IDEAS home Printed from https://ideas.repec.org/p/zbw/glodps/320.html
   My bibliography  Save this paper

Innovation, Automation, and Inequality: Policy Challenges in the Race against the Machine

Author

Listed:
  • Prettner, Klaus
  • Strulik, Holger

Abstract

We analyze the effects of R&D-driven automation on economic growth, education, and inequality when high-skilled workers are complements to machines and low-skilled workers are substitutes for machines. The model predicts that innovation-driven growth leads to an increasing population share of college graduates, increasing income and wealth inequality, and a declining labor share. We use the model to analyze the effects of redistribution. We show that it is difficult to improve income of low-skilled individuals as long as both technology and education are endogenous. This is true irrespective of whether redistribution is financed by progressive wage taxation or by a robot tax. Only when higher education is stationary, redistribution unambiguously benefits the poor. We show that education subsidies affect the economy differently depending on their mode of funding and that they may actually reduce education. Finally, we extend the model by fair wage concerns and show how automation could induce involuntary low-skilled unemployment.

Suggested Citation

  • Prettner, Klaus & Strulik, Holger, 2019. "Innovation, Automation, and Inequality: Policy Challenges in the Race against the Machine," GLO Discussion Paper Series 320, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:320
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/191983/1/GLO-DP-0320.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Oded Galor & Omer Moav, 2002. "Natural Selection and the Origin of Economic Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1133-1191.
    2. George A. Akerlof & Janet L. Yellen, 1990. "The Fair Wage-Effort Hypothesis and Unemployment," The Quarterly Journal of Economics, Oxford University Press, vol. 105(2), pages 255-283.
    3. Prettner, Klaus & Werner, Katharina, 2016. "Why it pays off to pay us well: The impact of basic research on economic growth and welfare," Research Policy, Elsevier, vol. 45(5), pages 1075-1090.
    4. Holger Strulik & Klaus Prettner & Alexia Prskawetz, 2013. "The past and future of knowledge-based growth," Journal of Economic Growth, Springer, vol. 18(4), pages 411-437, December.
    5. Daron Acemoglu & David Autor, 2012. "What Does Human Capital Do? A Review of Goldin and Katz's The Race between Education and Technology," Journal of Economic Literature, American Economic Association, vol. 50(2), pages 426-463, June.
    6. Peretto, Pietro F. & Seater, John J., 2013. "Factor-eliminating technical change," Journal of Monetary Economics, Elsevier, vol. 60(4), pages 459-473.
    7. Brent Neiman, 2014. "The Global Decline of the Labor Share," The Quarterly Journal of Economics, Oxford University Press, vol. 129(1), pages 61-103.
    8. Matteo Cervellati & Uwe Sunde, 2005. "Human Capital Formation, Life Expectancy, and the Process of Development," American Economic Review, American Economic Association, vol. 95(5), pages 1653-1672, December.
    9. Cords, Dario & Prettner, Klaus, 2018. "Technological unemployment revisited: Automation in a search and matching framework," Hohenheim Discussion Papers in Business, Economics and Social Sciences 19-2018, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    10. Eli Bekman & John Bound & Stephen Machin, 1998. "Implications of Skill-Biased Technological Change: International Evidence," The Quarterly Journal of Economics, Oxford University Press, vol. 113(4), pages 1245-1279.
    11. Abeliansky, Ana L. & Martínez-Zarzoso, Imnaculada & Prettner, Klaus, 2015. "The impact of 3D printing on trade and FDI," Center for European, Governance and Economic Development Research Discussion Papers 262, University of Goettingen, Department of Economics.
    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. Oded Galor, 2011. "Unified Growth Theory and Comparative Development," Rivista di Politica Economica, SIPI Spa, issue 2, pages 9-21, April-Jun.
    14. 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.
    15. Prettner, Klaus & Strulik, Holger, 2017. "The lost race against the machine: Automation, education and inequality in an R&D-based growth model," Hohenheim Discussion Papers in Business, Economics and Social Sciences 08-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    16. Gasteiger, Emanuel & Prettner, Klaus, 2017. "A note on automation, stagnation, and the implications of a robot tax," Discussion Papers 2017/17, Free University Berlin, School of Business & Economics.
    17. Abeliansky, Ana & Prettner, Klaus, 2017. "Automation and demographic change," Hohenheim Discussion Papers in Business, Economics and Social Sciences 05-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    18. Holger Strulik, 2005. "The Role of Human Capital and Population Growth in R&D-based Models of Economic Growth," Review of International Economics, Wiley Blackwell, vol. 13(1), pages 129-145, February.
    19. repec:eee:ecolet:v:159:y:2017:i:c:p:157-160 is not listed on IDEAS
    20. repec:aea:aecrev:v:108:y:2018:i:6:p:1488-1542 is not listed on IDEAS
    21. Oded Galor, 2011. "Unified Growth Theory," Economics Books, Princeton University Press, edition 1, number 9477, December.
    22. Alwyn Young, 1998. "Growth without Scale Effects," Journal of Political Economy, University of Chicago Press, vol. 106(1), pages 41-63, February.
    23. Daron Acemoglu, 2002. "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature, American Economic Association, vol. 40(1), pages 7-72, March.
    24. Jeffrey D. Sachs & Laurence J. Kotlikoff, 2012. "Smart Machines and Long-Term Misery," NBER Working Papers 18629, National Bureau of Economic Research, Inc.
    25. Prettner, Klaus, 2016. "The implications of automation for economic growth and the labor share," Hohenheim Discussion Papers in Business, Economics and Social Sciences 18-2016, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    26. Chakravarty, Satya R, 1988. "Extended Gini Indices of Inequality," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 29(1), pages 147-156, February.
    27. 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.
    28. David N. Weil & Oded Galor, 2000. "Population, Technology, and Growth: From Malthusian Stagnation to the Demographic Transition and Beyond," American Economic Review, American Economic Association, vol. 90(4), pages 806-828, September.
    29. 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.
    30. Holger Strulik & Jacob Weisdorf, 2008. "Population, food, and knowledge: a simple unified growth theory," Journal of Economic Growth, Springer, vol. 13(3), pages 195-216, September.
    31. Prettner, Klaus, 2014. "The non-monotonous impact of population growth on economic prosperity," Economics Letters, Elsevier, vol. 124(1), pages 93-95.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Automation; Innovation-Driven Growth; Inequality; Wealth Concentration; Unemployment; Policy Responses;

    JEL classification:

    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E25 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Aggregate Factor Income Distribution
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

    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:zbw:glodps:320. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - Leibniz Information Centre for Economics). General contact details of provider: http://edirc.repec.org/data/glaboea.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.