Xinjiang Agricultural Sciences ›› 2025, Vol. 62 ›› Issue (5): 1293-1300.DOI: 10.6048/j.issn.1001-4330.2025.05.028

• Animal Husbandry Veterinarian·Agricultural Eeconomy • Previous Articles    

Evaluation of agricultural production efficiency in four prefectures in Southern Xinjiang

TIAN Conghua(), CENG Hongmei, ZHANG Lizhao, MIAO Hongping, WANG Hongmei, DAI Junsheng()   

  1. Institute of Agricultural Economics and Information, Xinjiang Uyghur Autonomous Region Academy of Agricultural Sciences, Urumqi 830091, China
  • Received:2024-10-11 Online:2025-05-20 Published:2025-07-09
  • Correspondence author: DAI Junsheng
  • Supported by:
    Natural Science Foundation Program of Xinjiang “Research on the Optimization of Agricultural structure Adjustment in the Four Prefectures of Southern Xinjiang under the Intercropping Model”(2022D01A263);Third Xinjiang Comprehensive Scientific Investigation Project “A survey on the Evolution of Agricultural Structure and Layout in the Tarim River Basin”(2021xjkk020041)

新疆南疆四地州农业生产效率评价

田聪华(), 张利召, 苗红萍, 程红梅, 王红梅, 戴俊生()   

  1. 新疆维吾尔自治区农业科学院农业经济与信息研究所,乌鲁木齐 830091
  • 通讯作者: 戴俊生
  • 作者简介:田聪华(1978-),女,甘肃武威人,研究员,硕士,研究方向为区域经济与产业经济,(E-mali)391253466@qq.com
  • 基金资助:
    新疆维吾尔自治区自然科学基金项目“间作模式下南疆四地州农业结构调整优化研究”(2022D01A263);第三次新疆综合科学考察项目“塔里木河流域农业结构与布局演变调查”(2021xjkk020041)

Abstract:

【Objective】 Based on the intercropping pattern in four prefectures of southern Xinjiang, this paper aims to construct the index system of agricultural production efficiency and calculate the comprehensive efficiency, technical efficiency and scale efficiency of agricultural production. 【Methods】 Based on 22-year panel data from 2000 to 2021, DEA model method was used to analyze agricultural production efficiency and evaluate the input-output effect of agricultural factors. 【Results】 The agricultural production efficiency of the four prefectures was at a high level, which could effectively promote the rapid progress of agriculture in Xinjiang, but it was still a DEA non-active area.There were many redundant agricultural input factors, which did not achieve the best economic and social benefits. (2) The efficiency of the input index was in the order from good to bad: the number of rural labor force > the sown area of crops > the total power of agricultural machinery > rural electricity consumption > the amount of fertilizer applied > the amount of agricultural plastic film used > the expenditure on agriculture, forestry and water affairs. (3) The scale income was generally in the increasing stage, and the regional production potential could be continuously tapped【Conclusion】 There is a "surplus" of agricultural input factors in the four prefectures in southern Xinjiang, and government departments should strengthen macro-control, release the resources that have been over-invested in the primary industry, optimize the rational allocation of resources, and enhance the efficiency of inputs and outputs. They should do: (1) Rationally adjust the proportion of agricultural financial input and distribution, and optimize the rational allocation of resources, improve the efficiency of agricultural financial expenditure; (2) Guide the transfer of labor to secondary and tertiary industries.(3) Continuously promote the reduction of fertilizer and pesticide dosage and increase efficiency. (4) To improve the level of agricultural equipment and information technology.(5)Adjust planting structure and planting mode to improve the efficiency of land output.

Key words: intercropping pattern; agricultural production efficiency; DEA method

摘要:

【目的】基于新疆南疆四地州间作种植模式下,构建农业生产效率测度指标体系,测算农业生产综合效率、技术效率和规模效率。【方法】以2000~2021年22年面板数据为研究对象,运用DEA模型方法对农业生产效率进行分析,评价农业要素投入产出效果。【结果】(1)新疆南疆四地州农业生产综合效率为0.954,处于较高水平,可有效推动农业快速进步,但仍属于DEA非有效地区,农业投入要素冗余较多,未取得经济和社会的最佳效益。(2)投入指标效率由好到差依次为乡村劳动力人数>农作物播种面积>农业机械总动力>农村用电量>化肥施用量>农用塑料薄膜使用量>农林水事务支出。(3)规模收益总体处于递增阶段,可持续性挖掘区域生产潜力。【结论】新疆南疆四地州农业投入要素存在“过剩”,加强宏观调控将过度投入到第一产业的资源释放出来,优化资源合理配置,提升投入产出效率。(1)合理调整农业财政投入与分配比重,提高农业财政支出使用效率;(2)引导劳动力向二三产业转移。(3)持续推进化肥农药减量增效。(4)提升农业装备和信息化水平。(5)调整种植结构和种植模式,提高土地产出效率。

关键词: 间作模式, 农业生产效率, DEA方法

CLC Number: