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Developments in Undernutrition in Indian Children Under Five: A Decompositional Analysis

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Listed:
  • Nie, Peng

    (Xi’an Jiaotong University)

  • Rammohan, Anu

    (University of Western Australia)

  • Gwozdz, Wencke

    (Copenhagen Business School)

  • Sousa-Poza, Alfonso

    (University of Hohenheim)

Abstract

This study uses two waves (2004–2005 and 2011–2012) of the nationally representative Indian Human Development Survey to conduct a systematic decompositional analysis of the demographic and socio-economic factors contributing to undernutrition among children under five in India. The analytic method combines three types of decomposition: Blinder-Oaxaca, non-linear, and unconditional quantile. Child undernutrition is measured by z-scores for height-for-age (HAZ), weight-for-height (WHZ), weight-for-age (WAZ), and for the Composite Index of Anthropometric Failure (CIAF). Although our results show modest improvements on some measures, undernutrition among India's young children remains widespread. The improvements we do identify are partly attributable to changes in household wealth and maternal characteristics like body mass index and education.

Suggested Citation

  • Nie, Peng & Rammohan, Anu & Gwozdz, Wencke & Sousa-Poza, Alfonso, 2016. "Developments in Undernutrition in Indian Children Under Five: A Decompositional Analysis," IZA Discussion Papers 9893, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp9893
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    References listed on IDEAS

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    1. Brennan, Lance & McDonald, John & Shlomowitz, Ralph, 2004. "Infant feeding practices and chronic child malnutrition in the Indian states of Karnataka and Uttar Pradesh," Economics & Human Biology, Elsevier, vol. 2(1), pages 139-158, March.
    2. F. L. Jones, 1983. "On Decomposing the Wage Gap: A Critical Comment on Blinder's Method," Journal of Human Resources, University of Wisconsin Press, vol. 18(1), pages 126-130.
    3. Fairlie, Robert W., 2003. "An Extension of the Blinder-Oaxaca Decomposition Technique to Logit and Probit Models," Center Discussion Papers 28425, Yale University, Economic Growth Center.
    4. 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.
    5. Chalasani, Satvika, 2012. "Understanding wealth-based inequalities in child health in India: A decomposition approach," Social Science & Medicine, Elsevier, vol. 75(12), pages 2160-2169.
    6. Fairlie, Robert W, 1999. "The Absence of the African-American Owned Business: An Analysis of the Dynamics of Self-Employment," Journal of Labor Economics, University of Chicago Press, vol. 17(1), pages 80-108, January.
    7. Ben Jann, 2008. "The Blinder–Oaxaca decomposition for linear regression models," Stata Journal, StataCorp LP, vol. 8(4), pages 453-479, December.
    8. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    9. Bhalotra, Sonia & Valente, Christine & van Soest, Arthur, 2010. "The puzzle of Muslim advantage in child survival in India," Journal of Health Economics, Elsevier, vol. 29(2), pages 191-204, March.
    10. Deon Filmer & Lant Pritchett, 2001. "Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 115-132, February.
    11. Dean Spears, 2012. "How much international variation in child height can sanitation explain?," Working Papers 1438, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing..
    12. Edoka, I.P., 2012. "Decomposing Differences in Cotinine Distribution between Children and Adolescents from Different Socioeconomic Backgrounds," Health, Econometrics and Data Group (HEDG) Working Papers 12/29, HEDG, c/o Department of Economics, University of York.
    13. Smith, Lisa C. & Haddad, Lawrence, 2015. "Reducing Child Undernutrition: Past Drivers and Priorities for the Post-MDG Era," World Development, Elsevier, vol. 68(C), pages 180-204.
    14. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    15. Hammer, Jeffrey & Spears, Dean, 2013. "Village sanitation and children's human capital : evidence from a randomized experiment by the Maharashtra government," Policy Research Working Paper Series 6580, The World Bank.
    16. Kassouf, Ana L & Senauer, Benjamin, 1996. "Direct and Indirect Effects of Parental Education on Malnutrition among Children in Brazil: A Full Income Approach," Economic Development and Cultural Change, University of Chicago Press, vol. 44(4), pages 817-838, July.
    17. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    18. Pathak, Praveen Kumar & Singh, Abhishek, 2011. "Trends in malnutrition among children in India: Growing inequalities across different economic groups," Social Science & Medicine, Elsevier, vol. 73(4), pages 576-585, August.
    19. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    20. Cavatorta, Elisa & Shankar, Bhavani & Flores-Martinez, Artemisa, 2015. "Explaining Cross-State Disparities in Child Nutrition in Rural India," World Development, Elsevier, vol. 76(C), pages 216-237.
    21. Jörg Schwiebert, 2015. "A detailed decomposition for nonlinear econometric models," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(1), pages 53-67, March.
    22. Maitra, Pushkar & Rammohan, Anu & Ray, Ranjan & Robitaille, Marie-Claire, 2013. "Food consumption patterns and malnourished Indian children: Is there a link?," Food Policy, Elsevier, vol. 38(C), pages 70-81.
    23. Svedberg, Peter, 2000. "Poverty and Undernutrition: Theory, Measurement, and Policy," OUP Catalogue, Oxford University Press, number 9780198292685.
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    1. Swaminathan, Harini & Sharma, Anurag & Shah, Narendra G., 2019. "Does the relationship between income and child health differ across income groups? Evidence from India," Economic Modelling, Elsevier, vol. 79(C), pages 57-73.

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    More about this item

    Keywords

    child undernutrition; India; decomposition;
    All these keywords.

    JEL classification:

    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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