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Sieve bootstrap monitoring for change from short to long memory

Author

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  • Chen, Zhanshou
  • Xing, Yuhong
  • Li, Fuxiao

Abstract

This paper proposes a variance ratio statistic to monitor changes from short to long memory processes. The asymptotic distribution is derived under the null hypothesis and the consistency of the monitoring procedure is proven under the alternative hypothesis. A sieve bootstrap approximation method is introduced to determine the critical values. Simulations indicate that the new procedure is quite robust for many types of innovation processes and performs better than the existing retrospective test.

Suggested Citation

  • Chen, Zhanshou & Xing, Yuhong & Li, Fuxiao, 2016. "Sieve bootstrap monitoring for change from short to long memory," Economics Letters, Elsevier, vol. 140(C), pages 53-56.
  • Handle: RePEc:eee:ecolet:v:140:y:2016:i:c:p:53-56
    DOI: 10.1016/j.econlet.2015.12.023
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    References listed on IDEAS

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