中国小麦生产布局演化及影响因素研究

STUDY ON WHEAT SPATIAL DISTRIBUTION VARIATION AND INFLUENCING FACTORS IN CHINA

关键词:  小麦生产布局影响因素空间杜宾模型空间交互作用

Key words:  wheat  spatial distribution  influencing factors  spatial Durbin Model  Spatial interaction

摘要:

［目的］小麦作为我国重要的口粮作物，其生产布局变化影响市场供给的均衡性，关系小麦生产稳定，也关系国家粮食安全。［方法］采用1978—2014年全国省级面板数据，运用生产规模指数、集中度指数、生产重心指数及重心转变路径全面分析中国小麦生产布局空间演化特点，通过莫兰指数检验各区域小麦播种面积的空间相关性，构建空间杜宾模型分析小麦生产布局的影响因素。［结果］（1）随着时间迁移，小麦生产布局由分散逐渐变集中，主要集中于中部、黄淮海地区，该地区的面积和产量对全国小麦生产的贡献最大； （2）无论是从播种面积还是产量角度，中国小麦生产重心都表现出自北向南再向东的趋势； （3）小麦生产的空间集聚效应随时间变化越来越显著； （4）灌溉水平和化肥投入对该区、相邻地区和全国的小麦播种面积均有正向作用，机械投入、政策和技术水平对该区、相邻地区和全国的小麦播种面积均产生负向影响，比较收益和非农就业机会对该区和相邻地区的小麦播种面积均有影响，但作用方向相反。［结论］建议小麦生产布局优化要注重发挥相邻区域农民的学习效仿能力，促进小麦品种研发技术提升，增强小麦生长的环境适应性，提高小麦生产的要素配置效率，关注非农就业导致的小麦播种面积波动，保障主产省农民收益。

Abstract:

As one of the most important grain ration, the wheat spatial distribution has a tremendous impact on the equilibrium of market supply, also relates to wheat production stability and national food security. This study used the production scale index, the concentration index, the production center gravity index and gravity route transition comprehensively to analyze the wheat spatial distribution variation by combining provincial panel data from 1978 to 2014 in China. The spatial correlation of wheat sown area in each region was tested by Moran′s Index and the influence factors of wheat spatial distribution variation was analyzed by spatial Durbin Model. The results showed that wheat spatial distribution became concentrated over time, mainly in central and Huang Huai Hai region, the sown area and yield in this region gave the greatest contribution to national wheat production; the production center gravity index showed the China wheat′s productivity trend move from north to south and then to eastward, no matter from the sown area or the yield view; the space centralization effect of wheat production became increasingly evident with the passage of time; Irrigation level and fertilizer input had positive effect on own region, adjoining region and national region; Mechanization input, policy and technological level had negative effect on own region, adjoining region and national region. Comparative income and non agricultural employment opportunities had effect on both own region and adjoining region, however the effect was in the opposite direction. These results suggested that the wheat production layout optimization should pay attention to farmer′s learning and imitate ability in adjacent region; promote the improvement of wheat varieties R&D technology to enhance the environmental adaptability of wheat growth in order to improve the efficiency of wheat production factor allocation; pay attention to the non agricultural employment variation caused by the wheat sown area fluctuations, and effectively protect the main provinces of farmer′s income.