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Tracking the US Business Cycle With a Singular Spectrum Analysis

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  • Miguel de Carvalho
  • Paulo C. Rodrigues
  • António Rua

Abstract

The monitoring of economic developments is an exercise of considerable importance forpolicy makers, namely, central banks and fiscal authorities as well as for other economic agents such as financial intermediaries, firms and households. However, the assessment of the business cycle is not an easy endeavor as the cyclical component is not an observable variable. In this paper we resort to singular spectrum analysis in order to disentangle the US GDP into several underlying components of interest. The business cycle indicator yielded through this method is shown to bear a resemblance with band-pass filtered output. As the end-of-sample behavior is typically a thorny issue in business cycle assessment, a real-time estimation exercise is here conducted to assess the reliability of the several filters. The obtained results suggest that the business cycle indicator proposed herein possesses a better revision performance than other filters commonly applied in the literature.

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Paper provided by Banco de Portugal, Economics and Research Department in its series Working Papers with number w201009.

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Date of creation: 2010
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Handle: RePEc:ptu:wpaper:w201009

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  1. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, 05.
  2. Robert J. Hodrick & Edward Prescott, 1981. "Post-War U.S. Business Cycles: An Empirical Investigation," Discussion Papers 451, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  3. Athanasios Orphanides & Simon Van_Norden, 2000. "The Reliability of Output Gap Estimates in Real Time," Econometric Society World Congress 2000 Contributed Papers 0768, Econometric Society.
  4. Yogo, Motohiro, 2008. "Measuring business cycles: A wavelet analysis of economic time series," Economics Letters, Elsevier, vol. 100(2), pages 208-212, August.
  5. 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.
  6. Harvey, A.C. & Trimbur, T.M., 2001. "General Model-based Filters for Extracting Cycles and Trends in Economic Time Series," Cambridge Working Papers in Economics 0113, Faculty of Economics, University of Cambridge.
  7. James H. Stock & Mark W. Watson, 1998. "Business Cycle Fluctuations in U.S. Macroeconomic Time Series," NBER Working Papers 6528, National Bureau of Economic Research, Inc.
  8. Valle e Azevedo, Joao & Koopman, Siem Jan & Rua, Antonio, 2006. "Tracking the Business Cycle of the Euro Area: A Multivariate Model-Based Bandpass Filter," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 278-290, July.
  9. Hassani, Hossein & Heravi, Saeed & Zhigljavsky, Anatoly, 2009. "Forecasting European industrial production with singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 25(1), pages 103-118.
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