Who is that migrant labourer ?

We are nearing the end of May and lakhs of workers are still making their way every day across the country from the industrial metros to their villages in UP, Bihar, MP, Orissa, Bengal and other eastern states. 

It is an incredible reverse migration, a movement of millions of people the likes of which we have not witnessed since independence. The exodus started when the lockdown was extended after 21 days in mid April. Since then, we have seen a continuous stream of workers on the highways with their meagre belongings, walking, or riding on cycles, motorbikes, autos and taxis, or hitching rides in tankers and trucks, even incredibly sailing in boats to reach their villages anywhere from hundreds to a couple of thousand kms away. 

Belatedly, from May 1, the central government started point to point trains to transport workers home, but these have been sufficient only to meet a fraction of the demand. Getting a ticket on one of these trains involves negotiating a kafkaesque bureaucracy and for the worker is like winning a lottery ticket. The movement by road has continued unabated during May as many workers gave up on the trains after repeated attempts and decided to make the journey on their own.

How many workers have left so far? The government on May 23rd claimed that a total of 7.5 million workers had returned to their villages, 3.5 million by trains. The actual numbers are likely to be much higher. No government, at the centre or in the states, has an idea of the number of workers who are travelling making their own arrangements.

Who are these people so desperate to return?

The media terms them “migrant workers”. The term conjures up an image of people moving around  “here and there”, from one work site to another for a short period before heading back home. Like seasonal labourers at a construction site who, come harvest, head back to their villages and fields.

But those on the road are not just construction labour, street vendors, brick kiln workers and the like who may have a seasonal cycle. There are Metal fabricators, machinists, carpenters, textile workers, diamond cutters, tailors, restaurant workers, security guards, taxi and auto drivers. They live in Mumbai, Delhi, Chennai, Bengaluru, Surat, Ludhiana and Jalandhar. They have been in the city for years, some for a decade or more.

These are workers of small and medium factories and enterprises. Some could be working even in large projects and for government through a contractor like the workers building “Namma Metro” or managing garbage for BBMP in Bengaluru. Others like the taxi drivers are self   employed. 

True they were born in some other state. True they do not have their own houses and stay in rented accommodation.  True they have a certain attachment to their ancestral villages. But does any of this justify calling them migrants?

Switch for a moment to the famed software engineers of Bengaluru? Most of them have come from other places to work here, many stay in rented accommodation and may move to another city when they find it opportune. We do not refer to them as “migrant software engineers”, do we?  Students come from all over India to study in Bengaluru? We don’t refer to them as migrant students do we? Then why the appellate “migrant” for workers from out of state?

What is so problematic with this terminology, one may ask?

The labelling of out-of-state workers as “migrant labour” allows the government to abdicate on its basic responsibilities to them as citizens. In Bengaluru for example, these workers despite working here for 8-10 years are not able to participate in local elections and do not have access to the public distribution system or any type of health insurance. Labour laws do no apply to them. In the eyes of the state, they have no individual identity except being part of collective “migrant labour”. 

A worker who has thus been recast as “migrant labour” is easy prey for the would be employers who can take advantage of his low status and pay less for his labour. Businesses’s thrive on this labour. It is a cosy arrangement between employers and the state. After keeping money for basic expenses, workers send money home to their families. These workers have no savings.

For these workers, lockdown has meant loss of wages. Many have not been paid even for the work they did in March. The government has been content to appeal to employers to pay workers and landlords to not take rent but this expectedly has made no difference on the ground. With no access to rations, even food has become difficult. Workers feel abandoned by their employers as well as the state.

Stuck in an alien heartless country, all the workers want to do is make their way home. The common refrain is “We will die of hunger if we stay here any longer. We will make our way to our village and be with family. True, we may get infected with the virus on the way. But if we die, at least it will be in the presence of our loved ones”.

When the lockdown was extended in April, workers started coming on the streets, clashing with the police and making their desire to go home very clear. They initially had hope that the government would understand their plight and arrange trains or busses to get them home. Finding that there was no help forthcoming, many decided to take things into their own hands and started walking towards their villages.

In making the journey, workers have had to defy the lockdown, brave police persecution and hunger, suffer unimaginable physical hardship and literally put their life on the line. Many have perished on the road, some after reaching their destination.

Those making their own way on the highways travel through a hostile land. Villagers living in the vicinity of the highway are suspicious that they may be carrying the virus and are positively unwelcoming. State boundaries are a huge challenge. 

In the words of Vikramjeet, a carpenter who made his way from Ahmedabad to his village in Uttar Pradesh some 1300 km away after walking for 13 days, “ borders are created within the country; people are moving like cattle; there are check-posts everywhere and all is uncertain now, like at the time of independence.” Before starting on his trek, he had spent 8 days visiting Ahmedabad railway station every morning to see if he could board a train home.

The central government has the keys to what the stranded workers desperately need - transport by trains to their home states. When it permitted workers to travel to their homes in early May, it could  easily have organised trains on a continuous basis and provided access directly for workers like the way it has organised “Vande Bharat” missions to bring Indian Citizens from outside the country. 

Instead, workers have been treated as if they were the sole responsibility of the state where they were working and the state where their village was located. The central government is content to be just a transport operator, providing rail service. A worker is able to travel only if he registers his need with two states, the two agree to a train service between them and he is lucky enough to be selected for a seat allotment by those taking the decision on who should travel. In the eyes of the central government, the worker appears to be a second class citizen.

As of this writing (May 27), the government claims that they are moving 3.5 lakh workers a day by trains. The numbers registered with the state governments show no signs of decreasing.  It appears that the mass exodus will continue into June.

When the workers have eventually made their way to their homes - as they surely will - and the dust settles on this great migration, what will remain in many million minds is the memory of betrayal by employers, weeks of hunger, authorities devoid of humanity and a long march through a hostile country, an idea of India in tatters. Most deny that they will ever come back; poverty and unemployment will force some to change their resolve.

May 28 2010

Letter to a friend - Our perception of China

Dear friend,

Below is a quote from a recent mail of yours welcoming the Indian Govt. policy changes to make Chinese investment in India difficult:

“Important and welcome decision today!

For reasons I fail to understand China, our number one enemy always had an unfair advantage over Pakistan, our number two enemy!”

I will take up just a fragment from your quote, “....China, our number one enemy...”, for discussion below.

Is China our enemy, number one or otherwise? 

It is not unreasonable to suppose that you are using the word ‘enemy’ in the context of the nation. The Oxford dictionary defines ‘the enemy’ in this context as a hostile nation or its armed forces in time of war. We are certainly not at war with China.

India and China do have an unresolved issue and that is the lack of a settled boundary. This problem is historical and dates back over a hundred years to the period of British Rule. On the boundary issue, a recent statement of the Government of India has this to say:

“The two sides have agreed to appoint Special Representatives to explore the framework for a boundary settlement from the political perspective of the overall bilateral relationship.The 20th round of the Special Representatives Talks on the India-China boundary question was held in New Delhi on 22 December 2017. The two sides are committed to seeking a fair, reasonable and mutually acceptable solution to the boundary question through dialogue and peaceful negotiations”

So both countries agree that there is a “boundary question” and that a mutually acceptable solution must be found through peaceful negotiations. In this situation, how can one justify referring to China as an enemy?

Neither country wants the boundary question to overshadow their “overall bilateral relationship”. What is this relationship about? The short answer is trade.

China is India’s largest supplier of goods (nearly 14% of all imports at $70 billion in 2018-19) followed by the US. It is the third largest consumer of Indian goods (5% of all exports in 2018-19). Only US and UAE import more Indian goods. China and US are India’s two main trading partners ( each roughly accounting for 10% of all trade). Overall trade with China has increased by 18 times between 2002-03 to 2018-19. 

This trade bears looking into in greater detail. Items imported from China include components and parts for electronics, telecom and mobile products, active ingredients for pharmaceuticals and fertilisers. India’s exports include organic chemicals, mineral fuels, cotton and metal ores. The “telecom revolution” in India, the proliferation of smart phones, even the success of the Indian pharmaceutical industry are all tied to inexpensive parts and materials available from China. Our economy is significantly linked with that of China.

While the principle of “free trade” itself can be debated, in the present circumstances where India has accepted and practices it, the rapid rise in trade with China has to be seen as being beneficial to both countries. A most recent example of this is the import of 650000 Covid test kits (which arrived on Apr 16th) and the order for 15 million PPE kits from China at a time when India was facing a severe shortage of these items. Would India source test kits or China supply them if the two were “enemies”?

Is this trade relationship without its problems? The answer is of course no; India has an adverse balance of payments with China as its imports exceed exports by a huge margin. But this problem is not unique to India and these are issues that any country has to be prepared for it opts for “free trade”.

To summarise, China and India have a long-standing boundary issue for which they seek a mutually acceptable solution through dialogue; they are also partners in mutually beneficial trade that has been growing rapidly over the years. It makes no sense to see China as an “enemy”. Then  , you may ask, do we look upon China as a “friend”?

In my view, all nation states today act in their own interest. Even a nation that appears to be a “friend” is probably acting in its own interest. Political system, religion or shared culture does not make nations “friends” necessarily. Nepal shares religion and culture with India as well as open borders. However, we have an ongoing boundary dispute and there was a crisis in relations between India and Nepal for six months in 2015-16 when Nepal alleged that India was blockading goods coming into the country. Numerous dictatorial regimes around the world are considered to be “friendly states” by the US. When it comes to defending its own trade interests, the US is ready to bulldoze its “natural allies” be it India or Europe, into submission.

China will pursue its own self interest and so must we. Being neither “friend” nor “enemy”, we can still be still good neighbours.

Sincerely,

X

PMFBY – providing business to corporate insurers or relief to stricken farmers?

This piece was first published in Scroll.in on 1/2/2019

The Modi government replaced the existing crop loss insurance schemes with the Pradhan Mantri Fasal Bima Yojana in 2016. The new scheme was advertised as incorporating the best features of the earlier schemes while removing all their shortcomings.

But as the first part in this series reported, after the scheme’s introduction, crop insurance coverage shrunk, with a drop in the number of enrolled farmers.

The second part of the series takes stock of the extent of public funding for crop insurance and examines whether the funds are being utilised efficiently for the intended purpose.

How was crop insurance funded in India in the past?

Just as any other insurance, crop loss insurance works on the idea of spreading risk across a large number of people exposed to the same risk – in this case, farmers.

Insurers consider the risk of crop damage in India to be high as there is a record of a significant loss of food grain production once in every three years. Unsurprisingly, premiums arrived at on actuarial considerations, that is, after a statistical analysis of past production figures, are also high. The average across India was 10%-15% of sum assured for kharif or monsoon crops, with higher premiums in some areas and seasons. In 2016, for instance, it was between 19%-21% for kharif crops in Gujarat, Rajasthan and Maharashtra.

Such high premiums are unaffordable for small and marginal farmers who constitute 86% of the farmer population. The state needs to step in with public funds to make crop insurance work.

Two models for public funding of crop insurance have been tried in India. Before the launch of PMFBY, multiple insurance schemes were in operation using both these models.

Trust model: Farmers pay premiums to a trust which manages the funds and compensation payouts. Premiums are set at levels affordable by farmers. When crop loss compensation claims exceed the capacity of the trust to pay, the state steps in and makes good the deficit.

This model was followed by the National Agricultural Insurance Scheme (NAIS). Premiums were fixed by the government at relatively low levels – averaging under 3.5% for kharif crops as a whole. A public sector entity, the Agriculture Insurance Company, acted as the trust which collected premiums and serviced claims. If claims exceeded the ability of AIC to pay, the government with central and state contributions made good the deficit.

Insurance model: Here an insurance company collects premiums and pays compensation. Premiums are charged based on actuarial considerations that spread the risk across the insured, minimise the residual risk borne by the company and allow it to cover its overheads and make a profit. Farmers pay a portion of the premium and the state pays the rest. By paying actuarial rate premiums, the government together with the farmers have actually absorbed most of the risk.

This model was used in two schemes – the Modified National Agricultural Insurance Scheme (MNAIS) and the Weather Based Crop Insurance Scheme. Premiums and claims were managed by insurance companies. Insurers charged actuarially determined premiums – averaging across India to 10-11% for kharif crops – which were paid partly by farmers and partly by the government with central and state contributions. In order to control its overall expenditure, the government defined caps for the premium subsidy (75% of the premium in the case of MNAIS) and premium rate (11% for kharif crops in MNAIS). Insurers setting premium rates higher than this cap had to reduce the sum assured so that government expenditure did not increase beyond the limit.

How does PMFBY funding differ from earlier schemes?

In 2015-16, the scheme based on the trust model, the National Agricultural Insurance Scheme,

accounted for 64% of the farmers and 70% of the sum assured.

The other schemes based on the insurance model not only had a smaller footprint, most of the farmers enrolled in them had been compelled to take insurance along with public sector loans.

The voluntary participation was virtually non-existent in the Modified National Agricultural Insurance Scheme and less than 3% of farmers enrolled in the Weather-Based Crop Insurance Scheme.

All three schemes were replaced by PMFBY in 2016. The PMFBY conformed to the insurance model with actuarially determined premiums – all India average of 12-15% for kharif crops. The government fixed the premium contributions to be paid by farmers at levels similar to the National Agricultural Insurance Scheme and paid the rest with central and state contributions.

From the insurer’s perspective, the PMFBY was made much more attractive than earlier schemes. The caps present earlier on sum insured as well as the ‘premium subsidy’ provided by the government were relaxed. This meant that insurers could look forward to a potentially larger business from higher sums assured as well as higher enrolment. Since premium paid by farmers was fixed at low levels, the government would be largely footing the bill.

Where does money for crop insurance come from?

Even before PMFBY was introduced, crop insurance was largely funded by the state. In the last three years, more than 80% of the overall spending has come from public funds.

The table below shows the contribution of farmers and the government for the last five years. Government expenditure appears under two heads, premium contribution for all schemes and claims support for NAIS, the ‘trust model’ scheme that existed till 2015-16.

Data Sources: Lok Sabha (MoAFW 2018a, MoAFW 2018b, MoAFW

2018c); Rajya Sabha (MoAFW 2018d)

It is surely in the public interest to ask if the funds are being utilised efficiently to achieve its objectives. One measure to look at is what portion of government expenditure actually reaches the intended beneficiaries.

Where is the government money going?

Before 2016, insurers retained less than 12% of government funding for any season and the rest reached farmers. That situation changed dramatically with the advent of the PMFBY.

The chart below indicates the portion of government expenditure retained by insurers after settling claims of farmers during successive kharif seasons. Kharif season accounts for two-thirds of the sum assured over a year and data for this season is available till 2017 unlike for rabi or winter season. The portion shown as ‘routed to farmers’ is the flow of money to farmers over and above the premium amount collected from them.

Data Sources: Agricultural Statistics at a Glance, 2016; Lok Sabha (MoAFW 2018a, MoAFW 2018c); Rajya Sabha (MoAFW 2018d)

Examining 2015, the year before PMFBY was implemented, is instructive. This was a major drought year. The bulk of claim payouts to farmers was under the NAIS, which accounted for 70% of the sum assured, where the government paid the major share of the claims as they exceeded AIC’s capacity to pay. This meant that almost all the money ploughed in by the government was paid to farmers.

With the advent of the PMFBY, upwards of 80% of the actuarial rate premium is paid by the government to the insurers who have retained about 46% and 18% of it respectively in the last two kharif seasons. The amount retained by insurers has increased by an order of magnitude after the PMFBY was introduced in 2016. In two kharif seasons, 2016 and 2017, this amounted to Rs 9,300 crores.

Is the PMFBY model superior to the NAIS model?

The Modi government has tried to respond to the criticism that it has allowed insurers to make windfall gains with the PMFBY.

The agriculture secretary claims that the PMFBY model is superior to the NAIS model, as the government no longer carries the liability for claims which were “unlimited” earlier and could result in a huge payout in case of a major drought.

This argument is naive to say the least. Insurance companies have far lower capacity to absorb risk than the government and must minimize the risk they carry. They use actuarial rates to decide premiums which allow risk to be spread across the insured – in this case farmers and the government which pays over 80% of the premium. High risk equates to high premiums.

While in some specific year a situation can arise when the payout to farmers is higher than the premium collected, when cumulated over several years, premium collected on actuarial considerations must exceed the payouts to farmers and overheads to enable insurers to turn in profits. The government will spend more money over several years on actuarial rate premiums than if it just provided claims support when needed as in the NAIS.

The PMFBY with its actuarial rate premiums allows the participation of private insurers which is not possible in a scheme such as the NAIS operating on a trust model. Are there advantages for the farmer from this?

The usual argument in favour of private service providers is that because of competition they are more responsive to customers. This argument is not valid for the PMFBY as there is only one insurance provider in any area and the farmer has no choice. This means that competition is not driving improvement in service metrics. It is left to the government to cajole or threaten insurers for something as basic as timely settlement of claims.

The entire infrastructure used for insurance in rural India belongs to the public sector – from rural bank branches offering insurance and collecting premium to state machinery to determine crop yields and measure crop loss. Reports (such as this) suggest that private insurance providers have hardly any “boots on the ground” and farmers find it difficult to access these insurers for grievance redressal. It is not clear what value they add as an intermediary between the government and the farmers.

Who benefits from PMFBY?

To sum up, the government currently pays 80% - 85% of the premium to make insurance affordable to farmers. This means that the crop loss insurance program essentially runs on public funds. And the quantum of public expenditure is large, over Rs 47,000 crore in the last two years, during which only 25-30% of crop area has been covered.

Public infrastructure is almost exclusively used to advertise insurance, enrol farmers who have taken crop loans, collect premium from farmers and receive claims payment, specify sum to be assured for different crops and estimate crop loss.

It stands to reason that using a trust to manage the crop insurance program will lead to a far more efficient use of scarce public funds than working through insurance intermediaries and paying for their overheads and profits. The utilisation of public funds in the PMFBY and the NIAS bears this out.

The question that is left with us is what was the main consideration of the Modi government when it designed the PMFBY – providing business to corporate insurers or relief to stricken farmers?

References:

MoAFW (2018a): “Claims under crop insurance”, 16^th Lok Sabha, Unstarred question No 582, Ministry of Agriculture and Farmers Welfare, 6 February, http://164.100.47.190/loksabhaquestions/annex/14/AU582.pdf

                 (2018b): “Crop insurance schemes”, 16^th Lok Sabha, Unstarred question No 956, Ministry of Agriculture and Farmers Welfare, 24 July, http://164.100.47.190/loksabhaquestions/annex/15/AU956.pdf

(2018c): “Beneficiaries under PMFBY”, 16^th Lok Sabha, Unstarred question No 3435, Ministry of Agriculture and Farmers Welfare, 7 August, http://164.100.47.190/loksabhaquestions/annex/15/AU3435.pdf

(2018d): “Crop insurance under PMFBY”, Rajya Sabha, Unstarred question No 521, Ministry of Agriculture and Farmers Welfare, 14 December

Crop insurance is losing credibility

This piece was published in scroll.in on 31/1/2019. Reproduced below with charts and tables

Is crop insurance losing credibility?

The Modi government replaced the existing crop insurance schemes with the Pradhan Mantri Fasal Bima Yojana in 2016. The new scheme was advertised as incorporating the best features of the earlier schemes while removing all their shortcomings.

Unveiling the guidelines of the PMFBY, Prime Minister Narendra Modi attributed the low enrolment in crop insurance to farmers’ “lack of faith” in the earlier schemes. A rapid increase in enrolment was to be the hallmark of the PMFBY. The target was to cover 50% of the area under crops, about 98 million hectares, by 2018-19.

But in 2017-18, the second year of the PMFBY, the enrolment numbers fell sharply, taking the coverage to below 2015 levels. Against the target of 50% for 2018-19, the coverage stands at less than 26% in 2017-18.

Why did the coverage shrink? This analysis takes a closer look at the Modi government’s failure at expanding insurance coverage for farmers and the governance issues that it reveals.

What does the data show?

Prior to the introduction of the PMFBY in 2016-17, the number of farmers and crop area insured had been sequentially increasing. This trend continued through the first year of the implementation of the PMFBY. What is noteworthy is the sharp fall in numbers in 2017-18.

The government has been reluctant to put out 2018 kharif (monsoon crop) enrolment data even several months after the end of the season. The reason for this reluctance becomes apparent from a recent reply to an Right to Information query dated October 10, 2018. Enrolment as of date was down 10% from even 2017 levels. This data did not include enrolment in Bihar, but even after Bihar data gets included, 2018 kharif enrolment will fall short of 2017.

Can increasing coverage be equated with insurance gaining popularity?

In uninformed commentary, increasing coverage is equated with insurance gaining popularity with farmers. This is not necessarily true in the context of crop insurance in India because of the strong element of coercion exerted on farmers to take crop insurance cover.

Crop loans are given almost entirely by public sector financial institutions and cooperative banks which, following government directives, automatically deduct insurance premium from the loans they make to the farmer.

Compelling farmers to take insurance offers dual benefits from the government’s point of view. First, it ensures a minimum number of captive customers to make crop insurance viable. Second, the insurance serves as collateral for the farmer’s loan, since any insurance payout in the event of crop loss is routed through the same financial institution.

The government counts farmers whose insurance premium is deducted compulsorily from a crop loan as ‘loanee’ farmers and all others as ‘non-loanee’ farmers.

A rise in the number of crop loans or government pressure on banks for full compliance can result in a rise of ‘loanee’ farmers. But the real data of interest is the number of farmers who take insurance voluntarily.

Farmers enrolling voluntarily could be those who have never taken loans or those who have taken in the past, but not in the current season. Those who have never taken loans face several obstacles to enrolling, including access to insurers and the ability to produce documentation such as sowing certificates and land records. Those who have taken loans in the past presumably have access to all the above, and should not find it a problem to enrol voluntarily if they desire.

Has there been a “quantum jump” in the voluntary enrolment of farmers?

It appears that the government is extremely keen to show that the PMFBY is more popular with farmers than earlier schemes. The Agriculture Secretary recently claimed that after the implementation of the PMFBY in 2016, there has been a “quantum jump” in voluntary enrolment. He was repeating a claim first made by the Ministry of Agriculture and Farmers Welfare on December 7, 2016 (press release).

The Ministry claimed that the number of ‘non-loanee’ farmers which was only 1.5 million in kharif 2015 had jumped to 10.2 million in kharif 2016.

But data available in the public domain tells a different story. The graph below is based on the CAG Audit of Agriculture Crop Insurance Schemes, 2017 (CAG report 2017), barring the data for 2017 and 2018, which are taken from answers to queries posed in the Lok Sabha (7-8-2018) and under the RTI Act (10-10-2018). Kharif accounts for roughly two third of the insured farmers and crop area.

There were 9.8 million ‘non-loanee’ farmers insured in kharif 2015 as per the CAG report. This is also confirmed by Ashok Gulati, former Chairman of the Commission for Agricultural Costs and Prices, in a recent paper where he attributes his data to industry sources.

The important takeaway from the chart is that ‘non-loanee’ numbers have barely changed since 2015, remaining in the range of 10-11 million. There has been no “quantum jump”.

What explains the data discrepancy?

The numbers for 2015 reported in the agriculture ministry’s press release are completely at variance with numbers available in the CAG report. The CAG attributes its data to the Department of Agriculture Cooperation and Farmers Welfare. This means the Ministry has revised 2015 numbers after the implementation of the first season of PMFBY in 2016.

Clues as to the nature of revision are available in a recent RTI response from the Ministry dated October 10, 2018 which shows the number of ‘non-loanee’ farmers in Maharashtra to be under 0.2 million in 2015-16 instead of a number of 8.2 million gathered from Maharashtra government officials.

A 2005 Bombay High Court judgement prohibits the deduction of premium from farmers taking loans in Maharashtra without their consent. Farmers providing consent as well as those taking crop loans and insurance from different institutions all get reported as ‘non-loanee’ (voluntary) farmers by insurers. According to Maharashtra government officials, a very high percentage of insured farmers have been counted in the ‘non-loanee’ category in the state for many years.

Maharashtra typically accounts for more than half of the ‘non-loanee’ farmers across India in any year. It appears that the Ministry has changed the definition of ‘non-loanee’ as applicable to Maharashtra in a way that has resulted in the “quantum jump”.  

Questions about the numbers quoted in the agriculture ministry’s press release of December 2016 have been raised by the Centre for Science and Environment in its 2017 report on PMFBY  and also directly with government officials with no answer forthcoming. If the figures supplied to the CAG were wrong and the ministry has revised it since then, does it not owe a public clarification?

What does the sharp fall in enrolment in 2017 indicate?

We now return to the issue of fall in coverage that was raised earlier. An acutely embarrassed government has gone to great lengths to dispel the idea that this could be attributed to farmers’ dissatisfaction with the PMFBY.

It has advanced two reasons. One is that when states announce farm loan waivers, farmers keep payments on old loans pending, making them ineligible for new loans. This would mean a lesser number of farmers applying for new crop loans. Two, the introduction of Aadhar seeding in the loan approval process has eliminated the earlier practice of some farmers taking multiple loans for the same crop. Both these reasons could account for the lower number of insurance policies linked to loans, that is, the lower number of ‘loanee’ farmers, it claims.

An analysis of kharif data shows the number of insured farmers came down not only in Maharashtra and UP, which announced farm loan waivers, but in seven other states. These nine states account for more than 80% of the farmers insured for kharif 2016.

Jharkhand, Orissa, Karnataka, Tamil Nadu and Telangana bucked the trend, but these accounted for only a little over 10% of the insured in that season.

The loan waiver related argument advanced by the government begs the question: why is it that the farmers who did not get loan-linked insurance (as they did not take loans) not voluntarily opt for insurance if this was to their benefit?  

Rather than seeing an increase in ‘non-loanee’ enrolment, states such as MP, Maharashtra and West Bengal saw a significant fall. Other states saw negligible change.

Reports (like this one) in the media suggest that farmers are unhappy with the PMFBY because of delays in settlement of claims and the lack of avenues for redressal. There are even instances reported of farmers taking collective action to oppose the mandatory deduction of insurance premium from their crop loan accounts because claims have not been settled for a previous season. The drop in 2017 enrolment may have more to do with this than the government cares to acknowledge.

Has governance improved with PMFBY?

The quality and timely availability of data in the public domain is a window to the quality of supervision by the government. How does the government measure up on this account?

There are blatant errors in the data put out by the agriculture ministry. For example, the number of farmer beneficiaries in Rajasthan for kharif 2016 is indicated as 18.7 million in the PMFBY website while the total number of insured farmers in the state is only 10.1 million. The total number of kharif 2016 beneficiaries is shown as 25.8 million though the real number is around 10 million.This error has been repeated in a reply to a question raised in Parliament in Aug 2018. It appears that no one in the ministry even glances at the data.

Insurance premium paid for by (deducted from) farmers is almost exclusively handled by public sector financial institutions and service centres. Yet final kharif 2018 enrolment figures have not been released, though the official period for claims settlement is over. The government took 8 months after enrolment would have been completed to provide figures for rabi 2017-18 (Lok Sabha 7 Aug 2018).

It is imperative for farmers that claims of crop loss for any season are settled before the start of the next season, and the PMFBY guidelines on claims settlement recognize this. Yet the government is unable to provide even provisional claims data for rabi 2017-18 when we are in the midst of rabi 2018-19, surely indicating that there are huge delays in settling claims. The delays are of course confirmed by reports from the ground.

The delayed availability of data, frequent revisions and blatant errors all point to poor systems and oversight of the crop insurance program by the central government.

Farmers may have lacked faith in earlier insurance schemes, but the PMFBY has done nothing to restore it.

Changes in real incomes from paddy and wheat farming in the last 5 years

This was first published in The Wire. Reproduced below with data tables.

The Prime Minister spoke of his “dream” of doubling farmer’s income by 2022 in a farmers rally in early 2016. Since then, the government has been on a publicity overdrive to show that it is working towards this goal. The goal was reiterated by the Prime Minister in his Aug 15 2018 speech. One is naturally tempted to ask how incomes have changed in the recent past.

The NITI Aayog has pointed out the difficulties in estimating changes in the income of farmers in general. The problem becomes tractable if one confines oneself to incomes from just two crops, paddy and wheat whose importance for farmer’s income will be apparent shortly. This analysis shows that real incomes from paddy and wheat farming have fluctuated in a narrow band and in the case of paddy at levels lower than prevailing 5-6 years ago.

The importance of paddy and wheat

Paddy occupies 23% of total cropped area and is grown in most parts of India while wheat covers another 16%. So between them paddy and wheat use nearly 40% of total cropped area (See Agricultural Statistics). Paddy and wheat are also grown by the largest number of agricultural households – 59% and 39% respectively – according to the NSSO 2013 survey.

Further, the government procures over 30% of the total crop in both rice and wheat at the Minimum Support Price (MSP) that it announces every year. Procurement on this scale at MSP should strongly influence the prices in the APMC mandis.

Income from paddy and wheat is thus of interest both because of the number and spread of agricultural households who depend on it and also because of the government’s ability to influence it.

Avenues for increasing income

Higher income can come from increased earnings and increased productivity. Earnings are determined by how much the price realized by the farmer exceeds the cost of cultivation. Productivity measures the crop produced per hectare.  Let us consider the question of productivity first.

Productivity estimates for the current decade (2010’s) are available in the latest Price Policy Reports of the Commission for Agricultural Costs and Prices (CACP). The Compounded Annual Growth Rate (CAGR) of productivity in wheat is negative at -0.63%. Wheat farmers need higher earnings just to hold on to the same income levels.

The productivity of paddy is increasing, but at a paltry CAGR of 0.9%. This amounts to a growth of 5.5% in 6 years, and, as we shall see is not enough to compensate for falling earnings of paddy farmers.

The hope of higher income therefore rests on higher earnings. To estimate earnings on paddy or wheat we need to know the average price realized by the farmer.

Average prices realized by farmers

The ‘average price’ we are looking for is the total realization by paddy (or wheat) farmers in the country divided by the quantity produced. It turns out that this data is embedded in the NationalAccounts Statistics (NAS).

The NAS records the output value of each major crop including paddy and wheat. Output value is calculated as the product of price and quantity produced where the price is expected to capture as accurately as possible the income that accrues to the producer.

The Central Statistical Organization (CSO) determines output value at district level using production data and average wholesale prices prevailing in APMC mandis during the peak marketing season. District level output values are aggregated to obtain state and national level values (National Accounts Statistics Sources and Methods 2012).

The output value of paddy (wheat) in NAS is then an estimate of the total realization of paddy (wheat) farmers. The ‘average price’ can be calculated using production figures from the Ministry of Agriculture and Farmers Welfare (MOAFW).

The charts below show the average price of paddy and wheat realized by farmers along with the MSP announced by the government.

Source: NAS 2018, MOAFW, Author's calculation

Sources: NAS 2018, MOAFW, Author's calculations

The charts show what is expected, that the MSP announced by the government indeed largely determines the average price realized by wheat and paddy farmers. With the exception of 2011-12, the average prices of both wheat and paddy have remained higher but within 6% of MSP.

However, what really matters for farmers are earnings rather than the average price or MSP itself. We first look at earnings on sale at MSP as this provides a clearer picture of government policy at work.

Nominal and real earnings at MSP

Nominal earnings at MSP are obtained by deducting the cost of cultivation (“A2+FL” costs in CACP terminology, available in their ‘Price policy reports’) from the MSP. Real earnings can be estimated by adjusting nominal earnings for inflation.

Paddy is brought to the market almost throughout the year except the monsoon quarter. So the average Consumer Price Index (rural) prevailing over the other 3 quarters (for example for 2016-17, the average of Q4 2016, Q1 2017, Q2 2017) is used as the deflator of nominal earnings to get real earnings at 2012 prices.

Chart 3 shows the nominal and real earnings of paddy farmers who sell their produce at MSP. It is useful to remember that 30% of the total paddy produced is sold at MSP. The results are surprising to say the least.

Source: MOSPI, MOAFW, CACP, Author's calculation

First, the government actually let nominal earnings of paddy farmers fall each successive year till 2013-14 by keeping increases in MSP less than the increase in cost of production. The margins over cost built into the MSP were reduced from 38% in 2011-12 to 27% in 2013-14. Fall in nominal earnings lead to a steeper fall in real earnings because of inflation. This was a deliberate policy of the government to lower earnings of farmers selling at the government procurement price.

In subsequent years, the government of the day fixed MSP’s to increase nominal earnings every year but the increase was just enough to compensate for inflation. Margins over cost built into the MSP remained at 28-29%. Real earnings of farmers selling paddy at MSP barely changed from 2013-14 levels.

Why did the government act as it did?

It had two major concerns in this period – burgeoning stocks of cereals and inflation. The stocks of rice with the government rose from 19.6 million tons in July 2009 to 31.5 million tons in July 2013, far in excess of the stock norms. Higher stocks meant higher costs and a higher subsidy bill for the government.

MSP’s were held down for some years till stocks of procured rice came down to more manageable levels - 21.7 million tons by 2015. Subsequent pricing policy aimed at avoiding inflationary pressures from any rise in cereal prices by keeping real earnings on paddy more or less constant.

 

Let us turn to wheat.

Chart 4 shows the nominal and real earnings in wheat when sold at MSP.  As wheat is harvested in April-May, the average CPI (rural) prevailing in Q2 (for 2016-17 the average of Q2 2017) is appropriate as the deflator to get real earnings at 2012 prices.

Source: MOSPI, MOAFW, CACP, Author's calculation

The government set MSP’s for wheat at levels which led to real earnings of farmers falling till 2015-16. The margins over cost built into the MSP fell from 110% in 2011-12 to 94% in 2015-16.

Just as in the case of paddy, the motivation for such pricing was the rise in the level of wheat stocks with the government. Wheat stocks went up from 32.9 million tons in July 2009 to 49.8 million tons in July 2012. The government engineered successive reductions in real earnings by fixing low MSP’s until stocks reached a manageable level of 30.2 million tons in July 2016.

Real earnings at average prices

We can now return to a consideration of real earnings at average prices which are indicative of the incomes of farmers as a whole from paddy and wheat.

The procedure followed is the same as for computing real earnings at MSP. Charts 5 and 6 show earnings up to 2016-17 using NAS 2018 data and the author’s projections for 2017-18 earnings based on the prevailing MSP.

Sources: NAS 2018, MOSPI, CACP, MOAFW, AUthor's calculation

 

Sources: NAS 2018, MOSPI, CACP, MOAFW, Author's calculation

After a steep drop till 2013-14, real earnings in paddy have moved up and down in a narrow band. In the case of wheat too, they have moved up and down in a small range.  

To sum up, an analysis of earnings on paddy and wheat sold at MSP over the last 6 years reveals the government’s main concerns while deciding increments in MSP.

In the initial period, the concern was to reduce stocks of grain with the government which had reached over 80 million tons in 2012. The strategy employed was to fix MSP’s at levels which would help bring down procurement and facilitate the sale of excess stocks in the market.

After stocks came down to manageable levels – around 55 million tons – in 2016, the main concern was to avoid stoking inflation. MSP’s were fixed at levels that would ensure that nominal earnings kept pace with inflation and real earnings remained at the same levels.

The governments hand in fixing MSP’s shows up in how real earnings at average prices have moved over these years.

Earnings on both paddy and wheat have fluctuated in a narrow band, and in the case of paddy, at levels lower than prevailing 5-6 years ago. Given that a large majority of farmers grow paddy and/or wheat and that nearly 40% of cropped area is used for these crops, one has to conclude that increasing farmer’s income has not been high on the government’s agenda at least till this year. 

References to this article:

Mumbai Mirror piece - Oct 3, 2018