IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v7y1988i3p252-270.html
   My bibliography  Save this article

Recovering Measures of Advertising Carryover from Aggregate Data: The Role of the Firm's Decision Behavior

Author

Listed:
  • Gary J. Russell

    (Vanderbilt University)

Abstract

Data interval bias, the biased estimation of advertising carryover in aggregate data, can be viewed as a misinterpretation of the aggregate advertising-sales relationship due to missing micro advertising data. This paper argues that if the researcher does not explicitly model the firm's advertising decisions, he will incorrectly interpolate the missing data and thereby allow the firm's decision behavior to influence inferences about advertising carryover. Drawing upon a general model of advertising decision behavior, the expected aggregate form of the Koyck relationship is developed and compared to existing bias correction methodologies. Although it is difficult to find any parsimonious procedure which is robust with respect to all types of decision behavior, allowing lagged advertising to enter the classical Koyck equation emerges as a simple method of obtaining a reasonable estimate of advertising carryover in aggregate data.

Suggested Citation

  • Gary J. Russell, 1988. "Recovering Measures of Advertising Carryover from Aggregate Data: The Role of the Firm's Decision Behavior," Marketing Science, INFORMS, vol. 7(3), pages 252-270.
    • Handle: RePEc:inm:ormksc:v:7:y:1988:i:3:p:252-270
    DOI: 10.1287/mksc.7.3.252
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.7.3.252
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mksc.7.3.252?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kiygi Calli, M. & Weverbergh, M. & Franses, Ph.H.B.F., 2010. "To Aggregate or Not to Aggregate: Should decisions and models have the same frequency?," ERIM Report Series Research in Management ERS-2010-046-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.
    2. Debanjan Mitra & Peter N. Golder, 2006. "How Does Objective Quality Affect Perceived Quality? Short-Term Effects, Long-Term Effects, and Asymmetries," Marketing Science, INFORMS, vol. 25(3), pages 230-247, 05-06.
    3. Franses, Philip Hans, 2006. "Forecasting in Marketing," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 18, pages 983-1012, Elsevier.
    4. Gerard J. Tellis & Philip Hans Franses, 2006. "Optimal Data Interval for Estimating Advertising Response," Marketing Science, INFORMS, vol. 25(3), pages 217-229, 05-06.
    5. Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2017. "Modeling intra-seasonal heterogeneity in hourly advertising-response models: Do forecasts improve?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 90-101.

    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:inm:ormksc:v:7:y:1988:i:3:p:252-270. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.