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There Is No Aggregate Bias: Why Macro Logit Models Work

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  • 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
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    Cited by:

    1. Steven Tenn, 2006. "Avoiding aggregation bias in demand estimation: A multivariate promotional disaggregation approach," Quantitative Marketing and Economics (QME), Springer, vol. 4(4), pages 383-405, December.
    2. Peter Boatwright & Sanjay Dhar & Peter Rossi, 2004. "The Role of Retail Competition, Demographics and Account Retail Strategy as Drivers of Promotional Sensitivity," Quantitative Marketing and Economics (QME), Springer, vol. 2(2), pages 169-190, June.
    3. Cohen, Michael, 2010. "A Structured Covariance Probit Demand Model," Research Reports 149970, University of Connecticut, Food Marketing Policy Center.
    4. 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.
    5. 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.
    6. Birolini, Sebastian & Cattaneo, Mattia & Malighetti, Paolo & Morlotti, Chiara, 2020. "Integrated origin-based demand modeling for air transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    7. Koen Pauwels & Imran Currim & Marnik Dekimpe & Dominique Hanssens & Natalie Mizik & Eric Ghysels & Prasad Naik, 2004. "Modeling Marketing Dynamics by Time Series Econometrics," Marketing Letters, Springer, vol. 15(4), pages 167-183, December.
    8. Siotis, Georges & Martinez Granado, Maite, 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.
    9. Koen Pauwels & Shuba Srinivasan, 2004. "Who Benefits from Store Brand Entry?," Marketing Science, INFORMS, vol. 23(3), pages 364-390, July.
    10. 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.
    11. Zizhuo Wang & Chaolin Yang & Hongsong Yuan & Yaowu Zhang, 2021. "Aggregation Bias in Estimating Log‐Log Demand Function," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 3906-3922, November.
    12. Avogadro, Nicolò & Pels, Eric & Redondi, Renato, 2023. "Policy impacts on the propensity to travel by HSR in the Amsterdam – London market," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    13. 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.
    14. K. Sudhir, 2001. "Structural Analysis of Manufacturer Pricing in the Presence of a Strategic Retailer," Marketing Science, INFORMS, vol. 20(3), pages 244-264, October.
    15. 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.
    16. 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.
    17. 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.
    18. Little, John D. C., 1998. "Integrated measures of sales, merchandising, and distribution," Working papers WP 3997-98., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    19. 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.
    20. Mingyu Joo & Michael L. Thompson & Greg M. Allenby6, 2019. "Optimal Product Design by Sequential Experiments in High Dimensions," Management Science, INFORMS, vol. 65(7), pages 3235-3254, July.
    21. Vidal-Sanz, Jose M., 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.
    22. Gauri, Dinesh K. & Ratchford, Brian & Pancras, Joseph & Talukdar, Debabrata, 2017. "An Empirical Analysis of the Impact of Promotional Discounts on Store Performance," Journal of Retailing, Elsevier, vol. 93(3), pages 283-303.
    23. Barreiro, Jose Manuel & Ruzo, Emilio & Losada, Fernando, 2004. "Modelo logit multinomial y regresion con variables ficticias: una aplicacion regional al sector lacteo," Economic Development 81, University of Santiago de Compostela. Faculty of Economics and Business. Econometrics..

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