Poverty and Inequality in India: a Reexamination - Princeton University

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6.05.04.03.02.01.00.0Figure 7:Progress of Selected Social Indicators in the 1980s and 1990s(Per Cent Per Year)5.52.52.9Increase of real Decline of infant Decline of total Decline ofagricultural wages mortality rate fertility rate illiteracy rateSource: Drèze and Sen (2002), chapter 9.1.5its scope has expanded during the lastdecade. As the economy gives greater roomto market forces, uncertainty and inequalityoften increase, possibly leading toenhanced economic insecurity among thosewho are not in a position to benefit fromthe new opportunities, or whose livelihoodsare threatened by the changes in theeconomy. The increase of economic inequalityin the nineties, noted earlier,suggests that tendencies of this kind maywell be at work in India today. Adversetrends in living standards could take severaldistinct forms, including: (1) impoverishmentamong specific regions or socialgroups, (2) heightened uncertainty ingeneral, and (3) growing ‘hidden costs’ ofeconomic development.In connection with the first point, wehave already noted that some of the poorerstates, notably Orissa and Assam, have notfared well at all in the nineties. It is quitepossible that the poorer regions withinthese states have done even worse, to thepoint of absolute impoverishment forsubstantial sections of the population. Inthe case of Orissa, there is some independentevidence of localised impoverishmentin the poorer districts, due inter alia to thedestruction of the local environmental baseand to the dismal failure of state-sponsoreddevelopment programmes [Drèze2001]. 39Similarly, the overall improvement ofliving standards may hide instances ofimpoverishment among specific occupationgroups. The nineties have been a periodof rapid structural change in the Indianeconomy, leading in some cases to1.71.81.52.81980s1990sconsiderable disruption of earlier livelihoodpatterns. Examples include a deeprecession in the powerloom sector, a seriouscrisis in the edible oil industry afterimport tariffs were slashed, periodic wavesof bankruptcy among cotton growers, thedisplacement of traditional fishing bycommercial shrimp farms, and a numberof sectoral crises associated with the abruptlifting of quantitative restrictions on importsin mid-2001. 40 The destruction oflocal environmental resources is anothercommon cause of disrupted livelihoods inmany areas.A related issue is the possibility of ‘hiddenhardships’ associated with recent patternsof economic development. To illustrate,there is much evidence that, in many ofthe poorer regions of India, further impoverishmenthas been avoided mainly throughseasonal labour migration. 41 The latteroften entails significant social costs thatTable 6: Cereal Availability in the Nineties(Grams per person per day)are poorly captured, if at all, in standardpoverty indexes or for that matter in theother social indicators examined in thispaper. Examples of such costs includeirregular school attendance, the spread ofHIV/AIDS, the disruption of family life,and rising urban congestion. 42 Similarly,involuntary displacement of persons affectedby large development projects suchas dams and mines tends to have enormoushuman costs. These, again, are largelyhidden from view in income-based analysesof poverty. In fact, the incomes ofdisplaced persons often rise (with ‘cashcompensation’) even as their lives are beingshattered. 43 The ‘informalisation’ of labourmarkets is another example of economicchange with substantial hidden costs (e g,longer working hours, higher insecurity,lower status, and deteriorating work conditions).44 These issues are not new, butit is important to acknowledge the possibilitythat the hidden costs of economicgrowth have intensified in the nineties.This acknowledgement helps to reconcilethe survey-based evidence reviewedearlier with widespread media reports, inrecent years, of sectoral economic crisesand localised impoverishment. 45 Thisissue calls for further scrutiny, based onmore focused analysis of survey data aswell as on micro-studies.IV.3 The ‘Thin’ Rounds: AnUnresolved Puzzle?We have so far said very little about the‘thin’ rounds, and the poverty estimatesthat can be calculated from them. YetFigure 1 shows that the recent thin rounds,from the 51st through the 54th Round,generate poverty estimates that are hard toreconcile with the quinquennial ‘thick’rounds. If we were to connect up theseNet Production Net Imports Net Change in ‘Net Availability’Public Stocks (1+2-3)1985-89 422.7 2.0 -5.3 430.11990 456.9 0.3 5.0 452.11991 447.9 -1.4 0.4 446.11992 446.8 1.3 4.2 443.81993 446.4 2.5 16.6 432.31994 456.3 0.2 16.6 439.91995 448.6 -5.9 -2.3 445.11996 451.7 -6.9 -11.7 456.41997 445.5 -6.7 -4.2 443.01998 455.3 -4.7 11.0 439.61999 456.3 -5.4 25.3 425.62000 452.7 -5.2 30.7 416.8Note: All figures (except first row) are three-year averages centred at the year specified in the first column.Source: Calculated from Government of India (2002), p S-21.3742Economic and Political Weekly September 7, 2002
points with the official HCR estimates, wewould get a series in which poverty rosebetween 1993-94 and 1994-95, fell from1994-95 to the end of 1997, rose verysharply in the first half of 1998, and thenfell with extraordinary rapidity in 1999-2000. As we have seen, the official estimatefor 1999-2000 is too low, and the lastthin round, the 54th Round, ran for onlythe first six months of 1998, and maytherefore not be fully comparable withother rounds. Even so, and with due allowancefor corrections, it is very hard tointegrate the poverty estimates based onthe thin rounds with the picture that emergesfrom the thick rounds as well as from othersources surveyed in this paper.The story is further complicated by thefact that these thin rounds were run in twoversions, one of which resembled thestandard questionnaire up to and includingthe 50th Round, and one of which – theexperimental questionnaire – had differentreporting periods for different goods.Headcount ratios based on the experimentalquestionnaire (not shown in Figure 1)are lower than those from the standardquestionnaire, because the experimentalquestionnaire generated higher reports ofper capita expenditure. However, they alsoshow rising HCRs from the 52nd throughthe 54th Rounds, and the increase continuesinto the 55th Round if we use comparablereporting periods from that round.Based on the experimental questionnaire,a case could be made that the all-IndiaHCR has been rising since 1995-96 [Sen2000]. As we have seen, there are goodgrounds for distrusting the experimentalquestionnaire in the 55th Round, becauseof the juxtaposition of the seven-day recalland 30-day recall data for food-pan andtobacco. Quite likely, the ‘reconciliationeffect’ (see Section I.1) pulled down theestimates of per capita expenditure fromthe experimental questionnaire, thus exaggeratingpoverty by this count. Even so,if poverty were genuinely falling, there isno obvious explanation why the experimentalquestionnaire should show a risein poverty from 1995 through 1998.The Planning Commission has neverendorsed poverty counts from the thinrounds. In part, this has been because ofthe smaller sample sizes. The PlanningCommission needs estimates of HCRs, notjust for all-India, but for individual states,and the thin rounds are not large enough tosupport accurate estimates for some of thesmaller (of the major) states. But inadequatesample size generates variance,not bias, and in any case, the thin roundsample sizes are perfectly adequate togenerate accurate estimates for the all-India HCRs. The discrepancies in Figure 1cannot be explained by inadequatesample sizes.There are other differences between thickand thin rounds. For example, the samplingframe for the 51st, 53rd, and 54thRounds was not the census of population,but the ‘economic’ census. In the populationcensus, each household is asked ifit has a family business or enterprise, andonly such households are included in thefirst-stage sampling from the economiccensus when ‘first-stage units’ are drawnwith probability proportional to size. Thismeans that a village with few or no suchhouseholds has only a small or no chanceof being selected as a first-stage unit. Evenso, when the team reaches the village, allhouseholds are listed and have a chanceof being in the sample, so it is unclear thatthis choice of frame makes much difference.Indeed, comparison of various socioeconomicindicators (e g, literacy rates,years of schooling, landholding, or familysize) from the surveys suggests no obviousbreaks between the 51st and 53rd Roundson the one hand, and the 52nd Round(which used the population census) on theother. Conversations with NSS and PlanningCommission staff sometimes suggestthat there may be other (non-documented)differences in the sampling structure of thethin rounds. Certainly, a tabulation of thepopulation sizes of the first-stage unitsshows that the 52nd Round containedrelatively few large units compared withthe 51st, 53rd, 54th, and 55th rounds; thisis a different issue from the use of theeconomic rather than population census(both the 52nd and 55th Rounds use thelatter), and the finding suggests that thefirst-stage units in the 52nd Round wereselected differently from other rounds insome way that is not documented. Moreover,the measurement of consumption isnot the main purpose of any of these thinrounds, all of which have some otherobjective, so it is possible that consumptionis not so fully or carefully collectedas in the quinquennial rounds.In short, there are grounds for scepticismabout the validity of the thin rounds forpoverty estimation purposes, and this is allthe more so if we remember that aside fromindicating no poverty decline in the latenineties, the thin rounds also suggest thataverage per capita expenditure was stagnatingduring that period – something thatis very hard to reconcile with other evidence.Having said this, we have not beenable to identify any ‘smoking gun’ thatwould point to a specific problem with anyof these rounds and explain their apparentlyanomalous poverty estimates. Untilthat puzzle is resolved, we see the evidencefrom the thin rounds as casting a shadowof doubt over the interpretation of thepoverty estimates presented earlier in thispaper. Perhaps the thin rounds in the nextfive years will offer some useful clues.VBeyond Poverty IndexesThe decline of poverty in the nineties,as captured in the indicators examined sofar, can be seen as an example of continuedprogress during that period. Whether therate of progress has been faster or slowerthan in the eighties is difficult to say, andthe answer is likely to depend on how therate of progress is measured. There is, atany rate, no obvious pattern of “acceleration”or ‘slowdown’ in this respect.It is important to supplement the evidencereviewed so far, which essentiallyrelates to purchasing power, with otherindicators of well-being relating, for instanceto educational achievements, lifeexpectancy, nutritional levels, crime rates,and various aspects of social inequality.This broader perspective reveals that socialprogress in the nineties has followedvery diverse patterns, ranging from acceleratedprogress in some fields to slowdownand even regression in other respects.The point is illustrated in Figure 7,where simple measures of the progress ofdifferent social indicators in the ninetiesare compared with the correspondingachievements in the eighties.Elementary education provides an interestingexample of accelerated progress inthe nineties. 46 This trend is evident notonly from census data on literacy rates, butalso from National Family Health Surveydata on school participation. To illustrate,school participation among girls aged 6-14jumped from 59 per cent to 74 per centbetween 1992-93 and 1998-99. 47 The regionalpatterns are also instructive. It isparticularly interesting to note evidence ofrapid progress in Madhya Pradesh andRajasthan, demarcating them clearly fromBihar and Uttar Pradesh, the other twomembers of the so-called BIMARU set. 48There is an important pointer here to therelation between public action and socialachievements. Indeed, Madhya PradeshEconomic and Political Weekly September 7, 2002 3743
Page 5 and 6: eal terms, with updating on the bas
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Page 10 and 11: nineties. 28 Thus, real agricultura
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Page 20: Institute for Human Development (20

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