Beyond Funding: What Really Determines Employment Guarantee Success?

One of the contentious issues in the Vikshit Bharat Guarantee for Rojgar and Ajeevika Mission Bill, or VB-G Ram G, recently passed by Parliament, allows states to pause MGNREGA-related work for 60 days of their choosing during peak sowing and harvesting seasons. The central government argues that farm employment is generally available during this period and that labour shortages created by MGNREGA works may push up agricultural wages. This, in turn, could contribute to higher consumer price inflation, given the high weight of food in the Consumer Price Index. 

MGNREGA, with an average annual expenditure of about ₹860 billion, is the largest workfare programme in the world. Critics argue that the new 60:40 funding pattern — under which states must bear 40% of the financial cost —  will make it harder for fiscally weaker states to implement the programme effectively, thereby undermining its core objective of providing guaranteed employment to rural households seeking unskilled manual work.

But how effective was the implementation of MGNREGA in the first place? One might have expected poorer and less developed states such as Uttar Pradesh, Bihar, and Madhya Pradesh to benefit more from the programme. The data, however, suggest otherwise. Using Workers Level Schedule, or WLS, data from an All India Coordinated Report compiled by NITI Aayog, we examine  this issue. The states covered in the sample include Andhra Pradesh, Assam, Haryana, Himachal Pradesh, Jammu and Kashmir, Karnataka, Kerala, Odisha, Punjab, Rajasthan, Tamil Nadu, West Bengal, Meghalaya, Tripura, and Uttarakhand.

In total, 6,580 observations were collected from 40 districts, covering 162 gram panchayats. These districts and villages were selected using a stratified, multistage random sampling method. The analysis reveals substantial interstate variation in outcomes.

The impact of MGNREGA in generating employment opportunities and augmenting market wage rates varies widely across states. States that have performed relatively well in implementing MGNREGA works include Chhattisgarh, Telangana, Mizoram, Sikkim, and Tripura. While it is often assumed that poorer states would implement more MGNREGA works, data show no clear or direct correlation. For instance, despite high poverty levels in Bihar, Uttar Pradesh and Madhya Pradesh,  utilisation of MGNREGA funds has been relatively low. Similarly, among the northeastern states, Arunachal Pradesh and Manipur have not perform well in providing MGNREGA employment. By contrast, poorer states such as Chhattisgarh and Tripura have fared better in generating work under the programme.

In relatively more affluent states such as Punjab and Haryana, demand for MGNREGA work has been low, and there appears to be limited administrative or political interest in implementing the programme aggressively.

Workers from Himachal Pradesh, Jammu and Kashmir, Odisha, and West Bengal reported that MGNREGA interventions have led to higher market wage rates. By creating additional demand for unskilled labour, MGNREGA works appear to have generated spillover effects on wages for non-MGNREGA activities such as manual farm labour and porterage. These states are relatively less industrialised, and MGNREGA seems to have contributed to higher average market wages for unskilled workers.

In contrast, workers in more industrially advanced states such as Andhra Pradesh, Telangana, Tamil Nadu, and Karnataka report no significant improvement in market wage rates attributable to MGNREGA activities. Although southern states such as Andhra Pradesh, Karnataka, and Tamil Nadu have performed reasonably well in implementing MGNREGA works, a substantial share of funds has been used for capital-intensive activities, including the deployment of heavy machinery for asset creation. Given the availability of alternative employment opportunities in agriculture and industry, these states have been less successful in generating wage employment through MGNREGA. Karnataka, for instance, has a relatively strong agricultural sector and is a pioneer of the electronic National Agriculture Market (e-NAM), which has reduced demand for MGNREGA employment.

Source: Ministry of Rural Development, 2025

 Overall, the effectiveness of MGNREGA, and, by extension, the VB-G Ram G programme, in delivering employment benefits to the poor depends on a range of factors beyond a state's fiscal capacity or administrative willingness. A uniform, pan-India implementation framework is unlikely to be effective given the country’s diversity. Unless regional variations across states are incorporated into the design of the Act, implementation will remain uneven.

Both the institutional model and implementation strategy of the VB-G Ram G programme need to be tailored to regional conditions, while minimising corruption-related leakages across administrative layers. India is well placed to pursue such an approach as the National Sample Survey Organisation has divided the country into 88 agro-climatic regions based on soil characteristics, rainfall patterns, and agricultural productivity. For employment programmes to be effective, implementation should be aligned with these geographical characteristics and local occupational patterns, rather than being driven by uniform national mandates.