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Estimating the Impact of Voluntary Labeling of Trans Fats on the Market Demand for Processed Foods: A Nested PIGLOG Model Approach

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  • Vickner, Steven S.

Abstract

This paper estimates a nested PIGLOG demand system to assess the impact of voluntary labeling of trans fats on the market demand for processed foods.

Suggested Citation

  • Vickner, Steven S., 2005. "Estimating the Impact of Voluntary Labeling of Trans Fats on the Market Demand for Processed Foods: A Nested PIGLOG Model Approach," 2005 Annual meeting, July 24-27, Providence, RI 19342, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea05:19342
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    File URL: http://purl.umn.edu/19342
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    References listed on IDEAS

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    1. Giancarlo Moschini, 1995. "Units of Measurement and the Stone Index in Demand System Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(1), pages 63-68.
    2. Teisl, Mario F. & Roe, Brian & Hicks, Robert L., 2002. "Can Eco-Labels Tune a Market? Evidence from Dolphin-Safe Labeling," Journal of Environmental Economics and Management, Elsevier, vol. 43(3), pages 339-359, May.
    3. Nicholas E. Piggott, 2003. "The Nested PIGLOG Model: An Application to U.S. Food Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 1-15.
    4. Nicholas E. Piggott & Thomas L. Marsh, 2004. "Does Food Safety Information Impact U.S. Meat Demand?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 154-174.
    5. Mario F. Teisl & Nancy E. Bockstael & Alan Levy, 2001. "Measuring the Welfare Effects of Nutrition Information," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(1), pages 133-149.
    6. Smith, Mark E. & van Ravenswaay, Eileen O. & Thompson, Stanley R., 1987. "Sales Loss Determination in Food Contamination Incidents: An Application to Milk Bans in Hawaii," Working Papers 115803, Regional Research Project NE-165 Private Strategies, Public Policies, and Food System Performance.
    7. Pollak, Robert A & Wales, Terence J, 1981. "Demographic Variables in Demand Analysis," Econometrica, Econometric Society, vol. 49(6), pages 1533-1551, November.
    8. Bollino, Carlo Andrea, 1987. "Gaids: a generalised version of the almost ideal demand system," Economics Letters, Elsevier, vol. 23(2), pages 199-202.
    9. Foster, William & Just, Richard E., 1989. "Measuring welfare effects of product contamination with consumer uncertainty," Journal of Environmental Economics and Management, Elsevier, vol. 17(3), pages 266-283, November.
    10. Alston, Julian M. & Chalfant, James A. & Piggott, Nicholas E., 2001. "Incorporating demand shifters in the Almost Ideal demand system," Economics Letters, Elsevier, vol. 70(1), pages 73-78, January.
    11. Arthur Lewbel, 1985. "A Unified Approach to Incorporating Demographic or Other Effects into Demand Systems," Review of Economic Studies, Oxford University Press, vol. 52(1), pages 1-18.
    12. S.S. Vickner, 2004. "Media Coverage of Biotech Foods and Influence on Consumer Choice," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(5), pages 1238-1246.
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    Marketing;

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