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Title:Assessing the real-time informational content of macroeconomic data releases for now-/forecasting GDP: Evidence for Switzerland PDF Logo
Authors:Siliverstovs, Boriss
Kholodilin, Konstantin Arkadievich
Issue Date:2010
Series/Report no.:Discussion papers // German Institute for Economic Research 970
Abstract:This study utilizes the dynamic factor model of Giannone et al. (2008) in order to make now-/forecasts of GDP quarter-on-quarter growth rates in Switzerland. It also assesses the informational content of macroeconomic data releases for forecasting of the Swiss GDP. We find that the factor model offers a substantial improvement in forecast accuracy of GDP growth rates compared to a benchmark naive constant-growth model at all forecast horizons and at all data vintages. The largest forecast accuracy is achieved when GDP nowcasts for an actual quarter are made about three months ahead of the official data release. We also document that both business tendency surveys as well as stock market indices possess the largest informational content for GDP forecasting although their ranking depends on the underlying transformation of monthly indicators from which the common factors are extracted.
Subjects:Business tendency surveys
forecasting
nowcasting
real-time data
dynamic factor model
JEL:C53
E37
Document Type:Working Paper
Appears in Collections:DIW-Diskussionspapiere
Publikationen von Forscherinnen und Forschern des DIW

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