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Abstract
为了探究粮食主产区农业绿色发展的影响因素与质量动力,以农业绿色全要素生产率(GTFP)为切入点,运用超越对数函数形式的SFA模型对环境约束下2004—2018年松花江、黄河、长江三大流域粮食主产区展开分析。结果表明:环境规制、第一产业占比、农业财政支持对GTFP的增长具有显著正向影响,环境污染、自然灾害则反之;三大流域农业GTFP增长率的平均值为3.3%,农业绿色发展状况在不断改善,但改善速度前期波动较大、后期较小,且区域间呈现不均衡状态;松花江流域的发展动力主要来自技术效率、技术进步和规模效率的增长,黄河流域和长江流域分别来自技术效率主导和技术进步主导的效率与进步双重驱动,规模效率和要素配置效率对二者的贡献较为微弱。今后需要注重以提升绿色全要素生产率为核心,加大农业技术创新,发展适度规模经营,完善区域协调发展机制,并有效实施环境规制政策。
In this study, we used the stochastic frontier analysis(SFA) model in the form of the transcendental logarithmic function to analyze the major grain-producing areas in the Songhua River, Yellow River and Yangtze River basins from 2004 to 2018 under environmental constraints, in order to explore the influencing factors and quality dynamics of agricultural green development in major grain-producing areas based on agricultural green total factor productivity(GTFP). The results showed that environmental regulation, the proportion of the primary industry, and agricultural financial support had a significantly positive, while environmental pollution and natural disasters a negative effect on the growth of GTFP, respectively. The average growth rate of agricultural GTFP in the three major basins is 3.3%, and the agricultural green development situation is constantly improving, but the speed of improvement fluctuates significantly in the early stage, followed by amplitude reduction, showing an unbalanced profile among the regions. The Songhua River basin is mainly driven by the increase in technical efficiency, technological progress, and scale efficiency. The Yellow River basin and the Yangtze River basin are driven by technical efficiency and technological progress, respectively. The contribution of scale efficiency and factor allocation efficiency to the two is relatively weak. Therefore, we need to focus on the improvement of green total factor productivity, increase agricultural technological innovation, develop appropriate scale operation, improve regional coordinated development mechanism, and effectively implement environmental regulation policies.
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