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Cyclical Components in Economic Time Series: a Bayesian Approach

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  • Harvey, A.
  • TTrimbur, T.
  • van Dijk, H.

Abstract

Cyclical components in economic time series are analysed in a Bayesian framework, thereby allowing prior notions about periodicity to be used. The method is based on a general class of unobserved component models that allow relatively smooth cycles to be extracted. Posterior densities of parameters and smoothed cycles are obtained using Markov chain Monte Carlo methods. An application to estimating business cycles in macroeconomic series illustrates the viability of the procedure for both univariate and bivariate models.

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  • Harvey, A. & TTrimbur, T. & van Dijk, H., 2003. "Cyclical Components in Economic Time Series: a Bayesian Approach," Cambridge Working Papers in Economics 0302, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:0302 Note: EM
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    Cited by:

    1. Richard Kleijn & Herman K. van Dijk, 2006. "Bayes model averaging of cyclical decompositions in economic time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., pages 191-212.
    2. Klaus Abberger & Gebhard Flaig & Wolfgang Nierhaus, 2007. "ifo Konjunkturumfragen und Konjunkturanalyse : ausgewählte methodische Aufsätze aus dem ifo Schnelldienst," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 33, October.
    3. Martha López P., 2004. "Efficient Policy Rule for Inflation Targeting in Colombia," Money Affairs, Centro de Estudios Monetarios Latinoamericanos, vol. 0(1), pages 1-24, January-J.
    4. Gonzalo Llosa & Shirley Miller, 2004. "Using Additional Information in Estimating the Output Gap in Peru: a Multivariate Unobserved Component Approach," Money Affairs, Centro de Estudios Monetarios Latinoamericanos, vol. 0(1), pages 57-82, January-J.
    5. Wayne Robinson, 2004. "Real Shocks, Credibility & Stabilization Policy in a Small Open Economy," Money Affairs, Centro de Estudios Monetarios Latinoamericanos, vol. 0(1), pages 39-55, January-J.
    6. Gonzalo Llosa/Shirley Miller, 2004. "Using additional information in estimating output gap in Peru: a multivariate unobserved component approach," Econometric Society 2004 Latin American Meetings 243, Econometric Society.
    7. Adriana Arreaza & Enid Blanco & Miguel Dorta, 2004. "A Small Scale Macroeconomic Model for Venezuela," Money Affairs, Centro de Estudios Monetarios Latinoamericanos, vol. 0(1), pages 25-38, January-J.
    8. Harm Bandholz & Gebhard Flaig & Johannes Mayr, 2005. "Wachstum und Konjunktur in OECD-Ländern: Eine langfristige Perspektive," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(04), pages 28-36, February.

    More about this item

    Keywords

    band pass filter; Gibbs sampler; Kalman filter; Markov chain Monte Carlo; state space; unobserved components;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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