Early Warning Systems with Real-Time Data

This paper investigates the performance of early warning systems in real-time, using forecasts of indicators that were available at the moment predictions are to be made. The study analyzes currency crises in eight Latin American and Central and Eastern European countries, distinguishing an estimation period 1990-2009 and a prediction period 2010-2014. We apply two varieties of early warning systems: the signal approach and the logit models. For both methods we find that using forecasts of the indicators worsens the predictive ability of early warning systems compared to using the most recently available information (ex post)