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dc.contributor.authorLUETKEPOHL, Helmut
dc.contributor.authorXU, Fang
dc.date.accessioned2009-04-08T15:50:44Z
dc.date.available2009-04-08T15:50:44Z
dc.date.issued2009
dc.identifier.issn1830-7728
dc.identifier.urihttp://hdl.handle.net/1814/11150
dc.description.abstractFor forecasting and economic analysis many variables are used in logarithms (logs). In time series analysis this transformation is often considered to stabilize the variance of a series. We investigate under which conditions taking logs is beneficial for forecasting. Forecasts based on the original series are compared to forecasts based on logs. It is found that it depends on the data generation process whether the former or the latter are preferable. For a range of economic variables substantial forecasting improvements from taking logs are found if the log transformation actually stabilizes the variance of the underlying series. Using logs can be damaging for the forecast precision if a stable variance is not achieved.en
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherEuropean University Institute
dc.relation.ispartofseriesEUI MWPen
dc.relation.ispartofseries2009/06en
dc.relation.hasversionhttp://hdl.handle.net/1814/31057
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAutoregressive moving average processen
dc.subjectforecast mean squared erroren
dc.subjectinstantaneous transformationen
dc.subjectintegrated processen
dc.subjectheteroskedasticityen
dc.subjectC22en
dc.titleThe Role of log Transformation in Forecasting Economic Variablesen
dc.typeWorking Paperen
dc.neeo.contributorLUETKEPOHL|Helmut|aut|EUI70007
dc.neeo.contributorXU|Fang|aut|
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