This paper evaluates the R&D enhancing effects of two large public grant schemes for the German biotechnology industry (BioRegio, BioProfile). Both grant schemes are organized in the form of contents for cooperation with the goal to foster the performance of innovative firms by their...

In this paper, a set of neural network (NN) models is developed to compute short-term forecasts of regional employment patterns in Germany. NNs are modern statistical tools based on learning algorithms that are able to process large amounts of data. NNs are enjoying increasing interest in...

Socio-economic interrelationships among regions can be measured in terms of economic flows, migration, or physical geographically-based measures, such as distance or length of shared areal unit boundaries. In general, proximity and openness tend to favour a similar economic performance among...

Using a panel of 439 German regions we evaluate and compare the performance of various Neural Network (NN) models as forecasting tools for regional employment growth. Because of relevant differences in data availability between the former East and West Germany, the NN models are computed...

This paper offers an overview of experimental results, based on neural networks (NNs) used to forecast regional employment variations in Germany. NNs are statistical optimization tools inspired by the functioning of biological neural networks. Their main characteristics are their non-linear and...

This paper evaluates the R&D enhancing effects of two large public grant schemes for the German biotechnology industry (BioRegio, BioProfile). Both grant schemes are organized in the form of contents for cooperation with the goal to foster the performance of innovative firms by their...

In this paper, we evaluate the R&D enhancing effects of two large public grant schemes aiming at encouraging the performance of firms organized in clusters. These are Germany's well known BioRegio and BioProfile contests for which we compare the research performance of winning regions in...

We examine how city size affect wage levels of cities (agglomeration externality) and how it influence surrounding cities (spill-over effect) in China for the period between 1995 and 2009. Using spatial fixed-effect panel data models and allowing for endogenous and exogenous spatial dependence,...

We examine how city size affect wage levels of cities (agglomeration externality) and how it influence surrounding cities (spill-over effect) in China for the period between 1995 and 2009. Using spatial fixed-effect panel data models and allowing for endogenous and exogenous spatial dependence,...

In this paper, a set of neural network (NN) models is developed to compute short-term forecasts of regional employment patterns in Germany. NNs are modern statistical tools based on learning algorithms that are able to process large amounts of data. NNs are enjoying increasing interest in...