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Determinants of Nutritional Outcomes of Children in India: A Quantile Regression Approach

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  • Kandpal, Eeshani
  • McNamara, Paul E.

Abstract

In this paper, we use quantile regressions on data from the 2005-06 wave of the Indian National Family Health Survey to study the determinants of child body-mass-index, height-for-age, and hemoglobin at different points of the conditional distribution. Our results show that only considering the conditional mean of the entire distribution can yield misleading results. In light of compelling evidence on sex-selective abortion and infanticide, we use a Heckman correction for our quantile regression to control for the “underreporting” of female births documented by Rose (1999). We find that household maternal health and education have larger effects at the lower end of the distribution than on the upper end, for all three child nutritional indicators. Results show that iron supplements are less effective at increasing hemoglobin levels in the worst-off children. We argue that policy interventions must account for socioeconomic diversity or have little hope of meeting their target.

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File URL: http://purl.umn.edu/49415
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Bibliographic Info

Paper provided by Agricultural and Applied Economics Association in its series 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin with number 49415.

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Date of creation: 2009
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Handle: RePEc:ags:aaea09:49415

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Keywords: Food Consumption/Nutrition/Food Safety; International Development;

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  1. Das Gupta, Monica & Lokshin, Michael & Gragnolati, Michele & Ivaschenko, Oleksiy, 2005. "Improving child nutrition outcomes in India : can the integrated child development services be more effective?," Policy Research Working Paper Series 3647, The World Bank.
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Cited by:
  1. Katsushi Imai & Samuel Kobina Annim & Veena S. Kulkarni & Raghav Gaiha, 2013. "Does Women's Empowerment Reduce Prevalence of Stunted and Underweight Children in Rural India?," Discussion Paper Series DP2013-33, Research Institute for Economics & Business Administration, Kobe University.
  2. Sweeney, Stuart & Davenport, Frank & Grace, Kathryn, 2013. "Combining insights from quantile and ordinal regression: Child malnutrition in Guatemala," Economics & Human Biology, Elsevier, vol. 11(2), pages 164-177.
  3. Drescher, Larissa S. & Goddard, Ellen W., 2011. "Heterogeneous Demand for Food Diversity: A Quantile Regression Analysis," 51st Annual Conference, Halle, Germany, September 28-30, 2011 114484, German Association of Agricultural Economists (GEWISOLA).

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