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Since its implementation in 2013, India’s direct benefit transfer system has ensured fiscal and social gains by expanding 16 times – starting from 11 crore beneficiaries to 176 crore now
India’s DBT system has ensured that programmes like MGNREGS and PM-KISAN achieved 98% timely wage transfers and Rs 22,106 crore in savings. (Image: AFP/File)
Reflecting high efficiency, India’s direct benefit transfer system has resulted in savings of Rs 3.48 lakh crore and halved subsidy allocations since it was implemented in 2013. Ensuring fiscal and social gains, it has expanded 16 times in this period starting from 11 crore beneficiaries to 176 crore now.
According to a quantitative assessment, conducted by the BlueKraft Digital Foundation, the direct benefit transfer (DBT) system has redefined welfare delivery by increasing transparency, curbing leakages, and ensuring precise fund distribution. The policy document evaluates data from 2009 to 2024 to assess DBT’s impact on budgetary efficiency, subsidy rationalisation, and social outcomes.
The analysis shows that it achieved a cumulative savings of Rs 3.48 lakh crore through leakage reduction, a halving of subsidy allocations (16% to 9% of total expenditure), and a 16-fold expansion in beneficiary coverage (11 crore to 176 crore). The newly developed welfare efficiency index (WEI), which quantifies fiscal and social gains, surged from 0.32 in 2014 to 0.91 in 2023, it showed.
It, however, showed that there is still a need to expand the system to remaining subsidy schemes, while bridging the urban-rural gap when it comes to digital infrastructure. This will ensure inclusive growth and equitable welfare governance.
The assessment further shows that after 2013, the DBT system was aggressively implemented via the regime change at the Centre in 2014. The new government prioritised transparency and digitisation through the JAM Trinity (Jan Dhan accounts, Aadhaar authentication, and mobile connectivity), which became the backbone of DBT’s success.
WHAT ARE THE KEY FINDINGS?
- Fiscal Optimisation: Despite a rise in welfare budgets (Rs 2.1 lakh crore in 2009-10 to Rs 8.5 lakh crore in 2023-24), subsidy allocations declined proportionally, reflecting DBT-driven efficiency.
- Sectoral Impact: Food subsidies accounted for 53% of total savings (Rs 1.85 lakh crore), while programmes like MGNREGS and PM-KISAN achieved 98% timely wage transfers and Rs 22,106 crore in savings, respectively.
- Enhanced Targeting: Aadhaar-linked authentication eliminated ghost beneficiaries, enabling coverage expansion.
WHAT ARE THE POLICY RECOMMENDATIONS?
- Expand DBT Coverage: Transition remaining subsidy-based schemes to DBT.
- Strengthen Digital Infrastructure: Prioritise rural and semi-urban banking access to bridge inclusion gaps.
- Leverage Advanced Analytics: Integrate AI-driven fraud detection to further minimise leakages.
- Improve Grievance Redress: Establish robust mechanisms to address exclusion.
The analysis stated that DBT’s impact contradicts the critique of reduced welfare spending by optimising resource use and enabling broader beneficiary reach with lower fiscal outlays. By replacing inefficient subsidies with targeted transfers, India has achieved measurable gains in welfare efficiency.
The study employed a mixed-methods approach, synthesising Union Budget data, DBT portal records, and secondary sources. Analytical tools include correlation analysis, Granger causality tests, and the Welfare Efficiency Index (WEI) – a composite metric weighting DBT savings (50%), subsidy reduction (30%), and beneficiary growth (20%).
Here are the detailed results:
BUDGETARY ALLOCATION TRENDS
- Pre-DBT Era (2009-2013): Subsidies averaged 16% of total expenditure (Rs 2.1 lakh crore annually), with leakages.
- Post-DBT Era (2014-2024): Subsidies declined to 9% of expenditure (2023-24) despite a 16-fold surge in beneficiary coverage (11 crore to 176 crore).
- Covid-19 Outlier: A temporary spike in subsidies (2020-21) reflected emergency fiscal measures, but efficiency rebounded post-pandemic.
The assessment said a reduced subsidy burden, despite expanded coverage, highlights DBT’s role in optimising fiscal allocation. It does this by eliminating “ghost” beneficiaries and middlemen, so that funds reach genuine recipients.
SECTORAL ANALYSIS
- Food Subsidies (public distribution system): Rs 1.85 lakh crore saved (53% of total savings), attributed to Aadhaar- linked ration card authentication.
- MGNREGS: 98% timely wage transfers (saving Rs 42,534 crore) due to DBT-driven accountability.
- PM-KISAN: Rs 22,106 crore saved by deleting 2.1 crore ineligible beneficiaries.
- Fertiliser Subsidies: Reduced sales of 158 lakh MT, saving Rs 18,699.8 crore through targeted disbursement.
Sector-specific savings highlight DBT’s disproportionate impact on high-leakage programmes. Food subsidies, historically prone to diversion, benefited most from biometric authentication, while wage schemes like MGNREGS saw efficiency gains through direct transfers.
CORRELATION AND CAUSALITY FINDINGS
The analysis showed that increase in DBT savings caused a drop in subsidy allocations, proving it reduced leakages and improved targeting.
More savings allowed the government to expand welfare programmes, reaching more beneficiaries due to improved fund use. The DBT system’s precisely targeted broader coverage with reduced fiscal outlays.
WELFARE EFFICIENCY INDEX OUTCOME
The analysis further states that the WEI’s rise quantifies systemic improvements, stressing that efficiency gains from multi-dimensional factors, and not merely budget cuts. This index provides a replicable model for global policymakers to evaluate welfare reforms.
The WEI surged from 0.32 (2013) to 0.91 (2023). This was driven by DBT savings at Rs 3.48 lakh crore cumulative leakage reduction; subsidy reduction from 16% to 9% of expenditure; increase in the number of beneficiaries with 16-fold expansion.
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