Today’s model question is based on an editorial on gender budgeting, published in The Hindu on September 16, 2025, under the title “India’s Economic Ambitions Need Better Gender Data.” It is aligned with the UPSC Mains syllabus and aims to help aspirants link contemporary policy debates with exam-focused answer writing.
India’s gender gap is not new, but India’s response to it must evolve. Examine the role of gender-disaggregated data in shaping inclusive policy and economic growth.
Answer: India ranks 131/148 in the Global Gender Gap Report 2025, with women contributing only 18% of GDP despite being nearly half the population. Inclusive growth requires that women’s role be visible in data and policy.
Role of gender-disaggregated data
- Visibility: Exposes structural barriers like poor transition from skilling to entrepreneurship.
- Targeted policy design: Uttar Pradesh’s WEE Index guided reforms in transport recruitment and infrastructure.
- Evidence-based budgeting: Data ensures effective gender budgeting, linking resources to gaps.
- Monitoring & accountability: Departmental MIS with sex-disaggregated data allows course correction.
- Regional growth: District-level insights can help states achieve trillion-dollar economy goals.
- Challenges: fragmented data collection, undercounting unpaid work, weak local capacity.
- Way forward: make gender disaggregation mandatory across departments, scale tools like WEE Index, strengthen gender budgeting, conduct independent gender audits, and build local capacity for data use.
- Conclusion: Gender data is not just a statistical requirement but a governance tool. For India’s $30 trillion aspiration by 2047, embedding gender insights into every policy and budget is essential to unlock its full demographic dividend.
While India has made measurable progress in education, health, and financial inclusion for women, economic participation remains weak. Discuss the structural barriers responsible for this paradox.
India has improved female GER (46.3%), reduced MMR (97 per 100,000 live births), and expanded financial inclusion with 280 million Jan Dhan accounts. Yet, female labour force participation is only 41.7%, with 90% in informal jobs.
Structural barriers:
- Education–employment gap: High enrolment, but weak transition to STEM and skilled jobs.
- Unpaid care burden: Women spend 7× more time on household work than men.
- Patriarchal norms: Social expectations prioritise domestic roles.
- Workplace exclusion: Limited childcare, unsafe transport, lack of basic facilities.
- Credit access barriers: Women entrepreneurs face systemic hurdles in finance.
- Informalisation: Majority in low-paid, insecure jobs without social security.
- Policy gaps: Schemes like Beti Bachao Beti Padhao show uneven outcomes due to weak implementation.
Why paradox persists: gains in education/health are neutralised by poor skilling-employment linkages, undervaluation of unpaid work, and restricted job opportunities.
Way forward: invest in care economy, ensure equal pay and safe workspaces, gender-sensitive credit, and social norm transformation.
Conclusion: Social progress alone cannot guarantee economic empowerment. Dismantling structural barriers is vital for women’s full participation in India’s growth story.