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Advertising as a Signaling Device in the Swedish Pharmaceuticals Market

Author

Listed:
  • Hellström, Jörgen

    (Department of Economics, Umeå University)

  • Rudholm, Niklas

    (Department of Economics, Umeå University)

Abstract

The paper empirically studies whether pharmaceutical firms uses advertising as a signal for high quality drugs. A nested random effects count data hurdle model is introduced to handle the excess number of zero observations in the sample as well as nested random drug, firm and substance specific effects. The empirical study indicate that drug quality (measured as the number of side-effects) do not influence pharmaceutical firms decision to advertise or not, but do affect the number of ads in a given period. The higher quality of the drug the more ads.

Suggested Citation

  • Hellström, Jörgen & Rudholm, Niklas, 2003. "Advertising as a Signaling Device in the Swedish Pharmaceuticals Market," Umeå Economic Studies 612, Umeå University, Department of Economics.
  • Handle: RePEc:hhs:umnees:0612
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    References listed on IDEAS

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    1. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    2. Mark N. Hertzendorf & Per Baltzer Overgaard, 2001. "Price Competition and Advertising Signals: Signaling by Competing Senders," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 10(4), pages 621-662, December.
    3. Milgrom, Paul & Roberts, John, 1986. "Price and Advertising Signals of Product Quality," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 796-821, August.
    4. Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441, Elsevier.
    5. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    6. Nelson, Phillip, 1970. "Information and Consumer Behavior," Journal of Political Economy, University of Chicago Press, vol. 78(2), pages 311-329, March-Apr.
    7. Bagwell, Kyle & Riordan, Michael H, 1991. "High and Declining Prices Signal Product Quality," American Economic Review, American Economic Association, vol. 81(1), pages 224-239, March.
    8. Nelson, Philip, 1974. "Advertising as Information," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 729-754, July/Aug..
    9. Antweiler, Werner, 2001. "Nested random effects estimation in unbalanced panel data," Journal of Econometrics, Elsevier, vol. 101(2), pages 295-313, April.
    10. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
    11. Gene M. Grossman & Carl Shapiro, 1984. "Informative Advertising with Differentiated Products," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 51(1), pages 63-81.
    12. Thomas, Louis & Shane, Scott & Weigelt, Keith, 1998. "An empirical examination of advertising as a signal of product quality," Journal of Economic Behavior & Organization, Elsevier, vol. 37(4), pages 415-430, December.
    13. Mark W. Nichols, 1998. "Advertising and Quality in the U.S. Market for Automobiles," Southern Economic Journal, John Wiley & Sons, vol. 64(4), pages 922-939, April.
    14. Hao Zhao, 2000. "Raising Awareness and Signaling Quality to Uninformed Consumers: A Price-Advertising Model," Marketing Science, INFORMS, vol. 19(4), pages 390-396, January.
    15. Michael Spence, 1973. "Job Market Signaling," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(3), pages 355-374.
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    More about this item

    Keywords

    Signaling; pharmaceutical industry; advertising; product quality; nested random effects; count data;
    All these keywords.

    JEL classification:

    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L21 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Business Objectives of the Firm

    NEP fields

    This paper has been announced in the following NEP Reports:

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