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Who Is afraid of machines?

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Abstract

We study how various types of machines, namely, information and communication technologies, software, and especially industrial robots, affect the demand for workers of different education, age, and gender. We do so by exploiting differences in the composition of workers across countries, industries and time. Our dataset comprises 10 high-income countries and 30 industries, which span roughly their entire economies, with annual observations over the period 1982–2005. The results suggest that software and robots reduced the demand for low and medium-skill workers, the young, and women — especially in manufacturing industries; but raised the demand for high-skill workers, older workers and men —especially in service industries. These findings are consistent with the hypothesis that automation technologies, contrary to other types of capital, replace humans performing routine tasks. We also find evidence for some types of workers, especially women, having shifted away from such tasks.

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  • Satiris Blanas & Gino Gancia & Sang Yoon (Tim) Lee, 2019. "Who Is afraid of machines?," Economics Working Papers 1661, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:1661
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    Cited by:

    1. Ilona Pavlenkova & Luca Alfieri & Jaan Masso, 2021. "Effects Of Automation On The Gender Pay Gap: The Case Of Estonia," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 131, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    2. Sotiris Blanas, 2019. "The distinct effects of information technologies and communication technologies on the age-skill composition of labour demand," Working Paper Research 365, National Bank of Belgium.
    3. Henrik Schwabe & Fulvio Castellacci, 2020. "Automation, workers’ skills and job satisfaction," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-26, November.
    4. Beerli, Andreas & Indergand, Ronald & Kunz, Johannes S., 2021. "The supply of foreign talent: How skill-biased technology drives the location choice and skills of new immigrants," GLO Discussion Paper Series 998, Global Labor Organization (GLO).
    5. 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.
    6. Kerstin Hotte & Angelos Theodorakopoulos & Pantelis Koutroumpis, 2021. "Automation and Taxation," Papers 2103.04111, arXiv.org, revised Apr 2022.
    7. Mauro Caselli & Andrea Fracasso & Sergio Scicchitano & Silvio Traverso & Enrico Tundis, 2021. "Stop worrying and love the robot: An activity-based approach to assess the impact of robotization on employment dynamics," DEM Working Papers 2021/06, Department of Economics and Management.
    8. Dechezleprêtre, Antoine & Hémous, David & olsen, morten & Zanella, carlo, 2019. "Automating Labor: Evidence from Firm-level Patent Data," CEPR Discussion Papers 14249, C.E.P.R. Discussion Papers.
    9. Alessandra Bonfiglioli & Rosario Crinò & Harald Fadinger & Gino Gancia, 2020. "Robot Imports and Firm-Level Outcomes," CRC TR 224 Discussion Paper Series crctr224_2020_243, University of Bonn and University of Mannheim, Germany.
    10. Ballestar, María Teresa & García-Lazaro, Aida & Sainz, Jorge & Sanz, Ismael, 2022. "Why is your company not robotic? The technology and human capital needed by firms to become robotic," Journal of Business Research, Elsevier, vol. 142(C), pages 328-343.
    11. repec:hal:spmain:info:hdl:2441/7n49nkmngd8448a5ts5gt5ade0 is not listed on IDEAS
    12. Alex W. Chernoff & Casey Warman, 2020. "COVID-19 and Implications for Automation," NBER Working Papers 27249, National Bureau of Economic Research, Inc.
    13. Haapanala, Henri & Marx, Ive & Parolin, Zachary, 2022. "Robots and Unions: The Moderating Effect of Organised Labour on Technological Unemployment," IZA Discussion Papers 15080, Institute of Labor Economics (IZA).
    14. Gravina, Antonio Francesco & Foster-McGregor, Neil, 2020. "Automation, globalisation and relative wages: An empirical analysis of winners and losers," MERIT Working Papers 2020-040, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    15. M. Battisti & M. Del Gatto & A. F. Gravina & C. F. Parmeter, 2021. "Robots versus labor skills: a complementarity/substitutability analysis," Working Paper CRENoS 202104, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    16. Jasmine Mondolo, 2022. "The composite link between technological change and employment: A survey of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1027-1068, September.
    17. Battisti, Michele & Gravina, Antonio Francesco, 2021. "Do robots complement or substitute for older workers?," Economics Letters, Elsevier, vol. 208(C).
    18. Jaan Masso & Priit Vahter, 2020. "Innovation As A Firm-Level Factor Of The Gender Wage Gap," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 128, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    19. Golin, M. & Rauh, C., 2022. "The Impact of Fear of Automation," Janeway Institute Working Papers 2229, Faculty of Economics, University of Cambridge.
    20. Klump, Rainer & Jurkat, Anne & Schneider, Florian, 2021. "Tracking the rise of robots: A survey of the IFR database and its applications," MPRA Paper 110390, University Library of Munich, Germany.
    21. Golin, M. & Rauh, C., 2022. "The Impact of Fear of Automation," Janeway Institute Working Papers 2229, Faculty of Economics, University of Cambridge.
    22. Kerstin Hotte & Melline Somers & Angelos Theodorakopoulos, 2022. "Technology and jobs: A systematic literature review," Papers 2204.01296, arXiv.org.

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    More about this item

    Keywords

    Automation; robots; employment; labor demand; labor income share.;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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