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dc.contributor.authorBARDSEN, Gunnar
dc.contributor.authorLUETKEPOHL, Helmut
dc.date.accessioned2009-06-22T09:54:01Z
dc.date.available2009-06-22T09:54:01Z
dc.date.issued2009
dc.identifier.issn1725-6704
dc.identifier.urihttps://hdl.handle.net/1814/11676
dc.description.abstractSometimes forecasts of the original variable are of interest although a variable appears in logarithms (logs) in a system of time series. In that case converting the forecast for the log of the variable to a naive forecast of the original variable by simply applying the exponential transformation is not optimal theoretically. A simple expression for the optimal forecast under normality assumptions is derived. Despite its theoretical advantages the optimal forecast is shown to be inferior to the naive forecast if specification and estimation uncertainty are taken into account. Hence, in practice using the exponential of the log forecast is preferable to using the optimal forecast.en
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.relation.ispartofseriesEUI ECOen
dc.relation.ispartofseries2009/24en
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectVector autoregressive modelen
dc.subjectCointegrationen
dc.subjectForecast root mean square erroren
dc.subjectC32en
dc.titleForecasting Levels of log Variables in Vector Autoregressionsen
dc.typeWorking Paperen
dc.neeo.contributorBARDSEN|Gunnar|aut|
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