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The Characteristics and Geographic Distribution of Robot Hubs in U.S. Manufacturing Establishments

Author

Listed:
  • Erik Brynjolfsson

    (Stanford University and NBER)

  • Catherine Buffington

    (U.S. Census Bureau)

  • Nathan Goldschlag

    (U.S. Census Bureau)

  • J. Frank Li

    (Stanford University)

  • Javier Miranda

    (Halle Institute for Economic Research (IWH), and Friedrich-Schiller University Jena)

  • Robert Seamans

    (New York University)

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.

Suggested Citation

  • Erik Brynjolfsson & Catherine Buffington & Nathan Goldschlag & J. Frank Li & Javier Miranda & Robert Seamans, 2023. "The Characteristics and Geographic Distribution of Robot Hubs in U.S. Manufacturing Establishments," Jena Economics Research Papers 2023-014, Friedrich-Schiller-University Jena.
    • Handle: RePEc:jrp:jrpwrp:2023-014
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    References listed on IDEAS

    as
    1. Jay Dixon & Bryan Hong & Lynn Wu, 2021. "The Robot Revolution: Managerial and Employment Consequences for Firms," Management Science, INFORMS, vol. 67(9), pages 5586-5605, September.
    2. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    3. Daron Acemoglu & Claire Lelarge & Pascual Restrepo, 2020. "Competing with Robots: Firm-Level Evidence from France," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 383-388, May.
    4. Manav Raj & Robert Seamans, 2018. "Artificial Intelligence, Labor, Productivity, and the Need for Firm-Level Data," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 553-565, National Bureau of Economic Research, Inc.
    5. Nathan Goldschlag & Antonio Jones & Javier Miranda & Justin Z. Smith, 2022. "Imputing Establishment Robotics Data: I’m Afraid I Can’t Do That," CES Technical Notes Series 22-07, Center for Economic Studies, U.S. Census Bureau.
    6. Timothy F. Bresnahan & Erik Brynjolfsson & Lorin M. Hitt, 2002. "Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-Level Evidence," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(1), pages 339-376.
    7. Daron Acemoglu & Gary W. Anderson & David N. Beede & Catherine Buffington & Eric E. Childress & Emin Dinlersoz & Lucia S. Foster & Nathan Goldschlag & John C. Haltiwanger & Zachary Kroff & Pascual Res, 2024. "Automation and the Workforce: A Firm-Level View from the 2019 Annual Business Survey," NBER Chapters, in: Technology, Productivity, and Economic Growth, National Bureau of Economic Research, Inc.
    8. Barry T. Hirsch & David A. MacPherson, 2003. "Union Membership and Coverage Database from the Current Population Survey: Note," ILR Review, Cornell University, ILR School, vol. 56(2), pages 349-354, January.
    9. Faber, Marius, 2020. "Robots and reshoring: Evidence from Mexican labor markets," Journal of International Economics, Elsevier, vol. 127(C).
    10. Wolfgang Dauth & Sebastian Findeisen & Jens Suedekum & Nicole Woessner, 2021. "The Adjustment of Labor Markets to Robots [“Skills, Tasks and Technologies: Implications for Employment and Earnings]," Journal of the European Economic Association, European Economic Association, vol. 19(6), pages 3104-3153.
    11. Catherine Buffington & Javier Miranda & Robert Seamans, 2018. "Development of Survey Questions on Robotics Expenditures and Use in U.S. Manufacturing Establishments," Working Papers 18-44, Center for Economic Studies, U.S. Census Bureau.
    12. Henry Chen & Paul Gompers & Anna Kovner & Josh Lerner, 2010. "Buy Local? The Geography of Venture Capital," NBER Chapters, in: Cities and Entrepreneurship, National Bureau of Economic Research, Inc.
    13. Marc F. Bellemare & Casey J. Wichman, 2020. "Elasticities and the Inverse Hyperbolic Sine Transformation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(1), pages 50-61, February.
    14. Melissa C. Chow & Teresa C. Fort & Christopher Goetz & Nathan Goldschlag & James Lawrence & Elisabeth Ruth Perlman & Martha Stinson & T. Kirk White, 2021. "Redesigning the Longitudinal Business Database," NBER Working Papers 28839, National Bureau of Economic Research, Inc.
    15. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    16. Ron S Jarmin & Javier Miranda, 2002. "The Longitudinal Business Database," Working Papers 02-17, Center for Economic Studies, U.S. Census Bureau.
    17. Nancey Green Leigh & Heonyeong Lee & Benjamin Kraft, 2022. "Disparities in robot adoption among U.S. manufacturers: a critical economic development challenge," Industry and Innovation, Taylor & Francis Journals, vol. 29(9), pages 1025-1044, October.
    18. Erik Brynjolfsson & Wang Jin & Kristina McElheran, 2021. "The power of prediction: predictive analytics, workplace complements, and business performance," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 56(4), pages 217-239, October.
    19. Glenn Ellison & Edward L. Glaeser & William R. Kerr, 2010. "What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns," American Economic Review, American Economic Association, vol. 100(3), pages 1195-1213, June.
    20. Tom Mitchell & Erik Brynjolfsson, 2017. "Track how technology is transforming work," Nature, Nature, vol. 544(7650), pages 290-292, April.
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    More about this item

    Keywords

    robot; technology adoption; manufacturing; labor;
    All these keywords.

    JEL classification:

    • L64 - Industrial Organization - - Industry Studies: Manufacturing - - - Other Machinery; Business Equipment; Armaments
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital
    • O36 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Open Innovation
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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