Despite the extensive literature on prediction of banking crises by Early Warning Systems (EWS), their practical use by policy makers is limited, even in the international financial institutions. This is a paradox since the changing nature of banking risks as more economies liberalise and develop their financial systems, as well as ongoing innovation, makes the use of EWS for crisis prevention more necessary than ever. In this context, we assess the logit and signal extraction EWS for banking crises on a comprehensive common dataset. We suggest that logit is the most appropriate approach for global EWS and signal extraction for country specific EWS. Furthermore it is important to consider the policy maker's objectives when designing predictive models and setting related thresholds since there is a sharp trade-off between correctly calling crises and false alarms.
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