Identifying indicators of financial crises

Abstract

Early warning models have gained prominence after the global financial crisis of 2008 struck the world without remorse. The severity and the extent to which economies around the globe was affected resulted in massive costs. The notion of early warning indicators being able to identify areas of vulnerabilities with regard to oncoming financial crises justifies supplementary research into early warning indicators. Based on a dataset proposed by Rohn et al., (2015), this thesis discusses potential vulnerabilities that can lead to financial crises. The dataset includes more than 70 vulnerability indicators for 34 OECD countries between 2005 and 2014. However, monitoring an extensive list of potential vulnerabilities is not always possible. Dynamic factor analysis was therefore applied to the dataset as a measure of data reduction in order to identify a suitable set of early warning indicators that can be monitored to signal oncoming financial crises.