[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/52434.html
   My bibliography  Save this paper

A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data

Author

Listed:
  • Elrod, Terry
  • Keane, Michael
Abstract
Internal market structure analysis infers both brand attributes and consumer preferences for those attributes from preference or choice data. The authors exploit a new method for estimating probit models from panel data to infer market structures that can be displayed in few dimensions, even though the model can represent every possible vector of purchase probabilities.

Suggested Citation

  • 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.
    • Handle: RePEc:pra:mprapa:52434
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/52434/1/MPRA_paper_52434.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John R. Hauser & Steven M. Shugan, 2008. "Defensive Marketing Strategies," Marketing Science, INFORMS, vol. 27(1), pages 88-110, 01-02.
    2. DeSarbo, Wayne S. & De Soete, Geert & Eliashberg, Jehoshua, 1987. "A new stochastic multidimensional unfolding model for the investigation of paired comparison consumer preference/choice data," Journal of Economic Psychology, Elsevier, vol. 8(3), pages 357-384, September.
    3. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
    4. Geweke, John & Keane, Michael P & Runkle, David, 1994. "Alternative Computational Approaches to Inference in the Multinomial Probit Model," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 609-632, November.
    5. David B. MacKay & Joseph L. Zinnes, 1986. "A Probabilistic Model for the Multidimensional Scaling of Proximity and Preference Data," Marketing Science, INFORMS, vol. 5(4), pages 325-344.
    6. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    7. Joel Levine, 1979. "Joint-space analysis of “pick-any” data: Analysis of choices from an unconstrained set of alternatives," Psychometrika, Springer;The Psychometric Society, vol. 44(1), pages 85-92, March.
    8. John R. Hauser, 1978. "Testing the Accuracy, Usefulness, and Significance of Probabilistic Choice Models: An Information-Theoretic Approach," Operations Research, INFORMS, vol. 26(3), pages 406-421, June.
    9. Terry Elrod, 1988. "Choice Map: Inferring a Product-Market Map from Panel Data," Marketing Science, INFORMS, vol. 7(1), pages 21-40.
    10. Eric Holman, 1972. "The relation between hierarchical and euclidean models for psychological distances," Psychometrika, Springer;The Psychometric Society, vol. 37(4), pages 417-423, December.
    11. 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.
    12. Greg M. Allenby, 1989. "A Unified Approach to Identifying, Estimating and Testing Demand Structures with Aggregate Scanner Data," Marketing Science, INFORMS, vol. 8(3), pages 265-280.
    13. W. S. Desarbo & G. de Soete & J. D. Carroll & V. Ramaswamy, 1988. "A new stochastic ultrametric tree unfolding methodology for assessing competitive market structure and deriving market segments," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 4(3), pages 185-204, September.
    14. Vassilis A. Hajivassiliou & Daniel McFadden, 1990. "The Method of Simulated Scores for the Estimation of LDV Models with an Application to External Debt Crisis," Cowles Foundation Discussion Papers 967, Cowles Foundation for Research in Economics, Yale University.
    15. 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.
    16. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    17. Wayne DeSarbo & Vithala R. Rao, 1986. "A Constrained Unfolding Methodology for Product Positioning," Marketing Science, INFORMS, vol. 5(1), pages 1-19.
    18. Keane, Michael, 1993. "Simulation estimation for panel data models with limited dependent variables," MPRA Paper 53029, University Library of Munich, Germany.
    19. Kamel Jedidi & Wayne DeSarbo, 1991. "A stochastic multidimensional scaling procedure for the spatial representation of three-mode, three-way pick any/J data," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 471-494, September.
    20. Wayne DeSarbo & Jaewun Cho, 1989. "A stochastic multidimensional scaling vector threshold model for the spatial representation of “pick any/n” data," Psychometrika, Springer;The Psychometric Society, vol. 54(1), pages 105-129, March.
    21. Lee G. Cooper, 1988. "Competitive Maps: The Structure Underlying Asymmetric Cross Elasticities," Management Science, INFORMS, vol. 34(6), pages 707-723, June.
    22. Frank M. Bass & Abel Jeuland & Gordon P. Wright, 1976. "Equilibrium Stochastic Choice and Market Penetration Theories: Derivations and Comparisons," Management Science, INFORMS, vol. 22(10), pages 1051-1063, June.
    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. Gould, Brian W. & Dong, Diansheng, 2000. "The Decision Of When To Buy A Frequently Purchased Good: A Multi-Period Probit Model," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-17, December.
    2. Vassilis Argyrou Hajivassiliou, 1993. "Simulating Normal Rectangle Probabilities and Their Derivatives: The Effects of Vectorization," Working Papers _025, Yale University.
    3. Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441, Elsevier.
    4. 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.
    5. Siddhartha Chib & Edward Greenberg & Yuxin Chen, 1998. "MCMC Methods for Fitting and Comparing Multinomial Response Models," Econometrics 9802001, University Library of Munich, Germany, revised 06 May 1998.
    6. Lee, Lung-Fei, 1997. "Simulated maximum likelihood estimation of dynamic discrete choice statistical models some Monte Carlo results," Journal of Econometrics, Elsevier, vol. 82(1), pages 1-35.
    7. 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.
    8. Ricardo A. Daziano & Martin Achtnicht, 2014. "Forecasting Adoption of Ultra-Low-Emission Vehicles Using Bayes Estimates of a Multinomial Probit Model and the GHK Simulator," Transportation Science, INFORMS, vol. 48(4), pages 671-683, November.
    9. Inkmann, Joachim, 2000. "Misspecified heteroskedasticity in the panel probit model: A small sample comparison of GMM and SML estimators," Journal of Econometrics, Elsevier, vol. 97(2), pages 227-259, August.
    10. Ziegler Andreas, 2010. "Z-Tests in Multinomial Probit Models under Simulated Maximum Likelihood Estimation: Some Small Sample Properties," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(5), pages 630-652, October.
    11. Michael P. Keane, 2013. "Panel data discrete choice models of consumer demand," Economics Papers 2013-W08, Economics Group, Nuffield College, University of Oxford.
    12. McCulloch, Robert E. & Polson, Nicholas G. & Rossi, Peter E., 2000. "A Bayesian analysis of the multinomial probit model with fully identified parameters," Journal of Econometrics, Elsevier, vol. 99(1), pages 173-193, November.
    13. 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.
    14. Harris, Katherine M. & Keane, Michael P., 1998. "A model of health plan choice:: Inferring preferences and perceptions from a combination of revealed preference and attitudinal data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 131-157, November.
    15. DeSarbo, Wayne S. & Kim, Youngchan & Wedel, Michel & Fong, Duncan K. H., 1998. "A Bayesian approach to the spatial representation of market structure from consumer choice data," European Journal of Operational Research, Elsevier, vol. 111(2), pages 285-305, December.
    16. Park, Sang Soo & Lee, Chung-Ki, 2011. "베이지안 추정법을 이용한 주택선택의 다항프로빗 모형 분석 [Analysis of housing choice using multinomial probit model – Bayesian estimation]," MPRA Paper 37150, University Library of Munich, Germany.
    17. William Greene, 2001. "Fixed and Random Effects in Nonlinear Models," Working Papers 01-01, New York University, Leonard N. Stern School of Business, Department of Economics.
    18. Dawn Iacobucci & Doug Grisaffe & Wayne DeSarbo, 2017. "Statistical perceptual maps: using confidence region ellipses to enhance the interpretations of brand positions in multidimensional scaling," Journal of Marketing Analytics, Palgrave Macmillan, vol. 5(3), pages 81-98, December.
    19. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    20. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.

    More about this item

    Keywords

    Probit Model; Factor Analysis; Discrete Choice; Heterogeneity; Simulation based inference; Scanner data; Panel data;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    Statistics

    Access and download statistics

    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:pra:mprapa:52434. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.