Structured additive regression comprises many semiparametric regression models such as generalized additive (mixed) models, geoadditive models, and hazard regression models within a unified framework. In a Bayesian formulation, nonparametric functions, spatial effects and further model...

Precise knowledge about factors influencing the habitat suitability of a certain species forms the basis for the implementation of effective programs to conserve biological diversity. Such knowledge is frequently gathered from studies relating abundance data to a set of influential variables in...

Estimating nonlinear effects of continuous covariates by penalized splines is well established for regressions with cross-sectional data as well as for panel data regressions with random effects. Penalized splines are particularly advantageous since they enable both the estimation of unknown...

The thesis consists of four essays in the broad spectrum of development economics. While the first three essays are in the sphere of poverty measurement, the fourth essay is on the topic of trade and development. In recent years, the issue of international poverty measurement gained in...

Diese Arbeit ist eine Sammlung von Studien, welche sowohl die makro-, als auch die mikroökonomischen Aspekte und Charakteristika von Rücküberweisungen pakistanischer Migranten in ihr Heimatland analysieren, sowie deren ökonomische Auswirkungen auf das Konsumverhalten und die...

We reexamine the effect of economic development on the level of democracy based on the data sets of Acemoglu et al. (2008) with a novel regression specification utilizing a zero-one-inflated beta distribution for the response variable democracy. The zero-one-inflated beta distribution is more...

This dissertation includes three empirical essays on development economics and one on the economics of education. The first essay (co-authored by Stephan Klasen) is a contribution to the debate surrounding the Millennium Development Goals (MDGs) and the on-going debate about what international...

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...

Bayesian methods have become increasingly popular in the past two decades. With the constant rise of computational power even very complex models can be estimated on virtually any modern computer. Moreover, interest has shifted from conditional mean models to probabilistic distributional models...