IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v22y2001i1p45-66.html

Properties of Predictors in Overdifferenced Nearly Nonstationary Autoregression

Author

Listed:
  • Ismael Sanchez
  • Daniel Pena

Abstract

We analyze the effect of overdifferencing a stationary AR(p+1) process whose largest root is near unity. It is found that, if the process is nearly nonstationary, the estimators of the overdifferenced model ARIMA(p,1,0) are root‐T consistent. It is also found that this misspecified ARIMA(p,1,0) has lower predictive mean squared error, to terms of small order, than the properly specified AR(p+1) model due to its parsimony. The advantage of the overdifferenced predictor depends on the remaining roots, the prediction horizon and the mean of the process.

Suggested Citation

  • Ismael Sanchez & Daniel Pena, 2001. "Properties of Predictors in Overdifferenced Nearly Nonstationary Autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(1), pages 45-66, January.
    • Handle: RePEc:bla:jtsera:v:22:y:2001:i:1:p:45-66
    DOI: 10.1111/1467-9892.00211
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-9892.00211
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1467-9892.00211?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
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. Alfredo Garcia Hiernaux & Miguel Jerez & José Casals, 2005. "Unit Roots and Cointegrating Matrix Estimation using Subspace Methods," Documentos de Trabajo del ICAE 0512, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2021. "Spurious relationships in high-dimensional systems with strong or mild persistence," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1480-1497.

    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:jtsera:v:22:y:2001:i:1:p:45-66. 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: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.