A semiparametric two-step estimator in a multivariate long memory model.

This paper analyzes a two-step estimator of the long memory parameters of a vector process. The objective function considered is a semiparametric version of the multivariate Gaussian likelihood function in the frequency domain. In our context, semiparametric refers to the fact that only periodogra...

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Published in:Journal of Econometrics Vol. 90; no. 1; pp. 129 - 154
Main Author: Lobato, Ignacio N.
Format: Article
Published: Elsevier Science May 1999
Subjects:
Online Access:View this record in EBSCOhost
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      dt: May 1999
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      pub: Elsevier Science
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        512829881
        10.1016/S0304-4076(98)00038-4
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        atl: A semiparametric two-step estimator in a multivariate long memory model.
      aug:
        au: Lobato, Ignacio N.
      su:
        Gaussian processes
        Multivariate analysis
        Parameter estimation
        Foreign exchange
      sug:
        subj:
          Gaussian processes
          Multivariate analysis
          Parameter estimation
          Foreign exchange
      ab: This paper analyzes a two-step estimator of the long memory parameters of a vector process. The objective function considered is a semiparametric version of the multivariate Gaussian likelihood function in the frequency domain. In our context, semiparametric refers to the fact that only periodogram ordinates evaluated in a degenerating neighborhood of zero frequency are employed in the estimation procedure. Asymptotic normality is established under mild conditions that do not include Gaussianity. Furthermore, the simplicity of the form of the covariance matrix of the estimates facilitates statistical inference. We include an application of these estimates to exchange rate data. Reprinted by permission of the publisher.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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