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中国农机化学报

中国农机化学报 ›› 2024, Vol. 45 ›› Issue (11): 309-318.DOI: 10.13733/j.jcam.issn.2095‑5553.2024.11.047

• 农业机械化综合研究 • 上一篇    下一篇

广西农业经济增长的时空特征与影响因素研究——基于96个县域面板数据的空间计量分析

陆倩1,班锦才1,向云1,2   

  1. 1. 桂林电子科技大学商学院,广西桂林,541004; 2. 中山大学岭南学院,广州市,510275
  • 出版日期:2024-11-15 发布日期:2024-10-31
  • 基金资助:
    国家自然科学基金(71963007);广西哲学社会科学基金(20FMZ058)

Research on the spatio‑temporal characteristics and influencing factors of agricultural economic growth in Guangxi: A spatial econometric analysis based on panel data of 96 counties

Lu Qian1, Ban Jincai1, Xiang Yun1, 2   

  1. 1. Business School, Guilin University of Electronic Technology, Guilin, 541004, China; 
    2. Lingnan College, Sun Yat‑sen University, Guangzhou, 510275, China
  • Online:2024-11-15 Published:2024-10-31

摘要: 探究县域农业经济增长的空间特征及其影响因素,对促进广西县域经济协调发展意义重大。基于广西96个县域的面板数据,采用ESDA分析法分析广西农业经济增长的时空演变特征,构建空间杜宾模型深入剖析广西农业经济增长的影响因素及其空间效应,并分区域考察各影响因素对农业经济增长的贡献差异。结果表明:广西县域农业经济增长整体表现出较强的空间相关性,局部空间关联存在明显的“高—高”和“低—低”空间集聚特征;各投入要素对农业经济增长的影响存在较大差异,且空间效应以正向为主,土地、农业技术和政府资本等要素投入每增加1%,将分别带来农业经济增长水平提高0.706%、0.994%、0.108%;广西5大内部区域农业经济增长的主要影响因素及其影响程度存在明显差异,空间效应也存在明显的区域差异。基于研究结论得出政策启示:加强相邻县域之间农业发展的区域协同性,并努力缩减县域之间农业经济增长差距;各内部区域应有针对性地提升农业投入水平,遵循相对比较优势原则,通过增加农业要素投入促进农业经济增长。

关键词: 广西县域, 农业经济增长, 时空特征, 空间杜宾模型, 内部区域, ESDA分析法

Abstract: Exploring the spatial characteristics of county agricultural economic growth and its influencing factors is of great significance to promote the coordinated development of county economy in Guangxi. Based on the panel data of 96 counties in Guangxi, the spatial and temporal evolution characteristics of Guangxi's agricultural economic growth were analyzed by ESDA analysis method, and the influencing factors and spatial effects of Guangxi's agricultural economic growth were deeply analyzed by building a spatial Durbin model, and the difference of contributions of each influencing factor to agricultural economic growth was investigated by region. The results show that Guangxi county agricultural economic growth as a whole shows strong spatial correlation, and the local spatial correlation has obvious “high‑high” and “low‑low” spatial clustering characteristics. The influence of each input factor on agricultural economic growth has large differences, and the spatial effect is mainly positive, and every 1% increase in the inputs of factors such as land, agricultural technology and government capital will bring about an increase in the level of agricultural economic growth by 0.706%, 0.994%, and 0.108%, respectively; there are obvious differences in the main influencing factors of the growth of the agricultural economy in the five internal regions of Guangxi, as well as the degree of their influence, and the spatial effect also has obvious regional differences. The policy implications are drawn based on the findings of the study as follows: firstly, regional synergies in agricultural development between neighboring counties should be strengthened, and efforts should be made to narrow the gap in agricultural economic growth between counties. Secondly, each internal region should target the level of agricultural inputs, follow the principle of relative comparative advantage, and promote agricultural economic growth by increasing agricultural factor inputs.

Key words: Guangxi county, agricultural economic growth, spatio?temporal characteristics, spatial Durbin model, internal regions, ESDA analysis

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