Poverty and Inequality in India: a Reexamination - Princeton University

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and Rajasthan are two states where therehave been many interesting initiatives inthe field of elementary education in thenineties (on the part of government as wellas non-government institutions), in contrastwith Bihar and Uttar Pradesh whereschooling matters continue to be highlyneglected. The fact the literacy rates andschool participation have surged in themore ‘active’ states is an encouragingindication of the possibility of effectivepublic intervention in this field.Turning to instances of ‘slowdown’, wehave already referred to the slackening ofthe growth rate of real agricultural wagesin the nineties. Another important exampleis the slowdown of infant mortality decline.During the eighties, India achieveda reduction of 30 per cent in the infantmortality rate – from 114 deaths per 1,000live births in 1980 to 80 per 1,000 in 1990.During the nineties, however, the infantmortality rate declined by only 12.5 percent – from 80 to 70. 49 In fact, in thesecond half of the nineties, India’s infantmortality rate has remained virtually unchanged.In some states, notably Rajasthan,the infant mortality rate has stagnated foras long as 10 years. These worrying trendshave received astonishingly little attentionin policy debates, and even in the debateon ‘poverty in the nineties’.Finally, there have also been some areasof ‘regression’ in the nineties. The increaseof economic inequality, discussedearlier, can be seen in those terms. Giventhe adverse social consequences of economicinequality (ranging from elitist biasesin public policy to the reinforcement ofother types of inequality), this accentuationof economic disparities is not a trivialmatter. Another example of adversedevelopment in the nineties is the declinein the female-male ratio among children,from 945 girls per 1,000 boys (in the 0-6age group) in 1991 to 927 girls per 1,000boys in 2001. 50 This decline appears to bedriven by the spread of prenatal sexdeterminationtechnology and sexselectiveabortion, but this does not meanthat it is a ‘technological’ phenomenon,unrelated to other recent economic andsocial trends. Economic growth, in particular,may facilitate the spread of sexselectiveabortion, by making the use ofsex-determination technology more affordable.In this connection, it is worth notingthat the largest declines of the female-maleratio among children between 1991 and2001 occurred in five states (Gujarat,Haryana, Himachal Pradesh, Punjab andDelhi) that are relatively well-off economically,and have also experienced comparativelyhigh rates of growth of per capitaexpenditure in the nineties (Table 3). 51A detailed assessment of the progress ofdevelopment indicators in the nineties isbeyond the scope of this paper. However,a few general observations can be madeon the basis of these illustrations. First, asnoted already, poverty is not unidimensional.The poverty indexes used in thefirst part of this paper are useful indicatorsof inadequate purchasing power, but ontheir own do not do justice to the rangeof deprivations we ought to be concernedwith. Following on this, it is important toacknowledge that recent progress in eliminatingpoverty and deprivation has beenquite uneven in different fields. The debateon ‘poverty in the nineties’ has oftenoverlooked this basic point.Second, this recognition is also importantin assessing the relation betweenpoverty decline and economic growth. Asnoted earlier, the decline of poverty in thenineties, as captured by conventional indexessuch as the headcount ratio or thepoverty-gap index, has been overwhelminglydriven by the growth of average percapita expenditure. From this it may seemthat the reduction of poverty is mainly aquestion of economic growth. However,there is an element of circularity in thisargument: if poverty is defined as lack ofincome, it is not surprising that the growthof income plays a key role in reducing it.When the multidimensional nature ofpoverty is acknowledged, this relationappears in a different light. To illustrate,consider child mortality as an aspect of thedeprivations associated with poverty. Thereis, of course, a significant (negative) relationbetween child mortality and purchasingpower. But child mortality is alsostrongly influenced by other factors suchas educational levels, fertility rates, publichealth provisions (including clean waterand vaccinations), and various aspects ofgender relations. Looking at inter-statecontrasts in India, the correlation betweenchild mortality and average per capitaexpenditure (or even poverty indexes) isactually quite weak. Other factors, particularlyfemale literacy, are often more important.52 Similar comments apply in thecontext of elementary education: the ninetieshave demonstrated the possibility ofrapid progress in this field through publicintervention, with or without rapid economicgrowth. In short, the standard focuson headcount ratios and other expenditurebasedpoverty indexes tends to foster asimplistic view of the relation betweeneconomic growth and poverty decline.Third, it is also interesting to re-examinethe issue of trends in inequality, in the lightof this broader perspective. As discussedin Section III, there is much evidence ofrising economic inequality in the nineties,in the form of a widening rural-urban gap,enhanced inter-state disparities, and alsogrowing inequality within urban areas inmost states. What about other types ofsocial inequality, involving other dimensionsof well-being (e g, educational levelsor life expectancy) and other bases ofdisadvantage (e g, gender or caste)? Thedecline of the female-male ratio amongchildren illustrates the fact that the phenomenonof rising inequality in the ninetiesis not confined to standard economicinequalities: ‘natality inequality’ betweenmales and females is also rising. 53 But thisis not to say that inequality has risen acrossthe board. Even within the field of genderinequality, there are changes in the otherdirection, such as the emergence of asubstantial gender gap in life expectancyin favour of women, overturning India’slong history of female disadvantage in thisrespect. Similarly, it is interesting to notethat while economic disparities betweenrural and urban areas have sharply risenin the nineties, there are trends in theopposite direction as well. The rural-urbangap in life expectancy, for instance, hasdeclined from 10 years or so in the late1970s to seven years or so today, and ruralurbandifferentials in school participationhave also narrowed. 54 Here again, thepicture is more diverse (and more interesting)than it appears on the basis ofpurchasing-power indicators alone.Fourth, the broad approach explored herecalls for a correspondingly broad readingof the causal influences underlying theidentified changes. In the debate on ‘povertyin the nineties’, there has been atendency not only to view developmenttrends in unidimensional terms, but alsoto attribute these trends in a somewhatmechanical manner to the economic reformsinitiated around 1991. At one endof the spectrum, it has been claimed thatthe last decade has been a period of unprecedentedimprovement in living standards,thanks to liberalisation. 55 At theother end, the nineties have been describedas a period of widespread ‘impoverishment’,attributed to liberalisation. 56 Clearly,these readings fail to do justice to thediversity of recent trends. But in addition,3744Economic and Political Weekly September 7, 2002
they ignore the diversity of causal influencesthat have a bearing on these trends.The accelerated progress of elementaryeducation in the nineties, for instance, haslittle to do with liberalisation, and the sameapplies to the slowdown of infant mortalitydecline, not to speak of the decline ofthe female-male ratio among children.Much else than liberalisation has happenedin the nineties, and while issues of economicreform are of course extremelyimportant, so are other aspects of economicand social policy.VIConcluding RemarksA number of useful lessons emerge fromthis reexamination of the evidence onpoverty and inequality in the nineties. First,there is consistent evidence of continuingpoverty decline in the nineties, in terms ofthe ‘headcount ratio’. The extent of thedecline, however, remains somewhatuncertain at this time. Given the methodologicalchanges that took place betweenthe 50th and 55th Rounds of the NationalSample Survey, the official figures (implyinga decline from 36 per cent to 26 percent in the all-India headcount ratio between1993-94 and 1999-2000) are, strictlyspeaking, invalid. We have discussedalternative estimates, based on comparabledata from the two surveys. As it turns out,these adjusted estimates suggest that alarge part of the poverty decline associatedwith official figures is ‘real’, rather thandriven by methodological changes. Whilefurther corroboration and investigation ofthe adjustment procedure is required, theresults have been supported by one independentstudy using an entirely differentmethodology [Sundaram and Tendulkar2002]. Further, the adjusted figures fitreasonably well with related evidence fromthe national accounts statistics, the employment-unemploymentsurveys, and dataon agricultural wages.Second, we have discussed some importantlimitations of the headcount ratio asan index of poverty (even within the standardexpenditure-based approach), andargued for wider adoption of alternativepoverty indexes such as the poverty-gapindex. The main argument for usingheadcount ratios is that they have good‘communication value’, in so far as theyare relatively easy to understand and interpret.However, this transparency is tosome extent deceptive, and much cautionis required in interpreting poverty trendson the basis of headcount ratios. For thepurpose of the poverty comparisons examinedin this paper, the headcount ratio turnsout to be no less informative than thepoverty-gap index. Yet it was importantto calculate the PGIs, if only to discoverthat this refinement does not, after all,make much difference in this particularcontext.Third, growth patterns in the nineties arecharacterised by major regional imbalances.Broadly speaking, the western and southernstates (Andhra Pradesh excluded) havetended to do comparatively well. The lowgrowth states, for their part, form a largecontiguous region in the north and east.This is a matter of concern, since thenorthern and eastern regions were poorerto start with. Indeed, National SampleSurvey data suggest a strong pattern ofinter-regional ‘divergence’ in average percapita expenditure (APCE): states thatstarted off with higher APCE levels alsohad higher growth rates of APCE between1993-94 and 1999-2000. In some of thepoorer states, notably Assam and Orissa,there has been virtually zero growth ofaverage per capita expenditure (and verylittle reduction, if any, in rural poverty)between 1993-94 and 1999-2000. Theseregional patterns are at least broadly consistentwith independent estimates of thegrowth rates of state domestic product(SDP).Fourth, the intensification of regionaldisparities is only one aspect of a broaderpattern of increasing economic inequalityin the nineties. Two other aspects are risingrural-urban disparities in per capita expenditure,and rising inequality of per capitaexpenditure within urban areas in moststates. Further, the real wages of agriculturallabourers have increased more slowlythan per capita GDP, and conversely withpublic sector employees, suggesting someintensification of economic inequalitybetween occupation groups.Fifth, we have argued for assessingchanges in living standards in a broaderperspective, going beyond the standardfocus on expenditure-based indicators. Inthat broader perspective, a more diversepicture emerges, with areas of acceleratedprogress in the nineties as well as slowdownin other fields. For instance, thereis much evidence of rapid progress in thefield of elementary education, but the rateof decline of infant mortality has sloweddown. These and related trends deservegreater attention than they have received sofar in the debate on ‘poverty in the nineties’.Sixth, the case for going beyond expenditure-basedindicators applies also to theassessment of inequality. While expenditure-baseddata suggest rising disparitiesin the nineties, the same need not applyto other social indicators. For instance,while economic disparities between ruraland urban areas have increased in thenineties, there has been some narrowingof the rural-urban gap in terms of lifeexpectancy and school participation.Finally, we have argued against readingthese trends simply as evidence of theimpact (positive or negative) of ‘liberalisation’.For one thing, the impact of liberalisationis a ‘counterfactual’ question, andmuch depends on how the alternatives arespecified. For another, much else has happenedin the nineties, other than liberalisation.The evidence we have reviewed isof much interest in its own right, independentlyof the liberalisation debate. Muchwork remains to be done in terms of identifyingthe causal relations underlying thetrends we have identified. EPWNotes[We are grateful to Suresh Tendulkar for helpfulcomments]1 See Datt (1999a), Gupta (1999), Bhalla (2000a,2000b), Deaton and Tarozzi (2000), Drèze(2000), Lal, Mohan and Natarajan (2001),Nagaraj (2000), Ravallion (2000), Sen (2000),Sundaram and Tendulkar (2000, 2001, 2002),Visaria (2000), Sundaram (2001a, 2001b,2001c), Chandrasekhar and Ghosh (2002),Datt and Ravallion (2002), among others.2 On the first position, see, e g, Bhalla (2000a),Bhagwati (2001), Das (2000). On the otherside, see Mehta (2001), Sainath (2001a,2001b), Shiva (2001a), among others.3 These estimates build on earlier work by Deatonand Tarozzi (2000), Deaton (2001a, 2001b)and Tarozzi (2001).4 In the 50th Round, the correlation between thelogarithm of total household per capitaexpenditure and the logarithm of per capitaexpenditure on this subset of commodities is0.79 and 0.86 in the rural and urban sectors,respectively.5 More precisely, and somewhat less restrictively,we require that the probability of beingpoor, given the amount of a household’sexpenditure on these intermediate goods,remains the same in the 55th Round as it wasin the 50th. We require this on a state by statebasis, one sector at a time, which allows theconditional probability to vary by state and bysector.6 In Deaton and Tarozzi (2000), it is shown that,between the 43rd and 50th Rounds, thecomponent of the CPIAL for the uncovereditems grew somewhat less rapidly than thecomponent for the covered items. In consequence,if we were to supplement our priceindexes for uncovered items from the CPIAL,Economic and Political Weekly September 7, 2002 3745
Page 5 and 6: eal terms, with updating on the bas
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Page 12 and 13: consumption across states. Second,
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Page 18 and 19: the estimated rate of increase of c
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