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On the Typical Spectral Shape of an Economic Variable

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  • Levy, Daniel
  • Dezhbakhsh, Hashem

Abstract

In a classic article, Granger (Econometrica 34, 1966) asserted that most economic time series measured in level have spectra that exhibit a smooth declining shape with considerable power at very low frequencies. There has been no systematic attempt to examine Granger's assertion with international data. Output level spectra are estimated for 58 countries, divided into developed, high-income developing, and low-income developing groups. The shapes of the estimated spectra are found to be strikingly similar to Granger's typical shape, particularly for the developed countries.

Suggested Citation

  • Levy, Daniel & Dezhbakhsh, Hashem, 2003. "On the Typical Spectral Shape of an Economic Variable," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10(7), pages 417-423.
    • Handle: RePEc:zbw:espost:206826
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    References listed on IDEAS

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    Cited by:

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    2. Crowley, Patrick M., 2010. "Long cycles in growth : explorations using new frequency domain techniques with US data," Research Discussion Papers 6/2010, Bank of Finland.
    3. Crowley, Patrick M., 2009. "How do you make a time series sing like a choir? : Using the Hilbert-Huang transform to extract embedded frequencies from economic or financial time series," Research Discussion Papers 32/2009, Bank of Finland.
    4. Crowley, Patrick M., 2010. "Long cycles in growth: explorations using new frequency domain techniques with US data," Bank of Finland Research Discussion Papers 6/2010, Bank of Finland.
    5. Callen, Michael & Imbs, Jean & Mauro, Paolo, 2015. "Pooling risk among countries," Journal of International Economics, Elsevier, vol. 96(1), pages 88-99.
    6. Benk, Szil rd & Gillman, Max & Kejak, Michal, 2008. "US Volatility Cycles of Output and Inflation, 1919-2004: A Money and Banking Approach to a Puzzle," Cardiff Economics Working Papers E2008/28, Cardiff University, Cardiff Business School, Economics Section.
    7. Crowley, Patrick M., 2009. "How do you make a time series sing like a choir? Using the Hilbert-Huang transform to extract embedded frequencies from economic or financial time series," Bank of Finland Research Discussion Papers 32/2009, Bank of Finland.
    8. Crowley, Patrick M. & Lee, Jim, 2005. "Decomposing the co-movement of the business cycle: a time-frequency analysis of growth cycles in the euro area," Bank of Finland Research Discussion Papers 12/2005, Bank of Finland.
    9. Levy, Daniel & Dezhbakhsh, Hashem, 2003. "International evidence on output fluctuation and shock persistence," Journal of Monetary Economics, Elsevier, vol. 50(7), pages 1499-1530, October.
    10. Crowley, Patrick M. & Lee, Jim, 2005. "Decomposing the co-movement of the business cycle : a time-frequency analysis of growth cycles in the euro area," Research Discussion Papers 12/2005, Bank of Finland.
    11. Kufenko, Vadim, 2016. "Spurious periodicities in cliometric series: Simultaneous testing," Violette Reihe: Schriftenreihe des Promotionsschwerpunkts "Globalisierung und Beschäftigung" 48/2016, University of Hohenheim, Carl von Ossietzky University Oldenburg, Evangelisches Studienwerk.
    12. Rania Jammazi & Chaker Aloui, 2014. "Cyclical components and dual long memory in the foreign exchange rate dynamics: the Tunisian case," Working Papers 2014-198, Department of Research, Ipag Business School.
    13. Crowley, Patrick M. & Maraun, Douglas & Mayes, David, 2006. "How hard is the euro area core? : an evaluation of growth cycles using wavelet analysis," Research Discussion Papers 18/2006, Bank of Finland.
    14. Carlos A. Medel, 2014. "The typical spectral shape of an economic variable: a visual guide," Applied Economics Letters, Taylor & Francis Journals, vol. 21(14), pages 1017-1024, September.
    15. Crowley, Patrick M. & Maraun, Douglas & Mayes, David, 2006. "How hard is the euro area core? An evaluation of growth cycles using wavelet analysis," Bank of Finland Research Discussion Papers 18/2006, Bank of Finland.
    16. David E. Giles & Chad N. Stroomer, 2004. "Identifying the Cycle of a Macroeconomic Time-Series Using Fuzzy Filtering," Econometrics Working Papers 0406, Department of Economics, University of Victoria.
    17. Ricco, Giovanni, 2015. "A new identification of fiscal shocks based on the information flow," Working Paper Series 1813, European Central Bank.
    18. Carlos Medel, 2014. "The Typical Spectral Shape of An Economic Variable: A Visual Guide with 100 Examples," Working Papers Central Bank of Chile 719, Central Bank of Chile.
    19. Rodrigo Barbone Gonzalez & Joaquim Lima & Leonardo Marinho, 2015. "Business and Financial Cycles: an estimation of cycles’ length focusing on Macroprudential Policy," Working Papers Series 385, Central Bank of Brazil, Research Department.
    20. Leon, Costas & Eeckels, Bruno, 2009. "A Dynamic Correlation Approach of the Swiss Tourism Income," MPRA Paper 15215, University Library of Munich, Germany.
    21. Patrick M. Crowley & Andrew Hughes Hallett, 2021. "The Evolution of US and UK Real GDP Components in the Time-Frequency Domain: A Continuous Wavelet Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 233-261, December.
    22. Ricco, Giovanni & Callegari, Giovanni & Cimadomo, Jacopo, 2016. "Signals from the government: Policy disagreement and the transmission of fiscal shocks," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 107-118.

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    Keywords

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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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