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Bootstrapping Time Series Regressions with Integrated Processes

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  • Hongyi Li
  • Zhijie Xiao

Abstract

This paper studies the bootstrap procedures for time series regressions with integrated processes. Both estimation and hypothesis testing are studied. It is shown that the suggested bootstrap approximations to the distribution of the least squares estimator and the regression test statistic are asymptotically valid. A Monte Carlo experiment is conducted to evaluate the finite sample performance of these bootstrap procedures. The simulation results indicate that the bootstrap method provides reasonably good approximation to the distribution of the least squares estimator, and gives proper size and satisfactory power.

Suggested Citation

  • Hongyi Li & Zhijie Xiao, 2001. "Bootstrapping Time Series Regressions with Integrated Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(4), pages 461-480, July.
    • Handle: RePEc:bla:jtsera:v:22:y:2001:i:4:p:461-480
    DOI: 10.1111/1467-9892.00235
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    Cited by:

    1. Jack Strauss & Mark E. Wohar, 2007. "Domestic‐Foreign Interest Rate Differentials: Near Unit Roots and Symmetric Threshold Models," Southern Economic Journal, John Wiley & Sons, vol. 73(3), pages 814-829, January.
    2. Christis Katsouris, 2023. "Bootstrapping Nonstationary Autoregressive Processes with Predictive Regression Models," Papers 2307.14463, arXiv.org.

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