中国饲料粮生产格局演变及影响因素研究

CHANGES IN CHINA’S FEED GRAIN PRODUCTION PATTERN AND ITS INFLUENCING FACTORS

关键词:  饲料粮  生产格局  重心模型  空间杜宾模型  Moran's  I指数

Key words:  feed grain  production pattern  gravity center model  spatial Durbin model  Moran's I index

摘要:

目的 研究我国饲料粮生产布局的区域差异，剖析其影响因素，以期为优化饲料粮生产布局，促进饲料粮产业健康发展提供一定的参考。方法 文章选取2000—2021年我国31个省（市、区，不含港澳台）的数据，运用分品种投入法和重心模型分析了饲料粮的布局变迁及重心轨迹，利用空间杜宾模型进一步分析其影响因素。结果 （1）2000—2021年饲料粮产量整体不断增加，聚集特征越来越明显，逐渐向东北地区、华北地区、西南地区聚集。饲料粮生产重心在西南和东北方向变动，总体向东北方向移动，由河南省转移到河北省。（2）我国饲料粮生产存在明显的正向空间自相关性，饲料粮生产倾向于高产地区与高产地区聚集，低产地区与低产地区聚集。（3）农业产值比重、有效灌溉面积、化肥施用量、耕地面积和农业财政支出对饲料粮生产具有显著正向作用，邻近地区的农村居民人均可支配收入、第一产业就业人员、交通运输里程、农业机械总动力、有效灌溉面积、化肥施用量会影响到该地区的饲料粮生产，具有空间溢出效应。结论 建议优化饲料粮生产布局，注重饲料粮生产的空间相关性，充分发挥饲料粮生产能力高的省份的辐射带动作用，要加强省域之间的交流，提高中国饲料粮产业的发展，保障饲料粮安全。

Abstract:

This study aims to analyze regional variations and influencing factors on the production layout of feed grains in China, so as to optimize the production layout of feed grains and promote the healthy development of the feed grain industry. Using data from 31 provinces （cities, autonomous regions excluding Hong Kong, Macao and Taiwan) from 2000 to 2021 in China, this study employed the sub-species input method and the gravity model to evaluate changes in feed grain layout and its gravity center, and used the spatial Durbin model to further analyze the influencing factors. The results were listed as follows. (1) The overall production of feed grains had been continuously increasing from 2000 to 2021, and the clustering characteristics had become increasingly evident, with notable growth in spatial aggregation shifting to northeast, north China, and southwest regions. The gravity center of feed grain production shifted from Henan province to Hebei province with a focus on the southwest and northeast, and a general shift towards the northeast. (2) There was a positive spatial autocorrelation in China's feed grain production, with a trend towards clustering at both high- and low-yielding regions. (3) Factors such as the proportion of agricultural output, effective irrigation area, fertilizer application, cultivated land area, and agricultural financial expenditure had a significant positive impact on feed grain production. Furthermore, the per capita disposable income of rural residents in neighboring areas, number of employees in the primary industry, transportation mileage, total power of agricultural machinery, effective irrigation area, and fertilizer application had an impact on feed grain production in the region, demonstrating spatial spillover effects. Base on the results, it proposes policy implications to improve the high-quality development of feed grain industry and guarantee feed grain security, for example, optimize the production layout of feed grain, improve the radiation driving capacity of provinces with high production capacity through spatial correlation, and strengthen regional cooperation.