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Rank-based unit root testing in the presence of structural change under the null: simulation results and an application to US inflation

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  • Steven Cook
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    Abstract

    The size distortion of the Dickey-Fuller (Journal of the American Statistical Association, 74, pp. 427-31, 1979) unit root test is examined in the presence of structural changes in both the level and variance of integrated time series. In contrast to previous studies, the empirically relevant situation in which such breaks occur simultaneously is examined. It is shown that the severe distortion observed for the Dickey-Fuller test can be dramatically reduced via application of a simple rank-based method. The simulation results presented are supported by an empirical examination of the integrated nature of US inflation where differing inferences are drawn using the Dickey-Fuller test and the rank-based Dickey-Fuller test.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/0003684042000337370
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Economics.

    Volume (Year): 37 (2005)
    Issue (Month): 6 ()
    Pages: 607-617

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    Handle: RePEc:taf:applec:v:37:y:2005:i:6:p:607-617

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    1. Zivot, Eric & Andrews, Donald W K, 1992. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 251-70, July.
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    3. Aggarwal, Reena & Inclan, Carla & Leal, Ricardo, 1999. "Volatility in Emerging Stock Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(01), pages 33-55, March.
    4. Anindya Banerjee & Robin L. Lumsdaine & James H. Stock, 1990. "Recursive and Sequential Tests of the Unit Root and Trend Break Hypothesis: Theory and International Evidence," NBER Working Papers 3510, National Bureau of Economic Research, Inc.
    5. Perron, Pierre, 1990. "Testing for a Unit Root in a Time Series with a Changing Mean," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 153-62, April.
    6. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    7. Kim, Tae-Hwan & Leybourne, Stephen & Newbold, Paul, 2002. "Unit root tests with a break in innovation variance," Journal of Econometrics, Elsevier, vol. 109(2), pages 365-387, August.
    8. Marianne Sensier & Dick van Dijk, 2004. "Testing for Volatility Changes in U.S. Macroeconomic Time Series," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 833-839, August.
    9. Busetti, Fabio & Taylor, A M Robert, 2003. "Variance Shifts, Structural Breaks, and Stationarity Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(4), pages 510-31, October.
    10. 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 559-71, November.
    11. Stephen J. Leybourne And Paul Newbold, 2000. "Behaviour of the standard and symmetric Dickey-Fuller-type tests when there is a break under the null hypothesis," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 1-15.
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    Cited by:
    1. Basher, Syed A. & Westerlund, Joakim, 2006. "Is there Really a Unit Root in the Inflation Rate? More Evidence from Panel Data Models," MPRA Paper 136, University Library of Munich, Germany.

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