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dc.contributor.authorKapetanios, Georgeen
dc.date.accessioned2012-09-20T12:59:33Z-
dc.date.available2012-09-20T12:59:33Z-
dc.date.issued2002-
dc.identifier.urihttp://hdl.handle.net/10419/62833-
dc.description.abstractRecent work in the macroeconometric literature considers the problem of summarising efficiently a large set of variables and using this summary for a variety of purposes including forecasting. Work in this field has been carried out in a series of recent papers. This paper provides an alternative method for estimating factors derived from a factor state space model. This model has a clear dynamic interpretation. Further, the method does not require iterative estimation techniques and due to a modification introduced, can accommodate cases where the number of variables exceeds the number of observations. The computational cost and robustness of the method is comparable to that of principal component analysis because matrix algebraic methods are used.en
dc.language.isoengen
dc.publisher|aQueen Mary University of London, Department of Economics |cLondonen
dc.relation.ispartofseries|aWorking Paper |x466en
dc.subject.jelC13en
dc.subject.jelC32en
dc.subject.ddc330en
dc.subject.keywordFactor models, Subspace methods, State space modelsen
dc.subject.stwFaktorenanalyseen
dc.subject.stwPrognoseverfahrenen
dc.subject.stwSchätzungen
dc.subject.stwInflationen
dc.subject.stwGroßbritannienen
dc.subject.stwZustandsraummodellen
dc.titleFactor analysis using subspace factor models: Some theoretical results and an application to UK inflation forecasting-
dc.typeWorking Paperen
dc.identifier.ppn377026905en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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