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Endogeneity in Brand Choice Models

Author

Listed:
  • J. Miguel Villas-Boas

    (Haas School of Business, University of California at Berkeley, Berkeley, California 94720)

  • Russell S. Winer

    (Haas School of Business, University of California at Berkeley, Berkeley, California 94720)

Abstract

Applications of random utility models to scanner data have been widely presented in marketing for the last 20 years. One particular problem with these applications is that they have ignored possible correlations between the independent variables in the deterministic component of utility (price, promotion, etc.) and the stochastic component or error term. In fact, marketing-mix variables, such as price, not only affect brand purchasing probabilities but are themselves endogenously set by marketing managers. This work tests whether these endogeneity problems are important enough to warrant consideration when estimating random utility models with scanner panel data. Our results show that not accounting for endogeneity may result in a substantial bias in the parameter estimates.

Suggested Citation

  • J. Miguel Villas-Boas & Russell S. Winer, 1999. "Endogeneity in Brand Choice Models," Management Science, INFORMS, vol. 45(10), pages 1324-1338, October.
  • Handle: RePEc:inm:ormnsc:v:45:y:1999:i:10:p:1324-1338
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    File URL: http://dx.doi.org/10.1287/mnsc.45.10.1324
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    References listed on IDEAS

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    1. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
    2. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    3. Milgrom, Paul & Roberts, John, 1986. "Price and Advertising Signals of Product Quality," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 796-821, August.
    4. 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.
    5. Chintagunta, Pradeep K & Jain, Dipak C, 1995. "Empirical Analysis of a Dynamic Duopoly Model of Competition," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 4(1), pages 109-131, Spring.
    6. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
    7. Gourieroux, Christian & Monfort, Alain, 1993. "Simulation-based inference : A survey with special reference to panel data models," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 5-33, September.
    8. Peter M. Guadagni & John D. C. Little, 1983. "A Logit Model of Brand Choice Calibrated on Scanner Data," Marketing Science, INFORMS, vol. 2(3), pages 203-238.
    9. 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.
    10. Gerard J. Tellis & Fred S. Zufryden, 1995. "Tackling the Retailer Decision Maze: Which Brands to Discount, How Much, When and Why?," Marketing Science, INFORMS, vol. 14(3), pages 271-299.
    11. Füsun Gönül & Kannan Srinivasan, 1993. "Modeling Multiple Sources of Heterogeneity in Multinomial Logit Models: Methodological and Managerial Issues," Marketing Science, INFORMS, vol. 12(3), pages 213-229.
    12. Peter S. Fader & James M. Lattin & John D. C. Little, 1992. "Estimating Nonlinear Parameters in the Multinomial Logit Model," Marketing Science, INFORMS, vol. 11(4), pages 372-385.
    13. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    14. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    15. Winer, Russell S, 1986. " A Reference Price Model of Brand Choice for Frequently Purchased Products," Journal of Consumer Research, Oxford University Press, vol. 13(2), pages 250-256, September.
    16. Pradeep K. Chintagunta, 1993. "Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households," Marketing Science, INFORMS, vol. 12(2), pages 184-208.
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