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Common trends and common cycles in Belgian sectoral GDP

Published online by Cambridge University Press:  17 August 2016

Carolina Gervaz*
Affiliation:
CORE, Université catholique de Louvain
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Summary

The aim of this paper is to examine common trends and common cycles in Belgian sectoral output series. A multivariate technique proposed by Engle and Issler [1995] allows to deal with series which simultaneusly contain common trends and common cycles. An application of their methodology for eigth sectors of the Belgian per capita real GDP is presented in this article: it has been found that four independent common trends and four independent common cycles characterize the variables.

Résumé

Résumé

Le but de cet article est d'examiner les tendences et cycles communs des séries du PIB belge par secteur d'activité. La technique multi-variée proposée par Engle et Issler [1995] permet de travailler avec des séries présentant simultanément des tendences communes et des cycles communs. Une application de cette méthodologie à huit secteurs d'activités belges est présentée dans cet article : on trouve quatre tendences indépendentes communes et quatre cycles indépendents communs qui caractérisent les variables.

Keywords

Type
Research Article
Copyright
Copyright © Université catholique de Louvain, Institut de recherches économiques et sociales 1997 

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Footnotes

(*)

I wish to thank Professor Luc Bauwens and Professor Pierre Malgrange for their extremely helpful comments and suggestions, as well as Jean-Yves Pitarakis, seminar participants at CEPREMAP - ENSAE - MAD - CEME (Paris 1) and the Departement de Sciences Economiques (UCL), and two anonymous referees. Financial support from the FDS (Scientific Development Fund) of UCL and the European Union “Human Capital and Mobility Programme” is gratefully acknowledged. This text presents research results of the Belgian Program on Interuniversity Poles of Attraction initiated by the Belgian State, Prime Minister's Office, Science Policy Programming. All errors are my sole responsibility.

References

REFERENCES

Blanchard, O.J. and Quah, D. [1989], The dynamics effects of aggregate supply and demand disturbances, American Economic Review, 79(4), pp. 655673.Google Scholar
Campbell, J.Y. and Perron, P. [1991], Pitfalls and oportunities. What microe-conomists should know about unit roots, Technical Working Paper n° 100, NBER.Google Scholar
Cassiers, I.,De Villé, P., and Solar, P. [1993], Postwar growth in Belgium. A joint CEPR/IFS workshop, 11/12 June.Google Scholar
Dickey, D.A. and Fulley, W.A. [1981], The likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), pp. 10571072.Google Scholar
Doornik, J.A. and Hansen, H. [1994], A practical test of multivariate normality. Unpublished paper, Nuffield College.Google Scholar
Engle, R.F. and Granger, C.W.J. [1987], Cointegration and error correction: Representation, estimation and testing. Econometrica, 55(2), pp. 251276.Google Scholar
Engle, R.F. and Issler, J.V [1995], Estimating sectoral cycles using cointegration and common features. Journal of Monetary Economics, 35(1), pp. 83113.Google Scholar
Engle, R.F. and Kozicki, S. [1993], Testing for common features. Journal of Business and Economic Statistics, 11(4), pp. 369395.Google Scholar
Gervaz, C. [1993], Common Trends and Common Cycles in Belgian Sectoral GDP. Mémoire de fin d’Etudes, Maîtrise en Sciences Economies, UCL.Google Scholar
Gourieroux, C and Peaucelle, I. [1990], Séries codépendantes. Application à l’hypothése de parité du pouvoir d’achat, Document de Travail 9104, INSEE.Google Scholar
Johansen, S. [1988], Statistical analysis of cointegrated vectors. Journal of Economic Dynamics and Control, 12(2–3), pp. 231254.Google Scholar
Johansen, S. [1991], Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models, Econometrica, 59(6), pp. 15511580.Google Scholar
Long, J.B. and Plosser, C.I. [1983], Real business cycles, Journal of Political Economy, 91(1), pp. 3969.Google Scholar
Lucas, R.E. Jr. [1977], Understanding business cycles, Carnegie-Rochester Conference Series on Public Policy, vol. 5, Amsterdam, North Holland, pp. 729.Google Scholar
Osterwald-Lenum, M.[1992], A note with quantiles of the asymptotic distribution of the maximum likelihood cointegration rank test statistics, Oxford Bulletin of Economics and Statistics, 54(3), pp. 461472.Google Scholar
Phillips, P.C.B. and Perron, P. [1988], Testing for a unit root in time series regression, Biometrica, 75, pp. 335346.Google Scholar
Reimers, H.-E. [1992], Comparisons of tests for multivariate cointegration, Statistical Papers, 33, pp. 335359.Google Scholar
Savage, R. [1991], Chocs externes, structures productives et politiques d’ajustement, Bulletin de Documentation, n° 4, Ministere des Finances, Service D’etudes et de Documentation.Google Scholar
Vahid, F. and Engle, R.F. [1993], Common trends and common Ccycles, Journal of Applied Econometrics, 8(4), pp. 341360.Google Scholar