IDEAS home Printed from
   My bibliography  Save this article

A mixture-distribution factor model for multivariate outliers


  • Iliyan Georgiev


The aim of the paper is to go beyond the detection of outliers in multivariate time series, and to find regularities in the effect of special events on the series. The tool is a factor model in which the direction of every column of the loading matrix is identified, in contrast with Gaussian factor models, where only the span of the whole loading matrix is identified. Under asymptotics for rare and influential stochastic outliers, it is shown that the outliers' location is estimated consistently, and outliers are consistently classified into the factor components that have generated them. The direction, but not the length, of every column of the loading matrix is also estimated consistently. Inference on the directions, which underlies the interpretation of the factor structure, is asymptotically Gaussian under conditions that include Gaussianity of the innovations after accounting for the outliers. The model, augmented with a VAR specification for the conditional mean, provides a statistically acceptable and historically meaningful description of bond rates series for Denmark, Germany and the Netherlands. Copyright Royal Economic Society 2007

Suggested Citation

  • Iliyan Georgiev, 2007. "A mixture-distribution factor model for multivariate outliers," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 605-636, November.
  • Handle: RePEc:ect:emjrnl:v:10:y:2007:i:3:p:605-636

    Download full text from publisher

    File URL:
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.

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


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

    Cited by:

    1. Georgiev, Iliyan, 2010. "Model-based asymptotic inference on the effect of infrequent large shocks on cointegrated variables," Journal of Econometrics, Elsevier, vol. 158(1), pages 37-50, September.

    More about this item


    Access and download statistics


    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:ect:emjrnl:v:10:y:2007:i:3:p:605-636. 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: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: .

    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.