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dc.contributor.authorMüller, Christian-
dc.contributor.authorKöberl, Eva-
dc.date.accessioned2019-02-15T11:11:45Z-
dc.date.available2019-02-15T11:11:45Z-
dc.date.issued2008-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/15393-
dc.description.abstractIn this paper we develop a business cycle measure that can be shown to have excellent ex-ante forecasting properties for GDP growth. For identifying business cycle movements, we use a semantic approach. We infer nine different states of the economy directly from firms’ responses in business tendency surveys. Hence, we can identify the current state of the economy. We therewith measure business cycle fluctuations. One of the main advantages of our methodology is that it is a structural concept based on shock identification and therefore does not need any - often rather arbitrary - statistical filtering. Furthermore, it is not subject to revisions, it is available in real-time and has a publication lead to official GDP data of at least one quarter. It can therefore be used for one quarter ahead forecasting real GDP growth.de_CH
dc.format.extent17de_CH
dc.language.isoende_CH
dc.publisherKOF Swiss Economic Institutede_CH
dc.relation.ispartofseriesKOF Working Papersde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectBusiness Cycle Measurementde_CH
dc.subjectSemantic Cross Validationde_CH
dc.subjectShock Identificationde_CH
dc.subject.ddc338: Produktionde_CH
dc.titleBusiness cycle measurement with semantic filtering : a micro data approachde_CH
dc.typeWorking Paper – Gutachten – Studiede_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.organisationalunitFachstelle für Wirtschaftspolitik (FWP)de_CH
zhaw.publisher.placeZürichde_CH
dc.identifier.doi10.3929/ethz-a-005717922de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.series.number212de_CH
Appears in Collections:Publikationen School of Management and Law

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