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dc.contributor.authorKapetanios, Georgeen_US
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_US
dc.publisherQueen Mary, Univ. of London, Dep. of Economics Londonen_US
dc.relation.ispartofseriesWorking Paper, Department of Economics, Queen Mary, University of London 466en_US
dc.subject.keywordFactor models, Subspace methods, State space modelsen_US
dc.titleFactor analysis using subspace factor models: Some theoretical results and an application to UK inflation forecastingen_US
dc.typeWorking Paperen_US
Appears in Collections:Working Paper Series, School of Economics and Finance, Queen Mary, University of London

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