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dc.contributor.authorMüller, Christianen_US
dc.contributor.authorKöberl, Evaen_US
dc.date.accessioned2009-12-15en_US
dc.date.accessioned2011-10-06T15:40:12Z-
dc.date.available2011-10-06T15:40:12Z-
dc.date.issued2008en_US
dc.identifier.pidoi:10.3929/ethz-a-005717922en_US
dc.identifier.urihttp://hdl.handle.net/10419/50352-
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. Futhermore, 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.en_US
dc.language.isoengen_US
dc.publisherKOF Zürichen_US
dc.relation.ispartofseriesKOF working papers // Konjunkturforschungsstelle, Eidgenössische Technische Hochschule Zürich 212en_US
dc.subject.jelE32en_US
dc.subject.jelC4en_US
dc.subject.jelC5en_US
dc.subject.ddc330en_US
dc.subject.keywordbusiness cycle measurementen_US
dc.subject.keywordsemantic cross validationen_US
dc.subject.keywordshock identificationen_US
dc.subject.stwKonjunkturen_US
dc.subject.stwSchocken_US
dc.subject.stwMessungen_US
dc.subject.stwSozialprodukten_US
dc.subject.stwSchätzungen_US
dc.subject.stwSchweizen_US
dc.titleBusiness cycle measurement with semantic filtering: A micro data approachen_US
dc.typeWorking Paperen_US
dc.identifier.ppn614998530en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:KOF Working Papers, KOF Konjunkturforschungsstelle, ETH Zürich

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