In the introductory chapter it has been laid out, that knowledge as an input factor of production exhibits a strong influence on economic development. The increasing knowledge intensity in the globalised economy needs to focus on the determinants of the "knowledge based society". Two major determinants on which the "knowledge based society" and its economic analogon the "knowledge based economy" rely, are the creation and the diffusion of knowledge. The main motivation for this thesis stems exactly from the importance of knowledge and "knowledge diffusion" for the "knowledge based economy" and finally for the modern economic theory and empirics.The first two chapters after the introduction are direct applications from dynamic industrial organization. The first chapter deals with the question how knowledge transfer affects knowledge diffusion, whereas the second chapter tackles the relationship between firm size, innovation, market structure and learning.Until today, new economic geography applications, which cover knowledge diffusion topics are mainly empirically orientated and suffer from theoretical justification. We have a relative precise understanding about the grasp of knowledge diffusion but this aspect is not treated in regional growth literature. Thus, the first aim of the fourth chapter was to integrate the so called "folk theorem of spatial economics", which states that increasing returns to scale are essential for understanding the geographical distributions of economic activity, in a hybrid two sectoral regional growth model with an explicit focus on different grasps of knowledge diffusion.As mentioned above, the majority of economic applications treating knowledge diffusion topics is empirically based. In recent years, a new discipline, so called spatial econometrics, which can be labeled as a pendant to spatial economics, has emerged and has been established rather broadly in econometric society. Of course, this discipline is developing with respect to new estimation methods. Particularly, it seems that Bayesian methods are very attractive. Moreover, Bayesian methods do a great job within spatial econometrics, particularly when talking about spatial heterogeneity, which means that variances of observations are not constant over space, or outliers exist. The classic or frequentist methods today are not able to deal sufficiently with the phenomena of spatial heterogeneity. From this point it is rather astonishing, that most of spatial econometrics applications are still based only on the frequentist methods, despite their inherent limitations.Hence, the second aim of this chapter is to find out on the basis of a conducted cross section analysis, to what extent knowledge spillovers do contribute to regional growth. For this purpose it has been referred to German NUTS-2 regions.The final chapter alludes some revenues for further research, which are based on the previous chapters of this thesis.
