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On Improving Econometric Analyses Of Generic Advertising Impacts

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  • Tomek, William G.
  • Kaiser, Harry M.

Abstract

It is possible to obtain robust estimates of structural parameters using observational data, but it is difficult to do so. Necessary, but not sufficient, conditions are to adopt a modeling philosophy and to undertake a comprehensive evaluation of the results. Using a general-to-specific modeling philosophy, we obtained stable estimates of the long-run advertising elasticity for fluid milk. This result contrasts with an earlier, published model which did not provide stable estimates as new data points became available. It is difficult, however, to apply the general-to-specific modeling approach because it requires the researcher to specify an initial general model. But analysts are unlikely to agree on this initial model, and if this is true, then the "generality" of the model is in question. Moreover, it is a fact that the quality of the available data is sometimes insufficient to obtain the desired stable estimates.

Suggested Citation

  • Tomek, William G. & Kaiser, Harry M., 1999. "On Improving Econometric Analyses Of Generic Advertising Impacts," Working Papers 14755, Cornell University, Department of Applied Economics and Management.
    • Handle: RePEc:ags:cudawp:14755
    DOI: 10.22004/ag.econ.14755
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    References listed on IDEAS

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    1. Anya M. McGuirk & Paul Driscoll & Jeffrey Alwang, 1993. "Misspecification Testing: A Comprehensive Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(4), pages 1044-1055.
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    3. Kinnucan, Henry W. & Chang, Hui-Shung (Christie) & Venkateswaran, Meenakshi, 1993. "Generic Advertising Wearout," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 61(03), pages 1-15, December.
    4. John D. Jackson, 1997. "Effects of Health Information and Generic Advertising on U.S. Meat Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 13-23.
    5. Spanos, Aris, 1995. "On theory testing in econometrics : Modeling with nonexperimental data," Journal of Econometrics, Elsevier, vol. 67(1), pages 189-226, May.
    6. George C. Davis, 1997. "The Logic of Testing Structural Change in Meat Demand: A Methodological Analysis and Appraisal," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(4), pages 1186-1192.
    7. MacKinnon, James G, 1992. "Model Specification Tests and Artificial Regressions," Journal of Economic Literature, American Economic Association, vol. 30(1), pages 102-146, March.
    8. Wojciech W. Charemza & Derek F. Deadman, 1992. "New Directions In Econometric Practice," Books, Edward Elgar Publishing, number 84, December.
    9. Davis, George C., 1997. "The Formal Logic Of Testing Structural Change In Meat Demand: A Methodological Analysis," Faculty Paper Series 23975, Texas A&M University, Department of Agricultural Economics.
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    Cited by:

    1. Preszler, Trent L. & Schmit, Todd M., 2008. "Modeling Perceptions Of Locally Produced Wine Among Restaurateurs In New York City," Working Papers 45503, American Association of Wine Economists.
    2. Todd M. Schmit & Harry M. Kaiser, 2004. "Decomposing the Variation in Generic Advertising Response over Time," American Journal of Agricultural Economics, John Wiley & Sons, vol. 86(1), pages 139-153, February.
    3. Asada, Raphael & Hurmekoski, Elias & Hoeben, Annechien Dirkje & Patacca, Marco & Stern, Tobias & Toppinen, Anne, 2023. "Resilient forest-based value chains? Econometric analysis of roundwood prices in five European countries in the era of natural disturbances," Forest Policy and Economics, Elsevier, vol. 153(C).
    4. Zheng, Yuqing & Kaiser, Harry M., 2008. "Advertising and U. S. Nonalcoholic Beverage Demand," Agricultural and Resource Economics Review, Cambridge University Press, vol. 37(2), pages 147-159, October.

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