Identifying Unsustainable Credit Gap

Abstract

This paper aims to overcomes model uncertainty in using the credit gap as an early warning indicator (EWI) of systemic financial crises in a binary outcome setting. I propose using model averaging of different credit gap measurements to achieve better averaged model fit and out-of-sample prediction. I also propose a novel, superior criteria to judge the performance of an EWI than the one currently popularly used in the literature. The empirical results showed that the Bayesian averaged model I proposed could synthesize a single credit gap that out-performs any other popularly studied credit gap measurements in terms of an early warning indicator