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Does Women's Empowerment Reduce Prevalence of Stunted and Underweight Children in Rural India?

Author

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  • Katsushi S. Imai

    (Economics, School of Social Sciences, University of Manchester (UK) and RIEB, Kobe University (Japan))

  • Samuel Kobina Annim

    (Economics, School of Social Sciences, University of Manchester (UK) and Department of Economics, University of Cape Coast (Ghana))

  • Raghav Gaiha

    (Faculty of Management Studies, University of Delhi, India)

  • Veena S. Kulkarni

    (Arkansas State University, USA)

Abstract

This study investigates whether mother's empowerment as measured by mother's relative (to father) bargaining power affects children's nutritional status using the National Family Health Survey (NFHS) and National Council of Applied Economic Research (NCAER) data spanning the period between 1992 and 2006. First, the relative bargaining index defined as the share of mother's schooling years over father's schooling years positively and significantly influences z scores pertaining to the short-term measures of nutritional status of children, 'weight-for-age' and 'weight- for-height'-. The results of quantile regression suggest, however, that the bargaining power will improve the chronic measure of nutritional status 'height-for-age', at the low end of conditional distribution of z score.. Further, we find that access to health scheme or health insurance and health-related facility, infrastructure and environment are important factors in reducing child malnutrition.

Suggested Citation

  • Katsushi S. Imai & Samuel Kobina Annim & Raghav Gaiha & Veena S. Kulkarni, 2012. "Does Women's Empowerment Reduce Prevalence of Stunted and Underweight Children in Rural India?," Discussion Paper Series DP2012-11, Research Institute for Economics & Business Administration, Kobe University, revised Dec 2012.
  • Handle: RePEc:kob:dpaper:dp2012-11
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    References listed on IDEAS

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    Cited by:

    1. You, Jing, 2013. "The role of microcredit in older children’s nutrition: Quasi-experimental evidence from rural China," Food Policy, Elsevier, vol. 43(C), pages 167-179.
    2. Samuel Kobina Annim & Katsushi S. Imai, 2014. "Nutritional Status of Children, Food Consumption Diversity and Ethnicity in Lao PDR," Economics Discussion Paper Series 1404, Economics, The University of Manchester.
    3. Swarna Sadasivam Vepa & Vinodhini Umashankar & R.V. Bhavani & Rohit Parasar, 2014. "Agriculture and Child Under-Nutrition in India: A State Level Analysis," Working Papers 2014-086, Madras School of Economics,Chennai,India.
    4. Imai, Katsushi S. & Gaiha, Raghav & Thapa, Ganesh, 2015. "Does non-farm sector employment reduce rural poverty and vulnerability? Evidence from Vietnam and India," Journal of Asian Economics, Elsevier, vol. 36(C), pages 47-61.
    5. Katsushi S. Imai & Takahiro Sato, 2014. "Recent Changes in Micro-Level Determinants of Fertility in India: Evidence from National Family Health Survey Data," Oxford Development Studies, Taylor & Francis Journals, vol. 42(1), pages 65-85, March.
    6. Raghbendra Jha & Katsushi S. Imai & Raghav Gaiha, 2014. "Poverty nutrition traps," Chapters, in: Raghbendra Jha & Raghav Gaiha & Anil B. Deolalikar (ed.), Handbook on Food, chapter 10, pages 246-259, Edward Elgar Publishing.
    7. Katsushi S. Imai & Raghav Gaiha & Woojin Kang & Samuel Annim & Ganesh Thapa, 2012. "Does Risk Matter? A Semi-parametric Model for Educational Choices in the Presence of Uncertainty," Economics Discussion Paper Series 1226, Economics, The University of Manchester.
    8. Pratley, Pierre, 2016. "Associations between quantitative measures of women's empowerment and access to care and health status for mothers and their children: A systematic review of evidence from the developing world," Social Science & Medicine, Elsevier, vol. 169(C), pages 119-131.

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    More about this item

    Keywords

    Child Nutrition; Malnutrition; Empowerment; Bargaining; NFHS; NCAER; Quantile Regressions; Pseudo Panel; India;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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