IDEAS home Printed from https://ideas.repec.org/a/bes/jnlbes/v9y1991i1p1-14.html
   My bibliography  Save this article

There Is No Aggregate Bias: Why Macro Logit Models Work

Author

Listed:
  • Allenby, Greg M
  • Rossi, Peter E

Abstract

In this article, we examine the aggregation properties of (nested) logit models to understand their exceptional macro-level performance. The problem of aggregating micro logit models involves integrating nonlinear functions of model parameters over a distribution of consumer heterogeneity. The aggregation problem is analyzed using a mixture of analytic and simulation techniques, with the simulation experiments using actual panel data to calibrate the distribution of heterogeneity. We conclude that the practice of fitting aggregate logit models is theoretically justified under the following three conditions: (1) All consumers are exposed to the same marketing-mix variables, (2) the brands are close substitutes, and (3) the distribution of prices is not concentrated at an extreme value. These conditions are frequently met in store-level scanner data.

Suggested Citation

  • Allenby, Greg M & Rossi, Peter E, 1991. "There Is No Aggregate Bias: Why Macro Logit Models Work," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 1-14, January.
  • Handle: RePEc:bes:jnlbes:v:9:y:1991:i:1:p:1-14
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cohen, Michael, 2010. "A Structured Covariance Probit Demand Model," Research Reports 149970, University of Connecticut, Food Marketing Policy Center.
    2. G. Dekimpe, Marnik & Hanssens, Dominique M. & Silva-Risso, Jorge M., 1998. "Long-run effects of price promotions in scanner markets," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 269-291, November.
    3. Goddard, Ellen W. & Shank, Benjamin & Panter, Chris & Nilsson, Tomas K.H. & Cash, Sean B., 2007. "Canadian Chicken Industry: Consumer Preferences, Industry Structure and Producer Benefits from Investment in Research and Advertising," Project Report Series 52088, University of Alberta, Department of Resource Economics and Environmental Sociology.
    4. Harald J. van Heerde & Peter S. H. Leeflang & Dick R. Wittink, 2004. "Decomposing the Sales Promotion Bump with Store Data," Marketing Science, INFORMS, vol. 23(3), pages 317-334, December.
    5. Srinivasan, S. & Pauwels, K.H. & Hanssens, D.M. & Dekimpe, M.G., 2002. "Do Promotions Benefit Manufacturers, Retailers or Both?," ERIM Report Series Research in Management ERS-2002-21-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Martinez Granado, Maite & Siotis, Georges, 2006. "Computing Abuse Related Damages in the Case of New Entry: An Illustration for the Directory Enquiry Services Market," CEPR Discussion Papers 5813, C.E.P.R. Discussion Papers.
    7. Vibhanshu Abhishek & Kartik Hosanagar & Peter S. Fader, 2015. "Aggregation Bias in Sponsored Search Data: The Curse and the Cure," Marketing Science, INFORMS, vol. 34(1), pages 59-77, January.
    8. Siotis Georges & Martínez-Granado Maite, 2010. "Sabotaging Entry: An Estimation of Damages in the Directory Enquiry Service Market," Review of Law & Economics, De Gruyter, vol. 6(1), pages 1-57, April.
    9. David Besanko & Sachin Gupta & Dipak Jain, 1998. "Logit Demand Estimation Under Competitive Pricing Behavior: An Equilibrium Framework," Management Science, INFORMS, vol. 44(11-Part-1), pages 1533-1547, November.
    10. Koen Pauwels & Shuba Srinivasan, 2004. "Who Benefits from Store Brand Entry?," Marketing Science, INFORMS, vol. 23(3), pages 364-390, July.
    11. Vidal-Sanz, Jose M. & Esteban-Bravo, Mercedes, 2013. "A nonlinear product differentiation model à la Cournot: a new look to the newspapers industry," DEE - Working Papers. Business Economics. WB wb132002, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    12. Linda V. Green & Sergei Savin & Nicos Savva, 2013. "“Nursevendor Problem”: Personnel Staffing in the Presence of Endogenous Absenteeism," Management Science, INFORMS, vol. 59(10), pages 2237-2256, October.
    13. repec:eee:jouret:v:93:y:2017:i:3:p:283-303 is not listed on IDEAS

    More about this item

    Statistics

    Access and download statistics

    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:bes:jnlbes:v:9:y:1991:i:1:p:1-14. 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: (Christopher F. Baum). General contact details of provider: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.