How to evaluate an Early Warning System ?: Towards a Unified Statistical Framework for Assessing Financial Crises Forecasting Methods

This paper proposes an original and uni ed toolbox to evaluate nancial crisis Early Warning Systems (EWS). It presents four main advantages. First, it is a model free method which can be used to asses the forecasts issued from di erent EWS (probit, logit, markov switching models, or combinations of models). Second, this toolbox can be applied to any type of crisis EWS (currency, banking, sovereign debt, etc.). Third, it does not only provide various criteria to evaluate the (absolute) validity of EWS forecasts but also proposes some tests to compare the relative performance of alternative EWS. Fourth, our toolbox can be used to evaluate both in-sample and out-of-sample forecasts. Applied to a logit model for twelve emerging countries we show that the yield spread is a key variable to predict currency crises exclusively for South-Asian countries. Besides, the optimal cut-o correctly allows us to identify now on average more than 2/3 of the crisis and calm periods.Ce papier présente une nouvelle méthodologie d'evaluation des Systèmes d'Alerte Avancés pour les crises de change (en anglais Early Warning Systems) basée sur les méthodes traditionnelles de credit-scoring. L'analyse de capacités prédictives des modéles logit et Markov révèle la supériorité du modèle logit relativement au modèle Markov. De plus, l'introduction des variables d'anticipation du marché améliore les capacités prédictives des modèles EWS. Cette augmentation des capacités prédictives confirme la compétence des modèles de deuxième génération de crise pour expliquer l'apparition des crises de change