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Advertising as a signaling device: Simulated maximum likelihood estimation of a multiple random effects count data model

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  • Hellström, Jörgen
  • Rudholm, Niklas

Abstract

The paper empirically studies whether pharmaceutical firms use advertising as a signal for high quality drugs. A multiple random effects count data hurdle model is specified and a simulated maximum likelihood estimation approach is developed and utilized in the empirical analysis.

Suggested Citation

  • Hellström, Jörgen & Rudholm, Niklas, 2008. "Advertising as a signaling device: Simulated maximum likelihood estimation of a multiple random effects count data model," Economics Letters, Elsevier, vol. 101(3), pages 227-229, December.
  • Handle: RePEc:eee:ecolet:v:101:y:2008:i:3:p:227-229
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    References listed on IDEAS

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    1. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
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    6. Ernst R. Berndt & Iain M. Cockburn & Zvi Griliches, 1996. "Pharmaceutical Innovations and Market Dynamics: Tracking Effects on Price Indexes for Antidepressant Drugs," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(1996 Micr), pages 133-199.
    7. 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.
    8. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    9. 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.
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