If regional development agencies assume the cluster concept to be an adequate framework to promote regional growth and competitiveness, it is necessary to identify industrial clusters in a comprehensive manner. Previous studies used a diversity of methods to identify the predominant concentrations of economic activity in one industrial sector in a region. This paper is based on a multidimensional approach developed by Titze et al. With the help of the combination of concentration measures and input–output methods they were able to identify horizontal and vertical dimensions of industrial clusters. This paper aims to refine this approach by using a superior measure of spatial concentration and by integrating information about spatial interdependence of industrial cluster structures to contribute to a more adequate framework for industrial cluster identification.

This study analyzes the relationship between the specialization of a region in certain industries and the efficiency of the region in generating new knowledge. The efficiency measure is constructed by relating regional R&D input and output. An inversely u-shaped relationship is found between regional specialization and R&D efficiency, indicating the presence of externalities of both Marshall and Jacobs’ type. Further factors influencing efficiency are externalities resulting from high R&D intensity of the local private sector as well as knowledge from local public research institutions. The impact of both the specialization and the additional factors is, however, different for regions at different efficiency levels.

We use a combination of measures of spatial concentration, qualitative input-output analysis and innovation interaction matrices to identify the horizontal and vertical dimension of industrial clusters in Saxony in 2005. We describe the spatial allocation of the industrial clusters and show possibilities of vertical interaction of clusters based on intermediate goods flows. With the help of region and sector-specific knowledge interaction matrices we are able to show that a sole focus on intermediate goods flows limits the identification of innovative actors in industrial clusters, as knowledge flows and intermediate goods flows do not show any major overlaps.

This paper investigates the forces driving output change in a panel of EU manufacturing industries. A flexible modeling strategy is adopted that accounts for: (i) inefficient use of resources and (ii) differences in the production technology across industries. With our model we are able to identify technical, efficiency, and input growth for endogenously determined technology clubs. Technology club membership is modeled as a function of R&D intensity. This framework allows us to explore the components of output growth in each club, technology spillovers and catch-up issues across industries and countries.

This paper investigates the driving forces of output change in 77 countries during the period 1970–2000. A flexible modeling strategy is adopted that accounts for (i) the inefficient use of resources, and (ii) different production technologies across countries. The proposed model can identify technical, efficiency, and input change for each of three endogenously determined regimes. Membership in these regimes is estimated, rather than determined ex ante. This framework enables explorations into the determinants of output growth and convergence issues in each regime.

The ‘cluster theory’ has become one of the main concepts promoting regional competitiveness, innovation, and growth. As most studies focus on measures of concentration of one industrial branch in order to identify regional clusters, the appropriate analysis of specific vertical relations within a value-adding chain is developing in this discussion. This paper tries to identify interrelated sectors via national input-output tables with the help of Minimal Flow Analysis by Schnabl (1994). The regionalization of these national industry templates is carried out with the allocation of branch-specific production values on regional employment. As a result, the paper shows concentrations of vertical clusters in only 27 of 439 German NUTS-3 regions.

This study analyzes the relationship between the specialization of a region in certain industries and the efficiency of the region in generating new knowledge. The efficiency measure is constructed by relating regional R&D input and output. An inversely u-shaped relationship is found between regional specialization and R&D efficiency, indicating the presence of externalities of both Marshall and Jacobs’ type. Further factors influencing efficiency are spillovers within the private sector as well as from public research institutions. The impact of both the specialization and the additional factors is, however, different for regions at different efficiency levels.

Quality of service is of major economic significance in natural monopoly infrastructure industries and is increasingly addressed in regulatory schemes. However, this important aspect is generally not reflected in efficiency analysis of these industries. In this paper we present an efficiency analysis of electricity distribution networks using a sample of about 500 electricity distribution utilities from seven European countries. We apply the stochastic frontier analysis (SFA) method on multi-output translog input distance function models to estimate cost and scale efficiency with and without incorporating quality of service. We show that introducing the quality dimension into the analysis affects estimated efficiency significantly. In contrast to previous research, smaller utilities seem to indicate lower technical efficiency when incorporating quality. We also show that incorporating quality of service does not alter scale economy measures. Our results emphasise that quality of service should be an integrated part of efficiency analysis and incentive regulation regimes, as well as in the economic review of market concentration in regulated natural monopolies.

Wir untersuchen die Bedeutung verschiedener Inputs, insbesondere verschiedener Wissensquellen, für den regionalen Output an Erfindungen (Patente) mithilfe einer Wissensproduktionsfunktion. Als Wissensquellen werden die FuE-Beschäftigte im Privatsektor, die Größe der Universitäten und Fachhochschulen sowie das Volumen der von ihnen aus verschiedenen Quellen eingeworbenen Drittmittel berücksichtigt. Die Bedeutung dieser Wissensquellen wurde systematisch auf der Ebene der westdeutschen Kreise getestet, wobei Informationen sowohl über den jeweiligen Kreis als auch über die Nachbarkreise einbezogen wurden. Es stellt sich heraus, dass von der Qualität der in den Universitäten und Fachhochschulen betriebenen Forschung ein signifikanter Einfluss auf die regionale Innovationstätigkeit ausgeht. Die reine Größe der Universitäten und Fachhochschulen in der Region hat hingegen keinen Einfluss. Darüber hinaus ermitteln wir Unterschiede nach Herkunft von Drittmitteln sowie Unterschiede in der Bedeutung verschiedener Fachdisziplinen für regionale Innovationsaktivitäten. Wissensspillover sind im Wesentlichen auf die angrenzenden Kreise begrenzt.

Der Band enthält Aufsätze zu drei thematischen Schwerpunkten:

Erstens: Arbeiten zur Ausdehnung des Input-Output-Konzepts auf Felder, die bislang von der Input-Output-Analyse vernachlässigt worden sind. Dazu gehören die Erstellung sozio-ökonomischer Input-Output-Tabellen (C. Stahmer), die Einbeziehung der Verkehrsaktivitäten außerhalb der darauf spezialisierten Wirtschaftszweige in input-output-analytische Überlegungen (A. Diekmann) und die Generierung von Liquidität im Input-Output-Abbild des Güter- und Einkommenskreislaufs (R. Filip-Köhn).