Impact of the Digital Economy on Income Inequality: Evidence from Developing Economies

Abstract

This study examines the nonlinear relationship between digital economy development and income inequality across 40 developing economies from 2010 to 2022, employing a dual-model econometric framework. Combining a baseline fixed-effects panel regression with a partially linear functional-coefficient model, the analysis reveals that the digital economy reduces income inequality, but its marginal effects are contingent on economic development thresholds. The results demonstrate a U-shaped relationship, where the inequality-mitigating impact of digitalisation is strongest at intermediate economic development levels, reducing the Gini coefficient by 0.31 units per unit increase in the Digital Economy Index. Below this threshold, infrastructural and literacy gaps constrain equitable access to digital benefits, while above it, diminishing returns emerge due to labour market precarity and saturation effects. Mechanism analyses identified three critical pathways: digital entrepreneurship, financial inclusion, and labour market shifts. Platforms like Jumia and MercadoLibre lower entry barriers for informal workers, increasing rural incomes by 12%–40%, while mobile money adoption (e.g., M-Pesa) boosts rural savings rates by 22%, narrowing urban-rural gaps. However, gig economy expansion though creating millions of jobs, often perpetuates wage instability, with 54% of platform workers in India earning below the minimum wage. Policy implications emphasise context-specific strategies: low-REL economies must prioritise digital infrastructure and literacy (e.g., India’s Digital India), while high-REL economies should strengthen social safety nets (e.g., Brazil’s MEI program) to formalise gig workers. Entrepreneurship ecosystems targeting marginalised groups, such as Nigeria’s Andela, further amplify equity gains by bridging skill and capital gaps. JEL Classification : D63 , O15 , O33

Keywords

• Digital Economy
• Income Inequality
• Developing Economies
• Nonlinear Dynamics
• Entrepreneurship
• Policy Design

References

1. Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labour markets. Journal of Political Economy, 128(6), 2188– 2244. doi:10.1086/705716 google scholar
2. African Union (AU). (2022). Digital Transformation Strategy for Africa (2020-2030). African Union Commission. google scholar
3. Asongu, S. A., & Odhiambo, N. M. (2023). Mobile banking, financial inclusion, and inequality in Sub-Saharan Africa. Journal of African Economies, 32(1), 45–67. doi:10.1093/jae/ejac023 google scholar
4. Autor, D., Dorn, D., Katz, L. F., Patterson, C., & Van Reenen, J. (2020). The fall of the labour share and the rise of superstar firms. The Quarterly Journal of Economics, 135(2), 645–709. https://doi.org/10.1093/qje/qjaa004 google scholar
5. Bramwell, A., Nyström, K., & Wolfe, D. A. (2022). Digital entrepreneurship in emerging markets: Challenges and opportunities. Research Policy, 51(3), 104487. doi:10.1016/j.respol.2021.104487 google scholar
6. Chen, W., & Wu, Y. (2022). Does intellectual property protection stimulate digital economy development? Journal of Applied Economics, 25(1), 723–730. doi:10.1080/15140326.2022.2045846 google scholar
7. Gomes, M., Silva, A., & Oliveira, T. (2022). Handling missing data in unbalanced panels: A comparison of imputation methods. Journal of Econometric Methods, 11(1), 45–67. google scholar
8. Gong, Q., Song, M., He, P., & Zhang, B. (2023). Digital economy, space of flows and urban-rural income gap. Shanghai Journal of Economics, 6, 95–108. https://doi.org/10.19626/j.cnki.cn31-1163/f.2023.06.002 google scholar

9. Graham, J. W., Olchowski, A. E. and Gilreath, T. D. (2007). How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prev Sci, 8(3), 206–213. google scholar
10. Graham, M., & Anwar, M. A. (2019). The global gig economy: Towards a planetary labour market? First Monday, 24(4). https://doi.org/10. 5210/fm.v24i4.9913 google scholar
11. GSMA. (2022). The mobile economy: Sub-Saharan Africa 2022. GSM Association. https://www.gsma.com/mobileeconomy/wp-content/ uploads/2022/11/GSMA_ME_SSA_2022_English.pdf google scholar
12. Honaker, J. and King, G. (2010). What to do about missing values in time-series cross-section data. American Journal of Political Science, 54(2), 561–581. google scholar
13. Hussain, S., Qureshi, M. O., & Afzal, M. (2020). Empowering women through digital entrepreneurship: A case study of Pakistan. Journal of International Women’s Studies, 21(6), 1–18. https://vc.bridgew.edu/jiws/vol21/iss6/2 google scholar
14. International Labour Organisation (ILO). (2021). World employment and social outlook: The role of digital labour platforms in transforming the world of work. International Labour Office. google scholar
15. ITU. (2022). Measuring digital development: Facts and figures 2022. International Telecommunication Union. https://www.itu.int/hub/ publication/d-ind-ict_mdd-2022/ google scholar
16. Little, R. J. A., & Rubin, D. B. (2019). Statistical analysis with missing data (Vol. 793). John Wiley & Sons. google scholar
17. Mehta, A., Sharma, R., & Gupta, P. (2021). E-commerce and rural artisans: A study of Flipkart’s impact on small businesses in India. Journal of Rural Studies, 88, 428–437. https://doi.org/10.1016/j.jrurstud.2021.07.016 google scholar
18. Miao, Z. (2021). Digital economy value chain: Concept, model structure, and mechanism. Applied Economics, 53(37), 4342–4357. https:// doi.org/10.1080/00036846.2021.1899121 google scholar
19. Nambisan, S. (2017). Digital entrepreneurship: Towards a digital technology perspective of entrepreneurship. Entrepreneurship Theory and Practice, 41(6), 1029–1055. doi: 10.1111/etap.12254 google scholar
20. OECD. (2022). OECD employment outlook 2022: Navigating the COVID-19 crisis and recovery. OECD Publishing. https://doi.org/10.1787/1a 305c9c-en google scholar
21. Pata, U., Kartal, M., & Erdogan, S. (2023). Analysing the EKC hypothesis for technologically advanced countries: The role of ICT and renewable energy technologies. J Clean Prod 426, 139088. https://doi.org/10.1016/j.jclepro.2023.139088 google scholar
22. Pouri, M. J., & Hilty, L. M. (2021). The digital sharing economy: A confluence of technical and social sharing. Environmental Innovation and Societal Transitions, 38, 127–139. https://doi.org/10.1016/j.eist.2020.12.003 google scholar
23. Suri, T. and Jack, W. (2016). The long-run poverty and gender impacts of mobile money. Science, 354(6317), 1288–1292. https://doi.org/ 10.1126/science.aah5309 google scholar
24. Van Dijk, J. (2020). The digital divide. John Wiley & Sons. google scholar
25. World Bank. (2023). World development report 2023: Digital dividends. World Bank Publications. doi:10.1596/978-1-4648-2000-3 google scholar
26. White, I. R., Royston, P. and Wood, A. M. (2011). Multiple imputation using chained equations: Issues and guidance for practice. Stat Med, 30(4), 377–399. google scholar
27. Xu, Y., & Tao, J. (2025). Impact of the digital economy on income inequality: Evidence from China based on the partially linear functional coefficient model. Appl Econ Lett. https://doi.org/10.1080/13504851.2025.2450085 google scholar