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Unit Root Testing via the Continuous-Path Block Bootstrap

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  • Paparoditis, Efstathios
  • Politis, Dimitris N
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    Abstract

    A new resampling procedure, the continuous-path block bootstrap, is proposed in the context of testing for integrated (unit root) time series. The continuous-path block bootstrap (CBB) is a nonparametric procedure that successfully generates unit root integrated pseudo time series retaining the important characteristics of the data, e.g., the dependence structure of the stationary process driving the random walk. As a consequence, the CBB can accurately capture the distribution of many unit root test statistics. Large sample theory for the new bootstrap methodology is developed and the asymptotic validity of CBB-based unit root testing is shown via a bootstrap functional limit theorem. Applications of the new procedure to least squares and Dickey-Fuller type test statistics of the unit root hypothesis are given. Finite-sample simulations confirm a good alpha-level accuracy and an increased power associated with CBB-based unit root testing.

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    File URL: http://www.escholarship.org/uc/item/9qb4r775.pdf;origin=repeccitec
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    Bibliographic Info

    Paper provided by Department of Economics, UC San Diego in its series University of California at San Diego, Economics Working Paper Series with number qt9qb4r775.

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    Date of creation: 01 Mar 2001
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    Handle: RePEc:cdl:ucsdec:qt9qb4r775

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    Related research

    Keywords: Autocorrelation; hypothesis testing; integrated series; non-stationary series; random walk; resampling;

    References

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    1. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
    2. 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.
    3. Peter C.B. Phillips, 1985. "Time Series Regression with a Unit Root," Cowles Foundation Discussion Papers 740R, Cowles Foundation for Research in Economics, Yale University, revised Feb 1986.
    4. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220 National Bureau of Economic Research, Inc.
    5. DeJong, David N. & Nankervis, John C. & Savin, N. E. & Whiteman, Charles H., 1992. "The power problems of unit root test in time series with autoregressive errors," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 323-343.
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    Cited by:
    1. Gabriel Bruneau & Kevin Moran, 2012. "Exchange Rate Fluctuations and Labour Market Adjustments in Canadian Manufacturing Industries," Cahiers de recherche 1227, CIRPEE.
    2. Franz C. Palm & Stephan Smeekes & Jean-Pierre Urbain, 2008. "Bootstrap Unit-Root Tests: Comparison and Extensions," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(2), pages 371-401, 03.
    3. Peter C. B. Phillips, 2009. "Bootstrapping I(1) Data," Cowles Foundation Discussion Papers 1689, Cowles Foundation for Research in Economics, Yale University.
    4. Parker, Cameron & Paparoditis, Efstathios & Politis, Dimitris N., 2006. "Unit root testing via the stationary bootstrap," Journal of Econometrics, Elsevier, vol. 133(2), pages 601-638, August.

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