This paper provides a historical overview on financial crises and their origins. The objective is to discuss a few of the modern statistical methods that can be used to evaluate predictors of these rare events. The problem involves prediction of binary events and therefore fits modern statistical learning, signal processing theory, and classification methods. The discussion also emphasizes the need to supplement statistics and computational techniques with economics. A forecast’s success in this environment hinges on the economic consequences of the actions taken as a result of the forecast, rather than on typical statistical metrics of prediction accuracy.
About the Author
Òscar Jordà is a senior policy advisor in the Economic Research Department of the Federal Reserve Bank of San Francisco. Learn more about Òscar Jordà