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Technological knowledge and wages: from skill premium to wage polarization

Author

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  • Oscar Afonso

    (Universidade do Porto)

  • Tiago Sequeira

    (University of Coimbra)

  • Derick Almeida

    (University of Coimbra)

Abstract

This paper studies the impact of automation shocks on the technological-knowledge level, skill premium (or wage inequality), real prices, output, and economic growth. To highlight the economic mechanisms, we devise a task-based direct technical change model that allows us to analyze the determinants of the threshold task, the relative output and prices between sectors, intra- and inter-sectoral wage differences, wage polarization and economic growth rates. We observe that an increase in the efficiency of skilled or unskilled workers as well as a decrease in the efficiency of medium-skilled workers as possible result of automation always increase wage polarization as well as economic growth rates. In a quantitative exercise we also assess the change in the weight of routine and non-routine sectors in the economy. In this context, governments should implement policies to support the professional transition of medium-skilled workers to non-routinazable tasks.

Suggested Citation

  • Oscar Afonso & Tiago Sequeira & Derick Almeida, 2023. "Technological knowledge and wages: from skill premium to wage polarization," Journal of Economics, Springer, vol. 140(2), pages 93-119, October.
  • Handle: RePEc:kap:jeczfn:v:140:y:2023:i:2:d:10.1007_s00712-023-00833-y
    DOI: 10.1007/s00712-023-00833-y
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    References listed on IDEAS

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    1. Andreas Irmen, 2020. "Tasks, technology, and factor prices in the neoclassical production sector," Journal of Economics, Springer, vol. 131(2), pages 101-121, October.
    2. Robert C. Feenstra & Robert Inklaar & Marcel P. Timmer, 2015. "The Next Generation of the Penn World Table," American Economic Review, American Economic Association, vol. 105(10), pages 3150-3182, October.
    3. Florent Bordot, 2022. "Artificial Intelligence, Robots and Unemployment: Evidence from OECD Countries," Journal of Innovation Economics, De Boeck Université, vol. 0(1), pages 117-138.
    4. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    5. 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.
    6. Daron Acemoglu & Andrea Manera & Pascual Restrepo, 2020. "Does the US Tax Code Favor Automation?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(1 (Spring), pages 231-300.
    7. Andy Feng & Georg Graetz, 2020. "Training Requirements, Automation, and Job Polarisation," The Economic Journal, Royal Economic Society, vol. 130(631), pages 2249-2271.
    8. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    9. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    10. Grossmann, Volker & Steger, Thomas & Trimborn, Timo, 2013. "Dynamically optimal R&D subsidization," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 516-534.
    11. Oscar Afonso, 2006. "Skill-biased technological knowledge without scale effects," Applied Economics, Taylor & Francis Journals, vol. 38(1), pages 13-21.
    12. Laura Barbieri & Chiara Mussida & Mariacristina Piva & Marco Vivarelli, 2019. "Testing the employment impact of automation, robots and AI: A survey and some methodological issues," DISCE - Quaderni del Dipartimento di Politica Economica dipe0006, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    13. Daron Acemoglu & Fabrizio Zilibotti, 2001. "Productivity Differences," The Quarterly Journal of Economics, Oxford University Press, vol. 116(2), pages 563-606.
    14. Kwan, Yum K. & Lai, Edwin L. -C., 2003. "Intellectual property rights protection and endogenous economic growth," Journal of Economic Dynamics and Control, Elsevier, vol. 27(5), pages 853-873, March.
    15. Sequeira, Tiago Neves & Gil, Pedro Mazeda & Afonso, Oscar, 2018. "Endogenous growth and entropy," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 100-120.
    16. Francesco Bogliacino & Matteo Lucchese, 2016. "Endogenous skill biased technical change: testing for demand pull effect," Industrial and Corporate Change, Oxford University Press, vol. 25(2), pages 227-243.
    17. 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.
    18. Neves, Pedro Cunha & Sequeira, Tiago Neves, 2018. "Spillovers in the production of knowledge: A meta-regression analysis," Research Policy, Elsevier, vol. 47(4), pages 750-767.
    19. Thomas Lemieux, 2006. "Increasing Residual Wage Inequality: Composition Effects, Noisy Data, or Rising Demand for Skill?," American Economic Review, American Economic Association, vol. 96(3), pages 461-498, June.
    20. Holger Strulik, 2007. "Too Much of a Good Thing? The Quantitative Economics of R&D‐driven Growth Revisited," Scandinavian Journal of Economics, Wiley Blackwell, vol. 109(2), pages 369-386, June.
    21. 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.
    22. 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.
    23. 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.
    24. Marcel P. Timmer & Erik Dietzenbacher & Bart Los & Robert Stehrer & Gaaitzen J. Vries, 2015. "An Illustrated User Guide to the World Input–Output Database: the Case of Global Automotive Production," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 575-605, August.
    25. Elias Dinopoulos & Peter Thompson, 1999. "Scale effects in Schumpeterian models of economic growth," Journal of Evolutionary Economics, Springer, vol. 9(2), pages 157-185.
    26. Óscar Afonso & Pedro G. Lima & Tiago Sequeira, 2022. "The effects of automation and lobbying in wage inequality: a directed technical change model with routine and non-routine tasks," Journal of Evolutionary Economics, Springer, vol. 32(5), pages 1467-1497, November.
    27. Andre Jungmittag, 2021. "Robotisation of the manufacturing industries in the EU: Convergence or divergence?," The Journal of Technology Transfer, Springer, vol. 46(5), pages 1269-1290, October.
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    More about this item

    Keywords

    Automation; Technological-knowledge progress; Wages; Growth;
    All these keywords.

    JEL classification:

    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General
    • 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
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • P10 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - General

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