In this paper we construct simultaneous confidence bands for a smooth curve using penalized spline estimators. We consider three types of estimation methods: (i) as a standard (fixed effect) nonparametric model, (ii) using the mixed model framework with the spline coefficients as random effects...

The dissertation consists of three essays. The main focus is set on semiparametric regression modeling, which embodies the strength of parametric and nonparametric regression models in terms of flexibility, dimensionality and interpretability. The first essay is “Some Recent Advances in...

Die drei Kapitel der Dissertation behandeln unterschiedliche Aspekte der quantitativen Impactevaluatierung im mikroökonomischen Kontext. Das erste Kapitel betrachtet den Einfluss von Arbeitsmigration auf das Konsumverhalten von Haushalten in Tadschikistan. Es scheint sich hierbei um einen...

In this thesis, so far insufficiently considered characteristics of long-run equilibriums in food markets are investigated. For this purpose, multivariate time series methodologies, which were developed for the estimation of long-run relationships by allowing for causality and convergence, are...

In this paper, we propose a generic Bayesian framework for inference in distributional regression models in which each parameter of a potentially complex response distribution and not only the mean is related to a structured additive predictor. The latter is composed additively of a variety of...

Generalized additive models for location, scale and shape define a flexible, semi-parametric class of regression models for analyzing insurance data in which the exponential family assumption for the response is relaxed. This approach allows the actuary to include risk factors not only in the...

In this paper, we propose a unified Bayesian approach for multivariate structured additive distributional regression analysis where inference is applicable to a huge class of multivariate response distributions, comprising continuous, discrete and latent models, and where each parameter of these...

Empirical studies on farmland rental rates have predominantly concentrated on modelling conditional means using spatial autoregressive models, where a linear functional form between the response and the covariates is usually assumed. However, if it is in fact non-linear, misspecifying the...

Quantile regression provides a convenient framework for analyzing the impact of covariates on the complete conditional distribution of a response variable instead of only the mean. While frequentist treatments of quantile regression are typically completely nonparametric, a Bayesian formulation...