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'Rust in peace': Why are Germany’s bridges and schools falling apart?Oliver HoltemöllerThe Guardian, June 3, 2025
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.