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This study delves into the correlation between height and cognitive achievement among Indian children, emphasizing the lifelong health and economic impacts of early-life nutrition. The research explores how genetic potential and nutrition influence height and cognitive abilities, which in turn affect labor market outcomes. The India Human Development Survey data and cognitive achievement tests are used to analyze reading, math, and writing skills. The study also compares cognitive achievement data between India and the U.S., highlighting the significance of height as a predictor of cognitive abilities. Sanitation conditions and hygiene practices are found to play a crucial role in children's cognitive development. Overall, the study sheds light on the importance of childhood health environments and the need for further research in this area.
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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) • 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)
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
The India Human Development Survey • … needs no introduction here! Thank you for such a wonderful data set!
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
Part One The Indian gradient
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.
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.
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.
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
Part Two India& the U.S.
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
slope in India > slope in U.S.? achievementi = 0 + 1hfai Indiai + 2hfai + 3Indiai + 4femalei + 5femaleiIndiai + i. • Estimate separately for 8, 9, 10, 11 year olds • Indicate achievement with best content matches • Reads words • Reads letters
Maybe I chose badly? 84 regressions, for 84 levels s
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.
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.
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 \
Part 3: What is the omitted variable? Explaining the Indian gradient
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
Table 4 pretty flat
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)
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