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Unit Root Testing via the Continuous-Path Block Bootstrap

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  • Paparoditis, Efstathios
  • Politis, Dimitris N

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.

Suggested Citation

  • Paparoditis, Efstathios & Politis, Dimitris N, 2001. "Unit Root Testing via the Continuous-Path Block Bootstrap," University of California at San Diego, Economics Working Paper Series qt9qb4r775, Department of Economics, UC San Diego.
    • Handle: RePEc:cdl:ucsdec:qt9qb4r775
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    References listed on IDEAS

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    1. 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.
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    3. 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.
    4. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    5. 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.
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    1. Phillips, Peter C.B., 2010. "Bootstrapping I(1) data," Journal of Econometrics, Elsevier, vol. 158(2), pages 280-284, October.
    2. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Carsten Jentsch & Dimitris N. Politis & Efstathios Paparoditis, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 416-441, May.
    3. Brüggemann, Ralf & Jentsch, Carsten & Trenkler, Carsten, 2016. "Inference in VARs with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 191(1), pages 69-85.
    4. Bruggeman, Annick & Donati, Paola & Warne, Anders, 2003. "Is the demand for euro area M3 stable?," Working Paper Series 255, European Central Bank.
    5. 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.
    6. Rosa Badillo & Jorge Belaire-Franch & Carmelo Reverte, 2010. "Residual-based block bootstrap for cointegration testing," Applied Economics Letters, Taylor & Francis Journals, vol. 17(10), pages 999-1003.
    7. Gabriel Bruneau & Kevin Moran, 2017. "Exchange rate fluctuations and labour market adjustments in Canadian manufacturing industries," Canadian Journal of Economics, Canadian Economics Association, vol. 50(1), pages 72-93, February.
    8. 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, March.
    9. Peter Buhlmann, 2007. "Bootstrap schemes for time series (in Russian)," Quantile, Quantile, issue 3, pages 37-56, September.
    10. Andriy Andreev & Antti Kanto & Pekka Malo, 2007. "Computational Examples of a New Method for Distribution Selection in the Pearson System," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(4), pages 487-506.
    11. Christis Katsouris, 2023. "Bootstrapping Nonstationary Autoregressive Processes with Predictive Regression Models," Papers 2307.14463, arXiv.org.

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