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Demand for Fish by Species in India: Three-stage Budgeting Framework


  • Kumar, Praduman
  • Dey, Madan Mohan
  • Paraguas, Ferdinand J.


The demand studies for the fish sector are limited by their high degree of aggregation, and the lack of empirical basis for estimating the underlying elasticity of demand. In this study, the three-stage budgeting framework with quadratic almost ideal demand system (QAIDS) model has been used for fish demand analysis by species, using consumer expenditure survey data of India. Income and price elasticities of fish demand have been evaluated at mean level for different economic groups and have been used to project the demand for fish to a medium-term time horizon, by the year 2015. The domestic demand for fish by 2015 has been projected as 6.7-7.7 million tonnes. Aquaculture would hold the key to meet the challenges of future needs. Among species, Indian major carps (IMC) would play a dominating role in meeting the fish demand. Results have shown that the estimated price and income elasticities of demand vary across species and income classes. Fish species have not been found as homogenous commodities for consumers. All the eight fish types included in the study have been found to have positive income elasticity greater than one for all the income levels. Hence, with higher income, fish demand has been projected to increase substantially with change in the species mix. The own-price elasticities by species have been found negative and near to unitary.

Suggested Citation

  • 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), July.
  • Handle: RePEc:ags:aerrae:58469
    DOI: 10.22004/ag.econ.58469

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    References listed on IDEAS

    1. Abigail Tiffin & Richard Tiffin, 1999. "Estimates of Food Demand Elasticities for Great Britain: 1972–1994," Journal of Agricultural Economics, Wiley Blackwell, vol. 50(1), pages 140-147, January.
    2. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    3. 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 570-597, June.
    4. J. V. Meenakshi & Ranjan Ray, 1999. "Regional differences in India's food expenditure pattern: a complete demand systems approach," Journal of International Development, John Wiley & Sons, Ltd., vol. 11(1), pages 47-74.
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    3. Toufique, Kazi Ali & Belton, Ben, 2014. "Is Aquaculture Pro-Poor? Empirical Evidence of Impacts on Fish Consumption in Bangladesh," World Development, Elsevier, vol. 64(C), pages 609-620.
    4. Surabhi Mittal, 2010. "Application of the Quaids Model to the Food Sector in India," Journal of Quantitative Economics, The Indian Econometric Society, vol. 8(1), pages 42-54, January.
    5. Debnath, Biswajit & Biradar, R.S. & Ananthan, P.S. & Pandey, S.K., 2012. "Estimation of Demand for Different Fish Groups in Tripura," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 25(2).
    6. Javier García-Enríquez & Cruz A. Echevarría, 2016. "Consistent Estimation of a Censored Demand System and Welfare Analysis: The 2012 VAT Reform in Spain," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(2), pages 324-347, June.

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