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Approximate State Space Modelling of Unobserved Fractional Components

URN to cite this document:
urn:nbn:de:bvb:355-epub-384165
DOI to cite this document:
10.5283/epub.38416
Hartl, Tobias ; Weigand, Roland
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Date of publication of this fulltext: 08 Mar 2019 10:23



Abstract

We propose convenient inferential methods for potentially nonstationary multivariate unobserved components models with fractional integration and cointegration. Based on finite-order ARMA approximations in the state space representation, maximum likelihood estimation can make use of the EM algorithm and related techniques. The approximation outperforms the frequently used autoregressive or moving ...

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