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A dynamic multinomial probit model for brand choice with different long-run and short-run effects of marketing-mix variables

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Author Info
Richard Paap (Rotterdam Institute for Business Economic Studies, Erasmus University Rotterdam, PO Box 1738, NL-3000, DR Rotterdam, The Netherlands)
Philip Hans Franses (Econometric Institute and Department of Marketing and Organization, Erasmus University Rotterdam, The Netherlands)

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Abstract

In this paper we propose a dynamic multinomial probit model in order to estimate the long-run and short- run effects of marketing mix variables on brand choice. The latent variables, which contain the unobserved perceived utilities, follow a first-order vector error correction autoregressive process of order 1 with current and lagged explanatory variables. The unrestricted autoregressive parameter matrix concerns the intertemporal correlation in perceived utilities of households over purchase occasions and indicates the persistence in brand choice. As explanatory variables we consider relative prices and promotional activities like feature and display. An important and novel feature of our model is that it allows for different long-run and short-run effects of promotional activities, thereby extending the models that are currently available in the literature. Additionally, to account for different base preferences for brands across households, we allow for consumer heterogeneity. Our application concerns a panel of households choosing among several brands of a FMCG. Our estimated model turns out to be an improvement over a static model and over a model with only short-run effects, in terms of in-sample fit and out-of-sample forecasts. Copyright © 2000 John Wiley & Sons, Ltd.

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File URL: http://qed.econ.queensu.ca:80/jae/2000-v15.6/
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 15 (2000)
Issue (Month): 6 ()
Pages: 717-744
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Handle: RePEc:jae:japmet:v:15:y:2000:i:6:p:717-744

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Hendry, David F. & Pagan, Adrian R. & Sargan, J.Denis, 1984. "Dynamic specification," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 18, pages 1023-1100 Elsevier. [Downloadable!] (restricted)
  2. John Geweke, 1998. "Using simulation methods for Bayesian econometric models: inference, development, and communication," Staff Report 249, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  3. Geweke, John, 1996. "Bayesian reduced rank regression in econometrics," Journal of Econometrics, Elsevier, vol. 75(1), pages 121-146, November. [Downloadable!] (restricted)
  4. Geweke, John F. & Keane, Michael P. & Runkle, David E., 1997. "Statistical inference in the multinomial multiperiod probit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 125-165, September. [Downloadable!] (restricted)
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  5. 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 310-27, July.
  6. Jain, Dipak C & Vilcassim, Naufel J & Chintagunta, Pradeep K, 1994. "A Random-Coefficients Logit Brand-Choice Model Applied to Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 317-28, July.
  7. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240. [Downloadable!] (restricted)
  8. Allenby, Greg M. & Rossi, Peter E., 1998. "Marketing models of consumer heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 57-78, November. [Downloadable!] (restricted)
  9. Hausman, Jerry A & Wise, David A, 1978. "A Conditional Probit Model for Qualitative Choice: Discrete Decisions Recognizing Interdependence and Heterogeneous Preferences," Econometrica, Econometric Society, vol. 46(2), pages 403-26, March. [Downloadable!] (restricted)
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  10. Borsch-Supan, Axel & Hajivassiliou, Vassilis A., 1993. "Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models," Journal of Econometrics, Elsevier, vol. 58(3), pages 347-368, August. [Downloadable!] (restricted)
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  1. Fok, D. & Paap, R. & Horváth, C. & Franses, Ph.H.B.F., 2005. "A Hierarchical Bayes Error Correction Model to Explain Dynamic Effects of Price Changes," Research Paper ERS-2005-047-MKT Revision, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
  2. D. Fok & R. Paap & P.H. Franses, 2002. "Modeling dynamic effects of promotion on interpurchase times," Econometric Institute Report 289, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
    Other versions:
  3. Franses, Ph.H.B.F. & Paap, R. & Sijthoff, Ph.A., 2001. "Modeling Potentially Time-Varying Effects of Promotions on Sales," Research Paper ERS-2001-05-MKT Revision_, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
  4. Fok, D. & Franses, Ph.H.B.F. & Paap, R., 2001. "Econometric Analysis of the Market Share Attraction Model," Research Paper ERS-2001-25-MKT Revision_, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
  5. Kiygi Calli M. & Weverbergh M. & Franses P.H., 2008. "Modeling the Effectiveness of Hourly Direct-Response Radio Commercials," Working Papers 2008005, University of Antwerp, Faculty of Applied Economics. [Downloadable!]
  6. Heerde, H.J. van & Helsen, K. & Dekimpe, M.G., 2005. "Managing Product-Harm Crises," Research Paper ERS-2005-044-MKT Revision, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
  7. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2003. "Modeling Dynamic Effects of the Marketing Mix on Market Shares," Research Paper ERS-2003-044-MKT Revision, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
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