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Consumption of Pork Products: Now and to the Year 2020

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  • Lin, Biing-Hwan
  • Davis, Christopher G.
  • Yen, Steven T.

Abstract

Data from the U.S. Department of Agriculture’s 1994-96 and 1998 Continuing Survey of Food Intakes by Individuals (CSFII) are used to describe pork consumption patterns as well as to estimate a censored demand system for pork cuts. The descriptive analysis fills the void about basic information on who consumes pork, how much, and where. A censored system of four pork cuts is estimated for adults, using a maximum-likelihood procedure. The estimated system is used to predict consumption of pork products by adults through the year 2020.

Suggested Citation

  • Lin, Biing-Hwan & Davis, Christopher G. & Yen, Steven T., 2004. "Consumption of Pork Products: Now and to the Year 2020," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 22(2), pages 1-15.
  • Handle: RePEc:ags:jloagb:59403
    DOI: 10.22004/ag.econ.59403
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    References listed on IDEAS

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    1. Spanos,Aris, 1999. "Probability Theory and Statistical Inference," Cambridge Books, Cambridge University Press, number 9780521424080.
    2. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    3. Hajivassiliou, Vassilis A & Ruud, Paul A., 1993. "Classical Estimation Methods for LDV Models Using Simulation," Department of Economics, Working Paper Series qt3cg196fr, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    4. Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441, Elsevier.
    5. McDonald, John F & Moffitt, Robert A, 1980. "The Uses of Tobit Analysis," The Review of Economics and Statistics, MIT Press, vol. 62(2), pages 318-321, May.
    6. Amemiya, Takeshi, 1974. "Multivariate Regression and Simultaneous Equation Models when the Dependent Variables Are Truncated Normal," Econometrica, Econometric Society, vol. 42(6), pages 999-1012, November.
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    Cited by:

    1. Richard J. Vyn & Getu Hailu, 2015. "Discount Usage and Price Discrimination for Pork Products in Canada," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 63(4), pages 449-474, December.

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