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Bayes estimates of the cyclical component in twentieth centruy US gross domestic product

Author

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  • Harvey, A.C.
  • Trimbur, T.M.
  • van Dijk, H.K.

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 encompasses a range of dynamics in the stochastic cycle. This allows for instance relatively smooth cycles to be extracted from time series. Posterior densities of parameters and estimated components are obtained using Markov chain Monte Carlo methods, which we develop for both univariate and multivariate models. Features such as time-varying amplitude may be studied by examining different functions of the posterior draws for the cyclical component and parameters. The empirical application illustrates the method for annual US real GDP over the last 130 years.

Suggested Citation

  • Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2004. "Bayes estimates of the cyclical component in twentieth centruy US gross domestic product," Econometric Institute Research Papers EI 2004-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1798
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    References listed on IDEAS

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    11. Gomez, Victor, 2001. "The Use of Butterworth Filters for Trend and Cycle Estimation in Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 365-373, July.
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    Cited by:

    1. Ferroni Filippo, 2011. "Trend Agnostic One-Step Estimation of DSGE Models," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-36, July.
    2. Harvey, Andrew C. & Trimbur, Thomas M. & Van Dijk, Herman K., 2007. "Trends and cycles in economic time series: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 618-649, October.
    3. de Pooter, M.D. & Ravazzolo, F. & Segers, R. & van Dijk, H.K., 2008. "Bayesian near-boundary analysis in basic macroeconomic time series models," Econometric Institute Research Papers EI 2008-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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    More about this item

    Keywords

    Gibbs sampler; Markov chain Monte Carlo; band pass filter; business cycles; unobserved components;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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