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Height and Cognitive Achievement among Indian Children

Height and Cognitive Achievement among Indian Children. NCAER – 28 September 2011 Dean Spears. Height & cognitive achievement. on average. There are life-long health and economic consequences of early-life health and net nutrition ( eg Currie 2009)

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Height and Cognitive Achievement among Indian Children

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  1. Height and Cognitive Achievement among Indian Children NCAER – 28 September 2011 Dean Spears

  2. Height & cognitive achievement on average • There are life-long health and economic consequences of early-life health and net nutrition (eg Currie 2009) • Height is determined by genetic potential and net nutrition (eg Deaton 2007; Fogel) • “the difference between food intake and the losses to disease” • “Height is positively related to cognitive ability, which is rewarded in the labor market” (Case & Paxson 2008)

  3. Case & Paxson, Demography, 2010

  4. Why do we care? Why look in India? • Further demonstrates deep importance of childhood health environments • Effects could be different where the average child is very deprived • Contributes to debates on malnutrition in India • Recent literature, especially with big data sets, has focused on rich countries

  5. The India Human Development Survey • … needs no introduction here! Thank you for such a wonderful data set!

  6. IHDS cognitive achievement tests • Reading (5 levels) • none, letters, words, paragraphs, stories • Math (4 levels) • none, numbers, subtraction, division • Writing (2 levels) • none, writes with 2 or fewer mistakes

  7. Part One The Indian gradient

  8. ordered logitsby age, by urban-rural achievementi = 0 + 1hfai + i + step 2: 2malei + 3Engi + 3Hindii + θGi + step 3: 4CPCi + 5 CPCi² + 5hhsizei + 6childreni + 5ediadult + 5ediwoman.

  9. ordered logitsby age, by urban-rural achievementi = 0 + 1hfai + i + step 2: 2malei + 3Engi + 3Hindii + θGi + step 3: 4CPCi + 5 CPCi² + 5hhsizei + 6childreni + 5ediadult + 5ediwoman.

  10. ordered logitsby age, by urban-rural achievementi = 0 + 1hfai + i + step 2: 2malei + 3Engi + 3Hindii + θGi + step 3: 4CPCi + 5 CPCi² + 5hhsizei + 6childreni + 5ediadult + 5ediwoman.

  11. As linear as it seems? Box-Cox transformation (zλ-1)/ λ as the dependent variable Maximizes likelihood at λ* =1.26 Cannot reject null hypothesis thatλ =1

  12. Part Two India& the U.S.

  13. cognitive achievement data India: IHDS U.S.: NLSY 79 Peabody Individual Achievement Tests PIAT Recognition (1-84) PIAT Comprehension (1-84) Can construct comparable variables reads letters: recognition  18 reads words: recognition  23 • reads letters • reads words • reads paragraphs • reads stories Only reading can be matched, unfortunately

  14. Famous papers have called this positive slope a big deal!

  15. slope in India > slope in U.S.? achievementi = 0 + 1hfai  Indiai + 2hfai + 3Indiai + 4femalei + 5femaleiIndiai + i. • Estimate separately for 8, 9, 10, 11 year olds • Indicate achievement with best content matches • Reads words • Reads letters

  16. slope in India > slope in U.S.?

  17. Maybe I chose badly? 84 regressions, for 84 levels s

  18. reads words vs. PIAT recognition

  19. reads paragraphs, reads stories vs. PIAT comprehension

  20. Why the difference? • Cognitive and height outcomes (c and z) depend on a genetic potential g, and a deduction due to early life health h and net nutrition. • Assume gs are uncorrelated with one another and with h.

  21. Why the difference? • Let f be linear in both cases. • If conditional expectations are indeed linear, εs will be uncorrelated with h. • Further assume they are uncorrelated with one another.

  22. Why the difference?

  23. Why the difference? • India’s slope is still greater if we regress height on cognitive achievement • The regression estimated only with the Indian data has a greater R2 than just for the U.S. data \

  24. Part 3: What is the omitted variable? Explaining the Indian gradient

  25. Human Development Profile of India NCAER provided matchable data from 1994. HDPI includes only then-rural households. 2005 11 year olds 10 year olds 9 year olds 8 year olds 1994

  26. stepwise addition of variables

  27. Table 4 pretty flat

  28. Sanitation variables matter • None of the food or respiratory environment variables are individually significant • Toilet in household: 9 pp more likely to write (t = 2.93) • Long walk to water source: 8 pp less likely to write (t = 2.15) • No adult washes hands before eating • True of 19 percent of children • 41 pp less likely to write (t = 2.09)

  29. What have we learned? • Indian slope ranges from 2.4 times to 25 times the U.S. slope. • Height is a powerful predictor of children’s cognitive achievement • Being a short is not innocuous among Indian children • Being one standard deviation taller is associated with being 5 percentage points more likely to be able to write, a slope that falls to only 3.4 percentage points with many controls • Much remains to understand • Sanitation, water, and hygiene seem important

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