The Shape of Crisis Lessons from Self Organizing Maps

Abstract

Self Organizing Maps are computational tools whose engagement in various research fields has grown faster and wider in latest year, with the notable exception of macroeconomics, where contributions are somewhat lacking. However, we are going to provide evidence that joining Self Organizing Maps together with some graphs theory tools (namely: the Minimum Spanning Tree), they can be successfully employed to develop macroeconomic models thus taking both static and dynamic (i.e. over a moving period of time) snapshots of countries financial situations. In this way it is possible to generate useful information for policy makers, in order to realize more efficient interventions in periods of either higher instability or full-blown crisis situation.