This dissertation consists of two parts. The first part introduces a neural network approach that is used to forecast the conditional probability density function of asset returns. The model is unified with the idea of Arbitrage Pricing Theory (APT). In the second part, an algorithm called...

Linear regression is a popular tool that is often applied to biometric and epidemiological data. It relies on strong model assumptions that are rarely satisfied. To overcome this difficulty, Brannath and Scharpenberg (2014) proposed a new population based interpretation of linear regression...

Surveys are a widely used tool to answer socio-economic research question across disciplines. However, data collection can face certain problems such as nonresponding units. For household and population surveys, a large body of literature about the effects of nonresponse exist but only less is...

This volume was prepared by Benedikt Heid while he was working at the ifo Institute and the University of Bayreuth. It was completed in December 2013 and accepted as a doctoral thesis by the Department of Economics at the Ludwig-Maximilians-Universität München. It includes six self-contained...

This paper examines the relationship between health aid and infant mortality, using data from in total 135 countries, between 1975 and 2010. According to the findings, aid comes to have a statistically significant and positive effect on infant mortality rate, as doubling of aid leads to an...