Cyclical Components in Economic Time Series: a Bayesian Approach
AbstractCyclical 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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Bibliographic InfoPaper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0302.
Date of creation: Jan 2003
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band pass filter; Gibbs sampler; Kalman filter; Markov chain Monte Carlo; state space; unobserved components;
Other versions of this item:
- Herman K. van Dijk & Andrew Harvey & Thomas Trimbur, 2004. "Cyclical components in economic time series: A Bayesian approach," Econometric Society 2004 Australasian Meetings 105, Econometric Society.
- 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
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
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- Gonzalo Llosa & Shirley Miller, 2004.
"Using Additional Information in Estimating the Output Gap in Peru: a Multivariate Unobserved Component Approach,"
Centro de Estudios Monetarios Latinoamericanos, vol. 0(1), pages 57-82, January-J.
- Gonzalo Llosa & Shirley Miller, 2005. "Using additional information in estimating the output gap in Peru: a multivariate unobserved component approach," Working Papers 2005-004, Banco Central de Reserva del Perú.
- 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., vol. 21(2), pages 191-212.
- Harm Bandholz & Gebhard Flaig & Johannes Mayr, 2005. "Wachstum und Konjunktur in OECD-Ländern: Eine langfristige Perspektive," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 58(04), pages 28-36, 02.
- Klaus Abberger & Gebhard Flaig & Wolfgang Nierhaus, 2007. "ifo Konjunkturumfragen und Konjunkturanalyse : ausgewählte methodische Aufsätze aus dem ifo Schnelldienst," ifo Forschungsberichte, Ifo Institute for Economic Research at the University of Munich, number 33, October.
- 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.
- Kleijn, R.H. & Dijk, H.K. van, 2003. "Bayes model averaging of cyclical decompositions in economic time series," Econometric Institute Report EI 2003-48, Erasmus University Rotterdam, Econometric Institute.
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