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A Simple Method to Estimate the Roles of Learning, Inventories and Category Consideration in Consumer Choice

Listed author(s):
  • Andrew T. Ching

    ()

    (Rotman School of Management, University of Toronto, Canada)

  • Tülin Erdem

    ()

    (Stern School of Business, New York University, USA)

  • Michael P. Keane

    ()

    (Nuffield College, University of Oxford)

Models of consumer learning and inventory behavior have both proven to be valuable for explaining consumer choice dynamics. In their pure form these models assume consumers solve complex dynamic programming (DP) problems to determine optimal choices. For this reason, these models are best viewed as “as if” approximations to consumer behavior. In this paper we present an estimation method, based on Geweke and Keane (2000), which allows us to estimate dynamic models without solving a DP problem and without strong assumptions about how consumers form expectations about the future. The relatively low computational burden of this method allows us to nest the learning and inventory models. We also incorporate the “price consideration” mechanism of Ching, Erdem and Keane (2009), which essentially says that consumers may not pay attention to a category in every period. The resulting model may be viewed as providing a more “realistic” or “descriptive” account of consumer choice behavior.

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File URL: http://www.nuffield.ox.ac.uk/economics/papers/2014/learn_inventory_JOCM_1.pdf
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Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2014-W01.

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Length: 25 pages
Date of creation: 07 Jul 2014
Handle: RePEc:nuf:econwp:1401
Contact details of provider: Web page: https://www.nuffield.ox.ac.uk/economics/

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  1. Igal Hendel & Aviv Nevo, 2006. "Measuring the Implications of Sales and Consumer Inventory Behavior," Econometrica, Econometric Society, vol. 74(6), pages 1637-1673, November.
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  3. Daniel Houser & Michael Keane & Kevin McCabe, 2004. "Behavior in a Dynamic Decision Problem: An Analysis of Experimental Evidence Using a Bayesian Type Classification Algorithm," Econometrica, Econometric Society, vol. 72(3), pages 781-822, May.
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  8. 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, 04.
  9. Houser, Daniel, 2003. "Bayesian analysis of a dynamic stochastic model of labor supply and saving," Journal of Econometrics, Elsevier, vol. 113(2), pages 289-335, April.
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  11. Keane, Michael, 1993. "Simulation estimation for panel data models with limited dependent variables," MPRA Paper 53029, University Library of Munich, Germany.
  12. 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.
  13. Tülin Erdem & Michael P. Keane & Baohong Sun, 2008. "A Dynamic Model of Brand Choice When Price and Advertising Signal Product Quality," Marketing Science, INFORMS, vol. 27(6), pages 1111-1125, 11-12.
  14. Andrew Ching & Masakazu Ishihara, 2010. "The effects of detailing on prescribing decisions under quality uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 8(2), pages 123-165, June.
  15. Andrew T. Ching, 2010. "A Dynamic Oligopoly Structural Model For The Prescription Drug Market After Patent Expiration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 51(4), pages 1175-1207, November.
  16. Geweke, John & Keane, Michael, 2001. "Computationally intensive methods for integration in econometrics," Handbook of Econometrics,in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 56, pages 3463-3568 Elsevier.
  17. 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.
  18. Gregory S. Crawford & Matthew Shum, 2005. "Uncertainty and Learning in Pharmaceutical Demand," Econometrica, Econometric Society, vol. 73(4), pages 1137-1173, July.
  19. Daniel A. Ackerberg, 2003. "Advertising, learning, and consumer choice in experience good markets: an empirical examination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(3), pages 1007-1040, August.
  20. Alison Jing Xu & Robert S. Wyer Jr., 2007. "The Effect of Mind-Sets on Consumer Decision Strategies," Journal of Consumer Research, Oxford University Press, vol. 34(4), pages 556-566, June.
  21. 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.
  22. Houser, Daniel & Bechara, Antoine & Keane, Michael & McCabe, Kevin & Smith, Vernon, 2005. "Identifying individual differences: An algorithm with application to Phineas Gage," Games and Economic Behavior, Elsevier, vol. 52(2), pages 373-385, August.
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