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Covariate Unit Root Tests with Good Size and Power

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  • 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.

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File URL: http://www.uofaweb.ualberta.ca/economics2/pdfs/WP2011-04-Fossati.pdf
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Bibliographic Info

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

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

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

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References

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  1. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, Econometric Society, vol. 69(6), pages 1519-1554, November.
  2. Graham Elliott & Michael Jansson & Elena Pesavento, 2005. "Optimal Power for Testing Potential Cointegrating Vectors With Known Parameters for Nonstationarity," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 23, pages 34-48, January.
  3. Elliott, Graham & Jansson, Michael, 2000. "Testing for Unit Roots with Stationary Covariances," University of California at San Diego, Economics Working Paper Series qt47k7z69n, Department of Economics, UC San Diego.
  4. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(1), pages 5-17, January.
  5. 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.
  6. Bruce E. Hansen, 1995. "Rethinking the Univariate Approach to Unit Root Testing: Using Covariates to Increase Power," Boston College Working Papers in Economics 300., Boston College Department of Economics.
  7. 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.
  8. Elena Pesavento, 2006. "Near-optimal Unit Root Test with Stationary Covariate with Better Finite Sample Size," Emory Economics, Department of Economics, Emory University (Atlanta) 0606, Department of Economics, Emory University (Atlanta).
  9. 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.
  10. 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, Elsevier, vol. 32(6), pages 1949-1963, June.
  11. Graham Elliott & Thomas J. Rothenberg & James H. Stock, 1992. "Efficient Tests for an Autoregressive Unit Root," NBER Technical Working Papers 0130, National Bureau of Economic Research, Inc.
  12. 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, Blackwell Publishing, vol. 38(6), pages 1405-1430, September.
  13. 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.
  14. 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.
  15. Galvao Jr., Antonio F., 2009. "Unit root quantile autoregression testing using covariates," Journal of Econometrics, Elsevier, Elsevier, vol. 152(2), pages 165-178, October.
  16. 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, Elsevier, vol. 30(4), pages 457-469, June.
  17. 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, Elsevier, vol. 52(1), pages 16-29, September.
  18. Gatu, Cristian & Yanev, Petko I. & Kontoghiorghes, Erricos J., 2007. "A graph approach to generate all possible regression submodels," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 52(2), pages 799-815, October.
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Citations

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Cited by:
  1. Stefano Grassi & Tommaso Proietti, 2010. "Characterizing economic trends by Bayesian stochastic model specification search," EERI Research Paper Series EERI_RP_2010_25, Economics and Econometrics Research Institute (EERI), Brussels.
  2. Sebastian Fossati, 2013. "Unit root testing with stationary covariates and a structural break in the trend function," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 368-384, 05.
  3. Pitarakis, Jean-Yves, 2014. "A joint test for structural stability and a unit root in autoregressions," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 76(C), pages 577-587.
  4. Kazuki Hiraga, 2011. "New Methods for Testing the Sustainability of Government Debt," Keio/Kyoto Joint Global COE Discussion Paper Series, Keio/Kyoto Joint Global COE Program 2011-020, Keio/Kyoto Joint Global COE Program.

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