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Brand and Quantity Choice Dynamics Under Price Uncertainty

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  • Tülin Erdem
  • Susumu Imai
  • Michael Keane

Abstract

We develop a model of household demand for frequently purchased consumer goods that are branded, storable and subject to stochastic price fluctuations. Our framework accounts for how inventories and expectations of future prices affect current period purchase decisions. We estimate our model using scanner data for the ketchup category. Our results indicate that price expectations and the nature of the price process have important effects on demand elasticities. Long-run cross price elasticities of demand are more than twice as great as short-run cross price elasticities. Temporary price cuts (or “deals”) primarily generate purchase acceleration and category expansion, rather than brand switching. Copyright Kluwer Academic Publishers 2003

Suggested Citation

  • Tülin Erdem & Susumu Imai & Michael Keane, 2003. "Brand and Quantity Choice Dynamics Under Price Uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 5-64, March.
  • Handle: RePEc:kap:qmktec:v:1:y:2003:i:1:p:5-64
    DOI: 10.1023/A:1023536326497
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    1. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    2. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
    3. Hanemann, W Michael, 1984. "Discrete-Continuous Models of Consumer Demand," Econometrica, Econometric Society, vol. 52(3), pages 541-561, May.
    4. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    5. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
    6. Hong, Pilky & McAfee, R. Preston & Nayyar, Ashish, 2002. "Equilibrium Price Dispersion with Consumer Inventories," Journal of Economic Theory, Elsevier, vol. 105(2), pages 503-517, August.
    7. Michael P. Keane & Kenneth I. Wolpin, 2002. "Estimating Welfare Effects Consistent with Forward-Looking Behavior. Part I: Lessons from a Simulation Exercise," Journal of Human Resources, University of Wisconsin Press, vol. 37(3), pages 570-599.
    8. Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-342, March.
    9. 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.
    10. Ching, Andrew T., 2010. "Consumer learning and heterogeneity: Dynamics of demand for prescription drugs after patent expiration," International Journal of Industrial Organization, Elsevier, vol. 28(6), pages 619-638, November.
    11. Martin Pesendorfer, 2002. "Retail Sales: A Study of Pricing Behavior in Supermarkets," The Journal of Business, University of Chicago Press, vol. 75(1), pages 33-66, January.
    12. Zvi Eckstein & Kenneth I. Wolpin, 1989. "The Specification and Estimation of Dynamic Stochastic Discrete Choice Models: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 24(4), pages 562-598.
    13. Scott A. Neslin & Caroline Henderson & John Quelch, 1985. "Consumer Promotions and the Acceleration of Product Purchases," Marketing Science, INFORMS, vol. 4(2), pages 147-165.
    14. Terry Elrod, 1988. "Choice Map: Inferring a Product-Market Map from Panel Data," Marketing Science, INFORMS, vol. 7(1), pages 21-40.
    15. Tülin Erdem, 1996. "A Dynamic Analysis of Market Structure Based on Panel Data," Marketing Science, INFORMS, vol. 15(4), pages 359-378.
    16. Rajiv Lal, 1990. "Price Promotions: Limiting Competitive Encroachment," Marketing Science, INFORMS, vol. 9(3), pages 247-262.
    17. Jeongwen Chiang, 1991. "A Simultaneous Approach to the Whether, What and How Much to Buy Questions," Marketing Science, INFORMS, vol. 10(4), pages 297-315.
    18. Erdem, Tulin & Keane, Michael P. & Sun, Baohong, 1998. "Missing price and coupon availability data in scanner panels: Correcting for the self-selection bias in choice model parameters," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 177-196, November.
    19. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    20. Srinivasan, T C & Winer, Russell S, 1994. "Using Neoclassical Consumer-Choice Theory to Produce a Market Map from Purchase Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(1), pages 1-9, January.
    21. Elrod, Terry & Keane, Michael, 1995. "A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data," MPRA Paper 52434, University Library of Munich, Germany.
    22. Rudolph W. Struse, III, 1987. "Commentary—Approaches to Promotion Evaluation: A Practitioner's Viewpoint," Marketing Science, INFORMS, vol. 6(2), pages 150-151.
    23. 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.
    24. Winer, Russell S, 1986. "A Reference Price Model of Brand Choice for Frequently Purchased Products," Journal of Consumer Research, Oxford University Press, vol. 13(2), pages 250-256, September.
    25. Rajiv Lal & Ram Rao, 1997. "Supermarket Competition: The Case of Every Day Low Pricing," Marketing Science, INFORMS, vol. 16(1), pages 60-80.
    26. Lucas, Robert E, Jr & Rapping, Leonard A, 1969. "Real Wages, Employment, and Inflation," Journal of Political Economy, University of Chicago Press, vol. 77(5), pages 721-754, Sept./Oct.
    27. Füsun Gönül & Kannan Srinivasan, 1996. "Estimating the Impact of Consumer Expectations of Coupons on Purchase Behavior: A Dynamic Structural Model," Marketing Science, INFORMS, vol. 15(3), pages 262-279.
    28. Pradeep K. Chintagunta, 1993. "Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households," Marketing Science, INFORMS, vol. 12(2), pages 184-208.
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    More about this item

    Keywords

    price expectations; pricing; scanner data; dynamic programming; simulation; discrete choice; stock piling; inventories;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D1 - Microeconomics - - Household Behavior
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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