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Whittle-type estimation under long memory and nonstationarity

Author

Listed:
  • Ying Lun Cheung

    (Capital University of Economics and Business)

  • Uwe Hassler

    (Goethe University Frankfurt)

Abstract

We consider six variants of (local) Whittle estimators of the fractional order of integration d. They follow a limiting normal distribution under stationarity as well as under (a certain degree of) nonstationarity. Experimentally, we observe a lack of continuity of the objective functions of the two fully extended versions at $$d=1/2$$ d = 1 / 2 that has not been reported before. It results in a pileup of the estimates at $$d=1/2$$ d = 1 / 2 when the true value is in a neighborhood to this half point. Consequently, studentized test statistics may be heavily oversized. The other four versions suffer from size distortions, too, although of a different pattern and to a different extent.

Suggested Citation

  • Ying Lun Cheung & Uwe Hassler, 2020. "Whittle-type estimation under long memory and nonstationarity," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 363-383, September.
    • Handle: RePEc:spr:alstar:v:104:y:2020:i:3:d:10.1007_s10182-019-00358-0
    DOI: 10.1007/s10182-019-00358-0
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    References listed on IDEAS

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