The transformation of credit scores into probabilities of default plays an important role in credit risk estimation. The linear logistic regression has developed into a standard calibration approach in the banking sector. With the advent of machine learning techniques in the discriminatory phase...

Using detailed establishment-level micro data, this paper analyzes for the German case the hypothesis by Aghion, Bergeaud, Boppart, Klenow, and Li (2019), stating that officially published figures for real output growth would be systematically understated. The effect rests on overstated...

This paper presents a framework for estimating losses in the residential real estate mortgage portfolios of German banks. We develop an EL model where LGD estimates are based on current collateral values and PD dynamics are estimated using a structural PVAR approach. We confirm empirically that...

We introduce a novel simulation-based network approach, which provides full-edged distributions of potential interbank losses. Based on those distributions we propose measures for (i) systemic importance of single banks, (ii) vulnerability of single banks, and (iii) vulnerability of the whole...

We propose an algorithm to model contagion in the interbank market via what we term the credit quality channel. In existing models on contagion via interbank credit, external shocks to banks often spread to other banks only in case of a default. In contrast, shocks are transmitted via asset...