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...

Health-related quality of life assessment is important in the clinical evaluation of patients with metastatic disease that may offer useful information in understanding the clinical effectiveness of a treatment. To assess if a set of explicative variables impacts on the health-related quality of...

Hamilton (2017) criticises the Hodrick and Prescott (1981, 1997) filter (HP filter) because of three drawbacks (i. spurious cycles, ii. end-of-sample bias, iii. ad hoc assumptions regarding the smoothing parameter) and proposes a regression filter as an alternative. I demonstrate that Hamilton's...

The beta dispersion, which is the spread of betas on a stock market, can be interpreted as a measure of market vulnerability. This study examines the economic idea of the beta dispersion and its application as a market return predictor. Based on the empirical beta dispersion observed in the US...

Space-varying regression models are generalizations of standard linear models where the regression coefficients are allowed to change in space. The spatial structure is specified by a multivariate extension of pairwise difference priors thus enabling incorporation of neighboring structures and...

We evaluate the role of financial conditions as predictors of macroeconomic risk first in the quantile regression framework of Adrian et al. (2019b), which allows for non-linearities, and then in a novel linear semi-structural model as proposed by Hasenzagl et al. (2018). We distinguish between...