Advanced Search
MyIDEAS: Login

The Fragility of the KPSS Stationarity Test

Contents:

Author Info

  • Nunzio Cappuccio

    ()
    (Department of Economics and Management, University of Padova)

  • Diego Lubian

    ()
    (Department of Economics (University of Verona))

Abstract

Stationarity tests exhibit extreme size distortions if the observable process is stationary yet highly persistent. In this paper we provide a theoretical explanation for the size distortion of the KPSS test for DGPs with a broad range of first order autocorrelation coefficient. Considering a near-integrated, nearly stationary process we show that the asymptotic distribution of the test contains an additional term, which can potentially explain the amount of size distortion documented in previous simulation studies.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://dse.univr.it//workingpapers/fragility_kpss.pdf
File Function: First version
Download Restriction: no

Bibliographic Info

Paper provided by University of Verona, Department of Economics in its series Working Papers with number 67/2009.

as in new window
Length: 20
Date of creation: Dec 2009
Date of revision:
Handle: RePEc:ver:wpaper:67/2009

Contact details of provider:
Postal: Vicolo Campofiore, 2 - I-37129 Verona
Phone: +390458028097
Fax: +390458028486
Email:
Web page: http://www.dse.univr.it
More information through EDIRC

Related research

Keywords: KPSS stationarity test; size distortion; nearly white noise nearly integrated model;

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?," Cowles Foundation Discussion Papers 979, Cowles Foundation for Research in Economics, Yale University.
  2. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-66, July.
  3. Markku Lanne & Pentti Saikkonen, 2003. "Reducing size distortions of parametric stationarity tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 423-439, 07.
  4. Nunzio Cappuccio & Diego Lubian, 2006. "Local Asymptotic Distributions of Stationarity Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(3), pages 323-345, 05.
  5. Newey, Whitney K & West, Kenneth D, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Wiley Blackwell, vol. 61(4), pages 631-53, October.
  6. Leybourne, S J & McCabe, B P M, 1994. "A Consistent Test for a Unit Root," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 157-66, April.
  7. Bart Hobijn & Philip Hans Franses & Marius Ooms, 2004. "Generalizations of the KPSS-test for stationarity," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 483-502.
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 in new window

Cited by:
  1. Majid M. Al-Sadoon, 2014. "A general theory of rank testing," Economics Working Papers 1411, Department of Economics and Business, Universitat Pompeu Fabra.
  2. Tadeusz Bednarski, 2010. "Fr├ęchet differentiability in statistical inference for time series," Statistical Methods and Applications, Springer, vol. 19(4), pages 517-528, November.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:ver:wpaper:67/2009. 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: (Michael Reiter).

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.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 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.