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Measuring business cycles: A wavelet analysis of economic time series

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  • Yogo, Motohiro

Abstract

Multiresolution wavelet analysis is a natural way to decompose an economic time series into trend, cycle, and noise. The method is illustrated with GDP data. The business-cycle component of the wavelet-filtered series closely resembles the series filtered by the approximate bandpass filter.

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Bibliographic Info

Article provided by Elsevier in its journal Economics Letters.

Volume (Year): 100 (2008)
Issue (Month): 2 (August)
Pages: 208-212

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Handle: RePEc:eee:ecolet:v:100:y:2008:i:2:p:208-212

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Web page: http://www.elsevier.com/locate/ecolet

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References

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  1. Marianne Baxter & Robert G. King, 1995. "Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series," NBER Working Papers 5022, National Bureau of Economic Research, Inc.
  2. Margaret M. McConnell & Gabriel Perez Quiros, 1998. "Output fluctuations in the United States: what has changed since the early 1980s?," Staff Reports 41, Federal Reserve Bank of New York.
  3. James H. Stock & Mark W. Watson, 2002. "Has the Business Cycle Changed and Why?," NBER Working Papers 9127, National Bureau of Economic Research, Inc.
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Citations

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Cited by:
  1. Miguel de Carvalho & Paulo C. Rodrigues & António Rua, 2010. "Tracking the US Business Cycle With a Singular Spectrum Analysis," Working Papers w201009, Banco de Portugal, Economics and Research Department.
  2. Kožić, Ivan & Sever, Ivan, 2014. "Measuring business cycles: Empirical Mode Decomposition of economic time series," Economics Letters, Elsevier, vol. 123(3), pages 287-290.
  3. Michis, Antonis A., 2014. "Time scale evaluation of economic forecasts," Economics Letters, Elsevier, vol. 123(3), pages 279-281.
  4. Benhmad, François, 2013. "Dynamic cyclical comovements between oil prices and US GDP: A wavelet perspective," Energy Policy, Elsevier, vol. 57(C), pages 141-151.
  5. Joanna Bruzda, 2011. "Business cycle synchronization according to wavelets – the case of Poland and the euro zone member countries," Bank i Kredyt, National Bank of Poland, Economic Institute, vol. 42(3), pages 5-32.
  6. Reboredo, Juan C. & Rivera-Castro, Miguel A., 2014. "Wavelet-based evidence of the impact of oil prices on stock returns," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 145-176.
  7. António Rua & Luís Catela Nunes, 2012. "A wavelet-based assessment of market risk: The emerging markets case," Working Papers w201203, Banco de Portugal, Economics and Research Department.
  8. Christophe Boucher & Bertrand Maillet, 2011. "Une analyse temps-fréquences des cycles financiers," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00565229, HAL.
  9. António Rua, 2011. "A wavelet approach for factor‐augmented forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(7), pages 666-678, November.
  10. António Rua, 2010. "Measuring comovement in the time-frequency space," Working Papers w201001, Banco de Portugal, Economics and Research Department.
  11. Gazi Salah Uddin & Aviral Kumar Tiwari, 2013. "Measuring co-movement of oil price and exchange rate differential in Bangladesh," Economics Bulletin, AccessEcon, vol. 33(3), pages 1922-1930.
  12. Chevallier, Julien, 2011. "Wavelet packet transforms analysis applied to carbon prices," Economics Papers from University Paris Dauphine 123456789/6515, Paris Dauphine University.
  13. Caraiani, Petre, 2012. "Money and output: New evidence based on wavelet coherence," Economics Letters, Elsevier, vol. 116(3), pages 547-550.
  14. Antonis A Michis, 2011. "Denoised least squars forecasting of GDP changes using indexes of consumer and business sentiment," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 383-392 Bank for International Settlements.
  15. Cifter, Atilla & Yilmazer, Sait & Cifter, Elif, 2009. "Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey," Economic Modelling, Elsevier, vol. 26(6), pages 1382-1388, November.

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