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Print Advertisement Characteristics and Apple Variety Attraction: A Mimic Model Approach


  • Patterson, Paul M.
  • Richards, Timothy J.


A structural latent variable model of apple variety demand is used to analyze the effect of variety specific newspaper advertisement characteristics on variety attraction (preferences), and in turn on variety demand. The influence of advertisement size, the use of color and the Washington apple logo were analyzed. The estimated variety attraction variable is important in explaining demand. Model specifications which exclude this variable tend to understate demand elasticities. Advertisement size has a positive impact on Granny Smith, Fuji, and Gala sales. Red Delicious sales are positively influenced by color ads, but negatively affected by ads with the Washington apple logo.

Suggested Citation

  • Patterson, Paul M. & Richards, Timothy J., 1998. "Print Advertisement Characteristics and Apple Variety Attraction: A Mimic Model Approach," Working Papers 28537, Arizona State University, Morrison School of Agribusiness and Resource Management.
  • Handle: RePEc:ags:asumwp:28537

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    References listed on IDEAS

    1. John L. Park & Oral Capps, 1997. "Demand for Prepared Meals by U.S. Households," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(3), pages 814-824.
    2. Henry W. Kinnucan & Maria Thomas, 1997. "Optimal Media Allocation Decisions For Generic Advertisers," Journal of Agricultural Economics, Wiley Blackwell, vol. 48(1-3), pages 425-441.
    3. Anderson, T. W., 1989. "Linear latent variable models and covariance structures," Journal of Econometrics, Elsevier, vol. 41(1), pages 91-119, May.
    4. Eric J. Wailes & Gail L. Cramer, 1997. "A Microeconometric Analysis of Consumer Taste Determination and Taste Change for Beef," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 573-582.
    5. Ivaldi, Marc & Monier-Dilhan, Sylvette & Simioni, Michel, 1995. "Stochastic production frontiers and panel data: A latent variable framework," European Journal of Operational Research, Elsevier, vol. 80(3), pages 534-547, February.
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