25 Years IWH

Centre for Evidence-based Policy Consulting (IWH-CEP)

The Centre for Evidence-based Policy Consulting (IWH-CEP) of the IWH was founded in 2014. It is a platform that bundles and structures activities in research, teaching, and policy consulting. IWH-CEP pursues the objective of creating better foundations for a causal analysis of policy instruments in Germany.

IWH-CEP is designed as a service unit and supports the activities in the research groups by providing access to a supra-regional research and policy consulting network as well as access to data sets for causal analyses. IWH-CEP lies at the interface between three areas of responsibility and carries out coordination functions between them.

Centre for Evidence-based Policy Consulting (IWH-CEP)

The government intervenes in the market mechanism through a lot of policy instruments in order to achieve various economic objectives. However, for policy makers, it is important to know whether the originally intended objectives are also achieved. Scientific methods can make a significant contribution to this. These are necessary to establish a clear connection between a policy instrument and its effect. Against this background, the Centre for Evidence-based Policy Consulting (IWH-CEP) at the IWH was founded.

Research and Policy Consulting

Research and policy consulting take place in the research groups. At present, the "Joint Task of 'Improving the Regional Economic Structure'" in the Federal State of Saxony-Anhalt (which is the most important regional policy support scheme in Germany) is being evaluated. This project is intended as a pilot study. Evaluation techniques that are successful in this pilot study will be applied in the context of other policy support schemes. The project is carried out under the responsibility of IWH Research Group "The Performance of Firms and Regions". Topics from the Department of Financial Markets shall also be handled in future, and namely, how regulation affects capital allocation.

Set-up of a Network

IWH-CEP is part of the initiative for "Evidence-based Economic Policy", which is established by the Verein für Socialpolitik (German Economic Association). Through the connection with the initiative, visibility and knowledge transfer should be guaranteed in the scientific and political community.

Set-up and Maintenance of Databases

The major challenge in the analysis of effects of government interventions today lies in the development of administrative (funding) data. An IWH R&D Micro Database is set up, maintained and completed according to the (current) specialisation in the analysis of effects of industrial policy support schemes. Information about the funded projects alone is not sufficient to conduct causal analyses – corporate data of the official and commercial statistics must be referred to; this is organised using record linkage techniques. This task is perspectively carried out at the IWH Research Data Centre.

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Publications

20 years of innovation policy in East Germany – from a pure “survival support” to high-tech subsidy

Jutta Günther Nicole Nulsch Katja Wilde

in: Wirtschaft im Wandel , No. 2, 2010

Abstract

The article uses the occasion of “20 years German re-unification” in order to provide an overview of the range of innovation policy schemes in East Germany with the intention to identify changing patterns or paradigms in its philosophy and priorities over time. In general, innovation policy schemes aim at increasing research and development (R&D) activities of companies in order to strengthen their competitiveness as market incentives for R&D are usually too low (problem of market failure). However, in East Germany in the early 1990s the situation was different. At the very beginning, the transformation process in East Germany was accompanied by innovation policy schemes that aimed at the pure maintenance of industrial research and the stock of R&D personnel since the potential for innovation was at a risk to be eliminated completely. In the late 1990s the intention of innovation policies changed. Instead of financial support primarily for human resources, innovation policy schemes since then focused on the support of cooperation projects between different research entities (companies and scientific organizations) and, later on, also the setup of networks in order to close the economic differences between East and West Germany.

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Die horizontale und vertikale Dimension industrieller Cluster – methodische Aspekte am Beispiel Dresdens

Mirko Titze Matthias Brachert Alexander Kubis

in: Wirtschaft im Wandel , No. 7, 2009

Abstract

Das Konzept industrieller Cluster verzeichnet stetige Attraktivitätsgewinne bei Akteuren regionaler Wirtschaftsförderung. Folgt man der Überlegung, dass das Clusterkonzept einen Ansatzpunkt zur Förderung der Wettbewerbsfähigkeit von Regionen bildet, so ist es in einem ersten Schritt notwendig, industrielle Cluster umfassend zu identifizieren. Bisherige Untersuchungen bedienen sich dazu einer methodischen Vielfalt. Sie reicht von spezifischen regionalen Fallstudien über Cluster-Mapping und Input-Output-Methoden bis hin zu verschiedenen Konzentrationsmaßen. Der folgende Beitrag orientiert sich an einer mehrdimensionalen Clusterdefinition und versucht, die verschiedenen methodischen Ansätze zusammenzuführen. Durch die Kombination der Verwendung von Konzentrationsmaßen, Input-Output-Methoden sowie regionalen Matrizen innovativer Wissensflüsse wird ein ganzheitlicher Ansatz zur Identifikation horizontaler und vertikaler industrieller Cluster vorgestellt. Dieser ermöglicht es, regionsspezifische und regionsübergreifende Clusterstrukturen zu identifizieren. Am Beispiel des Großraums Dresden zeigt sich, dass sich die wirtschaftliche Aktivität mehrheitlich auf die kreisfreie Stadt Dresden konzentriert. Übersehen wird jedoch oftmals die Bedeutung des Umlandes für die Wissensgenerierung in Kernstädten. Mit Hilfe einer regionalen Matrix innovativer Wissensflüsse lassen sich positive Effekte der Wissensgenerierung durch die Kragenkreise Dresdens darstellen. Diese Strukturen gilt es in einer umfassenden Identifikation industrieller Cluster zu beachten, damit alle Akteure der Wissensgenerierung in die Clusteridentifikation einbezogen werden.

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