IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article

Examining Demand Elasticities in Hanemann's Framework: A Theoretical and Empirical Analysis

  • Nitin Mehta

    ()

    (Rotman School of Management, University of Toronto, Toronto, Ontario M5S 3E6, Canada)

  • Xinlei (Jack) Chen

    ()

    (Sauder School of Business, University of British Columbia, Vancouver, British Columbia V6T 1Z2, Canada)

  • Om Narasimhan

    ()

    (Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455)

This paper examines demand elasticities using an integrated framework proposed by Hanemann [Hanemann, M. W. 1984. Discrete/continuous models of consumer demand. (3) 541–561], which models the incidence, brand choice, and quantity decisions of a consumer as an outcome of her utility maximization subject to budget constraints. Although the Hanemann framework has been the mainstay of earlier efforts to examine these decisions jointly, empirical researchers who have used the it to study purchase behavior have often found that the quantity elasticities are around -1, regardless of the brand or category. We attempt to uncover the underlying reasons for this finding and propose approaches to get as close to the “true” quantity elasticities as possible. We do this by (i) analytically demonstrating how assumptions on the distribution of the brand-specific econometrician's errors imply certain restrictions that in turn force quantity elasticities to -1, (ii) discussing how these restrictions can be alleviated by considering a suitable specification of unobserved parameter heterogeneity, and (iii) using scanner data to empirically illustrate the impact of the restrictions on quantity elasticities and the relative efficacy of multiple specifications of unobserved heterogeneity in easing those restrictions. We find that the specification of unobserved heterogeneity influences estimates of quantity elasticities and that the mixture normal specification outperforms the alternatives.

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: http://dx.doi.org/10.1287/mksc.1090.0524
Download Restriction: no

Article provided by INFORMS in its journal Marketing Science.

Volume (Year): 29 (2010)
Issue (Month): 3 (05-06)
Pages: 422-437

as
in new window

Handle: RePEc:inm:ormksc:v:29:y:2010:i:3:p:422-437
Contact details of provider: Postal:
7240 Parkway Drive, Suite 300, Hanover, MD 21076 USA

Phone: +1-443-757-3500
Fax: 443-757-3515
Web page: http://www.informs.org/
Email:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Hanemann, W Michael, 1984. "Discrete-Continuous Models of Consumer Demand," Econometrica, Econometric Society, vol. 52(3), pages 541-61, May.
  2. Pradeep K. Chintagunta, 1993. "Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households," Marketing Science, INFORMS, vol. 12(2), pages 184-208.
  3. Nair, Harikesh S. & Dube, Jean-Pierre & Chintagunta, Pradeep, 2004. "Accounting for Primary and Secondary Demand Effects with Aggregate Data," Research Papers 1949, Stanford University, Graduate School of Business.
  4. Jeongwen Chiang, 1991. "A Simultaneous Approach to the Whether, What and How Much to Buy Questions," Marketing Science, INFORMS, vol. 10(4), pages 297-315.
  5. Baohong Sun, 2005. "Promotion Effect on Endogenous Consumption," Marketing Science, INFORMS, vol. 24(3), pages 430-443, July.
  6. 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.
  7. Neeraj Arora & Greg M. Allenby & James L. Ginter, 1998. "A Hierarchical Bayes Model of Primary and Secondary Demand," Marketing Science, INFORMS, vol. 17(1), pages 29-44.
Full references (including those not matched with items on IDEAS)

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:inm:ormksc:v:29:y:2010:i:3:p:422-437. 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: (Mirko Janc)

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.