E-Paper
India’s Gender Budget needs to count the women it reaches
This article is authored by Ankita Bhat, senior manager and Muskan Singh, associate, MicroSave Consulting (MSC).
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Twenty years after the Gender Budget Statement (GBS) was introduced, India has built a gender budgeting architecture few others have attempted: A mandated annual statement, a classification system grouping schemes by the share of spending estimated to benefit women, and gender budget cells across ministries. The 2026-27 statement reports ₹5.01 lakh crore for women and girls, 9.37% of the Union Budget.
India has institutionalised gender-responsive budgeting (GRB). The next opportunity is to strengthen the data systems beneath it, so gender budgeting captures reach and informs planning. Take G-RAM-G (formerly MGNREGA). The budget share tells us how much is allocated for women. But to understand reach and impact on women, we need to know how many women get work, how many days of work they receive, and what changes for them. The systems largely exist; departments already maintain these records. What is needed is a field that captures sex disaggregation in the data collection format, not a new system.
Nearly eight out of ten rupees in the 2026–27 Gender Budget go to schemes that benefit both women and men. But how much of that money reaches women? For many such schemes, this is not directly known; the share benefiting women is estimated using available information. Think of a ₹10 lakh family car: We know its cost, but not each person’s share of the benefit unless we know who uses it and how often. The government faces a similar problem when schemes serve women and men.
This challenge is not unique to India, several countries implementing gender budgeting at scale face similar challenges. In India, line departments use programme information and prescribed approaches to estimate the share attributable to women when records do not routinely capture sex-disaggregated information. Reliable, sex-disaggregated administrative data is foundational to evidence-based GRB: It can help governments assess who allocations reach, test the basis for attribution, and use the evidence to shape future spending.
This is why the next phase has to move outward from the centre. Gender budgeting may be designed at 30,000 feet, but its ultimate test is on the ground: whether a panchayat can build a girls’ toilet, or a health programme can reach adolescent girls needing screening. Reform happens where the underlying records are created.
And this is not a new idea for government. A JICA-supported project with the Himachal Pradesh government on forest ecosystems and livelihoods, for instance, collects sex-disaggregated data on participation in project activities and other project outcomes. An ADB-supported human capital project with the Meghalaya government similarly collected and analysed sex-disaggregated data to monitor women’s participation and identify implementation gaps. These examples show that the challenge is not collecting gender data from scratch; it is making this kind of data capture routine across government programmes.
Three practical reforms can turn principle into practice.
First, sex-disaggregated data belongs on the source document. Small changes to existing formats, adding fields to muster rolls, recording beneficiaries by sex, or capturing person-days by sex can make a large difference. Linking this data to expenditure can show who programmes reach and how spending benefits women and men.
Second, every estimate should show its basis. A simple field indicating whether a figure is enumerated or estimated would make this visible. It would help departments identify where estimates are weakest, while nodal authorities could target technical support accordingly.
Third, provide technical support where data is generated. GRB training has often focused on gender focal points; the next step is to support the technical, MIS, accounts and programme staff who create and reconcile these records. The support model used in externally aided projects can be adapted for nodal departments and administrative academies.
Better source data would make the GBS more useful for planning. Verified beneficiary data could inform scheme appraisal, identify gaps in reach, and shape future allocations, turning the statement from annual reporting into an input to budget decisions. For policymakers, this means treating routine records as gender-budgeting infrastructure. For departments, it means manageable changes: revised forms, defined indicators, named officers, and sustained support.
The first 20 years of gender budgeting established that women belong in the Union Budget. The next should make the numbers answerable: who benefits, what changes, what impact, and how we know.
(The views expressed are personal)
This article is authored by Ankita Bhat, senior manager and Muskan Singh, associate, MicroSave Consulting (MSC).
