摘要: |
目的 改革开放以来我国粮食供给经历了不同发展阶段和时空变化特征,自然条件、经济因素及政策因素都不同程度驱动形成当前粮食供给格局,通过对我国粮食供给情况时空变迁及过去产能提升路径分析,提出未来粮食产能提升可能的增长途径。方法 文章以粮食增产的角度重新划分粮食供给经历的不同发展阶段,在此基础上使用标准差椭圆描绘粮食增产的空间格局变化路径,并运用供给反应模型分析粮食供给增长的驱动因素,使用实证方法分析新一轮粮食产能提升的潜力和方向。结果 (1)我国粮食供给经历了1978—1998年、2003—2015年、2019年至今3个粮食供给增长阶段,在这3个阶段中粮食增产重心由西南—东北—西北移动,稻谷增产重心不断向东北偏移,小麦增产重心各阶段变化不大,玉米增产重心由西南—东北—西北移动,大豆增产重心由东北—西南—东北移动。(2)通过供给反应模型分析粮食供给增长驱动因素发现,粮食价格的提高、农业政策的实行对粮食供给有正向影响,而化肥价格的提高、自然灾害的增加对粮食供给有负向影响。地区经济发展与粮食供给增长趋势相反,粮食供给区域特征明显。结论 (1)应优化粮食产业布局,缓解粮食增长重心与自然条件、资源禀赋、经济发展水平配置之间的矛盾。(2)发挥粮食价格和农业政策对粮食生产的激励作用,保证农民粮食生产价格预期的稳定性。(3)加强农业基础设施建设和农业科技创新,提高粮食供给抵御自然风险的能力,从而提高粮食生产效率和粮食生产能力。 |
关键词: 粮食供给 时空变迁 千亿斤产能提升 标准差椭圆 供给反应模型 |
DOI:10.7621/cjarrp.1005-9121.20240904 |
分类号:F326.1 |
基金项目:中国农业科学院科技创新工程项目(10-IAED-08-2023) |
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THE PATH ANALYSIS OF SPATIAL-TEMPORAL CHANGES AND PRODUCTIVITY IMPROVEMENT OF GRAIN SUPPLY IN CHINA |
Wang Chen1, Zhang Wenbo2, Wang Jimin1
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1.Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing100081, China;2.Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing100081, China
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Abstract: |
Since the reform and opening up, grain supply has experienced different development stages and spatial-temporal changes in China. Natural conditions, economic factors and policy factors have driven the formation of the current grain supply pattern in different ways. This paper analyzed the path of the spatial-temporal changes of grain supply and productivity improvement in the past of China, and put forward the possible ways to increase grain productivity in the future. The different development stages of grain supply were reclassified from the perspective of grain production increase. On this basis, the standard deviation ellipse was used to describe the change path of grain production increase, and the supply response model was used to analyze the driving factors of grain supply growth, then the potential and direction of a new round of grain production capacity improvement was analyzed by the empirical method. It was found that grain supply experienced three stages of grain supply growth in China, it was from 1978 to 1998, from 2003 to 2015, and from 2019 to the present. In these three stages, the center of gravity of grain production increase moved from southwest to northeast to northwest. The center of gravity of rice production increase moved to northeast continuously, and the center of gravity of wheat production increase did not change much in each stage. The center of gravity of corn production increase moves from southwest to northeast to northwest, and the center of gravity of soybean production increase moved from northeast to southwest to northeast. By analyzing the driving factors of grain supply growth through the supply response model, it was found that the increase of grain prices and the implementation of agricultural policies had a positive impact on grain supply, while fertilizer prices and natural disasters had a negative impact on grain supply. The regional economic development was contrary to the growing trend of grain supply, and the regional characteristics of grain supply were obvious. Finally, summarizing the past experience and path of grain supply growth, the following suggestions are put forward to ensure the future increase of grain production capacity: Optimizing the distribution of grain industry to alleviate the contradiction between the center of gravity of grain growth and natural conditions, resource endowments and the levels of economic development. Giving full play to the incentive role of grain prices and agricultural policies in grain production, and ensuring the stability of farmers' expectations of grain production prices. At the same time, strengthening the construction of agricultural infrastructure and agricultural scientific and technological innovation, improving the ability of grain supply to resist natural risks, so as to improve grain production efficiency and capacity. |
Key words: grain supply spatial-temporal distribution 100 billion jin production capacity increase standard deviation ellipse supply response model |