IDEAS home Printed from https://ideas.repec.org/p/ipt/laedte/201908.html
   My bibliography  Save this paper

The impact of robots on labour productivity: A panel data approach covering 9 industries and 12 countries

Author

Abstract

Based on the expectation that the intensified use of robots contributes to the growth of labour productivity, this paper presents estimates of Cobb-Douglas production functions, using data for 12 EU countries and 9 manufacturing industries. The empirical results for the models pooling all available data confirm that stocks of robots per 1 million Euros non-ICT capital input contribute significantly to labour productivity growth in the period from 1995 to 2015. The results remain robust, when the whole observation period is split into two subsamples from 1995 to 2007 and from 2008 to 2015. Furthermore, the model is used to assess the impact of an increase of robots use on the labour productivity in each of the 9 manufacturing industries considered.

Suggested Citation

  • Andre Jungmittag & Annarosa Pesole, 2019. "The impact of robots on labour productivity: A panel data approach covering 9 industries and 12 countries," JRC Working Papers on Labour, Education and Technology 2019-08, Joint Research Centre.
    • Handle: RePEc:ipt:laedte:201908
    as

    Download full text from publisher

    File URL: https://publications.jrc.ec.europa.eu/repository/handle/JRC118044
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carol Corrado & Charles Hulten & Daniel Sichel, 2009. "Intangible Capital And U.S. Economic Growth," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(3), pages 661-685, September.
    2. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    3. Michael Koch & Ilya Manuylov & Marcel Smolka, 2021. "Robots and Firms," The Economic Journal, Royal Economic Society, vol. 131(638), pages 2553-2584.
    4. 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.
    5. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    6. Mary O'Mahony & Marcel P. Timmer, 2009. "Output, Input and Productivity Measures at the Industry Level: The EU KLEMS Database," Economic Journal, Royal Economic Society, vol. 119(538), pages 374-403, June.
    7. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2017. "Robots and the skill premium: An automation-based explanation of wage inequality," Hohenheim Discussion Papers in Business, Economics and Social Sciences 29-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    8. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," Boston University - Department of Economics - Working Papers Series dp-297, Boston University - Department of Economics.
    9. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    10. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    11. Arellano, M, 1987. "Computing Robust Standard Errors for Within-Groups Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 49(4), pages 431-434, November.
    12. Prettner, Klaus, 2019. "A Note On The Implications Of Automation For Economic Growth And The Labor Share," Macroeconomic Dynamics, Cambridge University Press, vol. 23(3), pages 1294-1301, April.
    13. Dauth, Wolfgang & Findeisen, Sebastian & Südekum, Jens & Wößner, Nicole, 2017. "German robots - the impact of industrial robots on workers," IAB-Discussion Paper 201730, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    14. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
    15. Südekum, Jens & Dauth, Wolfgang & Findeisen, Sebastian & Woessner, Nicole, 2017. "German Robots – The Impact of Industrial Robots on Workers," CEPR Discussion Papers 12306, C.E.P.R. Discussion Papers.
    16. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    17. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andreas Eder & Wolfgang Koller & Bernhard Mahlberg, 2024. "The contribution of industrial robots to labor productivity growth and economic convergence: a production frontier approach," Journal of Productivity Analysis, Springer, vol. 61(2), pages 157-181, April.
    2. Saam Marianne, 2024. "The Impact of Artificial Intelligence on Productivity and Employment – How Can We Assess It and What Can We Observe?," Intereconomics: Review of European Economic Policy, Sciendo, vol. 59(1), pages 22-27, February.
    3. Fernández-Macías, Enrique & Klenert, David & Antón, José-Ignacio, 2021. "Not so disruptive yet? Characteristics, distribution and determinants of robots in Europe," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 76-89.
    4. Antón, José-Ignacio & Fernández-Macías, Enrique & Winter-Ebmer, Rudolf, 2020. "Does Robotization Affect Job Quality? Evidence from European Regional Labour Markets," IZA Discussion Papers 13975, Institute of Labor Economics (IZA).
    5. Duan, Dingyun & Chen, Shaojian & Feng, Zongxian & Li, Jun, 2023. "Industrial robots and firm productivity," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 388-406.
    6. Zoltan Csefalvay & Petros Gkotsis, 2020. "Global race for robotisation - Looking at the entire robotisation chain," JRC Research Reports JRC121184, Joint Research Centre.
    7. Antonio Francesco Gravina & Neil Foster-McGregor, 2024. "Unraveling wage inequality: tangible and intangible assets, globalization and labor market regulations," Empirical Economics, Springer, vol. 67(4), pages 1375-1420, October.
    8. Septimiu Szabo, 2020. "Transition to Industry 4.0 in the Visegrád Countries," European Economy - Economic Briefs 052, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    9. MARSCHINSKI Robert & DE AMORES HERNANDEZ Antonio & AMOROSO Sara & BAUER Peter & CARDANI Roberta & CSEFALVAY Zoltan & GENTY Aurelien & GKOTSIS Petros & GREGORI Wildmer & GRASSANO Nicola & HERNANDEZ GUE, 2021. "EU competitiveness: recent trends, drivers, and links to economic policy: A Synthesis Report," JRC Research Reports JRC123232, Joint Research Centre.
    10. Andre Jungmittag, 2021. "Robotisation of the manufacturing industries in the EU: Convergence or divergence?," The Journal of Technology Transfer, Springer, vol. 46(5), pages 1269-1290, October.

    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. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    2. 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.
    3. Gasteiger, Emanuel & Prettner, Klaus, 2022. "Automation, Stagnation, And The Implications Of A Robot Tax," Macroeconomic Dynamics, Cambridge University Press, vol. 26(1), pages 218-249, January.
    4. Abeliansky, Ana Lucia & Prettner, Klaus, 2017. "Automation and demographic change," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168215, Verein für Socialpolitik / German Economic Association.
    5. Prettner, Klaus & Strulik, Holger, 2020. "Innovation, automation, and inequality: Policy challenges in the race against the machine," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 249-265.
    6. Brall, Franziska & Schmid, Ramona, 2020. "Automation, robots and wage inequality in Germany: A decomposition analysis," Hohenheim Discussion Papers in Business, Economics and Social Sciences 14-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    7. Geiger, Niels & Prettner, Klaus & Schwarzer, Johannes A., 2018. "Automatisierung, Wachstum und Ungleichheit," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2018, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    8. Basso, Henrique S. & Jimeno, Juan F., 2021. "From secular stagnation to robocalypse? Implications of demographic and technological changes," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 833-847.
    9. Dario Cords & Klaus Prettner, 2022. "Technological unemployment revisited: automation in a search and matching framework [The future of work: meeting the global challenges of demographic change and automation]," Oxford Economic Papers, Oxford University Press, vol. 74(1), pages 115-135.
    10. 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).
    11. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2019. "How can robots affect wage inequality?," Economic Modelling, Elsevier, vol. 81(C), pages 161-169.
    12. Aina Gallego & Thomas Kurer & Nikolas Schöll, 2018. "Not so disruptive after all: How workplace digitalization affects political preferences," Economics Working Papers 1623, Department of Economics and Business, Universitat Pompeu Fabra.
    13. Krenz, Astrid & Prettner, Klaus & Strulik, Holger, 2021. "Robots, reshoring, and the lot of low-skilled workers," European Economic Review, Elsevier, vol. 136(C).
    14. 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.
    15. 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.
    16. Gregory, Terry & Salomons, Anna & Zierahn, Ulrich, 2016. "Racing With or Against the Machine? Evidence from Europe," VfS Annual Conference 2016 (Augsburg): Demographic Change 145843, Verein für Socialpolitik / German Economic Association.
    17. Calì, Massimiliano & Presidente, Giorgio, 2021. "Robots For Economic Development," GLO Discussion Paper Series 942, Global Labor Organization (GLO).
    18. Schwarzbauer, Wolfgang & Strohner, Ludwig & Thomas, Tobias, 2018. "Roboter: Auswirkungen auf den Arbeitsmarkt sowie wirtschafts- und sozialpolitische Implikationen," Policy Notes 24, EcoAustria – Institute for Economic Research.
    19. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).
    20. Arthur Jacobs & Freddy Heylen, 2021. "Demographic change, secular stagnation and inequality: automation as a blessing?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1030, Ghent University, Faculty of Economics and Business Administration.

    More about this item

    Keywords

    Automation; labour productivity; panel data; production function; productivity measurement; robots;
    All these keywords.

    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:ipt:laedte:201908. 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: Publication Officer (email available below). General contact details of provider: https://edirc.repec.org/data/ipjrces.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.