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我国玉米种植区生态效率的区域差异及影响因素研究 被引量:4

Study on Regional Differences and Influencing Factors of Ecological Efficiency of Maize Planting Areas in China
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摘要 基于2004—2018年三大玉米种植区的面板数据,运用SBM模型方向性距离函数中的Malmquist-luenberger生产率指数和以产量为导向的DEA-malmquist指数,实证研究我国玉米种区生态效率的区域差异,以及在环境制约下我国玉米不同种区的真实生产状况。随后通过Tobit面板模型,分析不同玉米种区的生态效率和生产效率指数在相同影响因素下的差异。结果表明,我国玉米种区整体为粗放式的发展模式,北部种区整体生态效率较高,生产方式较为低碳;中部种区的平均生态效率较高,但技术效率退步明显;西部种区的生态效率增长缓慢,技术投入不足。受灾率、生态治理水平和环保投入因素对各玉米种区的生态效率和传统M指数存在趋同的影响作用,但不同种植区域还是存在较大的影响差异。 Based on the panel data of three corn growing areas from 2004 to 2018,this paper used the Malmquist-luenberger productivity index and yield oriented DEA-malmquist index in the directional distance function of SBM model to empirically study the regional differences of ecological efficiency of corn growing areas in China,and the real production situation of different corn growing areas under environmental constraints.Then,through Tobit panel model,the differences of eco efficiency and production efficiency index of different maize seed areas under the same influence factors were analyzed.The results showed that the overall development mode of maize seed area in China was extensive,the overall ecological efficiency of northern seed area was higher,and the production mode was low-carbon;the average ecological efficiency of central seed area was higher,but the technical efficiency declined significantly;the ecological efficiency of western seed area increased slowly,and the technical input was insufficient.The disaster rate,ecological management level and environmental protection input factors have a convergence effect on the ecological efficiency and traditional M index of maize planting areas,but there are still large differences in different planting areas.
作者 陈衍俊 CHEN Yan-jun(Economics and Management School of Yangtze University,Jingzhou,Hubei 434023)
出处 《安徽农业科学》 CAS 2022年第5期196-199,209,共5页 Journal of Anhui Agricultural Sciences
基金 国家社科基金项目“以生态安全和粮食安全并重为导向的粮食补贴政策研究”(17BGL250)。
关键词 玉米 SBM模型 地区差异 影响因素 Maize SBM model Regional difference Influencing factors
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