Real-time nowcasting the US output gap: Singular spectrum analysis at work

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• 作者：Miguel de Carvalho^a ; ^{MdeCarvalho@mat.puc.cl} ; Antó ; nio Rua^b ; ^c ; ^{Antonio.Rua@bportugal.pt}
• 关键词：Band-pass filter ; Fisher gg test ; Multivariate singular spectrum analysis ; Singular spectrum analysis ; US output gap ; Real-time data
• 刊名：International Journal of Forecasting
• 出版年：2017
• 出版时间：January-March 2017
• 年：2017
• 卷：33
• 期：1
• 页码：185-198
• 全文大小：1531 K
• 卷排序：33

文摘

We explore a new approach for nowcasting the output gap based on singular spectrum analysis. Resorting to real-time vintages, a recursive exercise is conducted in order to assess the real-time reliability of our approach for nowcasting the US output gap, relative to some well-known benchmark models. For our application of interest, the preferred version of our approach is a multivariate singular spectrum analysis, where we use a Fisher gg test to infer which components, within the standard business cycle range, should be included in the grouping step. We find that singular spectrum analysis provides a reliable assessment of the cyclical position of the economy in real time, with the multivariate approach outperforming its univariate counterpart substantially.