KRISHI
ICAR RESEARCH DATA REPOSITORY FOR KNOWLEDGE MANAGEMENT
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http://krishi.icar.gov.in/jspui/handle/123456789/685
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DC Field | Value | Language |
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dc.contributor.author | Pratap S. Birthal Shiv Kumar Digvijay S. Negi Devesh Roy | en_US |
dc.date.accessioned | 2016-11-29T05:32:58Z | - |
dc.date.available | 2016-11-29T05:32:58Z | - |
dc.date.issued | 2015-10-01 | - |
dc.identifier.citation | Not Available | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/685 | - |
dc.description | Not Available | en_US |
dc.description.abstract | Owing to several changes, such as shifts in food consumption away from staples towards high-value food products, growing stresses on natural resources, and climate change, Indian agriculture is becoming increasingly knowledge-intensive. Farmers need different types of information— ranging from weather forecasts and advisories, inputs, agronomic practices, pest management, markets and prices. The demand for information has amplified as farmers are tasked with not only enhancing agricultural productivity and conserving natural resources but also other requirements, such as complying with market preferences for diverse, safe and quality food. Adjusting to these changes requires a variety of information, the access to which can differentiate farm households, in terms of returns from farming. While the role of information is becoming increasingly important in improving efficiency of agricultural production, there have been limited efforts towards a rigorous impact assessment of the access to and use of this vital input on the outcomes of farming. In this paper, using data from a nationally representative survey, conducted by the National Sample Survey Organisation (NSSO) of the Government of India, we examine farm households’ access to and use of information, and its effects on farm income. Approximately 40% of the farm households in India have access to information on fertilizer application, crop varieties, pest management, marketing, etc. However, only 75% of those who access information, use it in their farming decisions. The distribution of users of information by its source indicates that the government information sources including public extension workers, Krishi Vigyan Kendras (agriculture science centres), farm demonstrations, farmers’ trainings and study tours organized by the government agencies, comprise a source of information for only 14% of the farm households. Farmers meet most of their information needs from other sources, including mass media, private sources and social networks. The social networks (progressive farmers, primary cooperative societies and village fairs) are utilized by 29% of the farm households, with progressive farmers being a prominent source. About 23% of the farm households depend on private sources, mainly on input dealers, for their information needs. Mass media sources, such as radio, television and newspaper are utilized by one-third of the farm households. A number of socio-economic characteristics differentiate users of information from its non-users. The users of information have relatively xii larger landholdings, higher endowment of labour and greater access to institutional credit. They are also more educated and better informed about the government policies. Further, the information use also differs by farm size and social status. About 41% of the large farmers (>4ha) use information compared to 20% of the sub-marginal farmers (<0.5ha). In rural areas, caste is an important indicator of social status, with scheduled caste and scheduled tribe being at the bottom of caste hierarchy. About 35% of the upper caste households use information as against 23% and 20% of the scheduled caste and scheduled tribe households, respectively. Further, smaller farmers and those at the bottom of social hierarchy (scheduled castes and scheduled tribes) use fewer information sources. Also, they are more dependent on informal information sources, i.e., social networks and private sources. Larger farmers and those from upper castes use information from multiple sources, relatively more from mass media. These indicate toward a potential bias in access to information, which probably could be due to differences in observable (farm size, caste, age, education, etc.) and unobservable (skill, attitude towards risk, etc.) characteristics of the farm households that may simultaneously influence returns from farming. The analysis of net income from cultivation by farm size and number of information sources used indicates that users of information (except sub-marginal farmers) realize significantly higher income per unit of land, and it increases with intensity of information use, i.e., number of sources used. After controlling for the potential selection biases, the study finds that users of information realize 12% more income than the non-users. The impact is bigger in diversified cropping systems (cash crops along with foodgrains). The income effect of information sources also differs; the formal information sources, though their outreach is smaller, have a larger impact on farm income—almost twice of that of the informal sources possibly due to qualitative differences in information content and its delivery systems. These findings are crucial for informed policy decisions regarding development of information delivery system. The agricultural extension policy should aim at developing information dissemination systems that are cost-effective, efficient in delivery and motivate farmers for a greater uptake of information on modern technologies and other practices irrespective of farm size and social status. Indian agriculture is diversifying towards higher-value crops; suggesting a need for developing information systems that cater to the needs of farmers growing these crops. Indeed, several government programs in India have relied on channels, such as radio, to implement large-scale agricultural programs without any scale or social bias. Our results suggest that returns on investment in extension services are quite attractive, and certainly there is a scope for improving outreach of such information sources for spread of agricultural technologies and practices in a heterogeneous rural society. xiii Investment on agricultural research and development has considerable potential for enhancing farm productivity and poverty reduction. A 12% higher net income for information users translates into an additional Rs 1140 per hectare of cropped area (at 2002-03 prices). This is much higher than the expenditure on public extension services (Rs 29 per hectare), and also on the research and education (Rs 157/ha). This indicates that investment in public extension services has not kept pace with the rising demand for information by the farmers, and implies that under-investment in public extension may limit realization of the potential gains in agricultural productivity from spending more on agricultural research. Mobiles, internets and inter-linked arrangements, such as contract farming and producer organizations are emerging as alternatives to traditional extension systems, and these are claimed to be more efficient in information dissemination. The need is to collect and collate the contextand location-specific right information and disseminate it in right time and in a right form through such cost-effective channels. There is also a need to create awareness among farmers about the benefits of using information, to provide bundled services (technological, financial and non-financial), and to create effective linkages of service providers with research organizations, public extension systems, and market places. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | National Publisher | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | Impact information Returns Farming | en_US |
dc.title | The Impact of Information on Returns from Farming | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Policy Paper | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Policy Paper | en_US |
dc.publication.volumeno | 29 | en_US |
dc.publication.pagenumber | 64 | en_US |
dc.publication.divisionUnit | Not Available | en_US |
dc.publication.sourceUrl | Not Available | en_US |
dc.publication.naasrating | Not Available | - |
Appears in Collections: | AEdu-NIAP-Publication |
Files in This Item:
File | Description | Size | Format | |
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Policy Paper 29.pdf | 1.31 MB | Adobe PDF | View/Open |
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