This paper uses data from the 2019 Annual Business Survey to document that firms adopting advanced technologies are larger in terms of employment than other firms in their same industry and cohort. Using data from the Longitudinal Business Survey, we show that adopters were already large and growing faster before artificial intelligence, robotics, cloud computing, and specialized software systems became broadly available. These findings support the view that adopters are large because of selection and not because adopting advanced technologies for automation causally expands their employment.
This paper describes the adoption of automation technologies by US firms across all economic sectors by leveraging a new module introduced in the 2019 Annual Business Survey, conducted by the US Census Bureau in partnership with the National Center for Science and Engineering Statistics (NCSES). The module collects data from over 300,000 firms on the use of five advanced technologies: AI, robotics, dedicated equipment, specialized software, and cloud computing. The adoption of these technologies remains low (especially for AI and robotics), varies substantially across industries, and concentrates on large and young firms. However, because larger firms are much more likely to adopt them, 12-64% of US workers and 22-72% of manufacturing workers are exposed to these technologies. Firms report a variety of motivations for adoption, including automating tasks previously performed by labor. Consistent with the use of these technologies for automation, adopters have higher labor productivity and lower labor shares. In particular, the use of these technologies is associated with a 11.4% higher labor productivity, which accounts for 20-30% of the difference in labor productivity between large firms and the median firm in an industry. Adopters report that these technologies raised skill requirements and led to greater demand for skilled labor but brought limited or ambiguous effects to their employment levels.
Manufacturers perform the majority of US patenting and R&D. The decades-long decline of US manufacturing employment raises concerns that US innovation will falter. We investigate the relationship between between physical production and innovation by constructing a new dataset linking all US firms and their establishments to location geocodes and innovative activities. Pre- liminary results indicate that while firms with both manufacturing and innovation establishments exhibit higher patenting when these facilities are more spatially proximate, manufacturing firms’ overall contribution to US innovation declines steadily and substantially over time. Moreover, cohorts of firms permanently exiting manufacturing in the 1990s and 2000s continue to patent at their prior pace.