1. Indian food puzzles: growth, poverty & (mal)nutrition Angus Deaton & Jean Drèze

2. Lots of growth Real GDP per capita growing at 3.6 percent a year since 1980 4.6 percent a year 00−04 Real per capita aggregate consumption growing at 2.0 percent in the 1980s, 2.6 percent in the 1990s, and 4.7 percent 00−04 Poverty reduction has been less than warranted by this growth rate if equally distributed Some increase in inequality Much more important are data inconsistencies Coverage differences, and outright discrepancies Survey consumption grows less rapidly than NAS consumption Errors on both sides Inconsistent survey instruments from year to year

3. Growth across the distribution NSS growth may be too low Generally some growth at all fractiles

4. Percentile10 th 25 th 50 th 75 th 90 th Rural 1983–1993/4 1999/00–2004.5 2000/01–2004.5 1.8 1.4 1.3 1.4 1.2 0.4 1.2 1.1 0.3 1.0 1.6 0.7 0.8 2.2 1.9 Urban 1983–1993/4 1999/00–2004.5 2000/01–2004.5 1.2 –0.6 –0.0 1.1 –0.4 –0.1 1.3 0.1 0.3 1.4 0.6 0.4 1.3 1.9 1.4 All India 1983–1993/4 1999/00–2004.5 2000/01–2004.5 1.7 1.3 1.1 1.4 0.9 0.3 1.2 0.8 0.3 1.1 1.0 0.9 1.1 1.7 1.5 Table 1: Growth by percentiles NSS data

5. But calorie consumption is falling YEARPCE (real)CaloriesProteinFats RuralUrbanRuralUrbanRuralUrbanRuralUrban 1983 1987–8 1993–4 1999–0 2000–1 2001–2 2002(2) 2003 2004(1) 38 43 50 55 56 57 58 59 60 142.5 157.7 159.9 179.3 185.3 182.2 189.0 192.4 194.7 230.7 245.7 264.9 306.4 311.1 301.8 318.2 314.4 315.3 2,240 2,233 2,153 2,148 2,083 2,018 2,025 2,106 2,087 2,070 2,094 2,073 2,155 2,027 1,982 2,014 2,020 2,036 63.5 63.2 60.3 59.1 56.8 54.8 55.4 58.0 56.9 58.1 58.6 57.7 58.4 55.3 54.2 54.9 55.5 56.0 27.1 28.3 31.1 36.0 34.6 33.6 34.7 36.4 35.6 37.1 39.3 41.9 49.6 46.1 47.0 46.7 47.1

6. Is this really correct? Data from National Nutritional Monitoring Bureau Rural (nine states) 1975-791988-901996-972000-012004-05 Energy2,3402,2832,1081,9541,907 Protein62.958.453.750.748.8 Note: Andhra Pradesh, Gujarat, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Orissa, Tamil Nadu, and West Bengal. 1988-90 and 1996-97 estimates exclude Madhya Pradesh and West Bengal. The 2004-05 figures exclude Gujarat..

7. Fall is clearest for cereals YearCerealsAll foods RuralUrbanAll IndiaRuralUrbanAll India 1983 1987–8 1993–4 1999–0 2000–1 2001–2 2002(2) 2003 2004(1) 1,681 1,648 1,533 1,455 1,422 1,391 1,381 1,412 1,419 1,303 1,296 1,231 1,200 1,161 1,130 1,137 1,142 1,165 1,596 1,569 1,458 1,392 1,357 1,330 1,318 1,345 1,357 2,240 2,233 2,153 2,148 2,083 2,018 2,025 2,106 2,087 2,070 2,094 2,073 2,155 2,027 1,982 2,014 2,020 2,036 2,201 2,202 2,133 2,150 2,069 2,009 2.022 2,084 2,075

8. 0 100 200 300 400 500 195019601970198019902000 Cereal availability Cereal + pulses availability Changes in government stocks of cereal gms per capita per day From Economic Survey of India

9. 0 100 200 300 400 500 195019601970198019902000 year Cereal availability Cereal + pulses availability Changes in government stocks of cereal gms per capita per day From Economic Survey of India NSS consumption

10. 50 100 150 200 250 195019601970198019902000 year RICE WHEAT OTHER CEREALS AVAILABILITY OF CEREALS, GM PER PERSON PER DAY Ministry of Agriculture

11. What about Engel? Engel’s law says that the share of food in the budget falls as incomes rise –Says nothing about levels of food consumption Calorie Engel curves show calories (including cereal calories) rising with income (or at least pce) over a range So we would expect calorie consumption to rise as living standards improve –India is growing rapidly, but remains poor –Average per capita calorie consumption in the bottom decile of pce in 1983 was less than 1,400 calories, and has been around 1,500 calories for last 20 years

12. Why are calories falling? One interpretation is that poverty and hunger are increasing, especially among rural households “Republic of hunger” If poor people were getting better-off, they would consume more calories, especially more cereals So some combination of falling incomes, rising prices, and unemployment must be impoverishing them Engel curves are correct, calorie data are correct, and NSS is overstating consumption levels

13. Rising poverty A weaker argument is based on calorie adequacy India’s poverty lines were originally set so that at the PL, households on average obtained 2,400 calories (rural) and 2,100 calories (urban) So we can calculate how many people are meeting these standards over time

14. Calorie poverty rates YearRoundRuralUrbanAll India 1983 1987–8 1993–4 1999–0 2000–1 2001–2 2002(2) 2003 2004(1) 38 43 50 55 56 57 58 59 60 66.1 65.9 71.0 74.1 76.2 79.8 79.6 78.4 78.5 60.5 57.1 58.1 58.2 60.7 64.2 63.0 63.3 61.5 64.8 63.9 67.8 70.1 72.3 76.1 75.3 74.6 74.3 Percentages of persons below recommended daily calorie allowances Calculations from NSS data

15. But, but.... The purchasing power of the original poverty lines has not changed (up to possible errors in price indexes) Pronab Sen (EPW) has shown that, if people around the poverty line were to pay the average price per calorie paid by people below the poverty line, they would meet the calorie norms So they must be reducing calories because they want to, not because they have to. Reports of numbers of people not getting “two square meals a day” have fallen dramatically over the last 20 years

16. What about malnutrition NFHS 3 from 2005−06 NFHS 1 (92−93) and NFHS 2 (98−99) are available but did not consistently measure all children across India In the 90s, children who were underweight (z-score less than −2 for weight for age) fell from 52 to 47 percent Latest results for most states show little improvement overall In the 90s, stunting improved in some states, worsened in others Latest results show improvements in most states (18 out of 21: worse in Arunachal Pradesh and Karnataka) Wasting has got worse (all but 4 out of 21 states) Much worse than might have been expected given growth and poverty estimates Better than expected if there is widespread and increasing hunger

17. 0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60 Andhra PradeshArunachal PradeshAssamChhattisgarhDelhi GujaratHaryanaHimachal PradeshJammu & KashmirKarnataka KeralaMadhya PradeshMaharashtraManipurMeghalaya OrissaPunjabRajasthanUttar PradeshUttaranchal West Bengal 1992-931998-99 2005-06 Graphs by State PREVALENCE OF STUNTING Ages 0-3

18. 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 Andhra PradeshArunachal PradeshAssamChhattisgarhDelhi GujaratHaryanaHimachal PradeshJammu & KashmirKarnataka KeralaMadhya PradeshMaharashtraManipurMeghalaya OrissaPunjabRajasthanUttar PradeshUttaranchal West Bengal mean of r1mean of r2 mean of r3 Graphs by State PREVALENCE OF WASTING Ages 0-3

19. 0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60 Andhra PradeshArunachal PradeshAssamChhattisgarhDelhi GujaratHaryanaHimachal PradeshJammu & KashmirKarnataka KeralaMadhya PradeshMaharashtraManipurMeghalaya OrissaPunjabRajasthanUttar PradeshUttaranchal West Bengal 1992-931998-99 2005-06 Graphs by State PREVALENCE OF UNDERWEIGHT Ages 0-3

20. 149.5 150 150.5 151 151.5 mean height 1020304050 Age Indian women are growing taller, though little progress for those born between 1965 and 1975

21. 148 149 150 151 152 mean height 1020304050 Age India Nepal Bangladesh and not as rapidly as women in Nepal and Bangladesh, though they are taller to start with

22. 165 170 678910 Log of real GDP per head in year of birth Average height South Asia Africa Latin America & Caribbean Europe US China And they remain among the smallest women in the world Central Asia

23. 148 150 152 154 156 mean women’s height in 1989/99 1500200025003000 mean per capita calories in region in 1983 black is urban blue is rural INDIAN NSS REGIONS

50. Fats and calories Much has been made of “nutritional transition” in countries like India Replacement of cereals by fats (milk, edible oil, chicken) and “animal source” foods, as well as sugar Concerns about consequences for health, especially diabetes and CVD But Indian rural poor are desperately short of fat, and for them, the nutritional transition is a good thing.

51. .4.5.6.7.8 44.555.566.5 1983 1987-8 1993-4 RURAL FOOD SHARES Fraction of the budget spent on food Logarithm of household total per capita expenditure “Thin” rounds 1994-98 1999-00 “Thin” rounds 2000-4

52. .3.4.5.6.7 4.555.566.57 1983 1987-8 1993-4 URBAN FOOD SHARES Fraction of the budget spent on food Logarithm of household total per capita expenditure “Thin” rounds 1994-981999-00 “Thin” rounds 2000-4

53. 7.2 7.4 7.6 7.8 8 44.555.566.5 R38 R43 R50 R55 R56-60 RURAL INDIA: Nonparametric Calorie Engel Curves Logarithm of household per capita expenditure Log per capita household calories

54. 7.2 7.4 7.6 7.8 8 44.555.56 R38 R43 R50 R55 R56-60 URBAN INDIA: Nonparametric Calorie Engel Curves Logarithm of household per capita expenditure Log per capita household calories

55. 7.4 7.6 7.8 8 44.555.56 R50 R55 R50 with 365 days for low frequency items Logarithm of household per capita expenditure Log per capita household calories RURAL INDIA: Nonparametric Calorie Engel Curves

56. 7 7.2 7.4 7.6 44.555.56 38 43 50 55 56-60 Rural calories from cereals logarithm of household total expenditure per capita logarithm of per capita calories from cereals

57. 6.8 7 7.2 7.4 7.6 4567 RURAL URBAN Calories from cereals, rural and urban together

58. 2.5 3 3.5 4 4.5 4567 Per capita fat consumption, rural and urban, all rounds logarithm of household total expenditure per capita logarithm of per capita fats

59. The puzzle remains Engel curves for nutrients have positive slopes Even for calories from cereals (rural households) Yet calorie consumption (& certainly cereal consumption) is falling Even among the poorest rural households What can be shifting the curve? Not prices Perhaps the curves are misleading? Cereal consumption really falls with income

60. Activity patterns Urban population is more sedentary But fall is within rural population too Rural population may need less energy Changing occupational mix More mechanization Less fetching of water and firewood Better public health: clean water & immunization But not clear that this helps Less work often yields relatively few calories Occupational mix (out of agriculture) is real, but too small relative to effects in regression equations’ Especially if the slopes of the Engel curves are correct Bigger people need more calories Falling for children too, according to NNMB

61. Biased Engel curves NNMB data show that better off households consume less cereal and fewer calories from cereals NCAER data appear to show the same thing But both of these have weak income measures Comparison of APL and BPL households in Rajasthan Literature on bias in Engel curves based on “indirect” measurement of nutrients (like NSS) Measurement error in quantities induces positively correlated measurement error in nutrient counts and in total expenditure, biasing slope towards unity

62. Some evidence on the bias Aggregation up to states, regions, districts The importance of varying tastes Instrumental variable estimates None perfect and at best suggestive Almost always other interpretations Aggregation and sample splitting reduces the slope But measurement error biases Perhaps evidence that the slope is too high But not convincing

63. Other reasons for bias If NSS measures food OK, but progressively understates non-food, true Engel curves would be flatter But can’t explain why it is falling over time The rich feed servants and guests, the poor get meals that are not recorded, so steepening the Engel curve Unlikely to be a large effect Engel curve should flatten over time, but not shift down at the bottom

64. But maybe Engel curves are OK? For the rural poor in agriculture, calories may not generate utility directly, but fuel for work Those who are healthier and stronger eat more, especially cereal calories, to generate earnings Causality is from calories to income Among non-manual workers, cereals are unresponsive to income, or even inferior As real wages rise, people are less willing to do hard physical labor, which moves calorie consumption down as incomes and consumption rises Which reconciles the Engel curve evidence