Theme 5: Statistical and Economic Issues for Prosperity of Rural Community. T5.1I Statistical Evaluation of Social Development at District Level

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1 Theme 5: Statistical and Economic Issues for Prosperity of Rural Community T5.1I Statistical Evaluation of Social Development at District Level P. Narain 1, S.D. Sharma 2, S.C. Rai 1, and V.K. Bhatia 2 1 Indian Society of Agricultural Statistics, New Delhi 2 Indian Agricultural Statistics Research Institute,, New Delhi Development programmes have been undertaken in the country through Five Year Plans to enhance the quality of life of the people by providing them the basic necessities as well as bringing about effective improvement in their social and economic well being. Commendable progress has been made in the agricultural as well as industrial sectors, the current economic growth being about 8 to 9 % of the GDP but there is no indication that it has reduced substantially the level of regional disparities in terms of socio-economic development. To address this issue one has to evolve a method to measure the extent of this disparity and apply it to data on indicators of the development. This is basically a statistical problem. While development is a multi-dimensional process, continuous in nature, we are accustomed to measure it in terms of a single indicator such as for instance the per capita income of a given area. This however does not capture the total picture of the development as other related indicators of development such as for instance the health status in the area may go in a different direction. Some sort of their aggregation in the form of an overall index is thus inevitable. There are various methods to do so. In the construction of the much talked about human development index of the United Nations, the method involves combining 3 indicators viz. life expectancy at birth, education and per capita GDP by taking their simple average after calculating the individual component index as a ratio. It does not take into account the variability in the indicator values. Here we adopt a method based on optimum combination of the indicators that is independent of their units of measurement, takes into account their variability and looks meaningful of the particular economic situation. This can be done by considering data on a number of indicators across a number of area units. Each datum is first transformed into a standardized value with zero mean and unit standard deviation by using mean and standard deviation of a given indicator over the area units. The deviation of each such value from the best value of the indicator across area units (either the maximum or the minimum value depending upon the direction of the impact of the indicator on the level of development) is squared and divided by the coefficient of variation of that indicator. The resultant value is summed over all the indicators for a given area unit, say i-th, its square-root taken and denoted by C i. The composite index of development for this area (DI i ) is then C i /C where C = (mean of C i ) + 3 (standard deviation of C i ). The value of the index varies between 0 and 1, a smaller value indicating high level of development while a higher value indicating low level of development. Based on this method, the Indian Society of Agricultural Statistics conducted a series of investigations to estimate the level of socio-economic development first for the different states in the country and then for different districts in the 10 states of Orissa, Andhra Pradesh, Kerala, Uttar Pradesh, Maharashtra, Karnataka, Tamil Nadu, Madhya Pradesh, Assam and Jammu & Kashmir (Narain et al., 1991, 1992, 1994, 1995, 1996, 1997, 2000, 2002, 2003, 2005). In the present paper, the results are reviewed for 282 districts of these states for the period 1991 to The results for the study conducted earlier involving all the states showed that the state of Punjab ranked the first with an index value of 0.37 whereas the state of Bihar ranked the last

2 with an index value of However, not all the districts of an under developed state were under developed; some of the districts were better developed. District-wise analyses in subsequent studies were therefore found to be more meaningful for assessing regional disparities. In the present study, the development indicators common to all the districts in a state were taken and involved variables in respect of agricultural, industrial, infrastructural, education, health, population and per capita GDP. The indices were calculated separately for the agricultural, industrial, and infrastructural sectors as well as for the overall socio-economic development, the number of indicators varying between 29 and 48 and the number of districts per state varying between 14 and 63. The composite index of development across 282 districts in the 10 states ranged between 0.44 and The agricultural development index as well as infrastructural development index were found to be positively associated with the socio-economic development index in almost all the states. At the aggregate level, the correlation coefficient between agricultural development and socio-economic development was found to be 0.67 and significant at 1% level. The districts falling in different stages of development such as high level, middle level and low level were identified for all the states. About 16% of districts for socio-economic development but about 33% for agricultural development were found to be better developed in comparison to other districts. The corresponding percentages for low level developed districts were found to be 25 and 14 respectively. For enhancing the development of low level districts, model districts were identified and potential targets for important development indicators were estimated. For this purpose, development distances between pairs of districts based on standardized values were first worked out and expressed as a distance matrix. Model districts with respect to a given low developed district, say A, are taken as those districts whose index is less than that of A and whose developmental distance from A is less than or equal to a critical distance based on the minimum distances for each row of the matrix. The best value for each developmental indicator of the model districts is the potential target for A. For instance, in the state of Andhra Pradesh, the districts of Guntur, Nellor, Chittoor and Nizamabad were found to be the model districts for most of the low developed districts that mostly belonged to Telangana region of the state. Development indicators like productivity of crops, population growth, credit facilities, transport system and literacy rate required improvement in the low developed districts. Similar results were found in the other states also. The study indicates that it would be useful to further narrow down the unit area from district to tesil or block level for making location specific recommendations as entire parts of the low level developed district were not low developed but some parts were also better developed. In conclusion, the study points out the desirability of conducting statistical evaluation of socio-economic development at the district level for all the districts of the country by determining development indices in the manner described herein on a continuing and regular basis. This needs to be urgently taken up by an agency of the Government of India so that appropriate development measures could be taken up in low level developed districts (identified in the manner described above) in respect of the development indicators found to be very poor. Such a programme, on a sustainable basis, is expected to go a long way in eradicating rural poverty in the country by 2015 or before as set out in the Millennium Development Goal (MDG). T5.2I Production and Utilization Pattern of the Major Agricultural Commodities in India: Role of Statistics in Its Rationalization

3 Nawab Ali Indian Council of Agricultural Research, Krishi Anusandhan Bhavan-2, New Delhi Agriculture traps and converts solar energy into chemical energy in the form of harvested biomass such as grains, roots, fruits, fibre, flesh, milk, etc. and these harvested biomass are processed and transformed into various edible products to derive nutrition and sustain life. Since food is the basic form of energy needed by human beings, its production through agriculture has been and continue to be, the most important human occupation on the planet earth to sustain life and the civilization. Agriculture is a rural based occupation and provides food essential for human survival and has contributed significantly in evolving various cultures/civilizations all over the world. India is predominantly an agricultural economy and 65-70% of the population live in villages and earn their livelihood through agriculture. It has traditional wisdom, knowledge, skill and crafts to practice agriculture. As of now India produces about 750 million tones of raw food materials of plant and animal origin. Raw food and feed commodities of plant and animal origin are processed into various value added products for human and animal consumptions to derive nutrients needed for growth, development and maintenance. During processing, there are positive as well as negative changes in nutritional value and quality of the end products. These need to be documented and nutritional profile of the end products should be known to consumers for an effective diet planning to keep better health and happiness. Each agricultural commodity, after harvesting, moves towards consumption and in the process get subjected to a number of operations, such as cleaning and grading; drying and storage; processing and value addition; packaging and transportation; stocking and marketing; preparation and utilization; metabolism and activity. There is a need to have data on as to what happens to the commodity from production to consumption value chain. Data such collected are to be analyzed and recommendations made as to what is the best value-chain for a particular commodity in terms of delivery and absorption of nutrients/comfort to the consumer and at what cost, energy and environmental safety. The statistics about production and utilization pattern of the major agricultural commodities such as cereals, pulses, oilseeds, F&V and dairy products may help in planning as to how these commodities could be best utilized in respect of nutrition delivery and economic gains. T5.3I Post-Harvest Management of Livestock, Poultry and Fish Based Products S.M. Ilyas Narendra Dev University of Agriculture & Technology, Kumarganj, Faizabad Besides globally applauded achievement in food grain production through "Green Revolution", the gains in the production and productivity of milk, meat, poultry (meat and egg) and fish are no less impressive. Due to fragmentation of holdings, the livestock husbandry is playing a saviour's role especially for small and marginal farmers. India is already largest producer of milk in the world and is forging ahead in meat, egg and fish production. The share of livestock is estimated to be about 36 per cent of total agri- sector and 9.33 per cent of GDP. With increasing income of the households, the demand of these produce is on rise and is likely to go up further and this is where lies the opportunity. While the production scenario is gratifying, the post production scenario is nothing to feel happy

4 about. The losses of these highly perishable produce are quite high. Losses start occurring right from production/catch and go on accumulating during handling, transport and storage stages. The post-harvest losses reduce the profit of farmers/producers on one hand and availability of quality produce to consumers on the other. To aggravate the already difficult situation, the awareness about quality and safety is minimal if not absent altogether. Growing urbanization, excessive use of pesticides (which enter into feed chain), lack of knowledge about safety have led to lengthening of food chain and potential to higher food borne hazards. The post-harvest management of these highly perishable commodities of animal, bird and fish origin is constrained by poor infrastructure, lack of awareness about quality and safety aspects and also poor dissemination of developed technologies. Further, the lack of investment and low risk taking capacity of the producers are also responsible for none too flattering scenario. The huge post harvest losses running into several millions of rupees are only expected but need to be brought down. The traditional methods of animal slaughter are totally unhygienic causing much pollution and other problems. Not only the unhygienic production and unsafe handling, transport and storage cause economic losses but these also impact negatively on beneficial utilization of various by-products like skin, blood, hair, viscera and bones. The hoof oil is very valuable and is used in lubrication of aircraft parts. Such examples are many. Similarly, the scenario in fish production is none too happier. Although a huge export earner, the handling, transport and processing need immediate intervention. The boost in processing and value addition of milk, meat, egg and fish will not only provide additional income but also generate opportunities for employment in production catchments. With modern approach and strict compliance of quality and safety standards, adequate infrastructure including financial support, capable human resource, appropriate processing and value addition and good market support, not only the Indian consumer will be benefited but will give much needed boost to export. T5.4I Food Security in Underprivileged Regions of India P.K. Joshi and Sant Kumar National Centre for Agricultural Economics and Policy Research, New Delhi Food security is regarded as access to enough food by all people at all times for a healthy life. Food security at the household level is yet to be realized despite near self-sufficiency in foodgrain production in India. Household food security is worse-off of people living in tribal, backward and hilly areas, known as underprivileged regions. A study was conducted in underprivileged areas to document the socioeconomic and food security status of those living in these areas. The study pertains to the primary survey conducted for the year The survey included 1415 households spread over 119 villages and 21 districts of 10 states in India. Analysis revealed that quantity of food consumed was below than the recommended level, except cereals. Cereals were overfed compare to other food items. Food security and livelihood of underprivileged people was mainly derived from agriculture. Agricultural situation was poor in terms of low area under HYV, fertilizer consumption and irrigation facilities as compared to the national average. Nearly two-thirds of total cropped area was under cereals. Area covered under pulses and oilseeds was between 10 and 15 percent in

5 tribal and backward region, while vegetables covered about 14 percent area in hilly region. Fruits, spices and other crops covered negligible area in selected regions. Productivity of crops in general was lower than the national average. Farming was the main source of income and employment. Farm incomes were insufficient to use modern inputs which resulted low crop productivity and led to food insecurity. To ensure food security for underprivileged people, a multi-pronged strategy is needed. In this regard, the existing social safety-net programmes may be amalgamated, redesigned and implemented for underprivileged regions. The existing programmes may be made more transparent, and effective for benefits of poor in rural and urban areas. Simultaneously agriculture needs to be reformed by improving incentives, reforming institutions and increasing investment for efficient production. Besides, the traditional sources of increasing income and employment are not able to cope up with the dramatically changing situation and dismal performance of agriculture in the country. To augment income of people, there is a need to diversify their production portfolio towards high value commodities (HVCs). Incidentally, the demand (domestic and foreign) of HVCs are increasing and fetching higher prices. For this purpose, an enabling environment is to be created so that farmers are encouraged to actively participate in the production and marketing of HVCs, and take advantage of opportunities in domestic and global markets. Markets and prices of such commodities may be protected from volatility. It is expected that measures suggested would be able to improve the socioeconomic and food security conditions of vulnerable households and underprivileged regions. T5.5I Gender Dynamics and Empowerment of Rural Women in the Backdrop of Economic Issues Before India Poonam Agrawal Department of Women s Studies, NCERT, New Delhi Traditionally the social, intellectual, or moral forces and in the contemporary context the economic forces have influenced the gender dynamics the world over, although not uniformly. The universal concern for equity and social justice prominently include gender justice and equality. With the realization that the women empowerment is crucial to a more caring, sharing, tolerant, just and peaceful world, it is now being seen as an investment into a more livable world and a better future. It has become evident that for sustainable development, this nearly 48% of the global population can not be ignored. This acceptance has resulted in the incorporation of women empowerment as a commitment in a number of international declarations including the UN millennium development goals. In the Indian scenario, empowering women has been taken up as a major strategy for social change and development in the recent Five Year Plans. Mainstreaming a gender perspective into the development process has been an important approach of the Tenth Plan. The focus of policy planning has shifted from women welfare, just after independence, to development, to now the empowerment. It is now seen no more just as a moral issue but as an investment. India with an up looking economy, with her GDP growth rate of over 8% in 2005, is marching ahead for a double digit growth rate and aspiring to be a developed nation. This, however, poses a number of economic issues, such as, dealing with cross border competition, skillfully developing the huge population, especially that from the rural areas, into an asset and successfully managing the diverse economy which encompasses traditional farming, modern

6 agriculture, cottage industries, a wide range of modern industries and a multitude of services. The services with 53.8% contribution to the GDP are the major source of economic growth, while the three-fifths of the work-force is in agriculture. Hence, to achieve the desired growth rate and sustain it, agriculture has to be diversified and the potentially productive human resource, nearly half of which are women, has to be suitably prepared to contribute to the economy. More than 70% of our population lives in rural areas. This calls for a renewed focus on rural community and the women resource. The paper attempts to critically analyze the impact of various traditional and contemporary forces on gender dynamics in the backdrop of economic issues before us. How the gender dynamics is correlated with the economy is discussed in the light of some prominent economies of the world. Relevant success models from rural areas have also been projected. T5.6I Employment Status of Rural Women in India: A Reconnaissance with the NSS Data Brajesh Jha Institute of Economic Growth, New Delhi The present study assesses employment status of rural women across space and time with the NSS quinquennial survey results on employment. In India women accounts for around 30 per cent of rural workforce, bulk of them (85%) are in agriculture. Manufacture, community services, trade, and construction are other industries that account for significant proportion of female workers in the rural sector. Again in agriculture, manufacture and community services female account for more than 20 per cent of workforce and in these industries proportion of female workers have increased significantly (more than 1 per cent) during the reference period ( ); the proportion of females at all industries level have increased marginally, suggesting that rural women in construction, trade, transport and business services have been marginalized further. There are different kinds of trend from states; unlike the aggregate figure proportion of female in agriculture has not increased in Bihar and Madhya Pradesh; in fact there are evidences of males crowding out female agriculture workers in these states. In manufacturing, though share of female at aggregate level increased (1.2%), the respective share has declined in Goa, Gujarat, Haryana, Himachal Pradesh, Punjab, Maharashtra and Karnataka. The collation of temporal changes in female workers share in agriculture and manufacturing suggest that with economic development share of females has increased in agriculture while that of male have increased in industries other than agriculture. If percent distribution of usually employed (principal + subsidiary) by their broad current daily status of employment suggest under-employment in agriculture, then almost one-third of rural females are under-employed in rural India. Again, the social security measures in India is often associated with the categories of employment: self-employed or regular or casually employed; unfortunately, in rural India for one regular employed female worker there have been more than one thousand casually employed female workers suggesting poor social security benefits for female workers in rural sector. On the above accounts of employment quality there is only marginal improvement in the status of rural female workers during the reference period ( ). The real wage for female workers is around 80 per cent of the wages for male workers in agriculture; the gender difference in wages is higher in

7 manufacturing, construction and community service workers. The real wages for female workers have increased at a slower pace as compared to the male workers in rural sector. Most of the employment trends for rural female can be explained with the push related factors of employment. T5.7I Do Dams Help Reduce Poverty? R.P.S.Malik Agricultural Economics Research Centre, University of Delhi, Delhi Meeting the year round water requirements in a water scarce economy, such as that of India, with an erratic and highly seasonal pattern of rainfall, requires making huge investing in storage of water. The storage of water is warranted not only as a hedge against natural calamities in an abnormal year but is also necessitated for making water available round the year even during a normal rainfall year. Over the past 150 years India has responded appropriately to these prevailing conditions and has made huge investments in large-scale water infrastructure, much of which brings water to previously water-scarce areas. This has resulted in a dramatic economic shift, with once-arid areas becoming the centers of economic growth, while the historically well-watered areas have seen much slower progress (Briscoe and Malik: 2006). While appreciating the need for creating more water storages, many social and community groups have often criticized investments in major water infrastructure and have instead been forcefully arguing for investments in small dispersed storages such as in tanks, small watersheds, rainwater harvesting structures, groundwater recharge structures etc. The opposition to large water harvesting structures by these groups has often been on several perceived, and often surmised, ill effects of large dams - economic, social, ecological and environmental. However, in practice, most of the opposition has been on account of issues relating to displacement and resettlement of people affected by the construction of such large projects. While no one would disagree with opposition to construction of large water storages on this account without a satisfactory resolution of the issues relating to fair compensation to the project affected people, however once resolved, are there any other legitimate economic reasons for opposing investments in large storage projects? The important socio-economic argument often advanced against construction of such water storage structures relate to inequity in distribution of benefits: the benefits of the development emanating from these structures are reaped by relatively better-off land owning households alone and non land owning and poor households are left out (see amongst others Pellekaan: 2002). As a result, it is argued, that such water resource development projects have either limited, nil or negative impact on poverty. We however premise that this is not an objective assessment of the impact of water resources infrastructure. Economic growth, initiated by policies of investments in either large (such as multipurpose dams) or small water resources infrastructure (such as watershed development) and/or other forms of investments generally tend to benefit everyone in the society, including the poor, proportionately. A recent World Bank study in a sample of 92 countries covering the period during the last four decades shows that when average incomes rise, the average incomes of the poorest fifth also rise equi- proportionately. This holds true across periods, regions, time, income levels and growth rates (Dollar and Kraay: 2001). This implies that increased investments, including those in water infrastructure and management, benefit all including the poor. An OED review of irrigation sector, based largely on the retrospective evaluation of over two hundred World Bank financed irrigation

8 projects over a four decades period, concluded that the benefits of most irrigation investment have reached the poor (World Bank: 1994). Water infrastructure has also evened out the seasonal demand for labor, resulting in major gains for the poor (Chambers et al: 1989). Given the likely demand for water and amount of the supply gap that needs to be bridged we argue that all forms and sizes of storages over ground, underground, large and small - are required to be built. Without, at this stage, going in to a comprehensive assessment of the benefits of alternative forms of storages, the paper demonstrate how the benefits of large water storage projects such as multipurpose dams are shared by all sections of the society, including the non land owning rural households as also even the urban households, and argues why investments in large dams serve could serve as an important vehicle for poverty reduction. The paper uses a Social Accounting Matrix (SAM) based fixed price multiplier model of Punjab economy to quantify the direct and indirect economic benefits of Bhakra multipurpose dam and demonstrate how these benefits have been shared by different sections of the society, including the poor. References Briscoe, John and Malik, R.P.S. (2006). India s Water Economy: Bracing for a Turbulent Future. New Delhi : Oxford University Press and The World Bank Chambers, R., Saxena, N.C. and Shah, T.(1989). To the Hands of the Poor. New Delhi: Oxford and IBH Publishing Company Pvt Ltd Dollar David and Kraay, A. (2001). Growth is Good for the Poor. Policy Research Working Paper Washington, D.C : The World Bank Pellekaan, Jack van Holst (2002). India: Evaluating Bank Assistance for Poverty Reduction : A Country Assistance Evaluation. Washington, DC: The World Bank, Operations Evaluation Department.