IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v41y1992i1p95-107.html
   My bibliography  Save this article

A Multivariate Time Series Analysis of Some Flour Price Data

Author

Listed:
  • Howard Grubb

Abstract

In this paper we develop and compare several multivariate models for some multiple time series data. The data are indices of the price of flour at three sites in the USA and have been used for illustration in a recent methodological paper. The models all come from the vector autoregressive moving average class so that comparisons between them can easily be made using criteria such as Akaike's information criterion. It is particularly interesting to compare the models produced by relatively complicated model specification procedures with those developed by using more straightforward techniques to see whether we gain any worthwhile improvements in fit.

Suggested Citation

  • Howard Grubb, 1992. "A Multivariate Time Series Analysis of Some Flour Price Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(1), pages 95-107, March.
    • Handle: RePEc:bla:jorssc:v:41:y:1992:i:1:p:95-107
    DOI: 10.2307/2347620
    as

    Download full text from publisher

    File URL: https://doi.org/10.2307/2347620
    Download Restriction: no
    File URL: https://libkey.io/10.2307/2347620?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. George Athanasopoulos & Farshid Vahid, 2008. "A complete VARMA modelling methodology based on scalar components," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(3), pages 533-554, May.
    2. Ribeiro Ramos, Francisco Fernando, 2003. "Forecasts of market shares from VAR and BVAR models: a comparison of their accuracy," International Journal of Forecasting, Elsevier, vol. 19(1), pages 95-110.
    3. Kato, Hiroko & Naniwa, Sadao & Ishiguro, Makio, 1996. "A bayesian multivariate nonstationary time series model for estimating mutual relationships among variables," Journal of Econometrics, Elsevier, vol. 75(1), pages 147-161, November.
    4. Xu Xiaojie, 2018. "Using Local Information to Improve Short-Run Corn Price Forecasts," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 16(1), pages 1-15, January.
    5. Francisco F. R. Ramos, 1996. "Forecasting market shares using VAR and BVAR models: A comparison of their forecasting performance," Econometrics 9601003, University Library of Munich, Germany.
    6. Galeano, Pedro, 2004. "Variance changes detection in multivariate time series," DES - Working Papers. Statistics and Econometrics. WS ws041305, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Lutkepohl, Helmut & Poskitt, D S, 1996. "Specification of Echelon-Form VARMA Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 69-79, January.
    8. Alfredo García Hiernaux & Miguel Jerez & José Casals, 2005. "Deteccióon de Raíces Unitarias y Cointegración mediante Métodos de Subespacios," Documentos de Trabajo del ICAE 0503, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

    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:bla:jorssc:v:41:y:1992:i:1:p:95-107. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.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.