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State Dependence and Alternative Explanations for Consumer Inertia

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  • Jean-Pierre Dubé
  • Günter J. Hitsch
  • Peter E. Rossi

Abstract

For many consumer packaged goods products, researchers have documented a form of state dependence whereby consumers become "loyal" to products they have consumed in the past. That is, consumers behave as though there is a utility premium from continuing to purchase the same product as they have purchased in the past or, equivalently, there is a psychological cost to switching products. However, it has not been established that this form of state dependence can be identified in the presence of consumer heterogeneity of an unknown form. Most importantly, before this inertia can be given a structural interpretation and used in policy experiments such as counterfactual pricing exercises,alternative explanations which might give rise to similar consumer behavior must be ruled out. We develop a flexible model of heterogeneity which can be given a semi-parametric interpretation and rule out alternative explanations for positive state dependence such as autocorrelated choice errors, consumer search, or consumer learning.

Suggested Citation

  • Jean-Pierre Dubé & Günter J. Hitsch & Peter E. Rossi, 2009. "State Dependence and Alternative Explanations for Consumer Inertia," NBER Working Papers 14912, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:14912
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    References listed on IDEAS

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    1. Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649, Elsevier.
    2. Igal Hendel & Aviv Nevo, 2006. "Sales and consumer inventory," RAND Journal of Economics, RAND Corporation, vol. 37(3), pages 543-561, September.
    3. Paul Klemperer, 1995. "Competition when Consumers have Switching Costs: An Overview with Applications to Industrial Organization, Macroeconomics, and International Trade," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 62(4), pages 515-539.
    4. Keane, Michael P, 1997. "Modeling Heterogeneity and State Dependence in Consumer Choice Behavior," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 310-327, July.
    5. Farrell, Joseph & Klemperer, Paul, 2007. "Coordination and Lock-In: Competition with Switching Costs and Network Effects," Handbook of Industrial Organization, Elsevier.
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    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L0 - Industrial Organization - - General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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