Key methodologies used for managing weather risks have relied on the assumption that climate is not changing and that the historic weather record is therefore representative of current risks. Anthropogenic climate change upends this assumption, effectively reducing the information available to...

This paper provides a comprehensive early warning system (EWS) that balances the classical signaling approach with the best-realized machine learning (ML) model for predicting fiscal stress episodes. Using accumulated local effects (ALE), we compute a set of thresholds for the most informative...

To complement the early warning signals literature, we study the determinants of banking and currency crises for small states and currency boards. Building on the crisis dataset by Laeven and Valencia (2020), we estimate a binominal logit model to identify the determinants of crises, and as a...

As a region that is impacted by multiple shocks, multi-hazard early warning systems (MHEWS) that provide timely, actionable information are critical to protecting lives, assets and livelihoods in the Caribbean. As the region experiences the compound and cascading effects of multiple hazards, the...

As a region that is impacted by multiple shocks, multi-hazard early warning systems (MHEWS) that provide timely, actionable information are critical to protecting lives, assets and livelihoods in the Caribbean. As the region experiences the compound and cascading effects of multiple hazards, the...