经济学院知识库

县域作为经济发展的最基本单元和空间载体，在发展过程中不可避免地受到不同程度的外部冲击和内部扰动，对社会稳定、经济发展、人民生活造成严重威胁。甘肃省作为我国重要的生态、安全、能源屏障，同时作为我国新一轮西部大开发实现内循环带的重要区域，在经历了脱贫攻坚之后仍面临严峻的乡村振兴之路，发展以县域为载体的乡村振兴更能带动甘肃省经济的发展。本研究进行甘肃省县域经济韧性时空分异及影响因素研究对补齐县域发展短板，提升乡村振兴水平，推动县域高质量发展具有重要意义，也为相似区域提供政策参考。

本研究以2011-2020年甘肃省87个县为研究对象，从抵御风险能力、再组织能力和创新转型能力三个维度构建县域经济韧性评价指标体系，利用熵值法对县域经济韧性进行测度，在此基础上，使用空间统计分析方法对甘肃省县域经济韧性进行了分析，最后采用空间杜宾模型，对甘肃省县域经济韧性影响因素进行了分析。研究结果显示：

• 经济韧性测度结果。总体上来看，2011-2020年甘肃省县域经济韧性水平小幅上升，由2011年的0.345上升为2020年的0.363，涨幅为5.3%，但仍处于较低水平。各县域经济韧性水平差异较大，城关区和嘉峪关市的经济韧性水平基本稳居前五名，受政策等因素影响肃北县经济韧性水平波动较大但保持在前10名内，经济韧性水平居于后10名的县域多分布在陇南地区。分区域来看，各区域经济韧性水平均上升，经济韧性水平呈“河西地区>陇中地区>总体>陇东地区>甘南地区>陇南地区”的特征。各子系统经济韧性水平表现出明显的波动性和层次性，具有明显的非平衡性。研究期内甘肃省县域经济韧性具有集聚连片特点，并表现出明显的地带性差异，县域经济韧性总体差异呈缩小态势，区域内部差异是经济韧性差异的主要来源。
• 经济韧性空间格局及相关性分析结果。“高-高”集聚的县域多集中在河西地区，“低-低”集聚的县域多集中在陇东和甘南地区，且陇东地区“低-低”集聚趋势降低，甘南地区“低-低”集聚趋势增强。
• 经济韧性影响因素分析结果。从经济因素、金融因素、财政因素、市场因素、文化教育因素和自然因素六个维度进行经济韧性影响因素分析，最终选用时间固定效应的空间杜宾模型，并根据效应分解结果得出，经济因素、财政因素、市场因素的直接效应较强，金融因素和文化教育因素的效应不明显。综上提出针对性的政策建议，以期提升甘肃省县域经济韧性，为西部欠发达地区县域尺度的乡村振兴发展提供参考。

As the most basic unit and space carrier of economic development, county region is inevitably subjected to different degrees of external impact and internal disturbance in the process of development, which poses a serious threat to social stability, economic development and people's life. As an important ecological, security and energy barrier, Gansu Province is also an important region in the inner cycle belt of the new round of western development. After poverty alleviation, Gansu province is still faced with a severe road of rural revitalization. The development of rural revitalization with county as the carrier can better promote the economic development of Gansu Province. In this study, the spatio-temporal differentiation and influencing factors of county economic resilience in Gansu Province are of great significance to complement the development weaknesses of counties, improve the level of rural revitalization and promote high-quality development of counties, and also provide policy reference for similar regions.

This study takes 87 counties in Gansu Province from 2011 to 2020 as the research object, constructs an evaluation index system of county economic resilience from three dimensions of risk resistance ability, reorganization ability and innovation and transformation ability, and uses entropy method to measure county economic resilience. On this basis, spatial statistical analysis method is used to analyze the county economic resilience of Gansu Province. Finally, the spatial Dubin model is used to analyze the factors affecting the economic resilience of Gansu Province. Among the findings:

First, the results of measures of economic resilience. In general, the level of county economic resilience in Gansu Province increased slightly from 0.345 in 2011 to 0.363 in 2020, with an increase of 5.3%, but it is still at a low level. The economic resilience of Chengguan District and Jiayuguan City basically ranked the top five. Affected by policies and other factors, the economic resilience of Subei County fluctuated greatly but remained in the top 10. The bottom 10 counties were mostly distributed in Longnan region. From the perspective of different regions, the level of economic resilience of all regions increased, showing the characteristics of "Hexi region > Longzhong region > overall region > Longdong region > Gannan region > Longnan region". The level of economic resilience of each subsystem shows obvious volatility and hierarchy, and has obvious non-equilibrium. During the study period, the economic resilience of Gansu Province's counties is characterized by cluster contiguity, and shows obvious zonal differences.the overall differences of economic resilience in counties showed a decreasing trend, and intra-regional differences were the main sources of economic resilience differences.

Second, the spatial pattern and correlation analysis results of economic resilience. The counties with "high-high" agglomeration are mostly concentrated in Hexi, while those with "low-low" agglomeration are mostly concentrated in Longdong and Gannan. The "low-low" agglomeration trend decreases in Longdong, while the "low-low" agglomeration trend increases in Gannan.

Third, the analysis results of influencing factors of economic resilience. From six dimensions of economic factors, financial factors, fiscal factors, market factors, cultural and educational factors and natural factors, the influence factors of economic resilience are analyzed. Finally, the spatial Durbin model of time fixed effect is selected. According to the effect decomposition results, the direct effects of economic factors, fiscal factors and market factors are strong, while the effects of financial factors and cultural and educational factors are not obvious. In conclusion, targeted policy suggestions are put forward in order to improve the resilience of county economy in Gansu Province and provide reference for rural revitalization and development at county level in underdeveloped western areas.