Variable introduction and descriptive statistics.

Studying the spatial relationship and driving forces between grain production and economic development in China can assist in the coordinated development of economic growth and grain production in both China and other developing countries. Based on panel data from 2000 to 2019 covering 2018 county-level units in China, this study comprehensively investigated the spatial distribution, spatial differences, dynamic evolution of distribution, and driving factors of China’s county-level spatial deviation index of grain and economy (SDIGE) using methods such as the standard deviation ellipse method, the three-stage nested decomposition of Theil index, kernel density estimation, and geographically weighted regression (GWR) model. The results show that (1) from 2000 to 2019, China’s SDIGE showed a development trend of "up—down—up," and the highest SDIGE was in the northeast region, the lowest in the east region, and the spatial pattern of "high in the northeast—low in the east coast" was increasingly prominent. (2) In terms of spatial difference, the overall difference of SDIGE in China from 2000 to 2019 showed a rising trend of development; The average contribution rate of the regional difference to the overall difference was the lowest, maintained at about 17.82%; The average contribution rate of intra city and inter-county differences to the overall difference is the highest, which is about 34.20%. (3) In terms of the driving force, the level of economic development hurts SDIGE, while population density, industrial structure, fiscal decentralisation, and terrain fluctuation have a positive and negative impact on SDIGE. To alleviate the imbalance between China’s economic development and grain production, it is necessary to implement differentiated policy measures tailored to the specific characteristics of different regions to assist agricultural producers and enhance the stability of grain production.

探究中国粮食生产与经济发展的空间关系及其驱动因素，有助于推动中国及其他发展中国家实现经济增长与粮食生产的协调发展。本研究基于2000至2019年覆盖中国2018个县域单元的面板数据，采用标准差椭圆法、泰尔指数三阶嵌套分解法、核密度估计法以及地理加权回归（GWR）模型等方法，全面探究了中国县域粮食经济空间偏离度指数（SDIGE）的空间分布格局、空间差异、分布动态演化特征及其驱动因素。研究结果显示：（1）2000至2019年，中国县域粮食经济空间偏离度指数整体呈现“升—降—升”的演变趋势；该指数在东北地区处于最高水平，东部地区最低，“东北高、东部沿海低”的空间格局愈发显著。（2）在空间差异层面，2000至2019年中国县域粮食经济空间偏离度指数的总体差异呈上升态势；区域间差异对总体差异的平均贡献率最低，维持在17.82%左右；市域内部与县域间差异对总体差异的平均贡献率最高，约为34.20%。（3）在驱动机制层面，经济发展水平对县域粮食经济空间偏离度指数具有负向影响，而人口密度、产业结构、财政分权以及地形起伏度则对该指数兼具正向与负向作用。为缓解中国经济发展与粮食生产之间的失衡问题，需针对不同区域的具体特征制定差异化政策举措，以扶持粮食生产者、提升粮食生产稳定性。