IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v18y1993i4p761-76.html
   My bibliography  Save this article

Seasonal Cointegration, Common Seasonals, and Forecasting Seasonal Series

Author

Listed:
  • Kunst, Robert M

Abstract

Seasonal cointegration generalizes the idea of cointegration to processes with unit roots at frequencies different from 0. Here, "common seasonals," also a dual notion of common trends, is adopted for the seasonal case. The features are demonstrated in exemplary models for German and U.K. data. An evaluation of the predictive value of accounting for several cointegration shows that season cointegration may be difficult to exploit to improve predictive accuracy even in cases where seasonal no-cointegration is clearly rejected on statistical grounds. The findings from the real-world examples are corroborated by Monte Carlo simulation.

Suggested Citation

  • Kunst, Robert M, 1993. "Seasonal Cointegration, Common Seasonals, and Forecasting Seasonal Series," Empirical Economics, Springer, vol. 18(4), pages 761-776.
  • Handle: RePEc:spr:empeco:v:18:y:1993:i:4:p:761-76
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Lof, Marten & Hans Franses, Philip, 2001. "On forecasting cointegrated seasonal time series," International Journal of Forecasting, Elsevier, vol. 17(4), pages 607-621.
    2. Arnade, Carlos & Pick, Daniel, 1998. "Seasonality and unit roots: the demand for fruits," Agricultural Economics, Blackwell, vol. 18(1), pages 53-62, January.
    3. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex.
    4. Wang, Zijun & Bessler, David A, 2002. "The Homogeneity Restriction and Forecasting Performance of VAR-Type Demand Systems: An Empirical Examination of US Meat Consumption," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(3), pages 193-206, April.
    5. Lof, Marten & Lyhagen, Johan, 2002. "Forecasting performance of seasonal cointegration models," International Journal of Forecasting, Elsevier, vol. 18(1), pages 31-44.
    6. Nga, Nguyen Thi Duong & Lantican, Flordeliza A., 1. "Spatial Integration of Rice Markets in Vietnam," Asian Journal of Agriculture and Development, Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), vol. 6(1).
    7. Adusei Jumah & Robert M. Kunst, 2008. "Seasonal prediction of European cereal prices: good forecasts using bad models?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 391-406.
    8. Reimers, Hans-Eggert, 1997. "Forecasting of seasonal cointegrated processes," International Journal of Forecasting, Elsevier, vol. 13(3), pages 369-380, September.
    9. Ozlem Tasseven, 2009. "Seasonal Co-integration An Extension of the Johansen and Schaumburg Approach with an Exclusion Test," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 56(1), pages 39-53, March.
    10. David R. Bell & Ronald C. Griffin, 2011. "Urban Water Demand with Periodic Error Correction," Land Economics, University of Wisconsin Press, vol. 87(3), pages 528-544.
    11. Hassler Uwe, 2001. "Wealth and Consumption. A Multicointegrated Model for the Unified Germany / Vermögen und Konsum. Ein multikointegriertes Modell für das vereinigte Deutschland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 221(1), pages 32-44, February.
    12. Cubadda, Gianluca, 2001. " Complex Reduced Rank Models for Seasonally Cointegrated Time Series," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 63(4), pages 497-511, September.

    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:spr:empeco:v:18:y:1993:i:4:p:761-76. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: http://www.springer.com .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.