Thursday, 28 August 2008



Agriculture and allied sectors are the most crucial sectors of the Kerala Economy as they provide livelihood to approximately two-third of the population and contribute a fourth of the SDP. The rich and varied biophysical resources of the State are exploited by this sector for the production of a wide range of agricultural products including spices and plantation crops and this sector accounts for bulk of the export earnings of the state. Moreover extensive infrastructure and support services including generation and transfer of technology, input supply, credit, processing, marketing, storage and irrigation have been created to provide the much need backward and foreward linkages. Obviously planning and policy making for these sectors necessitate extensive database for formulation of appropriate strategies within a comprehensive framework. The objective of the present paper is to appraise the adequacy and suitability of the present database in agriculture and allied section to serve the needs of planning and policy purposes in the dynamic contact of gloablization and to identify critical gaps in the database.

Need for a Database

It is imperative to have a comprehensive and scientific database for the purpose of sectoral planning, policy formulation, programme and project planning, implementation monitoring and evaluation, support system planning and for assisting the PRIs to take up decentralized planning and development. It also assumes great significance in the context of globalization with special reference to the trade in agriculture under the WTO regime. The following specific needs are identified.

For Sectoral Planning and Policy Formulation

1.Planning policy changes on export - import (foreign trade) price support subsidies, infrastructure and other market intervention policies.

2.Planning provision of other support services like credit, marketing, technological support, value addition, storage, transport etc.

3.Policy planning in respect of the use of bio-physical resources, like land and water, land use and cropping pattern, bio-diversity, environmental protection etc.

4.Issues relating to land reforms, labour supply, agricultural wages, terms of trade etc.

Programme Planning and Implementation

1.Planning and implementing programme to enhance production and productivity of different segments in agriculture and allied sectors.

2.Planning location specific development programmes under decentralized planning and for developing location specific technology.

3.Operationalising price support, price stabilization procurement, storage and marketing of agricultural products.

4.Monitoring and evaluation of different agricultural development programme.

5.Database to evaluate the input of major development programmes like irrigation, HYVs, marketing etc. on production, productivity and income.
User-oriented and demand driven data on market dynamics

1.Data on domestic and foreign trade of important agricultural products for the State.

2.Data on sanitary and phytosanitary standards.

3.Market Intelligence Data

Features of the Existing Database.

The main features of the existing database are

1.a commodity approach in data collection and management in contrast to the widely adopted system of multiple cropping systems in the state;

2.focus on institutional, programme and scheme-oriented database rather than on functional and behavioural performance aspects; and

3.the involvement of multiple agencies in data collection and compilation resulted in non-comparability of data due to differences in the methods, reference periods and coverage. The important agencies involved in collection and compilation of data are the following:

Commodity Boards (Coconut, Spices, Coffee Rubber and Tea

Department of Economics and Statistics

Departments of Agriculture, Animal Husbandry, Dairy Development, Forestry, Soil Survey, Irrigation, Ground Water, Meteorology, Farm Information Bureau, Land Use Board etc.

Cost of cultivation scheme

Agricultural Prices Board

The level of disaggregation of most of the data is at the district level. For certain aspects only state level pooled data are available. Lack of disaggregated data is the major constraint faced by local self-governments in preparing and implementing plans at the Panchayat and Block levels.

Although a lot of useful data is thrown up by individual research as well as through research projects, these are seldom related to the database. The quick compilation of certain date by the panchayats revealed that existing date base is weak and is beset with in accuracies.
There is thus a lack of data base management policy and programme, which could co-ordinate the efforts of different agencies, which collect and compile data in isolation depending on their perception, requirement, infrastructure and administrative convenience. Unfortunately there is not only duplication of efforts but also of these data-unsuitable for planning and policy purposes.


It needs to be noted that date base of the agricultural and allied sectors is most comprehensive compared other sectors of the economy. A lot of useful data is compiled and published by the efforts of a number of agencies and departments, which include data on area, production and productivity of individual crops, area covered by HYVs, details of area irrigated and sources of irrigation, fertiliser consumption schemes of agricultural development, area under forests and forest plantations, production of livestock, poultry and eggs, milk production, procurement sale etc. However critical gaps are seen to exist in a wide range of statistics. The limitations of the existing data are thus examined in terms of coverage, adequacy, usefulness for planning and policy making and information gaps including absence of disaggregated data in critical areas. Some of the most important limitations are briefly examined in the following paragraphs.

Optimising the use of Bio-physical Resources

Although a lot of data on different aspects of bio-physical resources are compiled and published, they are not fully adequate for the purposes of land use planning, cropping system planning and for optimisation of the use of land and water resources. The data on bio-diversity is also imperfect and inadequate to make any real use in planning and policy making. Data on irrigation, land use, soil capabilities are not available in the required form and at the desired level of disaggregation. Even the land use statistics is not uniformly available for all panchayats and local bodies. In the absence of reliable database on soil types, nutrient characteristics, soil capability at disaggregated levels, planning of agricultural development at panchayat levels has become an unscientific effort.

Contribution of Sub-sectors

The changing profile of agricultural development in terms of the relative contribution of major crops and sub-sectors in SDP cannot be captured from the existing data. While the overall decline in the share of agriculture in SDP is clearly shown by the data, the relative changes in the shares of major crops or segments is not reflected in the SDP statistics. This is a very crucial information for not only planning the support services for the fast growing sectors, but also to make efforts to minimise any possible unfavourable impact on the segments, which show declining trends.
Even the production data for certain perennial crops especially spices are far from satisfactory. There are complaints about unreliable estimates of the area and production of pepper in Kerala. The production figures quoted by trade circles are far different from the official estimates. This used to result in un-expected fluctuations in the price into forecasting and failure to anticipate the total supply more or less accurately.

Farming System-related Problems

The commodity based approach in collection and compilation of data employs the "accounting" area concept based on specific norms of crop density in each district. However except for rice, tea and cardamom and to a large extent rubber, the commodity approach is not relevant in farming. Ion the context of multiple cropping systems prevalent in the state, the objective of the farmer is to optimise the income from the farm and not from a single crop. Hence the commodity-based data are unsuitable for judging the productive (or economic?) efficiency of different farming systems. Moreover, the degree of crop diversification under different farming systems is an essential component of the risk management strategies of the farmers having different farm sizes. This aspect also cannot be captured from the present date base.
Even the impact of fall in the price of one or few crops on the total farm income cannot be assessed by the conventional methods in the context of multiple cropping systems. The farmer is more concerned with the overall farm income rather than income from a single crop. The impact will be different on different cropping systems. The multiple cropping had enabled the farms in the state to generate highest agriculture income per hectare (Rs.32000) compared to the most agriculturally advanced state of Punjab (Rs.22000).

Another consequence is to pool all cultivators and to treat them as a "homogenous category" disregarding their principal source of income and the nature of their stake in agriculture. While 85 per cent of the farms are owned and operate d by persons who derive principal source of income from outside the agricultural sector, the conventional methods of agricultural extension and transfer of technology becomes irrelevant. They are further segmented under different farming systems and sub-systems. In the absence of more elaborate information on these aspects, the transfer of technology appropriate to the farm conditions as well as support services needed for small farms cannot be planned. Even the crop specific package of practices has to be appropriately modified. All these require information on the average number of coconut palms, pepper vines etc. per small and marginal holdings, which can reflect the built in problems confronted by different types of farming systems.

Impact of HYVs and Hybrids

The improved technologies have contributed to faster growth in production and productivity in all major crops. But the present database is inadequate to assess the relative contribution of these improved varieties on production and productivity in respect of most of the crops except rice. No separate break-up is available on the area under improved varieties and their productivity in contrast to traditional varieties.
Even in rice where area under HYVs is reported, HYVs are treated as a generic group although dozens of varieties are cultivated in different locations. But the data fails to provide answers to the following questions:

Which varieties are widely accepted and in which areas they are adopted ?.

Why are they accepted or adoption ?.

What is the average yield realized in contrast to their genetic potential ?.

Which of the varieties are relatively diseases free.
But these types of information are very crucial for monitoring development of new varieties with desired attributes and for developing appropriate strategies for reducing the yield gap. There could also be price and quality differences, which also need to be examined. If a particular variety of certain crop like ginger, turmeric, cardamom or pepper is seen to have "geographical indications" or specific quality attributes, these need to be farther explored for getting premium price and rich export market to the farmers. These assume greater importance in the context of globalized trade under WTO regime.

These issues are equally relevant in animal husbandry and dairy development also. They are also relevant for medicinal herbs, minor forest products, floriculture and other related areas.

Labour Productivity and Real Wage Cost

The statistics on agricultural labour fails to provide information on changing profile of labour absorption (crop-wise, gender-wise and task-wise) in seasonal, annual and perennial crops. There are widely debated issues relating to agricultural labour which cannot be ensured with the help of available data. Some of the most important issues are (1) What is the evidence for declining labour response to rice cultivation in Kerala especially for weeding, harvesting and threshing (2) Has technology upgradation resulted in displacement of female labour by male labour in areas such as weeding, harvesting and threshing (3) Has there been significant gender bias especially against women in farm mechanisation and technological upgradations. (4) What is the truth in the reported decline in labour productivity in agriculture especially in seasonal and annual crops? (5) Is there a declining trend in the response of farmwomen to seasonal agricultural operations? (6) Which are the areas in which labour substitutions and labour displacements are taking place? The All India Labour Enquiry Surveys and the Agricultural Labour Enquiry Survey in Kerala had earlier provided useful data on the pattern of employment, number of days employment and wage rates. But in the absence of recent rounds the trends are not known..

Impact of changes in the Cropping Pattern

There has been a significant change in the cropping pattern at the micro level which might have caused notable changes in income and employment levels of small and marginal farmers as well as the agricultural labour especially the women. But this cannot be seen from secondary data. Moreover, impact of such changes at the average farm levels also cannot be seen from available data.

One very perceptible change in the agricultural sector has been the observed trend of increasing conversion of paddy land for other purposes. Although its impact is likely to be pervasive, practically little information is available on its impact and the nature of conversion. It is only marginally reflected in the decline in the area under rice. Other issues like how much land is converted? For which crops or for what purposes they are used? Are unanswered. Although the area under current fallow has been increasing, it cannot be related to reduction in paddy land and land conversion.

It is widely argued that there has been decline in soil fertility and degradation of crop lands especially low lands due to unscientific water management and irrational application of chemical fertilizers and neglect of soil conservation. This is a serious issue which cannot be addressed with the present database.

Impact of promotional efforts cannot be assessed

Although a wide range of support services are provided for promoting agriculture, the present database is inadequate to make assessment of the impact of programmes such as irrigation, distribution of planting materials, credit, fertilizer distribution, etc. The indicators of agricultural development published by the Department and the Planning Board are too general like fertilizer consumption per hectare, total planting Board are too general like fertilizer consumption per hectare, total planting materials distributed (irrespective of crops and varieties) which cannot be effectively used for examining the linkage between support services and productivity with the existing data. Moreover data on input supplies are not crop specific.

Here also the quality of data is very poor. For instance, the following problems are observed in the case of data on irrigation.

The irrigation data fails to show the actual area irrigated season wise as it is primarily based on irrigation potential created rather than on actual irrigation.

Since good part of the water from major irrigation projects is used for drinking purposes, the irrigation data reported seems to be an over estimate.

The unscientific water management practices and the lack of maintenance of canal systems result in tremendous wastage of water which reduces the area irrigated substantially.

Consumption Data

For most of the crops, reliable estimates of domestic requirement and consumption are not available. For instance no break up on domestic consumption within the state, outside the state, industrial/processing sectors' use and exports are available for some of the commercially important crops. Database is fairly good for those commodities covered by Commodity Boards.

There is also lack of information about the quality standards of the product. The uses of different segments are usually linked with specific qualities, but very seldom the break up is available.

Processing, Storage and Marketing
The present database lacks information on storage and warehousing facilities as well as on processing and value addition in respect of agricultural products. The scattered data is not adequate to make any commitments on procurement and storage of a product like copra, paddy or pepper. In spite of the increased thrust given for agri-processing by the Centre, absence of database has been a major constraint in the way of planning for processing and value addition of different agricultural products.

Gap in Trade Statistics

Besides, there is a virtual absence of market information. The biggest constraint in designing appropriate strategies for facing the challenges of the WTO regime is the lack of reliable data on international trade, prices, import duties, export opportunities, sanitary and phytosanitary requirements, quality standards, technical barriers to trade etc. A dynamic database to take advantage of the emerging opportunities and threats in international trades is a very urgent necessity.

A closely related issue is the inadequacies in the price statistics for crops not covered by the commodity Boards. The seasonal variations and the linkage with the market arrivals are incomplete in many respects.

Consumption Data on Meat, Milk and Egg

The supply gap for these products are estimated on the basis of the normative levels of consumption recommended by ICMR or Nutrition Monitoring Bureau and not based on the actual levels of demand. These could naturally be overestimates in many respects. However a lot of data on the consumption pattern for these products are available from N.S.S. rounds, which show the shifting food preference from cereals to milk, eggs, fish and meat. These data are not incorporated while examining the projected scenario in cattle and poultry development.

The livestock statistics thrown up by the Quinquennial Livestock Census is fairly comprehensive. But good part of it is not linked with the published statistics. However the level of disagregation is not satisfactory for local level planning.
Forest Data

The degree of imperfection seems to be greater in the case of forestry statistics. Even though the geographical coverage of forests is around 8 per cent only, it is still reported to be around 23 per cent. This is probably based on the legal status of forest lands which has nothing do with actual forest cover. The extensive loss of forest cover, progressive depletion of forest resources, and continuing trend of degradation of forest lands are not at all reflected in the forest statistics. Therefore it can seldom be used for planning and policy making. Even the classification of forests according to ever green, semi-ever green and forest plantations is incorrect. This is also true of the estimates of the outturn of minor and major forest products, which are affected by pilferage and extensive un-authorized utilization. The qualitative deterioration of the forest ecosystem cannot be linked with the available database.


The foregoing analysis was an attempt to highlight some of the important limitations of the existing database and to identify certain critical areas of data gap. The analysis is only tentative and suggestive. There are other areas of inadequacies, which also should receive urgent attention. But it needs to be remembered that the specific requirements of data are related to their end uses in planning, programming, monitoring, evaluation and policymaking. We need to have a clear statement of objectives for data base development and management. The data collections by different Departments are to be coordinated to satisfy the basic objectives mentioned above. The gaps already identified need to be filled and the consistency between different sources is to be ensured.

Above all, it is necessary to have Panchayat level disaggregated data to enable the Panchayats to attempt scientific process of planning at the grass root level.


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