• credit cycle;
  • switching regimes;
  • density forecast


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 literature. This model allows for a direct mapping of exogenous variables into state probabilities. We find that various surveys 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 Markov switching model in terms of forecasting accuracy, thus clearly indicating that economic figures are helpful in forecasting the credit cycle. Copyright © 2011 John Wiley & Sons, Ltd.