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Application of the Quaids Model to the Food Sector in India

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  • Surabhi Mittal

    (ICRIER, New Delhi 110003, India)

Abstract

Higher economic growth has led to diversification of the consumption bundle of households away from staple food. This has implications for the food policy as demand projections for different commodities impacts the farmers decision to diversify its production base which further has implications for the issue of food security. Thus it becomes important to project the demand, based on most realistic demand elasticities. Using the households consumer expenditure survey of the major National Sample Survey rounds, the paper estimates the price and expenditure elasticity’s of different food items/ groups in India. A two-stage Quadratic AIDS (QUAIDS) model is used to compute coefficients and calculate the demand elasticity’s. In this model assumption of linearity in the expenditure function is given away.

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Bibliographic Info

Article provided by The Indian Econometric Society in its journal Journal of Quantitative Economics.

Volume (Year): 8 (2010)
Issue (Month): 1 (January)
Pages: 42-54

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Handle: RePEc:jqe:jqenew:v:8:y:2010:i:1:p:42-54

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Postal: Managing Editor, Journal of Quantitative Economics, Indira Gandhi Institute of Development Research (IGIDR), Gen. A.K. Vaidya Marg, Goregaon (E), Mumbai 400 065 , INDIA
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Related research

Keywords: QUAIDS Model; Food Demand Elasticity; India;

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References

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  1. Meenakshi, J.V. & Ray, R., 1996. "Regional Differences in India's Food Expenditure Pattern: A Complete Demand Systems Approach," Papers 1996-06, Tasmania - Department of Economics.
  2. Awudu Abdulai, 2002. "Household Demand for Food in Switzerland. A Quadratic Almost Ideal Demand System," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 138(I), pages 1-18, March.
  3. repec:clg:wpaper:2000-04 is not listed on IDEAS
  4. Douglas Fisher & Adrian R. Fleissig & Apostolos Serletis, 2001. "An empirical comparison of flexible demand system functional forms," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(1), pages 59-80.
  5. Blundell, Richard & Robin, Jean Marc, 1999. "Estimation in Large and Disaggregated Demand Systems: An Estimator for Conditionally Linear Systems," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 209-32, May-June.
  6. Deaton, A., 1990. "Price Elasticities From Surveys Data: Extensions And Indonesian Results," Papers 69, World Bank - Living Standards Measurement.
  7. Surabhi Mittal, 2006. "Structural Shift in Demand for Food - Projections for 2020," Macroeconomics Working Papers 22223, East Asian Bureau of Economic Research.
  8. Brian W. Gould & Hector J. Villarreal, 2006. "An assessment of the current structure of food demand in urban China," Agricultural Economics, International Association of Agricultural Economists, vol. 34(1), pages 1-16, 01.
  9. Surabhi Mittal, 2010. "Demand-Supply Trends and Projections of Food in India," Working Papers id:2703, eSocialSciences.
  10. Kumar, Praduman & Dey, Madan Mohan & Paraguas, Ferdinand J., 2005. "Demand for Fish by Species in India: Three-stage Budgeting Framework," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 18(2).
  11. Blundell, Richard & Pashardes, Panos & Weber, Guglielmo, 1993. "What Do We Learn About Consumer Demand Patterns from Micro Data?," American Economic Review, American Economic Association, vol. 83(3), pages 570-97, June.
  12. Abdulai, Awudu & Aubert, Dominique, 2004. "A cross-section analysis of household demand for food and nutrients in Tanzania," Agricultural Economics, Blackwell, vol. 31(1), pages 67-79, July.
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