Economic Cycle Synchronization with Dynamic Time Warping

In a new post for Towards Data Science, Moritz Pfeifer unpacks the key insights from “Warpings in Time: Business and Financial Cycle Synchronization in the Euro Area”. The paper applies Dynamic Time Warping (DTW) to measure economic cycle synchronization across euro area member states, surpassing traditional static and mean-based methods by capturing dynamic lead-lag relationships in business and financial cycles. Through cluster analysis, the study identifies varied synchronization patterns across member states, offering policymakers a new tool to assess economic convergence and address obstacles to an optimal currency area.