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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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  • Sylvia Kaufmann

    (Oesterreichische Nationalbank, Vienna, Austria, and University of Basel, Switzerland)

Abstract

The information contained in a large panel dataset is used to date historical turning points 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 forecast evaluation confirms that the Markov switching panel with dynamic structure performs well when compared to other specifications. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/jae.1076
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File URL: http://qed.econ.queensu.ca:80/jae/2010-v25.2/
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 25 (2010)
Issue (Month): 2 ()
Pages: 309-344

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Handle: RePEc:jae:japmet:v:25:y:2010:i:2:p:309-344
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Find related papers by JEL classification:
  • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
  • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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  1. Chauvet, Marcelle & Piger, Jeremy, 2008. "A Comparison of the Real-Time Performance of Business Cycle Dating Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 42-49, January.
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  10. Sylvia Kaufmann & Sylvia Frühwirth-Schnatter, 2006. "How do changes in monetary policy affect bank lending? An analysis of Austrian bank data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 275-305.
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Cited by:

  1. Roberto Casarin & Komla Mawulom Agudze & Monica Billio & Eric Girardin, 2014. "Growth-cycle phases in China’s provinces: A panel Markov-switching approach," Working Papers 2014:19, Department of Economics, University of Venice "Ca' Foscari".
  2. 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.
  3. 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 Papers 2013:17, Department of Economics, University of Venice "Ca' Foscari".
  4. James D. Hamilton & Michael T. Owyang, 2011. "The Propagation of Regional Recessions," NBER Working Papers 16657, National Bureau of Economic Research, Inc.
  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. Sylvia Kaufmann, 2011. "K-state switching models with endogenous transition distributions," Working Papers 2011-13, Swiss National Bank.
  7. Christopher A. Sims & Daniel F. Waggoner & Tao Zha, 2006. "Methods for inference in large multiple-equation Markov-switching models," Working Paper 2006-22, Federal Reserve Bank of Atlanta.
  8. 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.
  9. Sylvia Kaufmann, 2014. "K-state switching models with time-varying transition distributions – Does credit growth signal stronger effects of variables on inflation?," Working Papers 14.04, Swiss National Bank, Study Center Gerzensee.
  10. 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).
  11. repec:dgr:uvatin:20130142 is not listed on IDEAS

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