Trends and cycles in macro series: The case of US real GDP

Guglielmo Maria Caporale and Luis Alberiko Gil‐Alana
Authors registered in the RePEc Author Service: Luis Alberiko Gil-Alana

Bulletin of Economic Research, 2022, vol. 74, issue 1, 123-134

Abstract: This paper proposes a new modeling framework capturing both the long‐run and the cyclical components of a time series. As an illustration, we apply it to four US macro series, namely, annual and quarterly real gross domestic product (GDP) and GDP per capita. The results indicate that the behavior of US GDP can be captured accurately by a model incorporating both stochastic trends and stochastic cycles that allows for some degree of persistence in the data. Both appear to be mean reverting, although the stochastic trend is nonstationary, while the cyclical component is stationary, with cycles repeating themselves every 6–10 years.

Date: 2022
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https://doi.org/10.1111/boer.12278

Related works:
Working Paper: Trends and Cycles in Macro Series: The Case of US Real GDP (2017)
Working Paper: Trends and Cycles in Macro Series: The Case of US Real GDP (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:bla:buecrs:v:74:y:2022:i:1:p:123-134

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