Testing the Power of Leading Indicators to Predict Business Cycle Phase Changes
In the business cycle literature researchers often want to determine the extent to which models of the business cycle reproduce broad characteristics of the real world business cycle they purport to represent. Of considerable interest is whether a model’s implied cycle chronology is consistent with the actual business cycle chronology. In the US, a very widely accepted business cycle chronology is that compiled by the National Bureau of Economic research (NBER) and the vast majority of US business cycle scholars have, for many years, proceeded to test their models for their consistency with the NBER dates. In doing this, one of the most prevalent metrics in use since its introduction into the business cycle literature by Diebold and Rudebusch (1989) is the so-called quadratic probability score, or QPS. However, an important limitation to the use of the QPS statistic is that its sampling distribution is unknown so that rigorous statistical inference is not feasible. We suggest circumventing this by bootstrapping the distribution. This analysis yields some interesting insights into the relationship between statistical measures of goodness of fit of a model and the ability of the model to predict some underlying set of regimes of interest. Furthermore, in modeling the business cycle, a popular approach in recent years has been to use some variant of the so-called Markov regime switching (MRS) model first introduced by Hamilton (1989) and we therefore use MRS models as the framework for the paper. Of course, the approach could be applied to any US business cycle model.
|Date of creation:||15 Jun 2005|
|Contact details of provider:|| Postal: GPO Box 2434, BRISBANE QLD 4001|
Web page: http://www.bus.qut.edu.au/faculty/economics/
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.:
- Allan Layton & Daniel Smith, 2000. "A further note on the three phases of the US business cycle," Applied Economics, Taylor & Francis Journals, vol. 32(9), pages 1133-1143.
- 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.
- Francis X. Diebold & Glenn D. Rudebusch, 1987. "Scoring the leading indicators," Special Studies Papers 206, Board of Governors of the Federal Reserve System (U.S.).
- Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 299-308, July.
- Andrew J. Filardo, 1993. "Business cycle phases and their transitional dynamics," Research Working Paper 93-14, Federal Reserve Bank of Kansas City.
- Tom Doan, "undated". "RATS programs to replicate Filardo JBES 1994 paper with time-varying Markov switching," Statistical Software Components RTZ00059, Boston College Department of Economics.
- Filardo, Andrew J. & Gordon, Stephen F., 1998. "Business cycle durations," Journal of Econometrics, Elsevier, vol. 85(1), pages 99-123, July.
- Gordon, S.F. & Filardo, A.J., 1993. "Business Cycle Durations," Papers 9328, Laval - Recherche en Politique Economique.
- Andrew J. Filardo & Stephen F. Gordon, 1993. "Business cycle durations," Research Working Paper 93-11, Federal Reserve Bank of Kansas City.
When requesting a correction, please mention this item's handle: RePEc:qut:dpaper:200. 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: (Angela Fletcher)
If references are entirely missing, you can add them using this form.