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The price consideration model of brand choice

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  • Andrew Ching
  • Tülin Erdem
  • Michael Keane

Abstract

The workhorse brand choice models in marketing are the multinomial logit (MNL) and nested multinomial logit (NMNL). These models place strong restrictions on how brand share and purchase incidence price elasticities are related. In this paper, we propose a new model of brand choice, the “price consideration” (PC) model, that allows more flexibility in this relationship. In the PC model, consumers do not observe prices in each period. Every week, a consumer decides whether to consider a category. Only then does he/she look at prices and decide whether and what to buy. Using scanner data, we show the PC model fits much better than MNL or NMNL. Simulations reveal the reason: the PC model provides a vastly superior fit to inter-purchase spells.
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Suggested Citation

  • Andrew Ching & Tülin Erdem & Michael Keane, 2009. "The price consideration model of brand choice," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(3), pages 393-420, April.
    • Handle: RePEc:jae:japmet:v:24:y:2009:i:3:p:393-420
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Elisabeth Honka, 2014. "Quantifying search and switching costs in the US auto insurance industry," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 847-884, December.
    2. Michael D. Grubb & Matthew Osborne, 2015. "Cellular Service Demand: Biased Beliefs, Learning, and Bill Shock," American Economic Review, American Economic Association, vol. 105(1), pages 234-271, January.
    3. Février, Philippe & Wilner, Lionel, 2016. "Do consumers correctly expect price reductions? Testing dynamic behavior," International Journal of Industrial Organization, Elsevier, vol. 44(C), pages 25-40.
    4. Stephan Seiler, 2010. "The impact of search costs on consumer behavior: a dynamic approach," 2010 Meeting Papers 559, Society for Economic Dynamics.
    5. Ching, Andrew T. & Erdem, Tülin & Keane, Michael P., 2014. "A simple method to estimate the roles of learning, inventories and category consideration in consumer choice," Journal of choice modelling, Elsevier, vol. 13(C), pages 60-72.
    6. Christopher Jeffords, 2014. "Preference-directed regulation when ethical environmental policy choices are formed with limited information," Empirical Economics, Springer, vol. 46(2), pages 573-606, March.
    7. Karthik Sridhar & Ram Bezawada & Minakshi Trivedi, 2012. "Investigating the Drivers of Consumer Cross-Category Learning for New Products Using Multiple Data Sets," Marketing Science, INFORMS, vol. 31(4), pages 668-688, July.
    8. Carson, Richard T. & Louviere, Jordan J., 2014. "Statistical properties of consideration sets," Journal of choice modelling, Elsevier, vol. 13(C), pages 37-48.
    9. Wiktor Adamowicz & David Bunch & Trudy Cameron & Benedict Dellaert & Michael Hanneman & Michael Keane & Jordan Louviere & Robert Meyer & Thomas Steenburgh & Joffre Swait, 2008. "Behavioral frontiers in choice modeling," Marketing Letters, Springer, vol. 19(3), pages 215-228, December.
    10. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    11. Talia Bar & Yuqing Zheng, 2016. "Leniency and Loyalty in the Choice of Certifiers: Evidence from the BRC Food Safety Standard," Working papers 2016-22, University of Connecticut, Department of Economics.
    12. repec:eee:hapoch:v1_661 is not listed on IDEAS
    13. Yan Liu & Subramanian Balachander, 2014. "How long has it been since the last deal? Consumer promotion timing expectations and promotional response," Quantitative Marketing and Economics (QME), Springer, vol. 12(1), pages 85-126, March.
    14. Michael P. Keane, 2013. "Panel data discrete choice models of consumer demand," Economics Papers 2013-W08, Economics Group, Nuffield College, University of Oxford.
    15. Ching, Andrew T. & Hayashi, Fumiko, 2010. "Payment card rewards programs and consumer payment choice," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1773-1787, August.
    16. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2016. "Empirical Models of Learning Dynamics: A Survey of Recent Developments," Economics Papers 2016-W12, Economics Group, Nuffield College, University of Oxford.
    17. Stephan Seiler, 2013. "The impact of search costs on consumer behavior: A dynamic approach," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 155-203, June.
    18. Michael P. Keane, 2010. "A Structural Perspective on the Experimentalist School," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 47-58, Spring.

    More about this item

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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