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Modeling demand structure using scanner data: Implications for salmon enhancement policies

Author

Listed:
  • Cathy R. Wessells

    (Department of Environmental and Natural Resource Economics, University of Rhode Island, 5 Lippitt Road, Kingston, RI 02881)

  • Petter Wallström

    (Department of Environmental and Natural Resource Economics, University of Rhode Island, 5 Lippitt Road, Kingston, RI 02881)

Abstract

In analyzing demand structures, one is often forced to overlook the possibility of instability of parameters, due to a lack of appropriate data. This article utilizes panel data consisting of scanner (Universal Product Code) data to estimate a random coefficient model which allows testing the stability of canned salmon demand across 34 US cities from 1988 through 1992. The results provide marketing strategies for the industry and implications for publicly funded salmon enhancement policies. [Econ-Lit citations: Q22, L66, D61] © 1999 John Wiley & Sons, Inc.

Suggested Citation

  • Cathy R. Wessells & Petter Wallström, 1999. "Modeling demand structure using scanner data: Implications for salmon enhancement policies," Agribusiness, John Wiley & Sons, Ltd., vol. 15(4), pages 449-461.
    • Handle: RePEc:wly:agribz:v:15:y:1999:i:4:p:449-461
    DOI: 10.1002/(SICI)1520-6297(199923)15:4<449::AID-AGR2>3.0.CO;2-9
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    References listed on IDEAS

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    1. Cotterill, Ronald W., 1994. "Scanner Data: New Opportunities For Demand And Competitive Strategy Analysis," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 23(2), pages 1-15, October.
    2. Oral Capps, 1989. "Utilizing Scanner Data to Estimate Retail Demand Functions for Meat Products," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(3), pages 750-760.
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    4. D. DeVoretz, 1982. "An Econometric Demand Model for Canadian Salmon," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 30(1), pages 49-60, March.
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    6. Rodolfo M. Nayga & Oral Capps, 1994. "Tests of Weak Separability in Disaggregated Meat Products," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(4), pages 800-808.
    7. Holland, Daniel & Wessells, Cathy R., 1998. "Predicting Consumer Preferences for Fresh Salmon: The Influence of Safety Inspection and Production Method Attributes," Agricultural and Resource Economics Review, Cambridge University Press, vol. 27(1), pages 1-14, April.
    8. Cotterill, Ronald W., 1994. "Scanner Data: New Opportunities for Demand and Competitive Strategy Analysis," Agricultural and Resource Economics Review, Cambridge University Press, vol. 23(2), pages 125-139, October.
    9. Wohlgenant, Michael K. & Haidacher, Richard C., 1989. "Retail to farm linkage for a complete demand system of food commodities," Technical Bulletins 312312, United States Department of Agriculture, Economic Research Service.
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    Cited by:

    1. Bergtold, Jason S. & Akobundu, Eberechukwu & Peterson, Everett B., 2004. "The FAST Method: Estimating Unconditional Demand Elasticities for Processed Foods in the Presence of Fixed Effects," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(2), pages 1-20, August.
    2. Kehar Singh & Madan M. Dey & Prasanna Surathkal, 2014. "Seasonal and Spatial Variations in Demand for and Elasticities of Fish Products in the United States: An Analysis Based on Market-Level Scanner Data," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 62(3), pages 343-363, September.

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