EconPapers    
Economics at your fingertips  
 

Using Long-, Medium-, and Short-Term Trends to Forecast Turning Points in the Business Cycle: Some International Evidence

García-Ferrer Antonio () and Queralt Ricardo A. ()
Additional contact information
García-Ferrer Antonio: Universidad Autónoma de Madrid, Universidad Autónoma de Madrid, ricardo.queralt@uam.es
Queralt Ricardo A.: Universidad Autónoma de Madrid, Universidad Autónoma de Madrid, ricardo.queralt@uam.es

Studies in Nonlinear Dynamics & Econometrics, 1998, vol. 3, issue 2, 29

Abstract: This paper provides rules for anticipating business-cycle recessions and recoveries for countries showing asymmetric cycle durations. Based on a Schumpeterian framework, we analyze business cycles as sums of short-, medium-, and long-term cycles defined for a particular class of unobserved component models. By associating the trend with the low frequencies of the pseudo-spectrum in the frequency domain, manipulation of the spectral bandwidth allows us to define subjective length trends with specific properties. In this paper, we show how these properties can be exploited to anticipate business-cycle turning points, not only historically, but also in a true ex-ante forecasting exercise. This procedure is applied to U.S. post-World War II GNP quarterly data, as well as to another set of European countries.

Keywords: unobserved components models; business cycles; turning-point forecast (search for similar items in EconPapers)
Date: 1998
References: Add references at CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://doi.org/10.2202/1558-3708.1042 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:sndecm:v:3:y:1998:i:2:n:2

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/snde/html

DOI: 10.2202/1558-3708.1042

Access Statistics for this article

Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach

More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().

 
Page updated 2025-03-19
Handle: RePEc:bpj:sndecm:v:3:y:1998:i:2:n:2