IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v23y2004i2p263-271.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1030.0024
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.1030.0024?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Nickolay V. Moshkin & Ron Shachar, 2002. "The Asymmetric Information Model of State Dependence," Marketing Science, INFORMS, vol. 21(4), pages 435-454, August.
    3. J. Morgan Jones & Jane T. Landwehr, 1988. "Removing Heterogeneity Bias from Logit Model Estimation," Marketing Science, INFORMS, vol. 7(1), pages 41-59.
    4. 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.
    5. Minakshi Trivedi & Frank M. Bass & Ram C. Rao, 1994. "A Model of Stochastic Variety-Seeking," Marketing Science, INFORMS, vol. 13(3), pages 274-297.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Tülin Erdem, 1996. "A Dynamic Analysis of Market Structure Based on Panel Data," Marketing Science, INFORMS, vol. 15(4), pages 359-378.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. José M. Labeaga & Mercedes Martos-Partal, 2007. "A Proposal to Distinguish State Dependence and Unobserved Heterogeneity in Binary Brand Choice Models," Working Papers 2007-02, FEDEA.
    2. Baltas, George & Doyle, Peter, 2001. "Random utility models in marketing research: a survey," Journal of Business Research, Elsevier, vol. 51(2), pages 115-125, February.
    3. Bronnenberg, Bart & Dube, Jean-Pierre, 2016. "The Formation of Consumer Brand Preferences," CEPR Discussion Papers 11648, C.E.P.R. Discussion Papers.
    4. Sergi Jiménez-Martín & Antonio Ladrón de Guevara-Martínez, 2009. "A state-dependent model of hybrid behavior with rational consumers in the attribute space," Investigaciones Economicas, Fundación SEPI, vol. 33(3), pages 347-383, September.
    5. Bart J. Bronnenberg & Jean-Pierre H. Dubé, 2016. "The Formation of Consumer Brand Preferences," NBER Working Papers 22691, National Bureau of Economic Research, Inc.
    6. Mohamed Lachaab & Asim Ansari & Kamel Jedidi & Abdelwahed Trabelsi, 2006. "Modeling preference evolution in discrete choice models: A Bayesian state-space approach," Quantitative Marketing and Economics (QME), Springer, vol. 4(1), pages 57-81, March.
    7. Dan Horsky & Sanjog Misra & Paul Nelson, 2006. "Observed and Unobserved Preference Heterogeneity in Brand-Choice Models," Marketing Science, INFORMS, vol. 25(4), pages 322-335, 07-08.
    8. Martijn G. de Jong & Donald R. Lehmann & Oded Netzer, 2012. "State-Dependence Effects in Surveys," Marketing Science, INFORMS, vol. 31(5), pages 838-854, September.
    9. Xiao Liu & Timothy Derdenger & Baohong Sun, 2018. "An Empirical Analysis of Consumer Purchase Behavior of Base Products and Add-ons Given Compatibility Constraints," Marketing Science, INFORMS, vol. 37(4), pages 569-591, August.
    10. Jean‐Pierre Dubé & Günter J. Hitsch & Peter E. Rossi, 2010. "State dependence and alternative explanations for consumer inertia," RAND Journal of Economics, RAND Corporation, vol. 41(3), pages 417-445, September.
    11. 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.
    12. González-Benito, Óscar, 2004. "Random effects choice models: seeking latent predisposition segments in the context of retail store format selection," Omega, Elsevier, vol. 32(2), pages 167-177, April.
    13. Joo, Mingyu & Wilbur, Kenneth C. & Zhu, Yi, 2016. "Effects of TV advertising on keyword search," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 508-523.
    14. Morten Overgaard Ravn & Stephanie Schmitt-Grohe & Martin Uribe, 2010. "Incomplete Cost Pass-Through Under Deep Habits," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 13(2), pages 317-332, April.
    15. Nanarpuzha, Rajesh, 2013. "Modeling Situational Factors in Variety Seeking Behaviour: An Extension of the Lightning Bolt Model," IIMA Working Papers WP2013-12-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    16. Victor Aguirregabiria & Jesus Carro, 2021. "Identification of Average Marginal Effects in Fixed Effects Dynamic Discrete Choice Models," Working Papers tecipa-701, University of Toronto, Department of Economics.
    17. Abramson, Charles & Buchmueller, Thomas & Currim, Imran, 1998. "Models of health plan choice," European Journal of Operational Research, Elsevier, vol. 111(2), pages 228-247, December.
    18. Itzhak Gilboa & Amit Pazgal, 1995. "History Dependent Brand Switching: Theory and Evidence," Discussion Papers 1146, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    19. Richard Paap & Philip Hans Franses, 2000. "A dynamic multinomial probit model for brand choice with different long-run and short-run effects of marketing-mix variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 717-744.
    20. Jean-Pierre Dubé, 2004. "Multiple Discreteness and Product Differentiation: Demand for Carbonated Soft Drinks," Marketing Science, INFORMS, vol. 23(1), pages 66-81, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:23:y:2004:i:2:p:263-271. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.