Globalisation and Income Inequality in BRICS Economies: The Mediating Role of Labour-Market Outcomes

Abstract

This study explores the impact of globalisation on income inequality and the labour market results for the BRICS countries from 2010 to 2025. The research relies on a balanced panel data set for Brazil, Russia, India, China and South Africa and investigates the relationship between more inclusive income distribution and better labour-market outcomes and the impact of economic integration. The Gini coefficient is used to measure income inequality, and employment, unemployment and labour-force participation measures are used to capture labour-market outcomes. The empirical analysis uses second-generation panel-data methods to address the issues of cross-sectional dependence and country-specific factors. Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) approach is used to estimate short-run and long-run relationships and the Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators are used for robustness. The findings suggest that globalisation has a statistically significant negative impact on the income inequality in the long run. Globalisation also has positive employment and labour-force participation effects, and lowers unemployment rates, which is beneficial to the labour market overall. Further analysis indicates that labour-market outcomes are important channels for globalisation to affect income distribution. This result is fairly stable across alternative specifications and estimators, lending robustness to the main outcomes. In conclusion, the study finds that globalisation can help achieve more inclusive economic results in the BRICS economies with the help of human-capital development, productive foreign investments, efficient labour-market institutions and stable macroeconomic environment. The results offer big policy implications to consider in designing globalisation policies that will foster both economic integration and inclusive development.

 Received: 2026-07-08 | Revised: 2026-09-28 | Accepted: 2026-09-29 | Published: 2026-09-30

Declarations

Consent to publish: The authors have provided consent to publish.

Competing interests: The authors declare no competing interests.

Data availability statement: Data will be made available on reasonable request from the corresponding author.

Funding: This research received no external funding.

Clinical Trial Number: Not Applicable.

Declaration of using generative AI: During the preparation of this work the author(s) used ChatGPT in order to correct the grammatical errors. After using this tool/service, the author(s) reviewed and edited the content as needed and take full responsibility for the content of the published article.

Author Contributions: A.M.I. and M.O.F.: Conceptualization, methodology, writing—original draft preparation, writing—review and editing. All authors have read and agreed to the published version of the manuscript.