WSEAS Transactions on Business and Economics
Print ISSN: 1109-9526, E-ISSN: 2224-2899
Volume 16, 2019
Synchronization of Business Cycles in the EU: Time Series Clustering
Authors: ,
Abstract: The enlargement of the European Union was the crucial factor of synchronization of business cycles. The main aim of the paper is to study macro variables co-movement within the EU and its underlying driving forces. The examined variables include GDP, export and employment. The choice of the similarity measure of time series depends mostly on the purpose of research. The authors have applied cluster analysis to identify the level of business activity convergence, based on an adaptive dissimilarity index covering both proximity on values and on behaviour, Euclidean distance and concordance measure. To distinguish homogenous groups of countries according to their business cycles dynamics two approaches were used: clustering based on matrix of dissimilarity measures calculated for a specific variable in time, and clustering based on average dissimilarity between countries. Authors presented also different methodological approaches to the identification of business cycles synchronisation (BCS) as well as current research. The results shows that there exists such phenomenon like “business cycles clubs”. It means that we can observe quite high similarity of business cycles across EU countries, according to dynamics and values of analysed indicators, especially for export and GDP, but only within homogenous groups of countries. Received results can be compared with results obtained by other authors, but its most important application is possibility of create and apply the same anticyclical financial, monetary and fiscal policy to the group of some/several countries. An identification of BCS by means of two measures focused on proximity on values and on behaviour in a multidimensional environment, as well as an assessment of concordance of obtained classification for a particular indicators and for applied measures evidence some novelty of the research.
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Keywords: business cycles, synchronisation, time series, dissimilarity measures, clustering, concordance, European Union
Pages: 298-305
WSEAS Transactions on Business and Economics, ISSN / E-ISSN: 1109-9526 / 2224-2899, Volume 16, 2019, Art. #33