Verfahren der konjunkturellen Wendepunktbestimmung unter Berücksichtigung der Echtzeit-Problematik
Forecasting business-cycle turning points under real-time conditions One of the greatest challenges in business cycle research is the timely and reliable identification of cyclical turning points.The data availability in real time constitutes a fundamental problem:First there is a publication lag of several months for some of the indicators concerning the real economy, and secondly those indicators are subject to substantial revisions even afterwards. The IMK undertook a systematic analysis of the business-cycle turning point detection problem in real time for Germany, applying and comparing four different econometric model classes. The employed methods recognize turning points two to four months ahead of official statistics in real time, for the evaluation sample of 2007 through 2010. A (nonlinear) dynamic probit model and a (linear) so-called subset VAR model seem to be especially well suited for this task. Based on our research results we conclude that it is advisable for the detection of turning points to combine many indicators.
|Date of creation:||2012|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +49 211 7778 234
Fax: +49 211 7778 4234
Web page: http://www.imk-boeckler.de
More information through EDIRC
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.:
- James H. Stock & Mark W. Watson, 1993.
"A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience,"
in: Business Cycles, Indicators and Forecasting, pages 95-156
National Bureau of Economic Research, Inc.
- James H. Stock & Mark W. Watson, 1992. "A Procedure for Predicting Recessions With Leading Indicators: Econometric Issues and Recent Experience," NBER Working Papers 4014, National Bureau of Economic Research, Inc.
- Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010.
2010-04, Banco de México.
- Tom Stark & Dean Croushore, 2001.
"Forecasting with a real-time data set for macroeconomists,"
01-10, Federal Reserve Bank of Philadelphia.
- Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
- Tom Stark and Dean Croushore, 2001. "Forecasting with a Real-Time Data Set for Macroeconomists," Computing in Economics and Finance 2001 258, Society for Computational Economics.
- Jonathan H. Wright, 2006. "The yield curve and predicting recessions," Finance and Economics Discussion Series 2006-07, Board of Governors of the Federal Reserve System (U.S.).
- Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
- Stock, J.H. & Watson, M.W., 1989.
"New Indexes Of Coincident And Leading Economic Indicators,"
178d, Harvard - J.F. Kennedy School of Government.
- James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
- Stark, Tom & Croushore, Dean, 2002. "Reply to the comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 563-567, December.
When requesting a correction, please mention this item's handle: RePEc:imk:studie:27-2012. 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: (Sabine Nemitz)
If references are entirely missing, you can add them using this form.