IDEAS home Printed from https://ideas.repec.org/p/hst/ghsdps/gd11-187.html
   My bibliography  Save this paper

Statistical Inference in Possibly Integrated/Cointegrated Vector Autoregressions: Application to Testing for Structural Changes

Author

Listed:
  • Eiji Kurozumi
  • Khashbaatar Dashtseren

Abstract

We develop a new approach of statistical inference in possibly integrated/cointegrated vector autoregressions. Our method is built on the two previous approaches: the lag augmented approach by Toda and Yamamoto (1995) and the artificial autoregressions by Yamamoto (1996). We show that our estimator is asymptotically normally distributed irrespective of whether the variables are stationary or nonstationary, and that the Wald test statistic for the parameter restrictions has an asymptotic chi-square distribution. Using this method, we also propose to test for multiple structural changes. We show that our test statistics have the same limiting distributions as in the standard case, irrespective of whether the variables are stationary, purely integrated, or cointegrated.

Suggested Citation

  • Eiji Kurozumi & Khashbaatar Dashtseren, 2011. "Statistical Inference in Possibly Integrated/Cointegrated Vector Autoregressions: Application to Testing for Structural Changes," Global COE Hi-Stat Discussion Paper Series gd11-187, Institute of Economic Research, Hitotsubashi University.
  • Handle: RePEc:hst:ghsdps:gd11-187
    as

    Download full text from publisher

    File URL: http://gcoe.ier.hit-u.ac.jp/research/discussion/2008/pdf/gd11-187.pdf
    Download Restriction: no

    More about this item

    Keywords

    multiple breaks; stationary; unit root; cointegration;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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:hst:ghsdps:gd11-187. 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: (Tatsuji Makino). General contact details of provider: http://edirc.repec.org/data/iehitjp.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.