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Title:Business cycle measurement with semantic filtering: A micro data approach PDF Logo
Authors:Müller, Christian
Köberl, Eva
Issue Date:2008
Series/Report no.:KOF working papers // Konjunkturforschungsstelle, Eidgenössische Technische Hochschule Zürich 212
Abstract:In 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.
Subjects:business cycle measurement
semantic cross validation
shock identification
JEL:E32
C4
C5
Persistent Identifier of the first edition:doi:10.3929/ethz-a-005717922
Document Type:Working Paper
Appears in Collections:KOF Working Papers, KOF Konjunkturforschungsstelle, ETH Zürich

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