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Politics & Governance19 Oct 2026 · about 6 min

Why Modi government’s rural jobs scheme is a sham in drought-hit Maharashtra district

The brief

VB-G RAM G is India’s revamped rural employment guarantee scheme, introduced in July 2025 to replace the Mahatma Gandhi National Rural Employment Guarantee Act. Its purpose is to provide paid work when rural households need income, while creating village infrastructure such as canals, ponds, roads, rainwater-harvesting structures, community buildings, and agricultural works. Work begins with a demand from the village. After approval by the gram sabha, an electronic muster roll is created. The gram panchayat assigns work to labourers who requested employment during the previous 15 days. The worksite is geo-tagged, and attendance is supposed to be recorded daily through a mobile monitoring app. The scheme matters most during crop failures, when farm income disappears. In Beed, Satish Shirsath earned Rs 3,000 after six days of canal digging. However, he then found no further work and migrated to Sangli. The article shows that the scheme’s promise depends on both available work and honest monitoring.

01

What is the VB-G RAM G scheme, and how is it supposed to provide work to rural households?

VB-G RAM G is India’s revamped rural employment guarantee scheme, introduced in July 2025 to replace the Mahatma Gandhi National Rural Employment Guarantee Act. Its purpose is to provide paid work when rural households need income, while creating village infrastructure such as canals, ponds, roads, rainwater-harvesting structures, community buildings, and agricultural works.

Work begins with a demand from the village. After approval by the gram sabha, an electronic muster roll is created. The gram panchayat assigns work to labourers who requested employment during the previous 15 days. The worksite is geo-tagged, and attendance is supposed to be recorded daily through a mobile monitoring app.

The scheme matters most during crop failures, when farm income disappears. In Beed, Satish Shirsath earned Rs 3,000 after six days of canal digging. However, he then found no further work and migrated to Sangli. The article shows that the scheme’s promise depends on both available work and honest monitoring.

02

How severe is the drought in Maharashtra and Beed, and how many workers were recorded as working under the scheme on October 4?

The drought is extensive across Maharashtra. More than two-thirds of the state’s tehsils—304 out of 358—were declared drought-hit after monsoon rainfall fell 18% below normal. Beed was hit harder, with a 37% deficit between July and September. The district collector called it the worst rainfall shortfall there in a decade.

The employment figures are striking. On October 4, 76,822 workers were marked present at worksites across Maharashtra’s 36 districts. Beed accounted for 40,267 of them, more than half the state total. That unusually high number suggested a large response to the drought and lack of farm work.

But Scroll’s visits raised serious doubts about the figures. Five Beed sites had work orders covering 47 labourers, yet no workers were present. Names and photographs had been uploaded as live attendance. If all 40,267 recorded workers were genuine, that day’s wages would have totalled Rs 1.2 crore.

03

How were workers’ names, photographs, and attendance allegedly falsified at worksites?

The alleged fraud targeted the scheme’s digital proof of attendance. Workers’ names appeared on electronic muster rolls, and photographs were uploaded to show that they were present at a specific worksite. Yet several listed workers told investigators they did not know about the work orders or where their wages were being credited.

A whistleblower claimed that fake GPS applications were used to create fraudulent location data. The whistleblower also said photographs collected during eKYC, or digital identity verification, were reused and presented as live, geo-tagged worksite photographs. Scroll reported finding the same pattern while checking five work orders.

The records showed attendance for 47 labourers marked between 8.55 am and 9.30 am on October 4. When the sites were visited, no workers were present. Rozgar sevaks said some gram panchayat members were involved in siphoning wages. Officials said 23,000 entries had been rejected after discrepancies emerged.

04

Who is responsible for creating work orders, preparing muster rolls, recording attendance, and paying wages under the scheme?

The process begins with a village-level demand for employment. After the gram sabha approves a project, an electronic muster roll is created. The gram panchayat then assigns the work to labourers who demanded employment during the previous 15 days. This makes the panchayat central to creating work orders and allocating workers.

Rozgar sevaks handle the muster roll and mark attendance under the scheme. They must use the National Mobile Monitoring Service App to record daily, live, time-stamped, and geo-tagged attendance. The article also reports that some gram panchayat members were allegedly complicit in fraudulent entries and wage diversion.

The article says workers did not know where their wages were being credited, and that the listed wages for October 4 would total Rs 1.2 crore. However, it does not specify which government department or authority formally pays the wages. It identifies the local administrative roles, but not the final disbursing authority.

05

What happens to rural families when the promised local work is unavailable during a crop failure?

Crop failure removes both food and income from farming households. In Beed, weak rainfall shrank Satish Shirsath’s soybean harvest so badly that it earned Rs 10,000, only half his Rs 20,000 investment. Once the crop failed, he needed wage work to support his family.

The employment scheme briefly helped. Shirsath earned Rs 3,000 after digging a canal for six days in August. But he then found no more work in his village. Without reliable local employment, the family could not depend on farming or the promised public works.

In mid-October, Shirsath and his wife travelled 350 km to Sangli for three months. They hoped to earn Rs 800 a day cutting sugarcane, while their three children stayed with their grandparents. The article presents migration as the only available option for some families when drought destroys crops and employment guarantees fail locally.

06

How are digital tools such as GPS, live photographs, and mobile attendance intended to prevent corruption—and why might those safeguards fail?

Digital tools are intended to make rural employment records harder to manipulate. Each worksite is geo-tagged, and the National Mobile Monitoring Service App is supposed to capture workers’ attendance in real time. Location data, time stamps, and photographs should connect a named worker to a specific site on a specific day.

The system’s key mechanism is cross-checking. A worker’s name on the electronic muster roll should match a live photograph, the worksite’s GPS location, and the attendance time. In theory, these records can reveal whether the worker was actually present and whether the project existed.

The article shows how those safeguards may be bypassed. A whistleblower alleged that external fake GPS applications supplied false locations, while eKYC photographs were reused as live images. Scroll found no workers at five inspected sites despite digital records. Weak local oversight and alleged collusion by some panchayat members can turn technology into evidence for a false claim.

07

Why do governments create rural employment guarantees, especially in regions where farming depends heavily on uncertain rainfall?

Governments create rural employment guarantees because farming income can collapse when rainfall fails. In regions such as Maharashtra’s Marathwada, households may depend heavily on crops, wells, and reservoirs. A drought can destroy harvests at the same time that farm work disappears, leaving families without a dependable local income.

A public employment scheme is meant to provide a fallback. Workers can request jobs on projects such as canals, ponds, roads, rainwater harvesting, and community buildings. The work supplies wages while improving village infrastructure. Shirsath’s six days of canal digging produced Rs 3,000 after his soybean crop failed.

The wider purpose is to reduce hardship and migration during crises. But the Beed case shows that a guarantee matters only when work is genuinely available and wages reach workers. False attendance records can remove the intended safety net. Effective oversight is therefore essential, especially during droughts when demand for employment rises.

This brief was written by AI from the original reporting and checked by other models. Names, figures and quotes come from the source; read it for full context.

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