IDEAS home Printed from https://ideas.repec.org/p/ris/kiepwe/2023_001.html
   My bibliography  Save this paper

Analysis on the Determinants of Labor Share and Its Policy Implications

Author

Listed:
  • Baek, Yaein

    (KOREA INSTITUTE FOR INTERNATIONAL ECONOMIC POLICY (KIEP))

  • Han, Minsoo

    (Department of International Trade, Inha University)

  • Kim, Wongi

    (Department of Economics, Sungshin Women’s University)

  • Kim, Hyunsuk

    (Int’l Macroeconomics Team, Int’l Macroeconomics & Finance Dept)

Abstract

There has been a significant decline in the global labor share, leading to numerous studies about the cause of this drop. The labor share is used as one of the main indicators of inequality because a decrease in the labor share can lead to aggravation of income inequality. This is because low-skilled workers can be greatly affected by such a decline in the labor share and the main source of in-come for the low-income class, including the self-employed, is labor income. Among various indicators of inequality, this study analyzes the determinants of the change in labor share. Technological changes such as adoption of robots, advancements in information and communications technology (ICT) and the Fourth Industrial Revolution (4IR) are expected to change the labor market. Hence, this study analyzes the impact of technological changes on labor share and suggests policy responses.(the rest omitted)

Suggested Citation

  • Baek, Yaein & Han, Minsoo & Kim, Wongi & Kim, Hyunsuk, 2023. "Analysis on the Determinants of Labor Share and Its Policy Implications," World Economy Brief 23-1, Korea Institute for International Economic Policy.
  • Handle: RePEc:ris:kiepwe:2023_001
    as

    Download full text from publisher

    File URL: https://www.kiep.go.kr/gallery.es?mid=a10105040000&bid=0007&act=view&list_no=10539&cg_code=
    File Function: Full text
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Labor Share; Skill-biased Technological Change; Robots; Income Inequality;
    All these keywords.

    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:ris:kiepwe:2023_001. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Geun Hye Son (email available below). General contact details of provider: https://edirc.repec.org/data/kieppkr.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.