Gaussian Semiparametric Estimation Of Multivariate Fractionally Integrated Processes

Katsumi Shimotsu

No 1062, Working Paper from Economics Department, Queen's University

Abstract: This paper analyzes the semiparametric estimation of multivariate long-range dependent processes. The class of spectral densities considered is motivated by and includes those of multivariate fractionally integrated processes. The paper establishes the consistency of the multivariate Gaussian semiparametric estimator (GSE), which has not been shown in other work, and the asymptotic normality of the GSE estimator. The proposed GSE estimator is shown to have a smaller limiting variance than the two-step GSE estimator studied by Lobato (1999). Gaussianity is not assumed in the asymptotic theory. Some simulations confirm the relevance of the asymptotic results in samples of the size used in practical work.

Keywords: fractional integration; long memory; semiparametric estimation (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2006-02
New Economics Papers: this item is included in nep-cba and nep-ets
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https://www.econ.queensu.ca/sites/econ.queensu.ca/files/qed_wp_1062.pdf First version 2006 (application/pdf)

Related works:
Journal Article: Gaussian semiparametric estimation of multivariate fractionally integrated processes (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:qed:wpaper:1062

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