Understanding the determinants of aggregated default probabilities (PDs)
has attracted substantial research over the past decades.
This study addresses two major difficulties in understanding the
determinants of aggregate PDs: Model uncertainty
and multicollinearity among the regressors.
We present Bayesian Model Averaging (BMA) as a powerful tool that
overcomes model uncertainty. Furthermore, we supplement BMA with
ridge regression to mitigate multicollinearity.
We apply our approach to an Austrian dataset.
Our findings suggest that factor prices like short term interest
rates and energy prices constitute major drivers of default rates,
while firms' profits reduce the expected number of failures.
Finally, we show that the results of our baseline model are fairly
robust to the choice of the prior model size.Series: Research Report Series / Department of Statistics and Mathematic
