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Is this really the ‘most dangerous man in Germany’?IWHThe Spectator, August 23, 2026
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.
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.
Using long-running data from the German Socio-Economic Panel (1984–2012), we investigate the impact of paternal unemployment on child labour market and education outcomes. We first describe correlation patterns and then use sibling fixed effects and the Gottschalk (1996) method to identify the causal effects of paternal unemployment. We find different patterns for sons and daughters. Paternal unemployment does not seem to causally affect the outcomes of sons. In contrast, it increases both daughters’ worklessness and educational attainment. We test the robustness of the results and explore potential explanations.
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.
In this paper we analyze the relationship between turnover-driven growth and subjective well-being. Our model of innovation-led growth and unemployment predicts that: (i) the effect of creative destruction on expected individual welfare should be unambiguously positive if we control for unemployment, less so if we do not; (ii) job creation has a positive and job destruction has a negative impact on well-being; (iii) job destruction has a less negative impact in areas with more generous unemployment insurance policies; and (iv) job creation has a more positive effect on individuals that are more forward-looking. The empirical analysis using cross sectional MSA (metropolitan statistical area)-level and individual-level data provide empirical support to these predictions.
Our paper pursues two aims: first, it presents an approach based on input–output innovation flow matrices to study intersectoral innovation flows within industrial clusters. Second, we apply this approach to the identification of structural weaknesses in East Germany relative to the western part of the country. The case of East Germany forms an interesting subject because while its convergence process after unification began promisingly in the first half of the 1990s, convergence has since slowed down. The existing gap can now be traced mainly to structural weaknesses in the East German economy, such as the absence of strong industrial cluster structures. With this in mind, we investigate whether East Germany does in fact reveal the abovementioned structural weaknesses. Does East Germany possess fewer industrial clusters? Are they less connected? Does East Germany lack specific clusters that are also important for the non-clustered part of the economy?
We empirically analyze whether support by the parent organization in the early (nascent and seed) stage speeds up the process of commercialization and helps spin-offs from public research organizations generate first revenues sooner. To identify the impact of support by the parent organization, we apply multivariate regression techniques as well as an instrumental variable approach. Our results show that support in the early stage by the parent organization can speed up commercialization. Moreover, we identify two distinct channels—the help in developing a business plan and in acquiring external capital—through which support by the parent organization can enable spin-offs to generate first revenues sooner.
