Evaluation of Subsidy Programmes
This research group focuses on two main research questions: (i) What is the causal effect of cooperative innovation activities on the performance of firms and regions? (ii) What are the causal effects of public Research and Development (R&D) support schemes on the performance of firms and regions? The first research question concerns the dynamics of firms and regions as a result of their different innovation activities. We apply a micro-based integrative perspective on innovative activities which allows identifying causal effects of cooperative activities on specific outcomes (e. g., patent applications, scientific publications, employment growth, or productivity growth). Concerning the second research question, recent studies mainly focus on the evaluation of one specific subsidy scheme. Research in this group aims to overcome this shortcoming by considering various support schemes. Indicators for the firms’ success are (amongst others) patent applications and employment growth. The results allow insights for the future design of innovation support schemes.
Research ClusterInstitutions and Social Norms
09.2019 ‐ 09.2022
Establishing Evidence-based Evaluation Methods for Subsidy Programmes in Germany (EVA-KULT)
European Regional Development Fund (ERDF)
The project aims at expanding the Centre for Evidence-based Policy Advice at the Halle Institute for Economic Research (IWH-CEP).
01.2018 ‐ 12.2020
Networked growth - Innovative Saxony-Anhalt through digital business models (Competence Center 4.0)
Federal Ministry for Economic Affairs and Energy (BMWI)
01.2017 ‐ 12.2018
Political Participation in Eastern Germany
Federal Ministry for Economic Affairs and Energy (BMWI)
12.2015 ‐ 11.2018
Socio-economic Effects of Research on Innovative Approaches for POC Diagnostics
Federal Ministry of Education and Research (BMBF)
Part of the EXASENS project. Coordinated by the Leibniz Institute of Photonic Technology (IPHT) in Jena, nine Leibniz institutes are working together on researching point-of-care (POC) technology for the prediction and diagnosis of chronic inflammatory respiratory diseases. See press release.
02.2017 ‐ 02.2018
The Importance of Non-University Research Institutions for the Development of Firms and Regions (Be_For_Reg-Projekt)
Federal Ministry of Education and Research (BMBF)
01.2015 ‐ 12.2016
Evaluation of the "Joint Task 'Improving the Regional Economic Structure'" in the Federal State of Saxony-Anhalt
R&D Collaborations and the Role of Proximity
in: Regional Studies, No. 12, 2017
R&D collaborations and the role of proximity. Regional Studies. This paper explores the impact of proximity measures on knowledge exchange measured by granted research and development (R&D) collaboration projects in German NUTS-3 regions. The results are obtained from a spatial interaction model including eigenvector spatial filters. Not only geographical but also other forms of proximity (technological, organizational and institutional) have a significant influence on the emergence of collaborations. Furthermore, the results suggest interdependences between proximity measures. Nevertheless, the analysis does not show that other forms of proximity may compensate for missing geographical proximity. The results indicate that (subsidized) collaborative innovation activities tend to cluster.
Benchmark Value-added Chains and Regional Clusters in R&D-intensive Industries
in: International Regional Science Review, No. 5, 2017
Although the phase of euphoria seems to be over, policy makers and regional agencies have maintained their interest in cluster policy. Modern cluster theory provides reasons for positive external effects that may accrue from interaction in a group of proximate enterprises operating in common and related fields. Although there has been some progress in locating clusters, in most cases only limited knowledge on the geographical extent of regional clusters has been established. In the present article, we present a hybrid approach to cluster identification. Dominant buyer–supplier relationships are derived by qualitative input–output analysis from national input–output tables, and potential regional clusters are identified by spatial scanning. This procedure is employed to identify clusters of German research and development-intensive industries. A sensitivity analysis reveals good robustness properties of the hybrid approach with respect to variations in the quantitative cluster composition.
Joint R&D Subsidies, Related Variety, and Regional Innovation
in: International Regional Science Review, No. 3, 2017
Subsidies for research and development (R&D) are an important tool of public R&D policy, which motivates extensive scientific analyses and evaluations. This article adds to this literature by arguing that the effects of R&D subsidies go beyond the extension of organizations’ monetary resources invested into R&D. It is argued that collaboration induced by subsidized joint R&D projects yield significant effects that are missed in traditional analyses. An empirical study on the level of German labor market regions substantiates this claim, showing that collaborative R&D subsidies impact regions’ innovation growth when providing access to related variety and embedding regions into central positions in cross-regional knowledge networks.
Complex-task Biased Technological Change and the Labor Market
in: Review of Economic Dynamics, April 2017
In this paper we study the relationship between task complexity and the occupational wage- and employment structure. Complex tasks are defined as those requiring higher-order skills, such as the ability to abstract, solve problems, make decisions, or communicate effectively. We measure the task complexity of an occupation by performing Principal Component Analysis on a broad set of occupational descriptors in the Occupational Information Network (O*NET) data. We establish four main empirical facts for the U.S. over the 1980–2005 time period that are robust to the inclusion of a detailed set of controls, subsamples, and levels of aggregation: (1) There is a positive relationship across occupations between task complexity and wages and wage growth; (2) Conditional on task complexity, routine-intensity of an occupation is not a significant predictor of wage growth and wage levels; (3) Labor has reallocated from less complex to more complex occupations over time; (4) Within groups of occupations with similar task complexity labor has reallocated to non-routine occupations over time. We then formulate a model of Complex-Task Biased Technological Change with heterogeneous skills and show analytically that it can rationalize these facts. We conclude that workers in non-routine occupations with low ability of solving complex tasks are not shielded from the labor market effects of automatization.
Mapping Potentials for Input-Output Based Innovation Flows in Industrial Clusters – An Application to Germany
in: Economic Systems Research, No. 4, 2016
Our paper pursues two aims: first, it presents an approach based on input–output innovation flow matrices to study intersectoral innovation flows within industrial clusters. Second, we apply this approach to the identification of structural weaknesses in East Germany relative to the western part of the country. The case of East Germany forms an interesting subject because while its convergence process after unification began promisingly in the first half of the 1990s, convergence has since slowed down. The existing gap can now be traced mainly to structural weaknesses in the East German economy, such as the absence of strong industrial cluster structures. With this in mind, we investigate whether East Germany does in fact reveal the abovementioned structural weaknesses. Does East Germany possess fewer industrial clusters? Are they less connected? Does East Germany lack specific clusters that are also important for the non-clustered part of the economy?
flexpaneldid: A Stata Command for Causal Analysis with Varying Treatment Time and Duration
in: IWH Discussion Papers, No. 5, 2019
The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) and its Stata implementation, the command flexpaneldid. The approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations (like investment grants or other subsidy schemes). Introducing more flexibility enables the user to consider individual treatment and outcome periods for the treated observations. The flexpaneldid command for panel data implements the developed flexible difference-in-differences approach and commonly used alternatives like CEM Matching and difference-in-differences models. The novelty of this tool is an extensive data preprocessing to include time information into the matching approach and the treatment effect estimation. The core of the paper gives two comprehensive examples to explain the use of flexpaneldid and its options on the basis of a publicly accessible data set.
Identifying Cooperation for Innovation – A Comparison of Data Sources
in: IWH Discussion Papers, No. 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 Discussion Papers, No. 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 Discussion Papers, No. 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 Discussion Papers, No. 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.