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What Will Drive Long-Run Growth in the Digital Age?

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  • Jakub Growiec

Abstract

This paper considers the prospective sources of long-run growth in the future. Historically, in the industrial era and at the early stage of the digital era (which began approximately in the 1980s) the main growth engine is R&D. If in the future all essential production or R&D tasks will eventually be subject to automation, though, the engine of growth will be shifted to the accumulation of programmable hardware (capital), and R&D will lose its prominence. By contrast, if neither production nor R&D tasks will be fully automated, R&D will remain the main growth engine. Additional mechanisms potentially accelerating and sustaining growth are the accumulation of R&D capital (particularly important under partial automation), and hardware-augmenting technical change.

Suggested Citation

  • Jakub Growiec, 2020. "What Will Drive Long-Run Growth in the Digital Age?," KAE Working Papers 2020-054, Warsaw School of Economics, Collegium of Economic Analysis.
  • Handle: RePEc:sgh:kaewps:2020054
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    References listed on IDEAS

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    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Robert J. Gordon, 2016. "The Rise and Fall of American Growth: The U.S. Standard of Living since the Civil War," Economics Books, Princeton University Press, edition 1, number 10544.
    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. Melanie Arntz & Terry Gregory & Ulrich Zierahn, 2016. "The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis," OECD Social, Employment and Migration Working Papers 189, OECD Publishing.
    5. 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.
    6. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "The Economics of Artificial Intelligence: An Agenda," NBER Books, National Bureau of Economic Research, Inc, number agra-1, March.
    7. Charles I. Jones & Jihee Kim, 2018. "A Schumpeterian Model of Top Income Inequality," Journal of Political Economy, University of Chicago Press, vol. 126(5), pages 1785-1826.
    8. 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.
    9. Christian Groth & Karl-Josef Koch & Thomas Steger, 2010. "When economic growth is less than exponential," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 44(2), pages 213-242, August.
    10. Seth G. Benzell & Laurence J. Kotlikoff & Guillermo LaGarda & Jeffrey D. Sachs, 2015. "Robots Are Us: Some Economics of Human Replacement," NBER Working Papers 20941, National Bureau of Economic Research, Inc.
    11. Jakub Growiec, 2019. "The Hardware–Software Model: A New Conceptual Framework of Production, R&D, and Growth with AI," Working Paper series 19-18, Rimini Centre for Economic Analysis.
    12. 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.
    13. Berg, Andrew & Buffie, Edward F. & Zanna, Luis-Felipe, 2018. "Should we fear the robot revolution? (The correct answer is yes)," Journal of Monetary Economics, Elsevier, vol. 97(C), pages 117-148.
    14. 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.
    15. Seth G. Benzell & Laurence J. Kotlikoff & Guillermo LaGarda & Jeffrey D. Sachs, 2015. "Robots Are Us: Some Economics of Human Replacement," NBER Working Papers 20941, National Bureau of Economic Research, Inc.
    16. Jones, Charles I, 1995. "R&D-Based Models of Economic Growth," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 759-784, August.
    17. Agrawal, Ajay & Gans, Joshua & Goldfarb, Avi (ed.), 2019. "The Economics of Artificial Intelligence," National Bureau of Economic Research Books, University of Chicago Press, number 9780226613338, December.
    18. Jeffrey D. Sachs & Seth G. Benzell & Guillermo LaGarda, 2015. "Robots: Curse or Blessing? A Basic Framework," NBER Working Papers 21091, National Bureau of Economic Research, Inc.
    19. Larry E. Jones & Rodolfo Manuelli, 1990. "A Convex Model of Equilibrium Growth," NBER Working Papers 3241, National Bureau of Economic Research, Inc.
    20. Seth G. Benzell & Erik Brynjolfsson, 2019. "Digital Abundance and Scarce Genius: Implications for Wages, Interest Rates, and Growth," NBER Working Papers 25585, National Bureau of Economic Research, Inc.
    21. Jones, Larry E & Manuelli, Rodolfo E, 1990. "A Convex Model of Equilibrium Growth: Theory and Policy Implications," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 1008-1038, October.
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    More about this item

    Keywords

    long-run growth; factor accumulation; technical change; automation; asymptotic dynamics;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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