Poverty and Inequality in India: a Reexamination - Princeton University

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for questionnaire design and for price indexes.Table 1b gives the correspondingpoverty-gap indexes.As the first two rows of each panelindicate, the official estimates are quitemisleading in their own terms: the 1999-2000 poverty estimates are biased downwardby the changes in questionnairedesign. For headcount ratios, the estimatesadjusted for changes in questionnairedesign ‘confirm’ about two-thirds of theofficial decline in rural poverty between1993-94 and 1999-2000, and about 90 percent of the decline in urban poverty. Forpoverty-gap indexes, the correspondingproportions (62 per cent and 77 per cent)are lower, especially for the urban sector.The fully-adjusted estimates in the lastrow of each panel show somewhat lowerrural poverty estimates and much lowerurban poverty estimates for 1999-2000than even the official estimates. Note,however, that because we are recalculatingthe poverty lines back to the 43rd Round,a good deal of the decrease took place inthe six years prior to 1993-94, not only inthe six years subsequent to 1993-94. Thefully-adjusted estimates for the headcountratios and poverty gap indexes suggest thatpoverty decline has been fairly evenlyspread between the two sub-periods (beforeand after 1993-94), in contrast withthe pattern of ‘acceleration’ in the secondsub-period associated with the officialestimates.The rural-urban gaps in the povertyestimates are also of interest. Looking firstat the base year (1987-88), the rural-urbangap based on adjusted estimates is muchlarger than that based on official estimates.Indeed, the latter suggest no differencebetween rural and urban poverty in thatyear. This is hard to reconcile with independentevidence on living conditions inrural and urban areas, such as a lifeexpectancygap of about seven years infavour or urban areas around that time. 15Our low estimate of the urban headcountratio relative to the official estimate (22.5per cent versus 39.1 per cent), and similardifferences in 1993-94 and 1999-2000,come from the fact that we take the ruralpoverty line in 1987-88 as our startingpoint, and peg the urban poverty linesabout 15 per cent higher than the ruralpoverty lines, in contrast to the much largerdifferentials embodied in the official lines.Figure 1 shows the new estimates of theheadcount ratios together with the officialestimates going back to 1973-74. The fullyadjusted figures are lower throughoutHeadcount ratio (per cent)6050403020Figure 1: Official and Adjusted Headcounts Ratios1970 1980 1990 2000YearSource: Planning Commission, Press Releases ( March 11, 1997, and February 22, 2001), Deaton (2001a,b), and Table 2a of this paper.because we treat the rural poverty line inthe 43rd Round as our baseline so that,with larger rural-urban gaps in the povertyestimates, we estimate lower povertyoverall. If instead, we had taken the urbanpoverty line as base, the adjusted figureswould have been higher than the officialfigures. From 1987-88 to 1993-94, theadjusted headcount ratio falls more rapidlythan the official headcount; this is becauseour price deflators are rising less rapidlythan the official ones. From 1993-94, theadjusted figures fall more slowly becausethe effects of the price adjustment are morethan offset by the correction for questionnairedesign. The estimates for the thinrounds – which look very different – areincluded to remind us of the residualuncertainty about our conclusions, andwill be discussed further in Section IV.3below.I.4 Regional ContrastsState-specific headcount ratios are presentedin Table 2a. 16 The table has thesame basic structure as Table 1a, exceptthat we jump straight from official to fullyadjustedestimates. The latter suggest thatthe basic pattern of sustained povertydecline between 1987-88 and 1999-2000,discussed earlier at the all-India level, alsoapplies at the level of individual states inmost cases. The main exception is Assam,where poverty has stagnated in both ruraland urban areas. In Orissa, there has beenvery little poverty decline in the secondsub-period, with the result that Orissa nowOfficial countsAdjusted countsThin roundshas the highest level of rural poverty amongall Indian states, according to the adjusted1999-2000 estimates. 17 Reassuringly, the‘anomalies’ noted earlier with respect torural-urban gaps in specific states tend todisappear as one moves from official toadjusted estimates.Table 2b shows the corresponding poverty-gapindexes. The general patterns arevery much the same as with headcountratios; indeed the PGI series are highlycorrelated with the corresponding HCRseries, with correlation coefficients of 0.98for rural and 0.95 for urban. Even the HCRand PGI changes between the 50th and55th Rounds are highly correlated; thecorrelation coefficient between changes inHCR and changes in PGI is 0.95 for therural sector, and 0.96 for the urban sector.Thus, in spite of its theoretical superiorityover the headcount ratio, the poverty-gapindex gives us very little additional insightin this case.In interpreting and comparing povertydeclines over time, it is useful to supplementthe poverty indexes with informationon the growth rate of average per capitaconsumption expenditure (hereafterAPCE). State-specific estimates of APCEgrowth between 1993-94 and 1999-2000are shown in Table 3, where states areranked in ascending order of APCE growthfor rural and urban areas combined. 18Here, a striking regional pattern emerges:except for Jammu and Kashmir, the lowgrowthstates form one contiguous regionmade up of the eastern states (Assam,Orissa and West Bengal), the so-called3734Economic and Political Weekly September 7, 2002
Figure 2: ‘Divergence’ of Per Capita Expenditure Across States, 1993-94 to 1999-00Average annual growth (per cent)6420BIORMPUPASKA200 300 400 500 600Source: Authors’ calculations using unit record data from the 50th and 55th Rounds of the National SampleSurvey.AI = All India; AP = Andhra Pradesh; AS = Assam; BI = Bihar; DE = Delhi; GU = Gujarat; HA = Haryana;HP = Himachal Pradesh; JK = Jammu and Kashmir; KA = Karnataka; KE = Kerala; MA = Maharashtra;MP = Madhya Pradesh; OR = Orissa; PU = Punjab; RA = Rajasthan; TN = Tamil Nadu; UP = Uttar Pradesh;WB = West Bengal.BIMARU states (Bihar, Madhya Pradesh,Rajasthan and Uttar Pradesh), and AndhraPradesh. The high-growth states, for theirpart, consist of the southern states (exceptAndhra Pradesh), the western states(Gujarat and Maharashtra) and the northwesternregion (Punjab, Haryana andHimachal Pradesh). Further, it is interestingto note that this pattern is reasonablyconsistent with independent data on growthrates of per capita ‘state domestic product’(SDP); these are shown in the last columnof Table 3. With a couple of exceptionson each side, all the states in the ‘lowAPCE growth’ set had comparatively lowrates of per capita SDP between 1993-94and 1999-2000 (say below 4 per cent peryear), and conversely, all the states in the‘high APCE growth’ set had comparativelyhigh annual growth rates of percapita SDP (the correlation coefficientbetween the two series is 0.45). 19This broad regional pattern is a matterof concern, because the low-growth statesalso tend to be states that started off withcomparatively low levels of APCE or percapitaSDP. In other words, there has beena growing ‘divergence’ of per capita expenditure(and also of per capita SDP)AIAPWBTNMAGURAHPHAKEJKPUGeometric mean PCE in 1993-94, rupees per headDEacross Indian states in the nineties. 20 Thepoint is illustrated in Figure 2, which plotsthe average growth in APCE for each statebetween 1993-94 and 1999-2000 againstthe geometric mean of APCE in 1993-94.It is worth asking to what extent theseregional patterns, based on APCE data, arecorroborated by regional patterns of povertydecline. One difficulty here is thatthere is no obvious way of ‘comparing’ theextent of poverty decline across states. Forinstance, looking at absolute changes in(say) HCRs would seem to give an unfair‘advantage’ to states that start off withhigh levels of poverty, and where theretends be a large number of householdsclose to the poverty line. To illustrate, theabsolute decline of the rural HCR between1993-94 and 1999-2000 was about twiceas large in Bihar (7.4 percentage points)as in Punjab (3.8 points), yet over the sameperiod APCE grew by only 6.9 per centin Bihar compared with 20.2 per centin Punjab, with virtually no change indistribution in either case. 21 The reasonfor this contrast is that Bihar starts off in1993-94 with a very high proportion ofhouseholds close to the poverty line, sothat small increases in APCE can producerelatively large absolute declines in theheadcount ratio.An alternative approach is to look atproportionate changes in HCRs or PGIs.These turn out to be highly correlated withthe corresponding growth rates of APCE.The point is illustrated in Figure 3, wherewe plot the proportionate decline in therural headcount ratio in each state againstthe growth rate of APCE in rural areas. Thecorrelation coefficient between the twoseries is as high as 0.91. This reflects thefact that poverty reduction is overwhelminglydriven by the growth rate of APCE,rather than by changes in distribution – weshall return to this point in Section III.From these observations, it follows that ifwe accept ‘proportionate change in HCR’(or PGI) as an index of poverty reduction,then the broad regional patterns identifiedearlier for the growth rate of APCE alsotend to apply to poverty reduction. Inparticular: (1) most of the western andsouthern states (with the important exceptionof Andhra Pradesh) have done comparativelywell; (2) the eastern region hasachieved very little poverty reductionbetween 1993-94 and 1999-2000; and(3) there is a strong overall pattern of ‘divergence’(states that were poorer to startwith had lower rates of poverty reduction).This reading of the evidence, however,remains somewhat tentative, since there isno compelling reason to accept the proportionatedecline in HCR (or PGI) as adefinitive measure of poverty decline.We end this section with a caveat. FromTable 2 and Figure 1, it may appear thatthe ‘pace’ of poverty decline in the ninetieshas been fairly rapid. It is important tonote, however, that the associated increasesin per capita expenditure have been rathermodest in most cases. For instance, thedecline of 6.6 percentage points in the all-India HCR (from 29.2 per cent to 22.7 percent) between 1993-94 and 1999-2000 isdriven by an increase of only 10.9 per centin average per capita expenditure – notexactly a spectacular improvement inliving standards. Similarly, Table 2a suggeststhat Bihar achieved a large step inpoverty reduction in the nineties, with therural HCR coming down from 49 per centto 41 per cent. Yet, as Table 3 indicates,average APCE in rural Bihar increasedby only 7 per cent between 1993-94 and1999-2000.Why are small increases in APCE associatedwith substantial declines in povertyindexes? It is tempting to answer that thedistribution of consumer expenditureEconomic and Political Weekly September 7, 2002 3735
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