The spatial evolution of the German solar industry is analysed in the light of the “window of locational opportunity” and the “selection environment” approach. The paper argues that differences in the regions' ability to promote the emergence of local external economies contribute to increasing regional differentiation in the German structure of the industry. Applied empirical methods enclose longitudinal firm entry and network analysis. A special focus is given upon the realignment processes in the science system. Our findings show a relatively rapid spatial concentration of production in eastern Germany since the year 2000. This process is accompanied by intensified networking between firms and between firms and universities as well as research institutes. The responsiveness of regional institutions and the self-organizing capabilities of the solar firms substantiate some propositions of the “selection environment” approach.

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.

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 '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 Unite´s Territoriales Statistiques (NUTS)-3 regions.

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.

We study the wage and employment effects of a German place-based policy using a research design that exploits conditionally exogenous EU-wide rules governing the program parameters at the regional level. The place-based program subsidizes investments to create jobs with a subsidy rate that varies across labor market regions. The analysis uses matched data on the universe of establishments and their employees, establishment-level panel data on program participation, and regional scores that generate spatial discontinuities in program eligibility and generosity. These rich data enable us to study the incidence of the place-based program on different groups of individuals. We find that the program helps establishments create jobs that disproportionately benefit younger and less-educated workers. Funded establishments increase their wages but, unlike employment, wage gains do not persist in the long run. Employment effects estimated at the local area level are slightly larger than establishment-level estimates, suggesting limited spillover effects. Using subsidy rates as an instrumental variable for actual subsidies indicates that it costs approximately EUR 25,000 to create a new job in the economically disadvantaged areas targeted by the program.

This study estimates the establishment-level employment effects of investment grants in Germany. In addition to the average treatment effect for the treated, we focus on discrimination in the funding rules as potential source of effect heterogeneity. We combine the difference-in-differences approach of Callaway and Sant’Anna (2021) that explicitly models variation in treatment timing with a ties matching at the cohort level. We observe a positive effect of investment grants on employment development in the full sample. The subsample analysis yields strong evidence for effect heterogeneity due to firm characteristics and the economic environment.

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.

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.

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.