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Pass-through timing

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  • Sergio Meza
  • K. Sudhir

Abstract

Trade promotions are the most important promotional tool available to a manufacturer. However trade promotions can achieve their objective of increasing short-term sales only if the retailer passes through these promotions. Empirical research has documented that there is a wide variation in retail pass-through across products. However little is known about the variations in pass-through over time. This is particularly important for products with distinct seasonal patterns. We argue that extant methods of measuring pass-through are inadequate for seasonal products. We therefore introduce a measurement approach and illustrate it using two product categories. We find interesting differences in pass-through for loss-leader products versus regular products during high demand and regular demand periods. We find that retailers use a deep and narrow pass-through strategy (high pass-through on loss-leader products, but small pass-through on regular products) during periods of regular demand and broad and shallow pass-through strategy (smaller, but similar pass-through on both loss-leader and regular products) during periods of high demand. Loss leader products continue to obtain higher pass-through in high demand periods, if the category's high demand period is also a high demand period for other product categories as well. Copyright Springer Science + Business Media, LLC 2006

Suggested Citation

  • Sergio Meza & K. Sudhir, 2006. "Pass-through timing," Quantitative Marketing and Economics (QME), Springer, vol. 4(4), pages 351-382, December.
  • Handle: RePEc:kap:qmktec:v:4:y:2006:i:4:p:351-382
    DOI: 10.1007/s11129-006-9008-y
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    References listed on IDEAS

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    1. K. Sudhir, 2001. "Competitive Pricing Behavior in the Auto Market: A Structural Analysis," Marketing Science, INFORMS, vol. 20(1), pages 42-60, January.
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    7. K. Sudhir, 2001. "Competitive Pricing Behavior in the US Auto Market: A Structural Analysis," Yale School of Management Working Papers ysm228, Yale School of Management.
    8. Judith A. Chevalier & Anil K. Kashyap & Peter E. Rossi, 2003. "Why Don't Prices Rise During Periods of Peak Demand? Evidence from Scanner Data," American Economic Review, American Economic Association, vol. 93(1), pages 15-37, March.
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    Cited by:

    1. Guhl, Daniel & Baumgartner, Bernhard & Kneib, Thomas & Steiner, Winfried J., 2018. "Estimating time-varying parameters in brand choice models: A semiparametric approach," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 394-414.
    2. Guhl, Daniel, 2019. "Addressing endogeneity in aggregate logit models with time-varying parameters for optimal retail-pricing," European Journal of Operational Research, Elsevier, vol. 277(2), pages 684-698.
    3. Kusum Ailawadi & Eric Bradlow & Michaela Draganska & Vincent Nijs & Robert Rooderkerk & K. Sudhir & Kenneth Wilbur & Jie Zhang, 2010. "Empirical models of manufacturer-retailer interaction: A review and agenda for future research," Marketing Letters, Springer, vol. 21(3), pages 273-285, September.
    4. Martín-Herrán, Guiomar & Sigué, Simon-Pierre & Zaccour, Georges, 2010. "The Dilemma of Pull and Push-Price Promotions," Journal of Retailing, Elsevier, vol. 86(1), pages 51-68.
    5. Pancras, Joseph & Gauri, Dinesh K. & Talukdar, Debabrata, 2013. "Loss leaders and cross-category retailer pass-through: A Bayesian multilevel analysis," Journal of Retailing, Elsevier, vol. 89(2), pages 140-157.

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