This paper looks at the surprisingly different labor market performance of the United States, Canada, Germany, and several other OECD countries during and after the Great Recession of 2008–9. A first important finding is that the large employment swings in the construction sector linked to the boom and bust in US housing markets is an important factor behind the different labor market performances of the three countries. We also find that cross-country differences among OECD countries are consistent with a conventional Okun relationship linking gross domestic product growth to employment performance.

Technological complementarity is argued to be a crucial element for effective R&D collaboration. The real structure is, however, still largely unknown. Based on the argument that organizations’ knowledge resources must fit for enabling collective learning and innovation, we use the co-occurrence of firms in collaborative R&D projects in Germany to assess inter-sectoral technological complementarity between 129 sectors. The results are mapped as complementarity space for the Germany economy. The space and its dynamics from 1990 to 2011 are analyzed by means of social network analysis. The results illustrate sectors being complements both from a dyadic and portfolio/network perspective. This latter is important, as complementarities may only become fully effective when integrated in a complete set of different knowledge resources from multiple sectors. The dynamic perspective moreover reveals the shifting demand for knowledge resources among sectors at different time periods.

Economists and business managers have long been interested in the impact of research and development (R&D) cooperation with scientific institutions on the innovation performance of firms. Recent research identifies a positive correlation between these two variables. This paper aims to contribute to the identification of the relationship between R&D cooperation with scientific institutions and the product and process innovation performance of firms by using a difference-in-difference approach. In doing so, we distinguish between two different types of scientific institutions: universities and governmental research institutes. For the econometric analyses, we use data from the German Community Innovation Survey. In total, data from up to 560 German service and manufacturing firms are available for the difference-in-difference analyses. The results suggest that R&D cooperation with universities and governmental research institutes has a positive effect on both product innovation and process innovation performance of firms.

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.

FuE-Kooperationen spielen eine bedeutende Rolle bei der Schaffung von Umweltinnovationen. Allerdings zeigt uns die Literatur, dass FuE-Kooperationen nicht immer vorteilhaft sind. Daher ist eine differenziertere Betrachtungsweise des Einflusses von FuE-Kooperationen auf die Fähigkeit von Unternehmen, Umweltinnovationen hervorzubringen, notwendig. Das Papier untersucht diesen Zusammenhang und differenziert dabei nach verschiedenen Typen von Kooperationspartnern wie Kunden, Lieferanten, Universitäten, staatlichen Forschungseinrichtungen, Konkurrenten, Beratern und anderen Firmen innerhalb der gleichen Firmengruppe. Zudem wird der Frage nachgegangen, ob Diversität von Kooperationspartnern einen Einfluss auf die Umweltinnovationsfähigkeit von Unternehmen hat. Dabei werden Daten von 2337 deutschen Unternehmen für eine Regressionsanalyse verwendet. Deutlich wird, dass FuE-Kooperationen mit Kunden, Lieferanten, Universitäten, staatlichen Forschungseinrichtungen, Beratern und anderen Firmen innerhalb der gleichen Firmengruppe einen signifikant positiven Einfluss auf die Umweltinnovationsfähigkeit haben. FuE-Kooperationen mit Konkurrenten haben keinen signifikanten Einfluss. Die Diversität von FuE-Kooperationspartnern hat ebenfalls einen signifikant positiven Einfluss auf die Umweltinnovationsfähigkeit.

This paper contributes to the discussion on the importance of physical distance in the emergence of cross-region collaborative Research and Development (R&D) interactions. The proximity theory, and its extensions, is used as a theoretical framework. A spatial interaction model for count data was implemented for the empirical analysis of German data from the period from 2005 to 2010. The results show that all tested proximity measurements (geographical, cognitive, social and institutional proximity) have a significant positive influence on collaboration intensity. The proximity paradox, however, cannot be confirmed for geographical, social and institutional proximity, but for cognitive proximity.

Even though state aid in order to rescue or restructure ailing companies is regularly granted by European governments, it is often controversially discussed. The aims for rescuing companies are manifold and vary from social, industrial and even political considerations. Well-known examples are Austrian Airlines (Austria) or MG Rover (Great Britain). Yet, this study aims to answer the question whether state aid is used effectively and whether the initial aim why aid has been paid has been reached, i.e. the survival of the company. By using data on rescued companies in the EU and applying a survival analysis, this paper investigates the survival rates of these companies up to 15 years after the aid has been paid. In addition, the results are compared to the survival rates of non-rescued companies which have also been in difficulties. The results suggest that despite the financial support, business failure is often only post-poned; best survival rates have firms with long-term restructuring, enterprises in Eastern Europe, smaller firms and mature companies. However, non-funded companies have an even higher ratio to go bankrupt.

The paper presents estimates for the impact of related variety, unrelated variety and the functions a region performs in the production process on regional employment growth in Germany. We argue that regions benefit from the existence of related activities that facilitate economic development. Thereby the sole reliance of the related and unrelated variety concept on standard industrial classifications (SIC) remains debatable. We offer estimations for establishing that conceptual progress can be made when the focus of analysis goes beyond solely considering industries. We develop an industry-function based approach of related and unrelated variety and test our hypothesis by the help of spatial panel approach. Our findings suggest that related variety as same as unrelated variety facilitate regional employment growth in Germany. However, the drivers behind these effects do differ. While the positive effect of related variety is driven by high degrees of relatedness in the regional “R&D” and “White-Collar”-functions, the effects of unrelated variety are spurred by “Blue Collar”-functions in this period.