IDEAS home Printed from https://ideas.repec.org/a/bpj/revmkt/v3y2005i1p21n3.html
   My bibliography  Save this article

Modeling Selectivity in Households' Purchase Quantity Outcomes: A Count Data Approach

Author

Listed:
  • Zhang Qin

    (University of Texas at Dallas School of Management, zhangq@utdallas.edu)

  • Seetharaman P.B.

    (Rice University, seethu@wustl.edu)

  • Narasimhan Chakravarthi

    (Washington University, St. Louis, Narasimhan@wustl.edu)

Abstract

We present an econometric technique for modeling endogenous selectivity in households quantity outcomes as observed in scanner panel data. Simultaneous models of incidence, brand choice and quantity, that treat quantity outcomes as count data, ignore such self-selectivity considerations in quantity outcomes. Previously proposed approaches to modeling selectivity in continuous quantity outcomes do not apply to count data. Therefore, we adopt a recently proposed econometric technique to deal with selectivity in count data, and then appropriately extend it to handle correlations of quantity outcomes not only with incidence outcomes but also with brand choice outcomes. Our proposed methodology will be useful to researchers who want to estimate simultaneous models of whether, what and how much to buy decisions of households, treating quantity data as counts.

Suggested Citation

  • Zhang Qin & Seetharaman P.B. & Narasimhan Chakravarthi, 2005. "Modeling Selectivity in Households' Purchase Quantity Outcomes: A Count Data Approach," Review of Marketing Science, De Gruyter, vol. 3(1), pages 1-21, July.
    • Handle: RePEc:bpj:revmkt:v:3:y:2005:i:1:p:21:n:3
    DOI: 10.2202/1546-5616.1035
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1546-5616.1035
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1546-5616.1035?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:bpj:revmkt:v:3:y:2005:i:1:p:21:n:3. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.