| 摘要: |
| 【目的】全方位分析河南省农田水利基础设施生产效率，为促进农田水利资源的合理使用提供对策建议。【方法】选取2013—2020年河南省15个省辖市的面板数据，运用DEA模型和Malmquist指数对河南省农田水利基础设施生产效率开展研究，并对2020年非DEA有效地区进行冗余分析，从静态和动态视角评价各省辖市农田水利基础设施效率水平。【结果】2020年开封市、鹤壁市、焦作市等6市综合技术效率达到DEA有效，其余均为无效状态；非DEA有效地区均存在不同程度的投入冗余和产出不足，郑州市在水库和第一产业就业人员上存在较高的投入冗余，新乡市在农村用电量上投入冗余较大，郑州市和许昌市在农林牧渔业总产值上产出不足量相对较高，洛阳市灌溉面积产出不足量相对较高；2013—2020年河南省部分省辖市农田水利基础设施全要素生产率的平均增长率达到10.0%，呈波动式增长趋势，主要驱动力是技术进步。【结论】通过因地制宜配置资源，促进农村劳动力非农化转移，以遏制盲目的农田水利建设投入；借助政策支持和创新资金筹措方式为农田水利发展落后地区提供发展保障，缓解农田水利发展的地区差异矛盾；将科技创新与农田水利工程项目有机结合，以项目带动水利科技研发与推广，实现区域内农田水利现代化建设。 |
| 关键词: 农田水利基础设施；效率分析；DEA-BCC；Malmquist指数；冗余分析 |
| DOI：10.13522/j.cnki.ggps.2022577 |
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| 基金项目: |
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| Using DEA Model and Malmquist Index to Analyze Efficiency of Farmland Water Infrastructure in Henan Province |
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LIU Guifang, YAO Feng
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School of Public Administration, Hohai University, Nanjing 211100, China
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| Abstract: |
| 【Objective】This study is to comprehensively analyze the efficiency of farmland water infrastructure in Henan province and provide guidelines for sustainable utilization of water resources in agriculture.【Method】Using data measured from 2013 to 2020 from 15 cities in the province, the efficiency of farmland water infrastructure was evaluated using the DEA model and the Malmquist index. Redundancy analysis was conducted to identify the areas of improvement for non-DEA effective regions in 2020. The evaluation considered both static and dynamic aspect to assess the efficiency of the farmland water infrastructure. 【Result】 In 2020, six cities, including Kaifeng, Hebi, and Jiaozuo, achieved DEA efficiency, while the remaining cities were deemed inefficient. The non-DEA effective regions exhibited varying degrees of input redundancy and output deficiencies. For example, Zhengzhou had high input redundancy in reservoirs and primary industry employment; Xinxiang had high input redundancy in rural electricity consumption; Zhengzhou and Xuchang had output deficiencies in the total output value of agriculture, forestry, animal husbandry, and fishery; Luoyang had output deficiencies in the irrigated area. The total factor productivity of the farmland water infrastructure in the province exhibited an average growth at a rate of 10.0% from 2013 to 2020, driven primarily by technological progress. 【Conclusion】To promote sustainable development, resource allocation should be tailored to local conditions, and efforts should be made to facilitate the non-agricultural transfer of rural labor, thereby reducing non-effective investment in farmland water conservation. Leveling regional development of farmland water infrastructure can benefit from policy support and innovative funding. Integrating science and technology innovation can facilitate modernization of the farmland water infrastructure. |
| Key words: farmland water infrastructure; efficiency analysis; DEA-BCC; Malmquist index; redundancy analysis |
