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Wenn die AfD hier gewinnt, wären die Folgen überall in Deutschland deutlich zu spürenReint GroppDer Spiegel, 8. Januar 2026
The effects of private equity buyouts on employment, productivity, and job reallocation vary tremendously with macroeconomic and credit conditions, across private equity groups, and by type of buyout. We reach this conclusion by examining the most extensive database of U.S. buyouts ever compiled, encompassing thousands of buyout targets from 1980 to 2013 and millions of control firms. Employment shrinks 12% over two years after buyouts of publicly listed firms—on average, and relative to control firms—but expands 15% after buyouts of privately held firms. Postbuyout productivity gains at target firms are large on average and much larger yet for deals executed amid tight credit conditions. A postbuyout tightening of credit conditions or slowing of gross domestic product growth curtails employment growth and intrafirm job reallocation at target firms. We also show that buyout effects differ across the private equity groups that sponsor buyouts, and these differences persist over time at the group level. Rapid upscaling in deal flow at the group level brings lower employment growth at target firms. We relate these findings to theories of private equity that highlight agency problems at portfolio firms and within the private equity industry itself.
We use data from the Annual Survey of Manufactures to study the characteristics and geographic distribution of investments in robots across US manufacturing establishments. Robotics adoption and robot intensity (the number of robots per employee) cluster in "robot hubs." Establishments that report having robotics are larger and have a larger production worker share, lower pay per worker, lower labor share, and higher capital expenditures, including higher IT capital expenditures. Notably, establishments are more likely to have robots if other establishments in the same core-based statistical area and industry also report having robotics, suggestive of agglomeration and peer effects.
We use establishment-level data from the US Census Bureau's Annual Survey of Manufactures to study the characteristics and geographic locations of investments in robots. We find that the distribution of robots is highly skewed across locations. Some locations, which we call Robot Hubs, have far more robots than one would expect even after accounting for industry and manufacturing employment. We characterize these Robot Hubs along several industry, demographic, and institutional dimensions. The presences of robot integrators, which specialize in helping manufacturers install robots, and of higher levels of union membership are positively correlated with being a Robot Hub.
Immigration can expand labor supply and create greater competition for native-born workers. But immigrants may also start new firms, expanding labor demand. This paper uses U.S. administrative data and other data resources to study the role of immigrants in entrepreneurship. We ask how often immigrants start companies, how many jobs these firms create, and how these firms compare with those founded by U.S.-born individuals. A simple model provides a measurement framework for addressing the dual roles of immigrants as founders and workers. The findings suggest that immigrants act more as "job creators" than "job takers" and that non-U.S. born founders play outsized roles in U.S. high-growth entrepreneurship
The pace of job reallocation has declined in the United States in recent decades. We draw insight from canonical models of business dynamics in which reallocation can decline due to (i) lower dispersion of idiosyncratic shocks faced by businesses, or (ii) weaker marginal responsiveness of businesses to shocks. We show that shock dispersion has actually risen, while the responsiveness of business-level employment to productivity has weakened. Moreover, declining responsiveness can account for a significant fraction of the decline in the pace of job reallocation, and we find suggestive evidence this has been a drag on aggregate productivity.
Many observers, and many investors, believe that young people are especially likely to produce the most successful new firms. Integrating administrative data on firms, workers, and owners, we study start-ups systematically in the United States and find that successful entrepreneurs are middle-aged, not young. The mean age at founding for the 1-in-1,000 fastest growing new ventures is 45.0. The findings are similar when considering high-technology sectors, entrepreneurial hubs, and successful firm exits. Prior experience in the specific industry predicts much greater rates of entrepreneurial success. These findings strongly reject common hypotheses that emphasize youth as a key trait of successful entrepreneurs.
Modern market economies are characterized by the reallocation of resources from less productive, less valuable activities to more productive, more valuable ones. Businesses in the High Tech sector play a particularly important role in this reallocation by introducing new products and services that impact the entire economy. In this paper we describe an extension to the Census Bureau’s Business Dynamics Statistics that tracks job creation, job destruction, startups, and exits by firm and establishment characteristics, including sector, firm age, and firm size in the High Tech sector. We preview the resulting statistics, showing the structural shifts in the High Tech sector over the past 30 years, including the surge of entry and young firm activity in the 1990s that reversed abruptly in the early‐2000s.
The field of entrepreneurship is growing rapidly and expanding into new areas. This article presents a new compilation of administrative panel data on the universe of business start-ups in the United States, which will be useful for future research in entrepreneurship. To create the US start-up panel data set, the authors link the universe of non-employer firms to the universe of employer firms in the Longitudinal Business Database (LBD). Start-up cohorts of more than five million new businesses per year, which create roughly three million jobs, can be tracked over time. To illustrate the potential of the new start-up panel data set for future research, the authors provide descriptive statistics for a few examples of research topics using a representative start-up cohort.
We use Hurricane Katrina’s damage to the Mississippi coast in 2005 as a natural experiment to study business survival in the aftermath of a capital-destruction shock. We find very low survival rates for businesses that incurred physical damage, particularly for small firms and less-productive establishments. Conditional on survival, larger and more-productive businesses that rebuilt their operations hired more workers than their smaller and less-productive counterparts. Auxiliary evidence from the Survey of Business Owners suggests that the differential size effect is tied to the presence of financial constraints, pointing to a socially inefficient level of exits and to distortions of allocative efficiency in response to this negative shock. Over time, the size advantage disappeared and market mechanisms seem to prevail.
This paper discusses the construction of a new longitudinal database tracking inventors and patent-owning firms over time. We match granted patents between 2000 and 2011 to administrative databases of firms and workers housed at the U.S. Census Bureau. We use inventor information in addition to the patent assignee firm name to improve on previous efforts linking patents to firms. The triangulated database allows us to maximize match rates and provide validation for a large fraction of matches. In this paper, we describe the construction of the database and explore basic features of the data. We find patenting firms, particularly young patenting firms, disproportionally contribute jobs to the U.S. economy. We find that patenting is a relatively rare event among small firms but that most patenting firms are nevertheless small, and that patenting is not as rare an event for the youngest firms compared to the oldest firms. Although manufacturing firms are more likely to patent than firms in other sectors, we find that most patenting firms are in the services and wholesale sectors. These new data are a product of collaboration within the U.S. Department of Commerce, between the U.S. Census Bureau and the U.S. Patent and Trademark Office.
