We propose a Bayesian nonparametric instrumental variable approach that allows us to correct for endogeneity bias in regression models where the covariate effects enter with unknown functional form. Bias correction relies on a simultaneous equations specication with flexible modeling of the...

Regressionsanalysen sind von Konfundierungseffekten betroffen, wenn Drittvariablen gleichzeitig mit Zielgrößen und Kovariablen korreliert sind. Klassische Regressionsmodelle sind in diesen Fällen nicht in der Lage, Kovariablen- und Drittvariableneffekte voneinander zu unterscheiden. Die...

This article proposes a simple and fast approach to build simultaneous confi dence bands and perform specification tests for smooth curves in additive models. The method allows for handling of spatially heterogeneous functions and its derivatives as well as heteroscedasticity in the data. It is...

The Cox proportional hazards model is the most commonly used method when analyzing the impact of covariates on continuous survival times. In its classical form, the Cox model was introduced in the setting of right-censored observations. However, in practice other sampling schemes are frequently...

The Basel II framework strictly defines the conditions under which financial institutions are authorized to accept real estate as collateral in order to decrease their credit risk. A widely used concept for its valuation is the hedonic approach. It assumes, that a property can be characterized...

This paper analyzes several modifications to improve a simple measure of vulnerability as expected poverty. Firstly, in order to model income, we apply distributional regression relating potentially each parameter of the conditional income distribution to the covariates. Secondly, we determine...

In this paper we reconsider the relationship between income on health, taking a distributional perspective rather than one centered on conditional expectation. Using Structured Additive Distributional Regression, we find that the association between income on health is larger than generally...

For numerous applications it is of interest to provide full probabilistic forecasts, which are able to assign probabilities to each predicted outcome. Therefore, attention is shifting constantly from conditional mean models to probabilistic distributional models capturing location, scale, shape...