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Price Trends in India and Their Implications for Measuring Poverty

National Sample Survey data on the unit values of a large number of foods can be used to compute price index numbers that can be compared with the official national price indices, the Consumer Price Index for Agricultural Labourers for rural India, and the Consumer Price Index for Industrial Workers for urban India. This paper finds that over the five years from 1999-2000 to 2004-05, the food component of the cpial understated the rate of food price inflation. This understatement can be attributed to the use of long outdated weights (from 1983), and the resultant over-weighting of cereals, whose prices fell relative to other foods. The overall weight of food in the cpial is also too large, so that the growth in the general cpial was understated during this period when food prices fell relative to non-food prices. Under conservative assumptions, the paper calculates that the five-year growth in the reported cpial of 10.6 per cent should have been 14.3 per cent. The nominal poverty lines are also understated. As a result, and ignoring other problems with the counts, the official poverty ratio of 28.3 per cent for rural India in 2004-05 should be closer to 31 per cent; at current rates of rural poverty reduction, this eliminates more than three years of progress.

SPECIAL ARTICLEfebruary 9, 2008 EPW Economic & Political Weekly42National Institute of Rural DevelopmentADVT
SPECIAL ARTICLEEconomic & Political Weekly EPW february 9, 200843I am grateful for comments and assistance to Montek Singh Ahluwalia, K L Datta, Jean Drèze, Himanshu, Reetika Khera, Rinku Murgai, Abhijit Sen, Pronab Sen, Suresh Tendulkar, and Thu Vu. The views expressed here are entirely my own.Angus Deaton( is at the Woodrow Wilson School of Public and International Affairs and the economics department of Princeton University.Price Trends in India and Their Implications for Measuring PovertyAngus DeatonThe purpose of this paper is to compare the behaviour over time of the food components of the official Indian price indexes, the Consumer Price Index for Agricultural Labourers (CPIAL) and the Consumer Price Index for Industrial Workers (CPIIW) with food price indexes based on the unit values of foods collected in the various rounds of the National Sample Survey (NSS). This comparison is of interest in its own right, partly to check the official numbers – the CPIAL andCPIIW are important price indexes with many uses – and partly to investi-gate the strengths and weaknesses of using the unit value data to construct price indexes. My findings indicate that if the survey numbers are correct, the rate of inflation in food prices from 1999-2000 to 2004-05 was almost 70 per cent higher than shown by the food component of theCPIAL, a finding that is at least in part attributable to over-weighting of cereals within the CPIAL food index. Over the same period, inflation in the overall (general) CPIAL index appears to be understated by a little more than 40 per cent, in part because of the understatement of its food component, and in part because theCPIAL attaches a weight to food that is almost 9 percentage points too high, so that when food prices rise less than other prices, as happened between 1999-2000 and 2004-05, the general index rises too slowly. Errors in the CPIIW are in the same direction, but are much smaller. One of the many roles of the CPIAL andCPIIW price indexes is in measuring poverty rates. Indian poverty lines are held constant in real terms, and are updated over time using versions of the CPIAL andCPIIW that are re-weighted to reflect the higher than average share of food among those close to the poverty line; more precisely, and according to the recommendations of a 1993 Expert Group, government of India (1993), the food and non-food components of the two indexes are re-weighted using average food shares of households near the poverty line in 1973-74, shares that are very much larger than the food shares of households near the poverty line in recent years. The nominal poverty lines so calculated are then used to calculate the fractions of people living in households with reported nominal per capita expendi-tures that fall below the lines. Any errors in the components of the CPIAL or CPIIW carry through into the estimated poverty rates. When I update the all India rural poverty line to match my revised price indexes, bur retaining the expert group’s weights for food and non-food, the rate of rural poverty in 2004-05 is increased from the official figure of 28.3 per cent of the popula-tion to 31.1 per cent of the population, an increase of 2.8 percent-age points. When I replace the expert group’s food shares for National Sample Survey data on the unit values of a large number of foods can be used to compute price index numbers that can be compared with the official national price indices, the Consumer Price Index for Agricultural Labourers for rural India, and the Consumer Price Index for Industrial Workers for urban India. This paper finds that over the five years from 1999-2000 to 2004-05, the food component of the CPIAL understated the rate of food price inflation. This understatement can be attributed to the use of long outdated weights (from 1983), and the resultant over-weighting of cereals, whose prices fell relative to other foods. The overall weight of food in the CPIAL is also too large, so that the growth in the general CPIAL was understated during this period when food prices fell relative to non-food prices. Under conservative assumptions, the paper calculates that the five-year growth in the reportedCPIAL of 10.6 per cent should have been 14.3 per cent. The nominal poverty lines are also understated. As a result, and ignoring other problems with the counts, the official poverty ratio of 28.3 per cent for rural India in 2004-05 should be closer to 31 per cent; at current rates of rural poverty reduction, this eliminates more than three years of progress.
SPECIAL ARTICLEfebruary 9, 2008 EPW Economic & Political Weekly44households near the poverty line with more recent poverty-line food shares, the poverty headcount ratio rises a further one percentage point, to 32.1 per cent of the population. A disaggre-gated, state by state analysis, which comes closer to replicating the Planning Commission’s own calculations, suggests a somewhat smaller discrepancy with the official poverty rates too low by 2.7 percentage points once all adjustments are made; at current rates, this is equivalent to the removal of more than three years worth of rural poverty reduction. Because food prices have fallen relative to non-food prices since 1999-2000, the use of outdated weights, which overstate the fraction of the budget spent on food, even for those near the poverty line, effectively short-changes the poor by assigning to them a price index that rises less rapidly than the cost of living based on their actual expenditure patterns. It is important to emphasise that this paper addresses only one of the many problems besetting the current Indian poverty lines. While the poverty lines are certainly affected by possible errors in measured inflation, they are also based on a set of state and sectoral price indexes that are at best outdated, and at worst simply incorrect. Beyond that, India’s poverty measures, like those of many other countries, are threatened by the effects of the long unresolved and still increasing discrepancy between the surveys and the national accounts [Deaton 2005].Survey-based price indexes have been calculated a number of times in the past. Recent examples are Deaton and Tarozzi (2006), who calculated price indexes for 1993-94 relative to 1987-88, and Deaton (2005) who updated the estimates to include the 55th round data for 1999-2000. For those two comparisons, rural and urban rates of inflation in Laspeyres price indexes based on food and a few other items (tobacco, alcohol, and some fuels) were very similar to the overall rates of inflation in the all-India CPIAL andCPIIW indexes. The period since 1999-2000, particularly from the end of 1999 to early 2001, was unusual in recent Indian history in that food prices were either stationary (CPIIW) or falling (CPIAL). The task of comput-ing price indexes is more difficult in such a period than in a period when the individual prices are dominated by a common upward trend. When each price is the sum of a common trend and an idiosyncratic component, the latter is readily identified and robustly measured, in spite of measurement error or uncer-tainty about the choice of weights. The same is not true in the absence of the trend. So the recent period is a particularly impor-tant one in which to check the official indexes. It should also be noted that, in recent years, there have been pronounced changes in Indian consumption patterns, with food becoming less impor-tant, and cereals becoming less important within food. At such times, regular updating of weights becomes important for price indexes, especially when the relative price of foods and non-foods has changed. In Section 1, I explain the general procedures and the use of the survey data. In Section 2, I compare the all India CPIAL and CPIIW indexes over time, focusing on the periods 1983, 1987-88, 1993-94, and 1999 to mid-2005, which are the dates covered by the 38th, 43rd, 50th, and 55th through 61st rounds of the NSS. In contrast to the earlier periods, the food component of the CPIAL rises less rapidly than the surveys show should be the case; from 1999-2000 to 2004-05, the price index of food-based on what rural households report having paid rose by 4.5 percentage points more than did the food component of the CPIAL. Since there was little increase in food prices over this period, and if the survey numbers are to be treated as correct, the true rate of rural food price inflation from 1999-2000 to 2004-05 was two-thirds as high again as shown in the official statistics. The urban differ-ence is in the same direction but much smaller. The surveys do not provide prices for non-foods, so I combine the inflation rates from the survey-based food price indexes with the inflation rates in the non-food component of the CPIAL. Because the weightof food in theCPIAL is less than one, the gap between the survey-based andCPIAL food indexes is diminished in the general index, but this is offset by the fact that theCPIAL assigns too large a weight to food in a period when food prices have risen less thannon-food prices. As a result, the increase in the general CPIAL is understated by almost as much as is the increase in its food component.Section 3 discusses the implications of the price indexes for the measurement of poverty, first using a short-cut All India methodology, and then state by state for the 17 largest states. 1 MethodsI use data from the most recent “large” NSS rounds, the 38th in 1983, the 43rd in 1987-88, the 50th in 1993-94, the 55th in 1999-2000, and the 61st in 2004-05, together with the smaller rounds 56 through 60, which fill in the period from mid-2000 to mid-2004. The 56th round ran from July 2000 to June 2001, the 57th from July 2001 to June 2002, the 58th from July 2002 to December 2002, the 59th through the calendar year 2003, and the 60th from January to June 2004. In each of these surveys, using questionnaires that have varied over time, but were close to identical from the 55th through the 61st rounds, a single house-hold respondent provides details of food purchases – both expen-ditures and physical quantities – on several hundred items. The ratio of expenditure to quantity provides a measure of price paid per unit for each good purchased by each household, and it is these “unit values” that I combine into food price indexes. Since I am working with prices over time, I compute chained indexes, so that each (large) survey provides the weights for the price index comparing it to the subsequent survey; for the “thin” rounds, 56 through 60, as for the 61st round itself, I use weights from the 55th round. Although changes in the questionnaire design have typically been incremental – an exception is the 50th round which was unique in distinguishing every possible good that might ever have been sold through the public distribution system (PDS) – the differences accumulate over time, so that the lists of foods in the 38th and 61st rounds have substantial differences. Chaining helps deal with this by comparing like with like and maximises comparability over time. It is also generally recommended because it allows adaptation to changing spending patterns over time. Indian consumption patterns have shown major changes over the last 25 years – food is less important in the overall budget, and cereals are less important within food – so that it makes little sense to measure current

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SPECIAL ARTICLEfebruary 9, 2008 EPW Economic & Political Weekly46poverty line excluded in principle, it is important to allow for the effects on the prices paid by consumers. For example, if rice from thePDS sells for Rs 5 per kilo, when the market price is Rs 11, but a substantial number of households are excluded from the former and shifted to the latter, the effective price rises, even though neither the PDS nor market price has changed. In order to accom-modate this, I calculate a single price each for wheat, rice, and sugar, calculated as a weighted average, weighted by mean shares on PDS and market, of the median prices in the PDS and the market. The official CPIAL uses a similar procedure, though it collects data on availability from the same fair price shops used to sample prices, rather than from households, and it is unclear from where they obtain data for market purchases, see govern-ment of India (1996). 2 All India Comparisons of Food IndexesTable 1 shows urban and rural chained Laspeyres food price indexes from the surveys in comparison to the food components of the CPIAL and the CPIIW. I have arbitrarily taken the 55th round (1999-2000) as 100, and scaled the other indexes to match. Note that this does not contradict the chaining for the survey-based indexes, where the 38th is base for the 43rd, the 43rd for the 50th, the 50th for the 55th, and the 55th for the later surveys. Up to 1999-2000, the survey-based and official food price indexes closely match one another; relative to 1999-2000, the two rural indexes were 28.16 per cent (survey) and 28.03 per cent (CPIAL), while the two urban indexes were 25.22 per cent (survey) and 25.09 (CPIIW). After 2000 things are different. Note first that rural food prices were lower in 2000-01 compared with 1999-2000, for both the CPIAL and the survey index; according to the monthly data for the CPIAL food index, the fall began at the end of 1999 and continued until early 2001. The food component of the CPIIW is only slightly higher in 2000-01 than in 1999-2000, by 0.8 per cent, and the monthly data show a fluctuating series without trend during the period from end 1999 to early 2001. During this time, the survey-based food price index does not decline by as much as does the food component of the CPIAL, to only 98.77 compared with 95.33 per cent, opening up a more than three point difference between the two indexes. By the 61st round, in 2004-05, this gap is nearly five points, with an additional widening between the two series in early 2004. Because food price inflation was gener-ally low from 1999-2000 to 2004-05, 6.7 per cent according to the CPIAL, and 11.2 per cent according to the survey-based indexes, the discrepancy is very large in ratio terms, with the survey-based index showing a rate of food price inflation that is two-thirds higher.For the urban price indexes, the gap is originally in the opposite direction, with the survey-based index, like its rural counterpart, showing a small decline in prices, compared to a small increase in the food component of the CPIIW. By the end of the period, and comparing 2004-05 with 1999-2000, the two series are very close, 113.9 for the survey index relative to 112.9 for the food component of the CPIIW. I have only limited information on the construction of the CPIAL andCPIIW, and in particular do not have access to the raw price information on which they are based. In consequence, I can only speculate about the sources of the discrepancies between them and the survey-based indexes shown here. The most obvious candidate is the use of outdated weights. The CPIAL is based in 1986-87, and uses weights from the 38th round of the NSS, which refers to calendar year 1983. The most notable change in expen-diture patterns since 1983 is the fall in the share of cereals in total expenditure; averaged over households, rice and rice products took up 21.0 per cent of the rural budget in 1987-88, but only 16.1 per cent in 1999-2000 (which may be an overestimate), and indeed the share has fallen to 13.2 per cent in 2004-05. The corre-sponding declines are 9.2 per cent (1983), 7.3 per cent (1999-2000), and 6.6 per cent (2004-05) for wheat, and 7.7 per cent (1983) to 2.3 per cent (1999-2000), and 2.0 per cent (2004-05) for coarse cereals and their products. As to rural price changes between the 55th and 56th rounds, which is one period in which the indexes diverge, the median price paid for rice held steady at Rs 10 per kilo, while that for wheat fell from Rs 7.5 to 7.0, with more substantial falls for coarse cereals, from Rs 7 to Rs 6 for bajra, jowar, and barley, and from Rs 6 to Rs 5 for maize. Given that the foodCPIAL index uses a weight for coarse cereals that is almost four times as large as it ought to be, it substantially overstated the fall in prices between the two rounds. The effect is smaller in the CPIIW, because even in the early 1980s, only a small fraction of the budget was spent on coarse cereals (2.4 per cent in 1983), but I do not have a full explanation of why the two pairs of indexes behave so differently in rural and urban areas. The use of outdated weights is unlikely to be the whole story, however. The fifth and sixth columns of Table 1 present Laspeyres indexes for the disputed period, using the same survey prices as in the chained indexes, but using constant 38th round (1983) weights throughout. If weighting is the problem, the rural version of this index should look more like the foodCPIAL than does the chained index in the first column, which is indeed what the table shows. The re-weighting, from 1999-2000 to 1983 weights, resolves most but not all of the difference between the survey-based food index and the food component of the CPIAL. In the Table 1: Food Price Indexes, All-India, 1983 to 2004-05 (1999-2000 = 100) Rural India Urban India 1983 (38th Round) WeightsRound Dates Survey-basedCPIAL Survey-based CPIIW Rural Urban Food Index Food Food Index Food38 January to December 1983 28.16 28.03 25.22 25.09 27.95 26.3843 Jul y 1987 to June 1988 36.52 35.29 34.16 34.87 – – 50 Jul y 1993 to June 1994 63.82 62.50 61.47 62.17 – –55 Jul y 1999 to June 2000 100 100 100 100 100 10056 July 2000 to June 2001 98.77 95.33 98.81 100.80 98.10 98.7457 Jul y 2001 to June 2002 101.71 96.89 101.57 104.03 99.75 100.9758 July 2002 to December 2002 105.40 100.19 106.56 107.24 103.44 105.4059 January to December 2003 104.58 102.68 106.60 108.88 102.21 105.2760 January to June 2004 109.35 103.53 109.51 110.38 106.52 108.0061 July 2004 to June 2005 111.21 106.67 113.90 112.88 108.49 112.44The survey based food indexes are chained Laspeyres indexes, using the large rounds (38, 43, 50, and 55) as base to calculate price levels in each subsequent round. For Rounds 56 through 61, the 55th round is used as base. The food components of the CPIAL and CPIIW are calculated by averaging monthly values over each round, and then scaling to be 100 in the 55th round. I was unable to locate the monthly CPIIW food indexes for July 1983, for August through November 1987, and for June 1988; these missing values were replaced by linear interpolation. The series was complete for all rounds from the 50th on. Columns (5) and (6) are rural and urban Laspeyres indexes using the unit values from the surveys but based on 38th round weights and scaled to be 100 in 1999-2000. The last two columns show indexes from 55th to 61st round with chaining throughout, so that the 55th provides the weights for the 56th, the 56th for the 57th, and so on.


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SPECIAL ARTICLEfebruary 9, 2008 EPW Economic & Political Weekly480.6207. The weight of food in the CPIAL is 0.6915 – because the CPIAL uses a 1983 food share – so that the second term is also positive. Taking all terms together, I finish up with a general CPIAL of 110.6 – from the official statistics – and a corrected general survey-based index of 114.3. As is to be expected, the corresponding correction to the generalCPIIW is smaller, from 121.1 (official) to 122.2 (survey-based).Three Reasons There are three reasons why these corrections to the general indexes are likely to be understated. The first is the chaining argument already given; I stop chaining my survey-based indexes in 1999-2000, so that they take no account of changes in demand patterns in the subsequent five years. The second argument notes the general supposition that the unique questionnaire in the 55th round resulted in exaggerated 30-day reports of food. If so, the resulting food weight, which I use to combine the survey-based food index with the official non-food indexes, is too high. Substi-tution of a lower food weight would cause further divergence between the survey-based and official indexes. Third, the food weights from the 55th round that I use are democratic weights, computed by averaging each household’s food share. The CPIAL, by contrast, uses a plutocratic weight from the 38th round, which is the ratio of average food expenditure to average total household expenditure. According to my calculations the plutocratic food share in 1983 was 66.1 per cent (reasonably close to the 69.2 per cent weight in the CPIAL), whereas the democratic food share was 70.3. In the 55th round, my democratic weight is 62.1 per cent, whereas the plutocratic weight is 53.8 per cent the use of which would raise the survey-based general index from 114.3 to 115.0. 3 Price Indexes and Measurement of PovertyIndian poverty estimates are calculated using a set of poverty lines, one for each state and each sector. These were proposed by the 1993 Expert Group, and are held fixed in real terms. From one large round to another, they are updated in nominal terms by a set of price deflators that are based on the state-specific CPIIW andCPIAL indexes. In order to make these indexes more relevant for people living near the poverty line, the food and non-food components of each index are re-weighted using weights that are listed in the Expert Group report. These are calculated from the 1973-74 round of the NSS, so that they are even more outdatedthan the weights in theCPIIW andCPIAL themselves, though they do have the advantage of being explicitly tailored to expenditure patterns near the poverty line. Even so, overweighting the share of food in a period where food prices are declining relative to other prices does no favour to people near the poverty line, because it leads to an underestimation of the increase in their cost of living.I start with illustrative calculations based on the all-India poverty lines. These lines are “implicit” lines, which are defined as those all-India urban and rural lines which, when applied to all households in each sector, lead to the all-India headcount ratios that have been calcu-lated by aggregating the state by state estimates. I shall reproduce something like the official calculations below, but start with the simpler calculation using the two all-India lines. Since there is little evidence of problems with price indexes prior to 1999-2000, I use the two poverty lines for the 55th round, which are 327.56 for rural and 454.11 for urban. Table 3: Price Indexes 2004-05 vs 1999-2000, Poverty Lines and Headcount Ratios in 2004-05: Rural IndiaState Survey-Based CPIAL Survey-Based CPIAL Official Headcount HCR Official HCR Adjusted HCR Adjusted Food Index Food General Index Poverty Lines Ratio Official Recalculated Food Price Food Price Index IndexandWeight (1) (2) (3) (4) (5) (6) (7) (8) (9)Jammu and Kashmir 109.0 102.7 113.5 107.8 391.26 4.3 4.3 5.9 6.4Himachal Pradesh 108.6 104.1 113.3 110.5 394.28 10.5 11.1 12.5 13.4Punjab 114.9 112.9 113.9 112.9 410.389.0 8.9 9.4 9.3Haryana 115.0112.7117.0115.2414.7613.213.514.214.3Rajasthan 103.8 106.5 110.2 111.6374.57 18.319.117.419.2Uttar Pradesh 108.7 107.3 113.6 111.9 365.84 33.3 34.1 34.9 36.7Bihar 105.9 103.6 111.0108.0 354.3642.643.245.147.0Assam 105.3 102.2 110.4 107.5 387.64 22.1 22.8 24.5 25.1West Bengal 107.5 104.1 114.4 109.7 382.82 28.4 28.2 30.9 32.6Orissa 97.695.7 105.3 101.2 325.79 46.9 46.9 48.351.0Madhya Pradesh 106.3 101.8 109.9 105.5 327.78 36.8 36.6 39.4 40.7Gujarat 115.8 108.3 118.5 112.9 353.9318.9 19.222.823.1Maharashtra 112.3111.1116.8115.3362.2529.629.730.431.6Andhra Pradesh 108.6 110.0 111.2 112.1 292.95 10.5 10.4 10.0 10.3Karnataka 105.2 101.3 110.8 107.6 324.1720.7 109.1116.8106.7112.4430.1213.212.710.210.1Tamil Nadu 110.9 111.5 115.6 115.1 351.86 23.0 22.9 22.7 23.6All India 111.2 106.7 114.3 110.6 356.30 27.3 27.6 28.7 30.0The survey based food index is calculated state by state according to the procedures described in the text. The all India number is taken from Table 1. The CPIAL food is calculated as the ratio of the averages of the monthly indexes for the 55th and 61st round. The CPIAL is the general index, again calculatedas the ratio of the averages of the monthly indexes for the two rounds. The survey-based general index is a weighted average of the survey-based food index and the non-food componentof the CPIAL, where the weights are the average food share over households in each state in the 55th round; it is my current best estimate of what an updated general CPIAL should be. The poverty lines are the official poverty lines for the 61st round.The official headcount ratios are my calculations of the fractions of persons in poverty using the official poverty lines; they differ slightly from the official calculations. The recalculated official headcount ratios are based on the 55th round poverty lines updated by my calculation of the price indexes used for the updating by the Planning Commission; there are reweighted versions of the CPIAL food and non-food using a set of food weights from the 1973B4 NSS and taken from the 1993 expert group report, Table AIV.1. The recalculated headcount ratios are typically close to the official ones. The first adjusted headcount ratios also use the 55th round poverty lines, and follow the expert group procedure as above. However, instead of using the food index of the CPIAL they use the survey-based food index in the first column.The second adjusted headcount ratios follow the same procedure, using the survey-based food index, but instead of the Expert Group food weights from 1973B4, they use the food shares at the poverty line calculated from the 55th round.Given that the food shares in the 55th round are likely to beoverstated, and given that food prices have fallen relative to non-food prices, this procedure is conservative; lower food shares would generate higher headcount ratios.The final row of the table, for all-India, does not always correspond in any obvious way to the entries for the states. In column (1), the all India survey-based index uses median unit values and average budget shares from all households, including those not residing in states in the table. Columns (2) and (4) show the all-India CPIAL food and general indexes, and column (3) is computed by combining the survey-based food price index with the non-food component of the CPIAL. The all India poverty line is calculated indirectly by finding the line which, when applied to the whole population, gives the same poverty rate as that obtained from combining the poverty rates for the individual states, including those not covered in the table. The all India implicit price index is the ratio of the all India poverty lines for the 61st and 55th rounds. The all-India adjusted poverty line in column (7) is the official all India poverty line multiplied by the ratio of the all India general CPIAL to the all India general survey-based index. The all-India poverty rate in the second to last column is from the official data, while the adjusted figure in the final columns is the weighted average over the states in the table; the population of these states comprises 92.4 per cent of the population of rural India.
SPECIAL ARTICLEEconomic & Political Weekly EPW february 9, 200849Starting with the rural line, my calculation of the Expert Group’s re-weighting of the CPIAL leads to an index of 1.091 from 55th to 61st round, see Table 2, which gives an all-India poverty line of 1.091 times 327.56 which is 357.37, close to the 356.30 which is the all-India implicit poverty line for the 61st round. The “official” poverty rate according to my calculation is 28.5 per cent, close to the true official figure of 28.3 per cent. (All calculations and official figures for comparison are based on the 30-day uniform recall period.) If I repeat this calculation, again follow-ing the expert group procedure, and using their weights for food and non-food, but replacing the food component of the CPIAL with the survey-based food index, the price index for updating the lines is 112.7, and the poverty rate rises to 31.1 per cent. Even this takes no account of the overestimation of the food share of the poor, set at 81.28 per cent. Using the 55th round data, I regressed the share of food on the logarithm of household per capita total expenditure and its square, and used the resulting equation to predict food shares at the 55th round poverty line. This gives a food share of 65.08 per cent; even the poor have reduced the share of their budget devoted to food over the quarter century between 1974-75 and 1999-2000! When I use 65.08 in place of 81.28, and the survey-based food index in place of the CPIAL food index, the updating index rises to 114.1, and the estimated poverty rate rises to 32.5 per cent of the population, a full four percentage points higher than my replication of the official rate. It should be noted that, even if there remain unresolved questions about the sources of the differences between the survey-based food price index and its CPIAL equivalent, there can be little defence for a poverty calculation that overstates by 16 points the food share of people at the poverty line, and thus understates the increase in the cost of living that they have recently faced.As with the price indexes, the urban corrections are much smaller. My recalculation of the urban poverty-line price index is 117.70, which gives a 61st round all-India urban poverty line of 117.70 times 454.11, which is 534.49, compared with 538.6 in the official publications. This gives an urban poverty rate of 25.11 per cent, compared with the published rate of 25.62 per cent. Substi-tuting the survey-based index for the CPIIW food index raises this to 25.58 per cent, and using both the survey-based index and the food share at the poverty line in the 55th round gives 26.86 per cent. Comparing this last with my version of the official count shows an underestimation of poverty in the latter by 1.75 percentage points.These shortcut calculations are best treated as illustrative because the official procedures work at the state level, deriving the all-India estimates by aggregation. Here I repeat the calcula-tions above for the 17 largest states, focusing entirely on the rural sector where the potential discrepancies are largest. The state by state calculations are of interest in their own right, and as we shall see the understatement of food inflation is replicated in most but not all states, and the size of the discrepancy varies from state to state.The calculations are laid out in Table 3 (p 48). The first two columns show the survey-based and CPIAL food price indexes for 2004-05 relative to 1999-2000 for each of the 17 largest states, as well as the all-India numbers previously discussed. In all states except Rajasthan, Andhra Pradesh, Kerala, and Tamil Nadu, the survey-based food price increase was larger than indicated by the state version of the CPIAL food index. In five states, Jammu and Kashmir (6.3 per cent), Himachal Pradesh (4.5 per cent), Madhya Pradesh (4.5 per cent), Gujarat (7.5 per cent), and Karnataka (3.9 per cent), the differences between the two indexes are substan-tial. The next two columns show the general CPIAL and the survey-based general index. The latter is calculated from the former and from the first two columns using equation (4) and the state by state average food shares from the 55th round survey as well as the weight of food in each state’sCPIAL. The official poverty lines are listed in the next column, followed by the official poverty rates and my recalculations of them. As before, I start from the 55th round poverty lines, and update following the Expert Group methodology using their state by state weights to combine the food and non-food components of theCPIAL. My versions of the official poverty rates are not identi-cal to those published by the Planning Commission and shown in the previous column, but they are close, and their average over the 17 states, weighted by state populations, is 27.6 per cent, as opposed to 27.3 per cent. The last two columns make two different adjustments. In the first, I substitute the state survey-based food index in column (1) for the CPIAL food index for the state, but otherwise maintain the Expert Group procedures. This shows the effect of recalcu-lating the food index, but without reweighting. The all-India headcount ratio rises from 27.6 per cent to 28.7 per cent, and the state ratios mostly rise, except for the four states where the survey-based food index is lower than the foodCPIAL. The last column shows the effects of modifying not only the food price index, but also the poverty line weights, substituting the pover-ty-line food shares for each state in the 55th round – calculated as above, but state by state – for the outdated weights used in the deflators for the official poverty lines. This takes the all-India headcount rate up to 30.0 per cent, an increase of 2.4 points from the base. Note that this increase is a good deal less than by the shortcut method, because the effects of the adjustments are different in different states, which have widely different headcount ratios. ReferencesDeaton, Angus (1997): The Analysis of Household Surveys: A Microeconometric Approach to Development Policy, (World Bank). (2003): ‘Prices and Poverty in India, 1987-2000’,Economic & Political Weekly, January 25, pp 362–68.– (2005): ‘Measuring Poverty in a Growing World (or Measuring Growth in a Poor World)’,Review of Economics and Statistics, 87(1), pp 1-19.Deaton, Angus and Alessandro Tarozzi (2005): ‘Prices and Poverty in India’ Chapter 16 in Angus Deaton and Valerie Kozel,The Great Indian Poverty Debate, MacMillan, New Delhi.Deaton, Angus, Jed Friedman, and Vivi Alatas (2004): ‘Purchasing Power Parity Exchange Rates from Household Surveys’, Research Programme in Develop-ment Studies, Princeton University, processed.Government of India (1993):Report of the Expert Group on Estimation of the Propor-tion and Number of Poor, Planning Commission, New Delhi.– (1996): Consumer Price Index for Agricultural Labourers in India: A Compendium, Ministry of Labour, Shimla/Chandigarh.– (2007): ‘Poverty Estimates for 2004-05’, Press Information Bureau, New Delhi, March 21.

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