Why PM Modi’s Pet Project 'Fasal Bima Yojana' Failed In Most States (Except One)

When the Central government launched the Pradhan Mantri Fasal Bima Yojana (PMFBY) with much fanfare in April 2016, there were high expectations that the scheme will prove to be a boon for the farmers who battle unpredictable monsoons, unseasonal rains, drought in some states, floods in other regions, occasional fire accidents that burn the whole harvest-ready crop to the ground and various other vagaries of the nature.

The failure of the government’s then ongoing crop insurance schemes like the National Agriculture Insurance Scheme (NAIS) and Modified NAIS (MNAIS) was apparent and there was an urgent need to shift to a good system of crop insurance from the culture of compensation packages (a ritual which followed after every mass incident of crop damage).

The Centre merged earlier insurance policies and tweaked them to make them more lucrative. This included reducing the premiums considerably. However, they were hobbled by many issues right from the start, something which Swarajya had highlighted in 2017 in this ground report.

Later, the government did try to reform some aspects of it but it seems to have made little impact in making it successful as highlighted in a discussion paper published recently by The International Food Policy Research Institute (IFPRI) and written by Rajalakshmi Nirmal, Director, Market Linkages, Indian Society of Agribusiness Professionals and Suresh Chandra Babu, a senior research fellow and head of capacity strengthening in the Development Strategy and Governance Division of IFPRI in Washington D.C..

In the paper, Nirmal and Babu have identified various reasons for the failure of PMFBY in most of the states except one - Karnataka. They have used the evidence collected from a field study in Marathwada, notorious for high number of farmer suicides, and compared it with the implementation in Karnataka. Based on the study of failures in Maharashtra and best practices in Karnataka which helped achieve relative success, authors have suggested some steps that the Centre can take to improve PMFBY.

The authors go through the history of various crop insurance schemes launched by governments since independence to reach the conclusion that the PMFBY ‘is far superior‘ though they highlight severe design and implementation issues that plague this scheme.

In their field study, the authors found that Crop Cutting Experiments (CCEs) ‘take a long time to complete, and payment of claims gets unduly delayed.’

In our ground report in 2017, Swarajya had also called attention to the problem with CCEs which are important in deciding the average yields of fields which in turn decide the compensation to farmers if yield falls below the average yield by a certain percentage. In light of its centrality in deciding the compensation, one would expect the government to put in place meticulous methods to arrive at the average yield number.

But how it really works is like this. An Agriculture Development Officer (ADO) is expected to carry out CCEs to decide on a threshold yield. The village is the Insurance Unit (IU). That means CCEs need to be carried out there.

Let’s take Haryana for example. Since four crops are notified by the State government under the scheme and there are 6,841 villages, more than 1,09,456 (at least four CCEs samples per crop are mandated) experiments need to be carried out in a very short window of 15-25 days when the crop is ready for harvest. The total number of ADOs is less than 1,000 in Haryana. That translates to more than 100 experiments per officer which is simply not possible and the workers had gone on strike to protest against such impractical caseload.

Thankfully, a tiny clause allows governments a neat way out of their own inefficiency: if the yield estimate of the IU cannot be carried out, the estimate can be arrived at by grouping several neighbouring IUs together. If that is also not possible, yield estimate can be arrived at as the average of an entire district. If even that is not possible, the figures of the adjacent district is acceptable.

Senior officials are spared the legwork of conducting the CCEs - threshold yields for districts and blocks are already given in the annexures of the state government notification. Officials can simply forward the data to insurance companies by the press of a button from the comfort of their own offices.

This potentially faulty information ends up deciding whether a farmer’s yield warrants release of insurance funds or not.

One is not surprised at all that the problem with the CCEs is highlighted in their working paper by Nirmal and Babu.

The paper summarises all the main issues with the PMFBY thus:

Thankfully, Karnataka, due to introduction of the online portal Samrakshane, was able to overcome many of the issues faced by farmers in the PMFBY scheme to an extent that ‘bogus CCEs, disputes regarding the yield data, and delays in claim settlement are not a major challenge in the state’ thanks to its digitization approach.

‘Digitisation of land records and their linkage to farmers’ accounts, real-time reporting of CCE data through smartphones, and an accessible portal for farmers for all vital information regarding the PMFBY program have ensured that the grievances are minimal,’ the paper adds exhorting other states to learn from this experience.

Nirmal and Babu suggest a series of steps to improve PMFBY implementation at state level. These include ‘buy-in from all stakeholders, adopting remote sensing technologies, strengthening infrastructure and institutional capacity, conducting outcome evaluation, and putting in place a monitoring system could be effective mechanisms to mainstream the program among smallholder farmers.’

Suffice to say that the States will have to do substantial amount of heavy lifting here as Karnataka example shows. Of course, Karnataka also has a lot of room for improvement. For instance, it’s not using remote sensing technology and artificial intelligence which can reduce the number of CCEs by 30 per cent and make damage assessment more accurate. Karnataka‘s reason for keeping away from remote sensing technology is that clouds obstruct satellite images during the kharif season but as Nirmal and Babu suggest, ’these challenges can be overcome by radar satellites (a microwave remote sensing technology) and through artificial intelligence–based algorithms that provide extremely reliable data.‘

One another area where Karnataka lags in is awareness of the scheme itself but that’s a low hanging fruit which can be picked with minimal effort.

One hopes that the Modi government will pay attention to all the deficiencies of the PMFBY scheme and ensure that this best-crop insurance scheme-so far doesn’t meet the fate of earlier programs due to lacunae in implementation.