Model Uncertainty and Aggregated Default Probabilities: New Evidence from Austria

Hofmarcher, Paul and Kerbl, Stefan and Grün, Bettina and Sigmund, Michael and Hornik, Kurt ORCID: https://orcid.org/0000-0003-4198-9911 (2012) Model Uncertainty and Aggregated Default Probabilities: New Evidence from Austria. Research Report Series / Department of Statistics and Mathematics, 116. WU Vienna University of Economics and Business, Vienna.

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Abstract

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.

Item Type: Paper
Keywords: Bayesian Model Averaging / model uncertainty / ridge regression / credit risk / firm defaults / stress testing
Classification Codes: JEL E44, C52, E37
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Josef Leydold
Date Deposited: 09 Jan 2012 09:28
Last Modified: 24 Oct 2019 13:41
FIDES Link: https://bach.wu.ac.at/d/research/results/57018/
URI: https://epub.wu.ac.at/id/eprint/3383

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