IDEAS home Printed from https://ideas.repec.org/p/ems/eureir/1476.html
   My bibliography  Save this paper

A hierarchical Bayes error correction model to explain dynamic effects

Author

Listed:
  • Fok, D.
  • Horváth, C.
  • Paap, R.
  • Franses, Ph.H.B.F.

Abstract

For promotional planning and market segmentation it is important to understand the short-run and long-run effects of the marketing mix on category and brand sales. In this paper we put forward a sales response model to explain the differences in short-run and long-run effects of promotions on sales. The model consists of a vector autoregression rewritten in error-correction format which allows us to disentangle the long-run effects from the short-run effects. In a second level of the model, we correlate the short-run and long-run elasticities with various brand-specific and category-specific characteristics. The model is applied to weekly sales of 100 different brands in 25 product categories. Our empirical results allow us to make generalizing statements on the dynamic effects of promotions in a statistically coherent way.

Suggested Citation

  • Fok, D. & Horváth, C. & Paap, R. & Franses, Ph.H.B.F., 2004. "A hierarchical Bayes error correction model to explain dynamic effects," Econometric Institute Research Papers EI 2004-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1476
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/1476/EI200427.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Robert C. Blattberg & Richard Briesch & Edward J. Fox, 1995. "How Promotions Work," Marketing Science, INFORMS, vol. 14(3_supplem), pages 122-132.
    2. Verhoef, P.C. & Pauwels, K.H., 2005. "Assessing Customer Evaluation and Revenue Consequences of Component Sharing Across Brands in the Vertical Product Line," ERIM Report Series Research in Management ERS-2005-007-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.
    3. Richard Paap & Philip Hans Franses, 2000. "A dynamic multinomial probit model for brand choice with different long-run and short-run effects of marketing-mix variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 717-744.
    4. Alan L. Montgomery & Shibo Li & Kannan Srinivasan & John C. Liechty, 2004. "Modeling Online Browsing and Path Analysis Using Clickstream Data," Marketing Science, INFORMS, vol. 23(4), pages 579-595, November.
    5. Gurumurthy Kalyanaram & Russell S. Winer, 1995. "Empirical Generalizations from Reference Price Research," Marketing Science, INFORMS, vol. 14(3_supplem), pages 161-169.
    6. Alan L. Montgomery, 1997. "Creating Micro-Marketing Pricing Strategies Using Supermarket Scanner Data," Marketing Science, INFORMS, vol. 16(4), pages 315-337.
    7. Granger, Clive W J, 1993. "What Are We Learning about the Long-Run?," Economic Journal, Royal Economic Society, vol. 103(417), pages 307-317, March.
    8. Moriarty, Mark M., 1985. "Transfer function analysis of the relationship between advertising and sales: A synthesis of prior research," Journal of Business Research, Elsevier, vol. 13(3), pages 247-257, June.
    9. Ruth N. Bolton, 1989. "The Relationship Between Market Characteristics and Promotional Price Elasticities," Marketing Science, INFORMS, vol. 8(2), pages 153-169.
    10. David R. Bell & Jeongwen Chiang & V. Padmanabhan, 1999. "The Decomposition of Promotional Response: An Empirical Generalization," Marketing Science, INFORMS, vol. 18(4), pages 504-526.
    11. Randolph E. Bucklin & Sunil Gupta, 1999. "Commercial Use of UPC Scanner Data: Industry and Academic Perspectives," Marketing Science, INFORMS, vol. 18(3), pages 247-273.
    12. Cleeren, K. & Dekimpe, M.G. & Verboven, F., 2005. "Intra- and Inter-Channel Competition in Local-Service Sectors," ERIM Report Series Research in Management ERS-2005-018-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.
    13. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2005. "The European Consumer: United In Diversity?," ERIM Report Series Research in Management ERS-2005-022-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.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Vroegrijk, Mark & Gijsbrechts, Els & Campo, Katia, 2016. "Battling for the Household's Category Buck: Can Economy Private Labels Defend Supermarkets Against the Hard-Discounter Threat?," Journal of Retailing, Elsevier, vol. 92(3), pages 300-318.
    2. 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.
    3. van Everdingen, Y.M. & Fok, D. & Stremersch, S., 2008. "Modeling Global Spill-Over of New Product Takeoff," ERIM Report Series Research in Management ERS-2008-067-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.
    4. Frison, Steffi & Dekimpe, Marnik G. & Croux, Christophe & De Maeyer, Peter, 2014. "Billboard and cinema advertising: Missed opportunity or spoiled arms?," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 425-433.
    5. Kiygi Calli, M. & Weverbergh, M. & Franses, Ph.H.B.F., 2008. "Modeling the Effectiveness of Hourly Direct-Response Radio Commercials," ERIM Report Series Research in Management ERS-2008-019-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.
    6. van Heerde, H.J. & Dekimpe, M.G. & Putsis, W.P., 2004. "Marketing Models and the Lucas Critique," ERIM Report Series Research in Management ERS-2004-080-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.
    7. Koen Pauwels & Imran Currim & Marnik Dekimpe & Dominique Hanssens & Natalie Mizik & Eric Ghysels & Prasad Naik, 2004. "Modeling Marketing Dynamics by Time Series Econometrics," Marketing Letters, Springer, vol. 15(4), pages 167-183, December.
    8. Dawes, John G., 2012. "Brand-Pack Size Cannibalization Arising from Temporary Price Promotions," Journal of Retailing, Elsevier, vol. 88(3), pages 343-355.

    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. Dawes, John G., 2012. "Brand-Pack Size Cannibalization Arising from Temporary Price Promotions," Journal of Retailing, Elsevier, vol. 88(3), pages 343-355.
    2. Praveen K. Kopalle & Carl F. Mela & Lawrence Marsh, 1999. "The Dynamic Effect of Discounting on Sales: Empirical Analysis and Normative Pricing Implications," Marketing Science, INFORMS, vol. 18(3), pages 317-332.
    3. Lamey, L. & Deleersnyder, B. & Dekimpe, M.G. & Steenkamp, J-B.E.M., 2005. "The Impact of Business-Cycle Fluctuations on Private-Label Share," ERIM Report Series Research in Management ERS-2005-061-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.
    4. Koen Pauwels & Shuba Srinivasan & Philip Hans Franses, 2007. "When Do Price Thresholds Matter in Retail Categories?," Marketing Science, INFORMS, vol. 26(1), pages 83-100, 01-02.
    5. Guyt, Jonne, 2015. "Consumer choice models on the effect of promotions in retailing," Other publications TiSEM c310f652-d725-4764-aac7-b, Tilburg University, School of Economics and Management.
    6. van Bruggen, G.H. & Wierenga, B., 2005. "When are CRM Systems Successful? The Perspective of the User and of the Organization," ERIM Report Series Research in Management ERS-2005-048-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.
    7. Weber, Anett & Steiner, Winfried J., 2021. "Modeling price response from retail sales: An empirical comparison of models with different representations of heterogeneity," European Journal of Operational Research, Elsevier, vol. 294(3), pages 843-859.
    8. Breugelmans, Els & Campo, Katia, 2016. "Cross-Channel Effects of Price Promotions: An Empirical Analysis of the Multi-Channel Grocery Retail Sector," Journal of Retailing, Elsevier, vol. 92(3), pages 333-351.
    9. van Oest, Rutger, 2013. "Why are Consumers Less Loss Averse in Internal than External Reference Prices?," Journal of Retailing, Elsevier, vol. 89(1), pages 62-71.
    10. Shuba Srinivasan & Koen Pauwels & Dominique M. Hanssens & Marnik G. Dekimpe, 2004. "Do Promotions Benefit Manufacturers, Retailers, or Both?," Management Science, INFORMS, vol. 50(5), pages 617-629, May.
    11. Baohong Sun, 2005. "Promotion Effect on Endogenous Consumption," Marketing Science, INFORMS, vol. 24(3), pages 430-443, July.
    12. Srinivasan, S. & Pauwels, K.H. & Hanssens, D.M. & Dekimpe, M.G., 2002. "Do Promotions Benefit Manufacturers, Retailers or Both?," ERIM Report Series Research in Management ERS-2002-21-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.
    13. Randolph E. Bucklin & Sunil Gupta, 1999. "Commercial Use of UPC Scanner Data: Industry and Academic Perspectives," Marketing Science, INFORMS, vol. 18(3), pages 247-273.
    14. David R. Bell & Jeongwen Chiang & V. Padmanabhan, 1999. "The Decomposition of Promotional Response: An Empirical Generalization," Marketing Science, INFORMS, vol. 18(4), pages 504-526.
    15. Jones, Eugene, 2014. "An Empirical Assessment of Consumers’ Preferences for Coffee," Journal of Food Distribution Research, Food Distribution Research Society, vol. 45(2), pages 1-26, July.
    16. Steenkamp, J-B.E.M. & Nijs, V.R. & Hanssens, D.M. & Dekimpe, M.G., 2002. "Competitive Reactions and the Cross-Sales Effects of Advertising and Promotion," ERIM Report Series Research in Management ERS-2002-20-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.
    17. Andrés Elberg & Pedro M. Gardete & Rosario Macera & Carlos Noton, 2019. "Dynamic effects of price promotions: field evidence, consumer search, and supply-side implications," Quantitative Marketing and Economics (QME), Springer, vol. 17(1), pages 1-58, March.
    18. Kim, Joon Ho & Kang, Kyung Ho, 2018. "The effect of promotion on gaming revenue: A study of the US casino industry," Tourism Management, Elsevier, vol. 65(C), pages 317-326.
    19. Raj Sethuraman & V. Srinivasan & Doyle Kim, 1999. "Asymmetric and Neighborhood Cross-Price Effects: Some Empirical Generalizations," Marketing Science, INFORMS, vol. 18(1), pages 23-41.
    20. Bernhard Baumgartner & Daniel Guhl & Thomas Kneib & Winfried J. Steiner, 2018. "Flexible estimation of time-varying effects for frequently purchased retail goods: a modeling approach based on household panel data," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 837-873, October.

    More about this item

    Keywords

    hierarchical Bayes; sales; short and long run effects; vector autoregression;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    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:ems:eureir:1476. 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: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/feeurnl.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.