IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v29y2010i3p422-437.html
   My bibliography  Save this article

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

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • Nitin Mehta & Xinlei (Jack) Chen & Om Narasimhan, 2010. "Examining Demand Elasticities in Hanemann's Framework: A Theoretical and Empirical Analysis," Marketing Science, INFORMS, vol. 29(3), pages 422-437, 05-06.
  • Handle: RePEc:inm:ormksc:v:29:y:2010:i:3:p:422-437
    DOI: 10.1287/mksc.1090.0524
    as

    Download full text from publisher

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

    File URL: https://libkey.io/10.1287/mksc.1090.0524?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Baohong Sun, 2005. "Promotion Effect on Endogenous Consumption," Marketing Science, INFORMS, vol. 24(3), pages 430-443, July.
    3. Hanemann, W Michael, 1984. "Discrete-Continuous Models of Consumer Demand," Econometrica, Econometric Society, vol. 52(3), pages 541-561, May.
    4. 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.
    5. Harikesh Nair & Jean-Pierre Dubé & Pradeep Chintagunta, 2005. "Accounting for Primary and Secondary Demand Effects with Aggregate Data," Marketing Science, INFORMS, vol. 24(3), pages 444-460, November.
    6. Peter E. Rossi & Greg M. Allenby, 2003. "Bayesian Statistics and Marketing," Marketing Science, INFORMS, vol. 22(3), pages 304-328, July.
    7. 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.
    8. Pradeep K. Chintagunta, 1993. "Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households," Marketing Science, INFORMS, vol. 12(2), pages 184-208.
    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. Pradeep K. Chintagunta & Harikesh S. Nair, 2011. "Structural Workshop Paper --Discrete-Choice Models of Consumer Demand in Marketing," Marketing Science, INFORMS, vol. 30(6), pages 977-996, November.
    2. Kappe, Eelco & Stadler Blank, Ashley & DeSarbo, Wayne S., 2018. "A random coefficients mixture hidden Markov model for marketing research," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 415-431.
    3. Jean-Pierre H. Dubé, 2018. "Microeconometric Models of Consumer Demand," NBER Working Papers 25215, National Bureau of Economic Research, Inc.
    4. John R. Howell & Sanghak Lee & Greg M. Allenby, 2016. "Price Promotions in Choice Models," Marketing Science, INFORMS, vol. 35(2), pages 319-334, March.
    5. Chen Lin & Sriram Venkataraman & Sandy D. Jap, 2013. "Media Multiplexing Behavior: Implications for Targeting and Media Planning," Marketing Science, INFORMS, vol. 32(2), pages 310-324, March.
    6. Mohammed, Rezgar & Murova, Olga & Chidmi, Benaissa, 2018. "Examining Demand Elasticities for Differentiated Yogurt," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266417, Southern Agricultural Economics Association.

    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. Pradeep K. Chintagunta & Harikesh S. Nair, 2011. "Structural Workshop Paper --Discrete-Choice Models of Consumer Demand in Marketing," Marketing Science, INFORMS, vol. 30(6), pages 977-996, November.
    2. Richards, Timothy J. & Gómez, Miguel I. & Pofahl, Geoffrey, 2012. "A Multiple-discrete/Continuous Model of Price Promotion," Journal of Retailing, Elsevier, vol. 88(2), pages 206-225.
    3. Nitin Mehta, 2007. "Investigating Consumers' Purchase Incidence and Brand Choice Decisions Across Multiple Product Categories: A Theoretical and Empirical Analysis," Marketing Science, INFORMS, vol. 26(2), pages 196-217, 03-04.
    4. Jie Zhang & Lakshman Krishnamurthi, 2004. "Customizing Promotions in Online Stores," Marketing Science, INFORMS, vol. 23(4), pages 561-578, June.
    5. Jean-Pierre H. Dubé, 2018. "Microeconometric Models of Consumer Demand," NBER Working Papers 25215, National Bureau of Economic Research, Inc.
    6. Harikesh Nair & Jean-Pierre Dubé & Pradeep Chintagunta, 2005. "Accounting for Primary and Secondary Demand Effects with Aggregate Data," Marketing Science, INFORMS, vol. 24(3), pages 444-460, November.
    7. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    8. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
    9. Joonhwi Joo & Ali Hortacsu, 2016. "Semiparametric estimation of CES demand system with observed and unobserved product characteristics," 2016 Meeting Papers 36, Society for Economic Dynamics.
    10. Kazuko Kano, 2018. "Consumer Inventory and Demand for Storable Goods: New Evidence from a Consumer Survey," The Japanese Economic Review, Springer, vol. 69(3), pages 284-305, September.
    11. Ailawadi, Kusum L. & Beauchamp, J.P. & Donthu, Naveen & Gauri, Dinesh K. & Shankar, Venkatesh, 2009. "Communication and Promotion Decisions in Retailing: A Review and Directions for Future Research," Journal of Retailing, Elsevier, vol. 85(1), pages 42-55.
    12. Minjung Kwon & Tülin Erdem & Masakazu Ishihara, 2023. "Counter-cyclical price promotion: Capturing seasonal changes in stockpiling and endogenous consumption," Quantitative Marketing and Economics (QME), Springer, vol. 21(4), pages 437-492, December.
    13. 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.
    14. Bhat, Chandra R. & Srinivasan, Sivaramakrishnan & Sen, Sudeshna, 2006. "A joint model for the perfect and imperfect substitute goods case: Application to activity time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 40(10), pages 827-850, December.
    15. Greg M. Allenby & Thomas S. Shively & Sha Yang & Mark J. Garratt, 2004. "A Choice Model for Packaged Goods: Dealing with Discrete Quantities and Quantity Discounts," Marketing Science, INFORMS, vol. 23(1), pages 95-108, June.
    16. Boztuğ, Yasemin & Bell, David R., 2004. "The Effect of Inventory on Purchase Incidence: Empirical Analysis of Opposing Forces of Storage and Consumption," Papers 2004,43, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    17. Bhat, Chandra R. & Sen, Sudeshna, 2006. "Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 35-53, January.
    18. Liang Guo, 2006. "—Removing the Boundary Between Structural and Reduced-Form Models," Marketing Science, INFORMS, vol. 25(6), pages 629-632, 11-12.
    19. Pradeep Chintagunta & Tülin Erdem & Peter E. Rossi & Michel Wedel, 2006. "Structural Modeling in Marketing: Review and Assessment," Marketing Science, INFORMS, vol. 25(6), pages 604-616, 11-12.
    20. Jack (Xinlei) Chen & Om Narasimhan & George John & Tirtha Dhar, 2010. "An Empirical Investigation of Private Label Supply by National Label Producers," Marketing Science, INFORMS, vol. 29(4), pages 738-755, 07-08.

    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:inm:ormksc:v:29:y:2010:i:3:p:422-437. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.