Forecasting the European Credit Cycle Using Macroeconomic Variables

Abstract

We question the ability of macroeconomic data to predict risk appetite and flight-to-quality periods in the European credit market using a model inspired by the Markov Switching (MS) literature. This model allows for a direct mapping of exogenous variables into states probabilities. We find that various survey and transformed hard data have a forecasting power. We show that despite its depth, the 2008-2009 crisis should not be regarded as an unusual episode that would have to be modelled by an additional state. Finally, we show that our model outperforms a pure MS model in terms of forecasting accuracy, thus clearly indicating that economic figures are helpful in forecasting the credit cycle.