It has been frequently argued that a firm’s location in the core of an industry’s innovation network improves its ability to access information and absorb technological knowledge. The literature has still widely neglected the role of peripheral network positions for innovation processes. In addition to this, little is known about the determinants affecting a peripheral actors’ ability to reach the core. To shed some light on these issues, we have employed a unique longitudinal dataset encompassing the entire population of German laser source manufacturers (LSMs) and laser-related public research organizations (PROs) over a period of more than two decades. The aim of our paper is threefold. First, we analyze the emergence of core–periphery (CP) patterns in the German laser industry. Then, we explore the paths on which LSMs and PROs move from isolated positions toward the core. Finally, we employ non-parametric event history techniques to analyze the extent to which organizational and geographical determinates affect the propensity and timing of network core entries. Our results indicate the emergence and solidification of CP patterns at the overall network level. We also found that the paths on which organizations traverse through the network are characterized by high levels of heterogeneity and volatility. The transition from peripheral to core positions is impacted by organizational characteristics, while an organization’s geographical location does not play a significant role.

The literature on the impact of R&D collaboration on environmental innovation performance of firms suggests that R&D collaboration is not always beneficial. Therefore, a more detailed analysis of the effects of R&D collaboration is necessary. This paper investigates the impact of R&D collaboration with different partner types on a firm’s environmental innovation performance. In addition, the paper addresses the question of whether the diversity of R&D collaboration partners is important to environmental innovation performance. Firm-level data from 2337 German firms are used in the regression analysis. The results suggest that R&D collaboration with suppliers, customers, universities, governmental research institutes, consultants and other firms within the same firm group has a significant positive impact on a firm’s environmental innovation performance, whereas collaboration with competitors has no significant impact. The diversity of R&D collaboration partners has a significantly positive impact on a firm’s environmental innovation performance.

The drivers of the spatial emergence and clustering of the photovoltaic industry in Germany. Following the relatedness literature, we explore to what extent related industries influenced the regional emergence of the photovoltaic (PV) industry. In addition, we shed light on factors explaining selective processes of clustering. We particularly argue that generic resources and resources of related activities have been crucial for the regional concentration in early phases of the industry life cycle. With increasing maturity, industry-specific resources became more important. Based on a unique dataset containing population dynamics of the German PV industry, the hypotheses are tested empirically. Our results partially confirm the assumed beneficial effects of related industries for the emergence of the PV industry. Moreover, we observe changes in the relative importance of factors supporting regional concentration, with industry-specific resources becoming dominant as the industry matures.

The aim of this paper is to contribute to the literature on internationalised research and development by investigating determinants of knowledge and technology transfer between foreign subsidiaries and the local economy in European post-transition economies. This inquiry leads to a better understanding of determinants that influence this knowledge and technology exchange. Applying a logit model, we find that, in particular, the foreign subsidiary’s corporate governance structure, its embeddedness in the multinational enterprise’s internal knowledge base, its own technological capacity, the growth of the regional knowledge stock and the regional sectoral diversification are all positively associated with the transfer of knowledge. Subsidiaries’ investment motives and the relative weight of the sector of investment in the region’s economy appear to be of less importance. The analysis focuses on European post-transition economies, using the example of five selected Central Eastern European countries and East Germany. We exploit a unique dataset, the IWH FDI Micro database, which contains information on one thousand two hundred forty-five foreign subsidiaries in this region.

Administrative data from a large and diverse community college are used to examine if underrepresented minority students benefit from taking courses with underrepresented minority instructors. To identify racial interactions we estimate models that include both student and classroom fixed effects and focus on students with limited choice in courses. We find that the performance gap in terms of class dropout rates and grade performance between white and underrepresented minority students falls by 20 to 50 percent when taught by an underrepresented minority instructor. We also find these interactions affect longer term outcomes such as subsequent course selection, retention, and degree completion.

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 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.

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.

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.