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Generalizing What Is Known About Temporal Aggregation and Advertising Carryover

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  • Robert P. Leone

    (The Ohio State University)

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    Abstract

    This paper provides a theoretical explanation for the inconsistent findings from previous econometric analyses of aggregated data concerning the duration of advertising carryover. Using this theoretical explanation and the knowledge of a data interval bias, the paper reviews and summarizes the empirical work in the area of sales response modeling, and then after adjusting for aggregation bias, presents support for an empirical generalization that the average advertising duration interval is of brief duration—typically between six and nine months.

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    File URL: http://dx.doi.org/10.1287/mksc.14.3.G141
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    Bibliographic Info

    Article provided by INFORMS in its journal Marketing Science.

    Volume (Year): 14 (1995)
    Issue (Month): 3_supplement ()
    Pages: G141-G150

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    Handle: RePEc:inm:ormksc:v:14:y:1995:i:3_supplement:p:g141-g150

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    Related research

    Keywords: advertising; advertising duration/carryover; regression-data aggregation;

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    Cited by:
    1. Dong, Diansheng & Schmit, Todd M. & Kaiser, Harry M., 2007. "Optimal Media Allocation of Generic Fluid Milk Advertising Expenditures: The Case of New York State," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 36(2), October.
    2. Henry W. Kinnucan & Yuliang Miao, 1999. "Media-specific returns to generic advertising: The case of catfish," Agribusiness, John Wiley & Sons, Ltd., vol. 15(1), pages 81-99.
    3. Mark W. Frank, 2006. "Media Substitution in Advertising: A Spirited Case Study," Working Papers 0606, Sam Houston State University, Department of Economics and International Business.
    4. Greg Filbeck & Xin Zhao & Daniel Tompkins & Peggy Chong, 2009. "Share price reactions to advertising announcements and broadcast of media events," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 30(4), pages 253-264.
    5. Cotterill, Ronald W. & Putsis, William P., Jr. & Dhar, Ravi, 2000. "Market Share and Price Setting Behavior For Private Labels and National Brands," Research Reports 25209, University of Connecticut, Food Marketing Policy Center.
    6. Ralph Breuer & Malte Brettel & Andreas Engelen, 2011. "Incorporating long-term effects in determining the effectiveness of different types of online advertising," Marketing Letters, Springer, vol. 22(4), pages 327-340, November.
    7. KIYGI CALLI, Meltem & WEVERBERGH, Marcel & FRANSES, Philip Hans, 2008. "Modeling the effectiveness of hourly direct-response radio commercials," Working Papers 2008005, University of Antwerp, Faculty of Applied Economics.
    8. Sina Henningsen & Rebecca Heuke & Michel Clement, 2011. "Determinants of Advertising Effectiveness: The Development of an International Advertising Elasticity Database and a Meta-Analysis," BuR - Business Research, German Academic Association for Business Research, vol. 4(2), pages 193-239, December.
    9. Franses, Philip Hans, 2006. "Forecasting in Marketing," Handbook of Economic Forecasting, Elsevier.
    10. Cotterill, Ronald W. & Putsis, William P., Jr. & Dhar, Ravi, 1999. "Assessing the Competitive Interaction Between Private Labels and National Brands," Research Reports 25177, University of Connecticut, Food Marketing Policy Center.
    11. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.
    12. Seldon, Barry J. & Jewell, R. Todd & O'Brien, Daniel M., 2000. "Media substitution and economies of scale in advertising," International Journal of Industrial Organization, Elsevier, vol. 18(8), pages 1153-1180, December.
    13. Naik, P. & Piersma, N., 2002. "Understanding the role of marketing communications in direct marketing," Econometric Institute Research Papers EI 2002-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Grewal, Rajdeep & Mills, Jeffrey A. & Mehta, Raj & Mujumdar, Sudesh, 2001. "Using cointegration analysis for modeling marketing interactions in dynamic environments: methodological issues and an empirical illustration," Journal of Business Research, Elsevier, vol. 51(2), pages 127-144, February.
    15. Richard, Oliver & Van Horn, Larry, 2004. "Persistence in prescriptions of branded drugs," International Journal of Industrial Organization, Elsevier, vol. 22(4), pages 523-540, April.
    16. Genesove, David & Simhon, Avi, 2008. "Seasonality and the Effect of Advertising on Price," CEPR Discussion Papers 6999, C.E.P.R. Discussion Papers.
    17. van Heerde, H.J. & Helsen, K. & Dekimpe, M.G., 2005. "Managing Product-Harm Crises," ERIM Report Series Research in Management ERS-2005-044-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    18. Franses, Ph.H.B.F. & Vriens, M., 2004. "Advertising effects on awareness, consideration and brand choice using tracking data," ERIM Report Series Research in Management ERS-2004-028-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

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