Forecasting the Turns of German Business Cycle: Dynamic Bi-factor Model with Markov Switching
In this paper a dynamic bi-factor model with Markov switching is proposed to measure and predict turning points of the German business cycle. It estimates simultaneously the composite leading indicator (CLI) and composite coincident indicator (CCI) together with corresponding probabilities of being in recession. According to the bi-factor model, on average, CLI leads CCI by 3 months at both peaks and troughs. The model-derived recession probabilities of CCI and those of CLI with a lag of 2-3 months capture the turning points of the ECRI's and OECD's reference cycle much better than the dynamic single-factor model with Markov switching.
|Date of creation:||2005|
|Contact details of provider:|| Postal: Mohrenstraße 58, D-10117 Berlin|
Web page: http://www.diw.de/en
More information through EDIRC
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.:
- Fritsche Ulrich & Kuzin Vladimir, 2005. "Prediction of Business Cycle Turning Points in Germany / Prognose konjunktureller Wendepunkte in Deutschland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(1), pages 22-43, February.
- Harm Bandholz, 2005. "New Composite Leading Indicators for Hungary and Poland," Ifo Working Paper Series Ifo Working Paper No. 3, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
- Marcelle Chauvet & Jeremy M. Piger, 2003.
"Identifying business cycle turning points in real time,"
Federal Reserve Bank of St. Louis, issue Mar, pages 47-61.
- Marcelle Chauvet & Jeremy M. Piger, 2002. "Identifying business cycle turning points in real time," FRB Atlanta Working Paper 2002-27, Federal Reserve Bank of Atlanta.
- Chauvet, Marcelle, 2002. "The Brazilian Business and Growth Cycles," Revista Brasileira de Economia, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 56(1), January.
- Diebold & Rudebusch, "undated".
"Measuring Business Cycle: A Modern Perspective,"
_061, University of Pennsylvania.
- 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 357-384, March.
- Sylvia Kaufmann, 2000. "Measuring business cycles with a dynamic Markov switching factor model: an assessment using Bayesian simulation methods," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 39-65.
- Konstantin Kholodilin, 2001. "Latent Leading and Coincident Factors Model with Markov-Switching Dynamics," Economics Bulletin, AccessEcon, vol. 3(7), pages 1-13.
- Diebold, Francis X & Mariano, Roberto S, 1995.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 13(3), pages 253-263, July.
- Tom Doan, "undated". "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Kim, C-J., 1991.
"Dynamic Linear Models with Markov-Switching,"
91-8, York (Canada) - Department of Economics.
- 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.
- Konstantin, KHOLODILIN, 2002.
"Two Alternative Approaches to Modelling the Nonlinear Dynamics of the Composite Economic Indicator,"
Discussion Papers (IRES - Institut de Recherches Economiques et Sociales)
2002027, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
- Konstantin A. Kholodilin, 2002. "Two Alternative Approaches to Modelling the Nonlinear Dynamics of the Composite Economic Indicator," Economics Bulletin, AccessEcon, vol. 3(26), pages 1-18.
- Ulrich Fritsche & Sabine Stephan, 2000.
"Leading Indicators of German Business Cycles: An Assessment of Properties,"
- Ulrich Fritsche & Sabine Stephan, 2000. "Leading Indicators of German Business Cycles: An Assessment of Properties," Discussion Papers of DIW Berlin 207, DIW Berlin, German Institute for Economic Research.
- James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
- repec:ebl:ecbull:v:3:y:2002:i:26:p:1-18 is not listed on IDEAS
- Diebold, Francis X & Rudebusch, Glenn D, 1989.
"Scoring the Leading Indicators,"
The Journal of Business,
University of Chicago Press, vol. 62(3), pages 369-391, July.
- Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
- Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
- Kholodilin, Konstantin A. & Yao, Vincent W., 2005. "Measuring and predicting turning points using a dynamic bi-factor model," International Journal of Forecasting, Elsevier, vol. 21(3), pages 525-537.
When requesting a correction, please mention this item's handle: RePEc:diw:diwwpp:dp494. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Bibliothek)
If references are entirely missing, you can add them using this form.