Crop Insurance in India - A Brief Review

Jour. Ind. Soc. Ag. Statistics 57 (Special Volume). 2004 : 217-225 Crop Insurance in India - A Brief Review Shivtar Singh' 12. Parmarth Apartments. Vikas Puri. New Delhi SUMMARY This paper traces the history of crop insurance in India and reviews briefly the methods both parametric and non-parametric, used for actuarial premium rate making; the contribution made by the scientists and the students at IASRI utilizing crop yield data collected from each taluk or mandai under CCIS; the feasibility of reducing the defined area from a taluklmandal to a Gram Panchayat; the contribution of ISAS; the experience of CCIS; the implementation of the National Agricultural Insurance Scheme and human aspect of Crop Insurance. Key words: Crop insurance, Actuarial premium, Indemnifiable limits. 1. Introduction The farming community in India continually faces risks in crop production due to natural calamities right from the time of sowing to harvesting. Floods may wash away the growing fields, droughts may wither plants, diseases may attack during crop growth and hailstorms may wipe out months of farmers' labour and likely production in a single stroke. The yield uncertainty, prevents farmers from maximizing production and discourages credit institutions from advancing loans for agricultural purposes. Further, the risk bearing capacity of majority of our farmers is limited due to scarce resources and sman holdings. They cannot withstand risks which are disastrous in nature. A serious crop failure means not only the loss of farm income but also the loss of investment for the next crop season. This leads to their indebtedness. The risk burden of the farmers and the agricultural lenders can be reduced through crop insurance, which is primarily a way of protecting farmers against the element of chance in crop production. Crop insurance spreads the crop losses over space and time, provides social security to the farmers, helps in maintaining their dignity, offers self-help, encourages large investments in agriculture for improving crop yield and increasing agricultural production. Moreover, the liability of the Government to bear the cost of relief measures to the farmers following crop failure is reduced to some extent as through crop insurance the farmers themselves contribute to their relief. I Former Principal Scientist, IASRI, New Delhi-l 10012

218 JOURNAL OF THE INDIAN SOCIETY OF AGRICULTURAL STATISTICS 2. Historical Background Although the need for crop insurance in India has been felt since 1947, the year it became independent, but it was in 1948 that Government of India appointed G.S. Priolkar as an Officer on Special Duty to study the feasibility of crop and cattle insurance schemes. His recommendations were considered at a Conference held at Bombay in September, 1949. The Indian Council of Agricultural Research (ICAR) was requested to prepare a draft Pilot Scheme. The draft Pilot Scheme as visualized by ICAR was to operate for a period of five years in the States of Madras, Bombay, Madhya Pradesh and Uttar Pradesh. The crops intended to be covered under the scheme were rice and cotton in Madras (in 5 centres), cotton in Bombay (in 3 centres); cotton, wheat and rice in Madhya Pradesh (in 5 centres) and wheat, rice and sugarcane in Uttar Pradesh (in 5 centres). The Pilot Scheme was compulsory on all risk insurance pattern. Indemnity was recommended to be paid when the actual yield of the area in a year fell below 75 per cent of the standard yield of the area subject to the maximum of 50 per cent of the standard yield in the event of total loss. It was estimated that 2.5 per cent and 4.5 per cent of standard yield might be sufficient as appropriate premium rates for rice and cotton respectively for Madras, 4.5 per cent standard yield may be sufficient for cotton for Bombay; 4.5 per cent, 4 per cent and 3 per cent of standard yield may be sufficient for cotton, wheat and rice respectively for Madhya Pradesh and 3 per cent, 5 per cent and 3 per cent of standard yield as appropriate premium rates for wheat, rice and sugarcane respectively in Uttar Pradesh. During the Third Five Year Plan, the Government of Punjab desired to implement an all-risk compulsory crop insurance scheme. This scheme too was based on area approach. The indemnity was payable when the actual yield of the area in a year fell below 75 per cent of the standard yield of the area, the maximum indemnity being limited to 50 per cent of its standard yield in the event of total crop loss. The crops proposed to be covered were wheat, gram, sugarcane and cotton on experimental basis in six selected blocks. In 1962, the Punjab State sought the technical advice of Dr. T. Yamanchi, the FAD expert on Crop Insurance. A few preliminary investigations were carried out for implementing crop insurance in Punjab, but due to paucity of funds, the scheme could not be taken up. However, this resulted in the formulation of a model scheme of crop insurance in 1965. The model scheme was referred to an Expert Committee headed by Dharam Narain. The committee recommended against setting up an insurance scheme. In 1972-73, General Insurance Department of Life Insurance Corporation introduced a crop insurance scheme on H-4 cotton on experimental basis in Gujarat. Subsequently, after nationalization of General Insurance Department, this scheme was taken up by General Insurance Corporation of India (OIC) from 1973 on the pattern of LIe scheme. The OIC implemented a few more experimental schemes in 1974 and 1975 for cotton, wheat, groundnut, potato

CROP INSURANCE IN INDIA - A BRIEF REVIEW 219 crops in selected small areas in Andhra Pradesh, Gujarat, Maharashtra, Karnataka, Tamil Nadu and West Bengal. Due to uneconomic nature of the schemes, these were phased out by the end of 1976. It was in 1979, that the GIC consulted Dr. V.M. Dandekar to study the Crop Insurance Programme. He suggested linking crop insurance with credit and a pilot scheme on crop insurance was started on. the basis of his recommendations in 1979. It was based on area approach. The premium, guaranteed yield for farmers in a particular defined area receiving credit facilities in terms of agricultural loans were to be uniform. Claims, if any were to be paid to all insured farmers at the same rate and this was equal to the shortfall in yield for that area during the insured season for the insured crop. The crop yield for a given area was to be based on an adequate number of scientifically planned crop cutting experiments (CCE) conducted by the State Government in an objective manner. 3. Comprehensive Crop Insurance Scheme The Government of India introduced the area based and credit linked Comprehensive Crop Insurance Scheme (CCIS) with effect from 1.4.1985. The crops covered were wheat, paddy, millets, oilseeds and pulses. The scheme was designed (i) to provide a measure of financial support to farmers in the event of crop failure due to natural calamities such as drought, floods, pests and diseases etc. (ii) to restore credit worthiness of the farmers in the case of crop failure and (iii) to seek to support and stimulate the production of cereals, pulses and oilseeds. The premium rates were uniform, 2 per cent of the sum insured for wheat, paddy and millets and one per cent for oilseeds and pulses. The sum insured was equal to the crop loan disbursed subject to a maximum of Rs. 10,000/- per farmer. 50 per cent of the premium payable by small and marginal farmers was subsidized equally between Central and State Governments. Indemnity claims were shared between the Central and State Governments in the ratio of 2: 1. If the actual average yield in any area notified under the scheme fell short of the guaranteed yield fixed for that area then, the farmers who had availed agricultural loans for insured crops were entitled to an indemnity under the scheme to the extent of short fall in the yield vis-a.-vis the guaranteed yield. The scheme was operated through GIC, with the active involvement of the States and Union Territories. The claims paid under CCIS during the first five years of its operation (1985-90) were of the order of Rs. 618 crore as against a premium income of Rs. 90 crore and the sum insured of Rs. 5200 crore. The claims of Gujarat, Orissa and Maharashtra were unexpectedly high due to successive natural calamities. Due to voluntary nature of the scheme. the States of Punjab and Haryana having low risk areas due to assured irrigation did not participate. As expected. the premium chargeable under the CCIS was token in nature and not

220 JOURNAL OF THE INDIAN SOCIETY OF AGRICULTURAL STATISTICS based on actuarial considerations, the premium income was not enough to meet the liability for payment of claims. Most of the implementing states had not been able to conduct the required number of CCE in all areas notified for purposes of determining the actual average yield for every season. The defined area in which the number of CCE conducted was less than 16 was clubbed with an adjoining defined area having similarity in the cropping pattern, climate and soil etc. so that the number of CCE for working out the average yield becomes 16 or more. The grouped average was applied only to the area where the number of CCE was less thanl6 for settlement of claims. In some states, the administrative unit for which yield data were available for the last 5 years, had been split into subadministrative units in the recent past. For these sub-units, data were available for one or two years. These states sent the data for the sub-units based on less than 16 CCE for one or two years and insisted for threshold yield for these subunits. It was suggested that these sub-units would remain a part of the original unit till such times their individual annual yields based on 16 or more number of CCE were available at least for 5 years. 4.1 Statistical Aspects ofccis 4. Contribution ofiasri to Crop Insurance Narain et al. [12] examined the statistical criteria for determining actuarial premium rates, effect of yield variability and level of coverage on premium rates and the financial implications of the newly implemented CCIS. It was observed that the premium rates in a defined area depend on two parameters : (i) year to year variability in the annual yield (measured in terms of coefficient of variation) and (ii) the level of coverage. The actuarial rates are directly proportional to these parameters. Based on 5 years yield data ending 1983-84 the average premium at country level was 5 per cent for paddy. 10.6 per cent for millets and 9.6 per cent for oilseeds at 80 per cent indemnifiable limits. The corresponding figures at 90 per cent indemnifiable limits were 7.2 per cent for paddy, 13.4 per cent for millets and 12.9 per cent for oilseeds. These rates included 0.3 per cent as administrative cost. It was pointed out that since the CCIS lacks the actuarial soundness, the premia received and the claims paid may not even out. Garg [8] empirically compared different methods of determining premium rates viz. USA method, MPD method and regression method and found that the premium rates calculated by regression method were lower as compared to obtained by other methods. Mittal [11] investigated the use of non-parametric methods in premium rate making, utilizing 30 years district-wise and 12 years taluk-wise time series data on paddy and wheat crop yields from Uttar Pradesh State. If one has a set of observed data points, as a sample from an unknown probability function, density

CROP llvsurance IN INDIA - A BRIEF REVIEW 221 estimation amounts to constructing an estimate of density function from the observed data without recourse to any assumption about the form of the parent population. She considered only Kernel method of density estimation and used five different Kernels namely Epanechnikov. Gaussian, Rectangular, Triangular and Biweight to work out the densities, which were used in working out the premium rates. She concluded that non-parametric method is especially useful when the yield data is not available for longer period of time. Singh et al. [16] considered the possibility of reducing the size of unit area from a block to a mandai or gram panchayat so as to make the CCIS more attractive and beneficial to the farmers. It was observed that reduction in the size of current notified areas would require conducting a large number of CCE's involving a large number of trained personnels and huge resources. This may not be desirable. The best course may be to look into the existing small domain estimation techniques for their suitability. A criterion of grouping the defined areas having less than 16 number of CCE's for getting the actuarial yield for settlement of claims if any, was suggested. Geethalakshmi [9] also used the two Kernels viz. Epanechnikov and Gaussian to work out the premium rates and compared the rates with those obtained through Normal Curve technique and concluded that non-parametric method was better than the parametric one. Singh [15] highlighted the findings of a project completed at IASRI, in which the statistkal issues namely variation in yields, their distribution, determination of actuarial premium rates at different levels of coverage and distribution of premium rates were studied utilizing taluklblock wise yield data for all insured crops under CCIS for the 10 years period ending 1986-87. Srivastava and Rai [17] examined the feasibility of reducing the defined area from taluk to a Gram Panchayat (GP), and the number of CCE needed at GP level. The analysis of data for yield of paddy crop obtained from two districts of Orissa State, revealed that coefficient of variation of crop yield estimates at Gram Panchayat level was at least 20 per cent. The required sample size at Gram Panchayat level at 95 per cent level of significance should be 8 to 10 crop cutting experiments. This requirement if enforced will increase the total number of crop cutting experiments on All India basis from 5 lakh to 74 lakh. This requirement is impossible to meet as it would involve huge resources in terms of money, trained manpower and equipment. This would also increase the non-sampling error of the estimate considerably. However, they suggested a practicable procedure based on small area estimation technique for estimating average yield at Gram Panchayat level. In the suggested approach the estimates obtained through sample surveys for a large area level are scaled down to smaller area levels through the use of additional ancillary information available from various other sources. The approach, if adopted is not likely to affect the existing system of General Crop Cutting Experiments adversely. Moreover, data collected at Gram Panchayat level directly from selected farmers on crop yield

222 JOURNAL OF THE INDIAN SOCIETY OF AGRICULTURAL STATISTICS (by enquiry) as well as other ancillary infonnation would be much cheaper. The technique is being tested and would be of immense use in developing crop yield estimates at Gram Panchayat in the National Agricultural Insurance Scheme. 4.2 A Research Project A research project entitled "Statistical Studies in Relation to Crop Insurance" was taken up by the scientists of the Institute. The project was designed to examine critically the existing actuarial techniques for determining premium rates for different crops covered under the CCIS. The different techniques used for premium rate making were compared. Statistical methodology for premium rates based on crop yield distribution has been developed. It was observed that premium rates did not differ very much among themselves based on USA method. Nonnal Curve technique and Mean Percentage Deviation (MPD) method. However, premium rates estimated by Type I Pearson Curve and regression techniques were lower than those obtained by other techniques. The crop yield data of paddy and wheat followed Type I Pearson distribution in majority of crop strata instead of nonnal The reduction in premium rate in regression technique was due to the fact that a part of variation due to systematic trend in crop yield was removed in premium estimation. The MPD procedure was preferred in comparison to other procedures of rate making because of its simplicity and also as it takes into account the variation in crop yields but it is not so in case of USA method. Further. it also avoids estimation of parameters as is done in nonnal curve technique and Type I Pearson curve technique for each crop strata. A study on the variability in premium rates between states and between crop strata within states had shown that a larger proportion of the total variability in premium rates ranging from 70 to 96 per cent was accounted for between crop strata within states indicating that differential rates of premium vis-a.-vis the flat (unifonn) rate should be used to partially balance the huge indemnities likely to be paid by the Government in its crop insurance programme. 5. Role ofisas in CCIS The Indian Society of Agricultural Statistics (ISAS) was associated in the conduct of CCIS in 1985, the year of its implementation as Consultant to the General Ipsurance Corporation of India, responsible for operating the scheme for a period of three years. The work involved preparation of premium tables using yield data provided by the states and updating the tables on the basis of new data supplied after each crop season. This had provided an opportunity to the scientists and professionals working in and associated with ISAS to acquaint themselves with the problems of crop insurance in India. The Society organized two symposia on Crop Insurance.

CROP INSURANCE IN INDIA -A BRIEF REVIEW 223 5.1 First Symposium The symposium on "Crop Insurance" was organized during 39 th Annual Conference of IS AS in December, 1985 at Panjabrao Krishi Vidyapeeth, Akola (Maharashtra). It was chaired by Shri K.N. Ardhanareeswaran, Additional Secretary, Ministry of Agriculture and Rural Development, Govt. of India, Krishi Bhawan, New Delhi. Prof. Prem Narain, the then Director, Indian Agricultural Statistics Research Institute and the Secretary of the Indian Society of Agricultural Statistics welcomed the Chairman and the participants. Prof. Narain mentioned that the introduction of CCIS by the Union Government was timely and beneficial to the farmers. However, there were a number of methodological problems involved in it. Its implications and limitations need to be critically examined. The Chairman in his opening remarks enumerated in brief the operational implications of the CCIS and stressed the need to make the scheme equitable and more attractive to the farmers. He emphasized the timely flow of credit and early settlement of claims and called for more investment in dry land farming. The Chairman desired that the possibility of an alternative to crop cutting experiments for estimating crop yield may be explored and suggested that suitable methodology for working out with objectivity and precision of the financial implications of the scheme may be evolved. In all 10 papers were received for the symposium and out of them, 7 were presented. The statistical, actuarial, procedural and technical aspects of CCIS were discussed in the papers. The paper presentations were followed by discussions. The detailed summaries of the papers as well as the recommendations emerging out of the deliberations were published as proceedings of the symposium on Crop Insurance in the Journal of the Indian Society of Agricultural Statistics, Volume 38 (1),1986,105-119. 5.2 Second Symposium The symposium on "Statistical Issues in National Agricultural Insurance Scheme" was held during the 54 th Annual Conference of the Indian Society of Agricultural Statistics in November, 2000 at Narendra Deva University of Agriculture & Technology, Narendra Nagar, Kumarganj, Faizabad (Uttar Pradesh). During this symposium the role and importance of Statistics in Crop Insurance in general and NAIS in particular was discussed. The role of Indian Society of Agricultural Statistics in the conduct of CCIS in late eighties was also emphasised. It was pointed that many statistical issues relating to premium rate making, indemnity determination, crop yield estimation for assessing the losses at defined area level were tackled at that stage. Some research problems emanated from the practical experience were also tackled by M.Sc. and Ph.D. students at that time.

224 JOURNAL OF THE INDIAN SOCIETY OF AGRICULTURAL STATISTICS The summaries of the presented papers as well as the recommendations emerging out of the deliberations were published as proceedings of the Symposium in the Journal of the Indian Society of Agricultural Statistics, Volume 54, No.1, 2001,139-173. 6. National Agricultural Insurance Scheme With a view to enlarge the coverage in respect of farmers, crops and risks of the Comprehensive Crop Insurance Scheme, a new scheme called "National Agricultural Insurance Scheme"(NAIS) has been introduced in place of CCIS from Rabi 1999-2000. It covers all farmers (loanee and non-ioanee) irrespective of their size of holding and envisages to cover all food crops, oilseeds and annual commerciallhorticultural crops for which past yield data are available. The NAIS proposes to cover higher level of risk and requires to operate at a smaller unit of insurance (within a period of 3 years, the notified area may be a panchayat instead of a block). 7. Social Aspects ofcrop Insurance The social aspect of crop insurance should not be lost sight of in its implementation because majority of the farmers have neither sufficient land nor resources to invest in farming. Due consideration need to be given to the sweated labour of the farmers engaged in food production not only for themselves but also for other countrymen in particular and the humanity in general. Therefore, the criterion of working out the indemnities and the premium rates should be determined not only by technical considerations alone but also by economic and social considerations such as paying capacity of the farmers, the resources that the Government is willing to allocate and the desirability and feasibility of income transfer from non-agricultural sector to the agricultural sector. In the absence of crop insurance, the Governments have been distributing the subsidy to the farmers in the case of crop losses due to crop failure or losses by natural calamities. Attempts should be made to make the NAIS more alternative and beneficial to the farmers. REFERENCES [1] Agarwal, D.K. (1973). Some investigations for crop insurance scheme under Indian conditions. Dissertation submitted in fulfillment of the requirement for award of Diploma in Agricultural Statistics of lars, ICAR, New Delhi. [2] Battese, G.E. and Francisco, F.M. (1977). Distribution of indemnities after crop insurance plans - with application to grain crops in New South Wales. Australian Journal ofagricultural Economics, 21, 67-79. [3] Botts, Ralph R. and Boles, James N. (1958). Use of normal curve theory in crop insurance rate making. Journal offarm Economics, 40, 733-740.

CROP INSURANCE IN INDIA -A BRIEF REVIEW 225 [4] Dandekar, V.M. (1976). Crop insurance in India. Economic and Political Weekly, 11, A61-A80. [5] Dandekar, V.M. (1985). Crop insurance in India-A review, 1976-77 to 1984-85. Economic and Political Weekly, Review of Agriculture. [6] Day, Richard H. (1965). Probability distribution of field crop yields. Journal of Farm Economics, 47, 713-74l. [7] Garg, J.N., Narain, P., Singh, S. and Mahesh Kumar (1990). Statistical Studies in relation to crop insurance. IASRI, Project Report. [8] Garg, Pankaj (1985). Crop insurance premium and methodology for its determination. M.Sc. Thesis, JARI, New Delhi. [9] Geethalakshmi (1991). Non parametric density approach for estimating premium rates in crop insurance. M.Sc. Thesis, IASRI. [10] Government of India, Min. of Agriculture, Department of AgrL & Cooperation, Krishi Bhavan, New Delhi (1990). Agenda Notes - National Workshop on Crop Insurance, held at Ashoka Hotel, Chanakya Puri, New Delhi. [11J Mittal, Pankaj (1989). Statistical aspects of crop insurance. Ph.D. thesis,!ari, New Delhi. [12] Narain, P., Singh, Shivtar, Garg, J.N. and Mahesh Kumar (1985). Statistical aspects of comprehensive crop insurance scheme. Proceedings of symposium on Crop Insurance. Jour. Ind. Soc. Agril. Stat., 38(1), 106-108. [13] Priolkar, G.S. (1950). Problems of crop insurance under Indian conditions. ICAR publication. [14J Ray, P.K. (1981). Agricultural Insurance Theory, Practice and Applications to Developing Countries. Second Edn. Pergeman Press, Inc., New York. [15] Singh, Shivtar (2000). Statistical issues in premium determination in crop insurance. Proceedings of symposium on Statistical Issues in National Agricultural Insurance. Jour. Ind. Soc. Agril. Stat., 54(1), 147-151. [16] Singh, Shivtar, Narain, P., and Garg, J.N. (1991). Data generation through crop estimation surveys for use in crop insurance. In : (Eds. Prem Narain et al.), Recent Advances in Agricultural Statistics Research, Wiley Eastern, New Delhi. [17] Srivastava, A.K. and Rai, Anil (2000). An approach for estimation of crop yield at Gram Panchayat level for National Agricultural Insurance Scheme. Proceedings of symposium on Statistical Issues in National Agricultural Insurance. Jour. Ind. Soc. Agril. Stat., 54(1), 160-167. [181 Yeh,.M.H. and Wu, R.Y. (1966). Premium rate making in an All Risk Insurance Program. Journal offarm Economics, 48,1580-1586.