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Nutrition, Activity Intensity and Wage Linkages: Evidence from India

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  • Katsushi S. Imai
  • Samuel Kobina Annim
  • Veena S. Kulkarni
  • Raghav Gaiha

Abstract

The present study tests the twin hypotheses, namely, (a) the poverty nutrition trap hypothesis that wages affect nutritional status, and (b) the activity hypothesis that activity intensity affects adult nutrition as measured by the Body Mass Index (BMI) in the context of India. The analyses draw upon three rounds of National Family Health Survey (NFHS) data in 1992, 1998 and 2005 and National Council of Applied Economic Research (NCAER) data in 2005. Our results indicate strong support for both the hypotheses in India. Physically intensive activity tends to worsen the nutritional conditions and there is evidence for a poverty nutrition trap associated with labor market participation.
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  • Katsushi S. Imai & Samuel Kobina Annim & Veena S. Kulkarni & Raghav Gaiha, 2014. "Nutrition, Activity Intensity and Wage Linkages: Evidence from India," Economics Discussion Paper Series 1411, Economics, The University of Manchester.
  • Handle: RePEc:man:sespap:1411
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    1. 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.
    2. Indranil Dutta & Shruti Kapoor & Prasanta K. Pattanaik, 2020. "Nutrient consumption in India: Evidence from a village study," Review of Development Economics, Wiley Blackwell, vol. 24(3), pages 855-877, August.
    3. 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.
    4. 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.

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    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
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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