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.
Sächsischer Technologiebericht 2012
in: Studie im Auftrag des Sächsischen Staatsministeriums für Wissenschaft und Kunst , 2013
Der „Sächsische Technologiebericht 2012“ verfolgt das Ziel, das Innovationsgeschehen im Freistaat Sachsen umfassend darzustellen. Er beschreibt Potenziale und Rahmenbedingungen sowie Stärken und Schwächen der Innovationspraxis im Freistaat und ermöglicht als Monitoring-Instrument die Beobachtung der Entwicklung innovationsrelevanter Indikatoren im Zeitverlauf. Die Funktion des Monitorings erschöpft sich dabei nicht in der Erfassung von Ist-Zustand und Dynamik des Innovationsgeschehens, sondern soll Rückschlüsse darauf zulassen, ob durch die Politik vorgegebene Ziele erreicht wurden.
What Drives Innovation Output from Subsidized R&D Cooperation? — Project-level Evidence from Germany
in: Technovation , No. 6, 2012
Using a large dataset of 406 subsidized R&D cooperation projects, we provide detailed insights into the relationship between project characteristics and innovation output. Patent applications and publications are used as measures for the innovation output of an R&D project. We find that large-firm involvement is strongly positively related with the number of patent applications, but not with the number of publications. Conversely, university involvement has positive effects on projects’ innovation output in terms of the number of publications but not in terms of patent applications. In general, projects’ funding as measure of projects’ size is an important predictor of the innovation output of R&D cooperation projects. No significant effects are found for the number of partners as (an alternative) measure of projects’ size, for spatial proximity between cooperation partners, for the involvement of a public institute for applied research, and for prior cooperation experiences. We derive conclusions for the design of R&D cooperation support schemes.
A Systemic View on Knowledge-based Development Metrics
in: International Journal of Knowledge-Based Development , No. 1, 2012
Drawing on the systems perspective of innovation processes, this article proposes a conceptual approach for a comprehensive analysis of regional knowledge generation and transfer. Instead of focusing on one single indicator, the approach emphasizes the importance to take multiple channels of knowledge transfer into account. This provides valuable insights into the spatial structure of innovation processes on different levels. We disentangle the innovation process and consider four different layers: i.) publications in peer-reviewed journals, ii.) patent applications, iii.) formal R&D collaboration projects, the iv.) localized input-output relations. Further, we demonstrate the relevance of the „multi-layer approach‟ by applying it empirically to a specific regional innovation system: The Free State of Saxony – a federal state in Germany. We argue that the approach could be a valuable tool to inform policy-makers about knowledge-based regional development strategies.
Measuring Regionalized Knowledge Generation and Transfer – A Feasibility Study Using a Multi-layer Approach in the Free State of Saxony
in: IWH-Sonderhefte , No. 5, 2010
Economic literature regards knowledge creation and learning as critical elements for gaining competitive advantage of regions. However, recognizing the importance of innovation and knowledge creation to economic success is far from being novel. Original is the view of increasing importance of knowledge creation for speeding up the depreciation of existing knowledge stocks. This puts a high pressure on regional actors to constantly participate in innovation processes to maintain their competitive advantages. Against this background, regional actors – if they aim to be successful in the globalized economy – first require access to a comprehensive and diversified knowledge base. Second, they need to participate in the processes of knowledge generation and knowledge transfer. Thereby, systemic innovation theory has pronounced the view that the locus of innovation and knowledge creation resides not only within the boundaries of the regional actors, such as private firms, universities, research laboratories, suppliers, and customers, but is the result of an interdependent exchange process between these different types. Collaborative interactions, bringing together different types of actors, may therefore lie well at the heart of accelerated knowledge creation and learning at the regional level (Lundvall and Johnson 1994).
The Identification of Industrial Clusters – Methodical Aspects in a Multidimensional Framework for Cluster Identification
in: IWH Discussion Papers , No. 14, 2010
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.