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Great moderation or “Will o’ the Wisp”? A time–frequency decomposition of GDP for the US and UK

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  • Crowley, Patrick M.
  • Hughes Hallett, Andrew

Abstract

In this paper the relationship between the growth of real GDP components at different cycle lengths is explored in the frequency domain using discrete wavelet analysis. This analysis is done for both the US and the UK using quarterly data, and the results reveal interesting differences between the two countries. One of the key findings is that the “great moderation” shows up only at certain frequencies, and not in all components of real GDP. A second result is that the great moderation appears to have shifted cyclical power from shorter and business cycles to long cycles, which has important implications for both policy formulation and the probability of less frequent but more severe economic crises. We use these results to explain why the incidence of the great moderation has been so ephemeral across GDP components, countries and time periods. This also explains why it has been so hard to detect periods of moderation (or otherwise) reliably in the aggregate data.

Suggested Citation

  • Crowley, Patrick M. & Hughes Hallett, Andrew, 2015. "Great moderation or “Will o’ the Wisp”? A time–frequency decomposition of GDP for the US and UK," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 82-97.
    • Handle: RePEc:eee:jmacro:v:44:y:2015:i:c:p:82-97
    DOI: 10.1016/j.jmacro.2014.12.006
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    References listed on IDEAS

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    Cited by:

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    3. Aguiar-Conraria, Luis & Martins, Manuel M.F. & Soares, Maria Joana, 2018. "Estimating the Taylor rule in the time-frequency domain," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 122-137.
    4. Power, Gabriel J. & Eaves, James & Turvey, Calum & Vedenov, Dmitry, 2017. "Catching the curl: Wavelet thresholding improves forward curve modelling," Economic Modelling, Elsevier, vol. 64(C), pages 312-321.
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    6. Crowley, Patrick M. & Hudgins, David, 2017. "Wavelet-based monetary and fiscal policy in the Euro area," Journal of Policy Modeling, Elsevier, vol. 39(2), pages 206-231.
    7. Rua, António, 2017. "A wavelet-based multivariate multiscale approach for forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 581-590.

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    More about this item

    Keywords

    Business cycles; Growth cycles; Economic growth; Time–frequency domain; Discrete wavelet analysis; Volatility;
    All these keywords.

    JEL classification:

    • E0 - Macroeconomics and Monetary Economics - - General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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