Empirical Economics

, Volume 52, Issue 4, pp 1379–1408 | Cite as

Monthly US business cycle indicators: a new multivariate approach based on a band-pass filter



This article proposes a new multivariate method to construct business cycle indicators. The method is based on a decomposition into trend-cycle and irregular. To derive the cycle, a band-pass filter is applied to the estimated trend-cycle. The whole procedure is fully model based. Its performance is evaluated in relation to the approach by Creal et al. (J Appl Econom 25:695–719, 2010). Using the same set of monthly and quarterly US time series as in Creal et al. two monthly business cycle indicators are obtained for the US. They are represented by the cycles of real GDP and the industrial production index. Both indicators can reproduce previous recessions very well. Series contributing to the construction of both indicators are allowed to be leading, lagging, or coincident relative to the business cycle. Their behavior is assessed by means of spectral concepts after cycle estimation. The proposed method can serve as an attractive tool for policy making, in particular due to its good forecasting performance and quite simple setting without elaborate mechanisms that account for, e.g., volatility changes.


Business cycle Multivariate structural time series model Univariate band-pass filter Forecasts Phase angle 

JEL Classification

E32 E37 C18 C32 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.University of HohenheimStuttgartGermany
  2. 2.Ministry of Finance and Public AdministrationMadridSpain

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