文章基本信息

标题：A Unified Methodology for Estimating the Demand for Improved Seed at the Farm Level in Developing Agriculture
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作者：Langyintuo, Augustine S. ; Mazuze, Feliciano M. ; Chaguala, P.A. 等
期刊名称：Journal of Agribusiness
印刷版ISSN：0738-8950
出版年度：2006
期号：suppl
出版社：Journal of Agribusiness
摘要：This paper proposes a novel approach for estimating farm level seed demand in developing countries. In principle, a farmer views an improved seed as a derived input embodying production attributes and a technology embodying consumption characteristics and jointly decides on its adoption and the quantity of seed required to plant a predetermined area. Drawing on the theory of demand for consumption goods characteristics and production input attributes, this paper specified and estimated improved seed adoption and demand models simultaneously using data collected from 300 randomly selected farm households in the Manica, Sussundenga and Chockwé districts of Mozambique in the 2003/04 crop season. The demand model results suggest that adoption rate, household wealth, distance to market, and input support programs (or free seed distribution) significantly influence farmers' seed purchase decisions. Wealth has a direct impact on seed demand and could be achieved through asset accumulation, credit access or competitive grain markets. To improve adoption rates and subsequently seed demand, it is recommended that agricultural extension activities should emphasize field demonstrations to show the superiority of improved maize varieties over the local ones in terms of yield and resistance to storage pests. Making seeds available to farmers at short distances will also improve adoption rate. Seed support programs, which can potentially damage rural seed market development should be implemented with care. It is concluded that the joint estimation of technology adoption and improved seed demand provides a holistic approach to the identification of relevant factors determining seed uptake at the farm level in developing agriculture and contributes to the literature on farm level seed demand modeling.