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Modeling Multiple Sources of State Dependence in Random Utility Models: A Distributed Lag Approach

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  • P. B. Seetharaman

    (John M. Olin School of Business, Washington University, Campus Box 1133, One Brookings Drive, St. Louis, Missouri 63130-4899)

Abstract

We propose a utility-theoretic brand-choice model that accounts for four different sources of state dependence: 1. effects of lagged choices (), 2. effects of serially correlated error terms in the random utility function (), 3. effects of serial correlations between utility-maximizing alternatives on successive purchase occasions of a household (), and 4. effects of lagged marketing variables (). Our proposed model also allows habit persistence to be a function of lagged marketing variables, while accommodating the effects of unobserved heterogeneity in household choice parameters. This model is more flexible than existing state-dependence models in marketing and labor econometrics. Using scanner panel data, we find structural state dependence to be the most important source of state dependence. Marketing-mix elasticities are systematically understated if state-dependence effects are incompletely accounted for. The Seetharaman and Chintagunta (1998) model is shown to recover spurious variety-seeking effects while overstating habit-persistence effects. Ignoring habit persistence type 1 leads to an underestimation, while ignoring habit persistence type 2 leads to an overestimation of structural state-dependence effects. We find lagged promotions to have carryover effects on habit persistence. Ignoring one or more sources of state dependence underestimates the total incremental impact of a sales promotion. We draw implications for manufacturer pricing.

Suggested Citation

  • P. B. Seetharaman, 2004. "Modeling Multiple Sources of State Dependence in Random Utility Models: A Distributed Lag Approach," Marketing Science, INFORMS, vol. 23(2), pages 263-271, April.
  • Handle: RePEc:inm:ormksc:v:23:y:2004:i:2:p:263-271
    DOI: 10.1287/mksc.1030.0024
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    References listed on IDEAS

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    1. Rishin Roy & Pradeep K. Chintagunta & Sudeep Haldar, 1996. "A Framework for Investigating Habits, “The Hand of the Past,” and Heterogeneity in Dynamic Brand Choice," Marketing Science, INFORMS, vol. 15(3), pages 280-299.
    2. 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.
    3. Abel P. Jeuland, 1979. "Brand Choice Inertia as One Aspect of the Notion of Brand Loyalty," Management Science, INFORMS, vol. 25(7), pages 671-682, July.
    4. 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.
    5. Nickolay V. Moshkin & Ron Shachar, 2002. "The Asymmetric Information Model of State Dependence," Marketing Science, INFORMS, vol. 21(4), pages 435-454, August.
    6. J. Morgan Jones & Jane T. Landwehr, 1988. "Removing Heterogeneity Bias from Logit Model Estimation," Marketing Science, INFORMS, vol. 7(1), pages 41-59.
    7. Minakshi Trivedi & Frank M. Bass & Ram C. Rao, 1994. "A Model of Stochastic Variety-Seeking," Marketing Science, INFORMS, vol. 13(3), pages 274-297.
    8. Tülin Erdem, 1996. "A Dynamic Analysis of Market Structure Based on Panel Data," Marketing Science, INFORMS, vol. 15(4), pages 359-378.
    9. Erdem, Tulin & Sun, Baohong, 2001. "Testing for Choice Dynamics in Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 142-152, April.
    10. Praveen K. Kopalle & Carl F. Mela & Lawrence Marsh, 1999. "The Dynamic Effect of Discounting on Sales: Empirical Analysis and Normative Pricing Implications," Marketing Science, INFORMS, vol. 18(3), pages 317-332.
    11. Flaig, Gebhard & Licht, Georg & Steiner, Viktor, 1993. "Testing for state dependence effects in a dynamic model of male unemployment behaviour," ZEW Discussion Papers 93-07, ZEW - Leibniz Centre for European Economic Research.
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