Researchers at Federal Reserve Bank Report New Data on Robotics (Automation and the Rise of Superstar Firms): Robotics

2025 MAY 09 (NewsRx) -- By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News -- Current study results on Robotics have been published. According to news reporting from San Francisco, California, by NewsRx journalists, research stated, “We provide empirical evidence suggesting that the rise of superstar firms is linked to automation. We explain this empirical link in a general equilibrium framework with heterogeneous firms and variable markups.”

The news correspondents obtained a quote from the research from Federal Reserve Bank, “Firms can operate a labor-only technology or, by paying a per-period fixed cost, an automation technology that uses both workers and robots. The fixed costs lead to an economy-of-scale effect of automation, such that larger and more productive firms are more likely to automate. Automation boosts labor productivity, allowing those large firms to expand further, raising industry concentration. Since robots substitute for workers, increased automation raises sales concentration more than employment concentration, consistent with empirical evidence.”

According to the news reporters, the research concluded: “Under our calibration, a modest robot subsidy mitigates markup distortions and improves welfare by stimulating automation investment, bringing aggregate output closer to the efficient level.”

This research has been peer-reviewed.

For more information on this research see: Automation and the Rise of Superstar Firms. Journal of Monetary Economics, 2025;151. Journal of Monetary Economics can be contacted at: Elsevier, Radarweg 29, 1043 Nx Amsterdam, Netherlands. (Elsevier - www.elsevier.com; Journal of Monetary Economics - http://www.journals.elsevier.com/journal-of-monetary-economics/)

Our news journalists report that additional information may be obtained by contacting Zheng Liu, Federal Reserve Bank, 101 Market St, San Francisco, CA 94595, United States. Additional authors for this research include Hamid Firooz and Yajie Wang.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.jmoneco.2025.103733. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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