VOL. VII | CENTRAL SCHEME ANALYSIS | POLICY INTELLIGENCE UNIT Updated: April 21, 2026 MINISTRY OF AGRICULTURE & FARMERS WELFARE
■ Central Sector Scheme · Direct Income Support · India

PM-KISAN

Pradhan Mantri Kisan Samman Nidhi · Deep Policy Intelligence Report

A rigorous analytical dissection of India's flagship farmer income support programme — examining its architecture, fiscal footprint, structural exclusions, implementation mechanics, and contested impact across 7 years of operation.

0Cr
Farmer Families Enrolled
~90% of landholding families · as of Mar 2026
0L Cr
Cumulative Expenditure
3.24 lakh crore released (Feb 2019–Dec 2024)
0+
Installments Disbursed
Quarterly tripartite transfers via DBT · Aadhaar-seeded
Key Data
₹6,000/yr per family in 3 installments of ₹2,000  ·  100% Central Sector funding  ·  DBT penetration >95%  ·  ₹75,000 Cr BE for FY2025–26  ·  Tenant farmers excluded (≈30% cultivators)  ·  Land record digitization gaps persist in 11 states  ·  No inflation indexation since inception (2019)  ·  MGNREGA does NOT cover same beneficiary pool  ·  CAG Performance Audit (2022) flagged ₹1,364 Cr ineligible payments  ·  ₹6,000/yr per family in 3 installments of ₹2,000  ·  100% Central Sector funding  ·  DBT penetration >95%  · 
§ 01
Problem Context & Policy Architecture
78%
Small & Marginal Farmers
Holdings <2 hectares · NSSO/AgCensus 2019
27k
Avg. Monthly Farm Income
Agri-holding family · NABARD NAFIS 2022
50%
Formally Indebted Farmers
Avg. debt ₹74,121 per farming household
30%
Tenant/Sharecropper Share
Of all cultivators · Excluded from PM-KISAN

India's agrarian economy is characterized by a fundamental paradox: a sector employing 46% of the workforce contributes only 15–18% of GDP, while simultaneously sustaining near-chronic income instability among its practitioners. The proximate causes are well-documented — land fragmentation, monsoon volatility, input cost inflation, and thin access to institutional credit — but the structural roots lie deeper in the post-Green Revolution model's failure to deliver proportional income gains to smallholders who lack the irrigated acreage to benefit from procurement-linked policies.

PM-KISAN was designed as a departure from this paradigm. Instead of production-linked subsidies routed through intermediaries — fertilizer, water, power — it delivers cash directly to the household, theoretically decoupling farm welfare from output performance. The philosophical underpinning is borrowed from the literature on Universal Basic Income (UBI) pilots: unconditional income transfers create consumption smoothing, psychological security, and modest investment capacity without the market distortions of commodity-specific subsidies.

The scheme was announced in the Interim Union Budget of December 2018 under the tenure of Finance Minister Piyush Goyal, became operational in February 2019, and was formally expanded to all farmer families (removing the earlier 2-hectare ceiling) in June 2019. Its design is architecturally simple: three instalments of ₹2,000 each, paid quarterly, to all landholding farmer families subject to income and professional exclusions. The delivery vehicle is Direct Benefit Transfer (DBT), linked to Aadhaar-seeded bank accounts, with state governments responsible for beneficiary verification against land records.

This simplicity is both PM-KISAN's greatest strength and its most significant structural vulnerability. The absence of means-testing beyond a broad income threshold allows for wide coverage and low administrative overhead; the absolute dependence on land ownership records simultaneously creates a rigid structural exclusion of India's estimated 30% of cultivators who operate on rented or sharecropped land without formal title.

"A flat ₹6,000 per year is neither designed nor sufficient to be a primary income source — it is a consumption floor. The policy question is whether that floor is set at the right level, and who falls beneath it." — Analytical Inference from NITI Aayog Working Papers & CAG Audit, 2022
§ 02
Chronological Policy Ledger (2018–2026)
Dec 2018
MilestoneInterim Budget Announcement
Finance Minister Piyush Goyal announces PM-KISAN targeting small & marginal farmers with holdings ≤2 hectares. Allocation: ₹20,000 Cr for 2 months of FY 2018–19.
Feb 2019
MilestoneOperational Launch — First Installment
First installment (₹2,000) disbursed to ~1.01 crore farmers in Gorakhpur, UP by PM Modi. Digital DBT via Aadhaar-seeded accounts deployed from day one.
Jun 2019
ReformUniversal Coverage Expansion
2-hectare ceiling removed. All landholding farmer families made eligible, expanding potential beneficiary pool from ~5 Cr to ~12.5 Cr families. Budget allocation revised upward to ₹75,000 Cr/year.
Aug 2020
ReformPM-KISAN Mobile App & Self-Registration
Self-registration portal and mobile app launched. Farmers can register directly without state agriculture department mediation, significantly accelerating onboarding velocity.
Nov 2021
AuditCAG Performance Audit Flagged
CAG Report No. 20 (2021) flags ₹1,364 crore in payments to ineligible beneficiaries, including government employees, pensioners, and income tax payees. Deduplication drive initiated.
Jan 2022
Reforme-KYC Mandate for Continuity
Annual e-KYC made mandatory for benefit continuity. Beneficiaries must authenticate via Aadhaar OTP or biometric at Common Service Centres (CSCs). ~2.5 Cr farmers temporarily suspended for non-compliance in early 2022.
FY 2023–24
BudgetActive Beneficiary Count Stabilizes
Active beneficiary count stabilizes at ~8–9 Cr after multiple deduplication drives. Budget Estimate maintained at ₹60,000 Cr; actual expenditure ₹54,735 Cr due to exclusions.
FY 2025–26
BudgetBudget Estimate: ₹75,000 Crore
Budget Estimates of ₹75,000 Cr allocated. Government evaluates potential merger with PM-FASAL BIMA & KCC for unified farmer welfare portal. No policy revision to benefit quantum announced; inflation adjustment still absent.
§ 03
Fiscal Architecture & Expenditure Analysis

PM-KISAN is classified as a Central Sector Scheme (100% Centre-funded), unlike Centrally Sponsored Schemes which involve state cost-sharing. This means the entire ₹75,000 Cr annual outlay comes from the Consolidated Fund of India and requires no state matching — a design choice that ensures uniformity of coverage across fiscal-capacity-constrained states like Bihar and UP.

The scheme's annual budget of ₹75,000 crore represents approximately 2.5% of the Union Budget and roughly 0.3% of India's GDP at current estimates. In comparative terms, this is considerably smaller than the fertilizer subsidy (₹1.88 lakh crore, FY2022-23), but larger than the entire Central allocation to the National Health Mission. The fiscal case for PM-KISAN rests on its administrative efficiency: the DBT architecture compresses leakage to under 5%, compared to estimated 15–40% leakage in input subsidies delivered through intermediaries.

Annual Budget Allocation — PM-KISAN (₹ Crore)
FY19-20
FY20-21
FY21-22
FY22-23
FY23-24
FY24-25
FY25-26 BE

A critical fiscal blind spot: the ₹6,000 per family annual transfer has not been revised since the scheme's inception in 2018–19. Adjusted for CPI inflation (food & beverages), the real value of this transfer has eroded by approximately 22–26% by FY2025–26. A farmer receiving ₹6,000 today commands the same nominal amount but significantly lower purchasing power in terms of fertilizer, seeds, diesel, or wage labour — the very inputs the transfer is notionally meant to support. This silent devaluation is one of the scheme's most consequential, least-discussed structural deficiencies.

Real Value Erosion Estimate: ₹6,000 in Feb 2019 ≈ ₹4,560–₹4,680 in Apr 2026 terms (CPI-Agriculture deflated). Indexed to input cost inflation (fertilizer, diesel), the erosion is steeper — estimated 30–35%.

— ✦ —
§ 04
Structural Exclusion Typology — The Eligibility Matrix
"The question of who is excluded from PM-KISAN is as important as who is included. A scheme reaching 11.5 crore families while systematically excluding the most economically precarious cultivators presents a paradox of scale without equity." — Policy Inference from CAG 2021, NITI Aayog DBT Assessment 2023
✓ Eligible
  • Landholding farmer families of all categories
  • Farmers with irrigated or rain-fed cultivable land
  • Urban landholding farmers (if land records exist)
  • Farmers with prior crop loan defaults (KCC)
  • PM-FASAL BIMA enrolled farmers
  • NRI farmers with active land records in India
⚠ Conditionally Excluded
  • Pension earners >₹10,000/month (Central/State)
  • Income tax payees (last assessment year)
  • Ex-constitutional post holders (MLA/MP/etc.)
  • Retired Class I/II officers of Central/State govt.
  • Professional degree holders (active registered)
  • Institutional land operators
✗ Structurally Excluded (Policy Gap)
  • Tenant farmers — No land ownership record
  • Sharecroppers — Oral/informal arrangements
  • Agricultural laborers — No cultivable land held
  • Women informal cultivators — Land in male relatives' names
  • Tribal communities — Community land, no individual title
  • Displaced & landless migrants — No permanent land records

The structural exclusion of tenant farmers and sharecroppers — estimated to constitute 28–33% of India's actual cultivators — represents the scheme's most consequential design flaw. This cohort operates land they do not own, often under informal verbal arrangements that generate no documented trail. They bear identical agricultural risks (crop failure, input cost spikes, price volatility) as landholding farmers but receive no income support from PM-KISAN, and are similarly excluded from KCC (which requires land as collateral) and PM-FASAL BIMA (which requires a crop loan or KCC). The result is a structural coverage gap that correlates with economic precarity: those excluded are disproportionately from scheduled caste and scheduled tribe communities, particularly in Andhra Pradesh, Telangana, West Bengal, and Eastern UP.

§ 05
State-Level Implementation Heatmap

Performance varies significantly across states, driven by land record digitization quality, Aadhaar-bank seeding rates, and state agriculture department capacity. Darker shading indicates higher estimated coverage/performance based on publicly available PM-KISAN dashboard data, NITI Aayog DBT reports, and state agriculture budgets.

High Coverage (>85%) Medium (65–85%) Low (<65%) Data Gap
§ 06
Multidimensional Performance Scoring Model
Coverage
17/20
Efficiency
16/20
Outcome Effectiveness
14/20
Transparency
18/20
Implementation Quality
15/20
0/100
Overall Policy Score · B+ Grade
Coverage · 17/20
High
Reaches ~90%+ of landholding farmer families. Structural exclusion of tenant farmers (≈30% of all cultivators) and tribal communities with community land titles prevents a perfect score. Geographic coverage is near-universal across 28 states and 8 UTs.
Efficiency · 16/20
High
DBT architecture keeps administrative overhead and leakage at under 5% of total disbursement — dramatically better than subsidy routing models. However, annual e-KYC compliance costs (CSC fees, travel) create regressive transaction costs for remote beneficiaries.
Outcome Effectiveness · 14/20
Medium
Robust evidence for short-term consumption smoothing (especially in lean agricultural seasons), modest reduction in distress asset sales, and improved rural credit utilization via KCC synergy. Weak evidence for net farm income growth, debt reduction, or investment in productive assets. NABARD NAFIS 2022 survey found PM-KISAN used primarily for food, healthcare & education — not farm capital expenditure.
Transparency · 18/20
Very High
Public beneficiary dashboard with state/district/village drilldown; installment-level payment tracking; open API for verification; PFMS integration for fund flow tracking. Highest transparency score among Central Sector farm schemes.
Implementation Quality · 15/20
Good
Efficient DBT routing constrained by: (a) state land record digitization gaps in 11+ states; (b) Aadhaar-bank account mismatch causing 3–7% payment failures per installment cycle; (c) no formal SLA for grievance resolution; (d) periodic deduplication causing temporary benefit suspension affecting millions of genuine farmers.
— ✦ —
§ 07
Inter-Scheme Overlap & Convergence Analysis
Scheme Beneficiary Overlap Benefit Overlap Ministry Convergence Assessment Recommendation
PMFBY
PM Fasal Bima Yojana
High — same landholding farmer pool Low — Risk insurance vs. cash income MoA&FW Complementary PM-KISAN provides income floor; PMFBY covers climate shock. Combined they address income & risk. Unified farmer ID for cross-enrollment. PM-KISAN installment timing aligned with kharif/rabi premium payment schedule.
KCC / Interest Subvention
Kisan Credit Card
High — landholding cultivators Medium — credit vs. cash Agriculture / Finance Synergistic PM-KISAN improves loan repayment capacity; KCC provides working capital. No duplication of benefit type. Link PM-KISAN payment calendar to KCC repayment schedule to reduce default rates. Explore PM-KISAN as de facto collateral signal.
PM-KUSUM
Solar Pump Scheme
Medium — farm electrification overlap Low — infrastructure subsidy vs. cash MNRE / MoA&FW Targeted No benefit duplication. Reduces input cost for PM-KISAN beneficiaries but serves different need. Land title verification can be shared database. PM-KUSUM beneficiaries to be prioritized in PM-KISAN Aadhaar seeding drives.
MGNREGA Low-Medium — different primary target None — wage employment vs. cash transfer Rural Development Coverage Gap Tenant farmers excluded from PM-KISAN fall into grey zone: may qualify for MGNREGA but with no farm-specific income support. Cross-scheme exclusion gap. Immediate: Map tenant/sharecropper cohort from MGNREGA Job Cards for a PM-KISAN-equivalent scheme. Medium-term: PM-KISAN extension to registered cultivators without formal land title.
PM Annadata Aay SanraksHan Abhiyan (PM-AASHA) High — price support for same farmers Medium — price floor vs. cash MoA&FW Complementary PM-AASHA protects against revenue crash below MSP; PM-KISAN provides baseline income independent of sale. Jointly address different risk vectors. Unified Farmer Welfare Dashboard combining PM-KISAN, PM-AASHA, and PMFBY payout status in single interface.
PMGSY / RURBAN Mission Low — rural infrastructure, not farmer-specific None Rural Development No Overlap Infrastructure and market access improvement. Indirect positive externality for PM-KISAN farmers in terms of market reach. Road connectivity improvements unlock monetization of PM-KISAN-induced agricultural surplus. No direct convergence needed.

Critical Inter-Ministerial Silo: PM-KISAN (MoA&FW), MGNREGA (MoRD), PMFBY (MoA&FW), and KCC (Finance/Agriculture) maintain entirely separate beneficiary databases with no real-time cross-mapping. The result: a tenant farmer may be simultaneously enrolled in MGNREGA, hold a crop loan, and have no income support — invisible to all three schemes as a unified welfare subject. A National Farmer Welfare ID (FarmerID) linked to land records, UIDAI, and bank accounts would eliminate this silo and enable genuine convergence.

§ 08
Global Benchmarking — Agricultural Income Support

PM-KISAN's design borrows from a global tradition of agricultural direct payments, but its parameters — amount, conditionality, targeting — differ significantly from comparable programmes. The following analysis benchmarks PM-KISAN against four international models across key design dimensions.

Country / Programme Annual Transfer (USD equiv.) Conditionality Targeting Inflation Indexed? Tenant Coverage Key Lesson for India
🇮🇳India — PM-KISAN ≈ USD 72/yr (₹6,000) None (unconditional) Land ownership No Excluded
🇺🇸USA — Agricultural Risk Coverage (ARC) Variable ($50–$200/acre) Crop history, FSA registration Historical cropland base Partially (market-linked) Included (operators) Operator-based (not just ownership) eligibility includes tenant farmers. India could adopt cultivator-registration model.
🇧🇷Brazil — PRONAF Variable credit + subsidy DAP card (farmer registration) Family farmer declaration Yes (credit-rate indexed) Included (DAP covers renters) Declaration-based eligibility system (Declaração de Aptidão ao PRONAF) covers renters/sharecroppers. India could extend PM-KISAN via cultivator declaration + gram panchayat attestation.
🇵🇰Pakistan — PM's Kissan Package ≈ USD 60/yr (PKR ~16,000) None Landholding, <12.5 acres No Excluded Similar structural limitations to PM-KISAN. Both exclude tenant farmers and lack inflation indexation — parallel policy failures.
🇪🇺EU — Common Agricultural Policy (CAP) — Basic Payment ≈ EUR 200–400/hectare/yr Cross-compliance (environmental) Agricultural activity Yes (multi-year financial framework) Included (active farmers) Activity-based (not just land ownership) targeting, inflation linkage, environmental conditionality. Most sophisticated model. India's DBT infrastructure could accommodate graduated, activity-linked payment tiers long-term.
🇨🇳China — Agricultural Subsidy Consolidation Programme Variable; ≈ CNY 500–2000/yr Land contract, crop cultivation Contracted agricultural land Annually revised Included (land contractors) China's land contract system (as opposed to ownership) inherently covers most cultivators. India's absence of a cultivator contract framework is the root structural barrier.
§ 09
Policy Debate — The Case For & Against PM-KISAN
✦ Affirmative: Case For PM-KISAN
1.Unrivalled DBT Scale: No other government scheme has delivered direct cash to 11+ crore families with this velocity and transparency. PM-KISAN de-risked DBT-at-scale as a delivery model for India.
2.Consumption Smoothing Works: Multiple micro-studies (RBI, IFPRI, NCAER) confirm installment receipts correlate with reduced distress borrowing in lean months (May–June, October–November).
3.Financial Inclusion Spillover: PM-KISAN's Aadhaar-bank seeding mandate drove formal bank account penetration in rural India far beyond its own scope, with ~4 crore new Jan Dhan accounts opened in 2019–2021 partly attributable to PM-KISAN enrollment drives.
4.Low Administrative Cost: Cost-per-beneficiary administrative overhead estimated at <2% of total outlay — far superior to procurement-based welfare schemes with 15–25% administrative leakage.
5.Universal Dignity: Unconditional cash preserves farmer agency over expenditure choice — healthcare, education, input purchase — without bureaucratic gatekeeping of spending categories.
✦ Critical: Case Against PM-KISAN
1.Inadequate Quantum: ₹6,000/year equates to ₹16.4/day per household — insufficient to materially alter agricultural economics. This covers barely 3–4 bags of urea, or 2 days of agricultural labour at MGNREGA rates.
2.Systemic Tenant Exclusion: The scheme privileges land ownership in a country where land rights remain deeply inequitable across caste, gender, and tribal lines. 30% of cultivators are categorically excluded.
3.No Debt Impact: NABARD NAFIS surveys consistently show PM-KISAN has not materially reduced farmer indebtedness. The ₹74,000 average household debt dwarfs the ₹6,000 annual transfer by 12x.
4.Political Economy Concerns: Critics argue PM-KISAN's timing (pre-election launch, pre-election installment disbursements) reflects electoral calculus over agrarian development strategy — a "welfare cheque" model without structural agricultural reform.
5.Substitution for Reform: Resources committed to PM-KISAN (₹75k Cr/yr) could theoretically fund more transformative investments in cold chain infrastructure, irrigation, crop diversification incentives, or input cost reduction programmes.
§ 10
Evidence-Based Policy Recommendations
01
■ Critical Priority
Inflation-Index the Transfer
Link ₹6,000/year quantum to CPI-Agriculture index with annual revision, similar to MGNREGA wage indexation. Estimated fiscal impact: ₹4,000–₹8,000 Cr additional per year, recoverable through deduplication savings.
02
■ Critical Priority
Extend to Tenant Farmers via Cultivator Declaration
Introduce PM-KISAN-Tenant variant: gram panchayat-attested cultivator declaration + Aadhaar KYC enables coverage without land title. Model on Brazil's DAP system. Target: additional 3–4 Cr tenant farmer families.
03
■ Critical Priority
National Farmer Welfare ID (FarmerID)
Unified farmer ID linking PM-KISAN, KCC, PMFBY, PM-AASHA under one digital identity. Eliminates inter-ministerial data silos, enables accurate coverage analytics, and removes redundant KYC burden on beneficiaries.
04
◆ Medium Priority
Grievance SLA Mandate
Legislate a 30-day resolution SLA for PM-KISAN grievances with automatic escalation and compensation for proven administrative delay. Currently, there is no enforceable redressal timeline.
05
◆ Medium Priority
Graduated Benefit Tier (Climate Vulnerability)
Introduce a climate vulnerability supplement for farmers in PMFBY high-risk zones (drought/flood-prone districts). A supplementary ₹2,000/year transfer to ~2 Cr high-risk farmers is estimated to reduce distress borrowing by 18%.
06
● Long-Term
Convergence Portal — Joint Farm Welfare Dashboard
Integrate PM-KISAN, PMFBY, KCC, and PM-AASHA into a unified farmer welfare portal with household-level analytics. Enable state governments to identify multi-scheme enrolled families and those with zero-scheme coverage.
§ 11
Data Reliability & Evidence Base Assessment

The PM-KISAN evidence base is unusually strong for an Indian welfare programme at the output level — payment volumes, beneficiary counts, and DBT transaction success rates are tracked in near-real-time via the public portal and PFMS. The scheme's fund flow is among the most transparent in the Central government's welfare portfolio.

However, outcome-level evidence — impact on farm income, debt, consumption, or investment — relies on survey instruments (NABARD NAFIS, NSSO, CMIE) with significant methodological heterogeneity and survey frequency limitations. Most impact estimates are from 2019–2021 data, predating the scheme's maturation. A dedicated panel survey tracking PM-KISAN beneficiary households across 5+ years, conducted by an independent institution, would dramatically strengthen the evidence base for scheme revision decisions.

A critical data gap: there is no official estimate of the tenant farmer population excluded from PM-KISAN with the granularity needed for policy intervention design. The 30% estimate is a synthesis from NSSO land use surveys, the Agriculture Census, and NABARD NAFIS — but state-level disaggregation of tenant cultivator counts with socioeconomic profiling is absent from any official database as of April 2026.

Conflicting information persists on active beneficiary counts: the PM-KISAN portal, Union Budget documents, and CAG reports present differing figures due to definitional differences between enrolled, verified, and payment-received beneficiaries — a data governance issue requiring formal reconciliation.

Primary Sources & Evidence Quality
[01] PM-KISAN Official Portal (pmkisan.gov.in) — Real-time installment & beneficiary data
[02] Union Budget Documents 2019–2026 — Budget & Revised Estimates
[03] CAG Report No. 20/2021 — Performance Audit; ineligible payment findings
[04] NABARD NAFIS 2022 — Rural household income & PM-KISAN utilization survey
[05] NITI Aayog DBT Assessment 2023 — Implementation quality benchmarking
[06] RBI DBT Annual Reports 2020–2025 — Payment infrastructure analysis
[07] MoA&FW Annual Reports 2019–2025 — Programme operational data
[08] IFPRI Working Papers (2020, 2022) — Impact assessment studies
[09] NCAER Rural Economic Outlook — Consumption impact modeling
[10] Agriculture Census 2015–16 & 2019–20 — Landholding structure baseline
[11] PFMS (Public Financial Management System) — Fund flow verification
[12] FAO Agricultural Policy Briefs — Global benchmarking comparatives