4.1.1 Agriculture plays a vital role in the Indian economy. Over 70 per cent of the rural households depend on agriculture as their principal means of livelihood. Agriculture along with fisheries and forestry accounts for one-third of the nation’s Gross Domestic Product (GDP) and is its single largest contributor. Agricultural exports constitute a fifth of the total exports of the country. In view of the predominant position of the Agricultural Sector, collection and maintenance of Agricultural Statistics assume great importance.
4.1.2 India has a well-established and internationally acknowledged Agricultural Statistics System. It is a decentralised system with the State Governments – State Agricultural Statistics Authorities (SASAs) to be more specific – playing a major role in the collection and compilation of Agricultural Statistics at the State level while the Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA) at the Centre is the pivotal agency for such compilation at the all-India level. The other principal data-gathering agencies involved are the National Sample Survey Organisation (NSSO), and the State Directorates of Economics and Statistics (DESs).
4.1.3 The Agricultural Statistics System is very comprehensive and provides data on a wide range of topics such as crop area and production, land use, irrigation, land holdings, agricultural prices and market intelligence, livestock, fisheries, forestry, etc. It has been subjected to review several times since independence so as to make it adaptive to contemporary changes in agricultural practices. Some of the important expert groups, which examined the working of the system are: the Technical Committee on Coordination of Agricultural Statistics (1949), the National Commission on Agriculture (1976), the High Level Evaluation Committee (1983) and the more recent Workshop on Modernisation of the Statistical System (1998).
4.1.4 The Technical Committee on Coordination of Agricultural Statistics in India (1949) under the Chairmanship of Shri W.R. Natu was the first to examine the Agricultural Statistics System after independence. It mainly focused on standardising concepts and definitions, devising uniform forms of returns for collection of data and suggesting the scope of enquiry in respect of areas where the system of land records did not exist. The Committee also suggested among other measures, a pattern of organisation for collection of Agricultural Statistics at different levels.
4.1.5 The National Commission on Agriculture (1976), while critically reviewing the entire range of Agricultural Statistics made far-reaching recommendations to lay a strong foundation for statistical operations and to help the Government in formulating appropriate strategies.
4.1.6 While reviewing the functions of the Central Statistical Organisation (CSO) with reference to different sectors of the economy, the High Level Evaluation Committee (1983) under the Chairmanship of Professor A.M. Khusro, brought to light important data gaps including methodological gaps and made a number of recommendations to improve the system. It emphasised the need for building up a strong database for Agricultural Statistics so as to aid planning and policy formulation. It also identified newly emerging areas such as crop estimates at the local-level Community Development Block (C.D.Block), and crop forecasting and recommended development of suitable methodologies for quantitative measurement of important parameters in those areas.
4.1.7 The recent Workshop on Modernisation of the Statistical System in India (1998) considered various measures required to modernise the system by identifying the lacunae, and suggested the use of latest techniques including information and communication tools to improve the timeliness, reliability and adequacy of Agricultural Statistics.
4.1.8 The National Statistical Commission took note of the findings and recommendations of all these important bodies in the context of the prevailing status of Agricultural Statistics and attempted a fresh analysis focusing its attention on an identification of the deficiencies of the system and the remedial measures required to set them right. The Commission was assisted in this task by detailed documentation furnished by the Secretariat and the Central and State Government agencies. It also benefited from personal interaction with the representatives of these agencies. The Conference of Central and State Statistical Organisations (held in October 2000) also provided valuable inputs on the issues under consideration.
4.1.9 This chapter on Agricultural Statistics deals with 21 subject areas. The approach followed in the presentation of the report is to first indicate the current status in respect of each of these subject areas dealt with including the methodology in use; then to highlight the major deficiencies and finally, to make recommendations for improvement. Most of the recommendations suggest the scope of improvement in the organisation and management of current practices, additional administrative support and better coordination among the State and Central agencies concerned with statistical operations.
4.1.10 Crop and land use statistics form the backbone of the Agricultural Statistics System. Reliable and timely information on crop area, crop production and land use is of great importance to planners and policy makers for efficient agricultural development and for taking decisions on procurement, storage, public distribution, export, import and many other related issues. With an increasingly evident trend of decentralised planning and administration, these statistics are needed with as much disaggregation as possible down to the level of village panchayats. India possesses an excellent infrastructure and it has a long-standing tradition of generating a comprehensive series of crop and land use statistics though, of late, there has been a disturbing deterioration in their quality. With most parts of the country having detailed cadastral survey maps, frequently updated land records and the institution of a permanent village reporting agency, the country has all the necessary means to produce reliable and timely statistics. The performance of the system was quite satisfactory until 2-3 decades ago but it has since become dysfunctional essentially due to administrative apathy and inaction. It is still not too late to revamp the system and restore its credibility. The following sections deal with the current status and deficiencies of the system and what needs to be done to improve it.
4.2.1 From the point of view of crop area statistics, the States and Union Territories can be classified into three broad groups:
(a) States and Union Territories which have been cadastrally surveyed and where area and land use statistics form a part of the land records maintained by the revenue agency (referred to as “temporarily settled States”). This system is followed in 18 States namely, Andhra Pradesh, Assam (excluding hill districts), Bihar, Chatisgarh, Goa, Gujarat, Haryana, Himachal Pradesh, Jammu and Kashmir, Jharkhand, Karnataka, Madhya Pradesh, Maharashtra, Punjab, Rajasthan, Tamil Nadu, Uttaranchal and Uttar Pradesh, and the five Union Territories of Chandigarh, Dadra and Nagar Haveli, Daman and Diu, Delhi and Pondicherry.
(b) Kerala, Orissa and West Bengal known as “permanently settled” States, where there is no land revenue agency at the village level and crop area and land use statistics are collected through a scheme of sample surveys.
(c) Part of Assam (hill districts), Arunachal Pradesh, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura, and the two Union Territories of Andaman and Nicobar Islands and Lakshadweep, for which only “conventional” estimates are available.
4.2.2 Statistics of crop area are compiled with the help of the village revenue agency (commonly known as patwari agency) in the temporarily settled parts of the country and by specially appointed field staff in the permanently settled States under a scheme known as “Establishment of an Agency for Reporting Agricultural Statistics (EARAS)”. The remaining eight States in the North-Eastern Region and two other Union Territories do not have a reporting system, though the States of Tripura and Sikkim (except some minor pockets) are cadastrally surveyed. They compile what are called conventional crop estimates based on personal assessment of the village chowkidars. The three categories of States and Union Territories account for eighty-six, nine and five per cent, respectively of the total reporting area. Besides, there is non-reporting area of around seven per cent of the geographical area that mainly consists of the hill tracts of North-Eastern States and the area under illegal occupation of Pakistan and China. No statistics are available for these areas.
4.2.3 In the States that have a patwari agency, a complete enumeration of all fields (survey numbers) called girdawari is made in every village during each crop season to compile land use, irrigation and crop area statistics. In the States covered by EARAS, the girdawari is limited to a random sample of 20 per cent villages of the State, which are selected in such a way that during a period of five years, the entire State is covered.
4.2.4 Crop area statistics of the temporarily settled areas are comprehensive, being based on the complete enumeration method. They are considered fairly reliable because of the patwari's intimate knowledge of local agriculture and his ready availability in the village. However, due to an increasing range of functions assigned to the patwari, the girdawari tended to receive low priority. In order to improve the timeliness and quality of crop area statistics, two schemes are in operation since early seventies namely, the Timely Reporting Scheme (TRS) and the scheme for Improvement of Crop Statistics (ICS).
4.2.5 The TRS has the principal objective of reducing the time lag in making available the area statistics of major crops in addition to providing the sampling frame for selection of crop-growing fields for crop cutting experiments. Under the TRS, the patwari is required to complete the girdawari on a priority basis in a 20 per cent random sample of villages and to submit the village crop statements to higher authorities by a stipulated date for the preparation of advance estimates of the area under major crops. These are used in the framing of crop forecasts. The TRS sample of villages is also selected in such a way that the entire temporarily settled parts of the country are covered over a period of five years.
4.2.6 Under the ICS scheme, an independent agency of supervisors carries out a physical verification of the patwari’s girdawari in a sub-sample of the TRS sample villages (in four clusters of five survey numbers each); and makes an assessment of the extent of discrepancies between the supervisor’s and patwari’s crop area entries in the sample clusters. The supervisor also scrutinises the village crop abstract prepared by the patwari and checks whether it is free from totaling errors and whether it has been dispatched to the higher authorities by the stipulated time. The ICS also covers the permanently settled States and the supervisory agency in this case too carries out the check in a sub-sample of EARAS sample villages using the same methodology followed in the temporarily settled States. In all, 10,000 sample villages are covered by the ICS, roughly 8,500 in the temporarily settled States and 1,500 in the permanently settled States. The National Sample Survey Organisation is responsible for the planning and operations of the ICS and employs full-time staff for field supervision. It shares the fieldwork with the designated State agencies, which carry out the field supervision in about half the number of sample villages.
4.2.7 More recently, since 1990, an attempt has been underway to use Remote Sensing (RS) technology for estimation of crop areas and land use through a Centrally sponsored scheme, “Crop Acreage and Production Estimation (CAPE)”. The objective of CAPE, among others, is to provide State-level crop area estimates, meeting a 90/90 accuracy goal using the remote sensing data covering mainly the crop growing parts of the States. Pre-harvest area estimates are reported to be generated on a regular basis for major crops like rice, wheat, ragi, jowar, groundnut and cotton. The feasibility of Remote Sensing in providing detailed and disaggregated area statistics at the local level (village or panchayat) has yet to be established.
4.2.8 As noted earlier, the main purpose of the ICS scheme is to monitor the performance of the primary reporting agency in the TRS and EARAS villages. The findings of the ICS over a number of years reveal a high degree of negligence in carrying out the girdawari, thereby casting doubt on the reliability of crop area statistics. For instance, a review of the ICS results for the four years ending 1998-99 (see Annexe 4.1) shows that:
(a) The patwaris submit crop statements to the processing centres without completing the girdawari in about 10 per cent of the villages;
(b) Village crop statements are received at the processing centre from only around 78 per cent of the sample villages (i.e. a non-response of 22 per cent) and around 45 per cent only by due date;
(c) Crop entries of the patwari and the supervisor do not tally with each other in about one third of the survey numbers inspected; and
(d) The net effect of discrepancies between the patwari’s and supervisor’s crop entries is quite large in respect of even some major crops.
4.2.9 It is significant that the ratios mentioned above are of the same order in a previous study of ICS results for the four-year period ending 1988-89.
4.2.10 This is the kind of performance in the TRS sample despite the patwari being aware that his work will be subjected to technical supervision; one cannot therefore expect a better performance in 80 per cent of the remaining villages.
4.2.11 The above findings are a clear indication of the patwari’s neglect of one of his major functions. It is a matter of concern that this has continued on for many years evidently with the knowledge and indulgence of the higher-level officials of the State departments of revenue and land records.
4.2.12 Another deficiency of crop area statistics needs to be mentioned. With the development and modernisation of agriculture, several new short duration crops are grown. Although the patwari is required to undertake intermediate crop inspection between the two major kharif and rabi seasons, this does not appear to be done regularly. Even if short duration crops like vegetables, flowers, mushroom, etc. are covered during the crop inspection, they are not listed separately in the final crop abstract but clubbed together under “other crops”.
4.2.13 It is seen that a major reason for the poor quality of area statistics is the failure of the patwari agency to devote adequate time and attention to the girdawari. The fact that the patwari agency is overburdened with multifarious functions and has to cope with a large geographical jurisdiction, typically four or five villages and in some States extending over more than 10 villages (Bihar, Himachal Pradesh, Orissa and Uttaranchal) has long been acknowledged. The National Commission on Agriculture (NCA), while reiterating that the patwari agency should continue to be responsible for the collection of basic Agricultural Statistics, recommended that his jurisdiction should be reduced wherever it is excessive and that intensive supervision through normal revenue and statistical staff should be organised over his work of area enumeration. The ICS fulfills the latter part of NCA recommendation and has been doing a commendable job in assessing the quality of crop area statistics and in highlighting the deficiencies. However, there has been no significant effort on the part of the State Revenue and Land Records Departments to take effective remedial measures.
4.2.14 Some southern states, a few years ago, replaced the hereditary system of appointing patwaris (karnams) by a state-wide cadre of transferable officials. This system is reported to be working quite well. However, it is desirable that the states concerned keep staff transfers to the minimum and see that when an officer is posted at a place, he remains there sufficiently long to take advantage of familiarity with the local conditions in discharging his functions.
4.2.15 It is worth emphasising that the patwari agency and the girdawari, which has stood the test of time and proved to be cost effective and efficient in generating crop and land use statistics down to the village level, should be restored to its past level of performance. It seems almost impossible at this stage to increase the strength of patwaris (as recommended by NCA) due to financial constraints. The only course readily available is to declare the girdawari as a programme of high priority and the patwari be mandated to carry out the crop inspection according to the prescribed time schedule, if necessary, by sparing him from other duties during that period. More importantly, this has to be ensured rigorously in the case of TRS sample villages. There should be intensive supervision of the patwari’s work by higher-level revenue officials as well as by the technical staff of the ICS and the former should be made accountable for any lapses.
4.2.16 Once the TRS is put on a sound footing, it is possible to use its results for framing not only the advance estimates but also the final estimates of crop area. Data from a 20 per cent sample is large enough to estimate crop area with a sufficient degree of precision at the all-India, State and district levels. By ensuring that the girdawari in the TRS sample is carried out under strict operational and technical control, area estimates based on the TRS data will be of high quality in terms of reliability and timeliness.
4.2.17 The Commission, therefore, considers it feasible that the forecasts of crop area as well as the final estimates published by the Ministry of Agriculture should henceforth be based on the TRS sample data alone. This makes it possible that the final area estimates also become available soon after the sowing is completed in each crop season. Transmission and processing of data can be expedited with the help of Information Technology and this can be handled more efficiently due to the reduced volume of data. The TRS data can also be used to build estimates of crop area separately under irrigated, un-irrigated, high yielding and local varieties.
4.2.18 If the TRS replaces the present system of cent per cent coverage in the preparation of forecasts and final estimates of crop area, there is a possibility that the girdawari in non-TRS villages may tend to be neglected more than before or not even conducted at all. Cent per cent coverage may still be required to frame estimates for small areas (block, panchayat, etc.). This can be organised in the local areas concerned whenever the need arises. The States may decide whether or not to continue the girdawari on a regular basis in the non-TRS villages. Dispensing with the cent per cent coverage and concentrating instead on a 20 per cent sample reduces the patwari’s workload substantially and enables him to pay due attention to the girdawari in the sample village(s) falling in his jurisdiction.
4.2.19 It may be mentioned that in the permanently settled States of Kerala, Orissa and West Bengal, the girdawari is confined to the 20 per cent villages covered under EARAS and this forms the basis of area estimates. This has to continue and the EARAS operations should be streamlined and effectively supervised, if necessary, by augmenting the strength of the primary reporting agency.
4.2.20 The North Eastern States and Union Territories that prepare crop area estimates based on personal assessment of village chowkidars need to improve the method of data collection. Some efforts have been made to extend EARAS to some of these States but in the absence of cadastral survey and detailed records it is not possible to use EARAS type of area estimation. The progress made by Remote Sensing Technology (RST) in area estimation holds out a promise to deal with this problem. The Space Application Centre (SAC) may pay special attention to frame crop area estimates in the North Eastern States with as much detail as possible.
4.2.21 The Commission, therefore, strongly favours the use of TRS and EARAS data for framing area forecasts as well as final estimates in the temporarily and permanently settled parts and the Remote Sensing technique in the rest of the country. Incidentally, the representatives of the Ministry of Agriculture and most States endorsed this approach in the Conference of Central and State Statistical Organisations held in October 2000.
4.2.22 Before the proposed method is adopted as a substitute for the present one, there should be an exploratory study to make sure that there are no unforeseen impediments in implementation and that it is fully viable to meet the intended purpose. One aspect that deserves consideration is the desirability of adding to the current year’s TRS sample, a small sub-sample of the preceeding year’s TRS sample. Data for two consecutive years from the same set of villages prove useful to improve the precision of the survey estimates.
4.2.23 The Commission, therefore, recommends that:
(i) As the data from a 20 per cent sample is large enough to estimate crop area with a sufficient degree of precision at the all-India, State and district levels, Crop area forecasts and final area estimates issued by the Ministry of Agriculture should be based on the results of the 20 per cent Timely Reporting Scheme (TRS) villages in the temporarily settled States and Establishment of an Agency for Reporting Agricultural Statistics (EARAS) scheme villages in the permanently settled states. In the case of the North-Eastern States, Remote Sensing methodology should be used for this purpose after testing its viability.
(ii) The patwari and the supervisors above him should be mandated to accord the highest priority to the work of the girdawari and the patwari be spared, if necessary, from other duties during the period of girdawari.
(iii) The patwari and the primary staff employed in Establishment of an Agency for Reporting Agricultural Statistics (EARAS) should be imparted systematic and periodic training and the fieldwork should be subjected to intensive supervision by the higher-level revenue officials as well as by the technical staff.
(v) Timely Reporting Scheme (TRS) and Establishment of an Agency for Reporting Agricultural Statistics (EARAS) scheme should be regarded as programmes of national importance and the Government of India at the highest level should prevail upon the State Governments to give due priority to them, deploy adequate resources for the purpose and ensure proper conduct of field operations in time.
4.3.1 Estimates of crop production are obtained by multiplying the area under crop and the yield rate. The yield rate estimates are based on scientifically designed crop cutting experiments conducted under the General Crop Estimation Survey (GCES). The GCES covers around 68 crops (52 food and 16 non-food) in 22 States and 4 Union Territories. Around 5,00,000 experiments are conducted every year with the help of State revenue and agricultural staff of a rank higher than the primary field staff of the departments. The survey design adopted is that of a stratified three stage random sampling with tehsil or taluka as the stratum, a village as the first stage unit, a field growing the specified crop as the second stage unit and a plot, usually 5m x 5m, as the ultimate unit. The experiment consists of marking the plot and harvesting and weighing the produce from the plot. These weights form the basic data for yield estimation. The number of experiments and their distribution over the strata are made in a manner to be able to obtain the yield rate estimates with a fair degree of precision at the level of the State and each major crop-growing district. The field staff is periodically trained in the conduct of crop cutting experiments.
4.3.2 The Improvement of Crop Statistics (ICS) scheme carries out a quality check on the field operations of GCES under which around 30,000 experiments are supervised by the ICS staff at the harvesting stage, one half by the Assistant Superintendents of the Field Operations Division (FOD) of NSSO and the remaining half by the staff of the State Agricultural Statistics Authority (SASA).
4.3.3 The method of crop cutting experiments is objective and unbiased and if properly followed provides reliable estimates of yield rates. In practice, however, the field staff do not strictly adhere to the prescribed procedures and thereby the survey estimates are subject to a variety of non-sampling errors. The supervisory check by ICS staff reveals a number of such lapses.
4.3.4 The review of ICS results referred to earlier (see Annexe 4.1) shows that the experiments in the GCES were conducted properly in only 80 per cent of the cases while the rest had one defect or the other. The defects mainly related to wrong selection of sample fields and location of experimental plots, and failure to use essential equipment such as proper weighing scales. The ICS and GCES yield estimates were seen to differ widely from each other, much more than what could be attributed to sampling errors. It is obvious that the GCES in many States is carried out perfunctorily unmindful of the serious consequences. The State departments of revenue and agriculture that are responsible for the surveys, do not seem to consider this programme important enough and there is little higher level supervision and control of field operations. The “High Level Coordination Committee (HLCC) on Agricultural Statistics” in the States is supposed to take remedial action and if it does so, it seems to have little impact on improving the situation.
4.3.5 GCES carries out around 5,00,000 experiments every year; but these are not still adequate to provide usable estimates below the district level. With the introduction of National Agricultural Insurance Scheme (NAIS) in several States a need is felt for assessment of yields of insured crops at the level of tehsil or C.D. Block and even at the panchayat level. NAIS has, therefore, prescribed additional crop cutting experiments for this purpose at the rate of 16 per block or 8 per panchayat for each insured crop. This imposes an enormous burden on the field agency, increases considerably the non-sampling errors and results in further deterioration of the quality of work. Apart from non-feasibility of carrying out such a huge number of experiments, the recent decision of Government of India that the States should combine GCES and NAIS series of experiments and use them together for framing crop production estimates is fraught with serious consequences. The objectives of the two series are different and the NAIS series is likely to underestimate yield rates because of local pressure from insured farmers whose interest lies in depressing the crop output.
4.3.6 Yet another deficiency in the production statistics is the divergence between the production figures available from different sources especially in respect of cash crops like cotton, oilseeds and horticultural crops.
4.3.7 The estimation of crop yields is based on sound and well-tested crop cutting experiment methodology. The main problem in producing reliable estimates is the poor performance of field operations. Urgent measures should be taken by the States to address this problem. There should be strict supervision of fieldwork by higher-level revenue and agricultural officials and appropriate action taken against those whose performance is consistently bad. There should be direct interaction between the ICS staff and the higher level officials of revenue and agricultural departments to instill a better awareness of the importance of the programme.
4.3.8 The immediate priority is to reduce the unacceptable level of non-sampling errors in the survey results. There should be adequate training of field staff every season. All field workers should have ready access to the experimental equipment and a serious view should be taken of anyone not using proper tools. There is scope for improving the equipment to make it more portable and easy to handle in the field.
4.3.9 At present, several State agencies are assigned the work of crop cutting experiments, which cannot, perhaps be avoided altogether when a large number of experiments have to be conducted within a short period. Nevertheless, an effort should be made to reduce the diversity of agencies and utilise as far as possible the State agricultural and statistical agencies for better control of field operations.
4.3.10 A Statistical Study may be made to examine whether the data collected in the ICS can be used for working out a correction or adjustment factor to be applied to official statistics of Crop Area to provide an alternative all-India estimate of crop area as a cross check on official statistics compiled from the States’ reports. If this is technically feasible, the design of the ICS can be modified and the scheme strengthened to generate such correction factors. The Commission appointed an Expert Group comprising representatives of ISI, IASRI and NSSO to look into this question. In the short time available the Expert Group could not examine the question of efficacy of the correction factor. After studying the report of the Expert Group, the Commission is of the view that, in view of the past experience of the Land Utilisation Surveys of the NSS, the modified objective of the ICS should be restricted to working out a correction factor and not the generation of independent estimates of crop area. Further statistical investigations of the problem will be required before redesigning ICS to meet the modified objective.
4.3.11 The need for crop production estimates for small areas (C.D blocks, panchayats) has assumed urgency especially after the introduction of crop insurance. As noted earlier, expansion of the scale of crop cutting experiments to meet this need is almost impossible if NAIS is implemented throughout the country and covers many more crops than at present. An approach other than crop cutting experiments has to be sought, and the technique of “small area estimation” holds out a promising solution. There has been considerable development in the field of small area statistics. The IASRI is experimenting with this method to frame block and panchayat level estimates and pilot studies are in progress. It is important to pursue this programme until a satisfactory and tested methodology is available.
4.3.12 The Commission, therefore, recommends that:
(i) In view of the importance of reliable estimates of crop production, the States should take all necessary measures to ensure that the crop cutting surveys under the General Crop Estimation Survey (GCES) are carried out strictly according to the prescribed programme.
(ii) Efforts should be made to reduce the diversity of agencies involved in the fieldwork of crop cutting experiments and use as far as possible agricultural and statistical personnel for better control of field operations.
(iii) A statistical study should be carried out to explore the feasibility of using the ICS data for working out a correction or adjustment factor to be applied to official statistics of crop area to generate alternative estimates of the same. Given the past experience of the Land Utilisation Surveys of the NSS and the controversies they created, the Commission is of the view that the objective of redesigning of the ICS, at present, should be restricted to working out a correction factor.
(iv) The two series of experiments conducted under the National Agricultural Insurance Scheme (NAIS) and the General Crop Estimation Survey (GCES) should not be combined for deriving estimates of production as the objectives of the two series are different and their merger will affect the quality of general crop estimates.
(v) Crop estimates below the level of district are required to meet several needs including those of the National Agricultural Insurance Scheme (NAIS). Special studies should be taken up by the National Statistical Office to develop appropriate “small area estimation” techniques for this purpose.
4.4.1 Final estimates of crop production based on area through complete enumeration and yield rate through crop-cutting experiments become available much after the crop is harvested. However, the Government needs advance estimates of production for various decisions relating to pricing, distribution, export and import, etc. The Directorate of Economics & Statistics, Ministry of Agriculture (DESMOA) releases advance estimates of crop area and production through periodical forecasts in respect of principal food and non-food crops (food grains, oil seeds, sugarcane, fibres, etc.), which account for nearly 87 per cent of agricultural output. Four forecasts are issued, the first in the middle of September, the second in January, the third towards the end of March and the fourth by the end of May.
4.4.2 The first forecast relating to the kharif crops is mostly based on reports prepared by the States mainly guided by the visual observation of field officials. The second forecast covering both the kharif and rabi crops takes into account additional information obtained from various sources including agricultural inputs, incidence of pests and diseases, and weekly reports of State departments of agriculture regarding area coverage, conditions of standing crops, etc. Results of Remote Sensing data are also considered at this stage. In the third forecast, the earlier advance estimates of both the kharif and rabi seasons are firmed up, again taking into account information received from sources such as Market Intelligence Units, Meteorological Department and the Crop Weather Watch Group (CWWG). The fourth forecast is based on firm figures supplied by State Agricultural Statistics Authorities (SASAs) who are by then in a position to obtain fairly dependable estimates of yield rates through GCES. In addition to the four forecasts, the DESMOA issues the “Final Estimates” of crop area and production in December. As a few States continue to revise their data on delayed receipt of information, the all-India crop statistics are brought out as “Fully Revised” in the next crop year in the following December.
4.4.3 Recently, the Ministry of Agriculture has set up a National Crop Forecasting Centre (NCFC) with the object of examining the existing mechanism of building forecasts of principal crops and developing more objective techniques. The NCFC takes into account information on weather conditions, supply of agricultural inputs, pests, diseases and related aspects including the proceedings of CWWG in the formulation of scientific and objective forecasting methods to replace the present system. The work of the NCFC is still at a preliminary stage and it needs more statistical support to be able to develop appropriate models of forecasting.
4.4.4 The present system of crop forecasts being based mostly on subjective appraisal at various levels does not reflect the ground situation correctly. This is specially the case with regard to the preliminary forecasts, which have to be fairly reliable for taking several policy decisions. There is need for more objective forecasting based on timely and detailed information on crop condition, meteorological parameters, water availability, crop damage, etc. The NCFC is still not in a position to develop a scientific procedure of forecasting using multi-dimensional models and assimilating the information received from various sources. The DESMOA is handicapped due to non-receipt of timely information from the States and it often has to prepare such forecasts based on incomplete data.
4.4.5 Frequent changes in the production figures especially of food grains between one forecast and another, and the “final” and “fully revised” estimates cause confusion and doubt among the users. While releasing these figures, the DESMOA may indicate the reasons for the change.
4.4.6 The system of forecasting crop production in the country by the Ministry of Agriculture needs to be replaced as soon as possible by an objective method using appropriate statistical techniques. The recent establishment of the NCFC, which has been assigned the responsibility of streamlining and improving the quality of forecasting, should go a long way in accomplishing this objective. However, it needs additional professional support, comprising statisticians and multi-disciplinary team of experts to devise scientific techniques of crop forecasting.
4.4.7 Remote Sensing technology can also provide a satisfactory means of developing reliable estimates of crop area and condition of the crop at various stages of growth for forecast purposes. The Space Application Centre (SAC) is already at an advanced stage of experimenting with the approach of Remote Sensing to estimate the area under principal crops through the scheme known as “Forecasting Agricultural output using Space, Agro-meteorology and Land based observations” (FASAL). Incidentally, this will form an important input in the forecasting methodology to be developed by NCFC. The land-based observations should be used to measure quantitative changes in crop growth besides discriminating one crop from another.
4.4.8 The Commission, therefore, recommends that:
(iii) The programme of Forecasting Agricultural output using Space, Agro-meteorology and Land based observations (FASAL), which is experimenting the approach of Remote Sensing to estimate the area under principal crops should be actively pursued.
(iv) The States should be assisted by the Centre in adopting the objective techniques to be developed by the National Crop Forecasting Centre (NCFC).
4.5.1 There are two main sources that generate statistics of production of horticultural crops. The first is the Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA), which operates a Centrally sponsored scheme “Crop Estimation Survey on Fruits and Vegetables” in 11 States covering 7 fruit and 7 vegetable and spice crops for estimating area and production. The fruit crops covered are mango, banana, apple, citrus, grapes, pineapple and guava. The vegetable and spice crops are potato, onion, tomato, cabbage, cauliflower, ginger and turmeric. The survey, which is still in a “pilot” stage follows a stratified three-stage random sampling design in the case of fruit crops, with village, orchard and fruit bearing tree as the sampling units at the successive stages. The sample size is usually 150 to 200 sample villages in each major fruit-growing district, five orchards per sample village and four fruit bearing trees per orchard. The number and weight of fruits gathered from the sampled trees is observed and recorded, which form the basis for yield estimation. The survey approach in the case of vegetable crops is somewhat more complex due to special features of cultivation of these crops especially the short duration of the crop and the number of pickings required to record the harvested produce. The results of the DESMOA survey are published in its “Report and Database of Pilot Scheme on Major Fruits and Vegetables”.
4.5.2 The second source of horticultural statistics is the National Horticultural Board (NHB), which compiles and publishes estimates of area, production and prices of all important fruit and vegetable crops based on reports furnished by the State Directorates of Horticulture and Agriculture. The methodology followed by NHB for estimating area and production has not been clearly spelt out. These estimates are apparently based on the informed assessment of local level officials dealing with horticulture and the reports of market arrivals in major wholesale fruit and vegetable markets.
4.5.3 The production estimates of fruits and vegetables available from the DESMOA pilot survey are based on sound technical methodology. However, the survey procedures are complex, time consuming and rather difficult to implement in practice. Further, the survey is limited to 11 States and its extension to the remaining States will take a long time due to the fact that many of them do not possess the necessary staff resources to carry out the fieldwork. Adoption of this methodology on a nation-wide scale is a remote possibility.
4.5.4 The estimates furnished by the NHB relate to the entire country but they are of doubtful reliability being essentially based on subjective reports received from the ground-level staff. There is, in fact, considerable divergence between the NHB and the DESMOA estimates for the States and the crops covered (see Annexe 4.2).
4.5.5 Neither NHB nor DESMOA provide estimates of production of crops such as mushroom, herbs and floriculture that are of emerging commercial importance.
4.5.6 The methodology used in the DESMOA survey for estimation of production is complex, time consuming and not cost-effective. It is observed that the field staff does not always follow the procedures laid down for collection of data. It is obvious that an alternative and more feasible methodology needs to be developed for estimating production of horticultural crops. Such an approach may consider the possibility of using the flow of data from sources concerned with horticultural crops such as wholesale markets, growers associations, fruit and vegetable processing plants, export trade, etc. in order to develop a suitable model for estimation. Special studies need to be carried out in this connection, which may be entrusted to a team comprising representatives of the Indian Agricultural Statistics Research Institute (IASRI), DESMOA, NSSO (FOD) and one or two major States growing horticultural crops.
4.5.7 The Commission recommends that:
(i) The methodology adopted in the pilot scheme of “Crop Estimation Survey on Fruits and Vegetables” should be reviewed and an alternative methodology for estimating the production of horticultural crops should be developed taking into account information flowing from all sources including market arrivals, exports and growers associations. Special studies required to establish the feasibility of such a methodology should be taken up by a team comprising representatives from Indian Agricultural Statistics Research Institute (IASRI), Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA), Field Operations Division of National Sample Survey Organisation (NSSO (FOD)) and from one or two major States growing horticultural crops. The alternative methodology should be tried out on a pilot basis before actually implementing it on a large scale.
(ii) A suitable methodology for estimating the production of crops such as mushroom, herbs and floriculture needs to be developed and this should be entrusted to the expert team comprising representatives from Indian Agricultural Statistics Research Institute (IASRI), Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA), Field Operations Division of National Sample Survey Organisation (NSSO (FOD)) and from one or two major States growing these crops.
4.6.1 Apart from the estimates of production compiled and published by the DESMOA, a separate series is also available for some major commercially important crops prepared by the trade organisations especially for cotton and oilseed crops. The estimates of cotton production are published by the Cotton Advisory Board (CAB) and those for the oilseeds by the Central Organisation for Oil Industry and Trade (COOIT). The DESMOA and Trade series differ widely from each other causing confusion among users and debate over the veracity of either series. The Commission examined in some detail the divergence between the two series and its findings are as follows:
4.6.2 The DESMOA compiles the production estimates on the basis of reports received from State Governments. These are obtained as the product of area sown under the crop through complete enumeration and the yield rate from crop cutting experiments. The CAB estimates are based on inputs from the Cotton Corporation of India, East India Cotton Association, Indian Cotton Mills Federation, etc. and these, in turn, depend on data on market arrivals, volume of cotton ginned and pressed in all ginning mills irrespective of the area sown or condition of the crop. The two series of estimates differ from each other within a range of 13 to 45 per cent over the years, the DESMOA estimates being consistently less than the CAB estimates (see Annexe 4.3). The main reasons for divergence are seen to be:
(a) Shortcomings of the girdawari on which the official estimate of area is based and the inadequacy of the GCES to give due representation and weight in its sample to different factors such as irrigated and un-irrigated, hybrid and local varieties of crop. Cotton is harvested through several pickings spread over time and it is possible that the primary agency is not careful to follow the prescribed procedure of the crop cutting experiments;
(b) The CAB estimates on the other hand, are of a subjective nature being compiled on the basis of reports from several agencies without proper attention to full coverage and standard procedures.
4.6.3 The DESMOA has been making consistent efforts to reduce the divergence between the two estimates by holding discussions with the concerned agencies. The following measures are suggested in this connection:
(a) The sample of crop cutting experiments may be suitably increased and made representative of various types of cotton cultivation;
(b) The primary agencies responsible for area enumeration and crop cutting experiments should be trained thoroughly;
(c) The methodology followed by CAB should be improved by a careful review of the data from sources like market arrivals, ginning factories, Annual Survey of Industries (ASI), unorganised manufacturing units, etc. in respect of cotton and the use of appropriate models.
4.6.4 The situation in the production statistics of oilseeds is not very different from that of cotton. The magnitude of divergence between the two series in this case is of the order of 14 per cent in respect of 9 important oilseeds (see Annexe 4.4). The DESMOA estimates are based on the girdawari for area and crop cutting experiments under the GCES for yield, whereas the estimates of COOIT mainly depend on the feedback received from important markets about arrivals, trend of crop and the additional information provided by members of the industry.
4.6.5 The main reasons for divergence, in this case too, are differences in methodology, post-harvest losses, incomplete market arrivals and the inclination of the oilseeds industry to underestimate production in order to lobby for larger imports. It is understood that the DESMOA constituted two regional committees in consultation with COOIT in Andhra Pradesh and Madhya Pradesh, respectively to look into the discrepancies and reduce them to the extent possible. The DESMOA should have the work of the regional committees completed expeditiously and in the light of their findings, undertake a special study of the major oilseed markets to devise more objective procedures of estimation to be followed by the trade agencies.
4.7.1 Statistics of land use are compiled from the village land records maintained by the patwari. The information is available according to each survey number and recorded under nine categories: (a) Forests, (b) Area under Non-Agricultural use, (c) Barren and Uncultured Land, (d) Permanent Pastures and other Grazing Land, (e) Miscellaneous Tree Crops, (f) Culturable Waste Land, (g) Fallow Land other than Current Fallows, (h) Current Fallows, and (i) Net Area Sown. The details of each category along with its definition may be seen in the Annexe 4.5.
4.7.2 Land use statistics are also being collected through nationwide land use or cover mapping by the National Remote Sensing Agency (NRSA) according to a 22-fold classification, the definition of each category is given in the Annexe 4.6. The categories are much more detailed and provide useful information for land development programmes. However, these details are still not available at the local levels of block and panchayat.
4.7.3 The nine-fold classification of land use based on village records is not adequate and does not, for instance, provide information on such characteristics as social forestry, marshy and water logged land, built-up land, etc. which are important for local development plans. On the other hand, it is out of question to introduce the 22-fold classification in the village records. The patwari cannot, in most cases, identify the characteristics of various categories not to speak of the heavy burden this work imposes.
4.7.4 It is suggested that the nine-fold classification may be slightly enlarged to cover two or three categories of land use which are of common interest to the Centre and States, and which can be easily identified by the patwari through visual observation. Such addition increases his workload only marginally. The categories to be added may be decided by joint consultation between the Centre and the States. Incidentally, there was a consensus in the Conference of Central and State Statistical Organisations on the addition of social forestry, marshy and water logged land, and land under still waters.
4.7.5 It is desirable to consider in this context the question of rationalisation and simplification of the Village Crop Register (Khasra Register) and other records maintained by patwari. The records have remained almost the same since the mid 50s. There are also marked differences in the content and format of the records among the States. Cropping practices have also changed over time and new crops especially of short duration are sown and harvested. The list of crops covered by the Village Crop Abstract (Jinswar) needs a review that may also result in some changes in the manual of instructions for the girdawari. The Commission appointed an Expert to suggest changes after undertaking a review of the system of land records in different parts of the country. On examination of the Report of the Expert, the Commission is of the view that the system of land records being different in different States, it would be appropriate if the State Governments review the systems by appointing experts in the field.
4.7.6 Computerisation of land records is another major effort in progress to modernise the land record system. Under this programme, plot-wise details of ownership are to be maintained in the computer and periodically updated so that each owner is able to obtain readily his ownership record. Incidentally, computerisation reduces the workload of the patwari to the extent that he does not have to record the permanent columns of the Khasra Register. Many States have reported substantial progress in implementing the programme. It should be ensured that this is completed expeditiously.
4.7.7 The Commission, therefore, recommends that:
(i) The nine-fold classification of land use should be slightly enlarged to cover two or three more categories such as social forestry, marshy and water logged land, and land under still waters, which are of common interest to the centre and States, and which can easily be identified by the patwari through visual observation.
4.8.1 Irrigation statistics mainly relate to data on area irrigated by different sources and under different crops. The principal sources of irrigation statistics are the crop statistics compiled by the Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA), and the publications of the Ministry of Water Resources. Besides these, some data on irrigated area are available from the administrative reports of State Government departments and the Agricultural Census. Rainfall and weather data are available from the India Meteorological Department (IMD).
4.8.2 In the temporarily settled States, irrigation statistics are compiled from the village girdawari, whereas the same are estimated on the basis of sample surveys in respect of the permanently settled States of Kerala, Orissa and West Bengal. These statistics relate to net or gross irrigated area by sources (canals, tanks, tube well, etc.) and also area under each crop. The data are collated and published by the DESMOA with a time lag of three to four years.
4.8.3 Groundwater is the principal source for minor irrigation and the Central Ground Water Board (CGWB) is responsible for generation and dissemination of statistics on ground water which inter-alia include statistics on minor irrigation. The Minor Irrigation Division of the Ministry of Water Resources also compiles information on minor irrigation at the national level on the basis of statistics furnished by nodal offices designated for the purpose in individual States. The Command Area Development Division of the Ministry compiles and disseminates data on Command Area Development Programme (CADP) furnished by State Command Area Development Authorities (CADAs).
4.8.4 Lack of a sound database for the minor irrigation sector has made it necessary to conduct a periodical Census of Minor Irrigation works throughout the country under the scheme of Rationalisation of Minor Irrigation Statistics (RMIS). The primary fieldwork of the census is entrusted to the patwari and the village level worker (of C.D. block) under the supervision of block-level officials who also exercise a five per cent sample check in randomly selected villages. The results of the sample check are used to apply a correction factor to the main census data. Validation of data takes place at the district level and further compilation and tabulation at the State level with the help of software provided by the National Informatics Centre. The First census was conducted with reference year 1986-87 and the all-India Census Report was published in November 1993. The Second census with reference year 1993-94 has been completed and the report released recently. The Third census is being launched with reference period 2000-2001. A sample survey with reference year 1998-99 to assess the status of minor irrigation schemes, in use at the time of Second census is also being conducted.
4.8.5 The Central Water Commission (CWC), which is the nodal agency for water resource development in the country, is responsible for statistics of water resources pertaining to major and medium irrigation projects. The River Management Wing of CWC is engaged in hydrological data collection relating to all the important river systems in the country with the help of as many as 877 hydrological observation sites. The Information System Organisation (ISO) in the CWC is involved in planning, implementing, monitoring and coordinating all aspects of activities associated with information-gathering activities, analytical studies and computerisation.
4.8.6 Statistics compiled by CWC on major and medium irrigation projects and those compiled by the Minor Irrigation Division, especially the irrigation potential created and actually being utilised are the alternative sources of estimates of total irrigated area.
4.8.7 There is a large variation between the statistics of “area irrigated” published by the DESMOA and the “irrigation potential utilised” published by the Ministry of Water Resources (see Annexe 4.7). Both data series are available with a considerable time lag.
4.8.8 The existing system of generation and dissemination of data in respect of major and medium irrigation projects does not permit real time monitoring of inflows of water and its utilisation through canals and the distributory system. Reluctance on the part of the States to furnish the data in view of their vested interest in the sharing of water is another stumbling block.
4.8.9 A large volume of useful data is reported to be available with the CWC on various aspects of irrigation without any statistical analysis. These data need to be put to use by the statistical machinery for better management of water resources.
4.8.10 In view of the wide variation between the data on irrigated area provided by the DESMOA and the Ministry of Water Resources, it becomes essential that State Governments make a special effort to minimise the divergence through appropriate interaction among the departments concerned. This is better attempted at the local level (panchayat or village).
4.8.11 It is desirable to have statistics of irrigated area with cross-classification by source of irrigation (major, medium and minor) and by individual crop. As this involves laborious tabulation at the village level, this may be done once in five years as part of the Agricultural Census.
4.8.12 In order to reduce the time lag between the generation and dissemination of data in respect of irrigation projects for real time monitoring of water resources, and proper and efficient water management, it is necessary that the major and medium irrigation projects are provided with computer facilities as well as appropriate Geographical Information Systems (GIS).
4.8.13 Involvement of the State Directorates of Economics and Statistics (DESs) in all State-level programmes of irrigation statistics and establishing direct linkage between the State DESs and the nodal Central Government agencies will help speedy data flow. The State DESs need to be strengthened for this purpose. The CWC has a major role in the production of water resources statistics. It is desirable to strengthen the network of CWC field offices by creating statistical monitoring and evaluation cells in them with trained statistical personnel. In order to oversee and guide the development and management of statistics of water resources, the Central Statistical Organisation (CSO) should designate a senior-level officer to interact with Central and State irrigation agencies.
4.8.14 The divergence between the two series of irrigated area published by the Ministry of Agriculture and Ministry of Water Resources is inevitable due to different concepts and definitions used by them. The data users should be made aware of these differences for proper understanding and analysis of data.
4.8.15 The Commission, therefore, recommends that:
(i) In view of wide variation between the irrigated area generated by the Ministry of Agriculture and the Ministry of Water Resources, the State Governments should make an attempt to explain and reduce the divergence, to the extent possible, through mutual consultation between the two agencies engaged in the data collection at the local level.
(ii) The State Directorates of Economics and Statistics (DESs) should be made the nodal agencies in respect of irrigation statistics and they should establish direct links with the State and Central agencies concerned to secure speedy data flow.
(iii) Statistical monitoring and evaluation cells with trained statistical personnel should be created in the field offices of the Central Water Commission (CWC) in order to generate a variety of statistics relating to water use.
(iv) The Central Statistical Organisation (CSO) should designate a senior level officer to interact with the Central and State irrigation authorities in order to promote an efficient system of water resources statistics and oversee its activities.
4.9.1 For the planning and implementation of land reforms, comprehensive information relating to the characteristics of different size classes of holdings is essential. This is also necessary to identify and formulate policies and programmes for the welfare of small and marginal farmers especially, the rural poor and economically weaker sections. The information is required by operational holdings as distinct from ownership holdings. An operational holding is defined as “all land, which is used wholly or partly for agricultural production and is operated as one technical unit by one person alone or with others without regard to title, legal form, size or location”. Thus, the Agricultural Census of operational holdings assumes importance as a source of basic data required for several uses.
4.9.2 Agricultural Censuses in the country are conducted at intervals of five years, as a part of the World Census of Agriculture (WCA). The census provides detailed statistics on the structure of operational holdings and their main characteristics like number and area, land use, irrigation, tenancy and cropping pattern. The first Agricultural Census was conducted with reference year 1970-71 and the sixth with reference year 1995-96 is nearing completion.
4.9.3 The census is carried out in three phases. During Phase I, a list is made of all the operational holdings and their primary characteristics like location, area, gender and social group of the holder. During Phase II, detailed data on tenure, tenancy, land use, irrigation, crop areas, etc. are collected. Phase III, popularly known as input survey, relates to collection of data on agricultural inputs (seeds, fertilisers, pesticides, etc.) according to five size groups of the holdings.
4.9.4 The census follows the method of re-tabulation of data from village land records in the temporarily settled States (accounting for 83 per cent of the total area). In the rest of the country, the census is taken through a household enquiry in a 20 per cent sample of villages. Even in the temporarily settled States, the data collected during Phase II is confined to a 20 per cent sample of the villages. The input survey (Phase III) is a household survey in a 7 per cent sample of villages selected from the 20 per cent villages (Phase II) in respect of both the temporarily and permanently settled States.
4.9.5 One of the principal shortcomings of the Agricultural Census is the delay in the availability of final results. The reference period of the census is an agricultural year (July-June) and normally the census results should be available within two years from the end of the reference period. In practice, however, the time lag is as long as 4-6 years (see Annexe 4.8). For example, the results of the current census with reference year 1995-96 are expected to be available only in 2001. The main reason for this delay is the pre-occupation of the patwari agency, which is designated for this complex and time-consuming work. Census operations also suffer from lack of adequate administrative and technical supervision over the work of the primary agency.
4.9.6 The census is based on re-tabulation of land records data in a large part of the country and its reliability rests on how accurate and up-to-date are the records. It is well known that the village records are deficient in several respects.
4.9.7 The census does not cover information on farm population and its composition, which is a major attribute of operational holdings. Likewise, it does not also provide details of livestock held by the holders.
4.9.8 The Agricultural Census is a major operation and the procedures prescribed for collecting the data are quite comprehensive and cover a wide variety of information. Initially, there was a fairly high-level hierarchy of officials responsible for planning and organising census operations. At the Central level there was an Agricultural Census Commissioner of India with adequate supporting staff and also a Monitoring Group under the Chairmanship of a Special Secretary. There used to be a corresponding mechanism at the State level to plan and supervise the census operations. However, over time, there has been depletion in the numbers and status of personnel in charge of the census. Apparently, the census ceased to have the same importance and priority, with the result that there has been significant erosion in the quality and timeliness of census data. It is essential that concerted measures are taken for effective management and organisation of the census and that it is carried out in time.
4.9.9 The patwari agency, which is responsible for this primary data collection, is already over-burdened with multifarious activities. The census work does not receive due priority and there is reason to believe that the work is not done properly. It is therefore desirable to explore the possibility of reducing the workload of patwari. The Commission proposes that the Agricultural Census should henceforth be carried out on a sample basis. A sample census in 20 per cent of villages is considered adequate to meet most of the data requirements. Even now a large part of the census information is obtained from a 20 per cent sample of villages. Only the information on the number and area of holdings is obtained with cent per cent coverage in the temporarily settled States and the rest of census operations are limited to a 20 per cent sample.
4.9.10 As mentioned before, the method of re-tabulation of land records in temporarily settled States does not enable collection of information on the farm and livestock population associated with the operational holdings. This needs a household enquiry. There is even now an element of household enquiry in these States to gather information on part holdings held by resident holders outside the village precincts. The scope of the enquiry may be slightly enlarged to include the above information. The household enquiry also serves as a cross check on the other characteristics of the holdings derived from re-tabulation of land records.
4.9.11 The Commission is of the view that a sample census will be a better-controlled and more manageable programme without in any way compromising its objectives. The computerisation of land records, that is likely to be completed shortly in many States, will also help in reducing manual re-tabulation and thus relieve the patwari agency of a part of the work load.
4.9.12 In order to improve the census operations, there has to be an appropriate strengthening of managerial personnel with an independent Agricultural Census Commissioner of sufficiently high status at the centre and suitable counterparts in the States. Necessary arrangements will have to be made for updating the village land records and for adequate supervision. Careful planning, advance preparation, and thorough training of primary staff are essential for successful conduct of the census.
4.9.13 The Commission, therefore, recommends that:
(iv) There should be adequate provision for effective administrative supervision over the fieldwork of Agricultural Census and also a technical check on the quality of data with the help of the State statistical agency.
(v) The post of the Agricultural Census Commissioner of India at the Centre should be restored and should be of the level of Additional Secretary to be able to interact effectively with the State Governments. Further, this post should be earmarked for a senior statistician.
4.10.1 The Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA) is responsible for the collection, compilation and dissemination of the price data of agricultural commodities. The price data are collected in terms of (a) weekly and daily wholesales prices, (b) retail prices of essential commodities, and (c) farm harvest prices.
4.10.2 Weekly wholesale prices cover 140 agricultural commodities from 620 markets. The data are collected by price reporters appointed by the State Governments or Agricultural Marketing Committees and forwarded to the State Directorates of Economics and Statistics (DESs). Daily wholesale prices cover 12 commodities (rice, paddy, wheat, jowar, bajra, ragi, maize, barley, gram, sugar, gur and khandsari) from 617 market centres. On receipt of the prices from various State agencies, the Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA) forwards the same to the Economic Adviser, Ministry of Commerce and Industry for monitoring wholesale prices. Wholesale prices of certain important cereals, gram and sugar are also sent to the Cabinet Secretary on alternate days for direct monitoring.
4.10.3 Retail prices of essential commodities are collected on a weekly basis from 83 market centres in respect of 88 commodities (49 food and 39 non-food) by the staff of the State Market Intelligence Units, State Directorates of Economics and Statistics (DESs) and State Department of Food and Civil Supplies. Flow of data from these agencies is not considered satisfactory.
4.10.4 Farm Harvest Prices are collected by the field staff of the State revenue departments for 31 commodities at the end of each crop season and published by the DESMOA. It brings out a periodical publication entitled, Farm Harvest Prices of Principal Crops in India.
4.10.5 Wholesale prices data are received in the DESMOA mostly through postal mail, which entails delay. Data on retail prices of the essential commodities are received with a time lag of about five to six weeks and the response rate is only of the order of 60 per cent. Supply of data through post is stated to be the reason for delay. The State Governments generally use part time reporters who are not fully conversant with the connotations of the different terms used in price data collection and they do not pay adequate attention to the reporting work. The main deficiency in the collection of price data arises due to large non-response. There is no coordination among the State agencies concerned nor an adequate supervisory check over price collection.
4.10.6 Wholesale prices are primarily used to monitor the weekly price movements. It is, therefore, essential to have quality data on prices by ensuring representative price collection centres and commodity-wise quotations of prices. For this purpose, a well-documented manual of instructions on collection of prices is required. The price collectors should be given thorough training on concepts, definitions and the methods of data collection. The training courses should be repeated periodically.
4.10.7 A mechanism to ensure timely data flow is an immediate need. For this, the latest tools of communication technology like e-mail should be availed of. Further, the system should ensure simultaneous data flow from lower levels to the State as well as to the Centre.
4.10.8 The State agencies at the district level and below should follow up cases of chronic non-response. The quality of data should be determined on the basis of systematic analysis of the price data both by the Centre and the States. Workshops and training courses should be an integral part of quality improvement.
4.10.9 The number of essential commodities should be reduced to an absolute minimum, especially the non-food crops, in consultation with Ministry of Consumer Affairs and Cabinet Committee on Prices. The centres of price collection should, as far as possible, be the same for the essential commodities as for those of wholesale prices.
4.10.10 The Commission recommends that:
(iii) Workshops and training courses should be made an integral part of quality improvement. The quality of data should be determined on the basis of systematic analysis of the price data of agricultural commodities both by the Centre and the States.
(vii) The number of essential commodities for which agricultural prices are collected should be reduced to an absolute minimum, especially the non-food crops, in consultation with Ministry of Consumer Affairs and Cabinet Committee on Prices.
4.11.1 On the recommendation of the Agricultural Prices Enquiry Committee, (1954), the Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA) set up 14 Market Intelligence Units (MIU) in the capitals of Andhra Pradesh, Assam, Bihar, Delhi, Gujarat, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Orissa, Rajasthan, Tamil Nadu, Uttar Pradesh, and West Bengal. The market intelligence units are intended to help the DESMOA in the formulation, implementation and review of the agricultural price policy relating to procurement, marketing, storage, transportation, import, export and credit, etc. The units furnish regular reports on market arrivals, off-takes, stocks, crop prospects, and outlook of market prices. They are also required to give their appraisal of production of various kharif and rabi crops at regular intervals to help preparation of crop forecasts.
4.11.2 Though the data to be supplied by the market intelligence units are of great utility, the units have ceased to be effective in discharging their functions mainly due to a lack of proper direction and control of their activities. Over the years, the staff strength of the units has been considerably reduced resulting in even worse performance.
4.11.3 Agricultural Market Intelligence is an important and useful instrument, and it should be strengthened and extended to all the States. The MIUs apparently have not been able to function in the manner envisaged. Their operations and staff requirements should be re-evaluated and appropriate measures taken to streamline the units. Full advantage of their services should be availed of to provide advance estimates of crop production, to collect auxiliary information required for framing “small area” estimates of crop production and several other studies. The Commission recommends the restoration of the MIUs and a revival of their activities fully.
4.11.4 The Commission recommends that:
4.12.1 In order to pursue its price support policy, the Government of India announces from time to time, the minimum support prices of principal crops. This necessitates the availability of relevant data on the cost of production of the crops concerned. To meet this requirement, a comprehensive survey of the Cost of Cultivation of Principal Crops was initiated in 1970-71. The survey is in operation in 16 States and covers 29 crops, the number and choice of crops in each State depending upon their importance to the State.
4.12.2 The Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA) has the overall charge of implementing the survey programme through the Agricultural Universities in 13 States and general universities in three States by providing them cent per cent financial assistance. The survey design followed is that of three-stage stratified random sampling with the tehsil or taluka as the first stage unit, a cluster of villages as the second stage unit and an operational holding as the third and ultimate stage unit. The fieldwork consists of collecting from each sample household through the cost accounting method, data on all aspects of cultivation (inputs, outputs, prices paid and received) by keeping a detailed record on a day-to-day basis. The universities engage full time field men for this purpose. Training to the field staff is imparted by the universities and whenever necessary, supplemented by the DESMOA.
4.12.3 The Cost of Cultivation Studies are primarily intended for use by the Commission for Agricultural Costs and Prices (CACP). In addition, these data are used by the Central Statistical Organisation, Planning Commission, other Economic Ministries of Government of India as well as research organisations.
4.12.4 It is reported that the data collected and processed under the scheme do not suffer from any serious deficiencies, and the only problem is shortage of manpower in the Central Analytical Unit of DESMOA, which results in delay in the availability of final results. This is, however, far from true. The CACP does not obtain timely and sufficient inputs from these studies, which are required in the fixing of the minimum prices. The requirements of the National Accounts Division of CSO are also not met adequately. Implementation of the scheme by the Agricultural Universities is reported to be unsatisfactory. The data entry and processing still make use of a DOS-based computer package called FARMAP provided by Food and Agricultural Organisation (FAO) and no updating of the package has been undertaken. There has been no report on the results of the scheme until recently. (The DESMOA has now brought out a consolidated report.)
4.12.5 Cost of cultivation studies should continue in view of their importance in price administration of agricultural commodities and several studies relating to farm economy. Irrespective of the agency that is assigned this work, there should be a more focused attention to proper organisation and management of the studies. It is necessary to have an early review of the number of centres, methodology, sample size, the existing schedule and questionnaire, etc. The universities should be encouraged to tabulate and analyse the data for which they should be provided the necessary support. The DESMOA should endeavour to release the survey results with least possible delay, and any strengthening needed for improving the performance of the scheme should be immediately provided.
4.12.6 The Commission recommends that:
(i) In view of the importance of the Cost of Cultivation Studies in the price administration of agricultural commodities and several studies relating to farm economy, the present programme should continue.
4.13.1 Data on livestock numbers are collected through a quinquennial Livestock Census that is a complete enumeration of all households with regard to livestock population, poultry, agricultural machinery and fishing craft. The data collected are quite detailed; the livestock is classified according to various species of animals by breed, sex and age. The First Livestock Census was conducted in 1919-20 and the Sixteenth census is in progress with the reference date of 15 October 1997.
4.13.2 The Livestock Census is a Centrally sponsored scheme coordinated by Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA). The census is conducted by the State Animal Husbandry Departments with the help of their field staff. In some States, the field operations are entrusted to the village patwari agency with technical supervision provided by the Department of Animal Husbandry. Reports of the Livestock Census are brought out in two volumes, the first relating to all-India and State-wise data, and the second to the district-wise information.
4.13.3 The Livestock Census is the only source of statistics on livestock numbers, their age and sex structure, and functional classification. The data collected are quite elaborate but the final published output leaves much scope for improvement in terms of timeliness and reliability. The sixteenth census scheduled to be completed in 1997 is still in progress in several States. The time lag in the availability of data from the Livestock Census may be seen from Annexe 4.8. Non-adherence to the reference date, incomplete coverage and spreading the census operations over long stretches of time reduce the utility of the census data.
4.13.4 Although the Livestock Census is based on household enquiry, the census data are not related to the households and their composition. It is important, for example, to have the number of purely livestock holdings classified by main occupation of the head of the household.
4.13.5 Changes in reference date and classification of the population over various censuses also vitiate comparison over time.
4.13.6 In view of the excessive delay in completing the census operation and long time-lag in the availability of census results, it is imperative to reduce drastically the volume of census work so that it can be completed at least within a period of one year, if not in a short interval of a few weeks around the reference date (15 October). It is also essential to ensure better organisation and management of the census through strict compliance to the time schedule, comprehensive training of field staff and regular supervision over the fieldwork. The Commission considers that the Livestock Census too, like the Agricultural Census, should henceforth be taken in a 20 per cent sample of villages in place of cent per cent coverage under the prevailing system. A sample census of this magnitude is quite adequate to provide reliable estimates of livestock numbers with details of principal characteristics down to the level of a district as of now. The sample census facilitates speedy collection of data and a more effective use of available resources for census work, reduces considerably the volume of data processing, and goes a long way in improving the timeliness, content and quality of the final census result. Another important measure towards securing this objective is the extensive use of Information Technology (IT) tools at various levels for processing and transmission of data.
4.13.7 The Commission, therefore, recommends that:
(iii) There should be a concerted effort towards better organisation and management of the Livestock Census operation through comprehensive training of the field staff and regular supervision over their work by both administrative and technical personnel.
4.14.1 The issue of integrating the Livestock Census with the Agricultural Census has been raised on several occasions in the past. There are both operational and substantive gains, if the two censuses are taken together as recommended by the FAO World Census of Agricultural Programme. Several committees and workshops recommended earlier that the two censuses should be merged in order to lessen the burden of fieldwork on the primary data collection agency, reduce the total expenditure and get more meaningful data. The Eighth Conference of Central and State Statistical Organizations (1988) recommended a pilot study to evolve suitable procedures for the integration of the two censuses. Later, the National Advisory Board on Statistics in its ninth meeting (1991) agreed that there was a definite need for the integration of the two censuses and this should be done in a phased manner. In spite of these recommendations, the Ministry of Agriculture and some State Governments advanced the following reasons as to why the two censuses cannot be integrated:
(a) The basic unit of enumeration in the Agricultural Census is an “operational holding” whereas in the Livestock Census it is a “household”.
(b) The reference period for the Agricultural Census is one year whereas it is a specific date for the count of numbers in the Livestock Census.
(c) Agricultural Census is conducted through a dual programme of census and sample survey whereas the Livestock Census is based on cent per cent coverage of all households in the country (urban and rural).
(d) Different field agencies are used for the two censuses, the patwari agency for the Agricultural Census and the field staff of the State Department of Animal Husbandry for the Livestock Census.
4.14.2 The Commission considers that the above-mentioned problems are not too difficult to overcome and that a satisfactory procedure can be evolved for integrating the two censuses. Like the Livestock Census, the Agricultural Census also follows the household approach in the permanently settled States where it has been possible to collect information on operational holdings through household enquiry. Even in the temporarily settled States, where the Agricultural Census is based on the re-tabulation of land records, there is an element of household enquiry to account for the details of land held by resident holders outside the village precincts. As regards different reference periods of the two censuses, the Livestock Census has never been able to adhere to the stipulation of a specific date for the count of numbers. On the contrary, the census is spread over several years. If the Agricultural and Livestock Censuses are synchronised to be taken during the same year, the livestock count could be concentrated around the specified reference date as far as possible with appropriate check of the change in numbers between the date of enquiry and the reference date. The Commission has already proposed that both the censuses be limited to a 20 per cent sample of villages, which also facilitates the process of integration. Finally, there is a definite advantage in entrusting the field operations to a single reporting agency with enough safeguards such as careful advance planning and by ensuring that the censuses are accorded the requisite priority by the State administration as in the case of the Population Census. It should be emphasised that the integration of the two censuses provides scope for several cross tabulations including distribution of livestock and farm population by the size of the land holdings. Moreover, the advantages in terms of more information, reduction of operational costs on staff training, data processing, etc. overall decrease in the work load of the field agency and early availability of the census results are other major factors in favour of the merger.
4.14.3 The Commission, therefore, recommends that:
(iii) The periodical National Sample Survey Organisation’s survey on land and livestock holdings be synchronised with Agricultural and Livestock Censuses in order to supplement as well as help in the crosscheck of information from the two sources.
4.15.1 Statistics of Livestock Products are obtained from two sources: (a) annual “Integrated Sample Survey for Estimation of Major Livestock Products”, a Centrally sponsored scheme under the Department of Animal Husbandry and Dairying implemented by most of the States; and (b) periodical household enquiries by the NSSO relating to livestock.
4.15.2 The Integrated Sample Survey is a large-scale survey covering 15 per cent of the villages in the country. The survey design is that of multistage sampling with villages constituting the first stage, households as the second stage and animals from the selected households as the third and ultimate stage. The survey provides for estimation of livestock numbers as well as major livestock products (milk, meat, wool, eggs and the unit cost of production of milk and eggs).
4.15.3 The NSSO livestock surveys estimate the livestock possessed by the households with details relating to sex, breed, purchase price, market value, disposal of animals, etc. Further, NSSO consumer expenditure and enterprise surveys include data on household consumption of livestock products and dairy enterprises, respectively.
4.15.4 Estimates of livestock products obtained through Integrated Sample Survey are reported to be fairly reliable at the all-India and State level. These are reviewed and validated periodically by a Technical Committee of Direction for Improvement of Animal Husbandry and Dairying Statistics. There are still a few data gaps relating to mutton, pork, poultry meat, meat by-products, livestock feed, fodder and concentrates. Information on conversion ratios such as milk to milk-products is either scanty or lacking.
4.15.5 The Integrated Sample Survey is carried out under the overall technical guidance of the IASRI that has developed the survey design and continues to provide technical inputs in the conduct of the survey. IASRI has several research programmes dealing with improvement of livestock statistics and it should be entrusted with the task of developing appropriate methodologies for filling up the remaining data gaps.
4.15.6 The Commission, therefore, recommends that:
(ii) The Indian Agricultural Statistics Research Institute (IASRI) should be entrusted with the task of developing appropriate methodologies for filling up the remaining data gaps relating to estimates of mutton, pork, poultry meat, and meat by-products.
4.16.1 Fisheries of India can be broadly classified into two types namely, marine fisheries and inland fisheries. The Fisheries Statistics Section of the Department of Animal Husbandry and Dairying in the Ministry of Agriculture is in charge of compiling the data relating to this sector. At present data on items like fish production, prawn production, fish seed production, disposal of fish catch, preserved and processed items and aquaculture are being collected from State Governments.
4.16.2 A multistage sample survey is used to estimate the fish production from the marine sector. The survey design developed by the Indian Agricultural Statistics Research Institute (IASRI) and the Central Marine Fisheries Research Institute (CMFRI) consists of sampling of landing sites of the fishing craft as well as sampling over time of the landings. Data on deep-sea fishing are obtained through reports required to be furnished by trawlers and other deep-sea fishing vessels.
4.16.3 So far as inland fisheries are concerned, there were several attempts to develop suitable sampling techniques for estimation of catch since 1955, but they have remained inconclusive. The Central Inland Fisheries Research Institute (CIFRI), Barrakpore lately devised a methodology for collection of data relating to some important still water areas. This involves dividing water sources into two categories namely, fresh water and brackish water bodies each with a distinct ecology, and classifying them further into three groups according to the level of production. Different sampling methods are adopted for assessment of fish production in each group. There is still a large data gap in coverage not only geographically but also in terms of several sources of inland fisheries such as rivers, canals, etc.
4.16.4 As regards marine fisheries statistics, the sample methodology in use is considered to be satisfactory. There is, however, a need for periodic review of sample size, stratification and intensity of data collection in view of the changes in the pattern of fish landings. There are also problems in the flow of data from States and consequently much delay in the compilation of all-India statistics. As far as the deep-sea sector is concerned, though only a small number of licensed vessels are in operation, the data on fish catch do not flow in a regular manner. There is a need to put in place a proper mechanism of reporting for this purpose.
4.16.5 The data on fish production from the inland sector are collected by the State Governments. It is noticed that the resources required for regular data collection are quite large and the cost incurred is not commensurate with the actual volume of fish production. Inland fisheries pose several problems due to the vast and diverse nature of water sources and it is necessary to develop a cost-effective methodology. IASRI is presently engaged in some pilot studies in this regard but more concerted effort is urgently called for.
4.16.6 The data on fish production from aqua culture, supplied by the States, similarly suffer from poor quality and become available with considerable time lag. The types of culturing methods are not reflected in the data.
4.16.7 The data on fisherman population, fishing craft and gear are available from both the State Governments and the Livestock Census, while data on workers engaged in fishing are also available from the population census. However, the data from these sources are not comparable due to differences in concepts and definitions and their application across States.
4.16.8 There is an apparent inconsistency between the value of the output and the export earnings, the latter being much higher. An exploratory study is required to reconcile the discrepancy.
4.16.9 It is observed that the present system is operating satisfactorily in the case of marine fisheries but a lot still needs to be done to evolve a suitable methodology with regard to inland fisheries. In the marine sector, there is a need to impart regular, training to field staff and impose adequate supervision to ensure quality of data. Use of modern tools of Information Technology for data communication and storage will improve the quality and timeliness of fisheries statistics. Since the CIFRI and the IASRI are involved in the development of sampling methodology for inland fisheries, the Commission considers that these institutes should be properly equipped to develop an alternative methodology. The alternative approach should also consider the possibility of undertaking enquiries of fishermen households wherever there is a large concentration of fishing especially along major riverbanks.
4.16.10 The Commission recommends that:
(i) The survey design for estimating production of marine fisheries should be modified taking into account the current distribution of landing sites and the volume of catch at different sites. The field staff engaged in collection of data should be imparted regular training and their work should be adequately supervised.
(ii) The survey methodology for estimating production of inland fisheries especially with regard to running water sources (rivers and canals) should receive urgent attention and the Indian Agricultural Statistics Research Institute (IASRI) along with the Central Inland Fisheries Research Institute (CIFRI) should be provided with adequate support to develop this programme on a priority basis.
(iv) The discrepancies between the two sources of data namely, Livestock Census and State reports with regard to data on fishermen, fishing craft and gear should be reconciled by adoption of uniform concepts and definitions and review of these statistics at the district and State levels.
4.17.1 Reliable forestry statistics are required for planning, policy-making, analysis and decision-making on forestry investment and development programmes. These statistics are collected mainly as a by-product of administrative reports of the State Forest Departments. On the recommendation of the National Commission on Agriculture (1976), the Forest Survey of India (FSI) was created in 1981 with the objective of monitoring the forest resources at a macro level, storing and retrieving forestry related data, designing methodology for forest surveys, etc. Besides the FSI, the Indian Council of Forestry Research and Education (ICFRE) is mandated to collect, collate and compile primary and secondary data generated by the State Forest Departments and various Central ministries. The data on the forestry are obtained through a set of periodical reports (45 in number) furnished by the State Forest Departments and other concerned agencies. In addition to details of forest area, the reports provide information on forest products (wood and non-wood), forest land under cultivation, and grazing land, etc.
4.17.2 Since 1987, the FSI has begun using Remote Sensing (RS) technology to collect data on forest cover under three broad classes (dense forest, open forest and mangroves) on a country-wide scale through a biennial survey. The latest survey (October-December, 1998) used satellite data having a resolution of 23.5 metres with digital image processing. Introduction of digital interpretation has helped in reducing the time lag in the availability of the area estimates to just a few months after the completion of the survey.
4.17.3 The Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA) also publishes statistics of area under forests as part of Land Use Statistics according to the definition adopted in the nine-fold classification of land. This includes all land categorised as forests under any legal enactment dealing with the forests or administered as forests whether State or private owned, whether wooded or maintained as potential forest land.
4.17.4 The main drawback in the compilation of forestry statistics (as in the case of several other sectors) is the inordinate delay in the availability of data. Except the area under forest cover now being assessed by the biennial RS satellite survey, all the other published data have long time lags. The FSI faces the problem of delayed transmission of data by the States, which tend to accord low priority to the reporting work. Nearly half the States do not furnish the statistics in time, which delays the national compilation. The latest estimates of forest area based on Land Use Statistics pertain to 1996-97.
4.17.5 The present contribution of the forest sector to the GDP is considered as an underestimate as it does not take into account several important items such as head loads of fire wood, wood used for power generation, eco-tourism, etc.
4.17.6 There is a large discrepancy between the area under forest cover as published by FSI and by DESMOA mainly due to the differences in the concepts and definitions followed by two agencies (see Annexe 4.9).
4.17.7 Forest area statistics are generated through two sources, the FSI and DESMOA, each using different sets of concepts and definitions resulting thereby in a wide divergence between the two estimates. It is desirable to reconcile these differences to the extent possible, which can be attempted only at the micro level. It is necessary to have the FSI survey data at the village level for this purpose.
4.17.8 Early measures are required to cover all forest products in the State reports in order to improve the GDP estimates of the forest sectors. It is reported that a Working Group set up by the FSI is presently examining this question. It is expected that its recommendation, when implemented, will improve the estimates of the share of forestry and logging sectors in the GDP.
4.17.9 To obviate delay in the transmission and to reduce the time lag in the availability of forestry statistics, it is desirable to set up statistical units under the State Conservators of Forests to oversee collection and compilation of forest statistics and make use of latest tools of Information and Communication Technology for storage, retrieval and rapid transmission of data.
4.17.10 The Commission recommends that:
(ii) The State Forest Departments should be adequately supported by the establishment of appropriate statistical units to oversee the collection and compilation of forestry statistics from diverse sources on forest products including timber and non-timber forest products.
(iv) In view of the unavoidable nature of the divergence between statistics from the two sources – land records and State Forest Departments – because of different coverage and concepts, the two series should continue to exist; but the reasons for divergence should be clearly indicated to help data users in interpreting the forestry statistics.
(v) A Statistics Division in the Ministry of Environment and Forests with adequate statistical manpower should be created for rationalisation and development of proper database on forestry statistics.
4.18.1 The Directorate of Marketing and Inspection (DMI), Ministry of Agriculture has been conducting surveys on marketable surplus and post-harvest losses of food grains. The surveys provide information on marketable surplus ratios as well as on a variety of other important items like farm retention for family consumption, for seed, feed and wastage, etc. The present surveys collect information on these parameters using the methodology approved by a Technical Committee constituted for the purpose under the Chairmanship of the Agricultural Marketing Adviser to the Government of India. The surveys cover the following crops: Paddy, Wheat, Jowar, Bajra, Maize, Ragi, Barley, Red Gram, Gram, Green Gram, Black Gram and Lentil. The methodology used is that of multistage stratified random sampling and consists in selecting 20 per cent of the districts in a State, 15 villages in each selected district and 10 cultivator households from each selected village with a maximum of 100 districts, 1500 villages and 15,000 households.
4.18.2 The fieldwork of the surveys is conducted by Designated State Agencies through field investigators employed by them under the overall supervision of the Directorate of Marketing and Inspection. The data so collected are analysed with the support of IASRI and published. The information collected through these surveys is used in the National Accounts Statistics, and Ministry of Commerce and Industry in fixing the weights for certain agricultural commodities while compiling the all-India Index Number of Wholesale Prices in addition to its uses in planning and procurement operations and market development programmes.
Conclusions and Recommendations
4.18.3 The schedules used in the collection of information in the surveys are exhaustive, the methodology is robust, and the data collected do not appear to suffer from any serious deficiencies. However, the agencies designated for the purpose of collection of data are reported to face a number of difficulties due to inadequate manpower.
4.18.4 The Commission recommends that:
(i) The existing methodology in conducting the surveys on marketable surplus and post-harvest losses of food grains should continue in future surveys of this type.
(ii) The agencies designated for the collection of information on marketable surplus and post-harvest losses of food grains should be provided additional manpower, wherever necessary, for the conduct of these surveys.
4.19.1 The concept of market research survey in India dates back to 1935. It started with the establishment of the Office of Agricultural Marketing Adviser for investigation of the chain of operations from production through final distribution of crops, while establishing appropriate marketing standards. The market surveys are carried out by the marketing officers visiting the centres of concentrated production, as well as areas where production is relatively sparse. The information is collected by interviewing representatives of different groups of persons concerned in the production and distribution of the commodity affected, for example, producers, wholesalers, manufacturers, railway agents, etc. Each marketing officer is responsible for making sure that the sample interviews are representative of all the different groups of persons in the chain of distribution. With the setting up of a Market Research and Planning Cell (MRPC) in the Directorate of Marketing and Inspection, the importance of market research has increased. While the headquarters of MRPC looks after the guidelines, questionnaire and schedules in use and synopsis for the collection and compilation of the data, the field offices located at various State capitals and important centres carry out the field surveys. The collection of data is done by teams of qualified and experienced officers through well-planned schedules and guidelines provided for the survey. The collected data are analysed and a report on each crop is published for the benefit of various market users.
4.19.2 It is reported that the field investigators often find it difficult to collect primary data from the producers of agricultural commodities, as they do not maintain any records. As a result, the information collected depends to a large extent on individual assessment by the investigators. Even so, the survey reports provide valuable information to the planners and policy makers. Several institutions both at the Central and State level carry out market research work. As there is no standard agricultural marketing research methodology, it is difficult to have uniformity in the work. A lot of statistics go into the preparation of the reports, but the MRPC is not adequately equipped to analyse and make full use of the data collected. The Cell has not been properly supported by statistical resources.
4.19.3 Despite the difficulty of getting accurate information from the producers of agricultural commodities and certain subjective element is involved in the data collection, the system seems to work well. However, as several institutions carry out market research, there is a need to prescribe a standard methodology for the survey work. This can better be achieved through appropriate support of statistical personnel and adoption of statistical techniques combined with the latest Information Technology tools.
4.19.4 The Commission, therefore, recommends that:
(i) The Directorate of Marketing and Inspection (DMI) should establish a Statistical Cell either independently or within Market Research and Planning Cell (MRPC) with sufficiently trained statistical personnel to undertake comprehensive analysis of survey data and aid the decision-making process.
(ii) The Statistical Cell of Directorate of Marketing and Inspection (DMI) should identify the problems and deficiencies in the market research surveys carried out by different institutions and develop a standard methodology for uniform adoption.
4.20.1 Index Numbers in Agriculture are required in order to study the trends over time in respect of area, yield, production, productivity, prices, etc. and for studying the comparative picture of the performance of agricultural sector vis-à-vis other sectors. The index numbers are constructed after making due allowance for changes in the coverage and methods of estimation as the absolute figures of area, yield, production, etc. are known to be unsuitable for a study of trends over time. The index numbers constructed by the Ministry of Agriculture can be grouped into two broad categories: (a) Index Numbers of Area, Production and Yield, and (b) Index Numbers of Terms of Trade between Agricultural and Non-agricultural Sectors.
4.20.2 The Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA) constructs the index number of area, index number of production and index number of yield separately for each State covering 46 crops. The crops are classified into two main groups and eight sub-groups as listed below:
Rice, Wheat, Jowar, Bajra, Maize, Ragi, Barley and Small Millets. (Crops except Rice and Wheat constitute the sub-group coarse cereals.)
Gram, Tur and other pulses.
Groundnut, Sesamum, Rapeseed and Mustard, Linseed, Castorseed, Safflower, Nigerseed, Soyabean, Sunflower, Coconut and Cottonseed. (The oilseed crops except Coconut and Cottonseed constitute 9 oilseeds.)
Cotton, Jute, Mesta and Sannhemp (Jute and Mesta constitute a sub-group.)
Tea, Coffee and Rubber.
Condiments and Spices
Pepper, Ginger, Garlic, Chillies, Turmeric, Arecanut, Coriander, and Cardamom.
Fruits and Vegetables
Potato, Onion, Banana, Cashewnut, Tapioca and Sweet Potato.
Sugarcane, Tobacco and Guarseed
Besides the State index numbers, the DESMOA also constructs the national level indices. The base year for the present series of “Index of Area, Production and Yield in Agriculture” is the triennium ending 1993-94 so as to be in harmony with the other series of indices such as Index of Industrial Production, Wholesale Price Index and other series of National Accounts Statistics. In order to smoothen the fluctuations of area and production from one year to another, the average of area and production over the triennium is taken for determining the base level area and production. The weight of a commodity for the production index is taken as the average production of the commodity in the triennium ending 1993-94 and the national average price of the commodity during 1993-94 as obtained from National Accounts Statistics. This has been done to fix the base production at its average level by eliminating the cyclical variation and to evaluate the production with a same price for all States in view of the wide variations observed in the State prices. The index number of area for a specified year for an individual crop is the percentage of current year area of the crop with respect to the base year area of the crop. The index of production is also calculated in the same manner taking the production figures instead of the area figures whereas the index number of yield for the specified crop is calculated as the percentage of the index number of production with respect to that of area. Though these indices are calculated for each State separately, the all-India indices are calculated independent of the State indices. The methodology adopted for the calculation is given at Annexe 4.10.
4.20.3 With a view to comparing the prices of exports of Agricultural Sector with prices of imports from non-Agricultural Sector, the Ministry of Agriculture constructs the index numbers of terms of trade (ITT) between the agricultural and non-agricultural sectors. It measures the relative change in the prices received by the farmers for produce sold by them in relation to a change in the prices paid by them for the commodities purchased for final and intermediate consumption as well as capital formation. While a value of ITT greater than 100 indicates favourable terms of trade for Agricultural Sector, less than 100 indicates adverse terms of trade. These indices are available from 1981-82 onwards. The base period for constructing the current series of ITT is the triennium ending 1990-91. The methodology used for the construction of ITT is the ratio of Index of Prices Received (IPR) to the Index of Prices Paid (IPP) by the Agricultural Sector expressed as a percentage.
4.20.4 The Index of Prices Received (IPR) covers 39 important crops and commodities at all-India level produced in the Agricultural Sector and nine livestock products. The percentage of the marketed value of each commodity with respect to the total value of marketed surplus for all the commodities is used as weights for the construction of the index.
4.20.5 The Index of Prices Paid (IPP) by the Agricultural Sector depend on the items and commodities and their quantities, which the Agricultural Sector purchases from the non-agricultural sector for the purposes of final consumption, intermediate consumption and capital formation together with their prices. Accordingly, three indices namely, IPP for final consumption (IPP-FC), IPP for final intermediate consumption (IPP-IC) and IPP for capital formation (IPP-CP) are separately calculated. The combined IPP is based on a weighted average of the three component indices with percentage weights 73.54, 21.63 and 4.83 respectively.
4.20.6 The index of terms of trade between Agricultural and non-Agricultural Sector is worked out as the percentage of index of prices received by the farmers with respect to the index of prices paid for final consumption, farm inputs and capital investment. The index numbers of the terms of trade between Agricultural and non-Agricultural Sectors with bifurcations of the index numbers of prices paid and those received for the years from 1981-82 to 1997-98 are given in Annexe 4.11. These indices are used in the formulation of price policies for agricultural commodities, monitoring the changes in the economy of the Agricultural Sector in relation to the rest of the economy.
4.20.7 The index number of area, production and yield that are available for every State are constructed covering all the crops. As all the crops may not be important in all the States, the State Indices are likely to give a wrong picture. The index of terms of trade has been observed to serve the purpose for which it is meant. There appears to be no deficiency in the process of developing the series. While it is a welcoming feature that the Ministry of Agriculture has been constructing the State Indices besides the all-India series of Index Numbers of Area, Production and Yield, it is necessary that the State Indices should give a correct picture of the State with reference to specific parameters. This would be possible if crops grown with reference to a specific State only are included in the construction of the State Indices with appropriate weights.
4.20.8 The Commission, therefore, recommends that:
(i) A review of the item basket for the construction of Index Numbers of Area, Production and Yield should be undertaken immediately.
(ii) The item basket for the construction of Index Numbers of Area, Production and Yield should be different for different States.
(iii) The present arrangements for the construction and release of Index of Terms of Trade should continue.
4.21.1 The practice of sowing crops in mixture in the same field is prevalent in almost all parts of the country. Cultivators usually mix crops that cannot stand a particular type of weather with another set of crops that resist and thrive under the same conditions. The methods employed for sowing such crops vary not only from State to State but also from area to area within the same State. The crops in the mixture are sown either individually in separate rows or are mixed together. In the former case, the seeds of the constituent crop are kept separate and a certain number of rows of one crop alternate with those of some other. In the latter case, the seeds of two or more crops are mixed together before sowing and the mixed seeds are either line-sown or broadcast.
4.21.2 The procedures followed for apportioning the net area under the constituent crops vary from State to State. The different procedures followed in the States are listed in Annexe 4.12. The major land records States of the country can be divided into the following three categories according to the manner of treatment of areas under crops grown in mixtures:
(a) States where allocation of the area to the constituent crops grown in mixture is done at the field level such as Andhra Pradesh, Assam, Bihar, Gujarat, Himachal Pradesh (except Kangra District), Karnataka, Maharashtra and Tamil Nadu.
(b) States where some major crop mixtures have been identified and the area at the field level of these recognised mixtures is recorded as such for the mixtures and allocation to the component crops done at higher levels on the basis of fixed ratios. For unrecognised mixtures, the allocation of areas to the components is done at the field level. The States following this procedure are Haryana, Kangra District of Himachal Pradesh, Jammu and Kashmir, Punjab and Rajasthan.
(c) States where some major mixtures have been identified and the area at field level of these mixtures is recorded as such, the allocation to the constituent crops being done at subsequent levels following fixed ratios. But for unrecognised mixtures, the entire area is recorded against the major crop or the recognised crop mixtures and the minor constituents are ignored. Madhya Pradesh and Uttar Pradesh follow this procedure.
4.21.3 Though many States have recognised crop mixtures on the basis of the cropping pattern followed, several others do not have such recognised crop mixtures. The allocation of area under constituent crops in respect of recognised mixtures is generally made using fixed ratios and rates. The same allocations have continued for several decades and they may not conform to the current cultivation practices. In the case of non-recognised mixtures, the area allocation is generally done at the field level using eye appraisal, which brings inaccuracies in the recording of crop area. It has also been observed that in some States, certain minor crops are mixed with major crop mixtures and the minor constituents are ignored while recording the area. For example, in Uttar Pradesh, for a mixture like ‘wheat, barley, and linseed’, the entire area is recorded as ‘wheat and barley’ (ignoring the linseed).
4.21.4 It is seen that the recognised crop mixtures and the procedures adopted for apportioning the net area under constituent crops of the crop mixtures have remained unaltered over a long period of time. These may no longer conform to the current cultivation practices. A review of the crop mixtures and the ratios of apportioning should be made by the Ministry of Agriculture using the data available from surveys like the ICS in order to arrive at realistic crop mixtures and ratios.
4.21.5 The Commission, therefore, recommends that:
(i) The rates used to apportion the areas of constituent crops of major crop mixtures should be fixed for the recognised mixtures at sub-district and district levels and updated periodically.
(ii) Data available from surveys conducted under schemes like Improvement of Crop Statistics (ICS) over the years should be used for deciding the crop mixtures and their ratios.
4.22.1 For a comprehensive appraisal of the agricultural economy, information on inputs such as fertiliser, pesticides, agricultural credit, multiple cropping, inventory of agricultural machinery and implements, mechanism of plant protection, quarantine and storage, etc. are of as much importance as the data on production. The input surveys conducted as a part of quinquennial Agricultural Census are an important source for such data. However, the latest available data pertain to the Input Survey 1991-92. More recent information on production, distribution and stocks held of fertilisers is available from the Fertiliser Association of India (FAI), but it does not provide details of actual consumption.
4.22.2 The Agricultural Implements and Machinery Division of the Department of Agriculture has been compiling and maintaining statistics relating to production and sale of tractors and power tillers from Tractors Manufacturing Association and Manufacturers of Tractors and Power Tillers.
4.22.3 Plant protection, quarantine and storage is another area where though data are collected, they are not compiled and maintained as an organised database. The Directorate of Plant Protection, Quarantine and Storage (PPQ&S) in the Ministry of Agriculture is the apex organisation in India for promoting plant protection. The Directorate advises and assists the Union Government on all matters relating to plant protection including international obligations, besides assisting the State Governments in their plant protection activities. Large amount of data are collected through Rapid Roving Surveys under the Pest Surveillance and Monitoring. In these surveys, the Surveillance Teams of the different Central Integrated Pest Management Centres move through intensive crop belts on predetermined routes at regular intervals, stop at regular distances and collect information on weather, crop stage and status, and pest and disease situation in the fields on both sides of the road. The Locust Warning Organisation of the Directorate entrusted with the task of monitoring and controlling locusts over an area of 2 lakh square kilometres in the desert areas across Rajasthan, Gujarat and Haryana collects information on locust development and movement together with related aspects. This information is Centrally collated and a fortnightly locust situation bulletin is brought out and circulated to various organisations including the Food and Agricultural Organisation (FAO). In addition, data are collected on several other parameters relating to the plant protection and quarantine, by the Directorate of Plant Protection, Quarantine and Storage.
4.22.4 Data on inputs to agriculture are also being collected through Crop Estimation Surveys, as well as the sample check on Crop Cutting Experiments under the scheme for Improvement of Crop Statistics.
4.22.5 Though some data on fertilisers are available from the input survey and from publications of the Fertiliser Association of India, they are incomplete and not available in time.
4.22.6 The collection and compilation of data with reference to agricultural implements and machinery is limited to tractors and power tillers and that too depends only on the data supplied by the manufacturers. The information is very often not complete and there is no scientific mechanism for collecting statistics in this area. Data on farm practices and farm management are not available, though these are very much required for an understanding of the farm practices.
4.22.7 Though a lot of statistics on plant protection, quarantine and storage flow into the headquarters of the Directorate of PPQ&S, they are not being fully compiled. The data have also not been organised for effective long-term use. The Directorate does not have enough statistical support and the existing ‘statistics and computer unit’ with only one Deputy Director and a Data Processing Assistant is not adequate.
4.22.8 The Commission recommends that:
(i) The Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA) should collect, compile and maintain a complete database on State-wise production, sale of tractors, power tillers, harvesters and other agricultural implements, density of such implements per hectare, investment made, level of mechanisation, adoption of water saving devices, etc.
(ii) A Farm Management Survey on an all-India basis should be conducted on a regular basis preferably at an interval of five years.
(iii) The Directorate of Plant Protection, Quarantine and Storage (PPQ&S) being the apex body for plant protection should act as a depository of information on plant protection. Efforts should be made to design, develop and maintain a comprehensive database on plant protection for effective long-term uses.
(iv) The Statistics and Computer Unit of the Directorate of Plant Protection Quarantine and Storage (PPQ&S) should be strengthened both in terms of statistical and computer personnel as well as computer equipment.
(v) Information collected through General Crop Estimation Surveys (GCES) and the scheme for Improvement of Crop Statistics (ICS) should be compiled to generate estimates on various inputs such as fertilisers, pesticides, multiple cropping, etc.