IDEAS home Printed from https://ideas.repec.org/p/kud/kuiedp/0305.html
   My bibliography  Save this paper

Cointegration Analysis in the Presence of Outliers

Author

Listed:
  • Heino Bohn Nielsen

    (University of Copenhagen Institute of Economics)

Abstract

The effects of innovational outliers and additive outliers in cointegrated vector autoregressions are examined and it is analyzed how outliers can be modelled with dummy variables. Using a Monte Carlo simulation it is illustrated how misspecified dummies may distort inference on the cointegration rank in finite samples. That questions the common practice in applied cointegration analyses of including unrestricted dummy variables to account for large residuals. Instead it is suggested to test the adequacy of a particular specification of dummies prior to determining the cointegration rank. The points are illustrated on a UK money demand data set

Suggested Citation

  • Heino Bohn Nielsen, 2003. "Cointegration Analysis in the Presence of Outliers," Discussion Papers 03-05, University of Copenhagen. Department of Economics.
  • Handle: RePEc:kud:kuiedp:0305
    as

    Download full text from publisher

    File URL: http://www.econ.ku.dk/english/research/publications/wp/2003/0305.pdf/
    Download Restriction: no

    References listed on IDEAS

    as
    1. Edward Morey & Kathleen Greer Rossmann, 2003. "Using Stated-Preference Questions to Investigate Variations in Willingness to Pay for Preserving Marble Monuments: Classic Heterogeneity, Random Parameters, and Mixture Models," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 27(3), pages 215-229, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Hans Christian Kongsted & Heino Bohn Nielsen, 2004. "Analysing I(2) Systems by Transformed Vector Autoregressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 379-397, July.

    More about this item

    Keywords

    cointegrated VAR; innovational outlier; additive outlier; dummy variables; Monte Carlo;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:kud:kuiedp:0305. 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: (Thomas Hoffmann). General contact details of provider: http://edirc.repec.org/data/okokudk.html .

    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.