Core-Periphery Business Cycle Synchronization in Europe and the Great Recession

Abstract

This article investigates the dynamics of business cycle synchronization in Europe. The European core business cycle is estimated by means of a cyclical trend decomposition model, and a testing procedure is proposed to study the stability of the interdependencies between the GDP growth rates of the economies and the cyclical common factor. Results show an extended European business cycle moving toward the synchronization levels enjoyed by core countries. In a second group of periphery economies (mainly economies of the EU enlargements of the 2000s) synchronization has increased since the beginning of the Great Recession.

Keywords:

• breaks
• European business cycle
• monetary union
• recursive estimation
• unobserved component models

JEL Classification:

• C32
• E32
• F44

ACKNOWLEDGMENTS

The authors thank the editor and two anonymous reviewers for their insightful comments on a previous version of this article. We are also grateful to José Luis Cendejas for his contribution.

Notes

1. The optimum currency area (OCA) theory argues that the benefits of a monetary union depend on the extent to which its member countries comply with certain criteria, known as the OCA properties. Among these properties, the similarity of business cycles plays an important role, because the more synchronized business cycles are, the lower the cost of giving up autonomous monetary policy.

2. The authors are aware, problematically, that many of the individual economies studied trade extensively with the United States and, therefore, should also be dependent on the U.S. business cycle (or the common world business cycle).

3. The existence of only one common factor has been confirmed employing the statistical criterion proposed by Bai and Ng (2002):

$\begin{array}{rl}& I{C}_{pl}(q)=log(det(\mathrm{\Sigma }))+q\frac{(N+T)}{nT}+log\left(\frac{nT}{N+T}\right)\\ & I{C}_{pl}(q)=log(det(\mathrm{\Sigma }))+q\frac{(N+T)}{nT}+log(min(n,T))\\ & I{C}_{pl}(q)=log(det(\mathrm{\Sigma }))+q\frac{log(min(n,T))}{(min(n,T))}\end{array}$

$\mathrm{w}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e}\mathrm{\Sigma }=variancematrixofresidual{e}_t$

.

4. Peña and Poncela (2006) assume a model in which the common dynamic structure of the time series vector is explained through a set of common factors that may be nonstationary, as in the case of common trends. Identification of the nonstationary I(d) factors is made through the common eigen structure of the generalized covariance matrices, properly normalized. The number of common nonstationary factors is the number of nonzero eigenvalues of the above matrices.

5. Following Stock and Watson (2002b, 2009), it is assumed that there are no structural breaks in the common EEC business cycle. Their article shows that despite possible time variations in the factor loadings, full- and subsample estimates of the factors could well be close, in the sense that the subsample estimates of the factor space are nearly spanned by the full-sample estimate of the factor space.

6. Luxembourg is omitted from this group due to the lack of available data for the same sample period as the rest of the founders (period 1991Q1–2013Q2), but it is included in the subsequent analysis.

7. This analysis finds no decoupling situations.

8. The period studied depends on the data availability offered by Eurostat for each country.

9. Denmark has a correlation close to 50% because of its relatively noisy GDP growth rate.

10. This result is also in line with Canova, Ciccarelli, and Ortega (2012), who consider that the euro area and non–euro area countries (like Sweden and Denmark) share business cycle variations and this process appears to be linked to a general process of convergence and synchronization taking place in Europe in the 1980–1990s.

11. In the period 1999–2007, annual mean growth was 3.6% in Spain and 2.2% in the euro area.

12. In line with Ferroni and Klaus (2015), we gather evidence of fluctuations in correlation in Spain, but in contrast to their work, the evidence in this article does not support the result of the decoupling of Spain but rather the existence of local permanent breaks.

Additional information

Notes on contributors

Sonia de Lucas Santos

Sonia de Lucas Santos is a Tenured Full-time Lecturer in the Department of Applied Economy (Statistics), Universidad Autónoma de Madrid. Maria Jesús Delgado Rodriguez is an Associate Professor in the Department of Applied Economy II, Universidad Rey Juan Carlos, Madrid

María Jesús Delgado Rodríguez

Sonia de Lucas Santos is a Tenured Full-time Lecturer in the Department of Applied Economy (Statistics), Universidad Autónoma de Madrid. Maria Jesús Delgado Rodriguez is an Associate Professor in the Department of Applied Economy II, Universidad Rey Juan Carlos, Madrid