Jump to content
 







Main menu
   


Navigation  



Main page
Contents
Current events
Random article
About Wikipedia
Contact us
Donate
 




Contribute  



Help
Learn to edit
Community portal
Recent changes
Upload file
 








Search  

































Create account

Log in
 









Create account
 Log in
 




Pages for logged out editors learn more  



Contributions
Talk
 



















Contents

   



(Top)
 


1 References  





2 Further reading  














Johansen test







Türkçe
Tiếng Vit
 

Edit links
 









Article
Talk
 

















Read
Edit
View history
 








Tools
   


Actions  



Read
Edit
View history
 




General  



What links here
Related changes
Upload file
Special pages
Permanent link
Page information
Cite this page
Get shortened URL
Download QR code
Wikidata item
 




Print/export  



Download as PDF
Printable version
 
















Appearance
   

 






From Wikipedia, the free encyclopedia
 


Instatistics, the Johansen test,[1] named after Søren Johansen, is a procedure for testing cointegration of several, say k, I(1) time series.[2] This test permits more than one cointegrating relationship so is more generally applicable than the Engle–Granger test which is based on the Dickey–Fuller (or the augmented) test for unit roots in the residuals from a single (estimated) cointegrating relationship.[3]

There are two types of Johansen test, either with trace or with eigenvalue, and the inferences might be a little bit different.[4] The null hypothesis for the trace test is that the number of cointegration vectors is r = r* < k, vs. the alternative that r = k. Testing proceeds sequentially for r* = 1,2, etc. and the first non-rejection of the null is taken as an estimate of r. The null hypothesis for the "maximum eigenvalue" test is as for the trace test but the alternative is r = r* + 1 and, again, testing proceeds sequentially for r* = 1,2,etc., with the first non-rejection used as an estimator for r.

Just like a unit root test, there can be a constant term, a trend term, both, or neither in the model. For a general VAR(p) model:

There are two possible specifications for error correction: that is, two vector error correction models (VECM):

1. The longrun VECM:

where

2. The transitory VECM:

where

The two are the same. In both VECM,

Inferences are drawn on Π, and they will be the same, so is the explanatory power.[citation needed]

References[edit]

  1. ^ Johansen, Søren (1991). "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models". Econometrica. 59 (6): 1551–1580. doi:10.2307/2938278. JSTOR 2938278.
  • ^ For the presence of I(2) variables see Ch. 9 of Johansen, Søren (1995). Likelihood-based Inference in Cointegrated Vector Autoregressive Models. Oxford University Press. ISBN 978-0-19-877450-1.
  • ^ Davidson, James (2000). Econometric Theory. Wiley. ISBN 0-631-21584-0.
  • ^ Hänninen, R. (2012). "The Law of One Price in United Kingdom Soft Sawnwood Imports – A Cointegration Approach". Modern Time Series Analysis in Forest Products Markets. Springer. p. 66. ISBN 978-94-011-4772-9.
  • Further reading[edit]


  • t
  • e

  • Retrieved from "https://en.wikipedia.org/w/index.php?title=Johansen_test&oldid=1214491529"

    Categories: 
    Mathematical finance
    Time series statistical tests
    Econometrics stubs
    Hidden categories: 
    Articles with short description
    Short description matches Wikidata
    All articles with unsourced statements
    Articles with unsourced statements from February 2019
    All stub articles
     



    This page was last edited on 19 March 2024, at 08:19 (UTC).

    Text is available under the Creative Commons Attribution-ShareAlike License 4.0; additional terms may apply. By using this site, you agree to the Terms of Use and Privacy Policy. Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc., a non-profit organization.



    Privacy policy

    About Wikipedia

    Disclaimers

    Contact Wikipedia

    Code of Conduct

    Developers

    Statistics

    Cookie statement

    Mobile view



    Wikimedia Foundation
    Powered by MediaWiki