IDEAS home Printed from https://ideas.repec.org/p/cmf/wpaper/wp2011_1104.html
   My bibliography  Save this paper

Advertising and Consumer Awareness of New, Differentiated Products

Author

Listed:

Abstract

This article proposes a novel approach to assess the dynamic effect that advertising expenditures have regarding which products consumers include in their choice sets. In a discrete-choice model consumers face choice sets that evolve according to their awareness of each product. Advertising expenditures have a dynamic effect in the sense that they raise consumer awareness of a product, increasing present and future sales. To estimate this effect the authors explicitly model the firms' dynamic advertising decisions and illustrate the model using data from the Spanish automobile market. The results show that the effect of advertising on awareness is dynamic and that accounting for it is crucial in explaining the evolution of product sales over its life cycle. Furthermore, we show that the awareness process can be significantly sped up by advertising. Thus there is a great heterogeneity in the awareness process among products depending on the level of advertising expenditures and it may range from one to six years.

Suggested Citation

  • Alicia Barroso & Gerard Llobet, 2011. "Advertising and Consumer Awareness of New, Differentiated Products," Working Papers wp2011_1104, CEMFI.
  • Handle: RePEc:cmf:wpaper:wp2011_1104
    as

    Download full text from publisher

    File URL: https://www.cemfi.es/ftp/wp/1104.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sridhar Narayanan & Puneet Manchanda, 2009. "Heterogeneous Learning and the Targeting of Marketing Communication for New Products," Marketing Science, INFORMS, vol. 28(3), pages 424-441, 05-06.
    2. Alok Bhargava & J. D. Sargan, 2006. "Estimating Dynamic Random Effects Models From Panel Data Covering Short Time Periods," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 1, pages 3-27, World Scientific Publishing Co. Pte. Ltd..
    3. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    4. Patrick Bajari & C. Lanier Benkard & Jonathan Levin, 2007. "Estimating Dynamic Models of Imperfect Competition," Econometrica, Econometric Society, vol. 75(5), pages 1331-1370, September.
    5. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.
    6. Andrew Ching & Masakazu Ishihara, 2010. "The effects of detailing on prescribing decisions under quality uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 8(2), pages 123-165, June.
    7. Trichy V. Krishnan & Dipak C. Jain, 2006. "Optimal Dynamic Advertising Policy for New Products," Management Science, INFORMS, vol. 52(12), pages 1957-1969, December.
    8. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    9. María Moral & Jordi Jaumandreu, 2007. "Automobile demand, model cycle and age effects," Spanish Economic Review, Springer;Spanish Economic Association, vol. 9(3), pages 193-218, September.
    10. Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-342, March.
    11. Ulrich Doraszelski & Sarit Markovich, 2007. "Advertising dynamics and competitive advantage," RAND Journal of Economics, RAND Corporation, vol. 38(3), pages 557-592, September.
    12. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    13. Hoyer, Wayne D, 1984. "An Examination of Consumer Decision Making for a Common Repeat Purchase Product," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(3), pages 822-829, December.
    14. Michelle Sovinsky Goeree, 2005. "Advertising in the US Personal Computer Industry," Industrial Organization 0503002, University Library of Munich, Germany.
    15. Frank Verboven, 1996. "International Price Discrimination in the European Car Market," RAND Journal of Economics, The RAND Corporation, vol. 27(2), pages 240-268, Summer.
    16. Richard Ericson & Ariel Pakes, 1995. "Markov-Perfect Industry Dynamics: A Framework for Empirical Work," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 62(1), pages 53-82.
    17. Chiang, Jeongwen & Chib, Siddhartha & Narasimhan, Chakravarthi, 1998. "Markov chain Monte Carlo and models of consideration set and parameter heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 223-248, November.
    18. John H. Roberts & Glen L. Urban, 1988. "Modeling Multiattribute Utility, Risk, and Belief Dynamics for New Consumer Durable Brand Choice," Management Science, INFORMS, vol. 34(2), pages 167-185, February.
    19. Ackerberg, Daniel A, 2001. "Empirically Distinguishing Informative and Prestige Effects of Advertising," RAND Journal of Economics, The RAND Corporation, vol. 32(2), pages 316-333, Summer.
    20. Mitra, Anusree & Lynch, John G, Jr, 1995. "Toward a Reconciliation of Market Power and Information Theories of Advertising Effects on Price Elasticity," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(4), pages 644-659, March.
    21. Draganska, Michaela & Klapper, Daniel, 2010. "Choice Set Heterogeneity and the Role of Advertising: An Analysis with Micro and Macro Data," Research Papers 2063, Stanford University, Graduate School of Business.
    22. C. Clark & Ulrich Doraszelski & Michaela Draganska, 2009. "The effect of advertising on brand awareness and perceived quality: An empirical investigation using panel data," Quantitative Marketing and Economics (QME), Springer, vol. 7(2), pages 207-236, June.
    23. Pradeep K. Chintagunta & Vrinda Kadiyali & Naufel J. Vilcassim, 2006. "Endogeneity and Simultaneity in Competitive Pricing and Advertising: A Logit Demand Analysis," The Journal of Business, University of Chicago Press, vol. 79(6), pages 2761-2788, November.
    24. Hansen, Lars Peter & Singleton, Kenneth J, 1982. "Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 50(5), pages 1269-1286, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Invited Paper ---Learning Models: An Assessment of Progress, Challenges, and New Developments," Marketing Science, INFORMS, vol. 32(6), pages 913-938, November.
    2. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    3. Draganska, Michaela & Klapper, Daniel, 2010. "Choice Set Heterogeneity and the Role of Advertising: An Analysis with Micro and Macro Data," Research Papers 2063, Stanford University, Graduate School of Business.
    4. Griffith, Rachel & Dubois, Pierre & O'Connell, Martin, 2014. "The Effects of Banning Advertising on Demand, Supply and Welfare: Structural Estimation on a Junk Food Market," CEPR Discussion Papers 9942, C.E.P.R. Discussion Papers.
    5. Simon P. Anderson & Federico Ciliberto & Jura Liaukonyte & Régis Renault, 2016. "Push-me pull-you: comparative advertising in the OTC analgesics industry," RAND Journal of Economics, RAND Corporation, vol. 47(4), pages 1029-1056, November.
    6. Victor Aguirregabiria & Margaret Slade, 2017. "Empirical models of firms and industries," Canadian Journal of Economics, Canadian Economics Association, vol. 50(5), pages 1445-1488, December.
    7. Coublucq, Daniel, 2013. "Demand estimation with selection bias: A dynamic game approach with an application to the US railroad industry," DICE Discussion Papers 94, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    8. Michael Cohen & Rui Huang & Chen Zhu, 2012. "The Use of Voluntary Marketing Initiatives to Improve the Nutritional Profile of Kids Cereals," Working Papers 11, University of Connecticut, Department of Agricultural and Resource Economics, Charles J. Zwick Center for Food and Resource Policy.
    9. Aguirregabiria, Victor & Nevo, Aviv, 2010. "Recent developments in empirical IO: dynamic demand and dynamic games," MPRA Paper 27814, University Library of Munich, Germany.
    10. Pakes, Ariel, 2017. "Empirical tools and competition analysis: Past progress and current problems," International Journal of Industrial Organization, Elsevier, vol. 53(C), pages 241-266.
    11. Ching, Andrew T., 2010. "Consumer learning and heterogeneity: Dynamics of demand for prescription drugs after patent expiration," International Journal of Industrial Organization, Elsevier, vol. 28(6), pages 619-638, November.
    12. Chan, Tat Y. & Narasimhan, Chakravarthi & Yoon, Yeujun, 2017. "Advertising and price competition in a manufacturer-retailer channel," International Journal of Research in Marketing, Elsevier, vol. 34(3), pages 694-716.
    13. Jean-Pierre Dubé & Günter Hitsch & Puneet Manchanda, 2005. "An Empirical Model of Advertising Dynamics," Quantitative Marketing and Economics (QME), Springer, vol. 3(2), pages 107-144, June.
    14. Victor Aguirregabiria & Gustavo Vicentini, 2006. "Dynamic Spatial Competition Between Multi-Store Firms," Working Papers tecipa-253, University of Toronto, Department of Economics.
    15. Brett R. Gordon & Wesley R. Hartmann, 2013. "Advertising Effects in Presidential Elections," Marketing Science, INFORMS, vol. 32(1), pages 19-35, June.
    16. Song Lin & Juanjuan Zhang & John R. Hauser, 2015. "Learning from Experience, Simply," Marketing Science, INFORMS, vol. 34(1), pages 1-19, January.
    17. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2020. "How much do consumers know about the quality of products? Evidence from the diaper market," The Japanese Economic Review, Springer, vol. 71(4), pages 541-569, October.
    18. Suppliet, Moritz, 2020. "Umbrella branding in pharmaceutical markets," Journal of Health Economics, Elsevier, vol. 73(C).
    19. Daniel Ackerberg, 2009. "A new use of importance sampling to reduce computational burden in simulation estimation," Quantitative Marketing and Economics (QME), Springer, vol. 7(4), pages 343-376, December.
    20. Reynaert, Mathias & Verboven, Frank, 2014. "Improving the performance of random coefficients demand models: The role of optimal instruments," Journal of Econometrics, Elsevier, vol. 179(1), pages 83-98.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cmf:wpaper:wp2011_1104. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Araceli Requerey (email available below). General contact details of provider: https://edirc.repec.org/data/cemfies.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.