Resource title

Model Uncertainty and Aggregated Default Probabilities: New Evidence from Austria

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Resource description

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. (author's abstract) ; Series: Research Report Series / Department of Statistics and Mathematics

Resource author

Paul Hofmarcher, Stefan Kerbl, Bettina GrĂ¼n, Michael Sigmund, Kurt Hornik

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Resource publish date

Resource language

en

Resource content type

application/pdf

Resource resource URL

http://epub.wu.ac.at/3383/1/Report116.pdf

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