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Estimating Coke's and Pepsi's Price and Advertising Strategies

Author

Listed:
  • Golan, Amos
  • Karp, Larry S
  • Perloff, Jeffrey M

Abstract

A Semiparametric, information-based estimator is used to estimate strategies in prices and advertising for Coca-Cola and Pepsi-Cola. Separate strategies for each firm are estimated with and without restrictions from game theory. These information/entropy estimators are consistent and efficient. These estimates are used to test theories about the strategies of firms and to see how changes in incomes or factor prices affect these strategies.

Suggested Citation

  • Golan, Amos & Karp, Larry S & Perloff, Jeffrey M, 2000. "Estimating Coke's and Pepsi's Price and Advertising Strategies," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 398-409, October.
    • Handle: RePEc:bes:jnlbes:v:18:y:2000:i:4:p:398-409
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    Citations

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    Cited by:

    1. Shinn‐Shyr Wang & Kyle W. Stiegert & Tirtha P. Dhar, 2010. "Strategic Pricing Behavior under Asset Value Maximization," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 58(2), pages 151-170, June.
    2. Clark, Robert & Gong, Yiran, 2024. "Why do some new products fail? Evidence from the entry and exit of Vanilla Coke," International Journal of Industrial Organization, Elsevier, vol. 97(C).
    3. Dhar, Tirtha & Chavas, Jean-Paul & Cotterill, Ronald W. & Gould, Brian W., 2002. "An Econometric Analysis of Brand Level Strategic Pricing Between Coca Cola and Pepsi Inc," Working Papers 201553, University of Wisconsin-Madison, Department of Agricultural and Applied Economics, Food System Research Group.
    4. Yokoyama, Kazuki, 2024. "Strategic Interdependence: Quasi-Experiment in the Maritime Industry during the 1880s in Japan," MPRA Paper 121730, University Library of Munich, Germany.
    5. Wang, Yafeng & Graham, Brett, 2009. "Generalized Maximum Entropy estimation of discrete sequential move games of perfect information," MPRA Paper 21331, University Library of Munich, Germany.
    6. Lee, Yunkyung & Giannakas, Konstantinos, 2020. "System-wide market and welfare effects of a U.S. sugar-sweetened beverages tax," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304297, Agricultural and Applied Economics Association.
    7. Enrico Ciavolino & Antonio Calcagnì, 2014. "A generalized maximum entropy (GME) approach for crisp-input/fuzzy-output regression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3401-3414, November.
    8. Horrace, William C. & Huang, Rui & Perloff, Jeffrey M., 2016. "Effects of increased variety on demand, pricing, and welfare," Research in Economics, Elsevier, vol. 70(4), pages 569-587.
    9. Wang, Yafeng & Graham, Brett, 2010. "Identification and Estimation of a Discrete Game by Observing its Correlated Equilibria," MPRA Paper 45656, University Library of Munich, Germany, revised 16 May 2011.
    10. Horrace, William & Huang, Rui & Perloff, Jeffrey, 2009. "Variety: Consumer Choice and Optimal Diversity," Research Reports 149942, University of Connecticut, Food Marketing Policy Center.
    11. Alessandro Bonanno & Carlo Russo & Luisa Menapace, 2018. "Market power and bargaining in agrifood markets: A review of emerging topics and tools," Agribusiness, John Wiley & Sons, Ltd., vol. 34(1), pages 6-23, December.
    12. Wang, Shinn-Shyr & Stiegert, Kyle W. & Dhar, Tirtha Pratim, 2006. "Strategic Pricing Behavior under Asset Value Maximization," Staff Papers 12612, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.

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