IDEAS home Printed from https://ideas.repec.org/a/hig/ecohse/202131.html
   My bibliography  Save this article

Economic Inequality in the Access to Remote Learning Assets Amongst Youth in BRICS Countries: What Can We Learn from Pre-COVID-19 Data?

Author

Listed:
  • Garen Avanesian

    (Southern Federal University, Rostov-on-Don, Russia)

  • Marina Borovskaya

    (Southern Federal University, Rostov-on-Don, Russia)

  • Sakshi Mishra

    (Columbia University, New York, USA)

  • Marina Masych

    (Southern Federal University, Rostov-on-Don, Russia)

  • Tatiana Fedosova

    (Southern Federal University, Rostov-on-Don, Russia)

  • Valeria Egorova

    (Southern Federal University, Rostov-on-Don, Russia)

Abstract

This paper analyzes economic inequalities in the access to such assets for remote learning as internet connection and personal computers at home in BRICS countries among young students (15–24 óears old). It is acknowledged that such household possessions as the internet and personal computer obtain a new role during the COVID-19 pandemic when the educational institutions are closed and in-person classroom instruction is disrupted. Data from household surveys collected from 2015 to 2019 show sharp differences between and within BRICS countries regarding access to these assets for remote learning. In addition to between-country inequalities, the analysis suggests that within-country disparities are also staggering, especially regarding an area of residence and wealth quintile groups, putting at risk the education of youth from most impoverished and rural backgrounds. Econometric application of concentration curves and estimation of concentration indices reveals household wealth as an essential driver of economic inequality in the access to remote learning amongst young students in BRICS countries, highlighting the critical degree of inequality in India and South Africa. The findings suggest that the more universal the access to remote learning is, the less economic inequality is observed in accessing remote learning modalities. In other words, policy implications aimed at expanding digital infrastructure could help ensure that young women and men are not falling behind in receiving a quality education, gaining relevant skills, and accessing decent employment opportunities. For BRICS countries to transform their economies and lead innovations, a digitally literate future workforce is critical, with access to digital resources being a first step towards achieving this. Inequalities in access to these tools show that BRICS countries have more to do before all youth can be connected and participate in a digital economy.

Suggested Citation

  • Garen Avanesian & Marina Borovskaya & Sakshi Mishra & Marina Masych & Tatiana Fedosova & Valeria Egorova, 2021. "Economic Inequality in the Access to Remote Learning Assets Amongst Youth in BRICS Countries: What Can We Learn from Pre-COVID-19 Data?," HSE Economic Journal, National Research University Higher School of Economics, vol. 25(3), pages 359-378.
  • Handle: RePEc:hig:ecohse:2021:3:1
    as

    Download full text from publisher

    File URL: https://ej.hse.ru/en/2021-25-3/530048375.html
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    COVID-19; educational inequality; educational equity; remote learning; internet access; household possessions; concentration curves; concentration indices;
    All these keywords.

    JEL classification:

    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    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:hig:ecohse:2021:3:1. 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: Editorial board or Editorial board (email available below). General contact details of provider: https://edirc.repec.org/data/hsecoru.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.