Abstract
ABSTRACT In this paper, we quantify business cycles synchronization in the European Union by combining Principal Component Analysis (PCA) with a Random Matrix Theory (RMT) model. We employ a balanced panel of industrial production indexes over the 2000–2017 period and we track the evolution of the European synchronization, as measured by the largest and statistically significant principal component. Using the information contained in the eigenvector associated to it, we then identify the dynamics of synchronization clusters. Our results suggest that the degree of synchronization has increased since the introduction of the common currency and until the Great Recession, but decreased thereafter. In addition, our results point to the evolution of synchronization clusters over the past decades. Whereas western and eastern countries had divergent business cycles at the beginning of the 21st century, they have become more synchronized over the analysed period. However, since the dawn of the European sovereign debt crisis, the synchronization divide has become more apparent between northern and southern economies.
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