Business cycle asymmetry and duration dependence: An international perspective
Terence Mills
Journal of Applied Statistics, 2001, vol. 28, issue 6, 713-724
Abstract:
The business cycle behaviour of macroeconomic variables has long been of interest to economists, and attention has recently focused on two aspects of this behaviour - the 'stylized facts' of cyclical asymmetry and duration dependence. Cyclical asymmetry is where the economy behaves differently over the expansion and recession phases of the business cycle. Duration dependence, on the other hand, concerns the question of whether, for example, the probability of a cyclical expansion is dependent on how long the expansion has been running, or whether business cycle lengths tend to cluster around a particular duration. Using an international data set containing annual output per capita for 22 countries, we focus attention on non-parametric techniques for extracting cyclical components and for modelling and testing asymmetry and duration dependence. Once outliers, primarily associated with wars, are omitted, there is little international evidence of asymmetry. There is considerably more evidence of duration dependence, which is detected in the majority of countries using a variety of non-parametric tests. There is thus widespread evidence against the constant hazard hypothesis that cyclical patterns occur simply by chance. Business cycle durations do appear to cluster around certain values, with the average duration being about 3.6 years.
Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/02664760120059246 (text/html)
Access to full text is restricted to subscribers.
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:taf:japsta:v:28:y:2001:i:6:p:713-724
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20
DOI: 10.1080/02664760120059246
Access Statistics for this article
Journal of Applied Statistics is currently edited by Robert Aykroyd
More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().