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On the Behaviour of Phillips–Perron Tests in the Presence of Persistent Cycles

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  • Tomás Del Barrio Castro
  • Paulo M. M. Rodrigues
  • A. M. Robert Taylor

Abstract

type="main" xml:id="obes12091-abs-0001"> In this paper, we analyse the impact of persistent cycles on the well-known semi-parametric unit root tests of Phillips and Perron (1988, Biometrika, Vol. 75, pp. 335–346). It is shown, both analytically and through Monte Carlo simulations, that the presence of complex (near) unit roots can severely bias the size properties of these tests. Given the popularity of these tests with applied researchers and their routine presence in most econometric software packages, the results presented in this paper suggest that practitioners should treat the outcomes of these tests with some caution when applied to data which display a strong cyclical component.

Suggested Citation

  • Tomás Del Barrio Castro & Paulo M. M. Rodrigues & A. M. Robert Taylor, 2015. "On the Behaviour of Phillips–Perron Tests in the Presence of Persistent Cycles," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(4), pages 495-511, August.
    • Handle: RePEc:bla:obuest:v:77:y:2015:i:4:p:495-511
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    File URL: http://hdl.handle.net/10.1111/obes.2015.77.issue-4
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    1. Pierre Perron & Serena Ng, 1996. "Useful Modifications to some Unit Root Tests with Dependent Errors and their Local Asymptotic Properties," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 63(3), pages 435-463.
    2. Castro, Tomás del Barrio & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2013. "The Impact Of Persistent Cycles On Zero Frequency Unit Root Tests," Econometric Theory, Cambridge University Press, vol. 29(6), pages 1289-1313, December.
    3. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    4. Taylor, A M Robert, 2003. "Robust Stationarity Tests in Seasonal Time Series Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 156-163, January.
    5. Bierens, Herman J., 2001. "Complex Unit Roots And Business Cycles: Are They Real?," Econometric Theory, Cambridge University Press, vol. 17(5), pages 962-983, October.
    6. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    7. Perron, Pierre & Ng, Serena, 1998. "An Autoregressive Spectral Density Estimator At Frequency Zero For Nonstationarity Tests," Econometric Theory, Cambridge University Press, vol. 14(5), pages 560-603, October.
    8. Niels Haldrup & Peter Lildholdt, 2002. "On the Robustness of Unit Root Tests in the Presence of Double Unit Roots," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(2), pages 155-171, March.
    9. Yoosoon Chang & Joon Park, 2002. "On The Asymptotics Of Adf Tests For Unit Roots," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 431-447.
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    11. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    12. Donald S. Allen, 1997. "Filtering permanent cycles with complex unit roots," Working Papers 1997-001, Federal Reserve Bank of St. Louis.
    13. Jansson, Michael, 2002. "Consistent Covariance Matrix Estimation For Linear Processes," Econometric Theory, Cambridge University Press, vol. 18(6), pages 1449-1459, December.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Unit Root Tests and Seasonally Adjusted Data
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2014-09-13 01:03:00

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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