IDEAS home Printed from https://ideas.repec.org/h/era/chaptr/2022-new-normal-new-technologies-new-financing-7.html
   My bibliography  Save this book chapter

Digital Transformation:‘Development for All’?

In: New Normal, New Technologies, New Financing

Author

Listed:
  • Lili Yan Ing

    (Economic Research Institute for ASEAN and East Asia (ERIA))

  • Gene Grossman
  • David Christian

    (Economic Research Institute for ASEAN and East Asia (ERIA))

Abstract

Technological advances over the last two millennia have generated remarkable improvements in the quality of life. But the gains that come with new technologies are rarely shared by all. Notably, we have witnessed in recent years rising income and wealth inequality in most countries, with greater shares accruing to capital owners and highly skilled workers often at the expense of less skilled workers. By 2020, the richest 1% of the world’s population owned almost half of global wealth. In the last 2 years alone, the ten highest earners (eight of whom are technological titans) saw their personal incomes more than double, while the poorest 99% of the global population suffered a decline in their collective income during this period (Hardoon, Ayele, and FuentesNieva, 2016; Ahmed et al., 2022). Might there be a connection between technological progress and income and wealth inequality?

Suggested Citation

  • Lili Yan Ing & Gene Grossman & David Christian, 2022. "Digital Transformation:‘Development for All’?," Chapters, in: Lili Yan Ing & Dani Rodrik (ed.), New Normal, New Technologies, New Financing, chapter 7, pages 75-88, Economic Research Institute for ASEAN and East Asia (ERIA).
  • Handle: RePEc:era:chaptr:2022-new-normal-new-technologies-new-financing-7
    as

    Download full text from publisher

    File URL: https://www.eria.org/uploads/media/Books/2022-G20-New-Normal-New-Technology-New-Financing/11_Ch.7-Digital-Transformation-new2.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mr. Anton Korinek & Mr. Martin Schindler & Joseph Stiglitz, 2021. "Technological Progress, Artificial Intelligence, and Inclusive Growth," IMF Working Papers 2021/166, International Monetary Fund.
    2. Ufuk Akcigit & Sina T. Ates, 2021. "Ten Facts on Declining Business Dynamism and Lessons from Endogenous Growth Theory," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 257-298, January.
    3. 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.
    4. Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2019. "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 31-50, Spring.
    5. Artuc, Erhan & Christiaensen, Luc & Winkler, Hernan, 2019. "Does Automatization in Rich Countries hurt Developing Ones? Evidence from the US and Mexico," Jobs Group Papers, Notes, and Guides 30834024, The World Bank.
    6. Matt Taddy, 2018. "The Technological Elements of Artificial Intelligence," NBER Working Papers 24301, National Bureau of Economic Research, Inc.
    7. Matt Taddy, 2018. "The Technological Elements of Artificial Intelligence," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 61-87, National Bureau of Economic Research, Inc.
    8. Cavenaile, Laurent, 2021. "Offshoring, computerization, labor market polarization and top income inequality," Journal of Macroeconomics, Elsevier, vol. 69(C).
    9. Pajarinen, Mika & Rouvinen, Petri, 2014. "Computerization Threatens One Third of Finnish Employment," ETLA Brief 22, The Research Institute of the Finnish Economy.
    10. Dan Andrews & Chiara Criscuolo & Peter N. Gal, 2016. "The Best versus the Rest: The Global Productivity Slowdown, Divergence across Firms and the Role of Public Policy," OECD Productivity Working Papers 5, OECD Publishing.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aránzazu Guillán Montero & David Le Blanc, 2019. "Lessons for Today from Past Periods of Rapid Technological Change," Working Papers 158, United Nations, Department of Economics and Social Affairs.
    2. Berlingieri, Giuseppe & Blanchenay, Patrick & Criscuolo, Chiara, 2024. "The great divergence(s)," Research Policy, Elsevier, vol. 53(3).
    3. Patrick Mellacher, 2021. "Growth, Inequality and Declining Business Dynamism in a Unified Schumpeter Mark I + II Model," Papers 2111.09407, arXiv.org, revised Nov 2023.
    4. Fabio Montobbio & Jacopo Staccioli & Maria Enrica Virgillito & Marco Vivarelli, 2022. "The empirics of technology, employment and occupations: lessons learned and challenges ahead," DISCE - Quaderni del Dipartimento di Politica Economica dipe0028, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    5. Gordon H. Hanson, 2021. "Immigration and Regional Specialization in AI," NBER Working Papers 28671, National Bureau of Economic Research, Inc.
    6. Giovanni DOSI & Maria Enrica VIRGILLITO, 2019. "Whither the evolution of the contemporary social fabric? New technologies and old socio‐economic trends," International Labour Review, International Labour Organization, vol. 158(4), pages 593-625, December.
    7. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
    8. Benjamin David, 2015. "Computer technology and probable job destructions in Japan: an evaluation," EconomiX Working Papers 2015-28, University of Paris Nanterre, EconomiX.
    9. Andrea Szalavetz, 2019. "Artificial Intelligence-Based Development Strategy in Dependent Market Economies - Any Room amidst Big Power Rivalry?," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 40-54.
    10. Cali,Massimiliano & Presidente,Giorgio, 2021. "Automation and Manufacturing Performance in a Developing Country," Policy Research Working Paper Series 9653, The World Bank.
    11. Nils Grashof & Alexander Kopka, 2023. "Widening or closing the gap? The relationship between artificial intelligence, firm-level productivity and regional clusters," Bremen Papers on Economics & Innovation 2304, University of Bremen, Faculty of Business Studies and Economics.
    12. Maarten de Ridder, 2022. "Market power and innovation in the intangible economy," POID Working Papers 064, Centre for Economic Performance, LSE.
    13. Antonio Martins-Neto & Nanditha Mathew & Pierre Mohnen & Tania Treibich, 2021. "Is There Job Polarization in Developing Economies? A Review and Outlook," CESifo Working Paper Series 9444, CESifo.
    14. Hémous, David & Dechezleprêtre, Antoine & Olsen, Morten & Zanella, carlo, 2019. "Automating Labor: Evidence from Firm-level Patent Data," CEPR Discussion Papers 14249, C.E.P.R. Discussion Papers.
    15. Jens Prüfer & Patricia Prüfer, 2020. "Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands," Small Business Economics, Springer, vol. 55(3), pages 651-672, October.
    16. Usabiaga, Carlos & Núñez, Fernando & Arendt, Lukasz & Gałecka-Burdziak, Ewa & Pater, Robert, 2022. "Skill requirements and labour polarisation: An association analysis based on Polish online job offers," Economic Modelling, Elsevier, vol. 115(C).
    17. Markus Nagler & Monika Schnitzer & Martin Watzinger, 2022. "Fostering the Diffusion of General Purpose Technologies: Evidence from the Licensing of the Transistor Patents," Journal of Industrial Economics, Wiley Blackwell, vol. 70(4), pages 838-866, December.
    18. Ernest Liu & Atif Mian & Amir Sufi, 2022. "Low Interest Rates, Market Power, and Productivity Growth," Econometrica, Econometric Society, vol. 90(1), pages 193-221, January.
    19. Davide Proserpio & John R. Hauser & Xiao Liu & Tomomichi Amano & Alex Burnap & Tong Guo & Dokyun (DK) Lee & Randall Lewis & Kanishka Misra & Eric Schwarz & Artem Timoshenko & Lilei Xu & Hema Yoganaras, 2020. "Soul and machine (learning)," Marketing Letters, Springer, vol. 31(4), pages 393-404, December.
    20. Carol Corrado & Jonathan Haskel & Massimiliano Iommi & Cecilia Jona-Lasinio & Filippo Bontadini, 2023. "Data, Intangible Capital, and Productivity," NBER Chapters, in: Technology, Productivity, and Economic Growth, National Bureau of Economic Research, Inc.

    More about this item

    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:era:chaptr:2022-new-normal-new-technologies-new-financing-7. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ranti Amelia (email available below). General contact details of provider: https://edirc.repec.org/data/eriadid.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.