To plug support package loopholes, Nabard plans farmer distress index

This index won’t be uniform across the country as it changes from place to pace depending on the stress levels. It will also help the entire financial sector, government departments and insurance companies. While the distress of a farmer is usually measured by the extent of his crop damage, this leaves way too many distressed farmers in other areas out of the beneficiary ambit.

According to a study jointly conducted by Nabard and Bharat Krishak Samaj (BKS), a farmers producers’ organization, in Punjab, more than 60 per cent of the ‘very high’ and ‘high’ distress small and marginal farmers (SMFs) did not receive farm loan waiver (FLW) benefits. The exclusion rate was also 60 per cent for the medium distress category SMFs.

In Maharashtra, SMFs that were relatively better off as they were categorised as ‘low’ distress received the maximum FLW benefits. Close to 42 per cent of the SMF whose distress category was ‘very high’ did not receive FLW benefits.

In UP, 47 per cent of the ‘very high distress’ category, and 45 per cent of the ‘high distress’ category SMF did not receive FLW benefits. In the three states together, more than 40 per cent of the ‘very high distress’ farmers did not receive any FLW benefits.

In Maharashtra and UP, the sugarcane farmers who had taken loans, mostly had irrigated land and were assured of a fair price in the form of FRP (fair and remunerative price) and SAP (state advised price). They all received the benefit of farm loan waiver. The more distressed small and marginal farmers having un-irrigated lands and growing lower value crops (particularly ones not procured at MSP) may not have taken crop loans. So, they have not benefited from FLW schemes, the study said. There were complaints about wealthy farmers getting the benefits of farm loan waivers announced by various state governments in the last couple of years.

Nabard study says this farmer distress index can integrate the available high-frequency data on key agricultural variables like deviation of monsoon rains, excessive rainfall, drought and dry spells, variations in temperature and soil moisture, yield of major crops in the district, proportion of area under irrigation, depth of underground water, unusual frost, marketing opportunities available to the farmer that may include the proportion of wheat, paddy, chana, tur, groundnut, soybean etc. produced and procured at MSP.

“Use of weather data derived from remote sensing technology, automatic weather stations, mobile telephony and artificial intelligence can help in identifying the distressed villages,” it said.

“Use of data of claims received for crop insurance is also likely to help in identification of distressed regions. These can be tracked on a real-time basis and be used to monitor and predict the level of farmer distress,” the study said. Technology breakthroughs like use of space technology, AI and block chain in agriculture can be harnessed to bring dynamism and credibility to the system.

“This index can be used by the policy makers and the government to plan and design a timely and targeted method of supporting distressed farmers,” said Nabard Deputy MD Shaji KN.

Further, depending on the kind and severity of distress, the support can be given as a combination of unconditional grants, loan restructuring and/or a complete debt waiver. The assistance to individual farmers can be based on a combination of district index and individual farmers’ distress captured via irrigation status of his land, income from crops grown by him, average productivity of the district and the average price in APMC markets of this district as compared to the average price of the state.