Analysis and visualization of synchronicity in European business and growth cycles and the implications for ECB monetary policy

[From the introduction]. The synchronicity of cycles in real output is a subject that has attracted increased attention in the eld of economics, largely because not only is the international synchronicity of turning points of business cycles a "stylized fact", but also because within a monetary union, given the absence of labor mobility and federal transfers, synchronicity of growth cycles is an important pre-requisite for optimal application of a single monetary policy. Given the fact that business cycles are largely the only cycle that economists recognize in national income data, it is perhaps natural to study the synchronicity of these cycles, and yet for monetary policy the dynamic of GDP growth at other frequencies is also important. Given that monetary policy usually operates at roughly a monthly level, the dynamic of GDP at even quarterly levels has implications for the implementation of monetary policy across different countries or jurisdictions. As the optimal currency area literature suggests that synchronization of business and growth cycles is an important consideration for adoption of a single currency, monetary policy is more easily formulated if these cycles in real GDP growth are similar between the member states that have qualified and subsequently adopted the euro. In this paper the synchronicity of business and growth cycles is first assessed assessed, both statically and dynamically, and then the paper goes on to look at the potential problems that these findings might raise for a single monetary policy in the euro area in the future. In the quantitative part of this paper, a new approach is taken to assessing synchronicity in real GDP growth, that of using a variation on recurrence plots and recurrence quantification analysis (RQA). RQA has its origins in physics, but is now used in many disciplines such as climatology, physiology, biology, chemistry, acoustics and astronomy. This technique is particularly suited to analysis of nonlinear dynamical systems, and so is likely better suited to analysis of business and growth cycles in real GDP than are linear econometric-based time series methods.