29 1.17 0.76 0.67 0.29 0.53 0.26 0.39

5. Results III : Correlations between the IV’s andthe errors in variables (EIV)

One may examine the correlation between the choseninstrumental variables and the seasonal/shortrundisturbances in the regressors and the regressands utilizingthe differences between the per capita (total/item)expenditure for the last month and the correspondingexpenditure for the last year. If one assumes that the lastyear expenditures represent the ‘true’ values, then thesedifferences can be taken as (estimates of) errors invariables. As already mentioned, in the 38th round ofthe NSS enquiry, last year data was collectedsimultaneously with last month data for the item groupsclothing, footwear, durables, medical care and education.Note that for the regressor xlnx, the errors in variables

were estimated as xlnx (last month) minus xlnx (last year,reduced to a 30 days basis).

Tables 6.1 and 6.2 present (in subtables (a)) the valuesof the correlation coefficients between each instrumentused and the estimated EIV in each regressor orregressand, averaged over twelve states, for the rural andurban sectors separately. The number of -ve signsoccurring among the statewise correlations is alsopresented in subtables (b) of these tables. For the sake ofinterest, the instrument f-c was included in these tableseven though f-c or (f-c)ln(f-c) was not used as instrumentin this study.

Many of the instruments show small values of the averagecorrelation coefficient — about 0.1 or 0.2 — with errors

SARVEKSHANA 13

in x and xlnx, but even these appear to be statisticallysignificant by the two-sided sign test. In fact, the tendencywould be significant at the 5% level if the numbers ofnegative signs in sub-table (b) is ≤ 2. The average valueof the correlation is often smaller, about 0.1 or less, forthe urban sector, and larger, about 0.15— 0.20, for therural sector.

As regards correlations between the instruments and theerrors in the five itemwise expenditures, the correlations

are somewhat higher (0.1—0.15) for expenditure onclothing or footwear and lower for the three remainingitems. Actually, for durables and education, the averagevalues of the correlations are nearly zero. Interestingly,the correlations are nearly the same for any instrument Zand the corresponding instrument ZlnZ. Judging by thesecorrelations, the best instruments would appear to be thosebased on (c+o-f), followed by those based on c. Butthese did not perform as well as the IV’s based on c+o,oor f in the different comparative studies reported above.

Table 6.1 : Summary of 12 statewise correlation coefficients between estimates of errors in variablesand different instruments : rural sector.

Errors in items Instrumental Variables

of expenditure c+o o c f c+o-f f-c (c+o)ln(c+o) olno clnc flnf (c+o-f)ln(c+o-f) (f-c)ln(f-c)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

(a) average value of correlation coefficient over states

total exp.(x) 0.17 0.15 0.11 0.19 0.04 0.19 0.16 0.15 0.11 0.19 0.03 0.18

xlnx 0.17 0.16 0.11 0.20 0.05 0.19 0.18 0.16 0.11 0.20 0.04 0.20

clothing 0.16 0.14 0.10 0.18 0.03 0.18 0.16 0.15 0.10 0.19 0.02 0.18

footwear 0.11 0.12 0.04 0.12 0.04 0.13 0.11 0.12 0.04 0.12 0.04 0.13

durables 0.04 0.03 0.04 0.05 0.00 0.04 0.04 0.03 0.04 0.05 0.00 0.04

medical care 0.07 0.06 0.05 0.08 0.02 0.07 0.06 0.05 0.05 0.07 0.02 0.06

education 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -0.05 0.00

(b) no. of –ve signs among the statewise correlation coefficients

total exp.(x) 0 0 0 0 1 0 0 0 0 0 2 0

xlnx 0 0 0 0 1 0 0 0 0 0 2 0

clothing 0 0 0 0 3 0 0 0 0 0 3 0

footwear 1 1 1 0 2 1 1 1 1 0 2 1

durables 3 3 3 3 3 2 3 2 3 3 4 2

medical care 0 0 1 0 3 0 0 0 1 0 3 0

education 5 5 5 6 8 4 5 6 6 6 9 5

SARVEKSHANA14

Table 6.2 : Summary of 12 statewise correlation coefficients between estimates of errors in variablesand different instruments : urban sector.

Errors in items Instrumental Variables

of expenditure c+o o c f c+o-f f-c (c+o)ln(c+o) olno clnc flnf (c+o-f)ln(c+o-f) (f-c)ln(f-c)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

(a) average value of correlation coefficient over states

total exp.(x) 0.09 0.08 0.05 0.11 0.02 0.10 0.09 0.08 0.05 0.11 0.02 0.11

xlnx 0.09 0.08 0.05 0.11 0.02 0.11 0.09 0.08 0.05 0.12 0.02 0.11

clothing 0.09 0.09 0.06 0.11 0.03 0.10 0.10 0.09 0.07 0.12 0.03 0.10

footwear 0.08 0.08 0.01 0.09 0.03 0.10 0.08 0.08 0.01 0.09 0.03 0.10

durables 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00

medical care 0.05 0.06 0.04 0.08 0.02 0.07 0.06 0.06 0.04 0.08 0.01 0.07

education 0.00 0.00 0.00 0.00 -0.03 0.00 0.00 0.00 -0.01 0.00 -0.03 0.00

(b) no. of -ve signs among the statewise correlation coefficients

total exp.(x) 1 1 2 0 3 0 1 2 1 0 4 1

xlnx 0 1 2 0 3 0 0 1 1 0 3 1

clothing 1 1 0 1 4 1 1 1 0 1 4 1

footwear 2 1 5 1 4 1 2 1 5 1 4 1

durables 5 5 4 5 8 6 5 5 4 6 8 6

medical care 0 0 2 1 3 1 1 1 2 1 5 1

education 5 6 5 5 8 6 5 7 5 5 8 5

6. Concluding Observations

Deaton (1994, p.89) notes that it is difficult to findinstruments that are not correlated with the measurementerror while being related to the true values. The findingsreported in Sections 3 — 5 indicate that some of the IV’stried have fairly low correlations with the errors invariables in the regressors or regressands considered.Consequently, IV estimates of engel elasticities based on‘last month’ data may be taken as approximations to engelelasticities based on‘last year’ data. However, theapproximation is not quite good, and if one tries to choosethe best pair of IV’s, the choice is not clear, beingdependent on the item-sector combination in question.Different IV’s give a range of estimates which may coverthe last year based engel elasticity and, hopefully, thetrue engel elasticity.

Deaton states that seasonal patterns can be estimated andused to make corrections. But this does not remove the

effects of other short-run fluctuations. Also, seasonalpatterns can vary across regions, ethnic groups,occupational groups etc. In India, for the rural sector,one has a rough picture of seasonality in householdconsumption pattern, as a large proportion of householdsdepend on cultivation and related activities. However, cropseasons and seasons for festivals or ceremonies need notbe the same for all households within a region and allhouseholds do not depend on cultivation. So,subroundwise results by states do not show a very clear-cut picture of seasonality. Also, seasonal variation isless pronounced for the urban sector. Theseconsiderations may throw light on some of the resultspresented above.

The NSS data on household budget are not above doubt,and Table 7 brings out one aspect of this. This tableshows the average values of x-X, where x = PCE (lastmonth) and X = PCE (per month, using last year datawherever available), separately for different class-

SARVEKSHANA 15

intervals of X, for rural areas of five selected states.Note that x - X is really the discrepancy between lastmonth expenditure on the five items considered here andthe corresponding expenditure during the last year. Ifthe data were perfect, these averages would be close tozero for each interval of X. One, however, finds apreponderance of positive values for most of the states.Table 3.1 of Ghose and Bhattacharya (1995) shows thatfor all-India rural, the per capita expenditure per 30

days, on the five items taken together was Rs.18.67 forthe last month but Rs.14.46 for the last year period.While this may partly explain the large proportion ofpositive discrepancies x - X in Table 7, it cannot explainthe increasing trend in the discrepancies as one considershigher and higher values of X. Some kind of recall bias,perhaps telescoping, affected the data, especially forthe relatively affluent sections (see United Nations,1982).

Table 7 : Average values of the difference between PCE using last month data(x) and PCE using lastyear data(X) whenever available, by size classes of PCE : rural sector, 5 selected states.

Class interval of Average values of (x-X)

PCE (X inRs.) Andhra Pradesh Maharashtra Tamil Nadu Uttar Pradesh West Bengal

(1) (2) (3) (4) (5) (6)

0 to 30 -1.17 -3.28 0.78 1.08 -1.73

30 to 40 0.34 -1.87 0.17 -0.05 -0.96

40 to 50 1.33 -2.14 -0.04 -0.56 -1.18

50 to 60 0.36 -1.67 -0.45 0.03 -0.33

60 to 70 1.78 -0.44 0.25 0.96 -0.70

70 to 85 1.54 -0.40 -0.36 1.68 -1.52

85 to 100 4.75 1.66 -0.25 1.99 0.30

100 to125 7.41 0.64 0.22 4.70 0.99

125 to150 14.23 3.39 2.88 6.70 4.36

150 to200 17.36 10.58 6.78 13.26 3.96

200 to 250 29.80 18.53 26.00 17.67 5.05

250 to 300 40.91 12.71 6.58 19.80 23.84

300 & above 54.29 28.79 110.17 25.77 21.92

Note that Engel curve estimation even based on availablelast year data cannot give perfect results, because forfood and for many groups of non-food items last yeardata was simply not available. The PCE (last year)denoted X is not a very good approximation to permanentconsumption expenditure of the household. Nevertheless,for items like clothing affected by transitory factors, WLSestimates of engel elasticities based on last month dataappear to be seriously biased. WLS estimates based onlast year data should be nearer the true elasticities. IV

estimates based on last month data are nearer to WLSestimates based on last year data. So the IV estimatesmay be really useful when only last month data have beencollected.

As the results of this analysis are based on the NSS 38thround, the data are somewhat old dated. Given theimportance of the on going debate concerningmeasurement of poverty in India and the related issues ofdiscrepancies between surveys and national accounts, the

SARVEKSHANA16

effects of questionnaire design, reporting periods, etc.,7

the methodology of the present study gains in relevanceand it would be worthwhile to replicate similar resultsfrom later rounds of NSS data to have up to date results.

References

Atkinson, A.B. (1975), The Economics of Inequality,Clarendon Press, Oxford.

Cochran,W.G. (1977), Sampling Techniques, Wiley, NewYork.

Cramer,J.S. (1969),Empirical Econometrics, North-Holland Publishing Company, Amsterdam.

Deaton, A. (1994), The Analysis of Household Surveys,(Draft),Research Programme in Development Studies,Princeton University.

Deaton, A. and Valerie Kozel (2005), Data and Dogma:Great Indian Poverty Debate, World Bank ResearchObserver, Volume 20, Number 2, 177-199

Friedman, M. (1957), A Theory of the ConsumptionFunction, Princeton University Press, Princeton.

Ghose, S. (1998), Engel Curve Estimation from BudgetData Relating to Short Reference Periods, Ph.D. Thesis,Indian Statistical Institute, Calcutta.

Ghose,S. and N.Bhattacharya (1995), Effect of referenceperiod on engel elasticities of clothing and other items :Further results, Sankhyâ, Series B, 57, Pt.3, 433-449.

Ghose,S. and N.Bhattacharya (1994), Effect of referenceperiod on engel elasticities of clothing and other items,Sarvekshana, XVII, No.3, Jan.—Mar.1994, 35-39,Journal of the NSSO, Govt. of India, New Delhi.

Johnston, J. (1963), Econometric Methods, Mc.GrawHill.

Judge,G.G., R.C.Hill, W.E.Griffiths, H.Lütkepohl andT.C.Lee (1988), Introduction to the Theory and Practiceof Econometrics, John Wiley, New York, Second Edition.

Labour Bureau, Govt. of India (1972), Working ClassConsumer Price Index Numbers in India — AMonograph, Ministry of Labour and Rehabilitation.

Liviatan,N. (1961), Errors-in-variables and Engel curveanalysis, Econometrica, Vol. 29, No.3, 336-362.

Malinvaud, E. (1972), Statistical Methods ofEconometrics, North Holland, Amsterdam.

National Sample Survey Organisation, Govt. of India(1986), Pattern of Consumer Expenditure of ScheduledCaste and Scheduled Tribe Households : Thirty-eighthRound (Jan.—Dec.1983), Report No.332, Dept. ofStatistics, New Delhi.

Prais, S.J., and H.S.Houthakker (1955), The Analysis ofFamily Budgets, Cambridge University Press, Cambridge.

United Nations (1982), Non-Sampling Errors inHousehold Surveys : Sources, Assessment and Control,National Household Survey Capability Programme.

7 See for example Deaton and Kozel (2005).

SARVEKSHANA 17

Disparities of Living in Rural India

Tushar kanti Mitra Tushar Kanti Ghara Gouranga Sinha

Introduction

There exists a wide regional variation in the levels ofdevelopment in the Indian economy. See e.g GOI PlanningCommission[1]. In a developing country like Indiaeconomic reforms are made mainly with a view toachieving high economic growth that gives rise to thebetterment of quality of life, apart from reducing incidenceof poverty and inequality. In the present paper, we havestudied how the quality of living in the rural sector variesacross fifteen major states as stated below. It may benoted that the total rural population in these states understudy accounts for 91% of the total rural population and65% of the total population in India[2]. We haveconsidered the monthly per capita expenditure (MPCE)data published in ‘Level and Pattern of ConsumerExpenditure, 2004-2005’, NSS 61st round, published byNSSO, Govt. of India. It may be assumed that the qualityof life of an Indian may be reflected in the average percapita expenditures on non-food items, apart fromexpenditures on food items. In this study we haveconsidered five groups of non-food items (Appendix-1),namely, (i) fuel and lighting, (ii) clothing, (iii) education,(iv)medical (institutional and non-institutional), (v)miscellaneous consumer goods and services (hhconsumables, conveyance and consumer services),expenditures on which may be reasonably assumed toreflect the quality of living. One may suppose that thehigher the expenditure on such groups of items, the betteris the quality of living. To this end in view, we haveconstructed a quality of living index (QLI) and rank thefifteen major states in India according to this index. Thesestates are Andhra Pradesh (A.P), Assam, Bihar, Gujarat,Haryana, Karnataka, Kerala, Madhya Pradesh (MP),Maharastra, Orissa, Punjab, Rajasthan, Tamil Nadu(TN), Uttar Pradesh (UP), West Bengal (WB).We havealso performed cluster analysis on the basis of the MPCE

data on the above groups of items in order to group thestates in respect of quality of living. For this We havecorresponded the states belonging to different clusters totheir respective average MPCE’s on the above groups ofnon-food items taken together. We also correspond thestates to their respective QLI ranks. In both cases, wehave identical interpretations.

The plan of the paper is as follows – Section2 relates tothe data undertaken for our study; Section 3 presents themethodology for the construction of QLI and clusteranalysis; Section4 presents the results with interpretationsand concluding remarks.

2. The Data and some preliminary analysis

The data source and the relevant data have been discussedearlier. On the basis of this data, we have computed thecoefficients of variation (c.v.) of MPCE’s for (i) fuel andlight, (ii) clothing, (iii) miscellaneous consumer goodsand services, (iv) education and (v) medical (Institutionaland non institutional). The c.v.’s across the states are27.20, 34.56, 49.02, 75.06 and 59.66 respectively (seeTable-1). This shows that the pattern of expenditure oneducation adds most to variation in the quality of living.We have also performed ANOVA to analyse the variationsin the consumption data. The ANOVA results are givenin Table-2 below.

TABLE-1 : c.v of MPCE

Items CV

Fuel & Light 27.20

Clothing 34.56

Misc.Consumer goods and Services 49.02

Education 75.06

Medical 59.66

SARVEKSHANA18

Table-2 ANOVA Results

source of variation degrees of freedom sum of squares mean sum of squares F(S.V) (D.F) (S.S) (M.S)

(1) (2) (3) (4) (5)

between states 14 9757.902 696.992 3.999*

between MPCE’s 4 27761.26 6940.315 39.83*

error 56 9757.9018 174.2482

total 74

“*” indicates significance at 1% level.

From Col-(v) of Table-2, it is found that the hypothesisof the equality of effects of the five groups on quality ofliving is highly rejected. To find which of the above effectsare significant we obtain the critical difference at, say,the 5% level, t

.025,4 × (2MSE/3)1/2, which is 18.7083. We

observe that the group relating to miscellaneous consumergoods and services has the maximum mean and thatrelating to education has the minimum mean. The meanMPCE’s of the five items are given below:

63.25 for (i) fuel and light, 25.73 for (ii)clothing, 17.74for (iii) education, 38.59 for (iv) medical, 65.12 for (v)miscellaneous. The critical differences of the expendituregroups as compared to the miscellaneous group are 1.87,39.40, 47.38 and 26.53 for (i) fuel and light, (ii) clothing,(iii) education and (iv) medical respectively.

3. Methodology

(i) Quality of living index (QLI) :QLI’s have been computed separately for all thefifteen states taking all the five non-food groups byusing the following formula

QLI=100 ×(H-A)/(H-L),

where H denotes the highest value of living qualityranking i.e 15×5=75, A denotes the actual value of

living quality ranking for the states concerned and Ldenotes the lowest value of living quality ranking i.e1×5=5.

(Rank 1 is assigned to the most and 15 to the leastquality of living for every group of item). The resultsare given in Table-3.

For cluster analysis we have done Ward’s [3]hierarchical analysis technique. The Euclideandistance function is,

where, xik

is the value of variable Xk, for state i and x

jk is

the value of the same variable for state j. Usually variablesare standardized in some way before distances arecalculated, so that five variables are equally important indetermining these distances. This can be done by codingthe variables so that the means are all zero and thevariances are all one. Finally, a dendogram can be formedusing hierarchical cluster analysis on this standardizeddata values.

SARVEKSHANA 19

4. Results and Interpretations:

From col-8 of Table-3 it is found that Kerala achievesthe highest value (93) of QLI followed by Haryana (90)

Table-3: QLI’s and its ranking of the states

States Ranks

Fuel clothing education medical miscellaneous Total QLI Rank& light of Ranks

(1) (2) (3) (4) (5) (6) (7) (8) (9)

AP 13 7 13 7 9 49 37 10.5

Assam 10 9 12 15 13 59 23 13

Bihar 14 10 15 14 14 67 11 15

Gujarat 5 14 14 11 4 48 39 9

Haryana 2 2 1 4 3 12 90 2.5

Karnataka 9 13 11 13 8 54 30 12

Kerala 4 1 3 1 1 10 93 1

MP 12 8 8 10 11 49 37 10.5

Maharastra 6 12 10 5 5 38 53 7.5

Orissa 15 15 9 12 15 66 13 14

Punjab 1 5 2 2 2 12 90 2.5

Rajasthan 7 3 6 6 7 29 66 4

TN 11 11 7 3 6 38 53 7.5

UP 3 6 4 9 10 32 61 5

WB 8 4 5 8 12 37 54 6

and Punjab(90). On the contrary, Bihar (11) has the lowestQLI preceded by Orissa (13), Assam (23). The values ofQLI’s of the other states lie in between.

Dendogram Showing Hierarchical Clustering

1-A.P, 2- Assam, 3- Bihar, 4- Gujarata, 5- Haryana, 6- Karnataka, 7-Kerala, 8- M.P, 9- Maharastra, 10-Orissa,11- Punjab, 12-Rajasthan, 13-T.N, 14-U.P, 15-W.B.

SARVEKSHANA20

From the dendogram it is found that there are 4 distinctclusters – Cluster-I (Kerala, Punjab, Haryana), Cluster-II (Gujarata, Maharastra, Rajasthan, Tamil Nadu, UttarPradesh). Cluster-III (AP, Karnataka, MP, WB), Cluster-IV ( Bihar, Assam, Orissa). We now correspond the statesbelonging to each cluster to their respective averageMPCE’s on the five groups taken together. These areCluster-1- (Kerala- Rs.557.52 ,Haryana-Rs. 443.55,Punjab- Rs. 430.30), Cluster-II (Gujarata- Rs. 250.63,Maharastra-Rs.274.46, Rajasthan- Rs. 266.86,TamilNadu-Rs.286.68,Uttar Pradesh-Rs.301.27), Cluster-III(MP- Rs.206.89, Karnataka- Rs.225.42, WB- Rs.232.18,AP- Rs.262.40),Cluster-IV (Bihar- Rs.146.85, Orissa-Rs.153.31, Assam- Rs.184.74).

The cluster-I, cluster-II, cluster-III and cluster-IV maybe said to represent states with superior quality of living,middle-grade quality of living, low middle- grade qualityof living and inferior quality of living respectively. Theabove clustering pattern is also supported when wecorrespond the various states to their respective QLI’s.

This study may be useful for policy makers in mattersrelating to the reduction of regional disparities in qualityof living in rural India as has been depicted above.

Acknowledgement

The authors are grateful to the referrer’s comments forthe improvement of the paper.

Referrences

[1] National Human Development Report, 2001, PlanningCommission, Govt. of India.

[2] Census of India, 2001, Govt. of India.

[3] Ward, Jr.,J.H.(1963) “ Hierarchical Grouping tooptimize an objective function.” J.Amer. Statist.

Assoc.,38, pp. 236-244

Appendix-1

Average monthly expenditure per person on different groups of non-food items of consumption for major 15states

STATES ITEM GROUP

medical miscellaneous group

fuel clothing education medical:inst. medical:non-inst. hh consumables conveyance consumer& light services

AP 49.91 25.82 7.7 7.5 31.11 14.5 21.7 20.9

Assam 54.8 24.1 7.96 0.78 9.28 11 10.68 14.18

Bihar 47.35 20.88 7.25 1.76 12.13 9.91 5.47 17

Gujarat 63.1 15.56 7.47 4.37 22.06 17.09 31.7 24

Haryana 90.56 42.49 50.53 18.8 34.22 18.59 42.1 41.76

Karnataka 56.14 17.89 8.29 4.04 16.38 13.81 22.43 21.24

Kerala 71.37 45.07 35.03 42.78 61.22 18.82 68.49 50.65

MP 52.48 24.21 10.28 2.51 25.78 11.28 16.86 17.63

Maharastra 61.39 19.43 10.21 10.72 29.38 15.02 31.46 25.29

Orissa 47.13 14.5 10.27 4.36 17.1 8.54 8.09 7.66

Punjab 108.88 28.72 35.96 14.91 42.15 22.19 48.63 43.55

Rajasthan 58.83 30.72 15.65 16.11 23.33 15.81 21.96 25.58

TN 53.81 19.82 14.18 27.87 26.82 16.77 30.11 22.03

UP 76.12 26.06 27.22 12.03 21.2 12.47 18.91 24.9

WB 56.85 30.65 18.12 7.75 30.38 10.53 14.64 10.83

Source: “Level and Pattern of Consumer Expenditure, 2004-2005”, NSS 61st Round (July 2004- June 2005).

SARVEKSHANA 21

NSS Experience on thePilot Survey on Non-Profit Institutions Serving Households

G. C. Manna

1. Background

1.1. As per the System of National Accounts (SNA)1993, non-profit institutions serving households (NPISH)is one of the five resident institutional sectors of theeconomy. The other four sectors include non-financialcorporations, financial corporations, general governmentand households. For the definitional aspects of theseinstitutional units and sectors, one may refer to paragraphs4.1 to 4.12 of section IV of SNA 1993. To quote fromthis document, the NPISH sector consists of all residentnon-profit institutions (NPIs)i, except those controlledand mainly financed by government, that provide non-market goods or services to households.

1.2 In the Indian Statistical System, database on NPIs– and more so for NPISHs – is rather weak. The firstsample survey on the private NPIs, such as trusts,charitable institutions, welfare associations, etc. wasattempted by the Reserve Bank of India (RBI)ii duringSeptember 1988 with 1986-87 as the reference period.This survey had a very small sample size. Further, theresponse rate was also not very encouraging. Thus thisstudy may probably be viewed more as a type study toget a broad picture of the organisational and financialaspects of these institutions.

1.3 Although the periodic economic censuses (EC)conducted by Central Statistical Organisation (CSO) docollect information on number of enterprisesiii, theirownership types, industry divisions, number of workersemployed by them, etc., information on whether anenterprise is an NPI or not was collected for the firsttime only in the fourth EC (1998). The practice hashowever been repeated in the fifth EC (2005). Accordingto the fourth EC, private NPIs had a share of little less

than 3% in the total number of non-agricultural enterprisesin India.

1.4 In the National Sample Survey (NSS), which isin operation since 1950 and where non-agriculturalenterprises have been covered in many NSS rounds, anattempt was made only in the 57th round (2001-02) toidentify the NPIs separately. According to this round, theNPIs were almost non-existent among the own accountenterprisesiv and their presence among the establishmentsv

was a little more than 4%.

1.5 Participatory Research in Asia (PRIA), incollaboration with Institute for Policy Studies, JohnsHopkins University, USA, conducted a survey on the Non-Profit Organisationsvi (NPO) in India during late 2000 tomid 2001. But the fieldwork for this survey was confinedto only 5 states of India, namely, West Bengal,Maharashtra, Delhi, Tamil Nadu and Meghalaya. Thissurvey estimated that about 1.18 million NPOs existedin the entire countryvii .

1.6 For estimation of private final consumptionexpenditure (PFCE), CSO requires the consumptionexpenditure of both households and NPISHs. While theconsumption expenditure of households is available fromthe NSS, the same is not directly available for theNPISHs. Further, over the years, the difference betweenthe estimated PFCE as per national accounts statistics(NAS) and estimated aggregate household consumerexpenditure as per NSS has been wideningviii. Thisobserved divergence may partly be attributed to theexpansion of the NPISH sector, whose contribution isnot known. While highlighting the indirect coverage ofNPISHs in the estimation of PFCE as the weakestlink, the National Statistical Commission under the

SARVEKSHANA22

Chairmanship of Dr. C. Rangarajan, recommended(August 2001) that periodical surveys/ type studies beconducted to collect data on the income and expenditureof the NPISHs.

1.7 Keeping the above aspects in view, the thenGoverning Council of National Sample SurveyOrganisation (NSSO), in its 85th meeting held on 11th

December 2002 decided to explore the possibilities ofconducting a pilot survey on NPISH in view of theimportance and relevance of the subject matter.Accordingly, the fieldwork of the pilot survey on NPISHwas undertaken by NSSO during July – December 2004.A report of this pilot survey has been brought out in March2007 by NSSO mainly for official use in planning furtherstudies and therefore it is not available in NSSO’s website.The purpose of this paper is to acquaint the readers aboutthe survey design and some of the major findings of thispilot survey.

2. Survey design

2.1 Geographical coverage: A major objective of thepilot survey was to gather experiences on the feasibilityof data collection from the NPISHs before launching anyfull-fledged survey on the subject. Accordingly, the pilotsurvey was conducted only in a few selected places ofsix States of the country. Broadly speaking, in each Statetwo districts having relatively large number of NPIs (asestimated from NSS 57th round survey) and falling underdifferent Regional Offices of Field Operations Divisionof NSSO were selected for the survey. The districts/placescovered by the pilot survey were Cachar and Kamrup(Assam), Delhi (Delhi Statutory Town), Indore andJabalpur (Madhya Pradesh), Mumbai and Nagpur(Maharashtra), Trichur and Kannur (Kerala) and Kolkataand Medinipur (West Bengal). Thus, the survey covered3 of the 4 largest metropolises (Mumbai, Delhi, Kolkataand Chennai) where a large proportion of NPIs was likelyto be located.

2.2 Activity coverage: The activities pursued by theNPIs could belong to primary, secondary or tertiary sector.

In fact, there was no restriction on the coverage in termsof industrial classification of the NPIs. Table A-1 in theAnnex gives a detailed list of activities covered in thepilot survey and corresponding industry codes as per theNational Industrial Classification (NIC) 1998 along withnotations used in the statements/tables of this paper. Someinstitutions might run many activities simultaneously orduring different parts of a year. For example, an institutionmay run a health centre and a night school; an organisationmanufacturing handkerchiefs may organise trainingprogrammes for women entrepreneurs; a dharamsalaix

may run a STD booth in its premises; etc. If accounts foreach such activity were separately available, the entireinstitution would be treated as more than one institutions(depending upon the number of activities). However, ifaccounts for different activities were not separable ormaintained separately, the data pertaining to the institutionas a whole (covering all market and non-market activities)would be collected and the institution would be classifiedas having mixed activities and the activities of such anorganisation would be a mixture of NICs. The appropriateNIC in such cases would be determined on the basis ofmajor activity (in terms of highest income/ turnover/employment). The above criteria were applied in the givenorder, viz., income first, then turnover and thenemployment, to determine the major activity. For the pilotsurvey, the activities were considered as mixed if theydiffered at 5-digit level of NIC-1998. For presenting theresults, the activities pursued by the institutions havebeen grouped into a few categories / major activities(Table A-1).

2.3 Sampling frame: A dual frame approach wasadopted for the purpose of sampling. Given that in Indiasome very ‘large’ NPIs/NPISHs (such as those registeredunder the Foreign Contribution Regulation Act (FCRA)1976 and similar other Acts/ authorities)x coexist withnumerous small NPIs/NPISHs (like sports and recreationclubs in the residential areas, which may not be evenregistered under any authority), a list frame ofinstitutionsxi was considered for sampling of ‘largeinstitutions’ and an area frame comprising villages asper Census 2001 and urban blocks as per EC 1998 was

SARVEKSHANA 23

considered for sampling the remaining institutions. Inthe area frame, a village or urban block was taken as thefirst-stage unit (fsu) and a frame of institutions withineach sample fsu (or part of fsu, if fsu had a population ofmore than 1,200) was prepared following a detailed listingprocedure (see paragraphs 2.3.2 to 2.3.5 and 2.4 fordetails).

2.3.1 Institutions comprising the list frame: It wasnoted that the largest registering authority, namely, theRegistrar of Societies, carry out registration under theSocieties’ Registration Act, 1860 (and its State variants)in a decentralised manner. It has offices in almost all theStates, and maintains the records manually. Compiling alist from their records, however, was found to be tediousand time-consuming. The Working Group constituted forfinalizing the survey methodology for this pilot surveydecided to use the list of institutions registered under theFCRA 1976 as the basic list and supplement this withlists from organisations under other ministries like thePlanning Commission (which also provides a list ofNGOs in its website), Centre for Advancement of People’sAction in Rural Technology (CAPART) under theMinistry of Rural Development, Ministry of Health, etc.For the selected districts of the States of Delhi, Kerala,Maharashtra and West Bengal, the list frame was preparedusing the list of institutions available from the websitesof the FCRA division and the Planning Commission,together with lists procured from CAPART and Ministryof Health. However, for Assam and Madhya Pradesh,the list also included the NPIs as obtained from the RBI.

2.3.2 Institutions in the area frame: For each samplefsu (see paragraph 2.4 for the selection procedure ofsample fsu’s), a frame of institutions as existing on thedate of survey was prepared by field investigators basedon a house-to-house visit. However, for an fsu havingpopulation (P) more than 1200, the fsu was divided intoa specified number (D) of sub-fsu’s (called hamlet-groupsin villages and sub-blocks in urban blocks), as per theprescribed guidelinesxii. Thus the whole fsu was surveyed(i.e., considered for preparation of frame of ultimateinstitutions), if P was less than 1201. Otherwise, at least

4 sub-fsu’s were formed (i.e. D

≥

4) and two of themwere selected by SRSWOR and merged to form thesample area unit (referred to as segment 1) for the purposeof listing of institutions for detailed enquiry. For samplefsu’s with sub-fsu formation, the frame of institutionsfor each sample fsu comprised two sub-frames, namely,(i) sub-frame 1 (referred in the survey as segment 9)consisting of all NPIs captured during NSS 57th round ofsurvey as well as other NPIs having at least 20 workers,found within the geographic boundary of the entire fsu;and (ii) sub-frame 2: consisting of all NPIs (other thanthose forming part of segment 9) which formed part ofsegment 1. Each sample fsu with no sub-fsu formationwas identified as segment 1 for the purpose of survey.The institutions featuring in the list frame, if found locatedwithin any sample fsu, were not considered/listed in thearea frame in order to avoid duplication of institutionsbetween two frames.

2.3.3 Within each sample fsu, the listing operation wasaimed at netting the NPISHs. The NPISH sector includesformal (registered or unregistered), and informalorganisations (institutions). The formal or largerorganisations, registered or unregistered, carry out theiroperations from a fixed site (either owned or taken onrent by the organisation). On the other hand, the informaland smaller organisations are located in the householdpremises of their members. In addition to these two typesof organisations, the National Accounts Division (NAD)of CSO informed that no database was available foractivities like “community constructionxiii” as these werenot covered earlier in any enterprise survey conductedby NSSO. Also, it is easier to capture such type ofactivities (like organising “night schools” carried out byhouseholds) in this survey as an extension of the informalNPI type activities. Accordingly, the units created for asingle project like community construction were alsolisted/captured. For preparing the frame of institutionswithin segment 1/9 of any sample fsu, two approacheswere adopted. While household approach was followedfor listing of institutions without fixed premises, a siteapproach was adopted to list the institutions having fixedpremises. In both the approaches, income-generating

SARVEKSHANA24

activities of the self-employed persons as well as otherprofit-making institutions were not considered for listing.

2.3.4 Each institution without fixed premises was listedat the household of the head of the institution. All suchinstitutions engaged (during the last 365 days precedingthe survey) in charitable/ welfare/ philanthropic activitiescarried out by a formal or informal group of persons (likesports/recreation clubs, pooja/milad organisingcommittees, welfare/religious associations, night guardgroups, drama clubs, charitable trusts, school managingcommittees, etc.) formed the target-group for listing.Among this target-group, only those institutions satisfyingall the three criteria, viz., i) funded entirely by membershipsubscription, ii) members consuming all the servicesproduced by the institution, and iii) not using any hiredworker, were kept out of the purview of frame/ surveycoverage.

2.3.5 Institutions having fixed premises were listed atthe respective sites. For such institutions, the ultimateframe included the following categories of institutions:

• Registered under listed Actsxiv and decision-making not controlled by government (i.e.other than government NPIs)

• Registered under listed Acts (specifiedabove) and not all the services renderedduring last 365 days exclusively forcorporate houses (i.e. other than corporateNPIs)

• Not registered under any Act but operatingwith an intention not to make profit (otherthan government/corporate NPIs)

• Not registered under any Act; operatingwith an intention to make profit but the unitcould not distribute profit among the co-owners (other than government/corporateNPIs)

2.4 Stratification, sample size and samplingprocedure: The institutions in the list frame werestratified by tabulation category (i.e., broad industrygroups) of NIC 1998. From each State/selected districts,90 institutions were selected in all. These 90 institutionswere allocated over strata in proportion to number ofinstitutions available in the respective strata as per theframe subject to a minimum allocation of 4 institutionsto each stratum. Some additional sample institutions (23in all considering all places) were however providedsubsequently because a small proportion of institutionswere found to be not actually located within the boundariesof the districts from which they were selected. Requirednumber of samples for each stratum was selected bySRSWOR. For area frame, fsu’s were stratified into 4strata, namely, stratum 1: sample fsu’s of NSS 57th roundnetting at least one NPI with receipt (excluding donationsreceived) less than total expenses (including compensationto employees, rent and interest payments); stratum 2: ofthe remaining fsu’s, sample fsu’s of NSS 57th roundnetting at least one other type of NPIs; stratum 3: of theremaining fsu’s, top 30 fsu’s in terms of number of NPIsfrom the EC 1998 list of fsu’s; and stratum 4: allremaining fsu’s in the frame. This stratification was doneindependently for rural and urban areas of a State butconsidering both districts (wherever applicable) of theState taken together. The sample allocation of number offsu’s for each of rural and urban sectors of a State was 4each to strata 1 and 2, and 3 each to strata 3 and 4. Inother words, 28 sample fsu’s were selected from eachState. For Delhi, where rural areas were not covered inthe pilot survey, all the 28 fsu’s were selected from urbanareas. For strata 1 and 2, fsu’s were selected by SRSWORwhereas for strata 3 and 4, sample fsu’s were selected byPPSWR with size as the number of workers in NPIs andin units receiving finance through Integrated RuralDevelopment Programme or assistance under povertyalleviation programmes as per EC 1998. Within eachsample fsu / segments 1 and 9, all eligible institutions(see paragraphs 2.3.3 to 2.3.5) were considered for survey.

2.5 Based on the sampling procedure, design-basedestimates of various survey characteristics were built up

SARVEKSHANA 25

using appropriate weights/multipliers. Separate estimatesfor list frame and area frame were generated and addedup to get combined aggregate estimates based on two

Statement 1: Sample size for the list frame

Number of institutions

Districts Available in Initially Additionalthe frame allotted samples Surveyed Casualty

allotted

(1) (2) (3) (4) (5) (6)

Delhi Statutory Town 1712 90 0 79 11

Cachar + Kamrup 836 90 1 88 3

Kolkata+ Medinipur 1358 90 8 95 3

Indore + Jabalpur 412 90 1 88 3

Mumbai + Nagpur 1150 90 1 85 6

Trissur + Kannur 502 90 12 94 8

All 5970 540 23 529 34

frames. Statements 1 and 2 below give the sample size ofthe pilot survey by districts. Distribution of sample sizeby district x major activity is given in Table A-2.

Statement 2: Sample size for the area frame

Rural UrbanDistricts Number of Number of Number of

fsu’s institutions fsu’s Number of unitssurveyed surveyed

Listed Surveyed Listed Surveyed

(1) (2) (3) (4) (5) (6) (7)

Delhi Statutory Town 0 0 0 28 55 39

Cacher + Kamrup 14 72 67 14 53 50

Kolkata + Midnapore 14 43 42 14 46 36

Indore + Jabalpur 14 73 70 14 65 51

Mumbai + Nagpur 13 87 82 14 133 122

Trissur + Kannur 14 55 50 14 53 46

All 69 330 311 98 405 344

SARVEKSHANA26

2.6 Schedules of enquiry and items of information:Pilot survey used two schedules namely Schedule 0.0(N)meant for listing of households/ institutions and Schedule2.0(N) as the detailed enquiry schedule for collectinginformation from the sample institutions. Schedule 2.0(N)was organized into few blocks, each block covering certainitems of information on related characteristics assummarized below:

• Block 0: Descriptive identification of sampleinstitution (name of State/ UT/ district/ tehsil/town/ village where institution is located; nameof head/informant; name and address of theinstitution)

• Block 1: Identification of sample institution (typeof frame used; sector; state-region; district;stratum; sub-round – all in terms of codes/numbers; Serial number of fsu; segment number;informant code distinguishing head/secretary/president, other member and other non-member;response code indicating level of cooperation;total time to canvass the schedule)

• Block 2: Particulars of operation of the institutionand background information (whether carriedmixed activity; details of major activity; natureof operation; number of months operated duringlast 365 days; location; availability of accounts;type of bank account; Act under which formed;year of registration under the Act; type ofassistance received during last five years; whetherworking mainly for government/corporate sector;if created for a one-time single-purpose activity)

• Block 3: Expenses and transfers for providinggoods and services during the reference year (withprovision for recording the details under variousheads)

• Block 4: Receipts during the reference year (withprovision for recording at the detailed item level-grants/donations received from government/

corporate bodies/households and membershipfees were separately recorded)

• Block 5: Employment particulars of theinstitution during the reference year (averagenumber of workers working for more than 8months / more than 3 months and up to 8 months/up to 3 months, with break-up for (a) sex, (b)type of worker: working member / hired worker/volunteer – with or without honorarium, and (c)full time/part time)

• Block 6: Compensation to workers during thereference year (with provision to record salary/wages for hired workers, salary/honorarium forworking members, honorarium for volunteers,and group benefits separately)

• Block 7: Fixed assets owned and hired as on thelast date of the reference year (by type of assetsi.e. land & building, plant & machinery, transportequipment, and tools & other fixed assets)

• Block 8: Financial assets as on the last date ofthe reference year (with provision to record (a)amount, interest/dividend and net additions tofixed assets during the reference year by type ofassets i.e. shares/ debentures/ fixed deposits/ cashin hand and at bank/ interest free deposits/ loans& advances/ others, (b) capital gain, and (c)capital loss)

• Block 9: Financial liabilities as on the last dateof the reference year (amount and interest/dividend payable by type of liability i.e. owncapital, shares issued, debentures issued, longterm interest bearing / interest free loans, loansand advances payable, and others)

• Block 10: Particulars of field operation

• Block 11/12: Remarks by investigator/supervisory officer(s)

SARVEKSHANA 27

2.7 Reference period: For all the institutions, dataon receipts, expenses, employment, emoluments, rent andinterest were collected for the “reference year”. Data werecollected from books of accounts from all the institutionswilling to provide information from their books ofaccounts. “Reference year” in these cases meant the lastaccounting year. For units that did not maintain booksof accounts (or maintained them but it was not possibleto get data from books of accounts), “reference year”meant the last 365 days preceding the date of enquiryand in such cases data were collected by oral enquiry.For an institution, which was unable to provideinformation for the last 365 days but could provideinformation for the latest 12 calendar months, figuresfor these 12 latest calendar months were taken. For someitems like value of assets, amount of loan outstanding,etc., the reference period was last day of the accountingyear/ date of survey/ last date of the last 12 completedcalendar months, depending on the method adopted fordata collection on expenses and receipts.

2.8 Efforts were made to collect as much informationfrom the books of accounts of the institutions as possible.For institutions willing to provide data from books ofaccounts, it was generally expected that the books ofaccounts would provide information for the period April2003 to March 2004. However, an institution, for somereason, either might extend its accounting period beyondone year, or reduce its accounting period to less than ayear. In such cases, the latest accounting period withclosing date falling within April 2003 to March 2004was considered as the reference period. However, if thelatest completed accounting period of an institution startedfrom April 2003 and extended beyond March 2004 (say,up to June 2004), figures from April 2003 to the end ofthis accounting period were collected. If the currentaccounting period of the institution (i.e., accounting periodstarting from April 2003) did not close till the date ofsurvey, figures from the latest completed accountingperiod were considered. If data could not be collectedfrom the books of accounts, oral enquiry was made torecord data required for the survey.

3. Major findings

3.1 General: This section presents estimates of somekey parameters relating to the NPIs. The findings relateonly to the group of districts of the six selected Statesand all these surveyed districts combined. Themethodology adopted for the pilot survey does not permitgeneration of State or national level estimates.

3.2 It is to be noted that the term ‘institution’ hasbeen used here to represent NPISH and Other NPI. Aninstitution has been classified as an NPISH if, thatinstitution, i) was not created for collective consumptionof households, ii) was not serving government orcorporate, iii) was not created for one-time single-purposeactivity and iv) had receipts from goods and services lessthan expenses on goods and services. Otherwise theinstitution is classified as ‘other NPI’. It may further benoted that NPISHs and other NPIs together do notnecessarily cover all NPIs since the pilot survey did notintend to cover corporate and government NPIs, althougha few such units could not be completely identified andeliminated at the listing stage. Such units found at thedetailed enquiry stage were surveyed and included under‘other NPIs’.

3.3 While discussing the survey results, ‘-’ has beenused in the statements and tables against the estimates ifno institution was surveyed in that particular level ofdisaggregation. On the other hand, the figure ‘0’ hasappeared at some levels of disaggregation where theestimated figure is very small and has become 0 due torounding off. The marginal totals and proportionspresented in various statements/tables may in some casesvary slightly due to rounding off of the figures.

3.4 The estimates presented here should be used withcaution keeping in view the number of sample institutionssurveyed at a particular level of disaggregation. This isparticularly true for many major activities for which thesample size is quite small (see Table A-2 for sample sizeby major activity).

SARVEKSHANA28

3.5 Estimated number of institutions and theirdistribution by major activity: As per the pilot survey,during 2004, about 368 thousand (rural and urbancombined) institutions (NPISHs and other NPIs) wereengaged in philanthropic activities in the surveyed districts(Table A-3). Nearly three-fourth (74%) of the institutionswere located in rural areas. As Figure 1 shows, of thetotal number of institutions, majority (64%) were‘religious organisations (REL)’ Other major activitieswith concentration of institutions were ‘activities of othermembership organizations (OMO)’(22%), ‘education(EDU)’ (5%), and ‘social work without accommodation(SWA)’ (5%). Considering all the activities, about 90%of the institutions in the rural areas and 78% of theinstitutions in the urban areas were ‘NPISHs’ and therest were ‘other NPIs’.

Figure 1: Percentage distribution of institutions by major activity

(EDU: Education; SWA: Social work without accommodation; REL: Religious organizations; OMO: Other membershiporganizations; OTH: Others)

3.6 Operational characteristics of the institutions:Considering all the 3,67,604 institutions (NPISHs andother NPIs combined) representing both list frame andarea frame, majority (87%) were perennial in nature, i.e.,operated during major part of the reference year(Statement 3). As regards the availability of books ofaccounts, nearly 71% did not maintain any accounts. Forabout 25% of the institutions, accounts were available.Majority of the institutions (86%) were not registeredunder any act at the time of formation. While 6% of theinstitutions were registered under Public Trust Act at thetime of their formation, nearly 5% of them were registeredunder Societies’ Registration Act 1860 or its Statevariants. About 77% of the institutions did not have anybank account. Nearly 13% of the institutions had bankaccount in the name of the organization – 12% having

SARVEKSHANA 29

savings bank account and 1% having current account.During the last five years preceding the date of survey,about 0.8% of the institutions received grant for capitalformation from international sources and 0.6% of theinstitutions received such grant from government sources.Other grants from international and government sourceswere respectively received by about 0.2% and 1.3% ofthe institutions. While 77% of the institutions receiveddonations from members, 92% of the institutions receiveddonation from other households. The above percentagesvary considerably between the list frame institutions andarea frame institutions (see Table A-4).

Statement 3: Percentages of institutions for certain operational characteristics

Estimated total number of institutions: 367,604

Characteristic Percentage of Characteristic Percentage ofinstitutions institutions

1. Nature of operation: 4. Possession of bank account:Perennial 86.8 No bank account 77.1Seasonal 6.6 Savings A/c in name of instn. 11.7

Current A/c in name of instn. 1.2

2. Availability of books of accounts: 5. Receipt of assistance during last 5 years:Not maintained 70.9 No assistance 3.0Maintained & available 25.1 Grant for CF- intl. Sources* 0.8Maintained, not available 3.7 Grant for CF – govt. sources 0.6

Other grant – intl. Sources 0.23. Act under which formed: Other grant – govt. sources 1.3Not under any Act 86.3 Donation from intl. Sources 0.2Public Trust Act 6.4 Donation from members 77.0Societies’ Registration Act 4.9 Donation from other hhs 92.2

(* CF: capital formation; intl: international)

3.7 Number of workers and their distribution bycategory of workers: An estimated 58,25,118 personswere engaged by 3,67,604 institutions in the selecteddistricts (Statement 4). In other words, on an average,each institution engaged about 15.8 persons. Femalesaccounted for 9.7% of the total number of workers.Majority of the workers were either working members(52.5%) or volunteers (41.8%) and the rest (5.7%) were

hired workers. Nearly 92% of the workers were workingwithout any honorarium.

3.8 It may be mentioned that if a member of aninstitution worked for the institution on a fairly regularbasis, with or without honorarium, he/she was called anworking member. In fact, for many institutions, membersthemselves manage all activities without help of any otherhelp (on a fairly regular basis). All working members,irrespective of the length of time for which they were inthe organisation, were accounted for. A hired workerwas a person employed directly or through some agency

on payment of regular wage/salary in cash or kind.Apprentices, paid or unpaid, were treated as hiredworkers. Paid household workers, servants and residentworkers of the institution were also considered as hiredworkers for the purpose of the survey. All non-memberworkers of the institution, except hired workers, wereconsidered as volunteers. Volunteers could have workedwith/without salary/honorarium.

SARVEKSHANA30

Statement 4: Distribution of workers by different categorizations of workers

Estimated number of institutions: 3,67,604; Estimated total number of workers: 58,25,118

Categorization 1 Categorization 2 Categorization 3

Male Female Working Hired Volunteer Working Workingmember worker with without

salary/ honorariumhonorarium

Aggregate number of workers:

52,60,330 5,64,788 30,60,741 3,31,885 24,32,492 4,41,417 53,83,701

Average number of workers per institution:

14.3 1.5 8.3 0.9 6.6 1.2 14.6

Percentage share of any given category of workers in total number of workers:

90.3% 9.7% 52.5% 5.7% 41.8% 7.6% 92.4%

3.9 Following another categorization, each workerwas classified as full-time or part-time worker. In thesurvey, data on employment during the reference yearwere collected for different length of time for whichworkers were engaged in the institution, e.g., up to 3months, 3 to 8 months, and more than 8 months. For aworker classified under any of these categories, she or hewas treated as a full-time worker if she/he worked formore than half of the period of normal working hours ofthe institution on a fairly regular basis during that giventime-period. Workers who did not qualify as full-timeworkers were considered as part-time workers. Accordingto the survey, majority (87%) of the workers of theinstitutions were part-time workers.

3.10 Major findings on NPISHs: In the remainingpart of this paper, we shall confine our discussions toNPISHs only (see paragraph 3.2 for definition of NPISH).It may be noted that, as per the pilot survey, out ofestimated 3,67,604 institutions (NPISHs and other NPIscombined), majority (86.7%) were NPISHs (refer to lastrow of Table A-3). The discussion will also be restrictedto the 8 major activities (viz., major activity codes M1,M2, N2, N3, N4, O2, O3 and O4) for each of which thetotal number of sample NPISHs in all surveyed districts

is at least 16 (see Tables A-2 and A-5 for sample size bymajor activity). Estimates for the remaining majoractivities (for each of which the sample size is less than10) are presented in the Appendix. The users are howeveradvised to use them with a great deal of caution. Thesurvey estimates of average per institution (NPISH) forthe following characteristics will be discussed here:Number of workers, Annual compensation to workers,Expenses and receipts, Net value added, Fixed assets andrent on hired assets, Financial assets, and Financialliabilities.

3.10.1 Average number of workers per institution: Onan average each institution (henceforth the terminstitution refers to NPISH) engaged 16.4 workers duringthe reference year (Statement 5 and Table A-5), out ofwhich majority (15.8) worked without any honorarium.Average number of workers per institution was muchhigher (48.7) for list frame institutions than that (16.2)of their counterparts in the area frame. This averagenumber of workers per institution in the combined framevaried considerably across the specific major activities(henceforth specific major activities would mean 8 majoractivities with sample size 16 or more) from 11.4 (forN4: Social work without accommodation) Social work

SARVEKSHANA 31

without accommodation Social work withoutaccommodation Social work without accommodation to68.1 (for N3: Social work with accommodation)Socialwork without accommodation.

Statement 5: Average number of workers per NPISH by type of frame

Major Average number of workers per NPISH Estimated number of Sample number ofactivity NPISHs NPISHs

List Area Combined List Area Comb. List Area Comb.Frame Frame Frame Frame Frame Frame

ALL WOH ALL WOH ALL WOH

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

M1 62.7 36.4 16.7 7.8 38.6 21.4 204 224 428 16 15 31

M2 34.2 16.3 31.3 6.2 32.3 9.7 94 180 274 12 6 18

N2 18.7 10.9 34.8 24.3 27.1 17.9 79 87 165 7 9 16

N3 87.1 39.8 5.4 1.9 68.1 30.9 325 99 424 29 7 36

N4 27.7 15.9 9.4 9.3 11.4 10.0 914 7616 8530 65 42 107

O2 53.2 32.8 12.2 11.7 12.2 11.7 220 227220 227440 21 202 223

O3 53.2 49.6 28.6 28.6 28.6 28.6 46 77533 77579 5 31 36

O4 30.1 24.8 17.7 16.6 23.0 20.1 81 108 189 7 16 23

All* 48.7 22.9 16.2 15.8 16.4 15.8 2228 316425 318652 183 345 528

* ‘All’ in the last row includes other major activities; See Table A-1 for descriptions of major activities;ALL: All workers; WOH: Those working without salary/honorarium)

3.10.2 Average annual compensation to workers perinstitution: Compensation included (a) salary/wages,allowances and other individual benefits for hired workers,(b) salary/honorarium for working members, (c)honorarium for volunteers, and (d) group benefits likeemployer’s contribution towards canteen, sports,insurance, etc. The survey revealed that out of total annualcompensation paid to workers by an institution, the majorpart went to pay salary/honorarium to hired workers(Statement 6). This is true for each of the specific majoractivities. There is a huge variation in the amount ofcompensation per institution over the specific major

activities, the highest amount having been observed formajor activity M2 (secondary education). Reference maybe made to Table A-6 for the position in respect of eachmajor activity by type of frame.

3.10.3 Expenses and receipts per institution: Estimatedaverage expenditure and average receipts per institution(NPISH) under different heads of expenses/receipts forthe combined frame by major activity are presented inTables A-7 and A-8, respectively. Grant/donationcomprised the major part of overall receipts. The majorcomponents of overall expenditure were expenditure ongoods and services, current transfers, emoluments, and‘other expenses’ (other than taxes on production/products,rent and interest).

SARVEKSHANA32

Statement 6: Average annual compensation to workers per NPISH

List frame and area frame combined

Major Average annual compensation to workers Number of institutionsactivity per institution (Rs)

Group Salary/honorarium Estimated Samplebenefits Working Hired Volunteer

member worker

(1) (2) (3) (4) (5) (6) (7)

M1 1468 29953 332150 72630 428 31

M2 0 2020 2380098 35 274 18

N2 494 4 71563 2108 165 16

N3 4626 19686 201420 184735 424 36

N4 153 1092 32541 614 8530 107

O2 4 92 2515 469 227440 223

O3 2 3 160 0 77579 36

O4 1300 6 118370 5180 189 23

All* 160 326 6378 732 318652 528

* ‘All’ in the last row includes other major activities; See Table A-1 for descriptions of major activities

3.10.4 Net value added per institution: Generally, valueadded by an institution or a sector of activity determinesits relative position in the economy. It is pertinent tomention here that since NPISH is a non-market non-profitinstitution, its output was evaluated by its cost ofproduction and hence ‘net value added (NVA)’ for NPISHwas defined as the sum of taxes on production,emoluments, rent and interest payable in the referenceperiod (the net operating surplus on the production ofnon-market goods or services produced by the NPISHsis assumed to be zeroxv). The average NVA during thereference year per institution for NPISHs separately by

type of frame and for each major activity is given in TableA-9. It may be seen that there is considerable variation inthe scale of operation as reflected in NVA across the twoframes used for the purpose of survey. For list frameNPISHs, the average annual NVA was Rs 5,91,129,whereas for area frame NPISH, it was only Rs 4,272.There is variation in NVA across different activities toofor each type of frame. If we look at the ‘specific majoractivities’, in the combined frame, the largest NVA perNPISH (Rs 23,94,677) was observed (Figure-2) forsecondary education (M2) and the smallest (Rs 796 only)for other membership organisation (O3).

SARVEKSHANA 33

Figure 2: Net value added (Rs) per NPISH during the reference year for combined frame

(M1: Primary education Primary education; M2: Secondary education; N2: Health activities other than hospital activities; N3: Socialwork with accommodation; N4: Social work without accommodation; O2: Activities of religious organizations; O3: Activities of othermembership organizations; O4: Recreational, cultural and sporting activities)

3.10.5 Fixed assets and rent on hired assets: Themarket value of fixed assets held by an institution as onthe date of survey for the purpose of producing orproviding goods or services was collected in the survey.This covered all goods, new or used, owned or hired, thathad a normal economic life of more than one year fromthe date of purchase. Fixed assets were classified by typeof assets, namely, land and building, plant and machinery,transport equipment, and tools and other fixed assets.The average market value of fixed assets and averagerent payable during the reference year for hired assetsper institution is given in Table A-10 separately for eachmajor activity and type of frame. The average value of

fixed assets (owned plus hired) was Rs. 2,25,297 forarea frame NPISH. On the other hand, the same wasRs. 69,57,331 for the list frame NPISH, almost 30 timesof its area frame counterpart. Only about 3.3 per cent ofthe assets held by a list frame NPISH was hired. Averagevalue of hired assets and rent payable on them per NPISHwas much higher for list frame units than those for areaframe units. Considering the specific major activities (seeStatement 7 below), average value of fixed assets ownedper NPISH for the combined frame was highest (aboutRs 109 lakh) for N3 (institutions engaged in social workwith accommodation) and lowest (Rs 2 lakh) for O2(religious organisations).

SARVEKSHANA34

Statement 7: Average value of fixed assets, net additions to fixed assets and rent payable on hired assets perNPISH in the combined frame

(Figures in rupees)

Major Average value of fixed assets as on Net additions Rent payableactivity last date of reference year to fixed assets on hired

Owned Hired All during assets duringLand and Others reference year reference yearBuilding

(1) (2) (3) (4) (5) (6) (7)

M1 248510 27151 82146 357807 47595 1496

M2 2057809 197735 979483 3235027 343187 8293

N2 584690 220721 372045 1177456 22473 11349

N3 9906690 954804 533090 11394584 1690566 23155

N4 529612 61579 16500 607692 119108 1539

O2 200432 4808 35160 240400 6679 70

O3 227550 4614 363 232527 143 0

O4 1186991 181699 57494 1426184 130991 1480

All* 230748 12088 29524 272360 10821 223

(* All includes other major activities)See Table A-1 for descriptions of major activities

3.10.6 Financial assets per institution: Information onvalue of financial assets as on the last date of referenceyear, net additions to financial assets during the referenceyear, and interest/ dividend receivable during the referenceyear by type of assets - i.e., shares, debentures, fixeddeposits, cash in hand and at bank, interest-free deposits,loans and advances receivable, and others - were collectedfrom each sample institution. The estimates of averagevalue per institution by major activity separately for list

frame and area frame are presented in Table A-11. Thecorresponding estimates for the combined frame and forspecific major activities are summarized in Statement 8.It may be seen that average value of financial assets perinstitution varied widely among specific major activities– viz., between Rs 4,617 (for O3: other membershiporganizations) to Rs 1,06,72,319 (for N3: institutionsengaged in social work with accommodation).

SARVEKSHANA 35

Statement 8: Average value of financial assets per NPISH in the combined frame

Major Value Net addition Annual Net capital Number of NPISHsactivity (in Rs.) of to financial interest/ gain

financial assets (in Rs.) dividend (in Rs.)assets as during the receivable during the

on last reference (in Rs.) reference year Estimated Sample

date of year during thereference reference year

year

(1) (2) (3) (4) (5) (6) (7)

M1 193596 43954 4776 -94 428 31

M2 1212922 805 76829 -22084 274 18

N2 1484445 403902 76981 12 165 16

N3 10672319 867973 448611 1068 424 36

N4 471188 63673 22577 -641 8530 107

O2 9646 -251 375 -36 227440 223

O3 4617 433 174 -3 77579 36

O4 978466 -18279 126773 -453 189 23

All* 40882 3134 1885 -76 318652 528

* All includes other major activitiesSee Table A-1 for descriptions of major activities

3.10.7 Financial liabilities: In the pilot survey, data onfinancial liabilities as on last date of reference year bytype of liability were also collected from each institution.Types of liabilities included institution’s own capital,shares issued, debentures issued, long-term interest-bearing/ interest-free loans, loans and advances payable,and others. Estimates of avearage values of financialliability and annual interest payable per institution bytype of frame x major activity are presented in Table A-12. For list frame NPISHs, the financial liability of aninstitution, on an average, amounted to Rs.76,23,553,which was about 162% of the value of financial assetsowned by them. The corresponding figure for area frameNPISHs was Rs 24,797 as average financial liability,which was about 311% of the average value of financialassets it owned. There are wide variations in theseestimates across major activities.

4. Concluding observations

4.1 Two types of frames, namely list frame and areaframe, were used in the pilot survey for sampling. Listframe was used with a view to capturing relatively largeinstitutions in adequate number so as to improve therepresentativeness of the estimates. As per the survey, anestimated 2,228 NPISHs of list frame on an averagecontributed Rs. 5,91,129 each while 3,16,425 NPISHs ofarea frame contributed about Rs. 4,272 each in theaggregate net value added. Thus the list frame units had ashare of about 49% in the aggregate net value addition bythe NPISH sector. In other words, identification of relativelyfew units at the stage of sampling helped in capturing asignificant contribution of aggregate value addition throughlist frame approach. It may be worthwhile to repeat thisprocedure in a full-fledged survey on this subject.

SARVEKSHANA36

4.2 It is to be noted that the list frame was constructedmainly using the frames maintained by FCRA divisionof Ministry of Home Affairs and the largest source ofNPIs, viz., those registered under the Societies’Registration Act, 1860 could not be considered forpreparation of the list frame because of the non-availability of computerized lists. This resulted in thecurtailing of the use of list frame in estimating theaggregate value addition and other survey characteristics.Thus development of a computerized list frame ofinstitutions registered under the Societies’ RegistrationAct would indeed be a significant achievement beforelaunching a survey on the subject.

4.3 In the pilot survey, out of 540 institutions selectedfrom the list frame, as many as 74 institutions were notfound at the given address or even close by. Further,substitution had to be resorted to in 13 cases due toincomplete address as per the frame. Thus, beforeplanning a detailed survey in future it would be desirableto have a more updated frame in order to overcome theidentification problems faced during the pilot survey.

4.4 In a good number of cases, field difficulties wereexperienced in collecting information on employment andcompensation to workers as per the detailed itemization,particularly in respect of the NPIs which did not maintainbooks of accounts. It may be advisable to avoid such adetailed itemization.

4.5 The pilot survey on NPISH was conducted bythe NSSO for the first time. One of the major objectivesof the survey was to assess the feasibility of collectionof data on receipts, expenditure, etc. in respect of suchinstitutions so that the experience could be utilized tore-orient the survey methodology for any main surveyon the subject in future. Although the overall responseby the institutions was found to be encouraging, ananalysis of the data on time taken to canvass the detailedenquiry schedule reveals that, on an average, thecanvassing time per schedule/institution was about 2hours 40 minutes in case of area frame and nearly 4hours 20 minutes in case of list frame. It may beappropriate to cut down the size of the schedule in orderto minimize respondents’ fatigue.

SARVEKSHANA 37

Annex

Table A-1: List of activities covered in the pilot survey

Tabulation category / Major activity NIC 1998 codes Notations used inthe statements

and tables

(1) (2) (3)

A Agriculture, hunting and forestry 01+02 A

B Fishing 05 B

C Mining and quarrying 10 to 14 C

D Manufacturing 15 to 37 D

E Electricity, gas and water supply 40+41 E

F Construction 45 F

G Trade, repair of motor vehicles, personal 50 to 52 Gand household goods

H Hotels 551 H1Restaurants 552 H2

I Transport, storage and communication 60 to 64 I

J Financial intermediation 65 to 67 J

K Real estate, renting and business activities 70 to 74 K

L Public administration and defence, compulsory 75 Lsocial security

M Primary education 801 M1Secondary education 802 M2Higher education 803 M3Adult and other education 809 M4

N Hospital activities 8511 N1Other health activities 8512+8519+8520 N2Social work with accommodation 8531 N3Social work without accommodation 8532 N4

O Activities of business, employers and professional 91-919 O1organizations and trade unionsActivities of religious organisations 9191 O2Activities of other membership organisations 919-9191 O3Recreational, cultural and sporting activities 92 O4Other service activities 90+93 O5

All tabulation categories under survey coverage (A-O) All

SARVEKSHANA38

Table A-2: Number of institutions surveyed by major activity and by districts

(List frame and area frame combined)

Number of institutions surveyed (NPISHs and other NPIs combined)Districts

Major Delhiactivity Statu- Cachhar+ Kolkata+ Indore+ Mumbai+ Trissur+ All

tory Kamrup Medinipur Jabalpur Nagpur KannurTown

(1) (2) (3) (4) (5) (6) (7) (8)

A 0 1 5 0 1 0 7 (3)

B 0 0 0 0 0 0 0 (0)

C 0 0 0 0 0 0 0 (0)

D 4 2 2 2 3 1 14 (2)

E 0 0 0 0 1 0 1 (0)

F 0 1 2 0 1 1 5 (2)

G 0 0 0 0 1 0 1 (0)

H1 1 1 2 4 2 1 11 (3)

H2 0 0 0 1 0 0 1 (0)

I 0 0 0 2 0 0 2 (0)

J 0 1 1 0 0 0 2 (0)

K 4 2 2 1 8 0 17 (9)

L 0 1 0 0 0 0 1 (0)

M1 5 37 11 35 10 10 108 (31)

M2 12 19 10 33 22 15 111 (18)

M3 3 6 2 2 18 7 38 (2)

M4 1 5 5 2 5 6 24 (6)

N1 1 2 0 4 5 10 22 (2)

N2 8 11 10 5 6 3 43 (16)

N3 9 5 4 8 19 36 81 (36)

N4 21 2 32 11 67 19 152 (107)

O1 4 6 1 1 1 0 13 (5)

O2 8 43 44 58 78 58 289 (223)

O3 4 32 10 4 11 6 67 (36)

O4 2 11 5 1 11 7 37 (23)

O5 0 4 4 2 2 1 13 (3)

N.R. 31 13 21 33 17 9 124 (1)

All 118 205 173 209 289 190 1184(528)Figures within brackets in column (8) denote number of sample NPISHs See Table A-1 for descriptions of major activities(N.R: Not reported)

SARVEKSHANA 39

Table A-3: Estimated Number of institutions by major activityAll districts combined Both frames combined

Number of institutions Rural & Urban Combined

Rural Urban % of institutions

Major NPISH Other NPISH Other Total Working Created foractivity NPIs NPIs number of mainly one-time

institutions for Govt./ single-corporate purpose

activity

(1) (2) (3) (4) (5) (6) (7) (8)

A 34 38 17 1 90 19 0

B - - - - - - -

C - - - - - - -

D 2 4 29 142 177 3 16

E - - - 4 4 0 0

F 1 1 2 18 22 5 75

G - 1 - - 1 0 0

H1 8 36 19 37 100 5 37

H2 - - - 4 4 0 0

I - 1 - 5 6 0 0

J - 30 - - 30 43 0

K 0 21 65 90 176 42 11

L - 1 - - 1 100 0

M1 300 8597 129 331 9357 31 36

M2 152 2312 121 493 3078 2 63

M3 0 61 37 385 483 2 0

M4 4 95 53 3560 3712 0 4

N1 0 41 35 89 165 4 4

N2 78 22 87 3494 3681 1 90

N3 138 86 285 273 782 10 6

N4 259 562 8272 10110 19203 0 1

O1 0 11 3282 100 3393 3 2

O2 193573 9485 33867 478 237403 0 3

O3 50916 1537 26665 157 79275 0 2

O4 103 1241 86 65 1495 8 0

O5 0 3371 18 76 3465 1 0

N.R. 0 281 16 1199 1496 0 2

All 245567 27838 73087 21112 367604 1 5(N.R: Not reported)See Table A-1 for descriptions of major activities

SARVEKSHANA40

Table A-4: Operational characteristics of institutions (NPISHs and other NPIscombined) by type of frame

Characteristic Percentage of institutions possessingthe characteristic

List frame Area frame Combined

(1) (2) (3) (4)

1. Nature of operation:

Perennial 75.3 86.9 86.8

Seasonal 0.2 6.7 6.6

2. Availability of books of accounts:

Not maintained 3.1 72.0 70.9

Maintained & available 66.1 24.4 25.1

Maintained, not available 6.9 3.6 3.7

3. Act under which formed:

Not under any Act 6.8 87.6 86.3

Public Trust Act 9.2 6.4 6.4

Societies Registration Act, 1860 48.4 4.2 4.9

4. Possession of bank account:

No bank account 2.2 78.4 77.1

Savings A/c in the name of institution 60.6 10.9 11.7

Current A/c in the name of institution 7.7 1.1 1.2

5. Receipt of assistance during last 5 years:

No assistance 3.5 3.0 3.0

Grant for capital formation- international sources 3.1 0.8 0.8

Grant for capital formation - govt. sources 3.8 0.5 0.6

Other grant - international sources 9.7 0 0.2

Other grant - govt. sources 34.5 0.8 1.3

Donation from international sources 14.0 0 0.2

Donation from members 27.8 77.8 77.0

Donation from other hhs 46.0 92.9 92.2

Estimated number of institutions 5,966 361,638 367,604

SARVEKSHANA 41

Table A-5: Average number of workers per NPISH by type of frame

Major Average number of workers per NPISH Estimated number of Sample number ofactivity NPISHs NPISHs

List Area Combined List Area Comb. List Area Comb.Frame Frame Frame Frame Frame Frame

ALL WOH ALL WOH ALL WOH

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

A 17.3 10.3 - - 17.3 10.3 51 - 51 3 0 3

B - - - - - - - - - 0 0 0

C - - - - - - - - - 0 0 0

D 29.2 0.1 - - 29.2 0.1 31 - 31 2 0 2

E - - - - - - - - - 0 0 0

F 83.3 10.7 - - 83.3 10.7 4 - 4 2 0 2

G - - - - - - - - - 0 0 0

H1 - - 25.8 20.8 25.8 20.8 - 27 27 0 3 3

H2 - - - - - - - - - 0 0 0

I - - - - - - - - - 0 0 0

J - - - - - - - - - 0 0 0

K 17.4 5.3 12.8 6.2 15.6 5.7 39 26 65 5 4 9

L - - - - - - - - - 0 0 0

M1 62.7 36.4 16.7 7.8 38.6 21.4 204 224 428 16 15 31

M2 34.2 16.3 31.3 6.2 32.3 9.7 94 180 274 12 6 18

M3 38.0 7.0 47.0 8.0 40.2 7.2 28 9 36 1 1 2

M4 30.8 5.3 6.7 4.4 25.6 5.1 44 12 57 3 3 6

N1 390.4 9.5 - - 390.4 9.5 35 - 35 2 0 2

N2 18.7 10.9 34.8 24.3 27.1 17.9 79 87 165 7 9 16

N3 87.1 39.8 5.4 1.9 68.1 30.9 325 99 424 29 7 36

N4 27.7 15.9 9.4 9.3 11.4 10.0 914 7616 8530 65 42 107

O1 35.0 35.0 15.0 14.0 15.1 14.1 11 3272 3283 1 4 5

O2 53.2 32.8 12.2 11.7 12.2 11.7 220 227220 227440 21 202 223

O3 53.2 49.6 28.6 28.6 28.6 28.6 46 77533 77579 5 31 36

O4 30.1 24.8 17.7 16.6 23.0 20.1 81 108 189 7 16 23

O5 27.0 27.0 9.7 5.6 15.4 12.7 6 12 17 1 2 3

N.R. 83.0 8.0 - - 83.0 8.0 16 - 16 1 0 1

All 48.7 22.9 16.2 15.8 16.4 15.8 2228 316425 318652 183 345 528

See Table A-1 for descriptions of major activities(ALL: All workers; WOH: Those working without salary/honorarium; N.R: Not reported)

SARVEKSHANA42

Table A-6: Average annual compensation to workers per NPISH by type of frame

Major Average annual compensation to workers Number of institutionsactivity per institution (Rs)

Group Salary/honorarium Estimated Samplebenefits Working Hired Volunteer

member worker

(1) (2) (3) (4) (5) (6) (7)

List Frame

A 0 8967 37841 7979 51 3

B - - - - - 0

C - - - - - 0

D 20299 1557794 1430 0 31 2

E - - - - - 0

F 0 0 16539 354714 4 2

G - - - - - 0

H1 - - - - - 0

H2 - - - - - 0

I - - - - - 0

J - - - - - 0

K 45842 64822 1197938 0 39 5

L - - - - - 0

M1 3083 14748 234576 112606 204 16

M2 0 5901 1360356 0 94 12

M3 0 0 538258 0 28 1

M4 0 8392 329118 71073 44 3

N1 1219896 0 873389 0 35 2

N2 0 0 67131 4427 79 7

N3 6034 24114 252966 240953 325 29

N4 1348 10191 280401 2840 914 65

O1 0 0 0 0 11 1

O2 2605 6153 1133852 468 220 21

O3 1543 4272 121799 741 46 5

O4 3035 0 272199 11550 81 7

O5 0 0 0 0 6 1

N.R. 5897 0 2870389 131762 16 1

All 22539 32910 427798 50376 2228 183

See Table A-1 for descriptions of major activities(N.R: Not reported)

(Contd.)

SARVEKSHANA 43

Table A-6: Average annual compensation to workers per NPISH by type of frame

Major Average annual compensation to workers Number of institutionsactivity per institution (Rs)

Group Salary/honorarium Estimated Samplebenefits Working Hired Volunteer

member worker

(1) (2) (3) (4) (5) (6) (7)

Area Frame

A - - - - - 0

B - - - - - 0

C - - - - - 0

D - - - - - 0

E - - - - - 0

F - - - - - 0

G - - - - - 0

H1 0 0 50485 10362 27 3

H2 - - - - - 0

I - - - - - 0

J - - - - - 0

K 27 0 164147 0 26 4

L - - - - - 0

M1 0 43777 420863 36284 224 15

M2 0 0 2910716 53 180 6

M3 0 0 643725 362082 9 1

M4 0 258 25046 5420 12 3

N1 - - - - - 0

N2 943 7 75590 0 87 9

N3 0 5138 32036 0 99 7

N4 10 0 2806 346 7616 42

O1 60 208 26719 0 3272 4

O2 1 86 1417 469 227220 202

O3 1 0 88 0 77533 31

O4 0 11 3098 407 108 16

O5 0 0 75709 11092 12 2

N.R. - - - - - 0

All 2 96 3412 383 316425 345

See Table A-1 for descriptions of major activities(N.R: Not reported)

(Contd.)

SARVEKSHANA44

Table A-6: Average annual compensation to workers per NPISH by type of frame

Major Average annual compensation to workers Number of institutionsactivity per institution (Rs)

Group Salary/honorarium Estimated Samplebenefits Working Hired Volunteer

member worker

(1) (2) (3) (4) (5) (6) (7)

Combined Frame

A 0 8967 37841 7979 51 3

B - - - - - 0

C - - - - - 0

D 20299 1557794 1430 0 31 2

E - - - - - 0

F 0 0 16539 354714 4 2

G - - - - - 0

H1 0 0 50485 10362 27 3

H2 - - - - - 0

I - - - - - 0

J - - - - - 0

K 27769 39250 790118 0 65 9

L - - - - - 0

M1 1468 29953 332150 72630 428 31

M2 0 2020 2380098 35 274 18

M3 0 0 563507 86684 36 2

M4 0 6640 263646 56936 57 6

N1 1219896 0 873389 0 35 2

N2 494 4 71563 2108 165 16N3 4626 19686 201420 184735 424 36

N4 153 1092 32541 614 8530 107

O1 60 207 26629 0 3283 5

O2 4 92 2515 469 227440 223

O3 2 3 160 0 77579 36

O4 1300 6 118370 5180 189 23

O5 0 0 50574 7410 17 3

N.R. 5897 0 2870389 131762 16 1

All 160 326 6378 732 318652 528

See Table A-1 for descriptions of major activities(N.R: Not reported)

SARVEKSHANA 45

Table A-7: Average value of expenses per NPISH in the combined frame

Major Average value of expenses (Rs) per institution during the reference yearactivity Goods Others Current Payments on

and Taxes on Others transfersservices Production Products Emoluments Rent Interest

(1) (2) (3) (4) (5) (6) (7) (8) (9)

A 67587 0 0 145437 146633 54787 8541 0

B - - - - - - - -

C - - - - - - - -

D 688363 0 0 800998 70144 1579523 73616 0

E - - - - - - - -

F 314783 78 0 115888 1224456 371253 151269 0

G - - - - - - - -

H1 571423 0 8845 452362 170082 60847 0 4243

H2 - - - - - - - -

I - - - - - - - -

J - - - - - - - -

K 2029893 103266 0 639311 288076 857137 318235 63

L - - - - - - - -

M1 61177 139 0 62518 28681 436113 1496 7096

M2 140382 3452 0 115912 203141 2382153 8293 780

M3 454527 3926 0 263344 4668 650397 42074 0

M4 295535 0 0 401784 278624 327222 1216 574

N1 9905477 530124 0 25161722 0 2093285 0 0

N2 411378 6 0 260841 81607 74169 11349 0

N3 2590420 8818 0 3966780 1356380 409788 23155 6678

N4 46800 1214 66 190882 137970 34399 1539 323

O1 4743 45 0 1837 88 26895 0 8

O2 15383 303 28 13883 11121 3079 70 37

O3 19056 629 15 3919 2583 165 0 1

O4 166738 601 390 102093 6619 124856 1480 0

O5 262863 11925 0 53133 26767 57983 1262 0

N.R. 1087661 57814 0 905600 510155 3008048 102500 0

All 22693 502 26 24850 14519 7595 223 55

See Table A-1 for descriptions of major activities(N.R: Not reported)

SARVEKSHANA46

Table A-8: Average value of receipts per NPISH in the combined frame

Major Average value of receipts (Rs) per institution during the reference yearactivity From goods and services Current Property Income Net

Market Non- Imputed grant/ Others capitalmarket receipts donation Rent Interest gain

(1) (2) (3) (4) (5) (6) (7) (8) (9)

A 8786 4799 23274 244481 161589 12407 323 0

B - - - - - - - -

C - - - - - - - -

D 8745 0 0 4505332 75720 0 35676 0

E - - - - - - - -

F 0 0 0 1950370 -70982 771 0 0

G - - - - - - - -

H1 4477 37152 7595 1185431 102 17967 273150 0

H2 - - - - - - - -

I - - - - - - - -

J - - - - - - - -

K 147346 4085 0 1927011 892433 443768 323352 -6386

L - - - - - - - -

M1 13961 2643 33 650651 9542 176 4776 -94

M2 6023 45439 242 2954237 7504 0 76829 -22084

M3 44267 95040 0 799842 62369 0 8197 0

M4 0 26729 0 1459429 5867 0 40952 0

N1 32118720 5389 105019 7904344 839838 0 128339 0

N2 212201 25 116 534590 210 0 76981 12

N3 5191 363233 4446 9627653 116568 124126 448611 1068

N4 2375 1585 122 386714 4230 16941 22577 -641

O1 0 7 0 41321 3 453 70 0

O2 26 1725 23 36954 2162 2669 375 -36

O3 129 2 24 25014 67 3551 174 -3

O4 1830 523 1554 141917 15383 24671 126773 -453

O5 0 0 0 58553 1264 35485 451859 0

N.R. 0 181605 0 4662689 88896 0 901884 -248520

All 3845 1831 49 62278 2177 3503 1885 -76

See Table A-1 for descriptions of major activities(N.R: Not reported)

SARVEKSHANA 47

Table A-9: Average annual net value added per NPISH by type of frame

Major Average net value added Sample number of institutionsactivity per institution (Rs)

List Area Combined List Area CombinedFrame Frame Frame Frame Frame Frame

(1) (2) (3) (4) (5) (6) (7)

A 63228 - 63328 3 0 3

B - - - 0 0 0

C - - - 0 0 0

D 1653139 - 1653139 2 0 2

E - - - 0 0 0

F 522599 - 522599 2 0 2

G - - - 0 0 0

H1 - 65090 65090 0 3 3

H2 - - - 0 0 0

I - - - 0 0 0

J - - - 0 0 0

K 1853027 397155 1278700 5 4 9

L - - - 0 0 0

M1 381452 502479 444844 16 15 31

M2 1395325 2914686 2394677 12 6 18

M3 586528 1045453 696397 1 1 2

M4 410863 30724 329012 3 3 6

N1 2623409 - 2623409 2 0 2

N2 95301 76639 85523 7 9 16

N3 559701 82835 448440 29 7 36

N4 320479 3524 37475 65 42 107

O1 900 27038 26949 1 4 5

O2 1308935 2223 3489 21 202 223

O3 146246 710 796 5 31 36

O4 291056 3953 126937 7 16 23

O5 0 106541 71170 1 2 3

N.R. 3168362 - 3168362 1 0 1

All 591129 4272 8375 183 345 528

See Table A-1 for descriptions of major activities(N.R: Not reported)

SARVEKSHANA48

Table A-10: Market value of fixed assets on date of survey and rent payable on hired assets duringthe reference per NPISH by type of frame

Average value of fixed assets per institution (Rs) Average rent payable onMajor hired assets peractivity Owned Hired institution (Rs)

List Area Combined List Area Combined List Area CombinedFrame Frame Frame Frame Frame Frame Frame Frame Frame

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

A 184211 - 184211 60444 - 60444 8541 - 8541

B - - - - - - - - -

C - - - - - - - - -

D 4336504 - 4336504 0 - 0 73616 - 73616

E - - - - - - - - -

F 3037025 - 3037025 714514 - 714514 151269 - 151269

G - - - - - - - - -

H1 - 2362263 2362263 - 0 0 - 0 0

H2 - - - - - - - - -

I - - - - - - - - -

J - - - - - - - - -

K 608929 2612145 1399177 47661 0 28859 525565 0 318235

L - - - - - - - - -

M1 311948 242671 275661 64743 97968 82146 1491 1500 1496

M2 6048092 282107 2255544 430940 1264915 979483 20612 1882 8293

M3 99407 473799 189039 1500000 0 1140892 48000 23245 42074

M4 380605 1377 298950 27665 0 21708 1549 0 1216

N1 33080490 - 33080490 2791292 - 2791292 0 - 0

N2 220698 1336728 805411 780456 930 372045 23737 92 11349

N3 13981743 608259 10861494 418145 910803 533090 17196 42736 23155

N4 5226423 35116 591191 121762 3872 16500 13744 75 1539

O1 650 4364 4351 0 149562 149056 0 0 0

O2 14937653 190951 205240 4084 35191 35160 69882 2 70

O3 2451182 230847 232164 1837 362 363 763 0 0

O4 2982413 159443 1368690 61794 54271 57494 3339 86 1480

O5 0 34363068 22954767 400000 0 132797 0 1889 1262

N.R. 316372 - 316372 0 - 0 102500 - 102500

All 6724391 197205 242836 232940 28092 29524 29143 20 223

See Table A-1 for descriptions of major activities(N.R: Not reported)

SARVEKSHANA 49

Table A-11: Value of financial assets per NPISH by type of frame

Major List Frame Area FrameActivity

Value (in Net Annual Value (in Net AnnualRs.) of addition to interest/ Rs.) of addition to interest/

financial financial dividend financial financial dividendassets as on assets (inRs.) receivable assets as assets (in receivablelast date of during (in Rs.) on last Rs.) (in Rs.)

reference reference during date of during duringyear year reference reference reference reference

year year year year

(1) (2) (3) (4) (5) (6) (7)

A 6934 348 323 - - -

B - - - - - -

C - - - - - -

D 2350630 -1921 35676 - - -

E - - - - - -

F 1233149 359571 0 - - -

G - - - - - -

H1 - - - 2202256 6938 273150

H2 - - - - - -

I - - - - - -

J - - - - - -

K 6467970 -1081147 175257 7736552 345077 550667

L - - - - - -

M1 324131 2795 6353 74917 81375 3342

M2 3360169 2570 224437 95611 -112 22

M3 210041 -69446 71 1071463 7600 34014

M4 1567409 -72383 52190 193 0 0

N1 4863030 -212157 128339 - - -

N2 3004406 807994 158462 103284 36711 2941

N3 13690697 1128242 571255 753832 12721 45599

N4 3511614 569105 153203 106437 3038 6907

O1 0 0 0 9744 27 70

O2 5778672 -8524 219178 4050 -243 163

O3 193022 3154 1690 4506 432 174

O4 2273892 -42920 294672 7736 185 957

O5 0 0 0 2360591 6315241 676429

N. R. 11262918 0 901884 - - -

All 4714480 400305 207476 7979 338 438See Table A-1 for descriptions of major activities(N.R: Not reported)

SARVEKSHANA50

Table A-12: Financial liability and annual interest payable per NPISH by type of frame and major activity

Liability (Rs.) Annual interest (Rs.)

Major List Area Combined List Area Combinedactivity Frame Frame Frame Frame Frame Frame

(1) (2) (3) (4) (5) (6) (7)

A 186746 - 186746 0 0 0

B - - - - - -

C - - - - - -

D 6662854 - 6662854 0 - 0

E - - - - - -

F 6843284 - 6843284 0 - 0

G - - - - - -

H1 - 3055814 3055814 - 4243 4243

H2 - - - - - -

I - - - - - -

J - - - - - -

K 659114 4240714 2072019 104 0 63

L - - - - - -

M1 531583 9183 257958 14902 0 7096

M2 7823549 562602 3047697 2278 0 780

M3 309448 8014244 2154019 0 0 0

M4 325595 0 255488 731 0 574

N1 40265138 - 40265138 0 - 0

N2 2453957 1003991 1694288 0 0 0

N3 23295038 466099 17968681 8711 0 6678

N4 6012317 98004 731525 2965 6 323

O1 5000 10091 10074 900 5 8

O2 3998336 1611 5483 33344 5 37

O3 425036 64961 65174 1900 0 1

O4 1893187 410 811199 0 0 0

O5 0 100390184 67061335 0 0 0

Not reported 7745092 - 7745092 0 - 0

All 7623553 24797 77920 7305 4 55

See Table A-1 for descriptions of major activities

SARVEKSHANA 51

Notes and References

[The author is deputy director general (Email:mannagcm@yahoo.com) in the Survey Design and ResearchDivision of National Sample Survey Organisation.]

i NPIs are legal or social entities created for the purpose ofproducing goods and services whose status does not permitthem to be a source of income, profit or other financialgain for the units that establish, control or financethem. The articles of association by which they areestablished are drawn up in such a way that theinstitutional units which control or manage them are notentitled to a share in any profits or other income whichthe NPIs receive.

ii See “Private Non-Profit Institutions Serving Households–A Profile” by Sri K. G. K. Subba Rao: Reserve Bank ofIndia Occasional Papers, Vol. 10. No. 2, June 1989.

iii An enterprise is an undertaking engaged in productionand/or distribution of goods or services mainly for thepurpose of sale.

iv An ‘own account’ enterprise is one which does not employany hired labour usually.

v An establishment is a unit which employs at least onehired worker on a fairly regular basis.

vi In this survey, an NPO was defined as an institution/organisation which met five criteria, viz., organised,private, non-profit-distributing, self-governing andvoluntary, simultaneously. The term ‘organised’ meantany institution which had its own constitution/charter offunctioning, irrespective of whether it was formallyregistered under any of the statutory provisions or not.

vii National report on PRIA’s study on the non-profit sectorin India is a priced publication. For further details, seewww.pria.org/publication; Non Profit Sector – OccasionalPaper Series: “Invisible Yet Widespread: The Non-ProfitSector in India”.

viii See “Report on Cross-validation Study of Estimates ofPrivate Consumption Expenditure Available fromHousehold Survey and National Accounts” by ExpertGroup on Non-sampling Errors; 88th Issue of Sarvekshana.

ix A dharamsala typically is a place where pilgrims can stayat a low cost. Some dharamsalas also provide subsidisedmeals to their boarders.

x In India, the major Acts of registration of the NPIs are:Societies’ Registration Act, 1860 (including the statevariants); Religious Endowment Act, 1863; Indian TrustAct, 1882; The Charitable and Religious Trust Act, 1920;Mussalman Wakf Act, 1923; Wakf Act, 1954; Public TrustsAct, Section 25 of Companies Act, 1956; Public Wakfs(Extension of Limitation Act) Act, 1959; ForeignContribution (Regulation) Act, 1976.

xi Henceforth the term institution would refer to NPI/NPISH.

xii The sub-fsu’s were formed by more or less equalisingpopulation, making sure that they were clearly identifiablein terms of physical landmarks.

xiii SNA ’93 has used the term “communal construction”. Inthis survey, the term has been replaced by “communityconstruction”.

xiv Listed Acts included Societies’ Registration Act 1860(including the State variants); Indian Trust Act 1882;Public Trusts Act; Section 25 of Companies’ Act 1956;Religious Endowments’ Act 1863; The Charitable andReligioud Trust Act 1920; Wakf Act 1954; MussalmanWakf Act 1923; Public Wakfs (Extension of LimitationAct) Act 1959; and Foreign Contribution (Regulation)Act 1976.

xv Reference: Paragraph 6.91, SNA ’93, page 134. It maybe noted that the NVA computed here does not includeconsumption of fixed capital, as this has not been collectedin the survey. To this extent, the estimates of NVA ofNPISH are on the lower side.

SARVEKSHANA52

SARVEKSHANA 53

PART - II

SUMMARY AND MAJORFINDINGS OF SURVEYS

SARVEKSHANA54

An Integrated Summary of NSS 58th Round (July 2002 - December 2002)On "Disabled Persons in India"

R. N. Pandey and A.L. Chatterjee*

1. Introduction

1.1 Because of the physical and mental disorders atthe time of birth and due to events such as accidents,illness, that may happen later on, certain segments of thesociety face physical and mental disability in their day-to-day activities. The Government of India hasimplemented a number of programmes for the welfare ofthe disabled persons in the country. It also formulatesnational policies on the different aspects relating to thesepeople. For formulation, monitoring and impactassessment of various programmes, government and othernational as well international agencies require timely andreliable statistics on different aspects of disability.

1.2 Surveys conducted by NSSO to measuredisability

1.2.1 The NSSO undertook a comprehensive surveyof disabled persons in its 36th round during the secondhalf of 1981, the International Year of the DisabledPersons. After a gap of ten years, a second survey on thedisabled persons was carried out in the 47th round duringJuly-December 1991 at the request of Ministry of SocialWelfare, Govt. of India. In these surveys, the objectivewas to provide the database regarding the incidence andprevalence of disability in the country. The basicframework of these surveys viz., the concepts, definitionsand operational procedures were kept the same.

1.2.2 Again after a gap of eleven years, the third surveyon the disabled persons was carried out in the 58th roundduring July-December 2002 at the request of Ministry of

Social Justice and Empowerment (MSJE), Govt. of India.In this round, the coverage was extended to include mentaldisability also, keeping all other concepts, definitions andprocedures for physical disability the same as those ofthe 47th round. The decision to include mental disabilityin the survey was taken on the basis of a pre-test of thequestions on mental disability, both for the listing anddetailed schedules.

1.3 Details of the Methodology of 58th Round

1.3.1 Survey period: The fieldwork for the 58th roundsurvey was carried out during the second half of 2002starting from July and continued up to December - thuscovering a period of six months.

1.3.2 Geographical coverage: The survey coveredwhole of Indian Union except (i) Leh and Kargil districtsof Jammu & Kashmir, (ii) interior villages of Nagalandlocated beyond 5 kms. from the bus routes and (iii) villagesin Andaman and Nicobar Islands which were inaccessiblethroughout the year.

1.3.3 Work programme: The survey period wasdivided into two sub-rounds of three months durationeach. Equal number of sample first stage units wasallocated to each of these sub-rounds with a view toensuring uniform spread of the interviews over the entiresurvey period.

1.3.4 Sample Design: A stratified multi-stage sampledesign was adopted for the 58th round. The first stageunits were in most cases 1991 census villages in rural

* Survey Design and Research Division, National Sample Survey Organisation, Kolkata

SARVEKSHANA 55

areas and urban blocks - demarcated by the Urban FrameSurvey - in urban areas. The ultimate stage units werehouseholds.

1.3.4.1 Stratification: Stratification adopted in thissample design is described next both for rural and urbansectors.

Rural sector: Two special strata were formed as givenbelow at the State/ UT level on the basis of PopulationCensus 1991 viz.

Stratum 1: FSUs with population between 0 to 50, and

Stratum 2: FSUs with population more than 15,000

1.3.4.2 The special stratum 1 was formed if at least 50such FSUs were found in a State/UT. Similarly, specialStratum 2 was formed if at least 4 such FSUs were foundin a State/UT. Otherwise, such FSUs were merged withthe general strata.

1.3.4.3 From the remaining FSUs (not covered understratum 1 &2) general strata (hereafter, stratum will referto general stratum unless otherwise mentioned) wasformed and numbered 3, 4, 5. etc. (even if no specialstrata have been formed). Each district of a State/UTwas normally treated as a separate stratum. However, ifthe provisional population of the district was greater thanor equal to 2.5 million as per Census 2001, the districtwas divided into two or more strata with more or lessequal population as per population census 1991 bygrouping contiguous tehsils. However, in Gujarat, somedistricts were not wholly included in an NSS region. Insuch cases, the part of the district falling in an NSS regionconstituted a separate stratum.

1.3.4.4 Urban sector: In the urban sector, stratum wasformed within each NSS region on the basis of size classof towns as per Census 1991 town population except forsome specified towns. The stratum number and theircomposition (within each region) are given below.

1.3.4.5 Composition of Urban Strata & the numbering

stratum no. Composition

(1) (2)

1 all towns with population (P) < 0.1million

2 all towns with 0.1 < P < 0.5 million3 all towns with 0.5 < P < 1 million4, 5,6, … each town with P > 1 million

The stratum numbers were retained as above even if, insome regions, some of the stratum were not formed.

1.3.5 Sub-stratification: There was no sub-stratification in the rural sector. However, to cover morenumber of households living in slums, in urban sectoreach stratum was divided into 2 sub-strata as follows:

sub-stratum 1: all UFS blocks having area type ‘slumarea’

sub-stratum 2: remaining UFS blocks

If there was only one UFS block with area type ‘slumarea’ within a stratum, sub-stratum 1 was not formed; itwas merged with sub-stratum 2.

1.3.6 Sample size: The number of sample villages andurban blocks surveyed in Central sample was 4637 and3354, respectively. A total of 45571 and 24731 householdswere surveyed in rural and urban areas, respectively. Thenumbers of disabled sample persons enumerated in ruraland urban India were 49,300 and 26,679, respectively.The total sample FSUs was allocated to the States andUTs in proportion to provisional population as per Census2001 subject to the availability of investigators ensuringmore or less uniform workload. The number of samplevillages/blocks allotted and surveyed in each State/UT isgiven in Annexure I.

1.3.7 Allocation of State/ UT level sample to Ruraland Urban sectors: State/UT level sample was allocated

SARVEKSHANA56

between two sectors in proportion to provisionalpopulation as per Census 2001 with double weightageto urban sector.

1.3.8 Allocation of Rural /Urban sector level samplesize to strata / sub-strata: Both rural and urban sectorsamples allotted to a State/UT were allocated to differentstrata in proportion to population of the stratum. All thestratum-level allocations were adjusted to multiple of 2.Stratum-level sample size in the urban sector was furtherallocated to 2 sub-strata in proportion to the number ofUFS blocks in them with double weightage to sub-stratum1 subject to a minimum sample size of 2 or 4 to sub-stratum 1 according as stratum-level allocation is 4 orgreater than 4. Sub-stratum level allocations in the urbansector were made even.

1.3.9 Selection of FSUs: FSUs were selected in theform of two independent sub-samples in both the sectors.For special stratum 2 and all the general strata of ruralsector, FSUs were selected by probability proportionalto size with replacement (PPSWR) where size was the1991 census population. For urban sector and specialstratum 1 of rural sector, FSUs were selected by simplerandom sampling without replacement (SRSWOR).

1.4 Selection of hamlet-groups/sub-blocks /households

1.4.1 Formation of hamlet-group/sub-block: Largevillages/ blocks having approximate present population1200 or more were divided into a suitable number ofhamlet-groups/sub-blocks as given below:

approximate no. of hamlet-groups/sub-present population blocks formedless than 1200 1 (no hamlet-group/sub-

block formation)1200 to 1799 31800 to 2399 42400 to 2999 53000 to 3599 6....and so on

For rural areas of Himachal Pradesh, Sikkim andPoonch, Rajouri, Udhampur and Doda districts ofJammu and Kashmir and Idukki district of Kerala wherehabitation pattern causes difficulty in listing due totopography of the area, hg formation criterion wasrelaxed for which number of hamlet groups formed asper population criterion is given below:

approximate no. of hamlet-groups/present population sub-blocks formed

less than 600 1 (no hamlet-group/sub- block formation)

600 to 899 3900 to 1199 41200 to 1499 5....and so on

1.4.2 Hamlet-groups / sub-blocks were formed by moreor less equalising population. For large urban blocks,the sub-block (sb) having slum dwellers, if any, wasselected with probability 1 and was termed as segment 1.However, if there were more than one sb having slumdwellers, the sb having maximum number of slumdwellers was selected as segment 1. After selection of sbfor segment 1, one more sb was selected by simple randomsampling (SRS) from the remaining sb’s of the block andwas termed as segment 2. For large blocks (having noslum areas) two sub-blocks were selected by simplerandom sampling without replacement (SRSWOR) andwere combined to form segment 2. For urban blockswithout sub-block formation, segment number was 1 or2 depending on whether the block was having a slum ornot. For large villages two hamlet-groups were selectedby SRSWOR and were combined to form segment 2.For villages without hamlet-group formation, segmentnumber was also 2. The segments were consideredseparately for listing and selection of the ultimate-stageunits.

SARVEKSHANA 57

1.5 The sample households were selected bySRSWOR from each SSS.

1.5.1 Formation of Second Stage Strata (SSS) andselection of households: In each selected village/block/segment, three second stage strata (SSS) were formed onthe basis of disability type. The number of householdsselected is given below:

Without segment with segment formationformation (for each segment)

SSS 1: households having at least one person with 4 2mental disability

SSS 2: households having at least one person with 4 2speech/hearing/ visual disability out ofremaining households

SSS 3: households having at least one person with 4 2locomotor disability out of remaining households

The sample households were selected by SRSWOR fromeach SSS.

For a household having a person with more than onedisability (i.e. multiple disability), SSS was assigned bypriority criterion e.g. a household having a person withmental disability as well as locomotor disability wasclassified under SSS 1 and a household having one personwith speech disability and another person with locomotordisability was classified under SSS 2

1.6 Estimation Procedure

1.6.1 Notations:

s = subscript for s-th stratumt = subscript for t-th sub-stratum of an urban

stratum ( t =1, 2)m = subscript for sub-sample (m =1, 2)i = subscript for i-th FSU [village (panchayat

ward) in Kerala/ block]u = subscript for a segment (u = 1, 2)j = subscript for j-th second stage stratum of

an FSU

k = subscript for k-th sample household undera particular second stage stratum within an

FSU D = total number of hg’s / sb’s formed in thesample village (panchayat ward) / block

D* = 1 if D = 1= D / 2 for rural FSUs with D > 1= (D – 1) for urban FSUs with D > 1 and

with segment 1

= D / 2 for urban FSUs with D > 1 and withoutsegment 1

N = total number of FSUs in an urban stratum /sub-stratum or rural stratum 1

Z = total size of a general stratum or specialstratum 2 of rural sector (= sum of sizes forall the FSUs of a stratum )

z = size of sample village used for selection.

n = number of sample village / block surveyedincluding zero cases but excluding casualtyfor a particular sub-sample and stratum /sub-stratum.

H = total number of households listed in asecond-stage stratum of a segment of asample FSU

h = number of households surveyed in a second-stage stratum of a segment of a sample FSU

x, y = observed value of characteristics x, y underestimation

X

, Y = estimate of population total X, Y for thecharacteristics x, y

SARVEKSHANA58

Under the above symbols,

ysmiujk

= observed value of the characteristic y for the k-thhousehold in the j-th second stage stratum of the u-thsegment (u = 1, 2) of the i-th FSU belonging to the m-thsub-sample for the s-th rural stratum;

ystmiujk

= observed value of the characteristic y for the k-th household in the j-th second stage stratum of the u-thsegment (u = 1, 2) of the i-th FSU belonging to the m-thsub-sample for the the t-th sub-stratum of s-th urbanstratum

However, for ease of understanding, a few symbols havebeen suppressed in following paragraphs where they areobvious.

1.6.2 Formulae for estimation of aggregates for aparticular sub-sample and stratum / sub-stratum inRural / Urban sector:

Rural:

(a) Estimation formula for stratum 1:

(i) For households selected in j-th second stage stratum:

(ii) For all selected households:

(b) Estimation formulae for general strata:

(i) For households selected in j-th second stage stratum:

, (j = 1, 2 or 3)

∑

==

3

1

ˆˆj

jYY

∑ ∑= = ⎥

⎥⎦

⎤

⎢⎢⎣

⎡×=

j

i

h

kjki

ji

ji

jj

ny

h

Hi

Dn

NY

ji

1 12

2

22*ˆ

∑ ∑= = ⎥

⎥⎦

⎤

⎢⎢⎣

⎡×=

j

i

h

kjki

ji

ji

ijj

ny

h

Hi

Dzn

ZY

ji

1 12

2

22*1ˆ , (j = 1, 2 or 3)

(ii) For all selected households:

Urban:

(a) Estimation formula for a sub-stratum of urbanstratum

(i) For households selected in j-th second stage stratum:

(ii) For all selected households:

(b) For the sth stratum:

1.6.3 Overall estimate for aggregates:

Overall estimate for aggregates for a stratum ( sY ) / sub-stratum ( stY ) based on two sub-samples is obtained as:

∑

==

3

1

ˆˆj

jYY

∑ ∑∑= == ⎥

⎥⎦

⎤

⎢⎢⎣

⎡×+=

j

i

h

kjki

ji

jih

kjki

ji

ji

jj

ny

h

Hi

Dyh

H

n

NY

jiji

1 12

2

2

11

1

121

*ˆ , (j = 1, 2 or 3)

∑

==

3

1

ˆˆj

jYY

∑

==

2

1

ˆˆt

sts YY

(i) for rural stratum,

∑=

=2

1

ˆ2

1ˆm

sms YY

∑

==

2

1

ˆ2

1ˆm

stmst YY(ii) for urban sub-stratum and

(iii) for urban stratum

∑=

=2

1

ˆˆt

sts YY

SARVEKSHANA 59

1.6.4 Overall estimate of aggregates at State/UT/all-India level:

The overall estimate Y at the State/ UT/ all-India levelis obtained by summing the stratum estimates sY over allstrata belonging to the State/ UT/ all-India.

1.6.5 Estimates of ratios:

Let Y and X be the overall estimate of the aggregatesY and X for two characteristics y and x respectively atthe State/ UT/ all-India level.

Then the combined ratio estimate )ˆ(R of the ratio

)(X

YR = will be obtained as

X

YR

ˆ

ˆˆ =

1.7 Difficulties in collecting information ondisability

1.7.1 Since the non-medical investigators collected thedata, it was imperative to define disability in a very carefuland guarded way to minimize the bias of the investigatorsand respondents. To minimise these difficulties and toinvolve feasible and practical concepts and definitions ofdisability, the experts from the relevant medical disciplineswere consulted prior to the 58th round. The decision toinclude mental disability in the survey was taken on thebasis of a pre-test of the questions on mental disability,both for the listing and detailed schedules.

1.8 Layout of the summary

1.8.1 The results presented in this summary relate toboth physical and mental disabilities, namely, (i) mentaldisability, (ii) visual disability, (iii) hearing disability, (iv)speech disability and (v) locomotor disability. The detailedconcept and definitions of selected terms used in the surveyare given in Annexure II. This summary gives theincidence and prevalence, marital status, educational level,

living arrangements, activity status, etc. of disabledpersons. The details of different types of disabilityincluding the cause of disability (as reported by theinformant) are also given. The data given in the maintext of the paper relate to all India only. However, selecteddata for the states and union territories are given inAnnexure I, III and IV.

2. Summary of Findings

2.1 The results presented in this summary relate tothe data of only the Central sample. At the all- India level,45571 and 24731 households having at least one disabledperson, selected from 4637 villages and 3354 urbanblocks respectively, were surveyed. The numbers ofdisabled sample persons enumerated in rural and urbanIndia were 49,300 and 26,679, respectively

2.2 About 10.63 per cent of the disabled personssuffered from more than one type of following disabilities,(i) mental disability in the form of (a) mental retardationor (b) mental illness, (ii) visual disability in the form of(a) blindness or (b) low vision, (iii) hearing disability,(iv) speech disability, and (v) locomotor disability. In thecase of locomotor disability, multiple type of locomotordisability was also considered as multiple disability.

2.3 The aggregated estimates of the disability in ruraland urban India are given in Statement 1, separately foreach sex and type of disability. These estimates areobtained by using survey proportions on the projectedpopulation. It is observed that among the different typesof disabilities, the number of persons having locomotordisability was the highest in both rural and urban Indiafollowed by the number of persons with hearing disabilityand visual disability. The number of disabled persons inthe country was estimated to be 18.49 million during Julyto December 2002. They formed about 1.8 per cent ofthe total estimated population1. About 10.63 per cent ofthe disabled persons suffered from more than one type ofdisabilities.1 The estimates have been obtained for 1st October 2002, by applyingdecennial (exponential) growth rate of population for 1991 – 2001 onCensus 2001 Population.

SARVEKSHANA60

Statement 1: Estimated* number (in ‘00) of disabled persons by type of disability and sex separately forrural and urban India

(in 00)

type of disability rural urban

male female persons male female persons

(1) (2) (3) (4) (5) (6) (7)

any disability** 83102 57748 140850 25811 18249 44060mental disability:

mental retardation 4434 2561 6995 1824 1128 2951mental illness 5022 3377 8399 1623 988 2611

Physical disability:visual disability:

blindness 7494 8536 16030 1793 2311 4104low vision 2982 3563 6545 711 877 1588

hearing disability 12516 11171 23687 3617 3313 6930speech disability 9495 6532 16027 3416 2102 5518locomotor disability 49987 29839 79826 16352 10162 26514

estd. (00) total persons 3923611 3711319 7634930 1545555 1391996 2937551* estimates are obtained by using survey proportions on the projected population.

** at least one of mental, visual, hearing, speech and locomotor disability.

2.4 The percentage distribution of disabled persons by type of disability (using the estimates) is depicted in chart 1.

Chart 1: Percentage distribution of disabled persons by type of disability

Rural India Urban India

SARVEKSHANA 61

Prevalence of disability: A person with restrictions orlack of abilities to perform an activity in the manner orwithin the range considered normal for a human beingwas considered disabled. The estimates of prevalence ofdisability (number of disabled persons per 1,00,000 per-sons) are given in Statement 2. The survey reveals thatfor every 1,00,000 people in India, there were 1755 whowere either mentally or physically disabled. Among therural residents, the prevalence of disability was 1.85 percent and that among the urban was 1.50 per cent. Be-tween the two sexes, the prevalence of disability wasmarginally higher among males than among females. Therates for males were 2.12 and 1.67 per cent while thatfor females were 1.56 and 1.31 per cent in rural and ur-ban India, respectively.

Statement 2: Number of disabled persons per 1,00,000 persons for each sex and sector -all-India

disabled persons per 1,00,000 persons

type of rural urban rural+urban

disability male female persons male female persons male female persons

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

mental retardation 113 69 92 118 81 100 115 72 94

mental illness 128 91 110 105 71 89 122 86 105

blindness 191 230 210 116 166 140 171 214 192

Low vision 76 95 86 46 62 54 68 87 77

hearing disability 319 301 310 234 238 236 296 285 291

speech disability 242 176 210 221 151 187 237 169 204

locomotor disability 1274 804 1046 1058 730 901 1217 785 1008

any disability 2118 1556 1846 1670 1311 1499 2000 1493 1755

2.5.1 The similar details at State/UT’s level arepresented in Annexure III. It may be seen that among themajor states number of disabled persons per 1,00,000population was highest in Himachal Pradesh (2571)followed by Orissa (2459) and Punjab ( 1987). Thisratio was lowest in Rajasthan (1468) succeeded by

Karnataka (1558) and Bihar (1652). As observed at allIndia level, this ratio was higher for males as comparedto females in all the States/Uts. The difference in thisratio for males and females was highest in HimachalPradesh followed by Jammu and Kashmir and UttarPradesh.

2.5.2 The incidence of disability in population i.e. thenumber of persons whose onset of disability (by birth orotherwise) had been during the specified period of 365days preceding the date of survey per 100, 000 person isshown in Statement 3 for all – India. About 69 personswere born or otherwise became disabled for 100000persons in rural India during the reference year. Theincidence rates were almost the same in both the rural

and urban India. As in the case of prevalence rate, theincidence rate is also observed to be higher among malesthan that among females. The rates among males were77 and 75 respectively in rural and urban India as against61 and 58 respectively among females

SARVEKSHANA62

Statement 3: Number of disabled persons who became disabled during the last 365 days per 1,0,000 personsfor each type of disability

number who became disabled during the last 365 days per 1,00,000 personstype of disability

male female persons

(1) (2) (3) (4)

rural

mental retardation 1 0 1

mental illness 4 2 3

blindness 7 11 9

low vision 3 5 4

hearing disability 9 7 8

speech disability 3 2 3

locomotor disability 58 40 49

any disability 77 61 69

urban

mental retardation 1 1 1

mental illness 4 3 4

blindness 4 7 6

low vision 3 3 3

hearing disability 8 6 7

speech disability 4 2 3

locomotor disability 60 43 52

any disability 75 58 67

rural + urban

mental retardation 1 1 1

mental illness 4 2 3

blindness 7 10 8

low vision 3 5 4

hearing disability 8 6 7

speech disability 3 2 3

locomotor disability 58 41 50

any disaility 76 60 69

2.5.3 About 8.4 percent and 6.1 percent of the totalestimated households in rural and urban India respectivelyreported to have at least one disabled person. Statement4 reveals the average size of these households is estimatedto be 5.7 in rural and 5.5 in urban sector, which is

significantly higher than the average household size ingeneral. Among these households, about 92 per cent hadone disabled person, about 7 per cent had 2 disabledpersons and nearly 1 per cent had 3 or more disabledpersons, both in rural and urban sectors.

SARVEKSHANA 63

Statement 4: Per 1000 distribution of households by number of disabled persons in the household reportingdisability

sectorHouseholds withdisabled persons rural urban rural+urban

(1) (2) (3) (4)

1 924 923 923

2 70 72 71

3 or more 6 5 6

all 1000 1000 1000

average hh size 5.7 5.5 5.7

2.6 Disability associated with birth: Some peopleare born with disability and the incidence varies over thetypes of disability. Prevalence of disability by birth isgiven in Statement 5 by type of disability separately foreach sex and sector at all-India level. It is seen that about84 per cent of the mentally retarded and 82 per cent ofthe persons having speech disability were born with

disability. For persons with other type of disability theincidence by birth is not as significant as in the case ofthe mentally retarded or persons with speech disability.Most of them become disabled during the course of life.Incidence for some of the disabilities is largely associatedwith the old age.

Statement 5: Number of disabled persons with onset of disability since birth per 1000 disabled persons bytype of disability for each sex and sector

onset of disability since birth

type of rural urban rural+urbandisability male female persons male female persons male female persons

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

mental retardation 838 871 850 824 803 816 834 851 840

mental illness 238 236 237 194 209 200 228 230 229

blindness 187 120 151 160 184 174 182 133 155

low vision 108 59 81 174 63 112 120 60 87

hearing disability 395 343 371 388 350 370 393 345 370

speech disability 828 841 833 742 781 757 807 827 815

locomotor disability 277 302 287 234 245 238 268 288 275

any disability 335 315 327 303 298 301 328 311 321

SARVEKSHANA64

2.7 Degree of physical disability: For determiningthe extent of physical disability of a disabled person, self-care, such as, ability to go to latrine, taking food, gettingdressed, etc. were taken into account. Irrespective ofwhether or not a disabled person had ‘single’ or ‘mul-tiple’ disability, they were classified into one of the fourcategories. There was a category of the disabled for whomthe aid/appliance was neither available nor tried and this

Statement 6: Per 1000 distribution of physically disabled persons by extent of physical disability by sex andsector

disabled extent of physical disabilitypersons

cannot take can take self- can take self-care aid/ appli- totalself-care care only with without aid/ appli- ance not

even with aid/ appliance ance tried/ notaid/ appli- available

ance

(1) (2) (3) (4) (5) (6)

rural male 116 179 610 93 1000

rural female 152 154 585 107 1000

rural persons 131 169 600 99 1000

urban male 126 186 625 60 1000

urban female 160 181 598 58 1000

urban persons 140 184 614 59 1000

male 118 181 613 86 1000

female 154 160 588 96 1000

persons 133 172 603 90 1000

category alone was about 9 per cent of all the disabled.The distribution of the disabled by these categories, givenin Statement 6 for each sex separately for rural and ur-ban sectors of all-India reveals that among the disabled,about 13 per cent in both rural and urban India wereobserved to be severely disabled as they could not func-tion even with aid/appliance.

2.8 Literacy among the disabled: Literates, for thepurpose of this survey, were those who could read and

write a simple message with understanding. Those whowere unable to do

SARVEKSHANA 65

Statement 7: Per 1000 distribution of disabled persons of age 5 years and above by level of general educationand sector

type of disability rural urban rural+urban

(1) (2) (3) (4) (5) (7) (8) (9) (10) (11) (12) (13) (14)

mental

retardation 887 90 20 3 809 150 36 5 866 106 24 3

mental illness 620 208 97 71 488 237 121 150 591 215 102 89

with blindness 826 113 37 23 546 257 76 119 773 141 45 41

with low vision 774 157 39 27 576 235 73 114 738 172 45 43

hearing 695 211 60 32 463 306 110 121 646 231 70 50

speech 715 210 49 25 527 314 84 74 670 235 57 38

locomotor 486 290 128 96 318 301 162 216 447 292 136 124

any disability 590 244 97 69 400 288 137 175 547 254 106 92

not l

itera

te

upto

pri

mar

y

mid

dle

seco

ndar

y &

abo

ve

not l

itera

te

upto

pri

mar

y

mid

dle

seco

ndar

y &

abo

ve

not l

itera

te

upto

pri

mar

y

mid

dle

seco

ndar

y &

abo

ve

literate literate literate

so were considered as illiterates. About 55 per cent ofthe disabled in India were illiterate and as expected, itwas highest among the mentally retarded (87 per cent)followed by the visually disabled (74 to 77 per cent). Theproportion of illiterate was about 59 per cent in the ruraland 40 per cent in the urban among the disabled. On theother hand, about 9 per cent were of the category“secondary and above”. Only about 7 per cent of thedisabled in rural India reported educational level“secondary and above” as against 18 percent in urbanIndia. The details are presented in Statement 7.

2.8.1 Literacy status of disabled persons of age 5 yearsand above, as a whole, at state/ut level has been presentedin Annexure IV. Among major states, illiteracy rate amongdisabled was highest in Jharkhand ( 65.7 per cent) closelyfollowed by Bihar (65.5 per cent) and Orissa ( 64.2 per

cent). The proportion of disabled with secondary andabove level of education was highest in Himachal Pradesh( 14.8 per cent) followed by Gujarat ( 13.6 per cent) andPunjab ( 13.4 per cent).

2.9 Marital status of the disabled: Statement 8 givesthe distribution of disabled persons by marital status foreach sex and sector at the all-India level. The male-femaledifferences in the proportions are quite significant. About30 to 31 per cent of disabled females in India werewidowed, divorced or separated as against 7 to 8 percent of disabled males (widowed, divorced or separated).Sharp changes are observed in the distributions over thetypes of disability. Most of the mentally retarded seem tolead an unmarried life. Similar is the situation, althougha little better, for persons having hearing disability.

SARVEKSHANA66

Statement 8: Per 1000 distribution of disabled persons by marital status by type of disability for each sex andsector

type of male femaledisability

never curre wido divor total never curre wido divor totalmarried ntly -wed ced/ marri ntly -wed ced/

marri separ ed marri separed ated ed ated

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

rural

mentally retarded 920 63 3 13 1000 899 47 23 31 1000

mentally ill 506 398 35 61 1000 338 393 171 97 1000

blindness 264 538 187 11 1000 132 275 580 13 1000

low vision 146 662 173 18 1000 92 273 626 5 1000

speech disabled 348 529 113 10 1000 292 318 365 24 1000

hearing disabled 728 240 23 8 1000 697 197 74 32 1000

locomotor disabled 483 456 53 8 1000 437 334 206 23 1000

all disabled 471 448 69 12 1000 376 316 281 26 1000

urban

mentally retarded 963 27 4 6 1000 941 29 10 20 1000

mentally ill 640 283 32 46 1000 522 220 190 68 1000

blindness 269 589 136 6 1000 297 198 495 10 1000

low vision 236 612 146 6 1000 88 305 599 8 1000

speech disabled 391 488 110 11 1000 298 297 386 18 1000

hearing disabled 767 207 16 11 1000 721 158 98 22 1000

locomotor disabled 453 493 48 6 1000 418 319 248 16 1000

all disabled 484 450 57 9 1000 415 284 283 18 1000

rural + urban

mentally retarded 931 53 3 11 1000 911 41 19 28 1000

mentally ill 536 371 35 57 1000 377 356 175 91 1000

with blindness 265 547 178 10 1000 165 259 563 12 1000

with low vision 162 653 169 16 1000 91 278 621 6 1000

speech disabled 737 232 21 9 1000 293 314 370 23 1000

hearing disabled 357 521 113 10 1000 703 188 79 30 1000

locomotor disabled 476 464 52 8 1000 433 330 216 21 1000

all disabled 474 449 66 11 1000 385 309 282 24 1000

SARVEKSHANA 67

2.10 Status of Vocational Training among Disabled:Along with the general educational level of the disabled,information relating to whether or not any vocationalcourse had been completed by them was also collected.The vocational courses have been broadly divided intotwo categories – engineering and non-engineering courses.The data have been tabulated for disabled of age 10 years

Statement 9: Number of disabled persons by attendance of vocational course per 1000 disabled persons ofage 10 years and above for each sector

course attended

sector not attendedany vocational

course engineering non-engineering

(1) (2) (3) (4)

rural 984 3 12

urban 963 9 26

rural+urban 979 4 15

2.11 Current Enrolment Status of Disabled:Statement 10 reveals that, contrary to the perception ofurban bias in the levels of literacy, the current enrolmentratio per 1000 disabled persons of age 5-18 years in theordinary school was higher in the rural sector than in theurban. The corresponding figures are 475 and 444respectively for the two sectors. However, the situation

and above and are presented in Statement 9. The datashow that ninety eight percent of disabled persons in ruraland urban India did not complete any vocational courseand of those who had completed, 80 percent of them werein non-engineering stream. In urban India, acomparatively higher number of disabled persons (35percent) have attended vocational courses.

is reversed in the case of special schools. About 11 percent of disabled persons of age 5 - 18 years were enrolledin the special schools in the urban as compared to evenless than 1 per cent in the rural. The enrolment ratio wasrelatively higher among the blind and children with speechdisability. However, the gender bias in the enrolment ratiois not prominent.

SARVEKSHANA68

Statement 10: Number of persons per 1000 disabled persons of age 5 - 18 years by enrolment status and typeof disability for each sex and sector

type of disability number per 1000 of disabled children

currently enrolled in ordinary currently enrolled in special schoolschool

male female persons male female persons

(1) (2) (3) (4) (5) (6) (7)

rural

mental retardation 155 95 134 45 9 32

mental illness 163 74 128 24 12 19

blindness 239 154 203 19 17 18

low vision 472 437 456 11 0 6

hearing 540 454 503 0 11 5

speech 412 341 383 12 7 10

locomotor 601 501 562 4 1 2

any disability 511 420 475 8 4 6

urban

mental retardation 128 100 117 141 137 139

mental ill- ness 145 128 138 102 81 94

blindness 254 110 143 74 716 569

low vision 628 629 629 0 42 19

hearing 490 469 480 47 46 47

speech 338 270 311 240 266 250

locomotor 564 577 569 21 18 19

any disability 461 421 444 79 143 106

2.12 Usual activity of the disabled: The usual activitystatus of an individual is the activity situation obtainingfor the person in respect of his/her participation ineconomic or non-economic activities during the referenceperiod of 365 days preceding the date of survey. Adoptinga relatively long time criterion, two major activity statusesare identified as:

Labour force: (i) Working or being engaged in economicactivities (work) (employed) and (ii) not engaged ineconomic activities (work) but available for work(unemployed).

Out of labour force - not engaged in work and also notavailable for work.

SARVEKSHANA 69

Statement 11: Per 1000 distribution of disabled persons by broad usual activity status for each sex and sector

type of disability rural urban rural+urban

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

male

mental retardation 89 0 911 58 1 941 81 1 919mental illness 199 2 799 99 4 897 176 2 821with blindness 139 4 857 193 5 802 149 4 847with low vision 339 5 655 291 7 702 331 6 663hearing 530 4 466 347 17 635 492 6 501speech 391 7 602 249 16 734 356 9 635locomotor 387 11 602 404 22 574 391 14 595all disabled 369 8 622 347 18 635 364 11 625

female

mental retardation 20 0 980 5 1 994 16 0 984mental illness 59 0 941 15 0 985 49 0 951with blindness 43 1 956 33 3 963 41 1 958with low vision 73 0 927 51 0 949 69 0 931hearing 198 0 802 101 3 896 177 1 822speech 143 3 854 64 7 929 125 4 871locomotor 98 4 898 107 5 888 100 4 896all disabled 109 2 889 87 4 909 104 3 893

persons

mental retardation 64 0 936 38 1 961 56 0 943mental illness 142 1 857 67 3 930 126 1 873with blindness 88 2 910 103 4 893 91 2 907with low vision 195 3 803 158 3 838 188 3 809hearing 374 2 624 229 10 761 343 4 653speech 290 5 705 178 13 809 263 7 730locomotor 279 9 712 289 15 696 282 10 708all disabled 263 6 731 238 12 749 257 7 735

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The distribution of disabled persons by their activitystatus, given in the column headings of Statement 11,shows that 26 per cent of the disabled persons wereemployed. The corresponding figures in rural and urbanIndia were 26 and 24 per cent, respectively. Most of

the mentally retarded remained out of labour force.The proportion of employed was lowest at 6 percentamong the mentally retarded while the rate was highestat 34 per cent among the persons having hearingdisability.

SARVEKSHANA70

2.13 Onset of disability with respect to work: Onsetof disability in a person who was usually working maysometimes lead to loss of work or change of work.Information on whether the disabled person was workingbefore the onset of disability was collected. For disabledpersons of age 5 years and above, the proportion (per

Statement 12: Number of persons who were working before the onset of disability per 1000 disabled personsof age 5 years and above for each sex and type of disability

type of number of persons who were working before the onset of disability per 1000 disableddisability persons of age 5 years

rural urban rural+urbanmale female persons male female persons male female persons

mental retardation 52 35 46 29 21 46 28 39

mental illness 579 462 533 472 268 398 556 424 505

blindness 591 546 567 560 326 424 585 501 540

low vision 696 580 634 542 381 455 670 546 603

hearing 574 478 528 547 312 429 569 443 509

speech 112 82 100 77 45 65 104 74 92

locomotor 406 305 368 389 215 322 402 283 357

at least one 415 352 389 374 224 311 406 323 372disability

1000 disabled) that were working before the onset ofdisability is given in Statement 12 for rural and urbanIndia. Here we observe that about 37 per cent of thedisabled (age 5 +) as a whole were working before theonset of disability.

2.14 Living arrangements of disabled persons:Information on living arrangement of the disabled personswas collected to know whether they were living alone orwith spouse only or with spouse and other members ofthe household. The results reveal that about 3 per cent ofthe disabled were living alone and it was 5 to 6 per centamong the visually disabled. Moreover, about 5 per centof the disabled persons lived with their spouses only. But

a large majority, about 92 per cent of the disabled livedwith their spouse and/or other members in the family.The results relating to the distribution of the disabled byliving arrangement can be seen from Statement 13. Therural-urban differences are not prominent. However, amarginal difference is observed among the various typesof disability.

SARVEKSHANA 71

Statement 13: Number of disabled persons by type of living arrangement per 1000 disabled persons in eachtype of disability

type of living arrangement

disability rural urban rural + urban

living living living living living living living living livingalone with with alone with with alone with with

spouse spouse spouse othes spoue spouseonly and/ or only only and / or

others others

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

mental retardation 3 4 992 1 3 995 3 4 993mental illness 31 44 922 19 32 945 29 42 927with blindness 49 80 872 55 57 888 50 75 874with low vision 61 97 840 47 50 902 59 88 851hearing 40 67 891 53 60 887 43 66 890speech 10 26 964 38 15 946 17 23 958locomotor 26 52 921 28 45 925 27 50 922

all disabled 31 55 914 33 44 922 31 52 915

3. Details of Different Types of Disabilities

3.1 Mental disability: The mentally disabled arecatagorised into two groups viz. mentally retarded andmentally ill. In the survey three probing questions wereasked and based on the information so obtained, thepersons were categorised into mentally retarded andmentally ill. The probing questions were:

• is there anyone in the family who hasdifficulty in understanding instruction, whodoes not carry out his/her activities likeothers of his / her age or exhibits behaviourslike talking to self, laughing / crying withoutreason, staring, violence;

• if the response was affirmative to thequestion above, it was asked whether thebehaviour was observed since birth /childhood but before 18 years of age;

• the third question was “was he/she late intalking, sitting, standing or walking?”

If the response to these three questions were all inaffirmative, then the person was categorised as mentallyretarded. On the other hand, if the response to the firstquestion was in affirmative but responses for the othertwo questions were not both in affirmative, then the personwas categorised as mentally ill. It may be noted that thetwo categories “mentally retarded and mentally ill” donot exhaust all possible combinations of answers by therespondent.

3.1.2 Prevalence of mental disability: The prevalencerate, number of mentally retarded / ill persons per1,00,000 persons, has been obtained separately for thementally retarded and mentally ill. Statement 14 providesthe prevalence rate for rural and urban sectors of all-India. It shows that about 94 persons per 1,00,000 werementally retarded and the corresponding rate was 105for the mentally ill. The prevalence rate was higher formales in both rural and urban sectors, and among thementally retarded and ill. For the mentally retarded theprevalence rate was higher among males (113 to 118) ascompared to females (69 to 81). The corresponding figuresfor the mentally ill were 105 to 128 and 71 to 91.

SARVEKSHANA72

Statement 14: Number of persons with mental retardation and mental illness per 100,000 persons for each sexand sector

mentally rural urban rural + urbandisabled male female persons male female persons male female persons

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

mental retardation 113 69 92 118 81 100 115 72 94

mental illness 128 91 110 105 71 89 122 86 105

3.1.3 Age at the onset of mental retardation/illness:The distribution of mentally disabled persons by age atonset is given Statement 15 for rural and urban sector ofIndia. Unlike the other disabilities, mental retardation isa phenomenon whose manifestation is observed since birthor at the very early ages of life. About 87 per cent of thementally disabled reported to have the problem since theirbirth and about 8 per cent had it in the age group 0-4

years. For the mentally retarded females about 90 percent among them had the problem since their birth. Animportant feature observed among the mentally retardedis that the manifestation of disability is completed withinthe teen-ages. The rural and urban features indicated thatthe phenomenon of mental retardation since birth is muchhigher in the rural than in the urban.

Statement 15: Per 1000 distribution of persons 60 years and above with mental retardation or mental illnessby age at onset of disability

category disa- age at onset (years)biliysincebirth

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

mental retardationrural male 883 117 0 0 0 0 0 0 0 0 0 1000rural female 916 0 0 84 0 0 0 0 0 0 0 1000rural persons 896 73 0 31 0 0 0 0 0 0 0 1000

urban male 645 0 0 224 131 0 0 0 0 0 0 1000urban female 803 197 0 0 0 0 0 0 0 0 0 1000urban persons 710 82 0 131 77 0 0 0 0 0 0 1000

all male 847 99 0 34 20 0 0 0 0 0 0 1000all female 896 35 0 69 0 0 0 0 0 0 0 1000all persons 866 75 0 47 12 0 0 0 0 0 0 1000

mental illnessrural male 59 0 10 0 17 34 32 44 130 380 291 1000rural female 49 0 9 8 8 26 34 38 118 441 269 1000rural persons 53 0 9 4 12 30 33 41 123 414 278 1000

urban male 18 0 10 18 23 14 44 49 90 221 513 1000urban female 35 0 0 6 9 48 10 27 235 207 422 1000urban persons 27 0 5 12 16 30 27 38 161 214 468 1000

all male 48 0 10 5 18 29 35 45 119 339 349 1000all female 46 0 7 7 8 31 29 36 143 392 301 1000all persons 47 0 8 6 13 30 32 40 132 368 323 1000

0 –

4

5 –

9

10 –

14

15 –

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20 –

24

25 –

29

30 –

34

35 –

44

45 –

59

60

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SARVEKSHANA 73

On the other hand, the problem of mental illness is moreof an old age problem. The possibility of onset of mentalillness increases as one gradually becomes older. Thetrend and the possibility of onset over the ages is seen tobe very steady for each sex and sector.

3.1.4 Cause of mental retardation: For mentallyretarded persons, the distribution was obtained byprobable cause of mental retardation and is given inStatement 16 for rural and urban India. The principal

Statement 16: Per 1000 distribution of persons with mental retardation and onset at age 0-18 years by cause ofmental retardation for each sex and sector

cause of rural urban rural+urban

mental male female person male female person male female person

retardation

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

1.pregnancy& birth relatd 22 43 29 27 34 30 23 40 29

2. seriousillnessduringchildhood 414 348 393 441 486 460 422 401 415

3. headinjury inchildhood 75 109 85 141 108 128 94 108 99

4. heredity 24 12 20 41 21 33 29 16 24

5. otherreasons 206 191 201 137 199 163 186 194 189

6.not known 240 273 250 208 150 184 231 226 229

total* 1000 1000 1000 1000 1000 1000 1000 1000 1000

* ’total’ includes not recorded cases of ‘cause of mental retardation’

cause of mental retardation was ‘illness during childhood’(42 per cent) followed by the ‘head injury in childhood’(10 per cent). Cases of mental retardation due to‘pregnancy and birth related’ was 3 per cent. About 2per cent of the mentally retarded reported that theincidence was hereditary. Note that for as high as 23 percent of the mentally retarded; the respondent was notaware of the probable cause of retardation. There aremarginal variations in these proportions in respect of sexand residential status.

3.1.5 Cause of mental illness: Statement 17 revealsthat only 9 per cent of the mentally ill reported ‘illnessduring childhood’ as the cause for their illness. About 46

per cent reported reasons other than the listed ones’ asthe cause. The ‘not known’ cases were as high as 36per cent.

SARVEKSHANA74

Statement 17: Per 1000 distribution of persons with mental illness by cause of mental illness for each sex andsector

cause of rural urban rural+urban

mental male female person male female person male female person

retardation

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

1.pregnancy &birth related 3 59 26 3 44 18 3 56 24

2. serious illnessduringchildhood 67 73 70 166 127 151 91 85 88

3. head injury inchildhood 27 21 25 45 57 49 31 29 30

4. heredity 29 32 30 21 32 25 27 32 29

5.other reasons 468 405 443 508 493 503 477 424 456

6.not known 397 399 398 248 241 245 362 365 363

total* 1000 1000 1000 1000 1000 1000 1000 1000 1000

* ’total’ includes not recorded cases of ‘cause of mental retardation’

3.2 Visual Disability

A person was treated as visually disabled if he/she didnot have light perception, both eyes taken together, or ifhe/she had light perception but could not correctly countfingers of a hand (with spectacles if he/she usedspectacles) from a distance of 3 metres in good daylight.Thus, following the above definition, the visually disabledpersons can be categorised into two broad groups:

Blindness: Include persons who do not have lightperception and persons who have light perception butcannot count fingers at a distance of 1 metre even withspectacles and:

normally use spectaclesnormally do not use spectacles

Low vision: persons who have light perception but cannotcount fingers up to a distance of 3 metres even withspectacles and:

normally use spectaclesnormally do not use spectacles

3.2.2 Prevalence of visual disability: The number ofvisually disabled persons per 1,00,000 population for all-India has been presented in Statement 18. Out of every1,00,000 persons, about 269 (240 for male and 301 forfemale) was visually disabled. Among them, 72 per centwere blind and rest 28 per cent had low vision. Theprevalence of visual disability was substantially higheramong the females than among males. The rate amongthe rural residents (296) was also significantly higherthan among the urban residents (194).

SARVEKSHANA 75

Statement 18: Number of persons with visual disability per 100,000 persons by degree of disability for eachsex

degree rural urban rural + urban

of disability male female persons male female persons male female persons

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

1. no light perception 95 109 102 55 81 68 84 102 93has light perception butcannot count fingers uptoa distance of 1 meter:

2. normally uses specs. 40 41 41 32 39 35 38 41 39

3. normally does not use specs. 56 80 67 29 45 37 49 71 59

blindness (sub-total: 1+2+3) 191 230 210 116 166 140 171 214 192

has light perception butcannot count fingers upto a distance of 3 meters:

4. normally uses specs. 26 27 27 23 25 24 25 27 26

5. normally does not use specs. 50 68 59 23 38 30 43 60 51

low vision(sub-total: 4+5) 76 95 86 46 62 54 68 87 77

all 267 326 296 163 228 194 240 301 269

3.2.3 Age at the onset of visual disability: Somepeople are born disabled and some acquire disability incourse of time. For those who acquired disability afterbirth information relating to age at onset of disabilitywas collected. In order to study the pattern of age at theonset of disability, the cohort of persons of age 60 yearsand above who acquired visual disability, have beenconsidered here and their distribution over age at onsetof disability is given in Statement 19 for rural and urbansectors India. The results are given separately for theblind and for persons with low vision. It appears thatvisual disability is an old age problem.

About 68 to 72 per cent acquired visual disability at theage of 60 years and above. The onset of visual disabilityseems to start progressing at the age somewhere in 35-44 years. In the remaining age-groups (at onset) from0-4 years, the percentages were found to be quite low 1per cent or even less. The results suggest that apartfrom old age, visual disability tends to manifest duringthe early years of life. Nevertheless, about 1 to 2 percent was visually disabled by birth. The distributionappears to be identical both for the blind and personswith low vision, for the rural and urban, and for themale and female.

SARVEKSHANA76

Statement 19: Per 1000 distribution of persons 60 years and above with blindness or low vision by age at onsetof disability all-India

category disa- age at onset (years)biliysincebirth

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

blindness

rural male 21 5 8 7 4 2 2 10 45 196 699 1000rural female 17 8 10 8 4 6 8 5 26 238 673 1000rural persons 19 7 9 7 4 4 5 7 34 220 684 1000

urban male 18 6 6 10 5 4 1 19 23 301 606 1000urban female 9 12 5 9 14 0 1 7 21 288 633 1000urban persons 13 9 5 10 10 2 1 12 22 294 621 1000

all male 21 5 7 7 4 2 2 12 41 214 683 1000all female 15 8 9 8 6 5 7 5 25 246 666 1000all persons 18 7 8 8 5 4 5 8 32 233 673 1000

low vision

rural male 13 2 6 4 3 2 0 2 6 234 729 1000rural female 2 8 5 3 0 1 2 0 12 259 708 1000rural persons 7 6 5 3 1 2 1 1 9 248 717 1000

urban male 12 0 1 4 0 0 1 0 15 231 727 1000urban female 2 2 0 3 0 7 0 0 25 254 709 1000urban persons 5 1 0 3 0 4 1 0 21 245 716 1000

all male 13 2 5 4 3 2 0 2 7 233 729 1000all female 2 7 4 3 0 2 1 0 14 258 708 1000all persons 6 5 4 3 1 2 1 1 11 248 717 1000

0 –

4

5 –

9

10 –

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15 –

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20 –

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25 –

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30 –

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3.2.4. Causes of Visual Disability : The distributionof visually disabled persons by probable cause of visualdisability is given in Statements 20 and 21 for rural andurban India. In India, the cause was not known to about9 per cent of the blind. About 24 per cent reported ‘oldage’ as the cause for their blindness. Apart from the ‘oldage’, ‘cataract’ happened to be one of the main causes ofblindness – the percentage reporting the cause was about

21. It may noted that the development of cataract takesplace normally as the age of an individual progressesand is relatively higher at the old ages. ‘Other eye diseases’caused blindness in about 17 per cent cases. These factssuggest that the blindness is essentially an old ageproblem. Although there is a marginal difference in themale–female and rural–urban distributions but the patternin them remains same.

SARVEKSHANA 77

Statement 20: Per 1000 distribution of persons with blindness by cause of blindness for each sex and sector

cause of rural urban rural+urban

blindness male female person male female person male female person

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

1. sore eyes firstmonth life 5 2 3 2 1 1 4 2 3

2. sore eyes afterone month 8 4 6 10 7 8 8 5 6

3.severe diarrhoeabefore age six 9 5 7 5 11 8 8 6 7

4. cataract 187 233 212 214 183 196 192 223 209

5. glaucoma 54 51 52 64 93 80 56 59 58

6.corneal opacity 26 17 21 24 54 40 25 24 25

7.other eye diseases 186 157 170 171 158 164 183 157 169

8. small pox 53 42 47 43 31 36 51 40 45

9. burns 4 4 4 4 0 2 4 3 3

10. injury otherthan burns 50 28 38 73 26 47 54 28 39

11.medical/surgicalintervention 21 23 22 48 49 49 26 28 27

12. old age 212 281 250 158 234 200 202 272 241

13. other reasons 91 54 70 89 62 74 90 55 71

14. not known 85 94 90 93 86 89 87 92 90

total* 1000 1000 1000 1000 1000 1000 1000 1000 1000

* ’total’ includes not recorded cases of ‘cause of blindness’

Even for the persons with low vision, the pattern ofdistribution remains same as that for the blind. About 10per cent of them did not know the probable cause of theirlow vision and about 57 per cent reported to have problem

due to old age or cataract. The other major causes forlow vision were found to be other eye diseases (12 percent), injury other than burns (5 per cent), corneal opacity(4 per cent), etc.

SARVEKSHANA78

Statement 21: Per 1000 distribution of persons with low vision by cause of low vision for each sex and sector

cause of rural urban rural+urban

low vision male female person male female person male female person

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

1. sore eyes firstmonth life 1 0 1 0 2 1 1 0 1

2. sore eyesafter one month 5 0 2 3 5 4 5 1 3

3.severe diarrhoeabefore age six 8 2 5 5 9 7 8 3 5

4. cataract 272 287 280 293 405 358 276 309 294

5. glaucoma 36 29 32 41 38 40 36 31 33

6. corneal opacity 59 39 48 22 8 14 53 33 42

7.other eye diseases 121 100 109 221 122 163 137 104 119

8. small pox 14 7 10 12 7 9 14 7 10

9. burns 2 4 3 3 3 3 2 4 3

10. injury otherthan burns 64 28 44 92 34 58 69 29 47

11.medical/surgicalintervention 21 13 17 23 31 28 22 16 19

12. old age 236 342 295 156 228 198 223 321 278

13. other reasons 38 31 34 65 43 52 42 33 37

14. not known 111 108 110 58 59 59 102 99 101

total* 1000 1000 1000 1000 1000 1000 1000 1000 1000

* 'total' includes not recorded cases of 'cause of low vision'

3.3 Hearing Disability

Inability of persons to hear properly was considered ashearing disability. For the purpose of the survey, hearingdisability was judged taking into consideration the abilityof the better ear. In other words, if one ear of a person wasnormal and the other ear had total hearing loss, the personwas judged as normal in hearing. Hearing disability wasjudged without taking into consideration the use of hearingaids. In this round, however, all persons were interviewedfor collection of information on hearing disability.

3.3.2 Prevalence of hearing disability: In Statement22, the prevalence rate i.e. number of persons withhearing disability per 100,000 persons is presented foreach sex separately for rural and urban sectors of all-India. The prevalence rate was higher in rural India(310) as compared to that in urban India (236) formales as well as females. Between the two sexes, theprevalence of hearing disability was marginally higheramong males (319) than among females (301) in ruralIndia while in urban India it was nearly of the sameorder (234 to 238).

SARVEKSHANA 79

Statement 22: Number of persons with hearing disability per 100,000 persons by degree of disability for eachsex and sector

degree rural urban rural + urbanof disability male female persons male female persons male female persons

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

1.profound 102 90 96 81 82 81 96 88 92

2. severe 123 124 123 85 85 85 113 114 113

3.moderate 93 86 90 68 70 69 86 82 84

all 319 301 310 234 238 236 296 285 291

3.3.3 Age at the onset of hearing disability: It isfound that some people suffer from hearing disability sincetheir birth, while some acquire it afterwards. Informationrelating to age at the onset of hearing disability wascollected for those who acquired it in course of life. Inorder to study the age at onset, the distribution of personsaged 60 years and above with hearing disability by ageat onset is given in Statement 23 for rural and urbansectors of all-India. The survey results reveal that in India,

about 7 per cent of the persons with hearing disabilitywere born with it. About 56 and 62 per cent reported theonset of hearing disability at ages 60 years and above inthe rural and urban sectors, respectively. In both thesectors, the onset of hearing disability in eachquinquennial age group up to 30-34 years was quite lowand almost of the same order - around 1 per cent. Theresults also indicate that the hearing disability is mainlya problem of old age.

Statement 23: Per 1000 distribution of persons 60 years and above with hearing disability by age at onset ofdisability for each sex and sector

category disa- age at onset (years)biliysincebirth

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

rural male 86 9 6 16 4 17 4 14 40 229 575 1000

rural female 51 5 8 14 5 16 7 19 51 283 540 1000

rural persons 68 7 7 15 5 16 5 16 46 257 557 1000

urban male 46 6 10 16 8 6 10 13 46 220 620 1000

urban female 60 4 18 4 11 9 6 14 47 210 616 1000

urban persons 53 5 14 10 10 8 8 13 47 215 618 1000

all male 77 8 7 16 5 14 5 14 41 227 585 1000

all female 53 5 10 12 6 15 7 18 51 267 557 1000

all persons 65 6 9 14 6 14 6 16 46 247 571 1000

0 –

4

5 –

9

10 –

14

15 –

19

20 –

24

25 –

29

30 –

34

35 –

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59

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SARVEKSHANA80

3.3.4 Probable cause of hearing disability: For thosewho acquired hearing disability in course of time,information on probable cause of hearing disability asknown to the informant, was collected. The distributionof such persons is presented in Statement 24 for all-India.

In about 25 and 30 per cent cases, for rural and urbanIndia respectively, the probable cause of hearing disabilitywas ‘old age’. Of the other reasons, ‘ear discharge’ and‘other illness’ were identified as the cause by acomparatively large proportion of persons with hearingdisability. It may be noted that nearly 1 per cent of thedisabled (hearing) persons reported ‘German measles/rubella’ as the cause of hearing disability. Thedistributions for each sex and sector are seen to be similarin pattern.

Statement 24: Per 1000 distribution of persons with hearing disability by cause hearing disability for each sexand sector

cause of rural urban rural+urban

hearing disability male female person male female person male female person

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

1.GermanMeasles/ Rubella 9 4 6 5 11 8 8 5 7

2.noise inducedhearing loss 22 13 17 38 23 31 25 15 20

3.ear discharge 169 160 165 136 129 132 162 154 158

4. other illness 221 237 229 214 228 221 220 235 227

5. burns 4 0 2 1 2 2 3 1 2

6. injury otherthan burns 53 41 47 71 47 59 56 42 49

7.medical/surgical intervention 11 16 14 19 26 22 13 18 15

8. old age 244 264 254 291 300 295 254 272 263

9.other reasons 74 81 77 99 100 99 79 85 82

10. not known 188 178 183 125 131 128 175 168 172

total* 1000 1000 1000 1000 1000 1000 1000 1000 1000

* 'total' includes not recorded cases of 'cause of hearing disability'

3.4 Speech Disability

As mentioned earlier, a person’s inability to speakproperly was considered his/her speech disability. Personswith speech disability were categorised as:

(i) Persons who could not speak at all;

(ii) Persons who could speak only in single words;

(iii)Persons who could speak only unintelligibly;

(iv) Persons who stammered;

(v) Persons who could speak with abnormal voice; likenasal voice, hoarse voice and discordant voice etc.,

(vi) Persons who had any other speech defects, such asarticulation defects, etc.

SARVEKSHANA 81

3.4.2 Prevalence of speech disability: In Statement25, the prevalence rate i.e., that the number of personswith speech disability per 100,000 persons is given forrural and urban sectors of all-India. The male-femaledifference was considerably high and a higher proportionof male had speech disability than females. Out of 100,000males in the rural areas 242 had speech disability whilethe corresponding number in the urban areas was 221.On the other hand, 176 and 151 females per 100,000females had speech disability in rural and urban India,respectively.

Statement 25: Number of persons with speechdisability per 100,000 persons for each sex and sector

sector male female persons

(1) (2) (3) (4)

rural 242 176 210

urban 221 151 187

rural & urban 237 169 204

3.4.3 Age at the onset of speech disability: For thosewho acquired the speech disability in course of time,information relating to age at the onset of speech disabilitywas also collected in the survey. In order to study the

Statement 26: Per 1000 distribution of persons 60 years and above with speech disability by age at onsetof disability for each sex and sector

category disa- age at onset (years)biliysincebirth

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

rural male 363 15 1 12 11 2 0 16 28 211 342 1000

rural female 394 5 22 20 0 0 4 6 40 161 349 1000

rural persons 375 11 9 15 7 1 2 12 33 190 345 1000

urban male 241 4 7 11 2 0 0 27 1 254 453 1000

urban female 383 8 12 1 0 2 2 0 9 174 410 1000

urban persons 306 6 9 6 1 1 1 15 4 218 434 1000

all male 331 12 2 11 9 1 0 19 21 222 371 1000

all female 391 6 19 14 0 1 4 4 31 165 367 1000

all persons 356 9 9 13 5 1 1 13 25 198 369 1000

0 –

4

5 –

9

10 –

14

15 –

19

20 –

24

25 –

29

30 –

34

35 –

44

45 –

59

60 &

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pattern of age at onset of speech disability, the cohort ofpersons of age 60 years and above having speech disabilityhas been considered and their distribution by age at onsetis given in Statement 26 for rural and urban sectors ofall-India. At the all-India level, about 35 and 43 percentin rural and urban sectors respectively reported that theywere affected by speech disability on reaching the age of60 years or more. About 38 per cent of the people in therural and 31 per cent in the urban areas have congenitalspeech defects. The next vulnerable age group shows thatthe development of speech defects was 45-59 years. Therural-urban differential in the onset of speech defect ismarked both for congenital onset as well for the age 60years or more. The onset of speech defects is seen to bemore at higher age groups.

3.4.4 Cause of speech disability: For those whoacquired speech disability in course of time, informationrelating to probable cause of speech disability wascollected. The results (Statement 27) reveal that in ruraland urban India, about 15 and 10 per cent of themrespectively, did not know the cause of speech disability.Among the reported causes, ‘paralysis’ and ‘other illness’were the major ones. As high as 46 and 49 per cent of

SARVEKSHANA82

cases of speech defects reported ‘paralysis’ or ‘otherillness’ as the cause in the rural and urban sectors,respectively. About 9 per cent had developed speechdisability due to mental illness/retardation and 8 per centdue to voice disorders. It may be worth noting thatcontrary to visual and hearing disabilities, only 1 per centreported old age as the cause of speech disability.

Statement 27: Per 1000 distribution of persons with speech disability by cause of speech disability of persons foreach sex and sector

cause of rural urban rural+urban

speech disability male female person male female person male female person

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

1.hearingimpairment 2 4 9 9 3 1 1 2 3

2.voice disorder 87 96 90 64 73 67 79 89 83

3.cleft palate/lip 7 27 15 23 18 21 12 24 17

4. paralysis 245 229 239 239 272 250 243 242 242

5.mental illness /retardation 67 98 79 91 117 100 75 103 85

6. other illness 236 198 222 238 251 243 237 214 228

7. burns 6 4 5 1 11 5 4 6 5

8. injury otherthan burns 62 22 46 79 30 62 68 24 51

9.medical/ surgicalintervention 19 21 20 37 55 44 25 31 27

10. old age 12 18 14 7 16 10 10 17 13

11.other reasons 57 85 68 75 56 68 63 76 68

12. not known 160 129 148 118 70 102 146 112 133

total* 1000 1000 1000 1000 1000 1000 1000 1000 1000

* 'total' includes not recorded cases of 'cause of speech disability'

3.5 Locomotor Disability

Persons having loss or lack of normal ability to executedistinctive activities associated with moving self andobjects from one place to another were treated as personshaving locomotor disability. Such loss or lack of normal

ability can occur due to (i) paralysis of the limb or body,(ii) deformity of the limb, (iii) loss of limb, (iv) dysfunctionof the joints of the limb and (v) deformity of the bodyother than that in the limb. These are termed as types oflocomotor disability .The survey estimated 10.66 millionpersons as having locomotor disability in the Country.Of them, about 8 million lived in the rural areas and 2.66

million in the urban areas. Further about 4 per cent ofthose who had locomotor disability reported to have eithermultiple locomotor disabilities (two or more types oflocomotor disabilities) or 2 or more other disabilities inboth the rural and urban sectors.

SARVEKSHANA 83

3.5.2 Prevalence of locomotor disability: Theprevalence rate (per 100,000 persons) of persons havinglocomotor disability is given in Statement 28 for eachsex separately for rural and urban sectors of all-India.Compared to other types of disability, the prevalence oflocomotor disability per 100,000 persons was higher. Therate was as high as 1046 and 901 in rural and urbanIndia. Among males, the prevalence was much higherthan among females, 1217 and 785 (per 100,000) formales and females, respectively, for both the sectors takentogether.

Statement 28: Number of persons with locomotordisability per 100,000 persons for each sex and sector

sex

sector male female persons

(1) (2) (3) (4)

rural 1274 804 1046

urban 1058 730 901

rural &urban 1217 785 1008

3.5.3 Pattern of age at onset of locomotor disability:In order to study the pattern of age at onset of locomotordisability, the cohort of persons of age 60 years and abovewho acquired locomotor disability in course of time haveonly been taken into account. The distribution of suchpersons by age at onset of disability is given in Statement29. For persons having two types of locomotor disability,the age of the onset of the first among them has beenconsidered. As was observed in the case of visual andhearing disability, for locomotor disability also, as highas 49 and 57 per cent were found to have acquired thedisability at the age of 60 years and above in rural andurban India respectively. The said percentage in thepreceding age-group (45-59 years) was 27 to 29. It alsoindicates that people in rural areas have relatively higherincidence of locomotor disability in the lower age-groupsthan those in the urban areas.

Statement 29: Per 1000 distribution of persons 60 years and above with locomotor disability by age at onset ofdisability for each sex and sector

category disa- age at onset (years)biliysincebirth

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

rural male 60 18 24 11 12 16 11 23 71 292 460 1000

rural female 58 19 11 17 3 7 3 16 48 284 531 1000

rural persons 59 19 18 14 8 12 7 20 61 288 492 1000

urban male 36 28 10 21 7 25 8 17 48 289 511 1000

urban female 37 21 9 6 6 5 3 8 26 248 629 1000

urban persons 37 24 10 14 6 16 6 13 38 269 567 1000

all male 54 20 20 14 11 18 11 21 66 291 472 1000

all female 53 20 11 14 4 6 3 14 42 274 557 1000

all persons 54 20 16 14 8 13 7 18 55 284 511 1000

0 –

4

5 –

9

10 –

14

15 –

19

20 –

24

25 –

29

30 –

34

35 –

44

45 –

59

60 &

abov

e

tota

l

SARVEKSHANA84

3.5.4 Probable cause of locomotor disability: Theinformation relating to probable cause of locomotordisability, as known to the informant, was collected forthose who were affected by locomotor disability. Thedistribution of such persons by probable cause oflocomotor disability is given in Statement 30 for all-India. Polio was found to be the major reason forlocomotor disability. About 30 and 27 per cent of thepersons with locomotor disabilities reported ‘polio’ asthe cause in the rural and urban sectors, respectively.The next in importance was the cause ‘injuries other

than burns’ accounting for 26 to 27 per cent. Contraryto the results relating to visual and hearing disability,the percentage of persons who acquired locomotordisability due to ‘old age’ was as low as 3 to4 at the all-India level. In this context, it may be mentioned that theincidence of locomotor disability due to causes, like,stroke, arthritis, cardio respiratory diseases, etc. wasgenerally higher at the older age than at the youngerages. Note that, about 3 per cent of the disabled personsreported leprosy (both cured and not cured) as the causeof locomotor disability.

Statement 30: Per 1000 distribution of persons with locomotor disability by cause of locomotor disability foreach sex and sector

cause of rural urban rural+urban

locomotor disability male female person male female person male female person

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

1. cerebral palsy 23 26 24 22 25 23 23 26 24

2. polio 297 291 295 269 273 270 290 286 289

3. leprosy cured 9 6 8 30 28 29 15 12 14

4. leprosy not cured 18 14 17 7 9 8 15 13 14

5. stroke 67 65 66 85 78 82 71 68 70

6. arthritis 22 43 29 21 57 35 22 46 31

7. cardio-respiratorydisease 4 2 3 2 3 3 4 2 3

8. cancer 3 4 3 2 1 2 3 3 3

9. tuberculosis 4 1 3 4 3 3 4 2 3

10. other illness 107 143 120 111 135 120 108 141 120

11. burns 19 22 20 18 18 18 19 21 19

12. injury otherthan burns 291 196 256 310 207 271 295 199 260

13. medical/ surgicalintervention 20 19 20 28 24 26 22 20 21

14. old age 21 59 35 14 58 31 20 59 34

15. other reasons 43 50 46 39 45 41 42 49 44

16. not known 44 52 47 31 31 31 41 47 43

total* 1000 1000 1000 1000 1000 1000 1000 1000 1000

* 'total' includes not recorded cases of 'cause of locomotor disability'.

SARVEKSHANA 85

3.6 Conclusions:

The data presented in this paper give an idea about theproblems faced by the disabled persons in the country invarious walks of their life. Though collecting suchdisability data through household survey has somelimitation, data presented here can be used by policymakers in devising various plans for improving the qualityof life of disabled in the country. Data presented herealso illustrate that information on sensitive subject likemental disability can be also collected successfullythrough household surveys by proper planning andpretesting.

Reference

National Sample Survey Organisation, Govt. of India(2003):Disabled Persons in India, 58th round, ReportNumber 485: July-December 2002

National Sample Survey Organisation, Govt. of India(1994):A report on Disabled Persons in India, 47th round,Report Number 393:July-December 1991

National Sample Survey Organisation, Govt. of India(1987): Characteristics of Disabled Persons, 36th round,Report Number 337:July-December 1981

National Sample Survey Organisation, Govt. of India(1983): Report on survey of Disabled Persons, 36th round,Report Number 305: July-December 1981

SARVEKSHANA86

Number of sample villages/blocks allotted and surveyed in the Central sample for NSS 58th round survey

State/UT allotted surveyed

rural urban rural urban

(1) (2) (3) (4) (5)

Jammu & Kashmir 152 100 96 66Himachal Pradesh 104 20 99 20Punjab 104 104 99 102Chandigarh 8 20 8 18Uttaranchal 48 32 45 30Haryana 80 64 79 64Delhi 8 144 8 121Rajasthan 228 140 226 138Uttar Pradesh 592 308 588 301Bihar 364 84 362 83Sikkim 56 16 56 14Arunachal Pradesh 72 36 58 7Nagaland 44 20 44 19Manipur 92 60 90 58Mizoram 80 152 33 67Tripura 104 40 103 40Meghalaya 64 32 62 25Assam 236 68 224 65West Bengal 372 292 370 278Jharkhand 132 76 129 68Orissa 192 68 190 67Chhatisgarh 84 40 83 40Madhya Pradesh 244 180 242 175Gujarat 120 136 119 132Daman & Diu 8 16 8 15D & N Haveli 12 12 12 12Maharashtra 292 420 291 409Andhra Pradesh 308 224 306 219Karnataka 180 188 175 177Goa 8 8 8 7Lakshadweep 8 8 8 8Kerala 172 108 160 102Tamil Nadu 228 356 226 351Pondichery 12 40 12 40Andaman & N. Isl 20 16 18 16

All-India 4828 3628 4637 3354

ANNEXURE - I

SARVEKSHANA 87

ANNEXURE - II

Concepts and Definitions

Some broad definitions of household, disability and itstypes, etc. that are used for collection of data pertainingto survey on disability are presented in this section.

1 Household: A group of persons normally livingtogether and taking food from a common kitchenconstituted a house-hold. The members of a householdmight not be related by blood to one another. Note thatresidential institutions for disabled were also covered forthe survey.

2 Disability: A person with restrictions or lack ofabilities to perform an activity in the manner or withinthe range considered normal for a human being wastreated as having disability. It excluded illness/injury ofrecent origin (morbidity) resulting into temporary loss ofability to see, hear, speak or move.

3 Mental disability: Persons who had difficulty inunderstanding routine instructions, who could not carryout their activities like others of similar age or exhibitedbehaviours like talking to self, laughing / crying, staring,violence, fear and suspicion without reason wereconsidered as mentally disabled for the purpose of thesurvey. The “activities like others of similar age” includedactivities of communication (speech), self-care (cleaningof teeth, wearing clothes, taking bath, taking food,personal hygiene, etc.), home living (doing somehousehold chores) and social skills.

4 Visual disability: By visual disability, it wasmeant, loss or lack of ability to execute tasks requiringade-quate visual acuity. For the survey, visually disabledin-cluded (a) those who did not have any light perception- both eyes taken together and (b) those who had lightperception but could not correctly count fingers of hand(with spectacles/contact lenses if he/she used spectacles/

contact lenses) from a distance of 3 metres (or 10 feet) ingood day light with both eyes open. Night blindness wasnot considered as visual disability.

5 Hearing disability: This referred to persons’inabili-ty to hear properly. Hearing disability was judgedtaking into consideration the disability of the better ear.In other words, if one ear of a person was normal and theother ear had total hearing loss, then the person was judgedas normal in hearing for the purpose of the survey.Hearing disability was judged without taking intoconsideration the use of hearing aids (i.e., the positionfor the person when hearing aid was not used). Personswith hearing disability might be having different degreesof disability, such as profound, severe or moderate. Aperson was treated as having ‘pro-found’ hearingdisability if he/she could not hear at all or could onlyhear loud sounds, such as, thunder or understands onlygestures. A person was treated as having ‘severe’ hearingdisability if he/she could hear only shouted words or couldhear only if the speak-er was sitting in the front. A personwas treated as having ‘moderate’ hearing disability if his/her disability was neither profound nor severe. Such aperson would usually ask to repeat the words spoken bythe speaker or would like to see the face of the speakerwhile he/she spoke or would feel difficulty in conductingconversations.

6 Speech disability: This referred to persons’inabil-ity to speak properly. Speech of a person wasjudged to be disor-dered if the person’s speech was notunderstood by the listener. Persons with speech disabilityincluded those who could not speak, spoke only withlimited words or those with loss of voice. It also includedthose whose speech was not understood due to defects inspeech, such as stammering, nasal voice, hoarse voiceand discordant voice and articulation de-fects, etc.

SARVEKSHANA88

7 Locomotor disability: A person with - (a) lossor lack of normal ability to execute distinc-tive activitiesassociated with the movement of self and objects fromplace to place and (b) physical deformities, other thanthose involving the hand or leg or both, regardless ofwhether the same caused loss or lack of normal movementof body – was considered as disabled with locomotordisability. Thus, persons having locomotor disabilityincluded those with (a) loss or absence or inactivity ofwhole or part of hand or leg or both due to amputation,paralysis, deformity or dys-function of joints whichaffected his/her “normal ability to move self or objects”and (b) those with physical deformities in the body (otherthan limbs), such as, hunch back, deformed spine, etc.Dwarfs and persons with stiff neck of permanent naturewho generally did not have difficulty in the normalmovement of body and limbs was also treated as disabled.

8 Economic activity: Any activity resulting inproduc-tion of goods and services that adds value tonational product was considered as economic activity.Such activities included produc-tion of all goods andservices for market i.e. production for pay or profit andthe production of primary commodities for ownconsumption and own account production of fixed assets,among the non-market activities. The entire spectrum ofhuman activity falls into two catego-ries viz. economicand non-economic activities. The economic activities havetwo parts - market activities and non-market activities.Market activities are those that involve remuneration tothose who perform it i.e., activity performed for pay orprofit. These are essentially production of goods and

services for the market including those of governmentservices etc. Non-market activities are the production forown consumption of primary products including ownaccount processing of primary products and own accountproduction of fixed assets. However the whole spectrumof economic activities as defined in the UN System ofNational Accounts (SNA) was not covered under‘econom-ic activity’ in the 58th round. The term “economicactivity” included:

(i) all the market activities described above i.e.the activi-ties performed for pay or profit,and (ii) of the non-market activities:

(a) all the activities relating to agriculturalsector which result in production(including gathering of uncultivatedcrops, forestry, collection of firewood,hunting, fishing etc.) of agriculturalproduce for own consumption and

(b) the activities relating to the own-account production of fixed assets.Own account production of fixedassets includes construction of ownhouses, roads, wells etc., and ofmachinery, tools etc. for householdenterprise and also construction of anyprivate or community facilities free ofcharge. A person may be engaged inown account construction either in thecapacity of a labourer or a supervisor.

SARVEKSHANA 89

Table 1: Number of disabled persons per 1,00,000 persons for each State/UT

State/UT rural urban rural+urban

male female person male female person male female person

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Jammu & Kashmir 2120 1173 1643 1401 1100 1255 1966 1158 1562Himachal Pradesh 3326 2135 2708 1632 1025 1318 3158 2026 2571Punjab 2576 1813 2224 1584 1363 1484 2255 1672 1987Chandigarh 865 703 799 577 549 567 603 567 590Uttaranchal 2200 1884 2052 1155 665 917 1966 1596 1791

Haryana 2256 1505 1896 1537 1159 1358 2076 1421 1762Delhi 823 451 670 642 368 522 690 388 559Rajasthan 1826 1202 1519 1596 1023 1316 1768 1158 1468Uttar Pradesh 2319 1574 1964 1821 1320 1590 2214 1523 1887Bihar 2098 1218 1677 1725 1169 1462 2056 1213 1652

Sikkim 1860 1565 1720 654 518 590 1734 1456 1602Arunachal Pradesh 1861 1471 1669 109 27 72 1599 1281 1444Nagaland 895 944 918 602 812 706 803 901 851Manipur 1092 849 973 1090 850 969 1091 849 972Mizoram 855 780 820 814 569 680 839 683 762

Tripura 748 686 719 1176 1061 1118 796 731 765Meghalaya 1871 1418 1646 1117 677 908 1765 1322 1546Assam 1062 894 986 1189 970 1085 1072 900 993West Bengal 2006 1355 1696 2094 1740 1927 2028 1451 1754Jharkhand 1614 934 1281 1352 726 1047 1563 893 1236

Orissa 2671 2418 2544 1971 1663 1821 2586 2330 2459Chhatisgarh 2012 1582 1800 1973 1743 1862 2006 1607 1810Madhya Pradesh 1969 1499 1746 1749 1220 1503 1909 1424 1680Gujarat 2169 1556 1867 1822 1325 1585 2036 1471 1761Daman & Diu 649 1370 923 1500 1229 1374 947 1309 1096

D & N Haveli 990 712 859 798 610 708 963 699 838Maharashtra 2375 1677 2031 1594 1398 1501 2067 1572 1827Andhra Pradesh 1980 1827 1905 1524 1302 1414 1852 1675 1765Karnataka 1977 1521 1749 1245 973 1112 1754 1359 1558Goa 2326 1039 1624 1454 1650 1533 2034 1174 1599

Lakshadweep 2768 1983 2331 2636 2592 2614 2691 2302 2487Kerala 2451 2010 2215 2552 2082 2303 2475 2026 2235Tamil Nadu 2188 1864 2028 1967 1558 1759 2112 1755 1934Pondicherry 1817 1792 1804 2310 2561 2424 2134 2238 2184Andaman & N. Isl 2266 1126 1670 1290 604 979 1975 999 1483

all-India 2118 1556 1846 1670 1311 1499 2000 1493 1755

ANNEXURE - III

SARVEKSHANA90

Table 2: Per 1000 distribution of disabled persons of age 5 years and above by level of general education foreach State/UT

State/UT rural urban rural+urban

literate literate literate

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

Jammu & Kashmir 659 155 97 88 551 181 128 141 641 160 103 96Himachal Pradesh 527 235 100 138 296 271 77 347 515 237 99 148Punjab 610 210 63 117 479 242 88 187 578 218 69 134Chandigarh 510 249 157 85 438 223 121 218 447 226 126 201Uttaranchal 616 231 106 47 394 234 149 216 590 231 111 67

Haryana 536 304 58 102 435 237 85 243 517 291 63 129Delhi 148 345 254 253 278 288 154 279 241 304 183 272Rajasthan 617 246 81 54 454 278 108 160 581 253 87 78Uttar Pradesh 612 236 98 53 453 274 119 154 584 242 102 68Bihar 678 179 72 69 444 295 119 143 655 191 76 77

Sikkim 692 247 43 19 314 412 78 176 677 253 44 24Arunachal Pradesh 837 84 42 21 523 105 216 157 835 84 43 22Nagaland 463 354 129 54 246 404 173 177 407 367 141 86Manipur 637 153 124 79 481 183 139 183 598 161 128 105Mizoram 489 391 89 31 377 398 151 71 447 393 112 46

Tripura 512 350 96 40 310 282 274 134 477 339 127 56Meghalaya 523 419 41 16 415 400 116 68 515 418 46 19Assam 504 360 101 34 287 329 226 156 484 357 112 45West Bengal 525 306 98 69 359 327 146 165 479 311 112 96Jharkhand 709 185 65 42 399 235 162 202 657 193 81 68

Orissa 657 208 91 44 492 229 142 135 642 210 96 52Chhatisgarh 578 305 72 44 490 273 88 149 563 300 75 62Madhya Pradesh 563 309 75 51 391 339 114 154 521 316 85 77Gujarat 506 265 140 88 342 261 162 231 451 264 148 136Daman & Diu 596 256 47 101 351 307 152 189 478 281 98 143

D & N Haveli 490 324 99 86 217 319 116 347 458 324 101 117Maharashtra 542 236 136 85 333 334 171 162 476 267 147 109Andhra Pradesh 686 183 65 66 472 240 105 183 637 196 74 93Karnataka 597 201 111 91 443 208 157 191 565 202 121 112Goa 483 239 121 157 332 186 244 238 443 225 154 179

Lakshadweep 365 513 82 40 521 367 80 31 456 428 81 35Kerala 345 371 195 89 285 380 180 154 331 373 192 104Tamil Nadu 586 249 86 78 404 268 134 194 528 255 101 115Pondicherry 546 339 75 40 380 381 128 111 433 368 111 88A & N.Isl 345 453 169 32 272 259 259 210 332 419 185 65

all-India 590 244 97 69 400 288 137 175 547 254 106 92

ANNEXURE - IV

not

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pri

mar

y

mid

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seco

ndar

y &

abov

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not

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rate

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SARVEKSHANA 91

An Integrated Summary of NSS 58th Round (July 2002 - December 2002)On "Village Facilities"

Siladitya Chaudhuri

Introduction:

A large section of our population lives in rural areas andit is often said that “India lives in her villages”. It is thuspertinent to know the quality of life of the people in thevillages, which in turn largely depends on the facilitiesavailable in the villages. The National Sample Surveyhas a long experience of collecting information on theavailability of various infrastructural facilities in villages.Such information was collected more or less regularlytill the 22nd round of NSS. But since then, only a fewNSS rounds have been devoted to collecting suchinformation. A detailed enquiry on village facilities wasconducted as part of the NSS 47th round (July-December1991). Similar information was collected along with thelisting operations during the NSS 52nd round (1995-96).The urgent need for reliable information on the subjectled to the inclusion of an enquiry on village facilities inthe 58th round of NSS (July-December 2002).

Objective of the survey:

In order to measure the quality of life of the people ofrural India, the NSS 58th round of survey, collected dataon the existence of various infrastructural facilities inthe villages or their distance from the nearest availablefacility of each kind. The facilities covered includedelectricity, drinking water, drainage, irrigation and non-conventional energy - the nature of availability beinginvestigated to some extent. It was further ascertainedwhether the village had a co-operative society, a self-help group, and a community TV centre, and whethercable TV connection was available. Next, it was enquiredwhether the village had any Government programme/

scheme relating to any of the following: (a) drinking water;(b) housing; (c) sanitation; (d) approach road; (e)employment; (f) pension; (g) electricity; (h) watershed/minor irrigation; (i) total literacy campaign/ adulteducation. Finally, information on the availability of some36 specified facilities was collected.

Coverage of the survey

The survey was conducted in the whole of India except(i) Leh and Kargil Districts of Jammu & Kashmir, (ii)interior villages of Nagaland situated beyond fivekilometres of any bus route and (iii) villages in Andamanand Nicobar Islands which remained inaccessiblethroughout the year. The field work for the survey startedin July 2002 and was completed in December 2002. Theentire survey period of this round was divided into twosub-rounds of three months duration each.

Sample design and Estimation procedure:

A stratified multi-stage design was adopted for the surveyof the NSS 58th round. The first stage units were 1991Census villages (Panchayat wards for Kerala) in generaland 1981 Census villages for Jammu & Kashmir.Normally, the rural areas of each district formed astratum. Wherever the rural population of a districtexceeded a certain limit, the district was divided into anumber of strata. The sample villages were selected withprobability proportional to population (except for specialstrata consisting of small villages where simple randomsampling was done), in the form of two independent sub-samples from each stratum. In all, 4646 sample villageswere surveyed at the all-India level in this round.

SARVEKSHANA92

Table 1: Number of surveyed villages by type of informant for schedule on village facilities

informant for schedule on village facilities

State/UT sarpanch other grampan— sewak/ school health other not all

male female chayat other teacher personnel informant recordedmember village

official

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Jammu & Kashmir 20 0 21 37 2 0 15 0 95

Himachal Pradesh 29 7 36 16 2 0 10 0 100

Punjab 53 10 24 7 1 1 4 0 100

Chandigarh 2 2 2 0 0 0 2 0 8

Uttaranchal 18 1 9 3 2 0 14 0 47

Haryana 42 8 12 1 2 0 8 0 79

Delhi 1 0 1 1 3 0 2 0 8

Rajasthan 57 19 51 37 44 0 19 0 227

Uttar Pradesh 257 43 88 58 40 3 83 6 578

Bihar 84 2 191 35 8 1 40 3 364

Sikkim 3 2 27 6 6 0 12 0 56

Arunachal Pradesh 14 0 10 7 13 0 24 3 71

Nagaland 12 0 15 15 2 0 0 0 44

Manipur 24 0 21 18 4 0 17 5 89

Mizoram 8 0 3 4 11 1 6 2 35

Tripura 40 1 36 19 4 0 0 2 102

Meghalaya 35 0 3 11 12 1 2 0 64

Assam 73 1 49 50 25 2 25 1 226

West Bengal 54 13 189 35 22 2 52 3 370

Jharkhand 4 1 14 15 15 2 79 0 130

Orissa 27 9 63 31 22 2 36 0 190

Chhattisgarh 32 9 16 17 7 1 2 0 84

Madhya Pradesh 66 12 53 60 34 1 14 0 240

Gujarat 34 8 26 39 10 0 2 0 119

Daman & Diu 2 1 1 4 0 0 0 0 8

Dadra & N. Haveli 5 1 2 4 0 0 0 0 12

Maharashtra 77 20 42 126 21 0 5 0 291

Andhra Pradesh 99 17 21 147 7 0 12 0 303

Karnataka 13 1 60 65 22 0 15 0 176

Goa 0 2 2 3 0 0 1 0 8

Lakshadweep 0 0 5 1 0 0 0 0 6

Kerala 11 4 71 23 18 0 31 0 158

Tamil Nadu 47 4 44 106 18 0 8 0 227

Pondicherry 0 0 2 0 2 3 5 0 12

A & N Islands 2 0 3 4 0 0 10 0 19

all-India 1245 198 1213 1011 379 20 555 25 4646

SARVEKSHANA 93

Estimation Procedure

Notations:

s = subscript for stratum

m = subscript for sub-sample (m =1, 2)

i = subscript for FSU (village/ panchayat ward)

N = total number of FSUs in rural stratum 1

Z = total size of a general stratum or special stratum 2 ofrural sector (= sum of sizes for all the FSUs of astratum)

z = size of sample village used for selection.

n = number of sample village surveyed including zerocases but excluding casualty for a particular sub-sample and stratum / sub-stratum.

x, y: observed values of characteristics x, y underestimation

X

, Y : estimate of the population totals X, Y forthe characteristics x, y

In terms of the above symbols,

ysmi

= observed value of the characteristic y for the i-thsample village belonging to the m-th sub-samplefor the s-th rural stratum;

However, for ease of understanding, a few symbols havebeen suppressed in the following paragraphs where theyare obvious.

Formulae for estimating the number of villagespossessing a characteristic for a stratum× sub-sample(based on the notation given in ‘note on the sample designand estimation procedure for 58th round- Annex-II) :

a) For stratum 1 (special strata consisting of smallvillages where simple random sampling was done)at State/UT level,

∑=

=n

yn

NY

i

i

1

ˆ

where iy is taken as 1 if a sample villagepossesses the characteristic and as 0otherwise.

b) For other strata,

Overall estimate of aggregates:

The overall estimate for aggregates for a stratum(

sY

) / sub-stratum ( stY ) based on two sub-samples is obtained as:

Overall estimate of aggregates at the State/UT/all-India level:

The overall estimate Y at the State/ UT/ all-Indialevel is obtained by summing the stratumestimates sY over all strata belonging to the State/UT/ all-India.

The Summary of Findings:

Apart from collection of data on some infratructuralfacilities like nature of availability of electricity, drinkingwater, drainage, irrigation, uses non-conventional energysources for cooking and lighting, village co-operativesociety, self-help group and Government programme/scheme if any, information on the availability of some 36specified facilities was collected; it was recorded whetherthe facility was available within the village; if not, thedistance of the village from the nearest such facility wasalso ascertained.

The group of 36 items formed five sub-groups: (i) general,(ii) education and related facilities, (iii) health facilities,(iv) other facilities and (v) facilities for disabled persons.Information on general facilities related to panchayat,

∑=

=n

yzn

ZY

ii

i1

1ˆ

∑

==

2

1

ˆ2

1ˆm

sms YY for a rural stratum.

SARVEKSHANA94

tehsil or district headquarters, railway station, bus stop,metalled road and all-weather road. Education-relatedfacilities included availability of schools, colleges, traininginstitutes, non-formal education centres, etc. Healthfacilities included dispensaries, primary health centres,hospitals, medicine shops, etc. Other facilities includedchild development service centres, post offices, telegraphoffices, banks, veterinary hospitals/dispensaries, fertilizer/pesticide shops, fair price shops, markets, etc. Facilitiesfor disabled persons included special schools for the blind,the deaf and dumb, and the mentally retarded, integratededucational centres, organizations for the rehabilitationof disabled persons, etc.

1. Availability of electricity

1.1 Information on the availability of electricity tothe villagers was recorded for the sampled villages.Emphasis was given on the purpose for which theelectricity was available. The results of the survey showed( table 2) that by 2002 more than three-fourths (77.6%)of villages in India had the facility of electricity, 100% ofthe surveyed villages getting the facility in twelve States.

Among villages with electricity, 23.6% reported thatelectricity was available for household purposes only2.3% had electricity for street lights only, 2.9% reportedavailability of electricity for agricultural purposes only,and 1.6% reported availability for industrial purposesonly. Finally, nearly 68% of the villages which had thefacility of electricity reported that it was available formore than one purpose.

1.2 The survey results showed that the states ofGujarat, Haryana, Karnataka and Kerala achieved 100%rural electrification and states of Punjab(94.4%),Chhattisgarh(92.3%), Madhya Pradesh(94.2%) andTamil Nadu(92.4%) were very close to achieve that goal.Among the major States and Union Territories theavailability of electricity in few States fell appreciablybelow the all-India average. Noticeable among them wereAssam (55.4%), Bihar (51.8%), Orissa (50.7%) andJharkhand (24.0%)(see Figure 2). With West Bengal andother few states were below the national average in thisrespect, it is seen that the villages of Eastern India lackedthis facility to a very great extent.

Figure-1

Percentage distribution of villages having electricityby purpose: India

SARVEKSHANA 95

Table 2: Number of villages having electricity connection per thousand, and their distribution by purpose ofavailability, for major States

Number of distribution (per 1000) of villages having electricity by purpose ofvillages availability of electricity

having street house- agricul- indus- two or not allState/UT electricity lights hold tural trial more of recor-

per 1000 only use purpose purpose the dedvillages only only only purposes

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Punjab 944 - 63 - 96 840 - 1000Haryana 1000 - 70 - - 930 - 1000Rajasthan 887 3 151 182 26 639 - 1000Uttar Pradesh 834 13 159 52 18 758 - 1000Bihar 518 14 382 50 4 261 289 1000Assam 554 10 787 - 6 196 - 1000West Bengal 737 47 391 16 12 534 - 1000Jharkhand 240 49 500 - - 451 - 1000Orissa 507 25 616 - 14 345 - 1000Chhattisgarh 923 60 485 - - 455 - 1000Madhya Pradesh 942 21 160 19 8 792 - 1000Gujarat 1000 - 137 2 7 854 - 1000Maharashtra 871 23 21 - 14 942 - 1000Andhra Pradesh 780 15 15 - 11 959 - 1000Karnataka 1000 45 5 - 12 938 - 1000Kerala 1000 15 9 7 27 942 - 1000Tamil Nadu 924 67 - 1 61 871 - 1000all-India 776 23 236 29 16 679 16 1000

Figure-2Availability of electricity in the villages of 17 states

SARVEKSHANA96

1.3 The findings of the survey on proportion ofvillages having specific sources of non-conventional

Table 3: per 1000 distribution of villages having non-conventional source of energy.

Number of distribution (per 1000) of villages having non-conventional source ofvillages energy (NCE) by energy source

having bio- solar wind two or Others not AllRural Sector NCE per gas energy energy more of recor-

1000 only only only the forms dedvillages in cols.3-5

(1) (2) (3) (4) (5) (6) (7) (8) (9)

all-India 117 536 173 12 57 113 109 1000

At the all-India level, non-conventional energy was foundto be available in 11.7% of all villages. Among the villagesusing non-conventional energy sources, 53.6% were usingbio-gas only, 17.3% were using solar energy only, 1.2%were using wind energy only, and 5.7% were using morethan one of these sources. 11.3% were using sources ofenergy other than those mentioned above.

2. Source of Drinking Water

2.1 Villages were categorised according to the use of

energy at all India level are shown in the table below(Table 3).

major sources of drinking water. The findings are shownin Table 3. At the all-India level, tube-wells or hand pumpswere the major source of drinking water for 55.1% of allvillages, tap water for 18.5% of the villages, wells for17.6%, springs for 2.9%, rivers/ canals/lakes for 1.9%,tanks or ponds reserved for drinking for 0.8%, and othertanks or ponds for 0.2%. The remaining 1.7% used othersources( figure 3).

Figure-3

All India percentage distribution of villages by major source of drinking water

SARVEKSHANA 97

Table 4: Distribution of villages by major source of drinking water per 1000 villages for each State/UT

distribution (per 1000) of villages by major source of drinking water

State/UT tube- other river/tap well/ well tank/ tank/ canal/ spring others not all

hand pond pond lake recordedpump

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

Punjab 202 786 12 - - - - - 1000

Haryana 525 354 113 8 - - - - - 1000

Rajasthan 186 518 147 84 3 62 - - - 1000

Uttar Pradesh 4 943 53 - - - - - - 1000

Bihar - 647 202 - 1 - - - 150 1000

Assam 60 458 398 3 45 25 11 - - 1000

West Bengal 61 727 207 - - 3 1 - - 1000

Jharkhand 2 292 477 - - 57 - 172 - 1000

Orissa 23 502 220 1 - 9 245 - - 1000

Chhattisgarh 3 903 94 - - - - - - 1000

Madhya Pradesh 39 595 348 - - 18 - - - 1000

Gujarat 354 524 110 11 - - - - - 1000

Maharashtra 449 266 179 - - 102 - 4 - 1000

Andhra Pradesh 468 314 78 1 2 4 39 94 - 1000

Karnataka 479 451 70 - - - - - - 1000

Kerala 112 10 855 - - - 23 - - 1000

Tamil Nadu 706 107 99 52 - 34 - 3 - 1000

All-India 185 551 176 8 2 19 29 17 13 1000

2.2 Among the major States, Tamil Nadu had by farthe highest proportion (over 70%) of villages using tapwater for drinking. Haryana had 52% and for Karnataka,Andhra Pradesh and Maharashtra the use of tap waterranged between 44% to 48%. Wells were the major sourcein 85% of Kerala’s villages, 48% of Jharkhand’s, and40% of Assam’s. In all major States other than thosementioned above, and also in Assam, tube-wells and hand-pumps were the most prevalent source of drinking water.River/canal/lake was found to be the major source in asmany as 10% of villages in Maharashtra.

3. Drainage system

3.1 The survey results show (Table 5) that thedrainage facility in the villages of India remained

inadequate. Only 30% of the villages in India had adrainage system. Amongst the villages having this facility43.0% had the open katcha drainage system, 50.4% hadthe open pucca type, 1.7% had the covered pucca type,and only 0.6% had the underground type.

3.2 Excepting Punjab and Haryana, where 85-86%of the villages had a drainage system (mainly the openpucca type), the proportion of villages having any kindof a drainage system was less than 60% in all major States.Though 58% of Karnataka’s and 46% of Bihar’s villageshad a drainage system, the majority of these were of theopen katcha type. However, the majority of the drainagesystems available in Maharashtra’s and Andhra Pradesh’svillages belonged to the open pucca variety.

SARVEKSHANA98

Table 5: Number of villages having drainage system per 1000 villages, and their distribution by type ofdrainage system for each State/UT

State/UT number of distribution (per 1000) of villages having drainage systemvillages having by type of drainage system

drainagesystem per under- covered open open not all

1000 villages ground pucca pucca katcha recorded

(1) (2) (3) (4) (5) (6) (7) (8)

Punjab 854 3 14 831 153 - 1000

Haryana 864 12 11 829 148 - 1000

Rajasthan 107 - - 753 247 - 1000

Uttar Pradesh 390 9 17 524 450 - 1000

Bihar 458 1 35 248 389 327 1000

Assam 326 - 10 - 985 6 1000

West Bengal 144 4 65 167 765 - 1000

Jharkhand 117 - 10 304 685 - 1000

Orissa 40 - 61 730 209 - 1000

Chhattisgarh 93 - 10 349 641 - 1000

Madhya Pradesh 133 14 - 511 475 - 1000

Gujarat 107 193 126 289 392 - 1000

Maharashtra 537 1 - 838 161 - 1000

Andhra Pradesh 464 2 8 734 257 - 1000

Karnataka 584 - 18 417 565 - 1000

Kerala 215 - - 350 650 - 1000

Tamil Nadu 350 - 8 591 401 - 1000

all-India 300 6 17 504 430 43 1000

4. Availability and source of irrigation

4.1 Information was collected on the main sourcesof irrigation in the villages with land used for agriculturalpurposes. The results (Table 6) show that some sourceof irrigation was available to 76.2% of Indian villages

where agriculture was practised. Among these villages,canals served as the main irrigation source for 17.3%,wells for 16.2%, tube-wells for 48.1%, streams/riversfor 7.4%, tanks/ponds for 5.6%, and 3.7% were servedby other sources.

SARVEKSHANA 99

Figure-4

Percentage distribution of villages having irrigation facility by type of facility : India

Table 6: Number of villages having irrigation facility per 1000 villages, and their distribution by type ofsuch facility for each State/UT

State/UT number of distribution* (per 1000) of villages having irrigation facility by type

villages having of irrigation facility

irrigation not

facility per canal tubewell stream/ tank/ well others recor- all

1000 villages river pond ded

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Punjab 976 70 900 - 7 23 - - 1000

Haryana 979 159 797 31 - 13 - - 1000

Rajasthan 893 165 485 13 12 309 16 - 1000

Uttar Pradesh 987 152 810 5 3 22 9 - 1000

Bihar 895 101 614 72 12 4 30 167 1000

West Bengal 845 160 371 90 116 62 192 9 1000

Jharkhand 352 108 38 114 209 503 28 - 1000

Orissa 281 561 88 148 67 - 137 - 1000

Chhattisgarh 652 410 291 70 91 74 64 - 1000

Madhya Pradesh 925 74 376 141 37 366 5 - 1000

Gujarat 891 123 451 - 5 421 - - 1000

Maharashtra 804 113 76 173 30 580 28 - 1000

Andhra Pradesh 796 232 349 76 219 62 63 - 1000

Karnataka 829 141 492 61 183 97 26 - 1000

Kerala 840 395 59 152 115 242 37 - 1000

Tamil Nadu 879 211 122 21 293 348 3 - 1000

All-India 762 173 481 74 56 162 37 17 1000

SARVEKSHANA100

4.2 Except for Assam, (20%), Orissa (28%) andJharkhand (35%), all major States had over 70% ofvillages reporting availability of irrigation facility. Themajor source of irrigation, however, differed widely fromState to State. Canals were the most common source inOrissa, Kerala and Assam. Wells were the major source

Figure-5

Percentage of villages having irrigation facility

in Maharashtra, Jharkhand and Tamil Nadu, and closelyfollowed tube-wells in Gujarat and Madhya Pradesh.Tube-wells were the most prevalent source in all othermajor States. Streams or rivers were the major source inmany of the North-Eastern States(Figure 5).

Table 7: Number of villages (per 1000) having facilities of Television, co-operative society and self-helpgroup in each State/UT

number of villages (per 1000) having

State/UT community TV cable TV cooperative self-helpcentre connection society group

(1) (2) (3) (4) (5)

Punjab 24 253 507 78Haryana 139 230 627 233Rajasthan 1 58 301 124Uttar Pradesh 1 21 209 207Bihar 1 21 128 54Assam 17 34 197 177West Bengal 86 145 385 232Jharkhand 1 18 46 48Orissa 10 70 79 106Chhattisgarh 31 122 399 276Madhya Pradesh 45 131 350 267Gujarat 179 324 481 134Maharashtra 98 187 573 431Andhra Pradesh 80 641 424 740Karnataka 87 529 425 357Kerala 416 853 859 800Tamil Nadu 823 770 538 697

all-India 65 164 302 240

SARVEKSHANA 101

5. Availability of TV connectivity,cooperative society and self-help group

5.1 The number of villages having the facility ofcommunity TV centre per 1000 villages is shown,Statewise, in column 2 of Table 7. At the all-India levelonly 65 per 1000 villages were found to have this facility.The major State with the highest percentage of suchvillages was Tamil Nadu (82%), followed by Kerala(41%) and Gujarat (18%). In all the other major Statesthe proportion was below 10%.

5.2 The survey indicated that at the all-India levelaround 30% of villages had co-operative societies. Thefacility was available in fewer than 5% of the villages ofJharkhand, and only 8% of the villages of Orissa. Amongthe major States, the one with the highest percentage ofvillages with cooperative societies was Kerala (86%),followed by Haryana (63%), Maharashtra (57%) andTamil Nadu (54%).

5.3 At the all-India level the overall percentage ofvillages having any self-help group(column 5 of Table 7)

was 20.4. All the States of India had self-help groups inat least 10% of their villages except for Jharkhand, Biharand Punjab. Kerala (80%), Andhra Pradesh (74%) andTamil Nadu (70%) had the highest percentages of villageswith this facility (see Figure 6).

6. Coverage of Government developmentprogrammes

6.1 The survey attempted to gauge the extent to whichIndia’s villages had actually been reached by certaincategories of development programmes of theGovernment. The programmes considered in the surveyrelated to drinking water, housing, sanitation, approachroad, employment, pension, electricity, watershed/ minorirrigation and total literacy/ adult education. If thevillagers were found to be getting any assistance fromthe Government through such a programme, then thevillage was considered to have been covered by theprogramme.

6.2 Table 8 gives the findings of the survey onavailability of government development programmes/

Figure-6

Percentage of villages having co-operative society and self help group

SARVEKSHANA102

schemes per thousand villages in each State/UnionTerritory. At the all-India level, it is seen that among thedifferent categories of government developmentalprogrammes, programmes relating to pension had reachedthe highest number of villages (70.5%), followed by thoserelating to drinking water (62.8%), housing (59.8%) andapproach road (57.1%). It is observed that theprogrammes relating to sanitation and watershed/irrigation have not received much attention as revealedby the number of villages covered (18-19%).

6.3 Schemes relating to drinking water wereestimated to cover more than 50% of villages in mostmajor States but less than 30% in Punjab. In case ofschemes for sanitation, only a few major States, viz.,Kerala, West Bengal, Andhra Pradesh, Tamil Nadu andMaharashtra, reported coverage of more than 35% oftheir villages (the national average being 19%). The

coverage of schemes relating to approach road showedlittle inter-State variation. Only two major States – Keralaand Andhra Pradesh – reported coverage of more than50% of their villages by employment generation schemes(the national average being 36.5%). More than 60% ofthe villages of nearly every major State were covered bypension schemes. Fewer than 17% of the villages ofJharkhand and only 28% of those of Bihar and Rajasthanwere covered by schemes for provision of electricity, thenational average being 45%. In Jharkhand, Assam,Rajasthan and Bihar, fewer than 10% of villages werecovered by watershed or minor irrigation programmes.In Kerala the coverage was over 80% in the case of sevenof the nine types of development programmes consideredby the survey. Andhra Pradesh was the next best Statewith coverage exceeding 37% of villages for all theprogrammes and Maharashtra and Tamil Nadu alsoperformed nearly as well.

Table 8: Number of villages (per 1000) having different government development programmes/ schemes ineach State/UT

number of villages per 1000 having government development programmes relating to

State/UT drinking housing sani- approach employ- pension electri- watershed/ literacywater tation road ment city minor campaign/

irrigation education

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Punjab 289 271 230 416 90 895 406 30 108Haryana 810 679 306 851 575 991 430 335 139Rajasthan 536 547 67 519 426 781 282 92 361Uttar Pradesh 753 542 231 606 405 604 352 202 195Bihar 527 529 58 420 208 591 279 98 232Assam 505 604 38 540 299 626 425 48 508West Bengal 669 773 446 640 453 735 509 222 615Jharkhand 428 491 38 419 145 405 165 23 95Orissa 671 737 68 563 446 807 337 127 191Chhatisgarh 940 879 33 715 491 944 851 268 315Madhya Pradesh 474 559 133 543 402 855 566 270 589Gujarat 684 594 48 699 326 554 546 124 154Maharashtra 687 726 370 704 385 749 599 303 333Andhra Pradesh 601 651 416 615 599 938 564 371 486Karnataka 699 740 208 561 247 711 803 163 331Kerala 863 958 872 972 648 963 806 447 821Tamil Nadu 744 663 379 675 357 793 685 326 160

all-India 628 598 188 571 365 705 449 184 306

SARVEKSHANA 103

Figure-7

Existence of literacy campaign/adult education programme in villages of 19 states in India

Among the different Government DevelopmentalPrograms the Literacy /Adult education programs havebeen studied. The highest percentage of villages wheresuch programs had been continuing was Kerala(82%),followed by west Bengal(62%) and MadhyaPradesh(59%). Lower activity was observed inJharkhand(10%), Punjab(11%), Hariyana(14%) andGujarat(15%)( see Figure 7).

7. Distance to travel by Indian villagers toavail various facilities:

7.1 Proximity to bus stops, railway stations, PCOs,post offices, banks, markets, etc.

7.1.1 Various distance statistics had been collectedduring 58th round. These covers from “general” facilitieslike distance from various: panchayat/ tehsil/ districtheadquarters, railway stations, bus stops, metalled roads,all-weather roads, post offices, telegraph offices/ PublicCall Offices/ e-mail facilities, banks, veterinary shops/dispensaries, fertilizer/ pesticide shops, fair-price shops,and markets/ weekly markets. Table 9 gives per 1000distribution of villages in India by distance from various“general” facilities.

SARVEKSHANA104

Table 9: Per 1000 distribution of villages by their distance from the nearest available facility for differentgeneral facilities

all-India

location of facility

outside village and at a distance of

facility within less 2 km to 5 km to 10 km not Allvillage than 2 less than less than or more recorded

km 5 km 10 km

(1) (2) (3) (4) (5) (6) (7) (8)

1. panchayat 302 229 267 86 102 14 1000headquarters

2. tehsil headquarters 5 16 79 180 706 13 1000

3. district headquarters - 3 11 34 940 13 1000

4. railway station 12 23 83 128 742 13 1000

5. bus stop 305 171 244 150 116 13 1000

6. metal road 446 160 191 89 99 13 1000

7. all-weather road 574 135 162 57 59 13 1000

8. post office 216 258 354 104 42 26 1000

9. telegraph office/ 196 141 255 143 250 15 1000PCO/e-mail services

10. bank 66 117 336 236 232 13 1000

11. veterinary hospital/ 81 111 299 223 273 13 1000dispensary

12. fertilizer/ pesticide 133 147 276 203 228 14 1000shop

13. fair price shop 431 218 223 77 37 15 1000

14. market/weeklymarket 110 148 323 188 217 14 1000

7.2 Proximity to schools, hospitals, etc.

7.2.1 The findings of the survey on availability ofeducational and health care facilities at all India level are

presented in table 10 below. Nearly two-thirds of thevillages of India had pre-primary schooling facilities and72% had primary school facilities during the period ofsurvey.

SARVEKSHANA 105

Table 10: Distribution of villages (per 1000) by their distance from the nearest education- and health-relatedfacilities

all-India

location of facility

outside village but at a distance of

facility within less 2 km to 5 km to 10 km not allvillage than 2 less than less than or more recorded

km 5 km 10 km

(1) (2) (3) (4) (5) (6) (7) (8)

educational

1. pre-primary school 665 143 47 14 115 17 1000

2. Primary 723 162 62 15 25 14 1000

3. middle school 289 216 351 78 53 13 1000

4. secondary school 119 145 385 200 138 13 1000

5. Higher secondary/ 41 83 249 247 367 14 1000college

6. college with degree 6 16 78 161 727 13 1000course

7. Industrial Training 3 7 30 66 880 14 1000Institute (ITI)

8. Non-formal Education 68 21 51 55 789 17 1000Centre (NFEC)

health

1. Integrated Child 548 113 140 59 125 15 1000Development ServiceCentre (ICDSC)(anganwadi)

2. sub-centre/ dispensary 163 160 318 189 156 15 1000

3. primary health centre 65 101 278 268 273 14 1000

4. community/ government 18 37 155 222 553 15 1000hospital

5. private hospital 19 38 133 181 614 14 1000

6. private clinic/doctor 201 126 246 200 214 13 1000

7. Medicine shop 103 132 271 217 264 13 1000

7.2.2 The survey found that inhabitants as many as 34%of all villages had to travel more than 5 km to travel tothe nearest sub-centre/ dispensary, the most peripheralcontact point in the Government’s primary health caresystem. For 55% of Indian villages, the nearest communityhealth centre/ government hospital was more than 10 km

away. Private hospitals were equally scarce, the nearestone being more than 10 km away for 61% of the villages.The private clinic or doctor was however, more readilyavailable. Finally, that essential ingredient of urban life,the medicine shop, selling medicines of any kind –allopathic, homeopathic, ayurvedic or unani – was found

SARVEKSHANA106

to exist in only 10% of India’s villages. Among otherhealth-related facilities, the integrated child developmentcentre (balwadi/ anganwadi) was found in course of thesurvey to be available in 55% of India’s villages.

7.3 Facilities for the disabled

7.3.1 The survey results on facilities for the disabledare presented at all-India level are shown in Table 11.Information was collected during the survey on theavailability of the following facilities for the disabled:integrated education centre, special school for the blind,special school for the deaf. The picture of facilities fordisabled person is very dismal. Only 4% villages hadintegrated education centres and the remaining schools/institutions for the disabled were found to be beyond 10

Table 11: Distribution of villages per 1000 by their distance from the nearest facility for disabled persons

all-India

location of facility

outside village but at a distance of

facility within less 2 km to 5 km to 10 km not allvillage than 2 less than less than or more recorded

km 5 km 10 km

(1) (2) (3) (4) (5) (6) (7) (8)

1. integrated education 41 38 17 32 854 17 1000center

2. special school for blind - 2 5 18 959 16 1000

3. special school for deaf 1 2 6 20 956 16 1000& dumb

4. special school for 1 1 5 13 967 15 1000mentally retarded

5. vocational training 2 3 17 33 931 14 1000center

6. institution/organization 1 2 6 16 959 16 1000for rehabilitation ofdisabled persons

number of villagesper 1000 to which : 23mobile rehabilitationservices available

km of 93-95% of the country’s villages. Mobilerehabilitation services were found to be available to only2% of all villages.

8. State wise comparison on availability ofvarious facilities within the village:

8.1 The table 12 gives a comprehensive picture ofthe villages of 17 major states in regard to the facilities:“general”, “educational”, “health related” and “facilitiesfor disabled” available within the villages. About 96% ofall Kerala panchayat wards were connected with busroute. 98% of rural roads of Haryana were metalled and99% of roads of Haryana and Kerala villages were allweather road. About 50% of Andhra Pradesh villageshad Post office within. Kerala had unique distinction of

SARVEKSHANA 107

highest percentage of villages having PCO and E-mailfacilities(52%), banks(37%), pesticide shops(38%) andweekly market(50%) where as, Haryana had highestpercentage of villages having veterinary hospitals(37%)and fair price shop(90%).

8.2 The state of Maharastra and Haryana were wayahead as far as basic educational facilities were concerned.Both pre-primary(96%) and primary(99%) educationalfacilities were available in villages of Maharastra.Haryana had highest villages having middle

schools(63%), secondary schools(35%) and highersecondary schools(12%) within the villages.

8.3 In providing health facilities the state of Karalahad integrated child development center in 99% villages,private hospitals in 14% and medicine shops in 41%villages. The state of Rajasthan had highest percentageof villages having primary health center(27%) and sub-centre(56%) in the country. However, the facilitiesprovided to disabled persons in the rural area of thecountry were as poor as ever.

SARVEKSHANA108

Tab

le 1

2 :

Per

thou

sand

dis

trib

utio

n of

vill

ages

whi

ch h

ad v

ario

us fa

cilit

y av

aila

ble

wit

hin

the

villa

ges

for

17 m

ajor

sta

tes

Raj

as-

Utt

arW

est

Jhar

-C

hhat

-M

adhy

aM

aha-

And

hra

Kar

na-

Tam

ilA

llFa

cili

ties

Pun

jab

Har

yana

than

Pra

desh

Bih

arA

ssam

Ben

gal

khan

dO

riss

ais

garh

Pra

desh

Guj

arat

rast

raP

rade

shta

kaK

eral

aN

adu

Indi

a

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

(19)

Gen

eral

faci

liti

es:

panc

haya

t55

871

022

530

816

251

9996

155

523

351

596

446

706

219

141

611

302

head

quar

ters

tehs

il1

02

06

715

152

53

43

331

34

5he

adqu

arte

rs

dist

rict

00

00

00

11

03

00

00

00

00

head

quar

ters

rail

way

sta

tion

2523

358

121

1012

31

1120

2018

89

1212

bus

stop

442

694

485

102

120

153

182

210

101

231

218

762

520

648

471

964

780

305

met

alle

d ro

ad81

198

059

046

922

120

429

225

131

532

321

079

069

368

054

097

287

644

6

all

wea

ther

roa

d78

599

374

657

635

736

971

135

847

654

744

778

174

065

760

699

385

257

4

post

off

ice

269

382

236

136

149

104

234

120

162

143

156

358

311

503

319

476

452

216

tele

grap

h of

fice

/28

134

627

216

718

933

241

148

135

139

194

168

155

315

194

518

453

196

PCO

/ e

-mai

l

bank

9412

671

3333

989

7736

4539

8811

511

589

371

173

66

vete

rina

ry22

237

067

3814

1183

1548

7867

5612

823

113

517

617

781

hosp

ital

/di

spen

sary

fert

iliz

er /

159

182

9710

912

758

267

110

9980

6818

218

917

912

338

625

213

3pe

stic

ide

shop

fair

pri

ce s

hop

544

899

311

429

390

551

356

315

272

361

226

443

681

704

443

807

801

431

mar

ket/

wee

kly

4276

7111

910

556

182

7967

230

4346

124

129

5849

724

711

0m

arke

t

SARVEKSHANA 109

Tab

le 1

2 :

Per

thou

sand

dis

trib

utio

n of

vill

ages

whi

ch h

ad v

ario

us fa

cilit

y av

aila

ble

wit

hin

the

villa

ges

for

17 m

ajor

sta

tes

Raj

as-

Utt

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est

Jhar

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hhat

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adhy

aM

aha-

And

hra

Kar

na-

Tam

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llFa

cili

ties

Pun

jab

Har

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than

Pra

desh

Bih

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ssam

Ben

gal

khan

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ais

garh

Pra

desh

Guj

arat

rast

raP

rade

shta

kaK

eral

aN

adu

Indi

a

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

(19)

Edu

cati

onal

faci

liti

es

pre-

prim

ary

785

874

776

545

449

709

747

526

615

710

728

758

958

696

741

809

791

665

scho

ols

prim

ary

scho

ols

838

945

896

602

506

741

763

462

648

927

846

771

987

827

743

684

826

723

mid

dle

scho

ols

349

628

305

185

147

269

196

185

308

296

276

392

452

456

475

385

354

289

seco

ndar

y21

835

412

261

5282

133

6814

271

5117

424

623

716

620

215

611

9sc

hool

s

high

er s

econ

dary

8112

443

466

2757

1412

4832

5357

4532

116

7241

scho

ols/

juni

orco

lleg

e

coll

age

wit

h2

32

21

106

910

71

1912

1511

124

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SARVEKSHANA110

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SARVEKSHANA 111

An Integrated Summary of NSS-58th Round (July 2002 - December 2002)Survey Results on "Conditions of Urban Slum"

Tapas Kumar Sanyal & Nilanjana Roy

1. Introduction

1.1. Slums are usually characterized by urban blightand by high rates of poverty and unemployment. Theytend to be breeding centers for many social problems suchas crime, drug addiction, alcoholism, high rates of mentalillness and despair. In many poor countries they exhibithigh rates of disease due to unsanitary conditions,malnutrition, and lack of basic health care. Therefore itis important to monitor the improvement of slum areasover the years.

1.2. The first nation-wide survey on the “EconomicCondition of Slum Dwellers in Urban Cities” wasconducted by NSSO in its 31st round (July 1976 - June1977). The survey was restricted to (i) all the class - Icities having 1971 census population one lakh or more(ii) two class - II cities viz. Shillong and Pondicherryhaving 1971 census population less than one lakh .Onlythe cities proper and not the urban agglomerations wereconsidered for the survey coverage .The survey resultswere published in NSS Report No. 290: Condition ofSlum Areas in Cities. The next survey on “Particulars ofSlums” was carried out in 49th round (January – June1993), which covered 1572 slums spread over 5072villages as well as 2928 urban blocks. After a gap ofnearly ten years, the third survey in this series wasconducted in the 58th round (July – December, 2002).Since slum is mainly an urban concept, it was decided to

cover only urban slums in this round.

1.3. For the purpose of this survey, slum was dividedinto two categories- notified and non-notified. A non-notified slum was defined as a compact area within theFirst Stage Unit (urban frame survey blocks) with acollection of poorly built tenements, mostly of temporary

nature, crowded together, usually with inadequate sanitaryand drinking water facilities in unhygienic conditions.Such an area was considered as a slum only if at least 20households lived in that area. Notified slums were thoseurban areas, which were notified (recognised) byrespective municipalities, corporations, local bodies ordevelopment authorities as slums. Slum dwellings haveseveral names in local language like ‘Jhopad Patti’ inMumbai, ‘Jhuggi Jhopri’ in Delhi and ‘Basti’ in Kolkataetc.

1.4. The main aim of the survey on slums was toportray the infrastructure facilities available to the urbanslums of India, like the ownership type of the area wherethe slum was located, condition of road within andapproaching the slum, availability of electricity, drinkingwater, sewerage, garbage disposal etc.

1.5. Geographical Coverage and Sample Design

1.5.1 The survey covered all the urban areas(recognised by 1991 census) of whole of Indian Union

except Leh and Kargil districts of Jammu & Kashmir.

1.5.2. A stratified sampling design was adopted forselection of the sample first-stage units (FSUs). TheFSUs, for this survey were Urban Frame Survey (UFS)blocks in urban areas. Each slum, notified or non-notified,found in the entire selected first stage units (FSUs) wasenumerated. In some cases, area of a slum was very largeand the selected FSU was part of the slum. In such cases,information was collected for the slum area falling underthe sample FSU only. However, if the slum was notified,then the part of it falling under the sample FSU was

considered as a notified slum.

SARVEKSHANA112

1.6. Sample Size

1.6.1 Total of 3552 urban FSUs (i.e., UFS blocks) wereselected for this survey, of which 3538 could be surveyed.At all-India level, a total of 692 slums were covered inthese surveyed urban blocks. Total number of notifiedslums surveyed was 360; for non-notified slums thenumber was 332. However, the results at the State/UTlevel have been confined to those States/UTs wherenumber of sample slums was ten or more, although theall-India level estimates are based on all the surveyedslums of all the states.

1.7 Period of survey and work programme

1.7.1 The entire survey period (1st July 2002 - 31st

December 2002) was divided into two sub-rounds of threemonths each (Sub-round 1: July-September 2002, Sub-round 2: October-December 2002) and an equal numberof sample blocks were allocated to each sub-round. EachFSU was surveyed during the sub-round period to whichit was allocated. Within a particular sub-round, thefieldwork was spread uniformly over the different monthsto the extent possible.

1.8 Lay-out

1.8.1 This integrated summary deals with estimates of

different parameters regarding the “Conditions of urbanslums” in India, based on the data collected through 58th

round on “Condition of urban slum” (Sch 0.21).Subsection 2 gives the summary of findings of the survey.All the summary results for state/UT are given inAnnexure-I.

2 Summary of findings

2.1 As per the survey results, about 52 thousandslums were scattered in the urban areas in India duringthe second half of 2002. Nearly 14 per cent (8 million)of the urban households were slum-dwellers.

A little more than half (51%) of the slums were notifiedby the respective municipalities, corporations, local bodiesor development authorities but they shared a relativelylarger portion (65%) of slum households implying thatthe notified slums were larger in size as compared to thenon-notified ones. Statement 1 provides the changes indistribution of households in notified and non-notifiedslums over last two rounds.

2.2 If state-wise distribution of slum households istaken into consideration (vide Table 1), percentage ofslums was highest in Maharashtra(32%) followed byWest Bengal (16 per cent) and Andhra Pradesh (15 percent).

Statement 1: - Percentage of notified and non-notified slums and percentage of households living in those slums

proportion of proportion ofslums households living in

Round non-notified non-notified Notified notified

slums slums

49th (Jan-Jun,1993) 36 64 44 56

58th (Jul-Dec, 2002) 51 49 65 35

Source: Table 1 in Annexure I & NSS Report No. 417

SARVEKSHANA 113

2.3 On an average, 159 households were living in anurban slum (see Table 1). Irrespective of the total areaof a slum, density of notified slum (average 205households) was more than that of non-notified slums

Chart 1 : Ownership among various public land owner authorities

Source : Table 2 in Annexure I

2.4 The type of a structure in a slum was classifiedinto three categories, viz., ‘pucca’, ‘semi-pucca’ and‘kutcha’. A pucca structure was one whose walls androofs were made of pucca materials whereas in case ofkatcha structure the material of roof and wall were katcha.A structure, which does not fall under any of these twocategories, was considered as semi-pucca. According to31st round result, percentages of slum dwellers residingin houses with pucca wall were 49.4% in 8 million pluscities and 34.8% in rest of 142 cities. During 49th and

(average 112 households). Around 65% of both notifiedand non-notified slums were located in public land (seeTable 2). Chart 1 further looks into the ownership patternof public land occupied by the slums.

58th rounds information on the type of structure of thehouses was not collected separately for each house in theselected slums but a question was put to the informantsregarding the type of structure of majority of the houses.About 30% of non-notified slums had majority of puccahouses. The said percentage was further higher in thecase of notified slums (64%) in 58th round (see Table 3).Chart 2 provides the graphical presentation of type ofstructure in both notified and non-notified slums in 58th

round.

Chart 2 : Type of structure of majority of houses in the slum

Source : Table 3 in Annexure I

SARVEKSHANA114

2.5 Supply of safe drinking water to all had been oneof the commitments in several five-year plans. In 1993(NSS 49th round survey), about 92% of the urban slumsin the country reported ‘tap’ and ‘tube-well’ as the majorsources of drinking water and the situation improvedslightly (93%) over the period of nearly ten years sincethen. However, a larger number of slums got the privilegeof having drinking water from tap (84 per cent for notifiedslums and 71 per cent for non-notified slums). Statement2 provides information regarding percentage of differentsources of drinking water for both notified and non-notified slums in the current round. It is worth mentioningthat around 93% of the slum population in 8 million pluscities during 31st round also had the facility of fetchingdrinking water from tap or tube-well.

Statement 2: Percentage distribution of sourcesof drinking water

Source Notified Non-slum slumnotified

Tap 84 71

Tube-well 10 22

Well 2 2

Others 4 5

Source: Table 4 in Annexure I

2.6 Electrification of the slums is done for household,street and both. In case of some slums, streetlight wasavailable only in some locations inside or at the boundaryof the slums. For the purpose of this survey those slumswere also counted as electrified slums. It was found thatelectricity connection was not at all available in only 1per cent of the notified slums and about 16 per cent ofthe non-notified slums (Details in Statement 3). In 1993,about 75 per cent of slums were having electricity. Around81 percent of slum population in million plus cities hadelectricity connection during 1976-77 (31st round).

Statement 3: Percentage distribution of electricconnection in slums

Non-Stages of Notified notifiedelectrification slum slum

Households only 84 53

Households and streets 11 25

Streets only 4 6

No connection 1 16

2.7 Information on the structure of the roads withinthe slums was collected in the present survey. About 71per cent of the notified slums and 37 per cent of the non-notified slums were reported to have pucca roads withinthe slums. This apart, proportion of slums with puccaapproach road to the slum was observed to be 86 percent for the notified slums and 67 per cent for the non-notified slums. The urban slums in many states, viz.,Rajasthan, Punjab, Bihar and Orissa, were largelydeprived of this facility. (Source: NSS Report NO. 486,Tables 9 & 10)

2.8 Waterlogging on roads inside the slum is a majorthreat to health of the slum dwellers. In the present round,in addition to information on waterlogging on roads insidethe slum, data on waterlogging on the approach road tothe slum were also collected. Slums for whichwaterlogging either on the roads within the slum or onthe approach road to the slum was reported, wereclassified as affected by waterlogging. Around 36% ofthe notified slums and 54% of the non-notified slums werefacing problem of waterlogging till the survey period.Previous surveys portray similar pictures. 60% of urbanslums in 1993 were waterlogged in monsoon whereas 65%of the slum population in million plus cities in 1976-77faced the same situation. (Source: NSS Report NO. 486,

Table 20; NSS Report NO. 417)

SARVEKSHANA 115

2.9 In case of latrine facility of the slums, thecondition has improved significantly over time. Only 17% of slums were not having any latrine facility in notifiedslums and the corresponding figure is 51% in non-notifiedslums in 2002. Worst case is Orissa where none of theslums had any latrine facility even in 2002. (Source: NSSReport NO. 486, Table 11)

2.10 Sewerage system and garbage disposal facilitiesare major parameters of judgment regarding hygiene ofslum dwellers. 31st round showed a huge difference insewerage facilities. 45% of the slum-dwellers in millionplus cities got the facility of underground sewerage systemwhereas only 5% slum population in smaller cities (lessthan 1 lakh population) got the same. As the 49th roundsurvey had shown in 1993, there was underground

sewerage system in 17 per cent of the urban slums andno drainage facility in 30 per cent of slums. Since then,the picture in this respect has improved according to thedata collected in the second half of 2002. About 30 percent and 15 per cent of the notified and non-notified slumsrespectively were estimated to have underground seweragesystem in 2002 (see Table 7).

2.11 Chart 3 gives the percentage distribution of slumsby type of garbage disposal agency separately for thenotified and non-notified slums in 58th round. Chart 4gives the percentage of slums having garbage collectedat least once in 7 days among slums having facility ofgarbage disposal. 49th round showed a very bleak picturein this regard with only 17% urban slums havingunderground sewerage system.

Chart 3 : Percentage distribution of slums by agency of garbage collection

Source : Table 6 in Annexure I

Chart 4 : Frequency of garbage collection in slums having arrangement of garbage collection

Source : NSS Report No. 486 (Table 21)

SARVEKSHANA116

2.12 In respect of availability of educational and healthfacilities, the slums did not reveal much distinctivefeatures from other urban areas and reflected more orless common urban features. About 92% of the slumswere found to have at least one primary school locatedwithin 1 km. The corresponding number in 1993 was ofthe same order (90%). Government hospitals wereavailable within 1 km. of 47% of slums in 2002 whereasit was 64% in case of urban slums in 1993.

2.13 Information was collected regardingimprovement/ deterioration of slum area as viewed bythe slum-dwellers. Therefore, the views were summarisedin Statements 4 and 6. As expected, the improvements inthe notified slums were faster than the non-notified one(see Statement 4).

Statement 4: Percentage of slums reportingimprovement of facilities duringlast 5 years

Facility Notified Non- notified

WithinRoad slum 53 21

Approach 51 40

Water supply 48 32

Electricity 35 27

Street light 39 23

Latrine 50 33

Drainage 47 23

Sewerage 24 6

Garbage 41 15

Source: NSS Report NO. 486 (Statement 15)

2.14 Statement 5 gives percentage of slums reportingimprovement of facilities during last 5 years by sourceof improvement It appears that Government had played

major role in improvement of facilities in the slumsirrespective of whether it is a notified or non-notified.The contribution of residents was also significant inproviding the facilities of latrine, drainage and seweragesystem. NGOs had also contributed to the overallimprovement of slums particularly in respect of drainage,sewerage, garbage disposal.

Statement 5: Percentage of slums reportingimprovement of facilities duringlast 5 years by source ofimprovement

Facility Govt. NGO Residents& others

Roadwithin 94 1 5slum

Approachroad to the 94 4 2slum

Water 93 1 6supply

Electricity 90 2 8

Street light 97 2 1

Latrine 77 7 16

Drainage 85 5 10

Sewerage 91 2 7

Garbage 95 4 1

(Reference Tables 31-39, NSS Report NO. 486)

2.15 Statement 6 presents a summary of informationregarding any deterioration in the availability of facilitiesduring the last five years as revealed from the datacollected. None of the percentages appears to beworrisome with respect to both notified and non-notifiedslums.

SARVEKSHANA 117

Statement 6: Percentage of slums reportingdeterioration of facilities duringlast 5 years

Facility Notified Non- notified

WithinRoad slum 3 13

Approach 3 3

Water supply 4 6

Electricity 1 3

Street light 1 3

Latrine 3 5

Drainage 3 11

Sewerage 5 6

Garbage 4 8

Source: NSS Report NO. 486(Statement 17)

Conclusion:

2.16 The survey revealed that the “conditions of urban

slums” had improved over the years in respect of safedrinking water, latrine facility, sewerage system, garbagedisposal, electricity connection etc. mainly with theintervention of the government. But as the survey hadrevealed the slums in certain states did lack certain basicfacilities, urgent intervention of government and otheragencies are required to bring about improvement in the

condition of the slums in those areas.

References:

1. National Sample Survey Organisation, Govt.of India (2003) : Report No. 486:Conditionsof Urban Slum: Salient Features, NSS 58th

Round (July-Dec, 2002)

2. National Sample Survey Organisation, Govt.of India (1997): Report No. 417: Slums inIndia, NSS 49th Round (January – June, 1993)

3. National Sample Survey Organisation, Govt.of India : Survey Results of NSS 31st round:Sarvekshana Vol III No. 4 April 1980

SARVEKSHANA118

SARVEKSHANA 119

Annexure - I

TABLESOF

INTEGRATED SUMMARY OFNSS FIFTY-EIGHTH ROUND (JULY - DECEMBER 2002)

ONCONDITIONS OF URBAN SLUMS

SARVEKSHANA120 Annex-I

List of Tables

Table no. Description

1 Estimated number of slums and estimated approximate number of households for each State/UT

2 Per 1000 distribution of slums by type of ownership of the land where the slum is located for

each State/UT

3 Per 1000 distribution of slums by type of structure of the majority of houses in slums for each

State/UT

4 Per 1000 distribution of slums by major source of drinking water for each State/UT

5 Per 1000 distribution of slums by status of electricity connection for each State/UT

6 Per 1000 distribution of slums by arrangement of garbage disposal for each State/UT

7 Per 1000 distribution of slums by availability of underground sewerage system for each State/UT

8 Per 1000 distribution of slums by distance from nearest primary school for each State/UT

9 Per 1000 distribution of slums by distance from nearest government hospital / health centre for

each State/UT

SARVEKSHANA 121

Table 1: Estimated number of slums and estimated approximate number of households for each

State/UT

estimated

State/UT number of slums approximate number of households number of sample slums

in

notified non all notified non-notified all notified non all

notified slums slums notified

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Jammu & Kashmir 219 145 364 9466 6414 15880 9 7 16

Punjab 52 104 157 6772 2190 8962 16 2 18

Delhi 169 1678 1847 43438 168861 212299 2 20 22

Rajasthan 12 862 874 1260 55600 56860 3 9 12

Uttar Pradesh 775 1868 2643 115162 112637 227799 15 20 35

Bihar 349 977 1326 26194 43168 69363 3 8 11

West Bengal 2871 5253 8125 797946 732975 1530920 38 56 94

Orissa 11 390 401 2585 15623 18208 1 12 13

Chhattisgarh 501 743 1244 51531 58371 109902 4 6 10

Madhya Pradesh 1530 691 2222 202540 105598 308138 23 14 37

Gujarat 413 1120 1532 61114 96749 157863 12 31 43

Maharashtra 10189 6472 16662 2377546 805030 3182576 113 60 173

Andhra Pradesh 6384 1340 7724 961541 167833 1129374 62 13 75

Karnataka 1178 805 1983 317454 166374 483828 17 12 29

Tamil Nadu 930 2234 3165 331342 288276 619618 18 32 50

Pondicherry 41 170 211 3275 8021 11296 4 10 14

all India 26166 25522 51688 5358272 2871472 8229744 360 332 692

Annex-I

SARVEKSHANA122 Annex-I

Table 2: Per 1000 distribution of slums by type of ownership of the land where the slum is located

for each State/UT

ownership type

State/UT public number of slums

private railway defence airport highway local others not n. r. all esti-

bodies known mated sample

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

Notified

Jammu & Kashmir 1000 0 0 0 0 0 0 0 0 1000 219 9

Punjab 429 0 0 0 0 571 0 0 0 1000 52 16

Delhi 0 0 0 0 0 695 0 305 0 1000 169 2

Rajasthan 0 0 0 0 0 1000 0 0 0 1000 12 3

Uttar Pradesh 978 9 13 0 0 0 0 0 0 1000 775 15

Bihar 656 344 0 0 0 0 0 0 0 1000 349 3

West Bengal 871 1 0 0 0 67 61 0 0 1000 2871 38

Orissa 0 0 0 0 0 0 1000 0 0 1000 11 1

Chhattisgarh 314 0 0 0 0 686 0 0 0 1000 501 4

Madhya Pradesh 10 0 0 0 0 876 112 2 0 1000 1530 23

Gujarat 142 0 0 0 0 858 0 0 0 1000 413 12

Maharashtra 241 29 3 8 3 443 265 8 0 1000 10189 113

Andhra Pradesh 393 0 0 0 23 416 159 0 9 1000 6384 62

Karnataka 174 13 0 0 0 814 0 0 0 1000 1178 17

Tamil Nadu 138 0 0 0 0 708 155 0 0 1000 930 18

Pondicherry 292 0 0 0 0 123 585 0 0 1000 41 4

all India 355 23 1 3 7 442 162 5 2 1000 26166 360

Non-notified

Jammu & Kashmir 428 0 10 0 0 10 551 0 0 1000 145 7

Punjab 0 0 0 0 0 48 952 0 0 1000 104 2

Delhi 0 0 0 0 0 921 79 0 0 1000 1678 20

Rajasthan 2 0 0 0 0 977 21 0 0 1000 862 9

Uttar Pradesh 742 0 194 0 0 53 0 11 0 1000 1868 20

Bihar 123 246 0 0 0 374 257 0 0 1000 977 8

West Bengal 494 171 0 0 0 101 213 21 0 1000 5253 56

Orissa 0 0 0 0 0 297 682 21 0 1000 390 12

Chhattisgarh 710 211 0 0 0 39 39 0 0 1000 743 6

Madhya Pradesh 77 0 0 0 0 518 406 0 0 1000 691 14

Gujarat 324 0 0 0 2 667 7 0 0 1000 1120 31

Maharashtra 439 38 4 0 0 360 158 0 0 1000 6472 60

Andhra Pradesh 286 0 0 0 0 714 0 0 0 1000 1340 13

Karnataka 34 0 0 0 0 467 259 241 0 1000 805 12

Tamil Nadu 139 132 0 0 0 611 74 44 0 1000 2234 32

Pondicherry 29 0 0 0 0 434 536 0 0 1000 170 10

all India 352 76 15 0 0 382 158 17 0 1000 25522 332

n.r.: - not reported

SARVEKSHANA 123Annex-I

Table 3: Per 1000 distribution of slums by type of structure of the majority of houses in slums for

each State/UT

type of structure of the majority of houses number of slums

State/UT pucca semi serviceable unserviceable no all estimated sample

pucca katcha katcha dwelling

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Notified

Jammu & Kashmir 0 610 390 0 0 1000 219 9

Punjab 429 476 95 0 0 1000 52 16

Delhi 1000 0 0 0 0 1000 169 2

Rajasthan 667 0 333 0 0 1000 12 3

Uttar Pradesh 611 381 0 9 0 1000 775 15

Bihar 0 656 0 344 0 1000 349 3

West Bengal 810 150 40 0 0 1000 2871 38

Orissa 0 1000 0 0 0 1000 11 1

Chhattisgarh 0 1000 0 0 0 1000 501 4

Madhya Pradesh 230 760 10 0 0 1000 1530 23

Gujarat 812 188 0 0 0 1000 413 12

Maharashtra 706 284 10 0 0 1000 10189 113

Andhra Pradesh 735 150 115 0 0 1000 6384 62

Karnataka 496 327 177 0 0 1000 1178 17

Tamil Nadu 682 219 50 50 0 1000 930 18

Pondicherry 415 0 585 0 0 1000 41 4

all India 645 295 53 7 0 1000 26166 360

Non-notified

Jammu & Kashmir 0 0 259 741 0 1000 145 7

Punjab 0 48 952 0 0 1000 104 2

Delhi 272 399 329 0 0 1000 1678 20

Rajasthan 39 227 247 487 0 1000 862 9

Uttar Pradesh 155 450 41 354 0 1000 1868 20

Bihar 0 118 631 251 0 1000 977 8

West Bengal 437 431 107 24 0 1000 5253 56

Orissa 0 31 969 0 0 1000 390 12

Chhattisgarh 0 789 211 0 0 1000 743 6

Madhya Pradesh 59 915 25 0 0 1000 691 14

Gujarat 295 688 17 0 0 1000 1120 31

Maharashtra 482 393 89 36 0 1000 6472 60

Andhra Pradesh 300 207 173 321 0 1000 1340 13

Karnataka 332 465 203 0 0 1000 805 12

Tamil Nadu 136 329 441 94 0 1000 2234 32

Pondicherry 0 0 930 70 0 1000 170 10

all India 303 397 200 100 0 1000 25522 332

SARVEKSHANA124 Annex-I

Table 4: Per 1000 distribution of slums by major source of drinking water for each State/UT

major source of drinking water number of slums

tube tank/ pond

State/UT well/ (reserved other river/

tap hand well for tank/ canal/ spring others all estimated sample

pump drinking) pond lake

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Notified

Jammu & Kashmir 1000 0 0 0 0 0 0 0 1000 219 9

Punjab 429 571 0 0 0 0 0 0 1000 52 16

Delhi 1000 0 0 0 0 0 0 0 1000 169 2

Rajasthan 1000 0 0 0 0 0 0 0 1000 12 3

Uttar Pradesh 335 665 0 0 0 0 0 0 1000 775 15

Bihar 0 1000 0 0 0 0 0 0 1000 349 3

West Bengal 889 111 0 0 0 0 0 0 1000 2871 38

Orissa 1000 0 0 0 0 0 0 0 1000 11 1

Chhattisgarh 314 686 0 0 0 0 0 0 1000 501 4

Madhya Pradesh 677 204 118 0 0 0 0 0 1000 1530 23

Gujarat 325 16 0 0 0 0 0 658 1000 413 12

Maharashtra 952 27 13 0 0 8 0 0 1000 10189 113

Andhra Pradesh 873 23 23 0 0 0 0 80 1000 6384 62

Karnataka 891 109 0 0 0 0 0 0 1000 1178 17

Tamil Nadu 851 0 0 0 0 0 0 149 1000 930 18

Pondicherry 1000 0 0 0 0 0 0 0 1000 41 4

all India 839 98 24 0 0 3 1 35 1000 26166 360

Non-notified

Jammu & Kashmir 979 21 0 0 0 0 0 0 1000 145 7

Punjab 0 1000 0 0 0 0 0 0 1000 104 2

Delhi 711 289 0 0 0 0 0 0 1000 1678 20

Rajasthan 266 3 0 0 0 0 0 731 1000 862 9

Uttar Pradesh 588 412 0 0 0 0 0 0 1000 1868 20

Bihar 0 1000 0 0 0 0 0 0 1000 977 8

West Bengal 719 177 80 0 0 0 0 24 1000 5253 56

Orissa 565 435 0 0 0 0 0 0 1000 390 12

Chhattisgarh 710 251 39 0 0 0 0 0 1000 743 6

Madhya Pradesh 751 249 0 0 0 0 0 0 1000 691 14

Gujarat 743 257 0 0 0 0 0 0 1000 1120 31

Maharashtra 908 27 10 0 0 0 0 55 1000 6472 60

Andhra Pradesh 455 545 0 0 0 0 0 0 1000 1340 13

Karnataka 765 160 0 0 0 75 0 0 1000 805 12

Tamil Nadu 925 29 47 0 0 0 0 0 1000 2234 32

Pondicherry 971 29 0 0 0 0 0 0 1000 170 10

all India 713 217 24 0 0 2 0 44 1000 25522 332

SARVEKSHANA 125Annex-I

Table 5: Per 1000 distribution of slums by status of electricity connection for each State/UT

slums with number of slums

State/UT electricity for

both street lights household street light no all estimated sample

and household use only only electricity

use

(1) (2) (3) (4) (5) (6) (7) (8)

Notified

Jammu & Kashmir 0 1000 0 0 1000 219 9

Punjab 171 571 257 0 1000 52 16

Delhi 695 305 0 0 1000 169 2

Rajasthan 0 333 667 0 1000 12 3

Uttar Pradesh 665 326 0 9 1000 775 15

Bihar 0 656 0 344 1000 349 3

West Bengal 957 0 43 0 1000 2871 38

Orissa 1000 0 0 0 1000 11 1

Chhattisgarh 1000 0 0 0 1000 501 4

Madhya Pradesh 890 8 102 0 1000 1530 23

Gujarat 836 16 148 0 1000 413 12

Maharashtra 819 169 12 0 1000 10189 113

Andhra Pradesh 925 3 72 0 1000 6384 62

Karnataka 887 0 113 0 1000 1178 17

Tamil Nadu 991 9 0 0 1000 930 18

Pondicherry 708 0 0 292 1000 41 4

all India 843 106 41 9 1000 26166 360

Non-notified

Jammu & Kashmir 238 762 0 0 1000 145 7

Punjab 0 0 48 952 1000 104 2

Delhi 390 610 0 0 1000 1678 20

Rajasthan 39 247 0 714 1000 862 9

Uttar Pradesh 409 125 11 455 1000 1868 20

Bihar 0 369 0 631 1000 977 8

West Bengal 616 138 89 158 1000 5253 56

Orissa 433 125 413 28 1000 390 12

Chhattisgarh 749 211 0 39 1000 743 6

Madhya Pradesh 335 665 0 0 1000 691 14

Gujarat 532 273 188 7 1000 1120 31

Maharashtra 551 354 60 35 1000 6472 60

Andhra Pradesh 567 112 0 321 1000 1340 13

Karnataka 982 0 18 0 1000 805 12

Tamil Nadu 741 88 85 86 1000 2234 32

Pondicherry 930 0 0 70 1000 170 10

all India 534 251 57 158 1000 25522 332

SARVEKSHANA126 Annex-I

Table 6: Per 1000 distribution of slums by arrangement of garbage disposal for each State/UT

garbage disposal system number of slums

arrangement by

State/UT panchayat / no

municipality / residents others arrangement all estimated sample

corporation

(1) (2) (3) (4) (5) (6) (7) (8)

Notified

Jammu & Kashmir 390 0 0 610 1000 219 9

Punjab 43 614 86 257 1000 52 16

Delhi 695 305 0 0 1000 169 2

Rajasthan 333 667 0 0 1000 12 3

Uttar Pradesh 689 266 27 17 1000 775 15

Bihar 0 0 0 1000 1000 349 3

West Bengal 914 45 0 41 1000 2871 38

Orissa 0 0 0 1000 1000 11 1

Chhattisgarh 372 628 0 0 1000 501 4

Madhya Pradesh 586 0 0 414 1000 1530 23

Gujarat 958 0 0 42 1000 413 12

Maharashtra 874 21 0 105 1000 10189 113

Andhra Pradesh 834 4 0 162 1000 6384 62

Karnataka 501 0 0 499 1000 1178 17

Tamil Nadu 991 0 0 9 1000 930 18

Pondicherry 708 292 0 0 1000 41 4

all-India 791 44 1 164 1000 26166 360

Non – notified

Jammu & Kashmir 0 238 0 762 1000 145 7

Punjab 0 0 0 1000 1000 104 2

Delhi 561 110 0 329 1000 1678 20

Rajasthan 19 0 0 981 1000 862 9

Uttar Pradesh 141 43 0 815 1000 1868 20

Bihar 118 123 0 759 1000 977 8

West Bengal 398 75 96 432 1000 5253 56

Orissa 106 53 28 812 1000 390 12

Chhattisgarh 39 0 39 921 1000 743 6

Madhya Pradesh 373 0 35 591 1000 691 14

Gujarat 180 512 7 301 1000 1120 31

Maharashtra 787 43 0 170 1000 6472 60

Andhra Pradesh 271 108 0 621 1000 1340 13

Karnataka 350 97 0 553 1000 805 12

Tamil Nadu 423 111 0 465 1000 2234 32

Pondicherry 140 761 0 99 1000 170 10

all-India 419 94 24 463 1000 25522 332

SARVEKSHANA 127Annex-I

Table 7: Per 1000 distribution of slums by availability of underground sewerage system for each

State/UT

underground sewerage system number of slums

State/UT available not available all estimated sample

(1) (2) (3) (4) (5) (6)

Notified

Jammu & Kashmir 0 1000 1000 219 9

Punjab 343 657 1000 52 16

Delhi 0 1000 1000 169 2

Rajasthan 0 1000 1000 12 3

Uttar Pradesh 353 647 1000 775 15

Bihar 0 1000 1000 349 3

West Bengal 627 373 1000 2871 38

Orissa 0 1000 1000 11 1

Chhattisgarh 0 1000 1000 501 4

Madhya Pradesh 240 760 1000 1530 23

Gujarat 830 170 1000 413 12

Maharashtra 343 657 1000 10189 113

Andhra Pradesh 117 883 1000 6384 62

Karnataka 232 768 1000 1178 17

Tamil Nadu 568 432 1000 930 18

Pondicherry 0 1000 1000 41 4

all-India 300 700 1000 26166 360

Non – notified

Jammu & Kashmir 0 1000 1000 145 7

Punjab 0 1000 1000 104 2

Delhi 31 969 1000 1678 20

Rajasthan 0 1000 1000 862 9

Uttar Pradesh 113 887 1000 1868 20

Bihar 0 1000 1000 977 8

West Bengal 232 768 1000 5253 56

Orissa 0 1000 1000 390 12

Chhattisgarh 0 1000 1000 743 6

Madhya Pradesh 0 1000 1000 691 14

Gujarat 74 926 1000 1120 31

Maharashtra 271 729 1000 6472 60

Andhra Pradesh 0 1000 1000 1340 13

Karnataka 241 759 1000 805 12

Tamil Nadu 107 893 1000 2234 32

Pondicherry 70 930 1000 170 10

all-India 147 853 1000 25522 332

n. r. = not reported

SARVEKSHANA128 Annex-I

Table 8: Per 1000 distribution of slums by distance from nearest primary school for each State/UT

distance from nearest primary school (in km) number of slums

State/UT less than 5 and

0.5 0.5 – 1 1 – 2 2 – 5 above all estimated sample

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Notified

Jammu & Kashmir 390 610 0 0 0 1000 219 9

Punjab 957 43 0 0 0 1000 52 16

Delhi 305 695 0 0 0 1000 169 2

Rajasthan 1000 0 0 0 0 1000 12 3

Uttar Pradesh 627 370 3 0 0 1000 775 15

Bihar 328 672 0 0 0 1000 349 3

West Bengal 785 215 0 0 0 1000 2871 38

Orissa 1000 0 0 0 0 1000 11 1

Chhattisgarh 372 0 628 0 0 1000 501 4

Madhya Pradesh 846 137 0 17 0 1000 1530 23

Gujarat 282 718 0 0 0 1000 413 12

Maharashtra 633 265 102 0 0 1000 10189 113

Andhra Pradesh 758 212 30 0 0 1000 6384 62

Karnataka 884 3 113 0 0 1000 1178 17

Tamil Nadu 816 177 8 0 0 1000 930 18

Pondicherry 708 292 0 0 0 1000 41 4

all-India 696 237 65 2 0 1000 26166 360

Non – notified

Jammu & Kashmir 438 0 551 10 0 1000 145 7

Punjab 48 952 0 0 0 1000 104 2

Delhi 360 320 320 0 0 1000 1678 20

Rajasthan 981 19 0 0 0 1000 862 9

Uttar Pradesh 195 570 1 234 0 1000 1868 20

Bihar 620 251 128 0 0 1000 977 8

West Bengal 682 249 70 0 0 1000 5253 56

Orissa 951 49 0 0 0 1000 390 12

Chhattisgarh 749 251 0 0 0 1000 743 6

Madhya Pradesh 664 275 61 0 0 1000 691 14

Gujarat 685 287 7 20 0 1000 1120 31

Maharashtra 803 151 21 26 0 1000 6472 60

Andhra Pradesh 799 201 0 0 0 1000 1340 13

Karnataka 506 94 400 0 0 1000 805 12

Tamil Nadu 646 325 29 0 0 1000 2234 32

Pondicherry 674 326 0 0 0 1000 170 10

all-India 659 246 66 28 0 1000 25522 332

n. r. = not reported

SARVEKSHANA 129Annex-I

Table 9: Per 1000 distribution of slums by distance from nearest government hospital / health centre

for each State/UT

distance from nearest government hospital / health centre (in km) number of slums

State/UT less than 5 and

0.5 0.5 – 1 1 – 2 2 – 5 above all estimated sample

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Notified

Jammu & Kashmir 0 0 390 0 610 1000 219 9

Punjab 95 648 0 43 214 1000 52 16

Delhi 0 0 305 695 0 1000 169 2

Rajasthan 0 0 1000 0 0 1000 12 3

Uttar Pradesh 39 614 330 17 0 1000 775 15

Bihar 0 0 0 1000 0 1000 349 3

West Bengal 193 239 372 88 108 1000 2871 38

Orissa 0 0 0 1000 0 1000 11 1

Chhattisgarh 0 314 628 58 0 1000 501 4

Madhya Pradesh 409 333 15 227 17 1000 1530 23

Gujarat 45 680 87 171 16 1000 413 12

Maharashtra 202 227 229 307 35 1000 10189 113

Andhra Pradesh 216 294 253 237 0 1000 6384 62

Karnataka 327 396 13 222 43 1000 1178 17

Tamil Nadu 217 421 362 0 0 1000 930 18

Pondicherry 0 0 0 1000 0 1000 41 4

all-India 203 278 236 247 36 1000 26166 360

Non – notified

Jammu & Kashmir 0 238 0 21 741 1000 145 7

Punjab 48 0 952 0 0 1000 104 2

Delhi 189 421 289 70 31 1000 1678 20

Rajasthan 731 19 243 7 0 1000 862 9

Uttar Pradesh 94 22 34 851 0 1000 1868 20

Bihar 123 380 118 380 0 1000 977 8

West Bengal 232 246 231 217 75 1000 5253 56

Orissa 328 53 538 21 59 1000 390 12

Chhattisgarh 0 0 79 921 0 1000 743 6

Madhya Pradesh 0 24 279 660 37 1000 691 14

Gujarat 60 179 34 702 25 1000 1120 31

Maharashtra 273 274 275 127 51 1000 6472 60

Andhra Pradesh 343 205 132 0 321 1000 1340 13

Karnataka 75 413 352 160 0 1000 805 12

Tamil Nadu 260 329 260 110 41 1000 2234 32

Pondicherry 309 621 70 0 0 1000 170 10

all-India 219 245 227 250 58 1000 25522 332

n. r. = not reported

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3.13 ãÉMÉ£ÉMÉ 41 |ÉÉÊiɶÉiÉ ¶Éc®ÉÒ {ÉÉÊ®´ÉÉ® +É{ÉxÉä {ÉÉÊ®ºÉ®Éå ºÉäBÉESÉ®ä BÉEä ÉÊxɪÉÉÊàÉiÉ ÉÊxÉ{É]ÉxÉ BÉEä ÉÊãÉA xÉMÉ® ÉÊxÉBÉEɪÉÉå ºÉä BÉEÉä<ǺÉcɪÉiÉÉ xÉcÉÓ ãÉäiÉä cé * ãÉMÉ£ÉMÉ 20 |ÉÉÊiɶÉiÉ ¶Éc®ÉÒ BÉÖE]Öà¤ÉÉå (MÉÆnÉÒ¤ÉÉκiɪÉÉå àÉå 26 |ÉÉÊiɶÉiÉ) BÉEä {ÉÉºÉ +É{ÉxÉä {ÉÉÊ®ºÉ® ºÉä BÉESÉ®ä BÉEä

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BROAD CONTENTS OF THE LAST THREE ISSUES OF ‘SARVEKSHANA’

(A) 88th ISSUE

Part-I : Technical Papers

Report on Cross-Validatioin Study of Estimates of Private Consumpotion Expenditure Availablefrom Household Survey and Ndatioinal Accounts

(Expert Group on Non-Sampling errors)

Part-II : Summary and Major Findings of Surveys

An Integrated Summary of NSS Fifty-Fifth Round (July 1999-June 2000) Survey Results on InformalSector Employment in India

(Asis Roy and Salil Mukhopadhyay)

(B) 89th ISSUE

Part-I : Technical Papers

1. Employment in Unorganised Manufacturing in India: Post-Reform Trends and Future Directions (G. K. Chadha and P. P. Sahu)

2. Small Area Estimation Using GIS ( Roma Choudhury Sahu, Kasturi Basu and Shibdas Bandyopadhyay)

3. Informal non-agricultural enterprise - NSS 55th round - Gujarat State

( D E S Gujarat)

4. Unorganised Sectors and its contributions in India (Pankaj K P Shreyaskar)

Part-II : Summary and Major Findings of Surveys

An Integrated Summary of the results of the survey on Unorganised Manufacturing Sector,NSS Fifty-Sixth Round (July 2000 - June 2001)

(A. J. Roy and M. Mallick)

(C) 90th ISSUE

Part-I : Technical Papers

1. A Study on the Precision of the Estimated Number of Workers and Gross Value Added per Workerfor the Unorganized Manufacturing Sector

(G.C. Manna)

2. Workforce Engaged in the Services Sector: A Study on the Divergences in the Estimates Based onHousehold and Enterprise Enquiries as per the NSS 57th Round

(G.C. Manna)Part-II : Summary and Major Findings of Surveys

An Integrated Summary of NSS Fifty-Seventh Round (July 2001 - June 002)

Unorganised Service Sector Survey Results(A.K. Verma)

l Authors are requested to send three typewritten copies of their papers /

articles to the Deputy Director General, Coordination and Publication

Division, National Sample Survey Organisation, Sardar Patel Bhavan,

New Delhi-110 001.

l Typescript should be double-spaced. Margins should be 1½² wide on the

left and 1² on the right. It is better that a soft copy of the paper/article in

MS Word/Excel is also forwarded. The paper/articles can directly be

e-mailed at ramkripal_skakawar@yahoo.co.in also.

l Mathematical formulae, symbols etc. should be neatly written, if typing is

not possible. The graphs, charts and diagrams, if any, should be complete

with all details and be such that direct reproduction can be obtained.

l Reference to other papers, books etc. should be given in full e.g. name of

author, title of publication, name of journal, date of publication etc.

l A summary of the paper not exceeding, 150 words should also be sent.

l Subscription to Sarvekshana should be sent to the Controller of

Publications, Department of Publication, Civil Lines, Delhi 110 054.

PDOS 57 XXVII No. 1&2450

The objective of this journal is to present analytical articles based on the results

published by NSSO. Sarvekshana welcomes contributions based on the NSS data

and those relating to its methodology.

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