Long Cycles in Growth: Explorations Using New Frequency Domain Techniques with US Data

52 Pages Posted: 18 Mar 2010

See all articles by Patrick M. Crowley

Patrick M. Crowley

Texas A&M University - Corpus Christi; Bank of Finland/Suomen Pankki

Date Written: February 21, 2010


In his celebrated 1966 Econometrica article, Granger first hypothesized that there is a ‘typical’ spectral shape for an economic variable. This ‘typical’ shape implies decreasing levels of energy as frequency increases, which in turn implies an extremely long cycle in economic fluctuations and particulary in growth. Spectral analysis is however based on certain assumptions particulary in that render these basic frequency domain techniques inappropriate for analysing non-stationary economic data. In this paper three recent frequency domain methods for extracting cycles from non-stationary data are used with US real GNP data to analyse fluctuations in economic growth. The findings, among others, are that these more recent frequency domain techniques do not provide evidence to support the ‘typical’ spectral shape and nor an extremely long growth cycle á la Granger.

Keywords: business cycles, growth cycles, frequency domain, spectral analysis, long cycles, Granger, wavelet analysis, Hilbert-Huang Transform (HHT), empirical mode decomposition (EMD), non-stationarity

JEL Classification: C13, C14, O47

Suggested Citation

Crowley, Patrick M., Long Cycles in Growth: Explorations Using New Frequency Domain Techniques with US Data (February 21, 2010). Bank of Finland Research Discussion Paper No. 6/2010. Available at SSRN: https://ssrn.com/abstract=1573641 or http://dx.doi.org/10.2139/ssrn.1573641

Patrick M. Crowley (Contact Author)

Texas A&M University - Corpus Christi ( email )

6300 Ocean Drive, Unit #5808
Corpus Christi, TX 78412
United States

HOME PAGE: http://patrickmcrowley.com

Bank of Finland/Suomen Pankki ( email )

P.O. Box 160
FIN-00101 Helsinki

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