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Demand for Nutrients in India, 1993–2004

Author

Listed:
  • Raghav Gaiha
  • Raghbendra Jha
  • Vani S. Kulkarni

Abstract

In response to the Deaton–Dreze (2009) explanation of a downward shift in the calorie Engel curve in terms of lower requirements due to health improvements and lower activity levels, we have developed an alternative explanation of changes in the consumption of calories, protein and fats over the period 1993–2004. This explanation is embedded in a standard demand theory framework, with food prices and expenditure (as a proxy for income) cast in a pivotal role. Based on different experiments, robust demand functions are estimated for each of three nutrients viz. calories, protein and fats, separately for rural and urban areas. Our results show consistently robust food price and expenditure effects. Besides, shifts in food price elasticities over time are captured. Over and above these effects, there are shifts in demands due to factors other than those specified in the demand equation. In the context of calories, for example, it is plausible that part of the reduction in their consumption was due to health improvements and less strenuous activity levels — especially but not necessarily confined to rural areas. So, while the Deaton–Dreze (2009) explanation is not rejected, it is arguable that it is complementary to the demand-based explanations.

Suggested Citation

  • Raghav Gaiha & Raghbendra Jha & Vani S. Kulkarni, 2010. "Demand for Nutrients in India, 1993–2004," ASARC Working Papers 2010-16, The Australian National University, Australia South Asia Research Centre.
  • Handle: RePEc:pas:asarcc:2010-16
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Indian calorie intakes decline despite rising incomes
      by Raghbendra Jha in East Asia Forum on 2010-09-07 05:12:25

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    Cited by:

    1. Jumrani, Jaya, 2023. "How responsive are nutrients in India? Some recent evidence," Food Policy, Elsevier, vol. 114(C).
    2. Nadia Shabnam & Fabio Gaetano Santeramo & Zahid Asghar & Antonio Seccia, 2016. "The Impact of Food Price Crises on the Demand for Nutrients in Pakistan," Journal of South Asian Development, , vol. 11(3), pages 305-327, December.
    3. McCullough, Ellen & Zhen, Chen & Shin, Soye & Lu, Meichen & Arsenault, Joanne, 2022. "The role of food preferences in determining diet quality for Tanzanian consumers," Journal of Development Economics, Elsevier, vol. 155(C).
    4. 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.
    5. Chiu, Alice & Headey, Derek & Kadiyala, Suneetha, 2011. "Agriculture's role in the Indian enigma: Help or hindrance to the undernutrition crisis?," IFPRI discussion papers 1085, International Food Policy Research Institute (IFPRI).
    6. Jaya Jumrani & J. V. Meenakshi, 2023. "How effective is a fat subsidy? Evidence from edible oil consumption in India," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 327-348, June.
    7. Edwin Mumah & Yu Hong & Yangfen Chen, 2025. "Exploring the reality of global food insecurity and policy gaps," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-23, December.
    8. Nidhi Kaicker & Vani S. Kulkarni & Raghav Gaiha, 2011. "Dietary Transition in India: An Analysis Based on NSS Data for 1993 and 2004," ASARC Working Papers 2011-10, The Australian National University, Australia South Asia Research Centre.
    9. Jayatilleke S. Bandara, 2013. "What is Driving India’s Food Inflation? A Survey of Recent Evidence," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 14(1), pages 127-156, March.
    10. Raghbendra Jha, 2018. "India's Long Road: The Search for Prosperity," The Economic Record, The Economic Society of Australia, vol. 94(305), pages 207-209, June.

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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