Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-22T18:57:48.506Z Has data issue: false hasContentIssue false
  • English
  • Français

Dating the Business Cycle in Britain

Published online by Cambridge University Press:  26 March 2020

Michael Artis
Michael Artis*
Affiliation:
EUI, Florence, University of Manchester and CEPR
Get access Rights & Permissions [Opens in a new window]

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.

Type
Articles
Information
National Institute Economic Review , Volume 182 , October 2002 , pp. 90 - 95
Copyright
Copyright © 2002 National Institute of Economic and Social Research

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

∗

The author is grateful to Ekaterina Vostroknoutova for research assistance and to Tommaso Proietti for his BB(M) progammes.

References

Artis, M.J., Kontomelis, Z, and Osborn, D. (1997), ‘Business cycles for G7 and European countries, Journal of Business, 70, pp. 249–279.CrossRefGoogle Scholar
Artis, M.J., Marcellino, M. and Proietti, T. (2002), ‘Dating the Euro Area business cycle’, mimeo, EUI, Florence, September.Google Scholar
Artis, M.J., and Toro, J. (2000), ‘Testing for common patterns in European business cycle chronologies’, Greek Economic Review, 20, Autumn, pp. 77–92.Google Scholar
Baxter, M. and King, R.G. (1999), ‘Measuring business cycles: approximate band-pass filters for economic time series’, Review of Economics and Statistics, 81, pp. 575–593.CrossRefGoogle Scholar
Bry, G. and Boschan, C. (1971), ‘Cyclical aspects of time series: selected procedures and computer programs’, National Bureau of Economic Research, Technical Paper No 20.Google Scholar
Canova, F. (1998), ‘De-trending and business cycle facts’, Journal of Monetary Economics, 41, pp. 475–512.CrossRefGoogle Scholar
Chow, G.C. and Lin, A.L. (1971), ‘Best linear unbiased interpolation, distribution and extrapolation of time series by related series’, Review of Economics and Statistics, 53, pp. 372–375.CrossRefGoogle Scholar
Hodrick, R.J. and Prescott, E.C. (1997), ‘Post-war US business cycles: an empirical investigation’, Journal of Money, Credit and Banking, 29, pp. 1–16.CrossRefGoogle Scholar
Kaiser, R. and Maravall, A. (1999), Estimation of the Business Cycle: A Modified Hodrick-Prescott Filter, Madrid, Banco de Espana.Google Scholar
Krolzig, H.-M. and Toro, J. (2001), ‘Classical and modern business cycle measurement: the European case’, University of Oxford, Discussion Papers in Economics, 60.Google Scholar
Osborn, D.R. (1995), ‘Moving average detrending and the analysis of business cycles’, Oxford Bulletin of Economics and Statistics, 57, pp. 547–558.CrossRefGoogle Scholar
Pagan, A. (2002), ‘Lectures on the business cycle’, mimeo, EUI, Florence, April.Google Scholar
Ravn, M.O. and Uhlig, H. (1997), ‘On adjusting the hp-filter for the frequency of observations’, Center Discussion Papers, 50.Google Scholar
Salazar, E., Smith, R., Weale, M. and Wright, S. (1997), ‘A monthly indicator of GDP’, National Institute Economic Review, 161, July, pp. 84–90.CrossRefGoogle Scholar