IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Structural Analysis of Manufacturer Pricing in the Presence of a Strategic Retailer

Listed author(s):
  • K. Sudhir


    (School of Management)

  • Vrinda Kadiyali


    (Samuel Curtis Johnson Graduate School of Management)

  • Vithala R. Rao


    (Samuel Curtis Johnson Graduate School of Management)

Registered author(s):

    Consumer goods manufacturers usually sell their brands to consumers through common independent retailers. Theoretical research on such channel structures has analyzed the optimal behavior of channel members under alternative assumptions of manufacturer-retailer interaction (Vertical Strategic Interaction). Research in the Empirical Industrial Organization has focused on analyzing the competitive interactions between manufacturers (Horizontal Strategic Interaction). Decision Support Systems have made various assumptions about retailer pricing rules (e.g., constant markup, category profit maximization). The appropriateness of such assumptions about strategic behavior for any specific market however is an empirical question. This paper therefore empirically infers: (1) The Vertical Strategic Interaction (VSI) between manufacturers and retailer (2) The Horizontal Strategic Interaction (HSI) between manufacturers simultaneously with the VSI; (3) The pricing rule used by a retailer The approach is particularly appealing because it can be used with widely available scanner data, where there is no information on wholesale prices. Researchers usually have no access to wholesale prices. Even manufacturers, who have access to their own wholesale prices, usually have limited information on competitors' wholesale prices. In the absence of wholesale prices, we derive formulae for wholesale prices using game theoretic solution techniques under the specific assumptions of vertical and horizontal strategic interaction and retailer pricing rules. We then embed the formulae for wholesale prices into the estimation equations. While our empirical illustration is using scanner data without wholesale prices, the model itself can be applied when wholesale prices are available. Early research on the inference of HSI among manufacturers in setting wholesale prices using scanner data (for e.g., Kadiyali, Vilcassim and Chintagunta, 1996, 1999) made the simplifying assumption that retailers charge a constant margin. This assumption enabled them to infer wholesale prices and analyze competitive interactions between manufacturers. In this paper, we show that this model is econometrically identical to a model that measures retail price coordination across brands. Hence the inferred cooperation among manufacturers could be exaggerated by the coordinated pricing (category management) done by the retailer. We find empirical support for this argument. This highlights the need to properly model and infer VSI simultaneously to accurately estimate the HSI when using data at the retail level. Functional forms of demand have been evaluated in terms of the fit of the model to sales data. But recent theoretical research on channels (Lee and Staelin, 1997; Tyagi, 1999) has shown that the functional form has serious implications for strategic behavior such as retail pass-through. While the logit and linear model implies equilibrium passthrough of less than 100% (Lee and Staelin call this Vertical Strategic Substitute (VSS)), the multiplicative model implies optimal passthrough of greater than 100% (Vertical Strategic Complement (VSC)). Since passthrough rates on promotions have been found to be below or above 100% (Chevalier and Curhan 1976; Armstrong 1991), we empirically test the appropriateness of the logit (VSS) and the multiplicative (VSC) functional form for the data. We perform our analysis in the yogurt and peanut butter categories for the two biggest stores in a local market. We found that the VSS implications of the logit fit the data better than the multiplicative model. We also find that for both categories, the best fitting model is one in which: (1) the retailer maximizes category profits (2) the VSI is Manufacturer-Stackelberg and (3) manufacturer pricing (HSI) is tacitly collusive. The fact that the retailer maximizes category profits is consistent with theoretical expectations. The inference that the VSI is Manufacturer-Stackelberg reflects the institutional reality of the timing of the game. Retailers set their retail prices after manufacturers set their wholesale prices. Note that in the stores and product categories that we analyze, the two manufacturers own the dominant brands with combined market shares of about 82% in the yogurt market and 65% in the peanut butter market. The result is also consistent with a balance of power argument in the literature. The finding that manufacturer pricing is tacitly collusive is consistent with the argument that firms involved in long-term competition in concentrated markets can achieve tacit collusion. Managers use decision support systems (DSS) for promotion planning that routinely make assumptions about VSI, HSI and the functional form. The results from our analysis are of substantive import in judging the appropriateness of assumptions made in such DSS.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: no

    Paper provided by Yale School of Management in its series Yale School of Management Working Papers with number ysm229.

    in new window

    Date of creation: 23 Oct 2001
    Handle: RePEc:ysm:somwrk:ysm229
    Contact details of provider: Web page:

    More information through EDIRC

    No references listed on IDEAS
    You can help add them by filling out this form.

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:ysm:somwrk:ysm229. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.