Comparing Different Early Warning Systems : Results from a Horse Race Competition Among Members of the Macro-Prudential Research Network

Over the recent decades researchers in academia and central banks have developed early warning systems (EWS) designed to warn policy makers of potential future economic and financial crises. These EWS are based on diverse approaches and empirical models. In this paper we compare the performance of nine distinct models for predicting banking crises resulting from the work of the Macroprudential Research Network (MaRs) initiated by the European System of Central Banks. In order to ensure comparability, all models use the same database of crises created by MaRs and comparable sets of potential early warning indicators. We evaluate the models' relative usefulness by comparing the ratios of false alarms and missed crises and discuss implications for practical use and future research. We find that multivariate models, in their many appearances, have great potential added value over simple signalling models. One of the main policy recommendations coming from this exercise is that policy makers can benefit from taking a broad methodological approach when they develop models to set macro-prudential instruments