This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

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

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Sylvia Kaufmann (Oesterreichische Nationalbank, Economic Studies Division, P.O. Box 61, A-1010 Vienna,)

Additional information is available for the following registered author(s):

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.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.oenb.at/de/img/wp144_tcm14-88579.pdf
File Format: application/pdf
File Function:
Download Restriction: no

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

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 49 pages
Date of creation: 19 Jun 2008
Date of revision:
Handle: RePEc:onb:oenbwp:144

Contact details of provider:
Postal: P.O. Box 61, A-1011 Vienna, Austria
Phone: +43/1/404 20 7205
Fax: +43/1/404 20 7299
Email:
Web page: http://www.oenb.at/
More information through EDIRC

Order Information:
Postal: Oesterreichische Nationalbank, Economic Studies Division, c/o Beate Hofbauer-Berlakovich, POB 61, A-1011 Vienna, Austria
Email:

For technical questions regarding this item, or to correct its listing, contact: (Markus Knell and Helmut Stix).

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

Find related papers by JEL classification:
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

This paper has been announced in the following NEP Reports:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Canova, Fabio & Ciccarelli, Matteo, 2004. "Forecasting and turning point predictions in a Bayesian panel VAR model," Journal of Econometrics, Elsevier, vol. 120(2), pages 327-359, June. [Downloadable!] (restricted)
    Other versions:
  2. Phillips, Kerk L., 1991. "A two-country model of stochastic output with changes in regime," Journal of International Economics, Elsevier, vol. 31(1-2), pages 121-142, August. [Downloadable!] (restricted)
  3. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May. [Downloadable!] (restricted)
  4. 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. [Downloadable!]
  5. Massimiliano Marcellino, 2005. "Leading Indicators: What Have We Learned?," Working Papers 286, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University. [Downloadable!]
    Other versions:
  6. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November. [Downloadable!] (restricted)
  7. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, vol. 137(1), pages 134-161, March. [Downloadable!] (restricted)
  8. 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. [Downloadable!] (restricted)
    Other versions:
  9. Hoogstrate, Andre J & Palm, Franz C & Pfann, Gerard A, 2000. "Pooling in Dynamic Panel-Data Models: An Application to Forecasting GDP Growth Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 274-83, July.
  10. Filardo, Andrew J. & Gordon, Stephen F., 1998. "Business cycle durations," Journal of Econometrics, Elsevier, vol. 85(1), pages 99-123, July. [Downloadable!] (restricted)
    Other versions:
  11. Paap, R. & Segers, R. & Dijk, D.J.C. van, 2007. "Do leading indicators lead peaks more than troughs?," Econometric Institute Report EI 2007-08 Revision_Date:, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
  12. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March. [Downloadable!] (restricted)
  13. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, vol. 111(471), pages C62-85, May. [Downloadable!] (restricted)
  14. Giancarlo Bruno & Claudio Lupi, 2004. "Forecasting industrial production and the early detection of turning points," Empirical Economics, Springer, vol. 29(3), pages 647-671, 09. [Downloadable!] (restricted)
    Other versions:
  15. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November. [Downloadable!] (restricted)
    Other versions:
  16. Dick van Dijk & Dennis Fok & Philip Hans Franses, 2005. "A multi-level panel STAR model for US manufacturing sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(6), pages 811-827. [Downloadable!]
  17. Fruhwirth-Schnatter, Sylvia & Kaufmann, Sylvia, 2008. "Model-Based Clustering of Multiple Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 78-89, January. [Downloadable!] (restricted)
    Other versions:
Full references

Statistics
Access and download statistics

Did you know? IDEAS also covers the most complete directory of Economics departments and institutes, EDIRC.

This page was last updated on 2009-11-19.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.