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Seasonal Unit Root Tests Based on Forward and Reverse Estimation

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  • STEPHEN LEYBOURNE
  • A. M. ROBERT TAYLOR

Abstract

In this paper, we suggest a new set of regression‐based statistics for testing the seasonal unit root null hypothesis. These tests are based on combining conventional Hylleberg et al. (1990) ‐type seasonal unit root test statistics calculated from both forward and reverse estimation of the auxiliary regression equation. We derive the asymptotic distributions of the new test statistics under the seasonal unit root null hypothesis. We provide finite sample critical values appropriate for the case of quarterly data together with asymptotic critical values, the latter appropriate for any seasonal aspect. Monte Carlo simulation of the finite‐sample size and power properties of the new tests reveals that, overall, they perform rather better than extant tests of the seasonal unit root hypothesis.

Suggested Citation

  • Stephen Leybourne & A. M. Robert Taylor, 2003. "Seasonal Unit Root Tests Based on Forward and Reverse Estimation," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 441-460, July.
    • Handle: RePEc:bla:jtsera:v:24:y:2003:i:4:p:441-460
    DOI: 10.1111/1467-9892.00315
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    References listed on IDEAS

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    1. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    2. Elliott, Graham, 1999. "Efficient Tests for a Unit Root When the Initial Observation Is Drawn from Its Unconditional Distribution," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(3), pages 767-783, August.
    3. Burridge, Peter & Taylor, A M Robert, 2001. "On the Properties of Regression-Based Tests for Seasonal Unit Roots in the Presence of Higher-Order Serial Correlation," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 374-379, July.
    4. Leybourne, S J, 1995. "Testing for Unit Roots Using Forward and Reverse Dickey-Fuller Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 57(4), pages 559-571, November.
    5. Smith, Richard J. & Taylor, A. M. Robert, 1998. "Additional critical values and asymptotic representations for seasonal unit root tests," Journal of Econometrics, Elsevier, vol. 85(2), pages 269-288, August.
    6. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
    7. Ghysels, Eric & Lee, Hahn S. & Noh, Jaesum, 1994. "Testing for unit roots in seasonal time series : Some theoretical extensions and a Monte Carlo investigation," Journal of Econometrics, Elsevier, vol. 62(2), pages 415-442, June.
    8. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    9. Rodrigues, Paulo M.M., 2001. "Near Seasonal Integration," Econometric Theory, Cambridge University Press, vol. 17(1), pages 70-86, February.
    10. Pantula, Sastry G & Gonzalez-Farias, Graciela & Fuller, Wayne A, 1994. "A Comparison of Unit-Root Test Criteria," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 449-459, October.
    11. A. M. Robert Taylor, 1998. "Testing for Unit Roots in Monthly Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(3), pages 349-368, May.
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    Cited by:

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    2. Jesús Otero & Jeremy Smith, 2012. "Response surface models for the Leybourne unit root tests and lag order dependence," Computational Statistics, Springer, vol. 27(3), pages 473-486, September.

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