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Crop Insurance in India

The National Agricultural Insurance Scheme is vital for providing insurance cover to farmers, across regions, across seasons and across crops. This paper comprehensively reviews the NAIS and suggests changes to make it more effective. The paper is based on a detailed analysis of exhaustive data for 11 crop seasons, covering the rabi season of 1999-2000 onwards up to the same in 2004-05. Field investigations were also conducted in Haryana, Rajasthan, Andhra Pradesh, Madhya Pradesh and Gujarat to assess the response of farmers, bankers and other stakeholders. The authors also rely on discussions with knowledgeable persons like government functionaries from the department of agriculture, bankers, academicians and farmer representatives in Nagpur, Jaipur and Hyderabad.

Special articles

Crop Insurance in India

Scope for Improvement

The National Agricultural Insurance Scheme is vital for providing insurance cover to farmers, across regions, across seasons and across crops. This paper comprehensively reviews the NAIS and suggests changes to make it more effective. The paper is based on a detailed analysis of exhaustive data for 11 crop seasons, covering the rabi season of 1999-2000 onwards up to the same in 2004-05. Field investigations were also conducted in Haryana, Rajasthan, Andhra Pradesh, Madhya Pradesh and Gujarat to assess the response of farmers, bankers and other stakeholders. The authors also rely on discussions with knowledgeable persons like government functionaries from the department of agriculture, bankers, academicians and farmer representatives in Nagpur, Jaipur and Hyderabad.


I Crop Insurance in India

arming involves numerous risks – natural, social and human. The uncertainty of crop yields is one of the basic risks that every farmer has to face. The individual farmer with limited resources is seldom able to face such risks, especially if they were to result in disastrous losses. Crop insurance, exists in many countries as an institutional response to nature induced risk [Hardaker et al 1997].

The generally agreed principles of crop insurance are: (a) the uncertainty faced by individual farmers is transferred to the insurer, and for availing this benefit, the insured farmers pay a risk premium; (b) a large number of participating farmers covering a large area over a period of time enable the horizontal spread of risks over a wide area, and vertical spread over many years;

(c) the risk premium reflects the group risk assumed by the insurer; and (d) an indemnity is to be paid to the individual farmer when a loss is incurred due to causes beyond his control, as long as he maintains the insurance contract valid by paying the premium.

The importance of risk mitigation cannot be overstated as far as Indian farmers are concerned. In India, agriculture continues to be the main source of livelihood for millions of households. A large majority of agricultural producers are small farmers. A large part of Indian agriculture is rain-fed agriculture. Thus, Indian agriculture is heavily dependent on the weather, and the uncertainty of the weather cycle makes agriculture a highly risky venture. For a section of farmers, the minimum support prices for certain crops provide a measure of income stability. In recent times, forward trading is also used to insure producers from market risk. However, for coping with natural risks crop insurance is the only mechanism available. It is an instrument that protects agriculturists against uncertainties of crop production that are beyond their control. As crop production in India is affected by the vagaries of nature and huge damages occur due to droughts, floods, cyclones, hailstorms, attacks of pests and diseases, crop insurance can play a vital role in sustaining farmers’ economy.

Credit for pioneering work on crop insurance in India goes to S Chakravarti, who in 1920, proposed an agricultural insurance scheme based mainly on the rainfall approach. The data on which the scheme was based pertained to the then Mysore state, though the scheme had an all India perspective. This scheme consisted of a package that included insurance of buildings, granaries and agricultural implements; cattle insurance and; insurance of crops. A concrete step for introducing crop insurance at the national level was taken only in October 1965. The then government drew up a Crop Insurance Bill and a model scheme of crop insurance at the central level in order to help states to introduce crop insurance. The draft bill was prepared and referred in March 1970 to an expert committee chaired by Dharam Narain. The committee opined that it was not advisable to go in for any type of crop insurance in India, not even on a pilot basis. However, the first ever scheme was introduced in Gujarat, during 1972-78. It covered the H-4 cotton variety initially, though subsequently other crops were also brought under its ambit. In Gujarat, an individual based approach scheme covered about 3,110 farmers who paid a premium of Rs 4.54 lakh and claimed compensation worth Rs.37.88 lakh leading to a high premium claim ratio of 8.34.

In 1976, an expert committee headed by V M Dandekar looked into issues and modalities of crop insurance in India [Dandekar 1976] and revisited the Dharam Narain Committee’s views. It opted for the introduction of crop insurance, and submitted its report to the General Insurance Corporation (GIC) in May 1976. The report admitted that the individual approach to crop insurance would be the ideal approach. It is because assessment of the indemnity has to be done separately for each individual based on the actual crop output of the concerned farmer each year compared to his normal output. However, it was pointed out that any scheme based on an individual approach would prove impracticable at the present juncture in our country because the process of assessing the indemnity separately for each individual would be administratively difficult, highly expensive, liable to

Economic and Political Weekly November 4, 2006 interminable disputes and fraught with grave dangers of moral hazard. The Pilot Crop Insurance Scheme (PCIS) based on the homogenous area approach was put in place on the basis of the recommendation of the Dandeker Committee report, in 1979-80. The Comprehensive Crop Insurance Scheme (CCIS) was introduced in 1985.

The National Agricultural Insurance Scheme (NAIS) replaced CCIS from the rabi season of 1999-2000. The Agricultural Insurance Company (AIC) has overall responsibility to implement the scheme. There are three policy goals implied in the scheme: (a) social response – providing support to the poor farmers who stand to lose the most during severe crop failures;

(b) risk management – improving rural financial services’ ability to manage commercial risk, which is important for improving access to finance by the farmers; and (c) fiscal exposure – controlling the fiscal exposure of the government, in terms of the average exposure as well as the peak exposure during disaster years. The scheme is a mix of voluntary and compulsory participation. The voluntarism is at the state level in terms of specific crops and areas to be covered. It becomes compulsory in selected areas of the state for farmers growing designated crops and taking loans from rural financial institutions. In other words, in the notified areas, farmers who borrow from financial institutions have to take insurance compulsorily.1

The objectives of the crop insurance schemes implemented in the country since 1985, have been (a) to provide insurance coverage and financial support to the farmers, in the event of failure of any of the notified crops as a result of natural calamities, pests and diseases; (b) to encourage farmers to adopt progressive farming practices, high value inputs and higher technology in agriculture; and (c) to help stabilise farm incomes, particularly in disaster years. Against this background, this paper comprehensively reviews the NAIS and suggests changes to make it more effective. The paper presents the result of detailed analysis of secondary data. Exhaustive data for 11 crop seasons since rabi 1999-2000 till rabi 2004-05 were provided by the AIC. Field investigations were also conducted in five major states, viz, Haryana, Rajasthan, Andhra Pradesh, Madhya Pradesh and Gujarat to assess response of farmers, bankers and other stakeholders such as government functionaries. Besides, field investigations, the authors also relied on discussions with knowledgeable persons like government functionaries from agriculture department, bankers, academicians and farmers representatives in Nagpur, Jaipur and Hyderabad.

II Market Penetration and Coverage

One of the objectives was to assess the coverage of farmers under NAIS and to assess the scope and define the strategy for fuller coverage in the coming years. This section gives a factual background on the coverage of farms in different seasons, their

Table 1: Number of Loanee and Non-Loanee Farmers across Seasons
(No in Lakh)
S e a s o n s Loanee Per Cent Share in Non-Loanee Per Cent Share in Total Per Cent
Farmers Change Total Per Cent Farmers Change Total Per Cent Farmers Change
1999-2000 (9) 2000-01 (18) 2001-02 (20) 2002-03 (21) 2003-04 (22) 2004-05 (23) Total 560 19.22 18.81 19.65 22.48 32.75 118.52 243.01 -2.16 4.49 14.37 45.70 96.64 91.91 96.19 84.48 50.84 92.72 79.51 0.20 16.9 0.74 3.61 21.73 2.57 30.55 769.03 -55.99 384.87 501.74 -88.17 3.36 8.09 3.81 15.52 49.16 7.28 20.49 5.80 20.92 19.55 23.27 44.21 35.32 149.07 260.68 -6.51 18.98 90.03 -20.11
2000 (17) 2001 (20) 2002 (21) 2003 (23) 2004 (25) Total 82.17 79.74 84.20 70.13 110.57 426.81 -2.95 5.59 -16.71 57.66 97.71 91.70 86.19 87.98 87.16 89.80 1.92 7.22 13.49 9.59 16.29 48.50 274.93 86.91 -28.98 70.11 2.29 8.30 13.81 12.03 12.84 10.20 84.09 86.96 97.69 79.72 126.86 475.31 3.41 12.34 -18.40 59.16

Note: Figures in parentheses are number of participating states. Source: AIC.

Table 2: Small/Marginal Farmers Covered across Seasons

(No in Lakh)

S e a s o n s Loanee Farmers Per Cent Change Non-Loanee Farmers Per Cent Change Total Farmers Per Cent Change Distribution of Loanee Non-Loanee Farmers Farmers
Rabi 1999-2000 2000-01 2001-02 2002-03 2003-04 2004-05 Total Kharif 2000 2001 2002 2003 2004 Total 4.01 13.93 14.36 14.31 16.66 22.37 85.63 53.44 52.88 57.03 48.05 71.76 283.17 247.37 3.10 -0.39 16.47 34.24 -1.05 7.84 -15.74 49.35 0.09 0.88 0.28 1.76 7.53 0.97 11.51 1.42 3.96 8.79 4.46 8.58 27.20 896.54 -67.81 518.22 328.04 -87.12 178.53 121.95 -49.29 92.49 4.1 14.81 14.64 16.06 24.19 23.34 97.14 54.86 56.84 65.81 52.51 80.34 310.37 261.41 -1.13 9.69 50.57 -3.52 3.61 15.78 -20.22 53.01 97.84 94.04 98.06 89.06 68.89 95.85 88.15 97.41 93.04 86.65 91.51 89.32 91.24 2.16 5.96 1.94 10.94 31.11 4.15 11.85 2.59 6.96 13.35 8.49 10.68 8.76
Source: AIC.
4586 Economic and Political Weekly November 4, 2006

break up in the categories of small and large farmers, crop are a insured – total as well as crop-wise – and share of different states.

Comprehensive crop insurance in India started in 1985 under CCIS and NAIS came into existence in rabi 1999-2000. Under CCIS, a total of 763 lakh farmers were covered between kharif 1985 and kharif 1999, while till rabi 2004-05, a total of 624.38 lakh farmers have been provided insurance cover during the 11 seasons of NAIS. Of the total number of the farmers covered, 79.51 per cent were loanee farmers (i e, those who have taken a loan from commercial or a cooperative bank) and the rest non-loanee farmers. In the case of loanee farmers, after the abrupt increase in rabi 2000-01, the coverage in terms of farmers insured had averaged around 19 lakh for three subsequent rabi seasons. However, during the next two rabi seasons (2003-04 and 2004-05), there was a significant improvement in coverage. While in case of non-loanee farmers, the coverage has widely fluctuated. The coverage in the kharif season has been far larger than in the rabi season. In five kharif seasons, since kharif 2000, a total of 475.31 lakh farmers have been covered, as against 149.07 lakh farmers in the rabi season (Table 1). The trend in kharif coverage appears to be linked to expansion of participating states, crops notified, extent of drought, and non-loanee farmers’ decision to participate in the scheme selectively, i e, after being certain of crop failure.

Coverage of Small versus Large Farmers

Since the inception of NAIS in rabi 1999-2000, till rabi of 2004-05, a total of 407.51 lakh small (including marginal) farmers2 were covered. A large proportion of these farmers –

90.50 per cent – were loanee farmers and the remaining were non-loanee farmers. A total of 97.14 lakh small farmers were covered during six rabi seasons since 1999-2000 (Table 2). Of these, 88.15 per cent were loanee farmers and the rest were nonloanee farmers. There is wide fluctuation in coverage of nonloanee small farmers over the various rabi seasons. In case of loanee small farmers, the changes are less volatile and smaller. During five kharif seasons, a total of 310.37 lakh small farmers were covered. A vast majority of them (91.24 per cent) were loanee farmers. The coverage of loanee small farmers has fluctuated, but peaked in kharif 2004 at 71.76 lakh. Non-loanee small farmers’ coverage fluctuated widely.

In case of large (including medium) farmers, a total of 216.76 lakhs were covered during 11 seasons since rabi 1999-2000. Of these 81.44 per cent were loanee farmers while the rest were non-loanee farmers. (Table3). A significant improvement in coverage of non-loanee large farmers is observed since 1999-2000 rabi.

Data shows that only 34.78 per cent of farmers insured during rabi seasons are large farmers and 65.22 per cent are small farmers. Five kharif seasons, since 2000, saw coverage of 1.65 crore large farmers (Table 3). Majority (87.08 per cent) of these were loanee farmers. There is a declining trend in coverage of loanee farmers since kharif 2000. Data shows that only 34.70 per cent of farmers insured during kharif seasons are large farmers and 65.30 per cent, are small farmers. The percentage coverage of small farmers among loanee farmers is 66.35 per cent, while among non-loanee farmers it is 56.06 per cent. Thus, small farmers require added support during kharif seasons due to higher vulnerability. This implies that if small farmers are adequately covered by credit by financial institutions, coverage could increase significantly under the NAIS.

State Level Coverage

In the first year of NAIS only nine states were implementing the scheme. Now a majority of the states/union territories are participating in the scheme. As regards the coverage of farmers, of the 624.38 lakh farmers covered during 11 seasons since rabi 1999-2000, 83.54 per cent are from Maharashtra, Andhra Pradesh, Madhya Pradesh, Gujarat, Uttar Pradesh, Orissa and Karnataka in order of importance (Table 4). In terms of area, the concentration of insured area (90.79 per cent) is in Madhya Pradesh, Andhra Pradesh, Maharashtra, Gujarat, Uttar Pradesh, Karnataka, Chhattisgarh and Orissa in order of importance. The coverage of farmers during rabi is concentrated in Uttar Pradesh, Madhya Pradesh, Maharashtra, West Bengal and Karnataka (74.39 per cent of all farmers covered and 88.95 per cent if we include Orissa and Andhra Pradesh). Rest of the country had hardly been covered. There is hardly any state where there is a continuous increase in coverage of farmers. There are sudden jumps and sudden falls during different years. Madhya Pradesh and Uttar Pradesh present a relatively more consistent picture of coverage.

In order to have a clearer picture of penetration by NAIS in each season, we relate the number of holdings (farmers) covered to total number of holdings. It is seen that in rabi 1999-2000 only

0.50 per cent of all holdings were covered by NAIS (Table 5). This proportion has been slowly going up since then and touched

3.81 per cent in the rabi 2003-04, but fell to 3.06 per cent in the rabi 2004-05. To arrive at these numbers we have taken the

Table 3: Medium/Large Farmers Covered across States

(No in Lakh)

S e a s o n s Loanee Per Cent Non-Loanee Farmers Change Farmers Rabi 1999-2000 1.59 0.11 2000-01 5.30 232.06 0.81 2001-02 4.45 -15.99 0.47 2002-03 5.35 20.24 1.85 2003-04 5.81 8.74 14.08 2004-05 10.38 78.50 1.60 Total 32.89 18.92 Kharif 2000 28.73 0.50 2001 26.86 -6.51 3.26 2002 27.17 1.17 4.70 2003 22.08 -18.74 5.13 2004 38.80 75.76 7.72 Total 143.63 21.31 Source: AIC. Per Cent Change 662.30 -41.74 293.32 659.23 -88.61 547.00 44.33 9.17 50.34 Total Farmers 1.70 6.10 4.92 7.20 19.89 11.99 51.81 29.23 30.11 31.87 27.21 46.52 164.95 Per Cent Change 258.91 -19.40 46.40 176.16 -39.75 3.03 5.84 -14.62 70.97 Distribution of Loanee Non-Loanee Farmers Farmers 93.76 6.24 86.75 13.25 90.42 9.58 74.26 23.74 29.24 70.76 86.63 13.37 63.48 36.52 98.28 1.72 89.18 10.82 85.25 14.75 81.13 18.87 83.41 16.59 87.08 12.92
Economic and Political Weekly November 4, 2006 4587

distribution of holdings as suggested by the agricultural census for the year 1995-96, and assumed that the number of farm holdings have remained stable since then. Obviously, this gives only an approximation of the coverage in terms of farm holdings (A recent NSSO report also suggests a coverage of 4 per cent of the farmers under the crop insurance scheme).3 It is significant to note that only in three states, Andhra Pradesh, Madhya Pradesh and Maharashtra, 10 per cent or more of the farmers had the benefit of crop insurance over the whole period (Table 4). It is more or less true in case of area coverage as well. In the rest of the states, both in terms of number of farmers and the area covered, the coverage was less than 5 per cent. It is also noteworthy that except for kharif 2004 and rabi 2004-05, the percentage of holdings covered is higher than the percentage of area covered, suggesting a higher penetration among small holdings. This pattern has changed during the last two seasons.

In the kharif seasons, the coverage of farmers constituted around 7 per cent of the total. (Here too we have considered farmers covered as per cent of total number of holdings in 1995-96.) Gujarat, Maharashtra, Andhra Pradesh, Karnataka, Madhya Pradesh, Rajasthan and Orissa did cross 10 per cent of their respective land holdings. The maximum penetration was observed in Gujarat followed by Rajasthan. Bihar observed a declining proportion. Only Gujarat has consistently covered above 27 per cent of holdings. However, there is no evidence of a steady year after year increase in any state.

For the five kharif seasons together, the coverage of farmers is concentrated in a few states ,viz, Maharashtra, Andhra Pradesh, Gujarat, Madhya Pradesh and Orissa (72.98 per cent share of all farmers insured) in order of importance (Table 4). If we add Karnataka, Chhattisgarh and Uttar Pradesh to this list, then these eight states account for 90.97 per cent of farmers covered during five kharif seasons. The rest of the states have a share of 3 per cent or less. Of late, Rajasthan has emerged as a major state in the kharif season. It is apparent that states that have a sizeable rainfed crop area have a higher coverage in the kharif seasons compared

to states that have relatively less rainfed area. The exception of course is Tamil Nadu where the kharif coverage has not picked up.

Crop Coverage

As far as the crops are concerned, the major coverage was for the food crops during rabi as well as in kharif seasons. Within food crops the dominating crops during rabi seasons had been summer paddy, wheat and groundnut. During the last two seasons, horse gram and gram too had acquired importance. Of the annual/ horticultural crops, sugarcane area was significantly insured followed by potatoes. The proportion of area insured under sugar cane has come down significantly, but the area insured under potatoes has gone up. In fact, during the rabi seasons among the non-food crops, potato is now the main insured crop. In the kharif season, farmers growing paddy outnumber farmers growing other crops. The other crops of significance are groundnut and soyabean. Jowar, bajra, red gram, black gram and maize are also in some reckoning. Thus, of the 20 kharif food crops/oilseeds notified across the states, barely a few crops are being covered. Similarly, among the 11 notified annual crops, sugarcane and cotton are the only two important crops registering some coverage.

The above analysis shows that there has been a significant increase in the coverage of farmers under NAIS compared to CCIS,

Table 5: Percentage of Farmers Coveredof Total Holdings and Area

S e a s o n Per cent Share S e a s o n Per cent Share
of Farmers in of Farmers in
Holdings Area Holdings Area
Rabi Kharif
1999-00 0.50 0.36 2000 7.28 5.15
2000-01 1.81 1.28 2001 7.52 7.89
2001-02 1.69 1.20 2002 8.45 5.98
2002-03 2.01 1.42 2003 6.90 4.88
2003-04 3.83 2.69 2004 10.98 15.02
2004-05 3.06 3.28

Note: 1995-96 agricultural census has been used to ascertain the number of holdings.

Table 4: Coverage of Farmers and Area under 11 Seasons of National Agricultural Insurance Scheme since Rabi 1999-2000

States Farmers Per Cent of Area Per Cent of Farmers Covered Per Cent Farmers Covered Per Cent
Covered Farmers (Lakh Area in during Six Rabi Share of during Five Kharif Share of
(Lakh) in States Hectares) States Seasons (Lakh) States Seasons (Lakh) States
AP 99.22 15.89 147.29 14.52 10.41 6.99 88.81 18.68
Assam 0.47 0.08 0.36 0.04 0.25 0.17 0.22 0.05
Bihar 9.53 1.53 10.32 1.02 2.81 1.89 6.72 1.41
ChhattisgarhG o a Gujarat Haryana H P 28.24 0.05 57.47 1.68 1.04 4.52 0.01 9.20 0.27 0.17 63.80 0.07 136.75 2.40 0.62 6.29 0.01 13.48 0.24 0.06 0.41 0.01 1.13 0.15 0.27 n e g 0.76 0.10 27.84 0.04 56.25 1.68 0.89 5.86 0.01 11.84 0.35 0.19
J&K Jharkhand 0.04 1.71 0.01 0.27 0.62 1.27 0.01 0.13 0.04 0.24 0.03 0.16 n e g 1.47 n e g 0.31
Karnataka 48.87 7.83 74.39 7.33 15.77 10.59 33.05 6.95
Kerala 1.94 0.31 1.64 0.16 1.23 0.83 0.71 0.15
MP 82.15 13.16 219.57 21.65 28.47 19.13 53.68 11.29
Maharashtra 128.37 20.56 141.14 13.91 20.50 13.77 107.87 22.69
Meghalaya Orissa 0.09 51.51 0.01 8.25 0.11 52.91 0.01 5.22 0.06 11.26 0.04 7.56 0.03 40.26 0.01 8.47
Rajasthan Sikkim Tamil Nadu 20.04 0.01 5.73 3.21 n e g 0.92 49.86 0.01 9.77 4.91 n e g 0.96 4.85 0.01 5.03 3.26 0.01 3.38 15.18 n e g 0.70 3.19 n e g 0.15
TripuraU P 0.04 54.04 0.01 8.65 0.02 85.03 n e g 8.38 0.03 29.34 0.02 19.71 0.01 24.64 n e g 5.18
Uttaranchal 0.19 0.03 0.23 0.02 0.10 0.07 0.09 0.02
West Bengal A and N Islands Pondicherry India 31.80 0.01 0.12 624.38 5.09 n e g 0.02 100 16.52 0.01 0.20 1014.36 1.63 n e g 0.02 100 16.67 n e g 0.10 149.91 11.20 n e g 0.07 100 15.13 0.01 0.02 475.31 3.18 n e g n e g 100
Note: Due to rounding up of figures total may not tally.
Source: AIC.
4588 Economic and Political Weekly November 4, 2006

yet only a very small proportion of the farmers have been covered by the scheme. A larger number of farmers are covered in the kharif season compared to the coverage in the rabi season. The bulk of the farmers covered are those linked to the banks as borrowers, i e, loanee farmers. Though there is no systematic trend, the share of non-loanee farmers is more in the rabi season compared to their share in kharif. The coverage of small farmers is primarily influenced by the compulsory nature of the scheme as far as the loanee farmers are concerned. Small farmers are still reluctant to get insurance coverage on their own. A larger number of small farmers, both loanees and non-loanees are covered if the preceding kharif season happens to have been poor. As far as the large farmers are concerned, the compulsory nature of the NAIS seems to have greater impact during kharif and a weaker impact during rabi. Crop insurance in our country has just touched the fringe of the total number of the farmers. The pattern of greater penetration in the kharif compared to rabi has not changed. No state suggests a steady increase in the number of farmers opting for crop insurance. Food crops are the main crops for which the farmers are keen to take insurance. Potatoes have emerged as an important commercial crop from the point of view of crop insurance.

III Premia and Claims

For the viability of a crop insurance scheme a discussion of the sum insured, premium paid and the claims disbursed as indemnity is important. The experience of NAIS in this regard is examined in this section.

Sum Insured

According to present practice the sum insured for loanee farmers must be at least equal to the amount of the crop loan. They are, however, allowed to select additional coverage up to 150 per cent of the average threshold yield. Non-loanee farmers can insure values at 150 per cent of the value of the threshold yield times the plantings. For all the 11 seasons taken together the sum insured under NAIS amounted to Rs 57,238.58 crore (Table 6). The share of food crops in the sum insured is high and rising.

Among the loanee farmers, the share of small/marginal farmers is higher in ‘sali’ paddy, groundnut, maize, ragi and potato during the rabi seasons, and in paddy, ragi, sugar cane, banana, cotton, chilli, turmeric and potato during the kharif seasons. In most other crops, large farmers have a higher share in the sum insured.

Premium Collection

Premium collected in 11 seasons taken together amounted to Rs 1,777.83 crore. There is improvement in overall growth rate in premium collection in recent years though the season-wise experience differs. A total of Rs 241.75 crore were collected as premium in six rabi seasons, while during five kharif seasons the collection was Rs 1,536.09 crore (Table 7).

As only a few crops are getting insured, premium collection is also from a small number of crops. In rabi 2004-05, the share of food crops was 74.33 per cent of all premium collected. Wheat and paddy are two major rabi crops contributing the largest share in premium collection. The importance of different crops has varied over a period of time (Table 8). The figures suggest that though a large number of crops are being covered by NAIS, the farmers get only a few crops insured.

Premium collection in a state naturally depends on crops; we have also seen that the sum insured is higher in the kharif season. The latter was due to the fact that initially the NAIS covered states, which had relatively smaller proportion of area under rabi.

Premium Subsidy

To the extent premium rates are below actuarial levels, there is an implicit subsidy. Apparently this subsidy is quite large. In an attempt to make rates actuarially sound and yet protect the small farmers, the latter have been made eligible for a 50 per cent premium subsidy. At present the state/UT government and the government of India equally share the subsidy. The premium subsidy was to be phased out in five years with premium rates progressively moving towards actuarial rates. The estimated amount of explicit subsidy over the seasons is as in Table 9.

Table 6: Season-wise Sum Insured

(Rs Lakh)

Season Sum Insured Food Crops Annual Crops Season Sum Insured Food Crops Annual Crops Per Cent Share Per Cent Share

Rabi 1999-2000 35640.71 61.28 38.72 Kharif 2000 690338.34 67.23 32.77 Rabi 2000-01 160268.52 64.24 35.76 Kharif 2001 750246.13 69.53 30.47 Rabi 2001-02 149751.11 82.26 17.74 Kharif 2002 943169.37 77.23 22.77 Rabi 2002-03 183752.55 78.07 21.93 Kharif 2003 811412.57 79.41 20.59 Rabi 2003-04 304949.21 82.91 17.09 Kharif 2004 1317015.82 83.87 16.13 Rabi 2004-05 377313.49 84.32 15.68 Total rabi 211675.59 Total kharif 4512182.23 Total for 11 seasons Rs 57,238.58 crore

Table 7: Season-wise Collection of Premium and Claims Paid

(Rs lakh)

Rabi Season Premium Per Cent Change Claims Paid Kharif Premium Per Cent Change Claims Paid

1999-2000 542.48 769.26 2000 20673.39 122248.15 2000-01 2778.76 412.31 5948.63 2001 26161.79 26.55 49353.57 2001-02 3014.73 8.49 6465.80 2002 32546.71 24.41 182155.07 2002-03 3850.14 27.71 18854.76 2003 28333.19 -12.97 63956.62 2003-04 6405.88 65.49 49035.20 2004 45893.55 62.02 72636.46 2004-05 7582.67 19.01 5878.53 Total rabi 24174.66 86982.18 Kharif 153608.63 491349.87 Grand total 177783.29 Rs 5783.02 crore

Source: AIC.

Economic and Political Weekly November 4, 2006

The top five states that availed the bulk (76.0 per cent) of the subsidy are Andhra Pradesh, Maharashtra, Gujarat, Orissa and Uttar Pradesh. The top five states in terms of per farmer subsidy are Meghalaya, Andaman and Nicobar Islands, Kerala, Andhra Pradesh and Gujarat. Food crops account for more than threefifths of the total amount of subsidies. The per farmer subsidy stood at Rs 35.12. Subsidy is higher for the loanee farmers; it is less than half for non-loanee farmers.

Claims Entertained

Claims under the scheme are settled only on the basis of yield data furnished by the department of agriculture of the respective states; the latter are based on production estimates through crop estimation surveys (i e, crop cutting experiments). No other data such as annavari, declaration of drought, declaration of floods, gazette notification, etc, by any department/authority is entertained. A total of Rs 5,783.02 crore claims have been paid in 11 seasons since 1999-2000 (Table 7) against total premium of Rs 1,777.83 crore, giving a claim premium ratio of 3.25 and a loss cost of 9.94 per cent.

At the aggregate level, Gujarat claimed the maximum share of all claims settled (29.33 per cent) followed by Karnataka (16.55 per cent), Maharashtra (12.91 per cent) and Andhra Pradesh

(12.07 per cent). Gujarat accounted for a high share in claims although it accounts for only 5 per cent of the total value of agricultural production in India because groundnut had a large share among the crops insured and Gujarat had a disproportionately large share of this crop. There were severe production losses in groundnuts. However, the season-wise distribution of claims among different states has not been uniform.

Of the total claims paid, Rs 1,718.77 crore (30.20 per cent) were awarded to small/marginal farmers. Considering loanee small/marginal farmers, Gujarat, Maharashtra, Andhra Pradesh, Orissa and Madhya Pradesh cornered three-fourths of all claims. Loanee small/marginal farmers accounted for the bulk of it. Among non-loanee farmers, small/marginal farmers obtained around 4 per cent of the claims.

Claim Premium Ratio

The consolidated claim to premium ratio for the duration of the NAIS comes to 3.25. In the case of loanee farmers, the claim to premium ratio is 3.26 and that for small/marginal farmers the ratio is 1.94 and 4.44 for large farmers. Claim to premium ratios for non-loanee farmers is significantly high. Here the gap between small/marginal and large farmers is still higher. At the state level, the claim-premium ratio varies between a high of 12.45 in Himachal Pradesh and a low of 0.21 in Meghalaya (no claims have been paid in J and K yet). In case of small/marginal farmers, the ratio between the highest and the lowest ratio at the state level is about

1:6. It is also noticed that in the case of small/marginal loanee farmers, the claim premium ratio is higher than for large farmers in Bihar, Goa, Maharashtra, Tripura, West Bengal and Uttaranchal. This is due to the relatively higher percentage of small/marginal farmers in these states.

There are variations in claim-premium ratios across seasons. The ratio is higher during kharif compared to rabi in the initial years and it is mainly because of the deficiency in rainfall. However, since rabi 2002-03 the claim-premium ratio in rabi is higher than that in the kharif. There are seasonal variations in the claim-premium ratio. This is how it should be, i e, compensating farmers in bad seasons and recouping resources in the good seasons. The premium-claim ratio fluctuates from season to season (Table 12). At the crop level, some crops have a very low claim premium ratio. This is primarily because of a small number of farmers covering these crops and/or such crops are not vulnerable to rainfall failure.

Farm-Size Claim Premium Ratio

Across seasons and among loanees, small/marginal farmers have a lower claim-premium ratio. It is only in two of the 11 seasons that in their case the ratio was more than 3.0. In case of nonloanee farmers, the claim-premium ratio is not only high for both

Table 8: The Important Crops (in Terms of Sharein Premium Paid)

S e a s o n s Food Crops Annual Crops
Rabi 1999-00 Summer paddy, wheat, groundnut, gram and jowar Sugar cane and potato
Rabi 2000-01 Summer paddy, wheat, groundnut, Potato and sugar cane
Rabi 2001-02 horsegram and jowar Summer paddy, wheat, groundnut, Potato and sugar cane
horsegram and jowar
Rabi 2002-03 Wheat, summer paddy, horsegram, jowar and groundnut Potato and onion
Rabi 2003-04 Wheat, summer paddy, Potato and onion
Rabi 2004-05 horsegram, jowar and sunflower Wheat, summer paddy, mustard, Potato and jeera
gram and groundnut
Kharif 2000 Groundnut, paddy, soyabean, bajra and redgram Cotton and sugar cane
Kharif 2001 Groundnut, paddy, soyabean, Cotton and sugar cane
Kharif 2002 redgram and jowar Paddy, groundnut, soyabean, Cotton and sugar cane
bajra and redgram
Kharif 2003 Paddy, groundnut, soyabean,redgram and bajra Cotton and sugar cane
Kharif 2004 Paddy, groundnut, soyabean, Cotton and sugar cane
bajra, maize and tur
Table 9: Season-wise Subsidy (Rs lakh)
Season Subsidy S eason Subsidy
Rabi 1999-00 165.70 Rabi 2000-01 823.44 Rabi 2001-02 778.04 Rabi 2002-03 672.85 Rabi 2003-04 624.17 Rabi 2004-05 412.50 Total rabi 3476.70 Total for 11 seasons Rs 219.27 crore Kharif 2000Kharif 2001 Kharif 2002 Kharif 2003 Kharif 2004 Total Kharif 4739.80 4762.11 4487.78 2444.26 2016.62 18450.57

Table 10: Claim Premium Ratio for Different Categories of Farmers

Seasons Loanee Farmer Non-Loanee Farmer Overall Ratio S/M Other S/M Others

Rabi 1999-00 0.98 1.95 4.31 3.85 1.42 Rabi 2000-01 1.23 2.37 10.46 11.76 2.14 Rabi 2001-02 1.14 2.59 12.16 15.10 2.14 Rabi 2002-03 3.98 5.08 6.33 9.45 4.90 Rabi 2003-04 1.26 1.03 12.32 7.00 7.65 Rabi 2004-05 0.61 0.94 2.70 0.31 0.78 (3.60)Kharif 2000 4.25 7.14 12.13 11.12 5.91 Kharif 2001 0.88 2.22 4.75 11.92 1.89 Kharif 2002 2.09 7.48 6.20 13.10 5.60 Kharif 2003 0.99 1.80 4.16 13.14 2.29 Kharif 2004 1.38 1.25 5.97 3.71 1.58 (3.20)

Note: Rabi 2004-05 and kharif 2004 are provisional and figures in brackets are aggregate ratios for six rabi seasons and five kharif seasons.

Economic and Political Weekly November 4, 2006

small/marginal and large farmers but also higher compared to loanee farmers (Table 10).

Loss-Cost Ratio

The loss-cost ratio4 at the aggregate level has been fairly high. The sum of claims for 11 seasons since rabi 1999-2000 turns out to Rs 57,238.58 crore when the claims paid amounted to Rs 5,690.42 crore. This gives a ratio of 9.94. At the state level, the loss-cost ratio ranges between a low of 0.92 in Haryana and a high of 27.87 in Bihar. There are seven states with a loss-cost ratio of 10 per cent or more. At the state level, nine out of 23 states had a loss-cost ratio of below 2 per cent and another three states had a ratio of 2 to 4 per cent (9 seasons since rabi 1999-2000). A few states, such as Gujarat, Himachal Pradesh, Karnataka, Orissa, Chhattisgarh and Tamil Nadu account for high ratio (Table 11). When two more seasons are added, more than half the states have a loss-cost ratio of more than 4 per cent. One-third of the states have a loss-cost ratio of below two. Evidently, the highest loss-cost ratio was reached during kharif 2002 and the least during rabi 1999-2000 in food crops. Generally, the loss-crop ratio in food crops has been higher than annual crops (Table 12).

We can say that the sum insured during kharif is higher than that during rabi season and the share of sum insured for food crops is high and over the years it is improving. With the exception of a few crops such as potato, and occasionally sugarcane and cotton, small farmers largely insure their food crops. The premium collection has increased over the years due to increased penetration especially among non-loanee farmers. As more food crops are covered, premium collected is higher in case of food crops/oilseeds across seasons. However, the importance of different crops is changing over the period. Generally, the states, which are more vulnerable during kharif (due to rainfall failure) go for insurance to a larger extent. There are, however, a few outliers – Orissa and Uttar Pradesh (in rabi) and Gujarat and Karnataka (in kharif). Small farmers’ share in premium paid is higher in the case of food crops both in kharif and rabi. The large farmers have a higher premium share in case of annual crops compared to food crops. Both for the small farmers and large farmers wheat is emerging as an important insured crop.

Table 11: Percentage of States with Different Levels of Loss-Cost Ratio

Loss Cost S tates Per Cent Sta t es Per Cent
9 Seasons 11 Seasons
Below 2.0 per cent 2 to 4 per cent 4 to 8 per cent 8 plus per cent Total states 9 3 4 7 2 3 39.13 13.04 17.39 30.43 100.00 8 3 5 9 2 5 32.00 12.00 20.00 36.00 100.00

Per farmer premium subsidy was not much (Rs 35) and bulk of it was accounted by the loanee farmers. There is concentration of claims payment. The top six states collected 85.4 per cent of all claims. Failure of food crops accounted for a major share of claims paid. Though the overall share of claims was higher in Gujarat, because of the importance of a vulnerable crop such as groundnut, the distribution of claims among the states varied seasonally. Overall, the claim-premium ratio for small farmer is less than half of the large farmers. The claim-premium ratio is higher for non-loanee farmers in rabi as well as kharif seasons than the loanee farmers. Overall, high loss-cost ratio is influenced by a few states. With the exception of rabi 1999-2000 and kharif 2001, in all other seasons the loss-cost ratio in case of food crops has been higher. With the exception of one or two seasons, small/ marginal loanee farmers have a lower loss-cost ratio compared to large farmers in case of both food crops and annual crops. In the case of non-loanee farmers also the same holds true. With the present arrangements the AIC should be prepared to contribute approximately 20 per cent of the loss cost.

IV Issues and Approaches

With the analysis of the secondary data, interviews with the farmers and interaction with other stakeholders several critical issues in the implementation of NAIS have surfaced. Some of the important among these are: (a) should crop insurance be apart of comprehensive insurance policy? (b) should the scheme remain compulsory in the notified areas or should it be made voluntary?

(c) what should be the strategy to extend the scheme to other areas and crops? (d) how can the problem of “moral hazard” can be minimised? (e) how should the premium be fixed? (f) how should the threshold yield be determined? (g) how should the actual yield be determined and indemnities paid? (h) what should be the role of different stakeholders: AIC, banks, central government and the state governments? (i) how best can the AIC be geared to perform its role effectively? We present below our observations on each of these issues briefly.

Crop Insurance as a Separate Programme

This paper has focused on examining the role of crop insurance, particularly the functioning of the NAIS administered by the AIC. There are other schemes to ensure income of the farmers, or insure their assets such as buildings, equipment and livestock. We maintain that crop insurance should be kept as a separate programme. It should not be clubbed with insurance of income or assets of the farmers, as the requirements and the protocol for these are entirely different.

Table 12: Loss-Cost Ratio in Different Seasons by States

S e a s o n HighRabi 1999-00 10.86 (Gujarat) Rabi 2000-01 42.37 (Gujarat) Rabi 2001-02 26.29 (Karnataka) Rabi 2002-03 30.42 (Tamil Nadu) Rabi 2003-04 55.54 (Maharashtra) Rabi 2004-05 61.92 (Bihar) Kharif 2000 47.7 (Gujarat) Kharif 2001 23.19 (Karnataka) Kharif 2002 35.80 (Gujarat) Kharif 2003 29.28 (Karnataka) Kharif 2004 14.05 (Tamil Nadu) Low 0.08 (HP) 0.14 (Assam) 0.44 (Kerala) 0.03 (Orissa) 0.05 (Orissa) 0.22 (HP) 0.03 (Tamil Nadu) 0.01 (West Bengal) 0.01 (Pondicherry) 0.02 (Rajasthan) 0.65 (Maharashtra) Food Crops 1.53 4.49 5.15 10.19 9.02 1.79 20.03 6.18 21.79 8.14 6.42 Annual Crops 3.16 2.31 0.46 10.46 1.89 0.30 12.87 7.52 9.75 5.73 0.94
Economic and Political Weekly November 4, 2006 4591

Compulsory versus Voluntary Nature of the Scheme

It is a maxim in insurance that the “risk spread is risk minimised”. On this principle, there is a clear need to extend the scope of NAIS rather than curtail it. At the same time the financial considerations cannot be overlooked. A huge amount of subsidy make the scheme unsustainable in the long run. Our study of the loss-ratio farm category-wise and crop-wise has shown that there is a scope to be discriminating in this regard. As far as the small farmers are concerned there is a strong case of retaining its compulsory character, as they do not have the capacity to withstand risk and, at the same time, hardly enjoy any other risk-mitigating device. To cover all small farmers is, however,administratively an uphill task. But this is not so when it comes to the loanee farmers. As the rural credit policy lays high emphasis on covering small farmers by rural financial institutions (RFIs), the two policies can be made to synergise. Also, on the ground of national food self-sufficiency – a strategy which we cannot abandon at this stage of our development

– there is a case for keeping all foodgrains in the ambit of crop insurance. As the largest area of the small farmers is devoted to foodgrains production, the insurance cover for these crops will also serve the objective of supporting small farmers more effectively. The burden of evidence and logic suggest that NAIS should be made compulsory for all loanee small farmers, and all loanee farmers, large or small, growing foodgrains. As more and more small farmers will be covered by RFIs, one should expect that all small farmers will enjoy insurance cover for their food crops, and every food crop grower will have an insurance cover.

Prioritising Areas of Extension

There is a strong case for extending NAIS to all parts of the country. This objective is by and large fulfilled, as apart from Punjab no major state has remained uncovered. But as far as the crops are concerned there is a long way to go. There is at the same time need for a clearer strategy of extension to crops than evidenced now. NAIS has been moving into new crops very rapidly. However, it is not clear how much data, especially on yield are available for these new crops. In all probability the data on yields for some of these crops are limited to a few years and may not be very reliable. Not all crops are subjected to crop cutting experiments. As a consequence chances of mistakes in rating are multiplied which create difficult actuarial problems. These could be serious issues, especially if AIC is going for re-insurance. Given the resources available to NAIS, the immediate need is to consolidate the coverage of the existing crops under its cover rather than increase the number of crops. It is suggested that in the first instance all farmers growing paddy, wheat and other cereals may be fully covered. The next priority may be accorded to oilseeds, especially groundnut, mustard and sunflower. The third priority should be given to other crops such as cotton, onion, sugar cane and potatoes. While food crops should be given first priority in every region, the second and third priority may change depending on the region’s agriculture. For high value crops such as plantation crops special insurance products need to be designed.

Problem of Moral Hazards

As we have observed earlier, many farmers, especially nonloanee farmers do not buy insurance cover till they are sure that the weather is adverse and that there will be serious crop loss. NAIS does have sales closing dates for two principal agricultural seasons, for kharif (April-September) and rabi (October-March). At present closing dates for submitting insurance declarations and premium payments for the non-loanee farmers are July 31 for kharif season and December 31 for the rabi season. The loanees farmers are covered before the end of 30 days following the months in which the loan is received. There are two serious problems with the present practice. As NAIS is optional for nonloanee farmers, chance of them getting adversely selected increases. They can possess more knowledge based on how the crop growth is advancing before deciding whether to go for crop insurance or not. It is suggested that the policy sales closing be set at between four and six weeks prior to planting. Secondly, sales closing dates need to fit the planting pattern in the specific regions as it varies widely across the country, even within the states. For example, in Rajasthan kharif sowing is far behind sowing in Kerala. It is important that each state should have a separate calendar.

Premium Fixation

Premium rates for kharif season food and oilseed crops are as follows: 3.5 per cent of the value of output at threshold level for rice, 2.5 per cent for bajra and oilseeds and other food crops. Premium rates for rabi season crops are 1.5 per cent for wheat and 2 per cent for other food crops and oilseeds, or actuarial rate, whichever is less. The premium rates for annual and horticultural crops are based on actuarial rates. There is a large element of subsidy with the prevailing premium rates. Therefore it is suggested in some quarters that in order to make NAIS financially viable actuarial rates should be charged. The earlier discussion has shown that the time is not yet ripe to charge actuarial rates from all sections for all crops. Given the present level of coverage an indiscriminate movement towards actuarial rates will take away the protection accorded to the small farmers for their major crops. As it is, even with subsidised premium only a fraction of the small farmers have opted, voluntarily, for crop insurance. There is no denying the fact that eventually actuarial rates will have to be applied to most of the crops. However, a beginning can be made to charge such rates for non-food crops, while exempting food crops for the time being. The other debatable issue is the uniformity of premium rate for a given crop all over the country. As a matter of fact, uncertainty and vulnerability varies from state to state, in fact within the state. There is a case for a risk weighted variable premium rate, especially for high value crops, e g, horticultural crops.

Determining Threshold Yield

As was discussed earlier, the NAIS is obligatory for loanee farmers for notified crops in notified areas up to the full loan amount. Additional coverage is available up to the value of threshold yield at normal premium rates, and from value of

Economic and Political Weekly November 4, 2006

threshold yield up to the value of 150 per cent of the average yield at actuarial premium rates. The monetary value is obtained by multiplying the insured yield by either the minimum support price (MSP) or the market price for crops not having MSP. NAIS allows non-loanee farmers to insure up to 150 per cent of the value of the threshold yield times the area planted. The scheme is open for all farmers including sharecroppers and tenant farmers. It is available in all states/UTs. An area approach is followed for coverage. In case of localised calamities, individual assessment on an experimental basis is taken up in limited areas. As long as NAIS uses area-based yields, and adverse selection can be controlled, issue of how to set the limits on the sum insured is not critical. The present procedure is quite reasonable. Many farmers may have their expected yields greater than the average for the area. It is healthy practice to allow 150 per cent scaling of the sum insured. Many other countries follow this practice.

For most insurance products, premium rate calculation is based on historical loss experience. In reality, calculating the crop-yield is more complex issue. Ideally, one should know the yield distribution for each individual farmer. This means knowledge of all the possible yield outcomes and the probability of occurrence for each of those outcomes. However, the reality is quite different. Most crop-yield insurance programmes have difficulty in estimating even the central tendency in yields. Estimating factors that influence the higher moments of the yield distribution is much more difficult. In the NAIS, threshold yields are based on a three-year moving average for rice and wheat, and a fiveyear moving average for all other crops. Yield averages are determined through crop-cutting experiments. Threshold yields are set on 60, 80 or 90 per cent of the moving average yield for the areas. NAIS uses only this measure as a way of discriminating against differences in relative risks, as premium rates are flat for the different crops. Due to high variability in different parts of the country, determination of threshold yield is not easy. (Yield pattern of main crops across states show wide variations.) In any event, NAIS is not effectively using longer time series of data. Fairly complex procedures are required for estimation of the central tendency of the yield probability distribution function. However, the institution will have to master such techniques once it moves towards actuarial rates of premium. A use of three- or five-year moving average results in significant estimation errors of the central tendency of the probability distribution function. Therefore, use of limited data renders the programme unfair. It intensifies the problem of adverse selection among non-loanee farmers. They use the cut-off period dates to the maximum benefit and get insurance cover if crop failure chances are very eminent. As a result, some farmers in some regions get too little payment for losses and some farmers in other regions get too much payment. In sum, threshold yields ought to be based on longer-term yield data than what is practised now.

Yield Determination and Indemnity Payment

Under the present system, the hierarchy of government administration is involved in administering NAIS. It is the responsibility of states to implement crop-cutting experiments. Crop-cutting experiments help in arriving at a yield estimate that is used for determining yield shortfalls. The state government decides the area and has the responsibility for crop-cutting experiments. The minimum number of crop-cutting experiments required varies according to the basic unit of area being used. At the tehsil level, a minimum of 16 crop-cutting experiments are to be carried out. Eight crop-cutting experiments are required at the gram panchayat level. As the unit area decreases, so does the number of cropcutting experiments.

The problem arises because not all crops covered under NAIS are subjected to crop-cutting experiments. The other problem is the delay in the timely availability of data as many functionaries and layers of administration are involved. There is a lag between crop-cutting experiments and release of official figures. Besides, crop-cutting experiments are not cost-effective. NAIS should seek to have an alternative way of assessing yields. If the damage done to the crop is extensive, dependable procedures for concurrent monitoring and payment have to be sought. Interviews with knowledgeable persons may help in assessing the damage to a crop at different points. Other indicators can also be used and more than one agency could be involved in this process. Subjective yield assessment is resorted to supplement other “scientific” methods by several countries (US, Spain, Canada, etc). There is also a need to look into the unit for indemnity payment. Under NAIS indemnity is calculated as the difference between the area yield and the threshold yield multiplied by the liability. This is an acceptable procedure.

The important issue here is how are the area boundaries to be determined? Presently the yield estimations are determined at the mandal/block level. NAIS was expected to move towards gram panchayat/village level within three years (since 19992000). This has not yet happened. This would be a desirable move as that could help in mitigating basis risk. However, there are two aspects on which clarity is needed, i e, preparedness to use a much larger sample (may be ten-fold increase) and its cost implication and, possible use of other markets (derivatives) to mitigate the basis risk.

Role and Responsibility of Stakeholders

Crop insurance in India is a multi-agency programme. The central government, state governments, National Bank for Agriculture and Rural Development (NABARD), General Insurance Corporation (GIC), commercial banks and cooperative banks all have a role to play. If the objective of a significant increase in the coverage and hassle free implementation is to be achieved, the role and responsibility of each major stakeholder will have to be clarified, and wherever necessary, strengthened.

The central government is the prime mover of NAIS. It is important that the government does not consider it an ad hoc scheme. With all its limitations AIC has made important strides in the area. The central government has to come out unequivocally in favour of a scheme such as NAIS as a permanent feature of agricultural policy. The other area where clarity is needed is the extent and duration of subsidy in the premium. We have earlier presented a case for the continuation of the subsidy at the present level for the small farmers for their food crops. This should continue at least for the next five years. The role of the states is equally critical, in terms of their share in subsidy and more importantly, in helping with the timely results of the crop-cutting experiments in determining the scale of indemnity to be paid to the farmers. On the consideration that stakeholders other than the central and the state governments should also “own” the scheme, there is a case for reducing the share of subsidy by the states. However, they should also contribute to the subsidy amount to own their responsibility to cultivators, especially the

Economic and Political Weekly November 4, 2006 small cultivators of their state. Their equally important role is to organise and deliver results of crop-cutting experiments in time. We heard the complaints from more than one quarter that the results are not transmitted to the concerned agencies for four to six months. This is quite a distance from the concurrent assessment and timely payment, which we have advocated.

At the same time, that the states are not represented on the board of the AIC is an anomalous fact. Several agencies including NABARD have made arrangements for the representation of the states on their boards on rotational basis. AlC should also follow these examples.

The commercial and the cooperative banks have a seminal role in the implementation of NAIS. First in canvassing the business of crop insurance, especially for the loanee farmers and then distributing the amount of indemnities to the affected farmers. Our discussion with bankers and other concerned parties suggested a lack of enthusiasm on the part of the banks to conduct this business although they are paid a token service charge. This is untenable, because the banks are the direct beneficiaries of crop insurance as the sum advanced by them is recouped even in the time of crop failure with the amount received by the growers as compensation. Indemnity payments are finally credited to the farmer’s loan or bank account. There is a need for greater involvement of the banks. The fact that some private banks on their own are entering the field of crop insurance, in one or the other variant, suggests that this business is not alien to them. AIC and the concerned banks should arrive at some arrangement which ensures greater stake of the banks in crop insurance. NABARD and GIC are among the sponsors of AIC. They should take a more proactive role in meeting the targets of larger coverage and smoother functioning of the scheme. Their representatives on AIC Board should act as two-way conduit between their parent organisations and AIC.

Role and Responsibilities of AIC

Within a short period of its existence AIC has performed creditably in this difficult area. It has also shown dynamism in experimenting with new methods and new approaches. However, several improvements are needed both at the organisational and at the functioning level. We understand that a study on the organisational and structural aspects of AIC is already afoot. Nevertheless we will like to comment on a critical area of organisation, i e, on the need for, and forms of decentralisation.

The earlier discussion has highlighted two important facts in this respect. One, the need for proper coordination with all stakeholders at the states level. Without involving states in a more active mode, an important activity such as crop insurance cannot be carried out effectively. Apart from the representation of the states at the board level, there is a need for an active state level advisory body, comprising state government representatives, agricultural experts and representative of the lead bank of the state together with representatives of AIC. To start with such advisory bodies may be constituted zone-wise with constituent states and their lead banks being represented on a rotational basis. An equally important step would be to have AIC’s presence at the district level. Following the model of NABARD’s district managers, a one-man office of AIC manager can be established. The persons recruited for this position should be carefully selected and properly trained. They will have an important coordinating role at the district level and will also act as the “ears and eyes” of AIC, lest it loses touch of the ground reality. We understand that the board of AIC is contemplating such a move. Our study lends support to this idea.

A related question is “outsourcing”. It is important to move in this direction if the coverage has to be extended and costs have to controlled. Unit for such out sourcing should be a district. There are several organisations functioning at the district level which may qualify to undertake the “agency” function for AIC. There could be Krishi Vigyan Kendra, an agri clinic, a vibrant NGO or a private sector enterprise. Following LIC’s example, AIC should also think in terms of involving private sector banks in the business of crop insurance, the role, which currently is assigned to only public sector and cooperative banks. AIC should be more catholic in the selection of the agent and should not follow a rigid model. The arrangement with these agencies should be flexible and subject to periodic review. For effective implementation of the scheme involvement of stakeholders at various level, monitoring of the activities at the district level and outsourcing to creditable organisation emerge as imperatives.

For millions of Indian farmers the NAIS is vital for providing insurance cover to farmers, across regions, across seasons and across crops. Based on our study, we have offered a few suggestions to improve the efficacy of the scheme.




[This paper is part of the larger study conducted at the behest of the Agriculture Insurance Company of India. The authors had the benefit of detailed discussions with the chairman of AIC, his colleagues on the Board and the staff of AIC on more than one occasion.]

1 The underlying assumption is that systems that improve risk management and help stabilise farm incomes will improve access to rural financial services. It would imply encouragement to savings, borrowing and insurance. Under NAIS, state government gives consent for implementation of schemes; notifies the crops and areas; and generates actual yield data through cropcutting experiments at harvest time. Generally, there are 24 crop-cutting experiments at the district level, 16 at the tehsil level, 10 at the mandal and at the gram panchayat levels. The loan granting banks are responsible for issuing coverage; collecting premium and disbursing claims. AIC works through an identified nodal bank branch. All programmes are based on area approach. Almost all-major states, with the notable exception of Punjab, are implementing the scheme. The scheme covers broadly three groups of crops, viz, food crops, oilseeds and annual commercial/horticultural crops (e g, sugar cane, cotton, potato, onion, chilly, turmeric, ginger, jute, tapioca, banana and pineapple). Major crops grown in the country are largely covered (for details see, Vyas and Singh 2005).

2 Definition of the small and marginal farmers is the same as used in Agricultural Census. 3 NSSO, Some Aspects of Farming based on the Situation Assessment Survey of Farmers, December 2003 for the agricultural year 2002-03. 4 Loss cost ratio is claims as per cent of sum insured.


Chakravarti, S (1920): Agricultural Insurance: A Practical Scheme Suited to Indian Conditions, Government Press, Bangalore (as cited in P K Misra, 1995, ‘Is Rainfall Insurance a New Idea? Pioneering Work Revisited’, Economic and Political Weekly, June 24).

Dandekar, V M (1976): ‘Crop Insurance in India’, Economic and Political Weekly, June 26. Hardaker, J B, R B M Huirne and J R Anderson (1997): Coping With Risk in Agriculture, CAB International, New York.

Vyas, V S and Surjit Singh (2005): Agricultural Crop Insurance: Performance and Needed Reforms, a report submitted to Agriculture Insurance Company of India.

Economic and Political Weekly November 4, 2006

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