Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/245199 
Year of Publication: 
2019
Citation: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 7 [Issue:] 1 [Publisher:] Taylor & Francis [Place:] Abingdon [Year:] 2019 [Pages:] 1-10
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
We adopt an unobserved components time series model to track the business cycles in the G7 countries using the Industrial production index over the period from 1:1961 to 8:2017. The advantage of adopting the industrial production series frequency is that the business cycle can be investigated in terms of a higher frequency than once per quarter. The aim here is to extract the classical cycle by dating the peaks and troughs and investigating the characteristics of the business cycle through the unobserved component model, which has the capacity to model fat tails data using a driven parameter through the Kalman filter. We find that the industrial production index has medium-term cycles which have a few statistical properties in common. We show that the length and amplitude of the business cycles vary over time and across countries.
Subjects: 
unobserved component time series model
maximum likelihood estimation
classical cycle
industrial production index
medium-term cycles
JEL: 
C410
E100
E310
E370
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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