Abstract
The NIESR's monthly GDP series is an innovative feature; most GDP estimates are published at an annual, or quarterly frequency at best. For purposes of dating the business cycle the availability of this series is an asset, unexploited until this paper. The paper applies a version of the standard business (or ‘classical’) cycle dating algorithm to the data, after light smoothing to remove outliers. Three classical cycles are detected in the period between the early 1970s and 2002, with turning points which are close to (but usually precede) classical cycle dating which does not benefit from the availability of monthly GDP, and instead relies on a ‘coincident’ indicator methodology. In addition the turning points of a deviation cycle are identified.
Publisher
Cambridge University Press (CUP)
Subject
General Economics, Econometrics and Finance
Cited by
6 articles.
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