A three-state early warning system for the European Union

Savas Papadopoulos, Pantelis Stavroulias, Thomas Sager and Etti Baranoff

Abstract

The global financial crisis of 2007–8 focused the attention of the financial authorities on improving forecasting methods in order to avoid future financial crises of similar magnitude. We contribute to the literature on crisis prediction in several important ways. First, we develop an early warning system (EWS) that provides between seven and twelve quarters’ advance warning with high accuracy in out-of-sample testing. Second, our EWS applies region-wide to the leading economies in the European Union. Third, the methodology is transparent, utilizing only publicly available macrolevel data and comparing standard statistical classification methodology (multinomial logistic regression, discriminant analysis and neural networks). Fourth, we employ two relatively novel methodological innovations in EWS modeling: three-state (ternary) classification to guarantee a minimumadvance warning period, and a fitting and evaluation criterion (the total harmonic mean) that prioritizes avoiding classification errors for the relatively infrequent events of most interest. As a consequence, a policy maker who uses these methods will enjoy a high probability that future crises could be signaled well in advance and that crisis warnings will not be false alarms. Finally, since we focus on EU15, we provide an overall response on where the most common macroeconomic indicators can be used uniformly for that region.