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Dating and forecasting turning points by Bayesian clustering with dynamic structure: A suggestion with an application to Austrian data

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Abstract

The information contained in a large panel data set is used to date historical turning points of the Austrian business cycle and to forecast future ones. We estimate groups of series with similar time series dynamics and link the groups with a dynamic structure. The dynamic structure identifies a group of leading and a group of coincident series. Robust results across data vintages are obtained when series specific information is incorporated in the design of the prior group probability distribution. The results are consistent with common expectations, in particular the group of leading series includes Austrian confidence indicators and survey data, German survey indicators, some trade data, and, interestingly, the Austrian and the German stock market indices. The forecast evaluation confirms that the Markov switching panel with dynamic structure performs well when compared to other specifications.

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Bibliographic Info

Paper provided by Oesterreichische Nationalbank (Austrian Central Bank) in its series Working Papers with number 144.

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Date of creation: 19 Jun 2008
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Handle: RePEc:onb:oenbwp:144

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Keywords: Bayesian clustering; parameter heterogeneity; latent dynamic structure; Markov switching; panel data; turning points.;

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Citations

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Cited by:
  1. Adrian Pagan & Don Harding, 2011. "Econometric Analysis and Prediction of Recurrent Events," CREATES Research Papers 2011-33, School of Economics and Management, University of Aarhus.
  2. Rubén Hernández-Murillo & Michael T. Owyang & Margarita Rubio, 2013. "Clustered housing cycles," Working Papers 2013-021, Federal Reserve Bank of St. Louis.
    • Rubén Hernández-Murillo & Michael T Owyang & Margarita Rubio, 2013. "Clustered Housing Cycles," Discussion Papers 2013/02, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  3. James D. Hamilton & Michael T. Owyang, 2011. "The Propagation of Regional Recessions," NBER Working Papers 16657, National Bureau of Economic Research, Inc.
  4. Neville Francis & Michael T. Owyang & Özge Savascin, 2012. "An endogenously clustered factor approach to international business cycles," Working Papers 2012-014, Federal Reserve Bank of St. Louis.
  5. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between eurozone and US booms and busts: A Bayesian panel Markov-switching VAR model," Working Paper 2013/20, Norges Bank.
  6. Kaufmann Sylvia, 2011. "K-state switching models with endogenous transition distributions," Working Papers 2011-13, Swiss National Bank.
  7. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between Eurozone and US Booms and Busts: A Bayesian Panel Markov-switching VAR Model," Tinbergen Institute Discussion Papers 13-142/III, Tinbergen Institute.

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