Publication type: Working paper – expertise – study
Title: Business cycle measurement with semantic filtering : a micro data approach
Authors: Müller, Christian
Köberl, Eva
DOI: 10.3929/ethz-a-005717922
Extent: 17
Issue Date: 2008
Series: KOF Working Papers
Series volume: 212
Publisher / Ed. Institution: KOF Swiss Economic Institute
Publisher / Ed. Institution: Zürich
Language: English
Subjects: Business Cycle Measurement; Semantic Cross Validation; Shock Identification
Subject (DDC): 338: Production
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. 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.
License (according to publishing contract): Licence according to publishing contract
Departement: School of Management and Law
Organisational Unit: Center for Economic Policy (FWP)
Appears in collections:Publikationen School of Management and Law

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