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Spectral bandwidth selection for long memory

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  • Grace Yap
  • Wen Cheong Chin

Abstract

Long-memory parameter estimation using log-periodogram regression relies largely on the frequency bandwidth and the order of estimation. Literature shows that a data-dependent plug-in method for the bandwidth significantly increases the MSE’s. In a long memory time series with mild short range effect, a simple approach to determine the bandwidth size is suggested based on the spectral analysis. Monte Carlo simulation results and empirical applications show that the proposed bandwidth selection performs satisfactorily.

Suggested Citation

  • Grace Yap & Wen Cheong Chin, 2016. "Spectral bandwidth selection for long memory," Modern Applied Science, Canadian Center of Science and Education, vol. 10(8), pages 1-63, August.
    • Handle: RePEc:ibn:masjnl:v:10:y:2016:i:8:p:63
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    References listed on IDEAS

    as
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    6. Liudas Giraitis & Peter M Robinson & Alexander Samarov, 2000. "Adaptive Semiparametric Estimation of the Memory Parameter - (Now published with revised title, Adaptive Rate-Optimal Estimation of the Memory Parameter, in Journal of Multivariate Analysis, 72 (2000)," STICERD - Econometrics Paper Series 379, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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