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Automation technologies: Long-term effects for Spanish industrial firms

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  • Camiña, Ester
  • Díaz-Chao, Ángel
  • Torrent-Sellens, Joan

Abstract

The introduction of automated technologies has raised concern about how this will transform the productivity and employment. This paper examines the link among automation technologies, productivity and employment in the long-term using a panel data analysis for 5511 Spanish industrial firms. We test four different hypothesis and we show the following results: (i) the use of automation technologies predicts some of the main firm consolidated results, such as sales, added value, exports, innovation and R&D activities; (ii) although the use of robotics and flexible production systems would boost long-term productivity, computer-aided design and manufacturing, and data-driven control would either slow down or do not explain productivity. In addition, the connection between four automation technologies in the explanation of productivity has not been confirmed; (iii) the use of industrial robots, data-driven control and flexible production systems have been consolidated as a labour-reducing factor; and (iv) despite this technological labour-reducing effect, the overall complementarity factor of four automation technologies and human capital enhance long-term trend of employment. Our results highlight the importance of the implementation of new management methods based on data-driven decision making and the generation of public policies to support automation skills.

Suggested Citation

  • Camiña, Ester & Díaz-Chao, Ángel & Torrent-Sellens, Joan, 2020. "Automation technologies: Long-term effects for Spanish industrial firms," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
  • Handle: RePEc:eee:tefoso:v:151:y:2020:i:c:s0040162519305530
    DOI: 10.1016/j.techfore.2019.119828
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    as
    1. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    2. Bresnahan, Timothy F. & Trajtenberg, M., 1995. "General purpose technologies 'Engines of growth'?," Journal of Econometrics, Elsevier, vol. 65(1), pages 83-108, January.
    3. Daron Acemoglu & Pascual Restrepo, 2020. "The wrong kind of AI? Artificial intelligence and the future of labour demand," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 25-35.
    4. Giulia Faggio & Kjell G. Salvanes & John Van Reenen, 2010. "The evolution of inequality in productivity and wages: panel data evidence," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 19(6), pages 1919-1951, December.
    5. Francesco Chiacchio & Georgios Petropoulos & David Pichler, 2018. "The impact of industrial robots on EU employment and wages- A local labour market approach," Working Papers 25186, Bruegel.
    6. David Autor & Anna Salomons, 2018. "Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share," NBER Working Papers 24871, National Bureau of Economic Research, Inc.
    7. Szalavetz, Andrea, 2019. "Industry 4.0 and capability development in manufacturing subsidiaries," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 384-395.
    8. Kul Luintel & Mosahid Khan & Konstantinos Theodoridis, 2014. "On the robustness of R&D," Journal of Productivity Analysis, Springer, vol. 42(2), pages 137-155, October.
    9. Brent Neiman, 2014. "The Global Decline of the Labor Share," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(1), pages 61-103.
    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. Chad Syverson, 2011. "What Determines Productivity?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 326-365, June.
    12. 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.
    13. Yongxin Liao & Fernando Deschamps & Eduardo de Freitas Rocha Loures & Luiz Felipe Pierin Ramos, 2017. "Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal," International Journal of Production Research, Taylor & Francis Journals, vol. 55(12), pages 3609-3629, June.
    14. Benoît Mahy & François Rycx & Mélanie Volral, 2011. "Wage Dispersion and Firm Productivity in Different Working Environments," British Journal of Industrial Relations, London School of Economics, vol. 49(3), pages 460-485, September.
    15. K.V. Ramaswamy, 2018. "Technological change, automation and employment: A Short review of theory and evidence," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2018-002, Indira Gandhi Institute of Development Research, Mumbai, India.
    16. David M. Byrne & John G. Fernald & Marshall B. Reinsdorf, 2016. "Does the United States Have a Productivity Slowdown or a Measurement Problem?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(1 (Spring), pages 109-182.
    17. Georg Graetz & Guy Michaels, 2017. "Is Modern Technology Responsible for Jobless Recoveries?," American Economic Review, American Economic Association, vol. 107(5), pages 168-173, May.
    18. Maarten Goos & Alan Manning & Anna Salomons, 2014. "Explaining Job Polarization: Routine-Biased Technological Change and Offshoring," American Economic Review, American Economic Association, vol. 104(8), pages 2509-2526, August.
    19. Erik Brynjolfsson & Kristina McElheran, 2016. "The Rapid Adoption of Data-Driven Decision-Making," American Economic Review, American Economic Association, vol. 106(5), pages 133-139, May.
    20. 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.
    21. Harrison, Rupert & Jaumandreu, Jordi & Mairesse, Jacques & Peters, Bettina, 2014. "Does innovation stimulate employment? A firm-level analysis using comparable micro-data from four European countries," International Journal of Industrial Organization, Elsevier, vol. 35(C), pages 29-43.
    22. 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.
    23. Dengler, Katharina & Matthes, Britta, 2018. "The impacts of digital transformation on the labour market: Substitution potentials of occupations in Germany," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 304-316.
    24. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2018. "Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 23-57, National Bureau of Economic Research, Inc.
    25. Chad Syverson, 2017. "Challenges to Mismeasurement Explanations for the US Productivity Slowdown," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 165-186, Spring.
    26. Bronwyn H. Hall & Francesca Lotti & Jacques Mairesse, 2013. "Evidence on the impact of R&D and ICT investments on innovation and productivity in Italian firms," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 22(3), pages 300-328, April.
    27. Trajtenberg, Manuel, 2018. "AI as the next GPT: a Political-Economy Perspective," CEPR Discussion Papers 12721, C.E.P.R. Discussion Papers.
    28. Gill A. Pratt, 2015. "Is a Cambrian Explosion Coming for Robotics?," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 51-60, Summer.
    29. Dalenogare, Lucas Santos & Benitez, Guilherme Brittes & Ayala, Néstor Fabián & Frank, Alejandro Germán, 2018. "The expected contribution of Industry 4.0 technologies for industrial performance," International Journal of Production Economics, Elsevier, vol. 204(C), pages 383-394.
    30. 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.
    31. Robert Seamans & Manav Raj, 2018. "AI, Labor, Productivity and the Need for Firm-Level Data," NBER Working Papers 24239, National Bureau of Economic Research, Inc.
    32. Díaz-Chao, Ángel & Sainz-González, Jorge & Torrent-Sellens, Joan, 2015. "ICT, innovation, and firm productivity: New evidence from small local firms," Journal of Business Research, Elsevier, vol. 68(7), pages 1439-1444.
    33. DeCanio, Stephen J., 2016. "Robots and humans – complements or substitutes?," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 280-291.
    34. 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].
    35. Wei, Zelong & Song, Xi & Wang, Donghan, 2017. "Manufacturing flexibility, business model design, and firm performance," International Journal of Production Economics, Elsevier, vol. 193(C), pages 87-97.
    36. Li Da Xu & Eric L. Xu & Ling Li, 2018. "Industry 4.0: state of the art and future trends," International Journal of Production Research, Taylor & Francis Journals, vol. 56(8), pages 2941-2962, April.
    37. Van Reenen, John, 1997. "Employment and Technological Innovation: Evidence from U.K. Manufacturing Firms," Journal of Labor Economics, University of Chicago Press, vol. 15(2), pages 255-284, April.
    38. Guy Michaels & Ashwini Natraj & John Van Reenen, 2010. "Has ICT Polarized Skill Demand? Evidence from Eleven Countries over 25 Years," CEP Discussion Papers dp0987, Centre for Economic Performance, LSE.
    39. Mario Coccia, 2018. "Optimization in R&D intensity and tax on corporate profits for supporting labor productivity of nations," The Journal of Technology Transfer, Springer, vol. 43(3), pages 792-814, June.
    40. Miguel A. León-Ledesma & Peter McAdam & Alpo Willman, 2010. "Identifying the Elasticity of Substitution with Biased Technical Change," American Economic Review, American Economic Association, vol. 100(4), pages 1330-1357, September.
    41. 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.
    42. 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.
    43. 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.
    44. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    45. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923.
    46. Schuelke-Leech, Beth-Anne, 2018. "A model for understanding the orders of magnitude of disruptive technologies," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 261-274.
    47. Ulrich Doraszelski & Jordi Jaumandreu, 2013. "R&D and Productivity: Estimating Endogenous Productivity," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(4), pages 1338-1383.
    48. repec:bin:bpeajo:v:49:y:2019:i:2018-01:p:1-87 is not listed on IDEAS
    49. Guy Michaels & Ashwini Natraj & John Van Reenen, 2014. "Has ICT Polarized Skill Demand? Evidence from Eleven Countries over Twenty-Five Years," The Review of Economics and Statistics, MIT Press, vol. 96(1), pages 60-77, March.
    50. Venturini, Francesco, 2015. "The modern drivers of productivity," Research Policy, Elsevier, vol. 44(2), pages 357-369.
    51. Weller, Christian & Kleer, Robin & Piller, Frank T., 2015. "Economic implications of 3D printing: Market structure models in light of additive manufacturing revisited," International Journal of Production Economics, Elsevier, vol. 164(C), pages 43-56.
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