IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_8741.html
   My bibliography  Save this paper

Robot Imports and Firm-Level Outcomes

Author

Listed:
  • Alessandra Bonfiglioli
  • Rosario Crinò
  • Harald Fadinger
  • Gino Gancia

Abstract

We use French data over the 1994-2013 period to study how imports of industrial robots affect firm-level outcomes. Compared to other firms operating in the same 5-digit sector, robot importers are larger, more productive, and employ a higher share of managers and engineers. Over time, robot import occurs after periods of expansion in firm size, and is followed by improvements in efficiency and a fall in demand for labor. Guided by a simple model, we develop various empirical strategies to identify the causal effects of robot adoption. Our results suggest that, while demand shocks generate a positive correlation between robot imports and employment, exogenous changes in automation lead to job losses. We also find that robot imports increase productivity and the employment share of high-skill professions, but have a weak effect on total sales. The latter result suggests that productivity gains from automation may not be entirely passed on to consumers in the form of lower prices.

Suggested Citation

  • Alessandra Bonfiglioli & Rosario Crinò & Harald Fadinger & Gino Gancia, 2020. "Robot Imports and Firm-Level Outcomes," CESifo Working Paper Series 8741, CESifo.
    • Handle: RePEc:ces:ceswps:_8741
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp8741.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Benjamin Moll & Lukasz Rachel & Pascual Restrepo, 2022. "Uneven Growth: Automation's Impact on Income and Wealth Inequality," Econometrica, Econometric Society, vol. 90(6), pages 2645-2683, November.
    2. Christian Broda & David E. Weinstein, 2006. "Globalization and the Gains From Variety," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(2), pages 541-585.
    3. Michael Koch & Ilya Manuylov & Marcel Smolka, 2021. "Robots and Firms," The Economic Journal, Royal Economic Society, vol. 131(638), pages 2553-2584.
    4. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    5. 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.
    6. Antoine Dechezleprêtre & David Hémous & Morten Olsen & Carlo Zanella, 2021. "Induced automation: evidence from firm-level patent data," ECON - Working Papers 384, Department of Economics - University of Zurich.
    7. David Autor & David Dorn & Lawrence F Katz & Christina Patterson & John Van Reenen, 2020. "The Fall of the Labor Share and the Rise of Superstar Firms [“Automation and New Tasks: How Technology Displaces and Reinstates Labor”]," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(2), pages 645-709.
    8. Sotiris Blanas & Gino Gancia & Sang Yoon (Tim) Lee, 2019. "Who is afraid of machines?," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 34(100), pages 627-690.
    9. Colin J. Hottman & Stephen J. Redding & David E. Weinstein, 2016. "Quantifying the Sources of Firm Heterogeneity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(3), pages 1291-1364.
    10. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    11. Emin Dinlersoz & Zoltan Wolf, 2024. "Automation, labor share, and productivity: plant-level evidence from U.S. manufacturing," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 33(4), pages 604-626, May.
    12. Chernozhukov, Victor & Hansen, Christian, 2008. "The reduced form: A simple approach to inference with weak instruments," Economics Letters, Elsevier, vol. 100(1), pages 68-71, July.
    13. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    14. Hong Cheng & Ruixue Jia & Dandan Li & Hongbin Li, 2019. "The Rise of Robots in China," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 71-88, Spring.
    15. Jaimovich, Nir & Saporta-Eksten, Itay & Siu, Henry & Yedid-Levi, Yaniv, 2021. "The macroeconomics of automation: Data, theory, and policy analysis," Journal of Monetary Economics, Elsevier, vol. 122(C), pages 1-16.
    16. 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.
    17. Jan De Loecker & Jan Eeckhout & Gabriel Unger, 2020. "The Rise of Market Power and the Macroeconomic Implications [“Econometric Tools for Analyzing Market Outcomes”]," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(2), pages 561-644.
    18. Wolfgang Dauth & Sebastian Findeisen & Jens Suedekum & Nicole Woessner, 2018. "Adjusting to Robots: Worker-Level Evidence," Opportunity and Inclusive Growth Institute Working Papers 13, Federal Reserve Bank of Minneapolis.
    19. Hémous, David & Dechezleprêtre, Antoine & Olsen, Morten & Zanella, carlo, 2019. "Automating Labor: Evidence from Firm-level Patent Data," CEPR Discussion Papers 14249, C.E.P.R. Discussion Papers.
    20. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    21. Francesco Caselli & Alan Manning, 2019. "Robot Arithmetic: New Technology and Wages," American Economic Review: Insights, American Economic Association, vol. 1(1), pages 1-12, June.
    22. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    23. James Bessen, 2019. "Automation and jobs: when technology boosts employment," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 34(100), pages 589-626.
    24. Wooldridge, Jeffrey M., 2009. "On estimating firm-level production functions using proxy variables to control for unobservables," Economics Letters, Elsevier, vol. 104(3), pages 112-114, September.
    25. repec:nbr:nberch:14019 is not listed on IDEAS
    26. Wiljan van den Berge, 2019. "Automatic Reaction – What Happens to Workers at Firms that Automate?," CPB Discussion Paper 390.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fan, Haichao & Hu, Yichuan & Tang, Lixin, 2021. "Labor costs and the adoption of robots in China," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 608-631.
    2. Domini, Giacomo & Grazzi, Marco & Moschella, Daniele & Treibich, Tania, 2022. "For whom the bell tolls: The firm-level effects of automation on wage and gender inequality," Research Policy, Elsevier, vol. 51(7).
    3. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the Digital Divide: Workers' Exposure to Digitalization and Its Consequences for Individual Employment," IZA Discussion Papers 14649, Institute of Labor Economics (IZA).
    4. Domini, Giacomo & Grazzi, Marco & Moschella, Daniele & Treibich, Tania, 2021. "Threats and opportunities in the digital era: Automation spikes and employment dynamics," Research Policy, Elsevier, vol. 50(7).
    5. Sergio De Nardis & Francesca Parente, 2022. "Technology and task changes in the major EU countries," Contemporary Economic Policy, Western Economic Association International, vol. 40(2), pages 391-413, April.
    6. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2021. "Stop worrying and love the robot: An activity-based approach to assess the impact of robotization on employment dynamics," GLO Discussion Paper Series 802, Global Labor Organization (GLO).
    7. Heyman, Fredrik & Norbäck, Pehr-Johan & Persson, Lars, 2021. "Automation, Work and Productivity: The Role of Firm Heterogeneity," Working Paper Series 1382, Research Institute of Industrial Economics, revised 09 Mar 2023.
    8. repec:hal:spmain:info:hdl:2441/7n49nkmngd8448a5ts5gt5ade0 is not listed on IDEAS
    9. Davide Dottori, 2021. "Robots and employment: evidence from Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 739-795, July.
    10. Calì, Massimiliano & Presidente, Giorgio, 2021. "Robots For Economic Development," GLO Discussion Paper Series 942, Global Labor Organization (GLO).
    11. Philippe Aghion & Céline Antonin & Simon Bunel, 2019. "Artificial Intelligence, Growth and Employment: The Role of Policy," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 149-164.
    12. Bürgisser, Reto, 2023. "Policy Responses to Technological Change in the Workplace," SocArXiv kwxn2, Center for Open Science.
    13. ARAI Kosuke & FUJIWARA Ippei & SHIROTA Toyoichiro, 2021. "Robot Penetration and Task Changes," Discussion papers 21093, Research Institute of Economy, Trade and Industry (RIETI).
    14. repec:spo:wpmain:info:hdl:2441/7n49nkmngd8448a5ts5gt5ade0 is not listed on IDEAS
    15. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    16. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    17. Leone, Fabrizio, 2021. "Foreign Ownership and Robot Adoption," CEPREMAP Working Papers (Docweb) 2111, CEPREMAP.
    18. Klump, Rainer & Jurkat, Anne & Schneider, Florian, 2021. "Tracking the rise of robots: A survey of the IFR database and its applications," MPRA Paper 107909, University Library of Munich, Germany.
    19. Philippe Aghion & Céline Antonin & Simon Bunel & Xavier Jaravel, 2022. "Modern manufacturing capital, labor demand, and product market dynamics: Evidence from France," SciencePo Working papers Main hal-03943312, HAL.
    20. Ke-Liang Wang & Ting-Ting Sun & Ru-Yu Xu, 2023. "The impact of artificial intelligence on total factor productivity: empirical evidence from China’s manufacturing enterprises," Economic Change and Restructuring, Springer, vol. 56(2), pages 1113-1146, April.
    21. Georg Graetz, 2019. "Labor Demand in the Past, Present, and Future," European Economy - Discussion Papers 114, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    22. Genz, Sabrina & Gregory, Terry & Janser, Markus & Lehmer, Florian & Matthes, Britta, 2021. "How Do Workers Adjust When Firms Adopt New Technologies?," IZA Discussion Papers 14626, Institute of Labor Economics (IZA).

    More about this item

    Keywords

    automation; displacement; firms; robots;
    All these keywords.

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_8741. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.