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Firmenpleiten auf höchstem Stand seit mehr als zwei JahrzehntenSteffen MüllerDer Spiegel, 9. April 2026
We use rich German administrative data to estimate new measures of skill transferability between manufacturing and other sectors. These measures capture the value of workers' human capital when applied in different sectors and are directly related to workers' displacement costs. We estimate these transferability measures using a selection correction model, which addresses workers' endogenous mobility, and a novel selection instrument based on the social network of workers. Our results indicate substantial heterogeneity in how workers can transfer their skills when they move across sectors, which implies heterogeneous displacement costs that depend on the sector to which workers reallocate.
In this paper, we study the domestic political determinants of military spending. Our conceptual framework suggests that power distribution over local and central governments influences the government provision of national public goods, in our context, military expenditure. Drawing on a large cross-country panel, we demonstrate that having local elections will decrease a country’s military expenditure markedly, controlling for other political and economic variables. According to our preferred estimates, a country’s military expenditure is on average 20% lower if its state government officials are locally elected, which is consistent with our theoretical prediction.
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.
We build on the analysis in Akcigit, Grigsby, and Nicholas (2017) by using US patent and census data to examine the relationship between immigration and innovation. We construct a measure of foreign born expertise and show that technology areas where immigrant inventors were prevalent between 1880 and 1940 experienced more patenting and citations between 1940 and 2000. The contribution of immigrant inventors to US innovation was substantial. We also show that immigrant inventors were more productive than native born inventors; however, they received significantly lower levels of labor income. The immigrant inventor wage-gap cannot be explained by differentials in productivity.
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.
Ample evidence indicates that a person’s human capital is important for success on the labor market in terms of both wages and employment prospects. However, unlike the efforts to identify the impact of school attainment on labor-market outcomes, the literature on returns to cognitive skills has not yet provided convincing evidence that the estimated returns can be causally interpreted. Using the PIAAC Survey of Adult Skills, this paper explores several approaches that aim to address potential threats to causal identification of returns to skills, in terms of both higher wages and better employment chances. We address measurement error by exploiting the fact that PIAAC measures skills in several domains. Furthermore, we estimate instrumental-variable models that use skill variation stemming from school attainment and parental education to circumvent reverse causation. Results show a strikingly similar pattern across the diverse set of countries in our sample. In fact, the instrumental-variable estimates are consistently larger than those found in standard least-squares estimations. The same is true in two “natural experiments,” one of which exploits variation in skills from changes in compulsory-schooling laws across U.S. states. The other one identifies technologically induced variation in broadband Internet availability that gives rise to variation in ICT skills across German municipalities. Together, the results suggest that least-squares estimates may provide a lower bound of the true returns to skills in the labor market.
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.
International data from the PIAAC survey allow estimation of comparable labor-market returns to skills for 32 countries. Returns to skills are larger in faster growing economies, consistent with the hypothesis that skills are particularly important for adaptation to economic change.
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.
We consider the simultaneity bias when examining the effect of individual risk attitudes on entrepreneurship. We demonstrate that entry into self-employment is related to changes in risk attitudes. We further show that these changes are correlated with the probability to remain in entrepreneurship.
