Finding a needle in a haystack: Do Early Warning Systems for Sudden Stops work?

The paper develops an Early Warning System (EWS) to identify the build up of vulnerabilities in the external sector of 31 Emerging Markets (EMs) across the period 1995-2017 and avoid the painful sudden reversal of capital flows associated to them. It contributes to the literature on the prediction of financial discontinuities in three ways. First, it uses a discrete choice model to calculate and compare the marginal effect of different domestic and global factors on the probability of a sudden stop materializing. Second, it analyzes the performance of the model with a recursive framework that reflects accurately the information set available to policymakers at the time of the prediction. Third, it investigates the relationship between ex-ante probability of a sudden stop and the ensuing output loss. We find that domestic and global factors contribute to the reversal of capital flows in a comparable way. Our model calls half of the pre-crisis periods, exhibiting a high specificity and a proper timing. Moreover, we find a positive link between the ex-ante probability of a sudden stop and the associated ex-post loss. These results call for an active use of Early Warnings in the policy-making sphere