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  • 标题:Technical-and-allocative inefficiency index of Indian sugarcane farms- A primal system approach
  • 本地全文:下载
  • 作者:K. Thomas Felix ; P. Naveen Kumar ; S. Arivarasan
  • 期刊名称:Environmental and Sustainability Indicators
  • 印刷版ISSN:2665-9727
  • 出版年度:2021
  • 卷号:11
  • 页码:100133
  • DOI:10.1016/j.indic.2021.100133
  • 出版社:Elsevier BV
  • 摘要:Cost of Cultivation of Principal Crops (CCPC) data from 2014–15 to 2016–17 was collected and converted as a panel data to estimate the technical and allocative inefficiency indexes and its impact on input demand and cost of sugarcane production. The present study adopted the primal system approach, with the Cobb-Douglas production function and the first-order conditions of cost minimization. Returns to scale value confirmed that there is a vast scope to increase India's sugarcane yield. Results also revealed that fertilizer is the most under-utilized whereas setts and irrigation are the most over-utilized resources in Indian sugarcane production. Machinery usage was under-utilized in Karnataka, Tamil Nadu, and Uttar Pradesh. The technical inefficiency in sugarcane production reduces the input demand of labour, setts, fertilizer, irrigation, and machinery by 2.70 percent, 4.90 percent, 3.30 percent, 3.50 percent, and 7.60 percent respectively. Technical-and-allocative inefficiency collectively increases the cost of sugarcane production by 46.80 percent in Andhra Pradesh, followed by 44.30 percent in Maharashtra, 35.90 percent in Tamil Nadu, 27.10 percent in Uttar Pradesh, 24.70 percent in Karnataka, and 23 percent in Uttarakhand. It confirms that existing sugarcane yield of India can be attained with 33.60 percent lesser than the existing production cost. These results suggest establishing rural-based agricultural machinery custom hiring centres, proper irrigation structures, and single bud chips as a planting material would increase the sugarcane production as well as reduce the cost of cultivation.
  • 关键词:Technical inefficiency index ; Allocative inefficiency index ; Sugarcane ; Primal system approach ; Stochastic frontier
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