Advanced Search
MyIDEAS: Login

Covariate Unit Root Tests with Good Size and Power

Contents:

Author Info

  • Fossati, Sebastian

    ()
    (University of Alberta, Department of Economics)

Abstract

The selection of the truncation lag for covariate unit root tests is analyzed using Monte Carlo simulation. It is shown that standard information criteria such as the BIC or the AIC can result in tests with large size distortions. Modifi ed information criteria can be used to construct tests with good size and power. An empirical illustration is provided.

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://www.uofaweb.ualberta.ca/economics2/pdfs/WP2011-04-Fossati.pdf
Our checks indicate that this address may not be valid because: 404 Not Found. If this is indeed the case, please notify (Brenda Carrier)
File Function: Full text
Download Restriction: no

Bibliographic Info

Paper provided by University of Alberta, Department of Economics in its series Working Papers with number 2011-4.

as in new window
Length: 31 pages
Date of creation: 01 May 2011
Date of revision:
Handle: RePEc:ris:albaec:2011_004

Contact details of provider:
Postal: 8-14 HM Tory, Edmonton, Alberta, T6G 2H4
Phone: (780) 492-3406
Fax: (780) 492-3300
Web page: http://www.economics.ualberta.ca/
More information through EDIRC

Related research

Keywords: unit root tests; truncation lag; information criteria; vector autoregressions;

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. Hofmann, Marc & Gatu, Cristian & Kontoghiorghes, Erricos John, 2007. "Efficient algorithms for computing the best subset regression models for large-scale problems," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 16-29, September.
  2. Elena Pesavento, 2006. "Near-Optimal Unit Root Tests with Stationary Covariates with Better Finite Sample Size," Economics Working Papers ECO2006/18, European University Institute.
  3. Galvao Jr., Antonio F., 2009. "Unit root quantile autoregression testing using covariates," Journal of Econometrics, Elsevier, vol. 152(2), pages 165-178, October.
  4. Gatu, Cristian & Yanev, Petko I. & Kontoghiorghes, Erricos J., 2007. "A graph approach to generate all possible regression submodels," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 799-815, October.
  5. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
  6. Elliott, Graham & Pesavento, Elena, 2006. "On the Failure of Purchasing Power Parity for Bilateral Exchange Rates after 1973," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1405-1430, September.
  7. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July.
  8. Donald W.K. Andrews, 1988. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Cowles Foundation Discussion Papers 877R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1989.
  9. Elliott, Graham & Jansson, Michael, 2003. "Testing for unit roots with stationary covariates," Journal of Econometrics, Elsevier, vol. 115(1), pages 75-89, July.
  10. G. William Schwert, 1988. "Tests For Unit Roots: A Monte Carlo Investigation," NBER Technical Working Papers 0073, National Bureau of Economic Research, Inc.
  11. Qu, Zhongjun & Perron, Pierre, 2007. "A Modified Information Criterion For Cointegration Tests Based On A Var Approximation," Econometric Theory, Cambridge University Press, vol. 23(04), pages 638-685, August.
  12. Serena Ng & Pierre Perron, 2005. "A Note on the Selection of Time Series Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(1), pages 115-134, 02.
  13. Graham Elliott & Michael Jansson & Elena Pesavento, 2003. "Optimal Power For Testing Potential Cointegrating Vectors with Known Parameters for Nonstationarity," Emory Economics 0303, Department of Economics, Emory University (Atlanta).
  14. Hansen, Bruce E., 1995. "Rethinking the Univariate Approach to Unit Root Testing: Using Covariates to Increase Power," Econometric Theory, Cambridge University Press, vol. 11(05), pages 1148-1171, October.
  15. Gatu, Cristian & Kontoghiorghes, Erricos J. & Gilli, Manfred & Winker, Peter, 2008. "An efficient branch-and-bound strategy for subset vector autoregressive model selection," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1949-1963, June.
  16. Jomana Amara & David Papell, 2006. "Testing for Purchasing Power Parity using stationary covariates," Applied Financial Economics, Taylor & Francis Journals, vol. 16(1-2), pages 29-39.
  17. Oke, T. & Lyhagen, J., 1999. "Small-sample properties of some tests for unit root with data-based choice of the degree of augmentation," Computational Statistics & Data Analysis, Elsevier, vol. 30(4), pages 457-469, June.
  18. Ivanov Ventzislav & Kilian Lutz, 2005. "A Practitioner's Guide to Lag Order Selection For VAR Impulse Response Analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-36, March.
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. Fossati, Sebastian, 2011. "Unit Root Testing with Stationary Covariates and a Structural Break in the Trend Function," Working Papers 2011-10, University of Alberta, Department of Economics.
  2. Grassi, S. & Proietti, T., 2014. "Characterising economic trends by Bayesian stochastic model specification search," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 359-374.
  3. Kazuki Hiraga, 2011. "New Methods for Testing the Sustainability of Government Debt," Keio/Kyoto Joint Global COE Discussion Paper Series 2011-020, Keio/Kyoto Joint Global COE Program.

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:ris:albaec:2011_004. 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: (Brenda Carrier).

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.