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

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  • Guglielmo Maria Caporale
  • Luis Alberiko Gil‐Alana

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.

Suggested Citation

  • Guglielmo Maria Caporale & Luis Alberiko Gil‐Alana, 2022. "Trends and cycles in macro series: The case of US real GDP," Bulletin of Economic Research, Wiley Blackwell, vol. 74(1), pages 123-134, January.
    • Handle: RePEc:bla:buecrs:v:74:y:2022:i:1:p:123-134
    DOI: 10.1111/boer.12278
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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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