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Article: A systems approach to recursive economic forecasting and seasonal adjustment

TitleA systems approach to recursive economic forecasting and seasonal adjustment
Authors
Issue Date1989
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/camwa
Citation
Computers And Mathematics With Applications, 1989, v. 18 n. 6-7, p. 481-501 How to Cite?
AbstractThe paper discusses a new, fully recursive approach to the adaptive modelling, forecasting and seasonal adjustment of nonstationary economic time-series. The procedure is based around a time variable parameter (TVP) version of the well known "component" or "structural" model. It employs a novel method of sequential spectral decomposition (SSD), based on recursive state-space smoothing, to decompose the series into a number of quasi-orthogonal components. This SSD procedure can be considered as a complete approach to the problem of model identification and estimation, or it can be used as a first step in maximum likelihood estimation. Finally, the paper illustrates the overall adaptive approach by considering a practical example of a U.K. unemployment series which exhibits marked nonstationarity caused by various economic factors. © 1989.
Persistent Identifierhttp://hdl.handle.net/10722/157770
ISSN
2015 Impact Factor: 1.398
2015 SCImago Journal Rankings: 1.092

 

DC FieldValueLanguage
dc.contributor.authorYoung, Pen_US
dc.contributor.authorNg, Cen_US
dc.contributor.authorArmitage, Pen_US
dc.date.accessioned2012-08-08T08:55:38Z-
dc.date.available2012-08-08T08:55:38Z-
dc.date.issued1989en_US
dc.identifier.citationComputers And Mathematics With Applications, 1989, v. 18 n. 6-7, p. 481-501en_US
dc.identifier.issn0898-1221en_US
dc.identifier.urihttp://hdl.handle.net/10722/157770-
dc.description.abstractThe paper discusses a new, fully recursive approach to the adaptive modelling, forecasting and seasonal adjustment of nonstationary economic time-series. The procedure is based around a time variable parameter (TVP) version of the well known "component" or "structural" model. It employs a novel method of sequential spectral decomposition (SSD), based on recursive state-space smoothing, to decompose the series into a number of quasi-orthogonal components. This SSD procedure can be considered as a complete approach to the problem of model identification and estimation, or it can be used as a first step in maximum likelihood estimation. Finally, the paper illustrates the overall adaptive approach by considering a practical example of a U.K. unemployment series which exhibits marked nonstationarity caused by various economic factors. © 1989.en_US
dc.languageengen_US
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/camwaen_US
dc.relation.ispartofComputers and Mathematics with Applicationsen_US
dc.titleA systems approach to recursive economic forecasting and seasonal adjustmenten_US
dc.typeArticleen_US
dc.identifier.emailNg, C:cnng@hkucc.hku.hken_US
dc.identifier.authorityNg, C=rp00606en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0024931610en_US
dc.identifier.volume18en_US
dc.identifier.issue6-7en_US
dc.identifier.spage481en_US
dc.identifier.epage501en_US
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridYoung, P=7402038199en_US
dc.identifier.scopusauthoridNg, C=7401705590en_US
dc.identifier.scopusauthoridArmitage, P=7103166272en_US

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