Measuring business cycle features
AbstractSince the extensive work by Burns and Mitchell (1947), many economists have interpreted economic fluctuations in terms of business cycle phases. Given this, we argue that in addition to usual model selection criteria currently used in the profession, the adequacy of a univariate macroeconomic time series model should be based on its ability to replicate two most important business cycle features of the U.S. data--duration and amplitude. We propose a number of checks for whether univariate statistical models generate business cycle features observed in US GDP and find that many popular non-linear models for the log of real GDP are no better at replicating the duration and amplitude features of the data than a simple ARIMA(1,1,0).
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by Federal Reserve Bank of Kansas City in its series Research Working Paper with number 95-10.
Date of creation: 1995
Date of revision:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Hans-Martin Krolzig & Michael Clements, 2000.
"Business Cycle Asymmetries: Characterisation and Testing based on Markov-Switching Autoregressions,"
Economics Series Working Papers
2000-W32, University of Oxford, Department of Economics.
- Clements, Michael P & Krolzig, Hans-Martin, 2003. "Business Cycle Asymmetries: Characterization and Testing Based on Markov-Switching Autoregressions," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 196-211, January.
- Clements, M.P. & Krolzig, H-M., 1999. "Business Cycle Asymmetries: Characterisationand Testing Based on Markov-Switching Autoregression," The Warwick Economics Research Paper Series (TWERPS) 522, University of Warwick, Department of Economics.
- Krolzig, H.-M. & Toro, J., 2001.
"Classical And Modern Business Cycle Measurement: The European Case,"
Economics Series Working Papers
9960, University of Oxford, Department of Economics.
- Hans-Martin Krolzig & Juan Toro, 2004. "Classical and modern business cycle measurement: The European case," Spanish Economic Review, Springer, vol. 7(1), pages 1-21, January.
- Hans-Martin Krolzig & Juan Toro, 2002. "Classical and Modern Business Cycle Measurement: The European Case," Economic Working Papers at Centro de Estudios Andaluces E2002/20, Centro de Estudios Andaluces.
- Bertrand Candelon & Luis A. Gil-Alana, 2004.
"Fractional integration and business cycle features,"
Springer, vol. 29(2), pages 343-359, 05.
- Luis A. Gil-Alana & Bertrand Candelon, 2004. "Fractional Integration and Business Cycles Features," Faculty Working Papers 09/04, School of Economics and Business Administration, University of Navarra.
- Candelon, Bertrand & Gil-Alaña, Luis A., 2001. "Fractional integration and business cycle features," SFB 373 Discussion Papers 2001,46, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lu Dayrit).
If references are entirely missing, you can add them using this form.