Quantifying the Digital Divide: A Mixed-Method Analysis of Socio-Economic Determinants, Educational Employment Mismatch Index (EEMI), and Female Labor Force Participation in India (2017–2024)
DOI:
https://doi.org/10.7719/jpair.v62i1.963Keywords:
Labor Economics, Female Labor Force Participation, Secondary Data Analysis, descriptive, New Delhi, IndiaDisciplines:
Development Economics, Labor EconomicsAbstract
This study analyzes how digital access and educational attainment shape female labor force participation in India from 2017 to 2024. Using nationally representative unit-level data from the Periodic Labor Force Survey (PLFS) and National Family Health Survey (NFHS-5), it examines how digital inclusion and education jointly influence women’s access to formal and decent employment. The findings reveal that while digital connectivity improves women’s labor market entry, entrenched socio-cultural norms and regional disparities continue to restrict participation, particularly among rural and marginalized groups. To quantify this, disconnect, the study introduces the Educational–Employment Mismatch Index (EEMI), which captures the gap between women’s academic qualifications and their presence in the formal sector. EEMI is computed only for women with more than 12 years of education to ensure valid mismatch detection Results show that education alone does not ensure economic inclusion unless complemented by digital infrastructure, institutional support, and gender-responsive labor policies. The paper calls for integrated strategies that bridge these gaps and enable meaningful female workforce participation.
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References
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Asian Development Bank. (2021). Asian development outlook 2021: Employment and economic transformation. https://www.adb.org/sites/default/files/publication/692111/ado2021.pdf
Bhagavatheeswaran, L., Nair, S., Stone, H., Isac, S., Hiremath, T., & Halli, S. (2016). The role of education in women’s labour force participation in India: Barriers and pathways. International Journal for Equity in Health, 15(1), 88. https://doi.org/10.1186/s12939-016-0370-z
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Copyright (c) 2025 Meghna Badlani, Gaurang Rami
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Open Access. This article published by JPAIR Multidisciplinary Research is licensed under a Creative Commons Attribution-Noncommercial 4.0 International (CC BY-NC 4.0). You are free to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material). Under the following terms, you must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes.
