Multidimensional Distance to Collapse Point and Sovereign Default Prediction

This paper focuses on predictability of sovereign debt crisis proposing a two-step procedure centered on the idea of a multidimensional distance-to-collapse point. The first step is non-parametric and devoted to constructing a generalized early warning system that signals a potential crisis. The second is parametric and tries to contextualize the country default within a theoretical-based process depending on the first step estimators. In this way we generalize the Mertonian distance-to-default within a multidimensional setting wherein we care about the distance of each indicator from its threshold. Our choice to semi-parametrically inspect the issue of country credit risk in the context of algorithmic and parametric modeling approaches is conceived with the end to bypass the reliability problem associated with predictive models, while maintaining a theoretical-based explanation of the process through which a country fails. Empirical evidence shows that our methodology predicts future defaults about the 80 per cent of the total events