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Beyond the Endogeneity Bias: The Effect of Unmeasured Brand Characteristics on Household-Level Brand Choice Models

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  • Pradeep Chintagunta

    () (Graduate School of Business, University of Chicago, 5807 South Woodlawn Avenue, Chicago, Illinois 60637)

  • Jean-Pierre Dubé

    () (Graduate School of Business, University of Chicago, 5807 South Woodlawn Avenue, Chicago, Illinois 60637)

  • Khim Yong Goh

    () (Graduate School of Business, University of Chicago, 5807 South Woodlawn Avenue, Chicago, Illinois 60637)

Abstract

We investigate the role of potential weekly brand-specific characteristics that influence consumer choices, but are unobserved or unmeasurable by the researcher. We use an empirical approach, based on the estimation methods used for standard random coefficients logit models, to account for the presence of such unobserved attributes. Using household scanner panel data, we find evidence that ignoring such time-varying latent (to the researcher) characteristics can lead to two types of problems. First, consistent with previous literature, we find that these unobserved characteristics may lead to biased estimates of the mean price response parameters. This argument is based on a form of price endogeneity. If marketing managers set prices based on consumer willingness to pay, then the observed prices will likely be correlated with the latent (to the researcher) brand characteristics. We resolve this problem by using an instrumental variables procedure. Our findings suggest that simply ignoring these attributes may also lead to larger estimates of the variance in the heterogeneity distribution of preferences and price sensitivities across households. This could overstate the benefits from marketing activities such as household-level targeting. We resolve the problem by using weekly brand intercepts, embedded in a random coefficients brand choice model, to control for weekly brand-specific characteristics, while accounting for household heterogeneity. Overall, our results extend the finding on the endogeneity bias from the mean of the heterogeneity distribution (i.e., the price effect) to include the variance of that distribution.

Suggested Citation

  • Pradeep Chintagunta & Jean-Pierre Dubé & Khim Yong Goh, 2005. "Beyond the Endogeneity Bias: The Effect of Unmeasured Brand Characteristics on Household-Level Brand Choice Models," Management Science, INFORMS, vol. 51(5), pages 832-849, May.
  • Handle: RePEc:inm:ormnsc:v:51:y:2005:i:5:p:832-849
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    File URL: http://dx.doi.org/10.1287/mnsc.1040.0323
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    References listed on IDEAS

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    13. Hruschka, Harald, 2010. "Considering endogeneity for optimal catalog allocation in direct marketing," European Journal of Operational Research, Elsevier, vol. 206(1), pages 239-247, October.
    14. Harikesh Nair, 2007. "Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games," Quantitative Marketing and Economics (QME), Springer, vol. 5(3), pages 239-292, September.
    15. Hovhannisyan, Vardges & Stiegert, Kyle & Bozic, Marin, 2014. "On the Endogeneity of Retail Markups in an Equilibrium Analysis: A Control-Function Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(2), August.
    16. Jean-Pierre Dubé & Günter Hitsch & Puneet Manchanda, 2005. "An Empirical Model of Advertising Dynamics," Quantitative Marketing and Economics (QME), Springer, vol. 3(2), pages 107-144, June.
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    18. Junhong Chu & Pradeep Chintagunta & Javier Cebollada, 2008. "Research Note—A Comparison of Within-Household Price Sensitivity Across Online and Offline Channels," Marketing Science, INFORMS, vol. 27(2), pages 283-299, 03-04.
    19. Eric Bradlow & Bart Bronnenberg & Gary Russell & Neeraj Arora & David Bell & Sri Duvvuri & Frankel Hofstede & Catarina Sismeiro & Raphael Thomadsen & Sha Yang, 2005. "Spatial Models in Marketing," Marketing Letters, Springer, vol. 16(3), pages 267-278, December.
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    24. Stefan Stremersch & Vardit Landsman & Sriram Venkataraman, 2013. "The Relationship Between DTCA, Drug Requests, and Prescriptions: Uncovering Variation in Specialty and Space," Marketing Science, INFORMS, vol. 32(1), pages 89-110, June.

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