An algorithm for computing the asymptotic Fisher information matrix for seasonal SISO models

Open Access
Authors
Publication date 2003
Series UvA Econometrics Discussion Paper, 2003/04
Number of pages 47
Publisher Amsterdam: Department of Quantitative Economics
Organisations
  • Faculty of Economics and Business (FEB) - Amsterdam School of Economics Research Institute (ASE-RI)
Abstract The paper presents an algorithm for computing the asymptotic Fisher information matrix of a possibly seasonal single input single output (SISO) time series model. That matrix is a block matrix whose elements are basically integrals over the oriented unit circle of rational functions. The procedure makes use of the autocovariance function of one or the cross-covariance function of two autoregressive processes based on the same noise. The algorithm also works when the input variable is omitted, the case of a seasonal ARMA model.
Document type Working paper
Language English
Published at http://www1.feb.uva.nl/pp/bin/472fulltext.pdf
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