IDEAS home Printed from https://ideas.repec.org/p/bot/quadip/wpaper135.html
   My bibliography  Save this paper

Co-integration rank determination in partial systems using information criteria

Author

Listed:
  • Giuseppe Cavaliere

    () (Università di Bologna)

  • Luca De Angelis

    () (Università di Bologna)

  • Luca Fanelli

    ()

Abstract

We investigate the asymptotic and finite sample properties of the most widely used information criteria for co-integration rank determination in ‘partial’ systems, i.e. in co-integrated Vector Autoregressive (VAR) models where a sub-set of variables of interest is modeled conditional on another sub-set of variables. The asymptotic properties of the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC) and the Hannan-Quinn Information Criterion (HQC) are established, and consistency of BIC and HQC is proved. No- tably, consistency of BIC and HQC is robust to violations of the hypothesis of weak exogeneity of the conditioning variables with respect to the co-integration parameters. More precisely, BIC and HQC recover the true co-integration rank from the partial system analysis also when the conditional model does not convey all information about the co-integration parameters. This result opens up interesting possibilities for practitioners who can determine the co-integration rank in partial systems without being concerned with the weak exogeneity of the conditioning variables. A Monte Carlo experiment which considers large systems as data generating process shows that BIC and HQC applied in partial systems perform reasonably well in small samples and comparatively better than ‘traditional’ approaches for co-integration rank determination. We further show the usefulness of our approach and the benefits of the conditional system anal- ysis to co-integration rank determination with two empirical illustrations, both based on the estimation of VAR systems on U.S. quarterly data. Overall, our analysis clearly shows that the gains of combining information criteria with partial systems analysis are indisputable.

Suggested Citation

  • Giuseppe Cavaliere & Luca De Angelis & Luca Fanelli, 2016. "Co-integration rank determination in partial systems using information criteria," Quaderni di Dipartimento 4, Department of Statistics, University of Bologna.
  • Handle: RePEc:bot:quadip:wpaper:135
    as

    Download full text from publisher

    File URL: http://amsacta.unibo.it/id/eprint/5417
    Download Restriction: no

    More about this item

    Keywords

    Information criteria; Co-integration; Partial system; Conditional model; VAR. Criteri di informazione; co-integrazione; modello condizionato; VAR;

    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:bot:quadip:wpaper:135. 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: (Michela Mengoli). General contact details of provider: http://edirc.repec.org/data/dsbolit.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.