Evaluierung von Subventionsprogrammen
Diese Forschungsgruppe untersucht die Effekte von Produktions- und Wissensnetzwerken auf die Produktivität von Unternehmen und Regionen. Darüber hinaus werden Wirkungen staatlicher Förderprogramme für Forschung und Entwicklung sowie regionalpolitischer Programme auf die Leistungsfähigkeit von Unternehmen und Regionen evaluiert.
ForschungsclusterInstitutionen und soziale Normen
09.2019 ‐ 09.2022
Etablierung einer evidenzbasierten Evaluationskultur für industriepolitische Fördermaßnahmen in Deutschland (EVA-KULT)
Europäischer Fonds für regionale Entwicklung (EFRE)
Das Vorhaben dient dem Ausbau des Zentrums für evidenzbasierte Politikberatung am Leibniz-Institut für Wirtschaftsforschung Halle (IWH-CEP).
01.2018 ‐ 12.2020
Vernetzt wachsen - Innovatives Sachsen-Anhalt durch digitale Geschäftsmodelle (Kompetenzzentrum 4.0)
Bundesministerium für Wirtschaft und Energie (BMWi)
01.2017 ‐ 12.2018
Politische Partizipation in Ostdeutschland
Bundesministerium für Wirtschaft und Energie (BMWi)
12.2015 ‐ 11.2018
Sozioökonomische Effekte der Erforschung innovativer Ansätze für die POC-Diagnostik
Bundesministerium für Bildung und Forschung (BMBF)
Teilvorhaben im Verbundprojekt “POC-Sensorplattform für chronisch-entzündliche Atemwegserkrankungen (EXASENS)”. Neun Leibniz-Institute arbeiten gemeinsam im Pilotprojekt EXASENS an der Erforschung einer Point-of-Care-Technologie zur Vorhersage und Diagnose von chronisch-entzündlichen Atemwegserkrankungen. Der Verbund wird vom Bundesministerium für Bildung und Forschung (BMBF) mit 6,25 Millionen Euro gefördert und liefert einen Beitrag zum Ausbau und zur Stärkung des Themenfeldes Gesundheitstechnologien.
Vgl. Pressemitteilung des Leibniz-Institut für Photonische Technologien (IPHT), Jena.
02.2017 ‐ 02.2018
Bedeutung außeruniversitärer Forschungseinrichtungen für die Entwicklung von Betrieben und Regionen
Bundesministerium für Bildung und Forschung (BMBF)
01.2015 ‐ 12.2016
Evaluierung der GRW-Förderung in Sachsen-Anhalt
What Drives Innovation Output from Subsidized R&D Cooperation? — Project-level Evidence from Germany
in: Technovation, Nr. 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, Nr. 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.
The Identification of Regional Industrial Clusters Using Qualitative Input-Output Analysis (QIOA)
in: Regional Studies, Nr. 1, 2011
The 'cluster theory' has become one of the main concepts promoting regional competitiveness, innovation, and growth. As most empirical applications focus on measures of concentration of one industrial branch in order to identify regional clusters, the appropriate analysis of specific vertical relations is developing in this discussion. This paper tries to identify interrelated sectors via national input-output tables with the help of minimal flow analysis (MFA). 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 Nomenclature des Units Territoriales Statistiques (NUTS)-3 regions.
Economic Structure and Regional Performance in Germany, 2002-2007
in: European Planning Studies, Nr. 2, 2012
This paper explores the impact of industrial clusters on regional growth at the German labour market region level using a regional convergence model. Based on the results of an exploratory study of the geography of German industrial clusters, we are able to differentiate the impact of industrial clustering from a horizontal and a vertical perspective while taking regional convergence into consideration. The results indicate that in addition to an all-German process of convergence, a specific East German one can be identified. The different types of industrial clusters show mixed effects within this framework. While vertically isolated industrial clusters have a negative impact on regional growth in this period, positive growth effects can be identified when industrial clusters show an intra-regional vertical interconnectedness.
Identifying Industrial Clusters from a Multidimensional Perspective: Methodical Aspects with an Application to Germany
in: Papers in Regional Science, Nr. 2, 2011
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.
flexpaneldid: A Stata Toolbox for Causal Analysis with Varying Treatment Time and Duration
in: IWH-Diskussionspapiere, Nr. 3, 2020
The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) for the staggered treatment adoption design and a Stata tool that implements the approach. This flexible conditional difference-in-differences approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations. Introducing more flexibility enables the user to consider individual treatment periods for the treated observations and thus circumventing problems arising in canonical difference-in-differences approaches. The open-source flexpaneldid toolbox for Stata implements the developed approach and allows comprehensive robustness checks and quality tests. The core of the paper gives comprehensive examples to explain the use of the commands and its options on the basis of a publicly accessible data set.
Identifying Cooperation for Innovation – A Comparison of Data Sources
in: IWH-Diskussionspapiere, Nr. 1, 2019
The value of social network analysis is critically dependent on the comprehensive and reliable identification of actors and their relationships. We compare regional knowledge networks based on different types of data sources, namely, co-patents, co-publications, and publicly subsidised collaborative Research and Development projects. Moreover, by combining these three data sources, we construct a multilayer network that provides a comprehensive picture of intraregional interactions. By comparing the networks based on the data sources, we address the problems of coverage and selection bias. We observe that using only one data source leads to a severe underestimation of regional knowledge interactions, especially those of private sector firms and independent researchers. The key role of universities that connect many regional actors is identified in all three types of data.
The Regional Effects of Professional Sports Franchises – Causal Evidence from Four European Football Leagues
in: IWH-Diskussionspapiere, Nr. 10, 2018
We use the locational pattern of clubs in four major professional football leagues in Europe to test the causal effect of changes in premier league membership on regional employment and output growth at the NUTS 3 level. We rely on the relegation mode of the classical round-robin tournament in the European model of sport to develop a regression-discontinuity design. The results indicate small and significant negative short-term effects on regional employment and output in the sports-related economic sector when clubs are relegated from the premier division of the respective football league. In addition, we find small negative effects on overall regional employment growth. However, total regional gross value added remains unaffected, indicating that in the main it is the less productive jobs that disappear in the short-term.
Who Benefits from GRW? Heterogeneous Employment Effects of Investment Subsidies in Saxony Anhalt
in: IWH-Diskussionspapiere, Nr. 27, 2017
The paper estimates the plant level employment effects of investment subsidies in one of the most strongly subsidized German Federal States. We analyze the treated plants as a whole, as well as the influence of heterogeneity in plant characteristics and the economic environment. Modifying the standard matching and difference-in-difference approach, we develop a new procedure that is particularly useful for the evaluation of funding programs with individual treatment phases within the funding period. Our data base combines treatment, employment and regional information from different sources. So, we can relate the absolute effects to the amount of the subsidy paid. The results suggest that investment subsidies have a positive influence on the employment development in absolute and standardized figures – with considerable effect heterogeneity.
Identifying the Effects of Place-based Policies – Causal Evidence from Germany
in: IWH-Diskussionspapiere, Nr. 18, 2016
The German government provides discretionary investment grants to structurally weak regions to reduce regional disparities. We use a regression discontinuity design that exploits an exogenous discrete jump in the probability of receiving investment grants to identify the causal effects of the investment grant on regional outcomes. We find positive effects for regional gross value-added and productivity growth, but no effects for employment and gross wage growth.