Efficient tapered local Whittle estimation of multivariate fractional processes

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Abstract

The semiparametric estimation of multivariate fractional processes based on the tapered periodogram of the differenced series is considered in this paper. We construct multivariate local Whittle estimators by incorporating the maximal efficient taper developed by Chen (2010). The proposed estimation method allows a wide range of potentially nonstationary long-range dependent series, being invariant to the presence of deterministic trends with the same extent of the differencing order, without a two-step procedure. We establish the consistency and asymptotic normality of the proposed estimators, which have no discontinuities, and show that the asymptotic variance is the same as that of the nontapered local Whittle estimation by increasing the order of a taper to infinity with a moderately slow rate. We examine the finite sample behavior of the proposed estimators through a simulation experiment.

Original languageEnglish
Pages (from-to)234-256
Number of pages23
JournalJournal of Statistical Planning and Inference
Volume215
DOIs
Publication statusPublished - Dec 2021

Keywords

  • Fractional processes
  • Multivariate time series
  • Nonstationarity
  • Semiparametric estimation
  • Tapering

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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