IDEAS home Printed from https://ideas.repec.org/p/tin/wpaper/19970042.html

Forecasting Dynamic Market Share Relationships

Author

Listed:
  • Nobuhiko Terui

    (Tohoku University)

Abstract

In market share analysis, it is well recognized that we have often inadmissible predicted marketshare, which means that some of predictors take the values outside the range [0, 1] and the totalsum of predicted shares is not always one, so called "logical inconsistency". In this article, basedon Bayesian VAR model, I propose a dynamic market share model with logical consistency. Theproposed method makes it possible to forecast not only the values of market share by themselves,but also various dynamic market share relations across different brands or companies. The dailyscanner data are analyzed by the proposed method.

Suggested Citation

  • Nobuhiko Terui, 1997. "Forecasting Dynamic Market Share Relationships," Tinbergen Institute Discussion Papers 97-042/4, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:19970042
    as

    Download full text from publisher

    File URL: https://papers.tinbergen.nl/97042.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Geweke, John, 1989. "Exact predictive densities for linear models with arch disturbances," Journal of Econometrics, Elsevier, vol. 40(1), pages 63-86, January.
    2. Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January.
    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. Kleibergen, F.R. & Hoek, H., 1995. "Bayesian Analysis of ARMA models using Noninformative Priors," Econometric Institute Research Papers EI 9553-/B, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Marsh, Thomas L. & Mittelhammer, Ronald C., 2000. "Truncated Regression In Empirical Estimation," 2000 Annual Meeting, June 29-July 1, 2000, Vancouver, British Columbia 36391, Western Agricultural Economics Association.
    3. Rombouts, Jeroen V.K. & Stentoft, Lars, 2014. "Bayesian option pricing using mixed normal heteroskedasticity models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 588-605.
    4. Ardia, David & Hoogerheide, Lennart F., 2010. "Efficient Bayesian estimation and combination of GARCH-type models," MPRA Paper 22919, University Library of Munich, Germany.
    5. Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
    6. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
    7. Shigeru Iwata & Evan Tanner, 2007. "Pick Your Poison: The Exchange Rate Regime and Capital Account Volatility in Emerging Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 57(7-8), pages 363-381, September.
    8. Siem Jan Koopman & Neil Shephard, 2002. "Testing the Assumptions Behind the Use of Importance Sampling," Economics Papers 2002-W17, Economics Group, Nuffield College, University of Oxford.
    9. VAN DIJK, Herman K., 1987. "Some advances in Bayesian estimations methods using Monte Carlo Integration," LIDAM Reprints CORE 783, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Feliz, Raúl Aníbal & Vargas, Laura, 1994. "Una prueba econométrica del enfoque moderno de la cuenta corriente en México," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 9(2), pages 189-207.
    11. Manabu Asai & Michael McAleer, 2022. "Bayesian Analysis of Realized Matrix-Exponential GARCH Models," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 103-123, January.
    12. Fok, Dennis & Franses, Philip Hans, 2007. "Modeling the diffusion of scientific publications," Journal of Econometrics, Elsevier, vol. 139(2), pages 376-390, August.
    13. Babula, Ronald A. & Bessler, David A. & Reeder, John & Somwaru, Agapi, 2004. "Modeling U.S. Soy-Based Markets with Directed Acyclic Graphs and Time Series Econometrics: Evaluating the U.S. Market Impacts of High Soy Meal Prices," Working Paper ID Series 15885, United States International Trade Commission, Office of Industries.
    14. van Dijk, H. K. & Kloek, T., 1983. "Experiments With Some Alternatives For Simple Importance Sampling In Monte Carlo Integration," Econometric Institute Archives 272281, Erasmus University Rotterdam.
    15. van Dijk, H. K. & Kloek, T., 1982. "Monte Carlo Analysis Of Skew Posterior Distributions: An Illustrative Econometric Example," Econometric Institute Archives 272268, Erasmus University Rotterdam.
    16. Villani, Mattias, 2006. "Bayesian point estimation of the cointegration space," Journal of Econometrics, Elsevier, vol. 134(2), pages 645-664, October.
    17. Heckelei, Thomas & Mittelhammer, Ronald C., 1996. "Bayesian Bootstrap Analysis of Systems of Equations," Discussion Papers 18786, University of Bonn, Institute for Food and Resource Economics.
    18. Garland Durham, 2004. "Likelihood-based estimation and specification analysis of one- and two-factor SV models with leverage effects," Econometric Society 2004 North American Summer Meetings 294, Econometric Society.
    19. Isaiah Hull & Or Sattath & Eleni Diamanti & Göran Wendin, 2024. "Quantum Technology for Economists," Contributions to Economics, Springer, number 978-3-031-50780-9, May.
    20. Rodney W. Strachan & Herman K. van Dijk, 2014. "Divergent Priors and Well Behaved Bayes Factors," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(1), pages 1-31, March.

    More about this item

    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:tin:wpaper:19970042. 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: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.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.