Abstract
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 g 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.
| Original language | English |
|---|---|
| Pages (from-to) | 185-198 |
| Number of pages | 14 |
| Journal | International Journal of Forecasting |
| Volume | 33 |
| Issue number | 1 |
| Early online date | 2 Feb 2016 |
| DOIs | |
| Publication status | Published - Jan 2017 |
Keywords / Materials (for Non-textual outputs)
- Band-pass filter,Fisher g test,Multivariate singular spectrum analysis,Real-time data,Singular spectrum analysis,US output gap
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Dive into the research topics of 'Real-Time Nowcasting the US Output Gap: Singular Spectrum Analysis at Work'. Together they form a unique fingerprint.Profiles
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Miguel de Carvalho
- School of Mathematics - Personal Chair of Statistical Data Science
Person: Academic: Research Active
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