Cyclical components in economic time series

Andrew C. Harvey, T.M. Trimbur and Herman K. van Dijk

No 293, Econometric Institute Report from Erasmus University Rotterdam, Econometric Institute

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.

Keywords: Band; pass; filter; Gibbs; sampler; Kalman; filter; Markov; chain; Monte; Carlo; State; space (search for similar items in EconPapers)
JEL-codes: C11 C32 E32 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2002
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Working Paper: Cyclical components in economic time series (2002)
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Persistent link: http://EconPapers.repec.org/RePEc:dgr:eureir:2002293

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