| 摘要: |
| ［目的］分析我国粮食生产效率的时空特征，并探讨其空间依赖性。［方法］文章构建DEA模型测算2003—2015年间我国30个省份的粮食生产效率，然后利用空间自相关模型对粮食生产效率的时空格局特征进行分析，最后基于空间杜宾模型对影响粮食生产效率的各类因素进行空间依赖性分析。［结果］（1）2003—2015年我国粮食生产效率基本稳定，但具有明显的阶段性变化特征； （2）粮食生产效率的空间差异性显著，综合技术效率从高到低依次为东北、华东、中南、西南、华南、华北和西北，并且随着时间的推移其空间格局特征并没有发生显著变化； “高高聚集”的区域主要为东北及华东的浙江、江苏等地，“低低聚集”的区域主要集中在陕西、宁夏、甘肃、山西等地区； （3）粮食单产水平是影响粮食生产效率的最主要因素； 除涝面积、机械总动力投入、农业化肥投入、人均收入水平等对粮食生产效率具有负向影响，而粮食作物播种面积比重和高中以上劳动力比例则对粮食生产效率具有正的空间溢出效应。［结论］我国粮食生产效率的提高不再依赖于大量中间生产要素的投入，今后应更加注重农业科技的推广和农村劳动力的文化水平的提高。 |
| 关键词: 粮食生产效率数据包络分析（DEA）时空特征空间依赖性动态空间杜宾模型（DSDM） |
| DOI： |
| 分类号:F3233 |
| 基金项目:国家自然科学基金项目“农地流转空间及形成机制研究——以贵州山区为研究样本”（71673065） |
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| ANALYSIS ON SPATIAL TEMPORAL PATTERNS AND SPATIAL DEPENDENCE OF CHINA′S FOOD PRODUCTION EFFICIENCY |
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Yang Xiaoxuan, Hong Mingyong, Pan Dongyang
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School of Management, Guizhou University, Guiyang, Guizhou , 550025, China
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| Abstract: |
| This paper analyzed the spatial temporal patterns of China′s food production efficiency and discussed on corresponding spatial dependence. Based on DEA Model, this paper firstly calculated the efficiency of food production of 30 provinces in China from 2003 to 2015; then the Spatial Autocorrelation Model and the Spatial Durbin Model were used to analyze the spatial patterns of food productivity efficiency and the spatial dependence of various factors affecting food production efficiency, respectively. The results showed that:（1）During 2003 2015, while a marked periodic change existed, China′s food production efficiency was basically stable. （2) The spatial difference of grain production efficiency is significant. The order of comprehensive technical efficiency from high to low is Northeast, East, South Central, Southwest, South, North and Northwest China，which spatial patterns did not change much over time; The "high high cluster" regions were mainly located in the Northeast and East China′s Zhejiang and Jiangsu provinces, meanwhile the "low low cluster" areas were mainly concentrated in Shaanxi, Ningxia, Gansu and Shanxi provinces; （3) Grain yield per hectare was the primary factor affecting food production efficiency; waterlogging control areas, total mechanical power, agrochemical usage and the level of per capita income had negative effects on food production efficiency, whereas the proportion of crop acreage and the proportion of rural labor force with high school education or above generated positive spillover effects. The improvement of food production efficiency in China was no longer dependent on the input of a large number of intermediate production factors, so it suggested that more attention should be paid to the extension of agricultural science and the improvement of educational level of rural labor force in the future. |
| Key words: food production efficiency data envelopment analysis spatial temporal patterns spatial dependence Dynamic Spatial Durbin Model |
