Context: India aspires to become a $30 trillion economy by 2047, but women who constitute nearly half the population contribute only 18% to the GDP. Their invisibility in data makes gender-disaggregated data crucial for inclusive growth.
Relevance of the topic:
Prelims: Gender budgeting, WEE Index (Uttar Pradesh)
Mains: Role of gender data in inclusive growth, governance reforms, women’s economic empowerment.
Almost 196 million employable women in India are outside the workforce. The biggest barrier to women’s economic empowerment is not merely the lack of opportunities but their invisibility in data. Without gender-disaggregated data their participation gaps across education, skilling, employment, and entrepreneurship will remain stalled.
Women’s Economic Empowerment Index:
- The WEE Index was recently launched by Uttar Pradesh. It aims to track the impact of government schemes on women's economic participation across all 75 districts of the state.
- It is India’s first district-level tool to track women’s participation across five economic levers:
- Employment
- Education and skilling
- Entrepreneurship
- Livelihood and mobility
- Safety and inclusive infrastructure
- The index shifts focus from participation numbers to structural barriers that limit women’s empowerment. E.g., Data showed women dominate skilling enrolments but remain very low in entrepreneurship due to poor access to credit.
Why Gender Data is Needed?
- Inclusive Growth: Inclusive economic growth cannot occur if half the population remains invisible in policy datasets. Gender-disaggregated data ensures women’s contribution is measured, valued, and integrated into growth strategies.
- Making Gaps Visible: Without a gender lens, existing indices on health, economy, and infrastructure mask inequities. Data reveals critical drop-off points such as high female dropout rates after Class 12 and post-graduation, or the gap between skilling enrolment and entrepreneurship.
- Catalyst for Reforms: Visibility of inequities prompts departments to act. E.g., In Uttar Pradesh, data on low female representation among bus drivers and conductors, led to new recruitment strategies and women-friendly infrastructure such as women’s restrooms in bus terminals.
- Shifting beyond Participation Rates: Gender data helps track retention, leadership roles, re-entry into work, and quality of employment, not just surface-level participation. It highlights systemic barriers such as limited access to credit for women entrepreneurs despite high skilling enrolments.
- To improve Gender Budgeting: Gender budgeting is often confined to welfare schemes or finance departments. True gender budgeting requires applying a gender lens to every rupee spent in sectors like education, infrastructure, energy, and housing, and this is only possible if robust gender-disaggregated data exists.
- Guiding Policy and Investment: Data makes it possible to design district-wise gender action plans, guiding budget allocations and infrastructure priorities.
A robust framework such as the WEE Index can be replicated and scaled in other states as well. It can help the states translate intent into implementation: turning data into district-wise gender action plans that guide budget allocations, infrastructure priorities and programmatic reforms.



