The Nasty Gap 30 years after unification: Why East Germany is still 20% poorer than the...
IWH FDI Micro Database
IWH FDI Micro Database The IWH FDI Micro Database (FDI = Foreign Direct...
Three Research Clusters ...
What South Korea has to do with the IWH ... Gerhard Heimpold about his experiences...
Benchmark Value-added Chains and Regional Clusters in R&D-intensive Industries
International Regional Science Review,
Although the phase of euphoria seems to be over, policy makers and regional agencies have maintained their interest in cluster policy. Modern cluster theory provides reasons for positive external effects that may accrue from interaction in a group of proximate enterprises operating in common and related fields. Although there has been some progress in locating clusters, in most cases only limited knowledge on the geographical extent of regional clusters has been established. In the present article, we present a hybrid approach to cluster identification. Dominant buyer–supplier relationships are derived by qualitative input–output analysis from national input–output tables, and potential regional clusters are identified by spatial scanning. This procedure is employed to identify clusters of German research and development-intensive industries. A sensitivity analysis reveals good robustness properties of the hybrid approach with respect to variations in the quantitative cluster composition.
Mapping Potentials for Input-Output Based Innovation Flows in Industrial Clusters – An Application to Germany
Economic Systems Research,
Our paper pursues two aims: first, it presents an approach based on input–output innovation flow matrices to study intersectoral innovation flows within industrial clusters. Second, we apply this approach to the identification of structural weaknesses in East Germany relative to the western part of the country. The case of East Germany forms an interesting subject because while its convergence process after unification began promisingly in the first half of the 1990s, convergence has since slowed down. The existing gap can now be traced mainly to structural weaknesses in the East German economy, such as the absence of strong industrial cluster structures. With this in mind, we investigate whether East Germany does in fact reveal the abovementioned structural weaknesses. Does East Germany possess fewer industrial clusters? Are they less connected? Does East Germany lack specific clusters that are also important for the non-clustered part of the economy?
Taking the First Step - What Determines German Laser Source Manufacturers' Entry into Innovation Networks?
International Journal of Innovation Management,
Early access to technological knowledge embodied in the industry’s innovation network can provide an important competitive advantage to firms. While the literature provides much evidence on the positive effects of innovation networks on firms’ performance, not much is known about the determinants of firms’ initial entry into such networks. We analyze firms’ timing and propensity to enter the industry’s innovation network. More precisely, we seek to shed some light on the factors affecting the duration between firm founding and its first cooperation event. In doing so, we apply a unique longitudinal event history dataset based on the full population of German laser source manufacturers. Innovation network data stem from official databases providing detailed information on the organizations involved, subject of joint research and development (R&D) efforts as well as start and end times for all publically funded R&D projects between 1990 and 2010. Estimation results from a non-parametric event history model indicate that micro firms enter the network later than small-sized or large firms. An in-depth analysis of the size effects for medium-sized firms provides some unexpected findings. The choice of cooperation type makes no significant difference for the firms’ timing to enter the network. Finally, the analysis of geographical determinants shows that cluster membership can, but do not necessarily, affect a firm’s timing to cooperate.
Drivers of the Spatial Emergence and Clustering of the Photovoltaic Industry in Germany
Zeitschrift für Wirtschaftsgeographie,
The drivers of the spatial emergence and clustering of the photovoltaic industry in Germany. Following the relatedness literature, we explore to what extent related industries influenced the regional emergence of the photovoltaic (PV) industry. In addition, we shed light on factors explaining selective processes of clustering. We particularly argue that generic resources and resources of related activities have been crucial for the regional concentration in early phases of the industry life cycle. With increasing maturity, industry-specific resources became more important. Based on a unique dataset containing population dynamics of the German PV industry, the hypotheses are tested empirically. Our results partially confirm the assumed beneficial effects of related industries for the emergence of the PV industry. Moreover, we observe changes in the relative importance of factors supporting regional concentration, with industry-specific resources becoming dominant as the industry matures.
Actors and Interactions – Identifying the Role of Industrial Clusters for Regional Production and Knowledge Generation Activities
Growth and Change,
This paper contributes to the empirical literature on systematic methodologies for the identification of industrial clusters. It combines a measure of spatial concentration, qualitative input–output analysis, and a knowledge interaction matrix to identify the production and knowledge generation activities of industrial clusters in the Federal State of Saxony in Germany. It describes the spatial allocation of the industrial clusters, identifies potentials for value chain industry clusters, and relates the production activities to the activities of knowledge generation in Saxony. It finds only a small overlap in the production activities of industrial clusters and general knowledge generation activities in the region, mainly driven by the high-tech industrial cluster in the semiconductor industry. Furthermore, the approach makes clear that a sole focus on production activities for industrial cluster analysis limits the identification of innovative actors.
Geoadditive Models for Regional Count Data: An Application to Industrial Location
ERSA conference papers,
We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data which allows us to simultaneously address some important methodological issues, such as spatial clustering, nonlinearities and overdispersion. We apply this model to study location determinants of inward greenfield investments occurred over the 2003-2007 period in 249 European regions. The inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity which induces spatial clustering. Allowing for nonlinearities reveals, in line with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some limit value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs would never overcome positive agglomeration externalities.