Agriculture

Can MGNREGA data serve as real-time index for rural distress?

Four researchers correlated IMD's drought data with the demand for and supply of MGNREGA jobs and created an online interactive map to show areas facing normal, moderate and critical distress from 2016 to 2018. This map can prove helpful to gauge rural distress since Centre releases monthly consumption expenditure at rural household level with a lag of two years

 
By Shagun Kapil
Last Updated: Monday 05 August 2019
Demand for jobs under the government’s employment guarantee scheme rises whenever there is distress in an area. Photo: Sandeep Das
Demand for jobs under the government’s employment guarantee scheme rises whenever there is distress in an area. Photo: Sandeep Das Demand for jobs under the government’s employment guarantee scheme rises whenever there is distress in an area. Photo: Sandeep Das

It is a tool of unparalleled proportions and potential. It draws on data generated to track the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), links it to rural distress in real time and enables quick delivery of relief measures.

MGNREGA employs at any point in time more than 100 million people across the country. This is half of Uttar Pradesh’s population.

By design it is a distress reduction scheme implemented in half-a-million villages. By default, it mirrors the state of distress at the village and district levels. But its use as an index to gauge real-time rural distress has only just been recognised and spoken about at the national level.

In 2018, four management researchers found the link. Prasanna Tantri, Shradhey Parijat Prasad and Nishka Sharma from the Indian School of Business (ISB), Hyderabad, and Sumit Agarwal from the National University of Singapore had been researching MGNREGA.

They correlated India Meteorological Department’s drought data with the demand for and supply of MGNREGA jobs at the block level and realised that whenever a district faced drought, there was a spike in the number of people employed. They analysed data for 2012 to 2017, expanded the study to 600-odd districts in the country, and found that the trend was valid almost everywhere.

Since MGNREGA data is updated daily, it could be used to highlight a problem in real time. They used parameters like job demand and developed an Index for Localised Distress (ILD) and an online interactive map to show areas facing normal, moderate and critical distress from 2016 to 2018.

The map can be a great device in a country that has no other mechanism to gauge rural distress. The Union Ministry of Statistics and Programme Implementation calculates monthly consumption expenditure at the rural household level, which can reveal local distress, but the data is released with a lag of two years.

Even the district-level GDP it releases is irregular. “By then, the time to do something for areas under stress has already passed. We shouldn’t have to wait for data for three or four years for taking action,” says Tantri.

Last year, the researchers approached the Cabinet Secretariat with their tool, after which ILD found a mention in the Economic Survey 2018-19 released on July 4. “As an economic shock significantly reduces consumption expenditure of the household, it is important to provide assistance to the household at the right time,” says the Economic Survey, citing the study and adds that skilful use of technology can make a difference on the ground.

Geo-tagging of works under MGNREGA and online monitoring of workers already provide a platform to flash alerts in real time for areas under distress. For example, Down To Earth monitored the real-time data to look at level of distress in July 2019.

According to the Union Ministry of Rural Development, in drought-struck Amravati and Nagpur districts of Maharashtra, for instance, 0.18 million people have demanded work under MGNREGA, while in Kolhapur and Raigad, which were relatively better off, the number is just 18,798. Similar is the case of Andhra Pradesh, where drought-hit Kurnool and Prakasam districts have 1.6 million people demanding work while in Kadapa and Visakhapatnam, the figure is less than 0.8 million.



The researchers have used drought as primary source to gauge rural distress because the rural poor, who are the target beneficiaries of MGNREGA, mostly depend on agriculture, and adverse weather becomes a natural indicator for economic distress. This, however, does not mean that drought is the only event it can be associated with.

The demand for work under MGNREGA can also be correlated with other real-time measures of weather, such as untimely rain, hail or snow that destroys crops and lead to rural distress.Moreover, drought is not the only trigger for an increase in MGNREGA numbers.

A pest attack that destroys crops could force people to opt for MGNREGA, so could land acquisitions for a big infrastructure project. All these could be gauged through the portal. Once the government notices a rise in MGNREGA numbers, it can launch a probe to find the cause and provide relief (see ‘Timely intervention’).

Though the government has not yet decided how to use the tool, it is accepting its utility. Raghvendra Pratap Singh, director, MGNREGA, Department of Rural Development, says that since all data under the scheme is being captured online, an assessment about rural distress can be made.

Still, the concept is not without flaws. “The records for jobs demand under MGNREGA are underestimated. The law says that if the government does not provide job to an applicant within 15 days, it must give him/her an allowance. Since governments do not want that, they do not register demands. Whenever they are able to give a job, they work the dates backwards and say the application came 15 days ago. So we are working on the assumption that the work provided is the work demanded,” explains Mihir Shah, member of the erstwhile Planning Commission.

K S Gopal, former member of the Central Employment Guarantee Council, a Central body that oversees the progress under MGNREGA, also says the demand for work will not be an efficient indicator for distress. Tantri concedes that there may be problems with the tool but says it is still better than waiting for data for years.

(This article was first published in Down To Earth's print edition dated August 1-15, 2019)

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