The Characteristics and Geographic Distribution of Robot Hubs in U.S. Manufacturing Establishments
Erik Brynjolfsson, Catherine Buffington, Nathan Goldschlag, J. Frank Li, Javier Miranda, Robert Seamans
IWH Discussion Papers,
No. 7,
2023
Abstract
We use data from the Annual Survey of Manufactures to study the characteristics and geography of investments in robots across U.S. manufacturing establishments. We find that robotics adoption and robot intensity (the number of robots per employee) is much more strongly related to establishment size than age. We find that establishments that report having robotics have higher capital expenditures, including higher information technology (IT) capital expenditures. Also, establishments are more likely to have robotics if other establishments in the same Core-Based Statistical Area (CBSA) and industry also report having robotics. The distribution of robots is highly skewed across establishments’ 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 presence of robot integrators and higher levels of union membership are positively correlated with being a Robot Hub.
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14.03.2023 • 7/2023
Gas storages full – economic outlook less gloomy
The severe slump in the German economy expected last fall has not materialised because gas supply stabilises. However, due to high inflation, higher real interest rates and declining real incomes, the economy is likely to remain weak. In its spring forecast, the Halle Institute for Economic Research (IWH) expects production to grow by just 0.4% in 2023, and inflation to remain high at 5.8%.
Oliver Holtemöller
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On the Employment Consequences of Automation and Offshoring: A Labor Market Sorting View
Ester Faia, Sébastien Laffitte, Maximilian Mayer, Gianmarco Ottaviano
Lili Yan Ing, Gene M. Grossman (eds), Robots and AI: A New Economic Era. Routledge: London,
2022
Abstract
We argue that automation may make workers and firms more selective in matching their specialized skills and tasks. We call this phenomenon “core-biased technological change”, and wonder whether something similar could be relevant also for offshoring. Looking for evidence in occupational data for European industries, we find that automation increases workers’ and firms’ selectivity as captured by longer unemployment duration, less skill-task mismatch, and more concentration of specialized knowledge in specific tasks. This does not happen in the case of offshoring, though offshoring reinforces the effects of automation. We show that a labor market model with two-sided heterogeneity and search frictions can rationalize these empirical findings if automation strengthens while offshoring weakens the assortativity between workers’ skills and firms’ tasks in the production process, and automation and offshoring complement each other. Under these conditions, automation decreases employment and increases wage inequality whereas offshoring has opposite effects.
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