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Working Paper
Identifying Financial Crises Using Machine Learning on Textual Data
We use machine learning techniques on textual data to identify financial crises. The onset of a crisis and its duration have implications for real economic activity, and as such can be valuable inputs into macroprudential, monetary, and fiscal policy. The academic literature and the policy realm rely mostly on expert judgment to determine crises, often with a lag. Consequently, crisis durations and the buildup phases of vulnerabilities are usually determined only with the benefit of hindsight. Although we can identify and forecast a portion of crises worldwide to various degrees with ...
Discussion Paper
The Global Recovery: Lessons from the Past
The downturn in global economic activity caused by the COVID-19 pandemic was unique both for its causes and for its severity. Even though, on a global scale, the recent contraction is unprecedented in modern times, it is useful to look at the consequences of large recessions which affected individual countries in the past.