The bioeconomy links industrial and agricultural research and production and is expected to provide growth, particularly in rural areas. However, it is still unclear which companies, research institutes and universities make up the bioeconomy. This makes it difficult to evaluate the policy measures that support the bioeconomy. The aim of this article is to provide an inventory of relevant actors in the three Central German states of Saxony, Saxony-Anhalt and Thuringia. First we take an in-depth look at the different sectors, outline the industries involved, note the location and age of the enterprises and examine the distribution of important European industrial activity classification (NACE) codes. Our results underline the fact that established industry classifications are insufficient in identifying the plant-based bioeconomy population. We also question the overly optimistic statements regarding growth potentials in rural areas and employment potentials in general.

Global economic activity appears to be expanding rapidly during spring 2017. Confidence among managers is either strong or has improved in all major regions, and world trade and industrial production have, after two years of weakness, picked up markedly during last winter. For 2 ½ years, the euro area economy has now been constantly expanding at an annual rate of about 1.6%, slightly above potential. Employment has also been expanding steadily. Production and employment have been recently rising almost everywhere, including countries such as France and Italy where unemployment rates still do not appear to be on a downward trend. Official investment data for 2015 and 2016 appear to be distorted: big multinational firms relocated parts of their assets (intellectual property products in particular) or their registered business offices from countries outside the euro area to Ireland. As a consequence, reported gross fixed capital formation in Ireland expanded by 33% in 2015 and by 45% in 2016. Without this effect, investment growth in the euro area is about one percentage point lower in 2015 and 2016. Headline inflation hit 2% in February, but this was only the effect of higher world oil prices. The core rate is stubbornly at slightly below 1%, and wages rise annually by scarcely 1.5%. The revival of the economy will have to continue for considerably more time until inflation will come close to the ECB target zone. As monetary conditions continue to support growth, financial policies will be slightly expansive, and a certain external stimulus should come from the apparent recovery of world trade. Overall, we forecast euro area GDP to expand by 1.7% in both 2017 and 2018. However, policy uncertainty is substantial and could have a negative effect. In particular, elections in member states might give power to movements that aim at disintegrating Europe. Such a turn could rapidly undermine confidence, in particular in the financial strength of highly indebted member states.

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.

The growth of the private equity industry has spurred concerns about its impact on the economy. This analysis looks across nations and industries to assess the impact of private equity on industry performance. We find that industries where private equity funds invest grow more quickly in terms of total production and employment and appear less exposed to aggregate shocks. Our robustness tests provide some evidence that is consistent with our effects being driven by our preferred channel.

Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of start‐ups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a nonemployer to employer firm among start‐ups. Several interesting patterns emerge regarding the dynamics of nonemployer start‐ups hiring their first employee. Hiring rates among the universe of nonemployer start‐ups are very low, but increase when the population of nonemployers is focused on more growth‐oriented businesses such as incorporated and employer identification number businesses. If nonemployer start‐ups hire, the bulk of hiring occurs in the first few years of existence. After this point in time, relatively few nonemployer start‐ups hire an employee. Focusing on more growth‐ and employment‐oriented start‐ups in the KFS, we find that Asian‐owned and Hispanic‐owned start‐ups have higher rates of hiring their first employee than white‐owned start‐ups. Female‐owned start‐ups are roughly 10 percentage points less likely to hire their first employee by the first, second, and seventh years after start‐up. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that nonemployers hire their first employee.

The contribution of this thesis is to widen the focus of the literature on related variety. So far, this line of research has a strong focus on technological relatedness and cognitive proximity (Boschma et al. 2015). This thesis puts emphasis on three dimensions of relatedness that not yet been at the heart of research: input-output linkages and vertically related variety, the occupational dimensions of relatedness as well as insights from a project level R&D efforts and their relevance for the analysis of technological relatedness. We contribute to the understanding of how the specific composition and the degree of relatedness of economic agents in space shape their ability to generate variety in terms of entry of new occupational specialisations in regions. We enhance the understanding of how related variety affects different regional outcomes such employment growth and innovation and offer insights into the structure of inter-industry relations from a technological perspective and explains how the rise of certain technologies shapes inter-industry relatedness patterns.

The pace of business dynamism and entrepreneurship in the U.S. has declined over recent decades. We show that the character of that decline changed around 2000. Since 2000 the decline in dynamism and entrepreneurship has been accompanied by a decline in high-growth young firms. Prior research has shown that the sustained contribution of business startups to job creation stems from a relatively small fraction of high-growth young firms. The presence of these high-growth young firms contributes to a highly (positively) skewed firm growth rate distribution. In 1999, a firm at the 90th percentile of the employment growth rate distribution grew about 31 percent faster than the median firm. Moreover, the 90−50 differential was 16 percent larger than the 50−10 differential reflecting the positive skewness of the employment growth rate distribution. We show that the shape of the firm employment growth distribution changes substantially in the post-2000 period. By 2007, the 90−50 differential was only 4 percent larger than the 50−10, and it continued to exhibit a trend decline through 2011. The overall decline reflects a sharp drop in the 90th percentile of the growth rate distribution accounted for by the declining share of young firms and the declining propensity for young firms to be high-growth firms.

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.

A growing body of evidence indicates that the U.S. economy has become less dynamic in recent years. This trend is evident in declining rates of gross job and worker flows as well as declining rates of entrepreneurship and young firm activity, and the trend is pervasive across industries, regions, and firm size classes. We describe the evidence on these changes in the U.S. economy by reviewing existing research. We then describe new empirical facts about the relationship between establishment-level productivity and employment growth, framing our results in terms of canonical models of firm dynamics and suggesting empirically testable potential explanations.