IDEAS home Printed from https://ideas.repec.org/a/ecm/emetrp/v60y1992i1p119-43.html
   My bibliography  Save this article

Canonical Cointegrating Regressions

Author

Listed:
  • Park, Joon Y

Abstract

A new procedure for statistical inference in cointegrating regressions is developed. The author introduces canonical cointegrating regressions (regressions formulated with the transformed data). The required transformations involve simple adjustments of the integrated processes using stationary components in cointegrating models. Canonical cointegrating regressions, therefore, represent the same cointegrating relationships as the original models. They are, however, constructed in such a way that the usual least squares procedure yields asymptotically efficient estimators and chi-square tests. The methodology presented here is applicable to a very wide class of cointegrating models, including models with deterministic and singular, as well as stochastic and regular, cointegrations. Copyright 1992 by The Econometric Society.

Suggested Citation

  • Park, Joon Y, 1992. "Canonical Cointegrating Regressions," Econometrica, Econometric Society, vol. 60(1), pages 119-143, January.
  • Handle: RePEc:ecm:emetrp:v:60:y:1992:i:1:p:119-43
    as

    Download full text from publisher

    File URL: http://links.jstor.org/sici?sici=0012-9682%28199201%2960%3A1%3C119%3ACCR%3E2.0.CO%3B2-R&origin=repec
    File Function: full text
    Download Restriction: Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ecm:emetrp:v:60:y:1992:i:1:p:119-43. 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/essssea.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.