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Taste Heterogeneity, IIA, and the Similarity Critique

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Author Info

  • Thomas J. Steenburgh

    () (Harvard Business School, Marketing Unit)

  • Andrew Ainslie

    () (UCLA Anderson, School of Management)

Abstract

The purpose of this paper is to show that allowing for taste heterogeneity does not address the similarity critique of discrete-choice models. Although IIA may technically be broken in aggregate, the mixed logit model allows neither a given individual nor the population as a whole to behave with perfect substitution when facing perfect substitutes. Thus, the mixed logit model implies that individuals behave inconsistently across choice sets. Estimating the mixed logit on data in which individuals do behave consistently can result in biased parameter estimates, with the individuals' tastes for desirable attributes being systemically undervalued.

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Bibliographic Info

Paper provided by Harvard Business School in its series Harvard Business School Working Papers with number 09-049.

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Length: 26 pages
Date of creation: Sep 2008
Date of revision:
Handle: RePEc:hbs:wpaper:09-049

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Related research

Keywords: Heterogeneity; Mixed Logit; Independence from Irrelevant Alternatives; IIA; Similarity Critique; Ecological Fallacy;

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  1. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
  2. Tülin Erdem & Michael Keane & Baohong Sun, 2008. "The impact of advertising on consumer price sensitivity in experience goods markets," Quantitative Marketing and Economics, Springer, vol. 6(2), pages 139-176, June.
  3. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
  4. Thomas J. Steenburgh, 2008. "The Invariant Proportion of Substitution Property (IPS) of Discrete-Choice Models," Marketing Science, INFORMS, vol. 27(2), pages 300-307, 03-04.
  5. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
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