Employ Prob India

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The Employment Challenge in IndiaAuthor(s): Ajit K. GhoseReviewed work(s):Source: Economic and Political Weekly, Vol. 39, No. 48 (Nov. 27 - Dec. 3, 2004), pp. 5106-5116Published by: Economic and Political WeeklyStable URL: http://www.jstor.org/stable/4415834 .

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S p e c i a l articles___T h e Employmenthallenge i n I n d i a

What is the nature of the employmentproblem that India currently confronts? And whatare the economic and social policies that could effectivelyaddress the problem? The core ofthe employmentproblem in India is that of the workingpoor and addressing this is alsothe most effective way of eliminating child labour and reducing gender inequality in theworldof work. In principle, this can be addressed either by reducing the level ofunderemployment,ncreasing the real wage ratefor casual labour or facilitating the transferof poor self-employedpersons and casual labourers to regular wage paid jobs. Theprioritymust be to generate a steadyprocess of labour transfer;ensuring that a substantialproportionof the newly created regular wage paid jobs are for low-skilledworkers,whichpoints to the needfor a growth strategy oriented towards exports of manufactures.AJITK GHOSE

IntroductionW ahat s thenature f theemployment roblemhat ndiacurrently confronts? And what are the economic andsocial policies thatcould effectively address the prob-lem? These arethe two questions that this paperseeks to answer.The questions, of course, are not new. There is a fairly substantialliterature that attempts to address them in some fashion.lNevertheless, in the view of this author, adequate answers areas yet unavailable. The existing literature identifies a host ofemployment-related problems but is not very helpful in identi-fying a core problem that could be the focus of policy. Cor-respondingly,policy discussions often list awhole setof desirablemeasures that need to be taken, thereby suggesting multipleobjectives that must somehow be pursued simultaneously. In allthis,considerationsof dynamicinteractions, rade-offsandpriorityordering are almost entirely missing.Yet, the available database for analysing India's employmentproblem is rich. The large-scale sample surveys of employmentand unemployment, carried out by the National Sample SurveyOrganisation(NSSO) once every five years, arericher in contentthan the standard labour force surveys conducted in otherdeveloping anddeveloped countries. And the data generated bythe NSSO surveys areparticularlyappropriate or understandingthe core characteristicsof employment/unemployment problemsin a typical labour-surplus developing economy. But most an-alysts, both in India and abroad, have failed to make adequateuse of this database, perhaps because they have been far tooconcernedwithusing theanalytical tools thatareappropriateonlyfor analysing labour markets in advanced industrial economies.This paperbases itself mainly on the most recent dataavailablefrom the 1999-2000 NSSO survey and the 2001 populationcensus. In dealing with some specific topics, it also relies onsome of thepastNSSO surveys and a few othersources, indicatedatappropriateplaces. Theplanof thepaper s asfollows. Section IIbriefly considers the question of appropriateuse of the database

availableoranalysis.Section IIreviews hecurrentmploymentscene naneffort oidentify hecoreof theemployment roblem.SectionIV examines ime-trends thepurposehere s tojudgetheprogressmade novercominghecoreproblem nd odevelopan understandingf the processes nvolved.Finaly,SectionVdevelopssomeconcreteguidelines orfuturepolicyand, n thiscontext,points osomeoutstandingssues thatcallforempiricalresearch.II

The DataNSSO samplesurveysare designedto providea statisticalpictureof the extremely complex employmentsituation hatprevails n India.Thecomplexityarises romthreebasic facts.First,very ewpeoplehaveregular,ull-timewageemployment;the vast majoritywork on an irregularbasis, either as self-employedor ascasualwage-labourers.Mostworkers,herefore,are in employmentwithoutnecessarilybeing at work on allworkdays n any given period.Second, as there is no well-developedsystemof social security,unemployments not anoptionexceptfor the well off; the poorhaveto work in orderto surviveeven when the return rom this work is inadequate

forbasicsubsistence.These acts mply, hird,hat hereprevailswhatmightbe termedas Say's Lawof employment;upplyoflabour reates ts owndemand. nthesecircumstances,tandardindicators uchasgrowthnthenumber fpeople nemploymentorchangesntherateof unemploymento nottellus muchaboutemploymentrendsor conditions.Tocaptureheessentials f thiscomplexreality,NSSOsurveysuse innovativemethodologies ndcategorisation. heyemploythreedifferentmethodsof determininghe activitystatusofpersons.Thefirstmethodseeks to identifythe usualprincipalactivitystatuscalled'usualprincipal tatus',henceforthUPS)of a personby usinga referenceperiodof 365 daysprecedingthe dateof survey.A person s countedas beingin the labourforce f he/sheeitherengaged neconomicallygainfulactivities

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or reportedseekingor beingavailable or' such activities orthe majorpartof the preceding365 days.2 A personactuallyworkingor themajorpartof theperiod s countedasemployedwhileapersonwho eitherwasseekingor was available orworkforthemajorpartof theperiod s countedas unemployed.Themethodmakes t possible o identify,withreasonable ccuracy,theactivity tatus fpersonsnasituationwherevery ewpeoplehold egular,ull-timeobs.Clearly, persondentifiedsemployedcould have beenunemployed n certaindays during heperiodjust as a person dentifiedas unemployed ould have workedon certaindays.Moreover,hose classifiedas beingoutside helabour orcecouldalso have workedor searched or workona few days during he period.Suchpersonsare considered ohave been 'usualsubsidiary tatus' (USS) participantsn thelabour orce,andthe surveysprovidethe relevantestimates.Thesecondmethods what s commonlyusedin labour orcesurveysnmanycountries.Thisusesa reference eriodof sevendays precedinlthe date of surveyand seeks to determinehecurrentctivity tatus called currentweeklystatus',henceforthCWS)of persons.A person s counted as employed f he/sheengagedin gainfulactivities for at least one hourduring hereferenceweek.Correspondingly,nunemployed erson s onewhodid not workbutwas seekingor available or workfor atleast an hourduring he referenceperiod.The implicitrule isthatactual or intendedparticipationn gainfulactivities haspriorityveractual r ntended articipationn all otheractivities.Thus a student,who engagedin gainfulactivitiesfor an hourduring he referenceweek,gets classifiedas employed,not asa student; imilarly,a housewife,who soughtor was availableforgainfulactivities or evenanhourduringhereferenceweek,gets classified as unemployed,andnot as a housewife.The thirdmethodalso uses a referenceperiodof sevendaysprecedinghe dateof surveybut seeks to determine he detailedtimedispositionof personson each day of the week ('currentdailystatus',henceforthCDS).A personsconsideredmployedforhalfadayif he/sheengaged ngainfulactivities or betweenoneand ourhoursandemployed or afullday f theengagementwas for four hours or more. The same rules are appliedtodeterminehestatus funemployment. learly, nanygivenday,a person ouldbe (i) employed orthefull dayor(ii) employedforhalf hedayandunemployedor heotherhalfor iii) employedfor half the day and out of the labour orce for theother halfor (iv) unemployedorhalf thedayand out of the labour orceforthe otherhalfor (v) unemployedorthe full dayor (vi) outof the labourorce forthefullday.Thus theCDSestimatesareof person-days employed,unemployedor not available foremployment) nd not of persons.Theanalysis n thispaper s basedmainlyon UPSdata;CWSandCDS dataare used as supplementary. he reasonsare asfollows. Whenmostpeoplehaveregularwage employment, sinadvancedndustrialountries,heemploymenttatus fpersonsduringa week does not radicallydiverge from their usualemployment tatus. In a developingeconomy such as India,however,the divergencecan be substantial. n any particularweek,a personwho usuallyworksas self-employedcould beworking sacasual abourer,ustas ausuallyunemployed ersoncould be employed.Similarly,a personwhousuallyengages nfarming ould be engaged n some non-farmactivityduringaparticularweek. For these reasons,the CWS methodis lessappropriatehan heUPSmethod ordetermininghe abourorceoremploymenttatusof persons n aneconomysuch asIndia's.

TheNSSOsurveys mplicitly ecognisehis; heUPSdataprovideinformationn awider ange femployment-relatedharacteristicsof persons hando the CWS data.However, he CWS dataareusefulfor a broadcomparison f India'semployment ituationwith that n othercountries, ince labour orcesurveys n mostof these countriesuse the CWS method.The CDS data,as alreadynoted,refer to person-days atherthanto persons.As such,thesedata areveryusefulforcertainpurposes fordetermininghe totalquantityof labouractuallyemployedduring givenperiod, orexample).Buttheyobscurerather han illuminate ome important spectsof employmentconditions.Forexample,observedemploymentor unemploy-mentof a certain umber fperson-daysoesnottell usanythingabouthenumber nd ypesofworkershat uppliedheseperson-days. Similarly,he observeddistributionf person-days crosssectors ractivities oesnot ell usanything bout hedistributionof workersacross sectors or activities.To understand ctualemployment onditions,we needto know about hecategoriesof workers n employment ndabout he conditionsof employ-ment of each of the categories.Researchersn Indiaoftenregard heUSS workersas partofthe labour orce.3 Inthispaper,we consideronlysomeof them- those who foundemploymentorjust a few days but wereseekingor available or work fora majorpartof the referenceyear- as beingin the labour orce.Thusthe categoryof un-employed ncludesa sectionof USS workers.The rest of theUSS workersareregardedas beingoutside the labour orce.It is well known thatNSSO surveysdo notprovidereliableestimatesof population.Forestimating he absolutenumbers,therefore,he ratios andproportions vailable romthe NSSOsurveysneed obecombinedwithpopulation'estimatesvailablefrom thepopulation ensuses.Thisby now is a fairlystandardpractice ndneedsno further laboration.Another imitation ftheNSSO urveyssthatheydo notdistinguishetween rganisedandunorganised egmentsof theeconomy.Yet, for some pur-poses, it is of interest o know the distribution f employmentbetweenorganised ndunorganisedegments.Fortunately,sti-mates of organised ectoremploymentare available romtheministry f labour,4and these are used in combinationwith thedata from the NSSO surveys n this paper.

IllEmploymentndLabourMarketsnIndiaCharacteristics of Labour Supply

In 2000, Indiahad a labourforce of 376.4 million5 in apopulation fjustover1billion.Theimpliedworker-populationratio 0.37) is obviously ow. Onereason,of course, s that hepopulationsyoung;nearly36percentof thepopulationsbelow15 yearsof age. But the labour orce participationateof theadultpopulations also low, as Table 1 shows.The mainex-planation,quiteobviously,lies in the low labour orce parti-cipationof women.Thereasonwhywomen's labour orceparticipations low isthatwomen ake heprincipalesponsibilityorhousework.Theindirectevidence of this is thatmanywomen seek workonlyintermittently.6The directevidence is that, if housework sregardeds againfulactivity,women'sparticipationateactuallyturnsout to be somewhathigherthanmen's (Table 2). It isimportantorecognisenthiscontext hat nlowincome ountries

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such as India, housework contributes much more to familywelfare than it does in high-income, developed countries.7Housework includes collection of free goods (fruits and vege-tables, firewood, cattle-feed, drinking water, etc) and activitiessuch as cattle tending as well as knitting, tailoring and weavingfor household use. Many of these goods and services are eitherpurchased in the market or supplied by paid employees indeveloped, high-income countries.The labour force in India, it is well known, includes somechildren (those belonging to the age group 5-14 years). In 2000,there were 8.6 million child workers8constituting 2.3 per centof the total labour force. One fact about child labour in Indiadeserves particular mphasis here. It is not truethatchildrenmissout on schooling because they areputto work or that all children,who do not attendeducational institutions, work.9 Only a smallpercentage of those children who are not attending educationalinstitutions actually work. In 2000, of the 248.4 million childrenin the age groupof 5-14 years, 181.2 million or 73 percent werefull-time students. Of the 67.6 million who were not attendingeducational institutions, only 8.6 million were in the labourforceandanother8.2 million were engaged in housework. Obviously,the choice is not between schooling and work; it is betweenidleness and work. The reasons why many children do not getan education are not the same as the reasons why some childrenwork. The absence of adequate publicly provided facilities forschooling as also the inability of many households to meet eventhe minimal expenses involved are among the most importantreasons why many children are not in school. The fact thatmostof these children actually do not work means that, in general,parents are most reluctant to send their children to work. Childlabourreflects extreme poverty, notunwise ormisguided parentalchoice. 0India's labour force is still largely low skilled (Table 3). In1999-2000, more than 42 per cent of those in the labour forcehad no education at all, and an average labour force participanthad only 3.9 years of education. The average skill level of thefemale labour force, expectedly, is much lower than that of themale labourforce. Sixty-nine percent of thefemale workershavehad no schooling, and an average female worker has only 1.9years of education; the comparable figures for male workers are33 per cent and 4.6 years of education. What appears some-what surprising is that the average educational level of thefemale labour force is lower thanthatof the female 'populationnot attending educational institutions'.11 The search for anexplanation reveals the following facts (Appendix Table Al).The labour force participation rate of women (who are notattendingeducational institutions) moves along aU-shaped curveas the level of education rises. This is a mirror image of theinverted U-shaped curve along which the rate of full-time en-gagement of women (who are not attending educationalinstitutions) in housework moves as the level of educationrises. And the end-points on the inverted U-shaped curve areabove those on the U-shaped curve which means that thepercentage of women engaged in housework exceeds thepercentage participating in economic activities at all levels ofeducation. Thus the level of education of women engaged inhousework (2.8 years) is significantly higher thanthatof womenin the labour force (1.9 years).These patterns of women's participation in the labour forceand housework, of course, are interesting in themselves. Let usalso note thattheprevailing cultural normsabout women's work

only explain the fact that more women areengaged in houseworkthan in gainful activities, irrespective of their level of education;they do notexplain theU-shaped curve (orthe invertedU-shapedcurve), and we need to search for other possible reasons. Themost likely explanation is that the economic return from house-work, in relation to that from possible employment, first risesand then falls as the level of education rises.12A noteworthyfact is that abourforce participationof men whohave up to five years of education and who are not attendingeducational institutions is noticeably lower than that of others(Table 4). The same pattern is observed in the case of womenTable 1: Comparison of Labour Force Participation (CWS)in India, 2000(Inpercent)

Country LabourForceParticipation ateTotal Male FemaleDenmark 80.1 84.3 75.9France 69.3 75.6 63.1Germany 72.3 80.4 64.0Japan 78.5 92.7 64.1Korea,Republic 65.1 75.6 54.3Mexico 65.0 90.2 42.4Spain 65.7 79.3 52.0Turkey 51.7 75.9 26.9UK 75.2 82.5 67.7US 78.2 84.7 71.8India 58.6 82.1 33.9Note: ForIndia, he estimateis forpopulation ged 15 years ormore. Forothercountries, he estimatesare forpopulation ged 15-64 years.Source: OECD exceptforIndia).

Table 2: Labour Force Participation Rates (UPS)by Alternative Definitions(Inpercent)Participation ateMale Female All

DefinitionA 82.5 30.6 57.1DefinitionB 90.9 32.6 61.9DefinitionC 91.3 93.3 92.1Notes:(i)Age group:15 years or more; ii)DefinitionA- the usualdefinitionwhereby abourorce s expressedas a percentageofpopulationntherelevantge group;Definition-labourforce sexpressedas apercentageof 'populationnot attendingeducationalinstitutions';DefinitionC -labourorce ncludes hose 'engaged nhousework' nd sexpressedasa percentageof 'population otattending ducationalnstitutions'.

Table 3: Level of Education of Populationand Labour Force (UPS)(Percentage)AverageYears NoEducation Tertiaryof Education Education

PopulationAll 3.4 38.2 3.9Male 4.2 28.3 5.0Female 2.7 48.9 2.6Population otattending ducationalnstitutionsAll 3.3 49.4 4.7Male 4.2 37.7 6.5Female 2.3 61.7 3.0LabourorceAll 3.9 42.4 6.3Male 4.6 33.0 7.3Female 1.9 68.5 3.7Notes:(i)Agegroup: iveyearsormore; ii)TheeducationcategoriesinNSSOsurveysarenot ntermsofnumber fyearsofeducation.Wemakethefollowingssumptionsnorder oderive heestimates n ermsofnumberofyearsofeducation:not iterate': yearsofeducation;literate ndupto primary': -5 years of education; middle': -8 years of education;'secondary':-10 yearsof education;higherecondary':1-12years ofeducation; nd'graduate ndabove':more han12yearsofeducation.



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when houseworkis regardedas againful activity. Theexplanationis as follows. The incidence of poverty varies inversely with thelevel of education; about 80 per cent of poor adults (those aged15 years or more) in the labour force either have no educationor have only up to 5 years of education (Appendix Table A2).There is also evidence to show that the number of children (agedless than 15 years) per adult is higher in poor households thanin non-poor households; in 2000, this number was 0.8 for thepoor and 0.5 for the non-poor.13 The two facts together indicatethat the number of children per adult is significantly higher forpersons with little or no education. This is the main reason whythe labour force participationof the population with little or noeducation is lower than that of the rest of the population.A final interesting fact is that a fairly large section (22 percent) of women with tertiaryeducation seem to be neither in thelabour force nor engaged in housework (Table 4). There are atleast two reasons for this.First, as these women obviously belongto well off households, they are under no pressure to earn andcan also hire domestic help for housework. Second, as we shallsee below, the rateof unemployment among women with tertiaryeducation is very high, andthis very probably discourages manyfrom entering the job market.

EmploymentIn 2000, 365.9 million persons were in employment in India,26.5 percent of themwomen. 14About91 percent of theemployedpersons were working-age (15-59 years), 2.3 percent were childworkers (age group:5-14 years) and the rest were older workers(age group: 60 years or more). Just over 50 per cent of theemployed worked as self-employed (including those working asunpaidfamily workers) andanother 34 percent worked as casualwage labourers.Less than 8 percent (28 million) were employedin the organised sector15of the economy, and just over 8 percent (29.4 million) were in regular wage employment outside

the organised sector.16Agriculture still accounts for the bulk (59 per cent) of totalemployment in the economy. Industry is the least importantemployer; it accounts forjust 16 percent of total employment.17There is a fairly close correspondence between the type ofemployment and the sector of employment. A large majority ofthe self-employed and the casual labourers work in agriculturewhile a large majority of the regular employees are in industryand services. The type of employment also corresponds closelyto the level of education of workers (Table 5). The regularemployees, whether in or outside the organised sector, have thehighest average level of education, while casual labourershavethe lowest. The level of education of the self-employed is higherthan that of casual labourers but substantially lower than thatof the regular employees.As these facts imply, there is a close correspondence betweenthe level of education of workers and the sector of theiremploy-ment (Table 6). Agricultural workers have the lowest level ofeducation while service sector workers have the highest level.And this pattern holds good for all types of workers - self-employed, casuallabourersandregularemployees. Overall,casuallabourers nagriculture re heleasteducatedandregular mployeesin industry and services are the most educated.The type of employment is also a good indicator of povertystatus Table7). There s a largecategoryof workingpoorinIndia;ornearly ne-third f those nemployment,arningsronm

employment reinadequateo guarantee consumptionevel,for themselvesand theirdependants, n or above the officialpoverty ine. The incidenceof poverty s high amongcasuallabourersbut also quitesubstantial mongthe self-employed.While a small section of regularwage employees s also poor,it can be said that the categoryof working poor in IndiaisTable 4: Labour Force Participation (UPS) Rates of PersonsNot Attending Educational Institutions by Level of Education(Inper cent)

Yearsof Education0 1-5 6-8 9-10 11-12 Morethan 12Excluding ouseworkAll 48.5 61.2 65.4 67.2 69.3 76.0Male 73.6 86.9 93.0 91.6 92.4 93.9Female 33.2 26.2 20.1 20.9 22.6 37.4IncludingouseworkAll 79.0 88.4 94.3 93.2 94.1 89.8Male 74.4 87.5 93.6 92.2 92.9 94.4Female 81.8 89.6 95.4 95.1 96.4 78.0Note: i)Age group: iveyearsormore;See note (ii)Table 3.

Table 5: Education and Employment (UPS)AverageYears Percentagewithof Education No Education TertiaryEducation

Employedpopulation 3.7 43.4 5.8Self-employed 3.7 41.6 4.4Casual abourers 1.8 60.3 0.3Regular mployees 7.8 12.7 22.0Notes:(i)Age group: iveyears ormore;See note (ii)Table 3.Table 6: Structure of UPS Employment and Level of Educationof Workers by Sector

Structure f Employment AverageYearsof(PerCent) Education fWorkersAgricultureAllworkers 100.0 2.6Self-employed 54.9 3.2Casual abourers 43.6 1.7Regular mployees 1.5 7.0IndustryAllworkers 100.0 4.5Self-employed 36.8 4.3Casual abourers 35.8 2.2Regular mployees 27.4 7.9ServicesAllworkers 100.0 5.8Self-employed 45.1 4.7Casual abourers 10.8 2.3Regular mployees 44.1 7.9Note: i)Age group: iveyears ormore;See note (ii)Table3.Table 7: Incidence of Poverty among Employed Persons

Self- Casual Regular AllEmployedEmployed Labourers Employees PersonsPercentageof theemployed npoverty 27.4 47.8 15.2 32.5Composition f theworkingpoor 44.7 48.4 6.9 100Notes:(i)Age group: iveyears or more;(ii)Employedpersons here refer othoseemployedaccordingousualstatus(thoseemployedaccordingousualprincipaltatus+ those employedaccording o usualsubsidiarystatus).Anemployedpersonbelonging o a householdwithpercapitaexpenditurebelowthe poverty ine(Rs 335.46 forruralareas and Rs451.19 forurbanareas, both n1999-2000 prices) s regardedas poor.



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essentially composed of casual wage labourers and the self-employed. In 2000, 48 percent of the working poor were casualwage labourers and another 45 per cent were self-employed.

UnderemploymentUnderemployment s difficultto measure; nfact,even definingit in a satisfactory manner is not easy. One way is to assumea norm for full-time employment and then consider the gapbetween this norm and the actual level of employment over any

given period of time; such a norm, unfortunately, cannot but bearbitrary.Another way is to consider the employed workers'subjective notion of what constitutes a satisfactory time-rateofemployment; but such a notion cannot be independent of theactual labour marketconditions that workersconfront andhencemust necessarily vary across individuals as well as over time.At any rate,estimates based on workers' revealed preferencesgenerally show the overall rate of underemployment to beimplausibly low. One study, for example, estimates the rate ofunderemployment to have been only 3.4 per cent in 1993-94[Ghose 1999]. This estimate is based on data relating to thoseemployed workers who seek additionalemployment for specifictime periods. Another indicator, often used by researchers inIndia,is given by thedifference between theCDS unemploymentrateand theCWS unemployment rate. 8This indicatoralso showsthe overall rate of underemployment to be implausibly low. In1999-2000, for example, the rate of underemployment by thismeasure was only 2.8 per cent.Given the implausible results that these measures yield, adifferent (and, hopefully, more appropriate)measure of under-employment is suggested in this paper. The CDS and CWSestimates of employment can be used together to work out theactualnumberof days of employment peremployed personduringthe reference week for different categories of workers. Giventhe definition of CDS employment, however, these estimates arenot in units of standardeight-hour days. But estimates in termsof standarddays can be derived by assuming that an averageregular employee works for six standard days in a week. Therate of underemployment among the self-employed and casuallabourerscan thenbe worked out by assuming that these workerswould also want to work for six standarddays in a week, if workwere available. The estimates based on this method, presentedin Table 8, show the overall rate of underemployment to be high:13.3 per cent of the available labour days remained unutilisedin 2000. The rate of underemployment is clearly very high forcasual labourers,but it is also substantial for the self-employed.

WagesFourimportant acts arehighlighted by thewage dataavailablefrom the NSSO surveys (Table 9). First, even the lowest wagein regular obs is generally adequate to ensure an above povertyline level of living for an average employee and his/herdependants.19 Since the lowest wage is to be found outside theorganised sector, it is clear once again that regular employees,irrespectiveof whetherthey are in oroutside the sector, arerarelyamong the poor. Second, wage differentials between men andwomen are far less significant in the case of regularemployeesthan in thecase of casual labourers. On average, a female regularemployee earns 92 percent of the wage earnedby a male regularemployeenrural reasand89percent nurban reas.Thissmall

differential arises, in all likelihood, not so much because womenare paid less than men in similarjobs but because, with a lowerlevel of education on average, they hold proportionately morelow-wage jobs than men. In contrast, a female casual labourerearns, on average, only 65 percent of the wage earnedby a malecasual labourer n rural areas and 60 percent in urban areas. Nodoubt a partof this differential also arises because women tendto do proportionately more low wage work than men, but it islegitimate to wonder if this is the sole explanation for such alarge differential.Third, the wage gap between regular employees and casuallabourers is very large. For a day's work, an average casuallabourer earns only 32 per cent of what an average regular

employee earns in rural areas and 34 per cent of that in urbanareas. This wage gap, moreover, is much largerfor women thanfor men. An average female casual labourer earns only 25 percent of what an average female regular employee earns in bothrural and urbanareas; the corresponding figure for males is 35per cent in rural areas and 37 per cent in urban areas. The gapsin monthly or annualearnings, for both men and women, wouldof course be even larger, since the average casual labourerdoesnot find work on all workdays in any given period.Finally, it is quite clear that a combination of low wage andhigh underemployment generates the observed widespreadpoverty amongcasual labourers.At theexisting level of underem-ployment, the ruling wage rates are clearly inadequateto ensureabove poverty line incomes for most casual labour households.It can also be inferred from this that the poverty of a substantial

Table 8: Rate of Underemployment(Inper cent)Self- Casual Regular AllEmployed Labourers Employees EmployedPersons

Male 5.0 21.7 0.0 10.0Female 21.7 28.3 0.0 21.7Employedpersons 11.7 25.0 0.0 13.3Note: Theestimatesare based on theassumption hatallworkerswouldwantto workon six, eight-hourdays ina week.

Table 9: Money Wage/Salary Per Day(Inrupees)ActualWage EstimatedPoverty-Average Lowest LineWage

RuralmaleRegular mployees 127.3 44.5 32.6Casual abourers 45.5 39.3 46.6Rural emaleRegular mployees 113.9 28.2 32.6Casual abourers 29.4 28.2 48.7UrbanmaleRegular mployees 169.5 60.2 43.9Casual abourers 63.3 49.7 62.7Urban emaleRegular mployees 140.2 33.9 43.9Casual abourers 38.2 29.0 65.5Notes:(i)Workersnage group15-59years. (ii)Inrural reas,thelowestwageis found ncultivation;nurbanareas, itis found nhouseholdservice.Theassumptionsused to estimatepoverty-linewages are as follows:(1) Poverty-line xpenditurepercapitain 1999-2000 is Rs 335.46 inrural reas and Rs 451.19 inurbanareas.(2) Theaverage numberof dependantsis 1.5 forregular mployeesand 1.8forcasual labourers.(3) Each workergets paidonlyforthe days actuallyworked.(4) A male casual labourer indswork or 4.7 days perweek whileafemalecasual labourerinds work or4.3 days perweek. Regularemployees, male orfemale,work ix days perweek.



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section of the self-employed also arises from a combination oflow return rom work andunderemployment (the explanation forboth must lie in a low asset-base). Indeed, since underemploy-ment is lower for the self-employed than for casual labourers,poorself-employed workersvery probablyearneven lower returnsfrom a day's work than poor casual labourers.20

UnemploymentIn 2000, 10.5 million persons were unemployed in India, sothat the rate of unemployment was only 2.8 per cent.21 In ad-vanced industrialcountries, this rateof unemployment would betakento indicate full employment. In India, it merely underlinesthe fact that most Indians cannot afford to be unemployed.That this is so is most clearly indicated by the fact that the

unemployed in India actually belong to the relatively well offsections of the population. The level of education of an averageunemployed person (9.1 years) is significantly higher thaneven that of theaverage regularemployee in industryor services(7.9 years). And the rate of unemployment steadily rises as thelevel of education rises (Appendix Table A3); it is insignificantfor those with little or no education, but high (6.5 per centupwards) for those with more than eight years of education.Less than5 percentof theunemployedare lliteratewhilenearly 26percent have tertiaryeducation. As alreadynoted, a persons levelof education is a good indicator of the level of income of thehousehold to which he/she belongs. On the whole, it is quiteclear that the poor and the unemployed are two distinct groups;the poor are not unemployed and the unemployed are not poor.

Gender Inequalities in EmploymentWomen's employment conditions are worse than men's inseveral respects. First, the average quality of women's employ-ment is worse than that of men's. The share of regularemployees

in the total employed is much lower for women (9.2 per cent)than for men (18 per cent). At the other end, the share ofcasual wage-labourers in total employed is much higher forwomen (42.5 per cent) thanfor men (31.1 per cent). These factsalso imply that women's employment is much more con-centratedin agriculture than men's; nearly 74 per cent of em-ployed women work in agriculture compared to 54 per cent ofemployed men.Second, underemployment is significantly higherfor women in all sectors (Table 8). This, of course, is notsurprisingsince women depend much more on self-employmentandcasual wage employment than men. Third,while there is littleunemployment among persons of both sexes with little or noeducation, educated women actually face a much higher rate ofunemploymentthaneducatedmen (Appendix TableA3). In2000,for persons with tertiary education, the rate of unemploymentwas less than 9 per cent for men but 27 per cent for women.Thusunemployed women, on average, have asignificantly higherlevel of education(10.3 years) thanunemployed men (8.7 years).Finally, as we have seen, women generally earn significantlylower wages than men.These gender inequalities in employment do not necessarilyimply the existence of gender-based discrimination in the labourmarket. Indeed, the fact that wage inequality among womenworkers is actually higher than that between men and womensuggests that gender-based discrimination in the labour marketisnot hemajor ourceofgendernequalities.Gendernequalities

in theworldof worklargelyreflectgender nequalitiesn edu-cation.As alreadynoted,the female labour orce has a muchloweraverage evelof educationhan he male abour orce.Wehavealso observed hat he level of education s closely linkedto boththetypeand sectorof employment.Thus,even if therewere no discriminationn the labourmarket, he qualityofwomen'semploymentwouldstill be worsethanthatof men's.Theseobservations onotimplythat here s nogender-baseddiscriminationn the labourmarket.Buttheydo implythat heexistenceof suchdiscriminationannotbe takenas anobviousfact, which requiresno investigation.In the case of casuallabourers,he arge ender-basedagedifferentialsould onceiv-ablyreflectdiscrimination,utwe need to be sure thattheydonotmerely eflectproductivityifferentials.n hecaseofeducatedpersons, hehigher evelof unemploymentf womencouldalsoreflectdiscrimination,utwe cannot gnore hepossibility hatmanyof theunemployedwomenmayhave had educationof atype thatgives themno employableskills.

Employment of ChildrenThe dataonemployment f children Table10)bringoutone

importantact: mostchildworkerswork as self-employedandcasual abourers,mainly n agriculture.n 2000, nearly94 percentof employed hildrenwereworking itherasself-employedorcasual abourers,nd75 percentof them(nearly71 percentof all employedchildren)were in agriculture.The 6 percent,who workedas regularemployees,were mainlyin services.Two pointsof significancecan be inferred romthesefacts.First, they suggest that workingchildrenactuallybelong toworking oorhouseholds.ike heworking oor,workinghildrenalso are eitherself-employedor casualwage labourers,mostlyinagriculture.econd, t is not obvious hat orcingchildren utof workwould mprove heirwelfareeven if mechanisms ouldbe found ocompensatehem orthe oss of income. t sarguablethat rregular ork, otheextent hat t makesacquisition f someskills possible,is preferableo a stateof idleness.As pointedout earlier, or workingchildren n India,workdoes not haveanopportunityost in termsof missed education.Onthe otherhand,work in family enterprises as traditionally eena formof apprenticeshiphroughwhichparentspasson skills to theirchildren.Casualwage-employmentlso has an apprenticeshipdimension; hildrenoftenaccompanyheirparentsor relativesin suchemployment.22

OverviewThe review of basic factsabout hecurrent mployment nd

labourmarket onditionsn India uggestsonefirmconclusion:the core of theemployment roblems thatof theworkingpoor,andovercomingt mustbe thepriority bjectiveof employmentpolicyat thisjuncture.Addressingheproblemof theworkingTable 10: Employment (UPS) of Children(Inmillions)

Agriculture Industry Services AllSectorsSelf-employment 3.4 (40.0) 0.9 (10.6) 0.4 (4.7) 4.7 (55.3)Casualwage-employment 2.6 (30.6) 0.5 (5.9) 0.2 (2.3) 3.3 (38.8)Regularwage-employment 0.1 (1.2) 0.1 (1.2) 0.3 (3.5) 0.4 (5.9)All ypes 6.1 (71.8) 1.5(17.7) 0.9(10.5) 8.5(100.0)Note:Figures nparenthesesarepercentages.

Economic and Political Weekly November 27, 2004 '5111


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poor is also the most effective way of eliminating child labourand of reducing gender inequality in the world of work; for itis in the world of the working poor that child labour and thewidest gender inequality are to be found.Unemployment is clearly not a problem that deserves priorityattention; the overall rate of unemployment is low and theunemployed arenon-poor. It is true thatthe rate of unemploymentamong the educated is high, and this certainly is a problem. Butit pales into insignificance when compared to the problem ofthe working poor. Also, as we shall see below, addressing theproblem of the working poor requires economic and socialpolicies that should have favourable employment effects for theeducated.23 On the other hand, policies geared to addressing theproblem of unemployment are most likely to have many inci-dental benefits for the working poor.Regular wage paid jobs, irrespective of whether these are inor outside the organised sector, allow the workers concerned toachieve at least above poverty line levels of living. While thereis undoubtedly much scope for improving the quality of manyof these jobs, particularlyof those outside the organised sector,it is hard to regardthis as a priority concern in a situation wherelarge groups of self-employed workers and casual labourersstruggle to survive with below poverty line incomes. Besides,it is arguable that addressing the problem of the working poorwill create the conditions for improving the average quality ofregular wage paid jobs,24 while improving the qualityof regularwage paid jobs is most unlikely to address the problem of theworking poor.25

IVTheTrends,1983-2000When we look at the time trends (Table 11), the first fact thatstrikes us is that, throughoutthe period of 1983 to 2000, the rateof growth of employment was exactly the same as that of the

labour force. However, this should not really surprise us sinceit merely reflects the fact that unemployment is not an optionfor most Indians. The same story is also told by the fact that therate of chronic (or long-term) unemployment shows no trendandhas consistently been below 3 per cent - the benchmark for fullemployment.26 The growth of the labour force in India impliesthe growth of employment, and this tells us why the standardlabourmarket ndicators are not appropriate or analysing labourmarket developments. The fact that employment growth wasslower during 1994 to 2000 thanduring 1983 to 94, for example,merely reflects the slow down in labour force growth and saysnothing about changes in employment conditions. It is alsoevident that conventional estimates of employment elasticitywould tell us nothing about the demand for labour and are notuseful tools of analysis or projection exercises. And the unem-ployment rate is clearly not a meaningful indicator of labourmarket conditions.How then do we judge if employment conditions have beenimproving or deteriorating over time? The following observa-tions suggest an answer. First, the reason why the rate of growthof employment always equals that of the labour force is that,in self-employment andcasual wage employment, sharingof anyavailable amount of work is institutionally feasible. The adjust-ment variable is the rate of underemployment, not employmentor unemployment rates. Second, as already stated, improvementin employment conditions in India essentially means decline in

theproportionof working poor in totalemployment. Ouranalysissuggests that, for this proportion to decline, either the level ofunderemployment must decline or the real wage rate for casuallabourmust rise or the rateof growth of regularwage employmentmust be higher than that of total employment so that poorself-employed and casual labourers have opportunities to moveto regular wage paid jobs.We can, therefore,think of threeindicators that areappropriateforjudging changes in employment conditions: rate of growthofperson-days of employment peremployed person, change in theratioof thenumberof workers n regularwage employmentto thatof all employed workers, and rate of growth of real wage rateforcasual labour in agriculture.The first indicator shows the changein the level of underemployment. The second indicator focuseson the process of labour transfer, from self-employment andcasual wage employment to regularwage employment. And therateof growthof therealwage ratefor casual labour nagriculture,which is the lowest real wage ratein theeconomy, is an indicatorof the trend in the reward for labour of the working poor.It should be noted, however, that the first indicator shows thechange in the overall level of underemployment while we shouldreally be interested in observing change in the level of under-employment of the working poor. Since the number of days ofemployment per person is always larger for regular wage em-ployees than for self-employed or casual labourers, a rise (fall)inperson-days peremployed does notnecessarily imply a declineTable 11: Growth of Population, Labour Force and Employment(Inpercent)

AverageAnnualRate of Growth1983-1994 1994-2000Population 2.17 1.79Labourorce(UPS) 2.16 1.37EmploymentUPS) 2.17 1.34

Table 12: Indicators of Change in Employment Conditions,1983-20001983 1994 2000

Person-daysofemploymentperemployedworkerperweek 6.3 6.5 6.4Percentageof regularwage employeesinallemployed 15.6 15.5 15.9Averageannualrateofgrowth per cent)of realwage rate forcasual labourinagriculture - 2.4 2.7Working ooras percentageofallemployed 43.7 35.7 32.5Employed hildworkersas percentageofallemployed 6.2 3 2.3Wage rateforfemalecasual labournagricultures percentageof thatformalecasual labour nagriculture 69.2 71.4 71.6Notes: (1) Theperson-daysofemployment re not nstandard ight-hourays.(2) To estimaterealwage rates,moneywage rateswere deflatedbytheconsumerprice ndex oragriculturalabourers.(3) The estimate of workingpooras a percentageof allemployedfor2000 is taken from this paper. The estimate for 1994 is fromSundaram ndTendulkar2002). Theestimate for1983 is derivedas follows:CombininghedatainSundaram ndTendulkar2002)and inGhose (1999),the numbersof poorandnon-poorpeople in1983 wereworkedout.We estimated,inthispaper,that,in2000,each poorworker upported1.8 dependentswhileeach non-poorpersonsupported .5 dependents.Weassumedthese figureswerevalid or 1983 andestimated heworking ooras apercentageofallemployed n1983 byusingthe formula:(PP/2.8) [(PP/2.8+ (NPP/2.5)]wherePP is the numberof poorpeopleand NPPis the numberofnon-poorpeople.



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(rise) in the level of underemploymentof theworkingpoor, whenthere is a simultaneous rise (fall) in the share of regular wageemployees in total employed. Thus the rateof growth of person-days per employed worker is not really a good indicator;the rateof growth of person-days per worker in self-employment andcasual wage employment would be more appropriate.Unfortu-nately,the datarequired oconstruct his moreappropriatendicatorare not readily available to us so that we cannot help relying onintuitive judgments in this paper.

The indicators suggested above focus on the processes thatchange the share of the working poor in the total employed. Inaddition, we could obviously also look at some outcome in-dicators. Three such indicators are particularlyrelevant: changein the percentage of working poor in total employed, change inthe percentage of child workers in total employed, and changein the ratio of the real wage rate for female casual labour inagricultureto that for male casual labour in agriculture.This lastindicator can be regarded as an indicator of change in genderinequality in the world of the working poor.The estimated values of the six indicators - three processindicators and three outcome indicators - are assembled inTable 12. From the outcome indicators, t is immediatelyapparentthat employment conditions improved in both periods (1983-1994 and 1994-2000), though painfully slowly; the proportionof the working poor in total employment declined, as did theproportionof child labour in total employment and the level ofgender inequality. The process indicators suggest, however, thatthe factors that brought about the improvement were somewhatdifferent in the two periods. The overall level of underemploy-ment declined in the first period and increased in the secondperiod. On the otherhand,the shareof regularwage employmentin total employment declined in the first period and increasedin the second period. Fromthese facts, we can infer thatthe levelof underemploymentof the self-employed and casual labourersdeclined significantly in the first period and rose significantlyin thesecond period.The real wage rate forcasual labourshowedfairly rapid growth in both periods.27Thus, in the first period, employment conditions improvedbecause the self-employed and casual labourers benefited fromboth reduced underemployment and increased returnsto labour.In the second period, on the other hand, employment conditionsimproved because the self-employed and casual labourers bene-fited from increased returnsto labour as well as from a processof transfer to regular wage paid jobs.Two important questions, therefore, arise. First, why didunderemployment, which had declined in the first period, in-crease in the second period? A part of the answer probably liesin the reported slow down in the growth of crop production inthesecond period.Anotherpartseems to lie in the fact thatperson-days of wage employment generated in rural areas under thespecial employment schemes increased substantially in the firstperiod and declined equally substantially in the second period(particularly fter1997) [PlanningCommission 2001a,Table 5.2].These conjectures gain plausibility from the fact that, in bothperiods, the trend in overall underemployment essentially re-flected the trend in underemployment in agriculture (AppendixTable A4).Second, what explains the rise in the share of regular wageemployment in total employment in the second period? Theanswerseems to be demographichanges.The rate of growthof regularwageemploymentwasactually ower(at 1.7percent

perannum) during 1994-2000 thanduring 1983-94 (2.1 percentperannum). The same was true of the elasticity of regularwageemployment with respect to GDP, which was 0.45 during1983-94 and 0.25 during 1994-2000. The reason why the rateof growth of regular wage employment was higher than that oftotal employment in the second period is that the rate of growthof totalemploymentwas lower, it declined from2.2 percentduring1983-94 to 1.4 percent during 1994-2000. And this decelerationresulted essentially from the deceleration in population growthfrom 2.2 to 1.8percent perannum(though theworker-populationratio also fell from 0.384 in 1994 to 0.375 in 2000, basicallybecause of a decline in the worker-population ratio for females).It thus appears that the economic and social policies pursuedduring 1994-2000 had no particular ocus on the problem of theworking poor. The favourable demographic changes, togetherwith a relatively high rate of economic growth (6.7 per cent perannum), had created an opportunity for sharply reducing theproportionof the working poor in total employment. In reality,the reduction was small because the elasticity of regular wageemployment with respect to GDP declined and the quantity ofrural wage employment, generated by the special employmentschemes, fell (when a rise was required).

VPoliciesAs already noted, the problem of the working poor can in

principle be addressed either by reducing the level of under-employment, orby increasing therealwage ratefor casual labour,or by facilitating the transferof poor self-employed persons andcasual labourersto regular wage paid jobs. A little reflection tellsus, however, that priority must be placed on generating andsustaining a process of labourtransfer romself-employment andcasual wage employment to regular wage employment. For, inthe absence of such a process, special employment schemes -themaininstrumentavailable forreducingunderemploymentandfor increasing the real wage rate for casual labour - will needto be implemented on an ever-expanding scale just to preventthe problem of the working poor from worsening. As this willimply an ever-increasing fiscal burden on the state, it is hardtosee how such a strategy can be sustainable.A priorityobjective of economic andsocial policies, therefore,must be to generatea steady process of labour transfer.Inspecificterms, economic policies must seek to ensure that the rate ofgrowth of regular wage employment exceeds that of labour forceby a substantialmargin.Whether the requisite growth of regularwage employment occurs in the organised or the unorganisedsegments of the economy is not of particularimportance, sinceall types of regularwage employment aresuperiorto casual wageemployment, or self-employment with a poor asset-base. How-ever, it is doubtful if there can be rapidoverall growth of regularwage employment when employment in the organised sectorstagnates.28

Sustaining a high rate of economic growth is obviously es-sential for sustaining a high rate of growth of regular wageemployment. But it is equally important o preventsharpdeclinesin theelasticity of regularwage employment withrespect to GDP.An adequateunderstandingof the causes of the observed declinein this elasticity during 1994-2000 is thus of much relevance.A proper investigation into the issue would require a separatestudy;only a few pertinent bservations,which aresuggestive



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of some hypotheses, can be made here. The data in Table 13show that the observed decline in the elasticity of regular wageemployment between the periods was associated with a sharpdeceleration in the growth of organised sector employment. Oneprobableexplanation for this deceleration, also suggested by thedata, is shedding of 'surplus labour', which seemingly had beenaccumulated in organised agriculture and in 'other industries'(mining, electricity,gas, waterandconstruction)during 1983-94.There is no obvious explanation for the sharp deceleration inthe growth of employment in organised services, but we knowthat high-tech services acquired prominence during 1994-2000andthat there was a sharp growth in remuneration or employeesin public services. One intriguing fact is that, in manufacturing,the growth of organised sector employment accelerated whilethe growth of regular wage employment outside the organisedsectordeceleratedverysharply.Itlooks as if liberalisationpolicies,though they stimulated growth of employment in organisedmanufacturing,29mayhave hadanadverse effect on employmentgrowth in unorganised manufacturing.The question of redesigning labour marketpolicies and insti-tutions also arises in this particularcontext. Because their domainof operation does not extend beyond the organised sector, thesepolicies and institutions tend to generate pressures for improve-ment in the quality of organised sector jobs, already the bestquality jobs available in the country. There is thus a tendencyfor the quality gap between organised sector jobs and all otherjobs in the economy to widen over time. Much more importantly,there is a trade-off between improvement in the quality of thesejobs andthat n theconditions of theworkingpoor.This is becausesustainable improvements in the quality of organised sectorjobsrequires rises in output per employee, which, in most circum-stances, means a slowdown in the rate of growth of these jobs.And such a slowdown leads to a slowdown in the growth ofregularwage paid obs in theeconomy, whichpre-empts potentialimprovements n the conditions of theworkingpoor by reversing,halting or slowing down the process of labourtransfer.Policies,therefore,have to be basedon anexplicit recognition of the trade-off. It is important o ask if andtowhatextentexisting labourmarketpolicies and institutions have the effect of restrainingthe growthof organised sector employment. And any redesigning of thesepolicies and institutions must have the objective of speeding upthe growth of regular wage employment in the economy.30While the focus of policies must be on generating and sus-taining a process of transfer of the working poor into regularwage paid jobs, some complementary policies are also needed.First, even a rate of growth of regular wage employment thatis substantially higher than that of the labour force does not infact ensure that some members of the working poor actually gettransferred o regular wage paid jobs. For, it is always possiblethat the newly createdjobs go to relatively well off persons whopreviously were either unemployed or not in the labour force.Additional policies, therefore, are required. On the one hand, itis necessary to ensure that a substantial proportionof the newlycreated regular wage paid jobs is for low-skilled workers, andthis points to the need for a growth strategy oriented towardsexports of manufactures.On the otherhand,special skill develop-ment programmesfor the working poor must be envisaged. Theworking poor, as we have seen, have little or no education, andthis will make it difficult for them to move into regular wagepaid jobs in industry and services even when more such jobsare available. The existing skill development programmes are

of little help as these are not geared to trainingpersons with littleorno education. New, innovative skill development programmesfor the working poor will need to be developed.Second, given the numbers involved, even a rapid process oflabour transfer cannot pull all the working poor out of povertyexcept in the medium term. Hence government sponsored specialemployment programmes, designed to directly generate wageemployment for the working poor, must remain an essentialcomponent of policy. But so long as a process of labourtransferis sustained, the scale of these programmescan be progressivelyreduced over time.Special employment schemes can and should be viewed asinstruments for simultaneously reducing underemployment and

increasing the real wage for casual labour in agriculture. In thiscontext, two questions can be usefully asked. Is there a case forconfining the schemes to carefully identified geographical areas,where the share of the working poor in total employed is par-ticularly high? Is there a case for paying a 'poverty-line' wagefor work under the schemes? Our answer to each of the questionsis yes, but therecertainly is scope for serious debateson the issues.Currently, special employment schemes targetthe working poorwherever they may be physically located; this has the effect ofspreading resources too thinly. The effectiveness of theprogrammes is most likely to increase if they instead targetgeographical areas with a high share of working poor in totalemployment. As for wages, there are good arguments forinstitutionalisinga national minimumwage, based on thenationalpoverty line, for unskilled casual labour.31 And payment of a'poverty-line' wage for work under the special employmentschemes can be an effective instrument for enforcing a nationalminimum wage.

Table 13: Growth of Regular Wage Employment (UPS)(Inpercent)AverageAnnualRate of Growth1983-1994 1994-2000

Regularwage employment 2.1 1.7Agriculture -5.7 -2.7Manufacturing 3.1 0.7Other ndustries 1.2 -1.0Services 3.5 2.8Inorganisedsector 1.4 0.2Agriculture 2.0 -1.1Manufacturing 0.1 0.5Other ndustries 1.2 -1.0Services 1.9 0.4Inunorganised ector 3.0 3.3Agriculture -8.3 -3.8Manufacturing 8.1 0.8Other ndustries 0.0 0.0Services 5.4 4.9Table 14: Share of Industryin Total Employment(Inper cent)

Maximum 1978 1983 1988 1994 2000AttainedUK 55.0 (1901) 39.1 33.4 33.1 27.9 25.5US 36.1 (1950) 31.1 28.0 27.0 24.0 22.9Japan 37.3 (1973) 35.1 34.9 34.3 34.2 31.4Korea,Rep 35.9 (1991) 29.5 29.1 34.8 33.2 28.0China 17.5 19.1 23.1 24.4 21.8Thailand 10.7 13.0 11.3 18.0 19.0India 13.1 14.3 16.1 15.7 16.0Note: Figures nparenthesesindicate heyearof attainment.Source: ForUK,US andJapan:Bairochet al (1968) and OECD.ForKorea(Rep):OECD.ForChinaandThailand: LO.



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Third, the working poor, as noted earlier, suffer from a de-mographicdisadvantage. The dependency ratio is higher for thepoorthan for the non-poor,and the basic reason is thatthenumberof children per adult is higher in poor households. Policies thatseek to eliminate this demographic disadvantage of the workingpoor will clearly be helpful. This emphasises the need for in-tegratedprogrammesof maternity,child health and family plan-ning services with universal access. It is known that poorerfamilies tend to have more children at least partly because theyface higherchild mortality.Family planningservices will produceresultsonly when these are delivered together with maternityandchild health services.

Fourth, historical experience suggests that the maximum at-tainable share of industry in total employment in India, as in alllate developing countries, is most likely to be much lower thanAppendix

Table Al: Rates of Participation (UPS) of Women (NotAttending Educational Institutions) in Labour Forceand in Housework by Years of Education(Inper cent)Yearsof Education Participationn

LabourForce Housework0 33.2 48.61-5 26.2 63.46-8 20.1 75.39-10 20.9 74.211-12 22.6 73.8More han12 37.4 40.6Note:Agegroup: iveyearsormore.

Table A2: Poverty by Level of Education(Inper cent)YearsofEducation Incidence fPoverty Distributionf PoorPersonsMale Female All Male Female All0 42.8 46.1 44.0 44.0 70.6 57.41-5 30.5 34.9 33.1 26.6 16.4 21.56-8 23.2 27.8 26.1 16.0 8.0 11.99-10 15.1 19.4 17.9 8.1 3.4 5.811-12 10.0 15.1 13.4 3.3 1.1 2.2More han12 4.3 8.9 7.4 2.0 0.5 1.2All 31.7 33.6 32.6 100 100 100

Table A3: Unemployment (UPS) and Level of Education(Inper cent)YearsofEducation RateofUnemployment DistributionfUnemployedMale Female All Male Female All0 0.4 0.1 0.3 5.1 3.8 4.81-5 1.7 1.3 1.6 15.2 7.7 13.36-8 3.7 4.9 3.8 21.5 11.5 19.09-10 5.4 15.8 6.5 21.5 23.1 21.911-12 7.6 21.1 9.1 15.2 15.4 15.2More han12 8.5 27.0 11.3 21.5 38.5 25.8Note: Unemployed repersons,aged 5 yearsormore,whoareunemployedaccordingo usualprincipaltatus.Source:Author's stimates based on the population stimates inAppendixTable 1 and relevantdataavailable nNSSO(2000).

Table A4: Person-days per Worker (UPS) per Week1983 1994 2000

Agriculture 6.0 6.4 6.2Manufacturing 6.6 6.6 7.0Otherndustries 7.7 6.5 7.3Services 6.9 6.8 6.7Note:Theperson-daysare notinstandardeight-hourdays.

what was atteined in today's industrialised countries or even incountrie; such as South Korea. The point emerges ratherobvi-ously firom he data presented in Table 14. The point at whichde-industriailsation sets iil tends, o be lower in a late developingcountry.The reason is not difficu:t to understand:a late-developermust bor:o.v technologw frommn early-developer andthe labourintensity ot teclhnolo, always declines over time.Given the historicil experience and linkage between the shareof industry in total employment and the share of regular wageemployment in total emp ovment, it would be wise to assumethat, even with the best of efforts, the share of regular wageemployment intotalemployment cannotbe raisedabove acertain,fairlylow level (except pcrhlapsn thevery long run).This impliesthat the share of self-employrent in total employment will haveto remainfairly high in the foreseeable future.Policies, therefore,must seek to hold a substantial proportion of the labour forcein viable self-employment, and the sector where this can be doneis agriculture.Pasttrends n agriculture,however, show decliningself-employmentandrisingcasual\v.tgeemployment.Thesetrendsneed to be halted and that is why land reforms have to be viewedas animportant omponentof employment policy. However, landreformprogrammeshave to be designed so as to promoteviableand technologically dynamic family farms and, therefore, haveto do away with both tiny plots and large (wage labour based)farms. Besides, measures that prevent concentration of land onthe one hand and subdivision and fragmentation on the othermust also be major components of land reform programmes.The policies discussed so farare meant to address the problemof the working poor - the core of the employment problem inIndia. As arguedearlier, overcoming this problem will go a longway towards reducing child labour and gender inequality. Butelimination of these problems will also require implementationof appropriateeducation policies. When there are no workingpoor, there will be no compulsion for children to work forsurvival. But this by itself will not eliminate incentives forchildren to work. For. so long as public facilities for a minimumof 10 years of education for all children are not in place, therewill be idle children. And it is not obvious that idleness is moredesirable than work. Creation of public facilities for ensuring10 years of schooling for all children must, therefore, be apriority objective of education policy. This will also be of fun-damental importance in reducing gender inequality in the worldof work. For, as our analysis has suggested, gender inequalityin education is a far more importantcause of gender inequalityin the world of work than gender-based discrimination in thelabour market.WT1Address for correspondence:[email protected] Notes[Theviewsexpressed nthepaperare heauthor'sandshouldnot beattributedto the organisationto which he belongs.]

1 See, for example, Ghose (1999); PlanningCommission(2001a, 2001b,2002); and Sundaramand Tendulkar(2002).2 Economicallygainful activities are defined to include productionofgoods andservices forpayorprofit,productionof primary ommoditiesfor own-consumption,and own account productionof fixed assets.3 See, for example, PlanningCommission (2001a); and SundaramandTendulkar(2002).4 These estimates are publishedin the annual EconomicSurveyof theMinistryof Finance,Governmentof India.



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5 This estimate is based on UPS. The estimate based on CWS, used inTable 1 to ensure comparability, s slightly higher: 388.3 million.6 The CWSparticipationateof womenis higher han he UPSparticipationrate thetworatesareroughly hesameformen),and mostof thepersonswith USS employment (84 per cent) are also women.7 It is useful to note that,even around1950, the worker-populationatiofor womenwas also low in thedevelopedworld: 19percent inBelgium,32 per cent in Denmark,12 per cent in Spain, 30 per cent in France,27 percent in GreatBritain,22 percent in Italy,20 percent in Norway,20 per cent in the Netherlands,23 per cent in Sweden, 26 per cent inSwitzerland nd 22 percent in the UnitedStates.See Bairochet al(1968).8 7.5 million (or 87 per cent) of these belonged to the age-group of10-14 years and the rest belonged to the age-groupof 5-9 years.9 In the literature n child labour, t is often assumedthatchild workerswould havebeen in school hadtheynot been working: ndeed,estimatesof child labourhave sometimesbeen basedon estimatesof the numberof childrenwhoarenotattending ducationalnstitutions.Theunderlyingassumption s thatparentsmake a choice between sendingchildrentoschooland ending hem owork.Suchanassumptionwouldbeappropriateif, first, therewere enough schools to accommodateall childrenup tothe age of 14 and,second, all parents n a positionto meet the requirededucationalexpenses, however small they might be. Neither of theseconditions is met in India.10 There is now a substantialliterature,theoreticaland empirical, thatdevelopsthisview. See, inparticular,Basu and Van(1998);Basu(1999);and Dar et al (2002). In the case of India,NSSO data can be used toempirically verify the argumentspresented above, but the requiredresearchremains to be done.11 Incontrast,heaverage evel of education f themale abour orce s higherthan thatof the male 'populationnot attendingeducational nstitutions'.12 As already noted, housework is an importantcontributorto familywelfare. And we shall see below that the level of education(for bothmen andwomen)variesdirectlywith householdincome. We shallalsosee thatthe kindof workavailableto womenwith littleor no educationyieldsextremely ow incomes. Even such low incomesexceed the valueof housework for manyof the poorestwomen; they could hardlytendcattle thatdo not exist or stitch clothes thatcannot be purchased.Butthere would clearlybe strongincentivesto forego suchemploymentashousehold ncomesrise, thereby ncreasing he valueof housework.Onthe other hand, at household incomes comfortablyabove the povertyline,thevalueofhouseworkbeginstodecline(asmoregoodsandservicescanbepurchased) nd ncomes frompossibleemploymentalsorise(sincewomen in such households tend to be bettereducated).13 Note the implication hat the incidence of poverty s significantlyhigheramong childrenthan among adults.14 This s theUPS-based stimate.TheCWS-based stimatesslightlyhigher:371.2 million persons in employment,28.7 per cent of them women.15 In India, the organised sector is defined to include the whole publicsector and the privatesector establishmentsthat employ 10 or moreworkers.16 NSSO surveysdefine regularwage employees as personswho work inenterprisesownedby othersand,in return,receive salaries or wages ona regularbasis(i e, not on the basisof dailyorperiodicrenewalof workcontract).The numberof regularwage employeesoutsidetheorganisedsector s derivedby subtractinghenumberof employeesintheorganisedsector(availablefrom the ministryof labour)fromthe totalnumber nregularwage employment(available from the NSSO survey).17 Manufacturing ccounts for just 11 per cent of total employment.18 It is reasonable o interpretUPS unemploymentas chronicor long-termunemployment,CWSunemployment schronicplustemporary r short-termunemployment, ndCDS unemploymentas chronicunemploymentplustemporary nemploymentplusvisibleunderemployment.t followsthat hedifferencebetweenCDSunemployment ndCWSunemploymentis a measure of visible underemployment.19 Theonlyexception s found nthecase of thosefemaleregular mployeeswho earnthe lowest wage. They would be in povertyif they are headsof households.20 Poorself-employedpersonshave the optionof workingas casual wagelabourers.As such, we should expect the income froma day's work tobe roughlyequal for both groups of workers. In reality, it seems, thepoor self-employedchoose to increase overall income at the cost ofreducing ncome from a day's work below the casual wage rate.Thisis consistentwith the logic of peasantproduction.See Sen (1966).

21 This is the UPS rate of unemployment, which measures chronicunemployment.heCWSrateofunemployment, hich ncludes emporaryunemployment,shigher 4.4percent),and heCDSrateofunemployment,which additionally includes visible underemploymentof employedworkers,is even higher (7.2 per cent).22 On the otherhand,gettingchildworkersoutof regularwageemployment,which tendsto be exploitativein characterandoften involves a varietyof risks, s likelyto improve heirwelfareprovided heyarecompensatedfor the loss of income.23 The policies include, as we shall see, export-orientedndustrialisationandparticularypesof health,educationandskill developmentpolicies.All this should increase the demand for educatedworkers.24 It is the existence of a sizeable categoryof working poor thatensuresvirtuallyunlimited upplyof workers oreven regularobs of the lowestquality. In these circumstances,regularwage employees' bargainingpowercannotbutbe weak or even non-existent.Addressing heproblemof the working poor shouldbegin to strengthen his bargainingpowerandthuscreate a sustainablebasis for improvingthe qualityof regularwage paidjobs.25 Indeed, there could be a trade-off between improvingthe quality ofregularwage paid obs andovercoming heproblemof theworkingpoor,as we shall see below.26 The UPS rateof unemploymentwas 2.8 percent in 1983, 2.6 percentin 1994 and 2.8 per cent in 2000.27 Precisely what has been driving the growth in the real wage rate forcasual abour nagricultureemainsunclear.This is an issuethatdeservesattentionfrom researchers.28 The linkage between organisedsector employment and regularwageemploymentoutside the organisedsector is not at all well understood.The issue deserves attentionfrom researchers.29 Empirical tudiesgenerallysupport his view. See, forexample, Goldar(2002) and Ghose (2003).30 Forananalysisof the issues andsome ideas forreform,see ILO(1996).31 See Ghose (1997) for a discussion of the issues.References

Bairoch, P, T Deldycke and H Gelders (1968): The WorkingPopulationand Its Structure,Centred'EconomiePolitique,Institutde Sociologie,Universite Libre de Bruxelles.Basu,K(1999): 'ChildLabour:Cause,ConsequenceandCure,withRemarkson InternationalLabourStandards',Journal of Economic Literature,Vol 37, pp 1083-1119Basu, K andPhamHoang.Van (1998): 'The Economics of Child Labour',American Economic Review, Vol 88, No 3, pp 412-27.Dar,A, N-HBlunch,B KimandM Sasaki(2002): 'Participationf Childrenin Schooling and LabourActivities: A Review of EmpiricalStudies',DiscussionPaper,SocialProtectionUnit,WorldBank,Washington,DC.Ghose, Ajit K (1997): 'Should There Be a National MinimumWage inIndia?', IndianJournal of LabourEconomics, Vol 40, No 4.- (1999): 'Current ssues of EmploymentPolicy in India', EconomicandPolitical Weekly,Vol 36, No 36.- (2003): Jobs and Incomes in a Globalising World,InternationalLabourOffice, Geneva.Goldar,B N (2002): 'TradeLiberalisation ndManufacturingEmployment:The Case of India', EmploymentPaper 2002/34, InternationalLabourOffice, GenevaILO (1996): India: Economic Reformsand LabourPolicies, South AsiaMultidisciplinaryAdvisory Team, InternationalLabourOrganisation,New Delhi.PlanningCommission (2001a): Reportof the TaskForce on EmploymentOpportunities,Governmentof India, New Delhi.- (2001b): Reportof the Steering Committeeon Labourand Employmentfor the 10th Five YearPlan, Governmentof India, New Delhi.- (2002):Reportof theSpecialGroupon TargetingTenMillionEmploymentOpportunities er Yearoverthe 10thPlan Period,Government f India,New Delhi.Sen, A K (1966): 'PeasantsandDualismWithor WithoutSurplusLabour',Journal of Political Economy, Vol 74.Sundaram,K and S Tendulkar (2002): 'The Working Poor in India:Employment-Poverty Linkages and Employment Policy Options',Discussion Paper 4, Recovery and Reconstruction Department,InternationalLabourOffice, Geneva.


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