MGNREGA is expected to provide employment opportunities to migrant workers, who were displaced by the economic disruption due to the Covid-19 outbreak. Most of these migrant workers belong to the rural poor-income households. While state governments claim they care about the lives of these workers, and that there are enough employment opportunities available via the programme, let’s see what the workers actually think?

In a first of its kind, by using a unique database, Workers Level Schedule (WLS), sourced from the All India Coordinated Report by the NITI Aayog (earlier, Planning Commission) we have tried to find out workers’ response to the programme’s effectiveness. The states considered are 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 raw data points were collected from 40 districts, covering a range of 162 gram panchayats. These districts and villages are chosen based on a stratified, multistage random sampling method. We find some interesting results.

The impact of MGNREGA in providing employment opportunities and augmenting market-wage rates varied enormously across states. The states which did well in terms of implementing MGNREGA programmes are Chhattisgarh, Telangana, Mizoram, Sikkim, and Tripura. Although it is natural to assume that poorer states will introduce more MGNREGA programmes, yet data find no such direct correlation. For example, while there are incidences of poverty in Bihar, Uttar Pradesh and Madhya Pradesh, there seems to be lack of usage of MGNREGA funds. Likewise, among the north-eastern states, Arunachal Pradesh and Manipur did not do well in terms of providing MGNREGA work.

On the other hand, some poorer states, like Chhattisgarh and Tripura did well in term of providing MGNREGA work. For the relatively rich states such as Punjab and Haryana, where the demand for MGNREGA work was low, there is apparently not much interest for the programme implementation.

Workers from the states of Himachal Pradesh, Jammu and Kashmir, Odisha, and West Bengal believed that MGNREGA intervention has led to the increase in market-wage rates.

MGNREGA work has created demand for unskilled workers and this had some spill-over effect in raising market-wage rates for non-MGNREGA-related unskilled work, such as manual farm labour, porter, etc. The states of Jammu and Kashmir, Odisha, and West Bengal are industrially backward, and MGNREGA work has been helpful in increasing average market-wage rates for unskilled workers.

For the industrially advanced states like Andhra Pradesh, Telangana, Tamil Nadu, and Karnataka, the workers felt no drastic improvement in market-wage rates to arise from MGNREGA-related activities.

For instance, while the southern states of Andhra Pradesh, Karnataka, and Tamil Nadu have fared well in terms of implementing MGNREG schemes, most of these funds have been used for buying heavy machinery for the construction of MGNREGA assets. As there is a presence of an alternative industrial base (where there is a demand for manual labour), these states were not that successful in terms of providing wage employment related to MGNREGA work. Karnataka, for example, boasts a thriving agricultural sector and is a pioneer in the electronic national agriculture market (e-NAM), with less demand for work under MGNREGA.

There is evidence of corruption. There are many ways money is stolen — through false documentation, bogus workers’ lists, and a significant portion of missing assets. In many cases it was found that jobs were allocated on a ‘verbal basis’, and no documentation was available with the village body. This record strengthens the picture of disparity and irregularity due to the self-selection bias, which is primarily due to the undesirable and unlawful political intervention. For example, in Kerala, not many workers are available for MGNREGA work and the panchayat pradhans are instructed to submit wage bills where the beneficiaries are the local party workers.

The workers in Kerala have alternative employment opportunities in tea plantation, spice, and tourism industries. Likewise, in Assam we observe a big difference in MGNREGA-wage rate and market-wage rates. This has to do with a flourishing oil, tea plantation, and tourism sectors in Assam. While the native people of Assam work in these sectors, most of the migrant labourers (some of them from across international borders) prefer to work in low-wage-type MGNREGA work.

Political affiliation matters. In the state of West Bengal, households that are politically active and supporters of the local ruling party are more likely to receive MGNREGA work. In the state of Rajasthan, the workers themselves did not apply for work knowing that the government is slow in implementing the MGNREGA work.

In terms of transparency, the Himalayan states of Himachal Pradesh, Jammu and Kashmir and Uttarakhand were more unbiased in doling out MGNREG schemes. Unfortunately, the militant activities in Jammu and Kashmir, and hilly terrain in Himachal Pradesh and Uttarakhand is limiting the success of MGNREG schemes.

For a scheme such as MGNREGA, a pan-India, uniform implementation won’t be effective. If the variations, based on the diversity of the states, are not incorporated in the Act, implementation cannot be perfect. Both the model and the method of implementation of MGNREGA must be customised according to the needs of every region, with minimum leakage of funds due to corruption in various administrative layers.

Fortunately for India, the National Agricultural Research Project by Indian Council of Agricultural Research has divided the country into 127 independent agro-climatic zones depending on soil, rainfall, and agricultural productivities. For programmes to be effective, it is advisable that the MGNREG scheme is implemented as per the requirements of the geographical characteristics, taking into consideration the occupational patterns of the local people. (IPA Service)