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Robot arithmetic: can new technology harm all workers or the average worker?

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  • Francesco Caselli
  • Alan Manning

Abstract

It is well-established that new technology can cause large changes in relative wages and inequality. But there are also claims, based largely on verbal expositions, that new technology will harm workers on average or even all workers. Using formal models (which impose logical consistency and clear links between assumptions and conclusions) we show - under plausible assumptions - that new technology will cause average wages to rise if the prices of investment goods fall relative to consumer goods (a condition supported by the data) and if the new technologies do not lead to a fall in market competition. Some groups of workers must gain but others may be harmed. However, if workers can freely choose their occupation, or redistribution among workers is possible, all workers can gain.

Suggested Citation

  • Francesco Caselli & Alan Manning, 2017. "Robot arithmetic: can new technology harm all workers or the average worker?," CEP Discussion Papers dp1497, Centre for Economic Performance, LSE.
  • Handle: RePEc:cep:cepdps:dp1497
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    1. Gene M. Grossman & Elhanan Helpman & Ezra Oberfield & Thomas Sampson, 2017. "Balanced Growth Despite Uzawa," American Economic Review, American Economic Association, vol. 107(4), pages 1293-1312, April.
    2. 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.
    3. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    4. 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.
    5. Jones, C.I., 2016. "The Facts of Economic Growth," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 3-69, Elsevier.
    6. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    7. Joao Guerreiro & Sergio Rebelo & Pedro Teles, 2022. "Should Robots Be Taxed? [Skills, Tasks and Technologies: Implications for Employment and Earnings]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(1), pages 279-311.
    8. H. Uzawa, 1961. "Neutral Inventions and the Stability of Growth Equilibrium," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 28(2), pages 117-124.
    9. 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.
    10. repec:oup:qjecon:v:129:y:2013:i:1:p:61-103 is not listed on IDEAS
    11. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    12. 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.
    13. Per Krusell & Lee E. Ohanian & JosÈ-Victor RÌos-Rull & Giovanni L. Violante, 2000. "Capital-Skill Complementarity and Inequality: A Macroeconomic Analysis," Econometrica, Econometric Society, vol. 68(5), pages 1029-1054, September.
    14. Daron Acemoglu & Pascual Restrepo, 2016. "The Race Between Machine and Man: Implications of Technology for Growth, Factor Shares and Employment," NBER Working Papers 22252, National Bureau of Economic Research, Inc.
    15. Daniel Susskind, 2017. "A Model of Technological Unemployment," Economics Series Working Papers 819, University of Oxford, Department of Economics.
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    Cited by:

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    2. Fierro, Luca Eduardo & Caiani, Alessandro & Russo, Alberto, 2022. "Automation, Job Polarisation, and Structural Change," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 499-535.
    3. Annie Tubadji & Toby Denney & Don J. Webber, 2021. "Cultural relativity in consumers' rates of adoption of artificial intelligence," Economic Inquiry, Western Economic Association International, vol. 59(3), pages 1234-1251, July.

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    More about this item

    Keywords

    technology; wages;

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • 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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