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Long Memory or Structural Change: Testing Method and Empirical Examination

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  • Chih-Chiang Hsu

    (National Central University)

Abstract

In this paper, we focus on how to test for long-range dependence when the process may have a one-time mean change and how to estimate the change point when data may be long-range dependent. We first analyzed why traditional long-memory tests have serious size distortions when data have short memory with breaks. In order to overcome this problem, a local Whittle method is proposed. Simulation results confirm that our change-point estimator is well behaved even when data are long-range dependent, and that our test for long memory maintains proper size when a change is present. These results indicate that our method is practically useful and has a much wider applicability. In order to assess the empirical relevance of our procedure, we applied it to analyze monthly G7 inflation rates.

Suggested Citation

  • Chih-Chiang Hsu, 2000. "Long Memory or Structural Change: Testing Method and Empirical Examination," Econometric Society World Congress 2000 Contributed Papers 0867, Econometric Society.
    • Handle: RePEc:ecm:wc2000:0867
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    References listed on IDEAS

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    Cited by:

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    3. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.
    4. Luis Gil-Alana, 2008. "Real GDP growth rates across countries: long memory and mean shifts," Applied Economics Letters, Taylor & Francis Journals, vol. 15(6), pages 449-455.

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