Market Power, Input Costs, and Technology

The research group deals with the empirical analysis of the dynamics and determinants of economic development. Thereby, we recognize that these are individual heterogeneous firms with their specific capabilities to innovate and to efficiently allocate scarce resources that shape patterns at higher level of aggregation (e.g. cause structural change). While following a micro-level approach we aim at adding to the understanding of the actual mechanisms and dynamics in the development of economies as well as for the development of policy instruments. For instance, one of the current research projects deals with the effect of import competition on the productivity and innovating behaviour of firms as well as on the dynamic in and of industries

The research group works closely together with CompNet.

Research Cluster
Productivity and Institutions

Your contact

Dr Matthias Mertens
Dr Matthias Mertens
Mitglied - Department Structural Change and Productivity
Send Message +49 345 7753-707 Personal page

EXTERNAL FUNDING

10.2022 ‐ 09.2024

MULTIMSPROD/MULTIMSPROD AUT

European Commission

Enhancing the Micro Foundation of the Research Output of National Productivity Board (NPBs). Using CompNet and expanding its Micro Data Infrastructure (MDI).

See project page

Professor Javier Miranda, PhD

09.2016 ‐

The Competitiveness Research Network (CompNet)

Funding institutions: European Central Bank (ECB), European Investment Bank (EIB), European Bank for Reconstruction and Development (EBRD), Tinbergen Institute, European Commission.

The Competitiveness Research Network (CompNet) provides a forum for high level research and policy analysis in the areas of competitiveness and productivity. Its main activities include the regular updating of its micro-based competitiveness database for European countries, unprecedented in terms of coverage and cross-country comparability.

Professor Reint E. Gropp, PhD

Refereed Publications

Working Papers

How Does Industry Specialization Affect the Efficiency of Regional Innovation Systems?

Michael Fritsch Viktor Slavtchev

in: Jena Economic Research Papers, Nr. 2008-058, No. 58, 2008

Abstract

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.

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Universities as Driver of Regional Innovation?

Michael Fritsch Viktor Slavtchev N. Steigenberger

in: Arbeitspapier / Hans-Böckler-Stiftung, Nr. 158, 2008

Abstract

Innovation ist der wesentliche Motor wirtschaftlicher Entwicklung. Denn vor allem die Andersverwendung von Ressourcen, weniger deren Mehreinsatz führt zu Wachstum und Wohlstand. Aus diesem Grund stellt Innovation auch einen wichtigen Ansatzpunkt für eine auf Wachstum zielende Politik dar. Dies gilt sowohl auf gesamtwirtschaftlicher Ebene als auch für einzelne Branchen und Regionen. In Innovationsprozessen stellt Wissen die entscheidende Ressource dar. Wissen ist mehr als bloße Information. Es umfasst insbesondere auch die Fähigkeit, Informationen zu interpretieren und anzuwenden bzw. ihre Anwendbarkeit einzuschätzen. Wissen ist an Menschen gebunden und lässt sich vielfach nur in direktem persönlichen Kontakt weitergeben. Aus diesem Grund hat Wissen eine regionale Dimension: Die Verfügbarkeit von Wissen hängt davon ab, wo sich die Menschen aufhalten, die über dieses Wissen verfügen. Dies ist ein wesentlicher Grund dafür, dass die Fähigkeit zur Innovation von Region zu Region wesentliche Unterschiede aufweisen kann. Für eine Politik, die auf die Stärkung der Innovationsfähigkeit von Regionen gerichtet ist, kommt den öffentlichen Forschungseinrichtungen – Universitäten, Fachhochschulen und außeruniversitären Forschungsinstituten – aus mindestens zwei Gründen zentrale Bedeutung zu: Erstens verfügen die öffentlichen Forschungseinrichtungen in besonderem Maße über innovationsrelevantes Wissen. Ihre Kernaufgabe ist es, Wissen zu produzieren, zu sammeln und weiterzugeben. Zweitens ist der Bereich der öffentlichen Forschungseinrichtungen – im Gegensatz zur privaten Wirtschaft – von der Politik direkt gestaltbar. Aus diesen Gründen stellt die Steuerung des Hochschulsektors ein zentrales Handlungsfeld der Innovationspolitik dar.

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Industry Specialization, Diversity and the Efficiency of Regional Innovation Systems

Michael Fritsch Viktor Slavtchev

in: Jena Economic Research Papers, Nr. 2007-018, No. 18, 2007

Abstract

Innovation processes are characterized by a pronounced division of labor between actors. Two types of externality may arise from such interactions. On the one hand, a close location of actors affiliated to the same industry may stimulate innovation (MAR externalities). On the other hand, new ideas may be born by the exchange of heterogeneous and complementary knowledge between actors, which belong to different industries (Jacobs’ externalities). We test the impact of both MAR as well as Jacobs’ externalities on innovative performance at the regional level. The results suggest an inverted u-shaped relationship between regional specialization in certain industries and innovative performance. Further key determinants of the regional innovative performance are private sector R&D and university-industry collaboration.

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What Determines the Efficiency of Regional Innovation Systems?

Michael Fritsch Viktor Slavtchev

in: Jena Economic Research Papers, Nr. 2007-006, No. 6, 2007

Abstract

We assess the efficiency of regional innovation systems (RIS) in Germany by means of a knowledge production function. This function relates private sector research and development (R&D) activity in a region to the number of inventions that have been registered by residents of that region. Different measures and estimation approaches lead to rather similar assessments. We find that both spillovers within the private sector as well as from universities and other public research institutions have a positive effect on the efficiency of private sector R&D in the respective region. It is not the mere presence and size of public research institutions, but rather the intensity of interactions between private and public sector R&D that leads to high RIS efficiency. We find that relationship between the diversity of a regions’ industry structure and the efficiency of its innovation system is inversely u-shaped. Regions dominated by large establishments tend to be less efficient than regions with a lower average establishment size.

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Measuring the Efficiency of Regional Innovation Systems – An Empirical Assessment

Michael Fritsch Viktor Slavtchev

in: Freiberg Working Papers, Nr. 08-2006, No. 8, 2006

Abstract

We measure the efficiency of regional innovation systems (RIS) in Germany by means of a knowledge production function. This function relates private sector Research and Development (R&D) in a region to the number of inventions that have been registered by residents of that region. Two approaches are followed. First, it is assumed that differences in the productivity of private sector R&D between regions affect the slope of the KPF, which represents the marginal productivity of R&D input. The second approach assesses regional differences within the framework of a stochastic frontier knowledge production function. This approach mainly reveals differences with regard to the intercept of the knowledge production function and, therefore, with regard to the average productivity. We compare the results of both approaches and discuss a number of critical issues such as the properties of the distribution of efficiencies, the appropriate size of RIS, and how to deal with the issue of spatial autocorrelation.

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