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

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  • de Carvalho, Miguel
  • Rua, António

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.

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  • de Carvalho, Miguel & Rua, António, 2017. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.
    • Handle: RePEc:eee:intfor:v:33:y:2017:i:1:p:185-198
    DOI: 10.1016/j.ijforecast.2015.09.004
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    2. Marcelo C. Medeiros & Henrique F. Pires, 2021. "The Proper Use of Google Trends in Forecasting Models," Papers 2104.03065, arXiv.org, revised Apr 2021.
    3. Paulo Canas Rodrigues & Olushina Olawale Awe & Jonatha Sousa Pimentel & Rahim Mahmoudvand, 2020. "Modelling the Behaviour of Currency Exchange Rates with Singular Spectrum Analysis and Artificial Neural Networks," Stats, MDPI, vol. 3(2), pages 1-21, June.
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    5. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    6. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    7. de Carvalho, Miguel & Martos, Gabriel, 2020. "Brexit: Tracking and disentangling the sentiment towards leaving the EU," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1128-1137.
    8. Juan B'ogalo & Pilar Poncela & Eva Senra, 2020. "Understanding fluctuations through Multivariate Circulant Singular Spectrum Analysis," Papers 2007.07561, arXiv.org, revised Aug 2023.
    9. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org.

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