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• W3135469478 abstract "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." @default.
• W3135469478 created "2021-03-15" @default.
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• W3135469478 date "2021-03-04" @default.
• W3135469478 modified "2023-10-18" @default.
• W3135469478 title "Trends and cycles in macro series: The case of US real GDP" @default.
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• W3135469478 doi "https://doi.org/10.1111/boer.12278" @default.
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