IDEAS home Printed from https://ideas.repec.org/h/spr/dymchp/978-3-319-07061-2_3.html

The Great Moderation Under the Microscope: Decomposition of Macroeconomic Cycles in US and UK Aggregate Demand

In: Wavelet Applications in Economics and Finance

Author

Listed:
  • Patrick M. Crowley

    (Texas A&M University)

  • Andrew Hughes Hallett

    (George Mason University)

Abstract

In this paper the relationship between the growth of real GDP components is explored in the frequency domain using both static and dynamic wavelet analysis. This analysis is carried out separately for both the US and the UK using quarterly data, and the results are found to be substantially different in the two countries. One of the key findings in this research is that the “great moderation” shows up only at certain frequencies, and not in all components of real GDP. We use these results to explain why the incidence of the great moderation has been so patchy 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. We argue it cannot be done without breaking the GDP components down into their frequency components across time and these results show why: the predictions of traditional real business cycle theory often appear not to be upheld in the data.

Suggested Citation

  • Patrick M. Crowley & Andrew Hughes Hallett, 2014. "The Great Moderation Under the Microscope: Decomposition of Macroeconomic Cycles in US and UK Aggregate Demand," Dynamic Modeling and Econometrics in Economics and Finance, in: Marco Gallegati & Willi Semmler (ed.), Wavelet Applications in Economics and Finance, edition 127, pages 47-71, Springer.
    • Handle: RePEc:spr:dymchp:978-3-319-07061-2_3
    DOI: 10.1007/978-3-319-07061-2_3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Crowley, Patrick M. & Hudgins, David, 2015. "Euro area monetary and fiscal policy tracking design in the time-frequency domain," Research Discussion Papers 12/2015, Bank of Finland.
    2. Crowley, Patrick M. & Hudgins, David, 2016. "Analysis of the balance between U.S. monetary and fiscal policy using simulated wavelet-based optimal tracking control," Bank of Finland Research Discussion Papers 21/2016, Bank of Finland.
    3. Patrick M. Crowley & David Hudgins, 2018. "What is the right balance between US monetary and fiscal policy? Explorations using simulated wavelet-based optimal tracking control," Empirical Economics, Springer, vol. 55(4), pages 1537-1568, December.
    4. Crowley, Patrick M. & Hudgins, David, 2016. "Analysis of the balance between U.S. monetary and fiscal policy using simulated wavelet-based optimal tracking control," Research Discussion Papers 21/2016, Bank of Finland.
    5. Wen-Yi Chen & Yai-Wun Liang & Yu-Hui Lin, 2018. "Does Health Spending Crowd out Defense in the United States? Evidence from Wavelet Multiresolution Analysis," Defence and Peace Economics, Taylor & Francis Journals, vol. 29(7), pages 780-793, November.
    6. 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.
    7. 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.
    8. Crowley, Patrick M. & Hudgins, David, 2015. "Fiscal policy tracking design in the time–frequency domain using wavelet analysis," Economic Modelling, Elsevier, vol. 51(C), pages 502-514.
    9. Vassilios Babalos & Guglielmo Maria Caporale & Nicola Spagnolo, 2021. "Equity fund flows and stock market returns in the USA before and after the global financial crisis: a VAR-GARCH-in-mean analysis," Empirical Economics, Springer, vol. 60(2), pages 539-555, February.
    10. repec:bof:bofrdp:urn:nbn:fi:bof-201508131350 is not listed on IDEAS
    11. Fousekis, Panos & Grigoriadis, Vasilis, 2016. "Spatial price dependence by time scale: Empirical evidence from the international butter markets," Economic Modelling, Elsevier, vol. 54(C), pages 195-204.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:dymchp:978-3-319-07061-2_3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.