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dc.contributor.authorRaknerud, Arvid
dc.contributor.authorSkjerpen, Terje
dc.contributor.authorSwensen, Anders Rygh
dc.date.accessioned2011-11-08T21:59:43Z
dc.date.available2011-11-08T21:59:43Z
dc.date.issued2007
dc.identifier.issn1892-753x
dc.identifier.urihttp://hdl.handle.net/11250/180667
dc.description.abstractAbstract: We use state space methods to estimate a large dynamic factor model for the Norwegian economy involving 93 variables for 1978Q2–2005Q4. The model is used to obtain forecasts for 22 key variables that can be derived from the original variables by aggregation. To investigate the potential gain in using such a large information set, we compare the forecasting properties of the dynamic factor model with those of univariate benchmark models. We find that there is an overall gain in using the dynamic factor model, but that the gain is notable only for a few of the key variables. Keywords: Dynamic factor model, Forecasting, State space, AR modelsno_NO
dc.language.isoengno_NO
dc.publisherStatistics Norway, Research Departmentno_NO
dc.relation.ispartofseriesDiscussion Papers;No. 504
dc.subjectDynamic factor modelno_NO
dc.subjectForecastingno_NO
dc.subjectEconometric modelingno_NO
dc.subjectJEL classification: C13no_NO
dc.subjectJEL classification: C22no_NO
dc.subjectJEL classification: C32no_NO
dc.subjectJEL classification: C53no_NO
dc.titleForecasting key macroeconomic variables from a large number of predictors : a state space approachno_NO
dc.typeWorking paperno_NO
dc.subject.nsiVDP::Social science: 200::Economics: 210::Economics: 212no_NO
dc.source.pagenumber31 s.no_NO


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